DEFF Research Database (Denmark)
Smets, Barth F.; Lardon, Laurent
2009-01-01
of the outcomes to the various plasmid dynamic parameters. For our analysis, we developed a set of user-friendly MatLab® routines, which are deposited in the public domain. We hope that the availability of these routines will encourage the computationally untrained microbiologist to make use of these mathematical...... models. Finally, further permutations, as well as limitations of these mass action models in view of the structured complexity of most microbial systems are addressed....
Genetic parameters for various random regression models to describe the weight data of pigs
Huisman, A.E.; Veerkamp, R.F.; Arendonk, van J.A.M.
2002-01-01
Various random regression models have been advocated for the fitting of covariance structures. It was suggested that a spline model would fit better to weight data than a random regression model that utilizes orthogonal polynomials. The objective of this study was to investigate which kind of random
Genetic parameters for different random regression models to describe weight data of pigs
Huisman, A.E.; Veerkamp, R.F.; Arendonk, van J.A.M.
2001-01-01
Various random regression models have been advocated for the fitting of covariance structures. It was suggested that a spline model would fit better to weight data than a random regression model that utilizes orthogonal polynomials. The objective of this study was to investigate which kind of random
Energy Technology Data Exchange (ETDEWEB)
Champion, C. [Universite Paul Verlaine-Metz, Laboratoire de Physique Moleculaire et des Collisions, 1 Boulevard Arago, Technopole 2000, 57078 Metz (France)], E-mail: champion@univ-metz.fr; Incerti, S. [CNRS/IN2P3, Centre d' Etudes Nucleaires de Bordeaux-Gradignan, UMR 5797, Gradignan F-33175 (France); Universite de Bordeaux, Centre d' Etudes Nucleaires de Bordeaux-Gradignan, UMR 5797, Gradignan F-33175 (France); Aouchiche, H.; Oubaziz, D. [Universite M. Mammeri, Laboratoire de Mecanique, Structure et Energetique, BP 17, Tizi-Ouzou 15000 (Algeria)
2009-09-15
The present work provides an accurate description of the elastic scattering process for low-energy electrons (10 eV-10 keV) in liquid water by means of a free-parameter quantum-mechanical treatment. The calculations are performed in the partial-wave formalism by means of a total interaction potential taking into account a static contribution as well as fine effects like exchange and polarization contributions. The obtained results in terms of singly differential and total cross sections exhibit relatively good agreement with available experimental data (in gaseous water). They have been incorporated into the Geant4 toolkit, which has been recently extended with physics processes for microdosimetry applications in liquid water down to the electronvolt scale. They offer an improved alternative to the semi-empirical and to the screened Rutherford models already available in this very low-energy extension.
Owhondah, Raymond O; Walker, Mark; Ma, Lin; Nimmo, Bill; Ingham, Derek B; Poggio, Davide; Pourkashanian, Mohamed
2016-06-01
Biochemical reactions occurring during anaerobic digestion have been modelled using reaction kinetic equations such as first-order, Contois and Monod which are then combined to form mechanistic models. This work considers models which include between one and three biochemical reactions to investigate if the choice of the reaction rate equation, complexity of the model structure as well as the inclusion of inhibition plays a key role in the ability of the model to describe the methane production from the semi-continuous anaerobic digestion of green waste (GW) and food waste (FW). A parameter estimation method was used to investigate the most important phenomena influencing the biogas production process. Experimental data were used to numerically estimate the model parameters and the quality of fit was quantified. Results obtained reveal that the model structure (i.e. number of reactions, inhibition) has a much stronger influence on the quality of fit compared with the choice of kinetic rate equations. In the case of GW there was only a marginal improvement when moving from a one to two reaction model, and none with inclusion of inhibition or three reactions. However, the behaviour of FW digestion was more complex and required either a two or three reaction model with inhibition functions for both ammonia and volatile fatty acids. Parameter values for the best fitting models are given for use by other authors.
Energy Technology Data Exchange (ETDEWEB)
Hung, Nguyen Trong; Thuan, Le Ba [Institute for Technology of Radioactive and Rare Elements (ITRRE), 48 Lang Ha, Dong Da, Ha Noi (Viet Nam); Van Khoai, Do [Micro-Emission Ltd., 1-1 Asahidai, Nomi, Ishikawa, 923-1211 (Japan); Lee, Jin-Young, E-mail: jinlee@kigam.re.kr [Convergence Research Center for Development of Mineral Resources (DMR), Korea Institute of Geoscience and Mineral Resources (KIGAM), Daejeon, 305-350 (Korea, Republic of); Jyothi, Rajesh Kumar, E-mail: rkumarphd@kigam.re.kr [Convergence Research Center for Development of Mineral Resources (DMR), Korea Institute of Geoscience and Mineral Resources (KIGAM), Daejeon, 305-350 (Korea, Republic of)
2016-06-15
Uranium dioxide (UO{sub 2}) powder has been widely used to prepare fuel pellets for commercial light water nuclear reactors. Among typical characteristics of the powder, specific surface area (SSA) is one of the most important parameter that determines the sintering ability of UO{sub 2} powder. This paper built up a mathematical model describing the effect of the fabrication parameters on SSA of UO{sub 2} powders. To the best of our knowledge, the Brandon model is used for the first time to describe the relationship between the essential fabrication parameters [reduction temperature (T{sub R}), calcination temperature (T{sub C}), calcination time (t{sub C}) and reduction time (t{sub R})] and SSA of the obtained UO{sub 2} powder product. The proposed model was tested with Wilcoxon's rank sum test, showing a good agreement with the experimental parameters. The proposed model can be used to predict and control the SSA of UO{sub 2} powder.
van den Donker, M. N.; Hamers, E. A. G.; Kroesen, G. M. W.
2005-07-01
The transition pressure above which powder formation takes place was experimentally determined in a parallel plate RF silane-hydrogen plasma as a function of the process parameters—power, temperature, gas flow and hydrogen dilution—using the dc-bias voltage as powder formation indicator. The resulting empirical scaling law describes in what conditions powders are formed and in what conditions the plasma is powder-free. Second, a semi-empirical model was developed that treats the nano-particle density in the plasma. This model was applied to analytically describe the transition pressure above which nano-particle coagulation takes place as a function of process parameters. The resulting modelled scaling law shows good correspondence with the experimentally found scaling law. Finally, a series of amorphous silicon films was deposited. The reflection-transmission spectra of the films were measured and modelled through Tauc-Lorentz formalism. The optical analysis shows that at around the plasma transition pressure there occurs also a transition in the properties of the deposited material.
A six-parameter space to describe galaxy diversification
Fraix-Burnet, Didier; Chattopadhyay, Asis Kumar; Davoust, Emmanuel; Thuillard, Marc
2012-01-01
Galaxy diversification proceeds by transforming events like accretion, interaction or mergers. These explain the formation and evolution of galaxies that can now be described with many observables. Multivariate analyses are the obvious tools to tackle the datasets and understand the differences between different kinds of objects. However, depending on the method used, redundancies, incompatibilities or subjective choices of the parameters can void the usefulness of such analyses. The behaviour of the available parameters should be analysed before an objective reduction of dimensionality and subsequent clustering analyses can be undertaken, especially in an evolutionary context. We study a sample of 424 early-type galaxies described by 25 parameters, ten of which are Lick indices, to identify the most structuring parameters and determine an evolutionary classification of these objects. Four independent statistical methods are used to investigate the discriminant properties of the observables and the partitioni...
Describing Ecosystem Complexity through Integrated Catchment Modeling
Shope, C. L.; Tenhunen, J. D.; Peiffer, S.
2011-12-01
Land use and climate change have been implicated in reduced ecosystem services (ie: high quality water yield, biodiversity, and agricultural yield. The prediction of ecosystem services expected under future land use decisions and changing climate conditions has become increasingly important. Complex policy and management decisions require the integration of physical, economic, and social data over several scales to assess effects on water resources and ecology. Field-based meteorology, hydrology, soil physics, plant production, solute and sediment transport, economic, and social behavior data were measured in a South Korean catchment. A variety of models are being used to simulate plot and field scale experiments within the catchment. Results from each of the local-scale models provide identification of sensitive, local-scale parameters which are then used as inputs into a large-scale watershed model. We used the spatially distributed SWAT model to synthesize the experimental field data throughout the catchment. The approach of our study was that the range in local-scale model parameter results can be used to define the sensitivity and uncertainty in the large-scale watershed model. Further, this example shows how research can be structured for scientific results describing complex ecosystems and landscapes where cross-disciplinary linkages benefit the end result. The field-based and modeling framework described is being used to develop scenarios to examine spatial and temporal changes in land use practices and climatic effects on water quantity, water quality, and sediment transport. Development of accurate modeling scenarios requires understanding the social relationship between individual and policy driven land management practices and the value of sustainable resources to all shareholders.
Describing variations of the Fisher-matrix across parameter space
Schäfer, Björn Malte
2016-01-01
Forecasts in cosmology, both with Monte-Carlo Markov-chain methods and with the Fisher matrix formalism, depend on the choice of the fiducial model because both the signal strength of any observable as well as the model nonlinearities linking observables to cosmological parameters vary in the general case. In this paper we propose a method for extrapolating Fisher-forecasts across the space of cosmological parameters by constructing a suitable ba- sis. We demonstrate the validity of our method with constraints on a standard dark energy model extrapolated from a {\\Lambda}CDM-model, as can be expected from 2-bin weak lensing to- mography with a Euclid-like survey, in the parameter pairs $(\\Omega_\\text{m},\\sigma_8)$, $(\\Omega_\\text{m}, w_0)$ and $(w_0, w_\\text{a})$. Our numerical results include very accurate extrapolations across a wide range of cosmo- logical parameters in terms of shape, size and orientation of the parameter likelihood, and a decomposition of the change of the likelihood contours into modes, ...
Identification of parameters in amplitude equations describing coupled wakes
Fullana, J M; Zaleski, S; Le Gal, P; Fullana, Jose Maria; Rossi, Maurice; Zaleski, Stephane; Le Gal, Patrice
1996-01-01
We study the flow behind an array of equally spaced parallel cylinders. A system of Stuart-Landau equations with complex parameters is used to model the oscillating wakes. Our purpose is to identify the 6 scalar parameters which most accurately reproduce the experimental data of Chauve and Le Gal [{Physica D {\\bf 58}}, pp 407--413, (1992)]. To do so, we perform a computational search for the minimum of a distance \\calj. We define \\calj as the sum-square difference of the data and amplitudes reconstructed using coupled equations. The search algorithm is made more efficient through the use of a partially analytical expression for the gradient \
Frameworks for understanding and describing business models
DEFF Research Database (Denmark)
Nielsen, Christian; Roslender, Robin
2014-01-01
This chapter provides in a chronological fashion an introduction to six frameworks that one can apply to describing, understanding and also potentially innovating business models. These six frameworks have been chosen carefully as they represent six very different perspectives on business models ...... Maps (2001) • Intellectual Capital Statements (2003) • Chesbrough’s framework for Open Business Models (2006) • Business Model Canvas (2008)......This chapter provides in a chronological fashion an introduction to six frameworks that one can apply to describing, understanding and also potentially innovating business models. These six frameworks have been chosen carefully as they represent six very different perspectives on business models...... and in this manner “complement” each other. There are a multitude of varying frameworks that could be chosen from and we urge the reader to search and trial these for themselves. The six chosen models (year of release in parenthesis) are: • Service-Profit Chain (1994) • Strategic Systems Auditing (1997) • Strategy...
A Dualistic Model To Describe Computer Architectures
Nitezki, Peter; Engel, Michael
1985-07-01
The Dualistic Model for Computer Architecture Description uses a hierarchy of abstraction levels to describe a computer in arbitrary steps of refinement from the top of the user interface to the bottom of the gate level. In our Dualistic Model the description of an architecture may be divided into two major parts called "Concept" and "Realization". The Concept of an architecture on each level of the hierarchy is an Abstract Data Type that describes the functionality of the computer and an implementation of that data type relative to the data type of the next lower level of abstraction. The Realization on each level comprises a language describing the means of user interaction with the machine, and a processor interpreting this language in terms of the language of the lower level. The surface of each hierarchical level, the data type and the language express the behaviour of a ma-chine at this level, whereas the implementation and the processor describe the structure of the algorithms and the system. In this model the Principle of Operation maps the object and computational structure of the Concept onto the structures of the Realization. Describing a system in terms of the Dualistic Model is therefore a process of refinement starting at a mere description of behaviour and ending at a description of structure. This model has proven to be a very valuable tool in exploiting the parallelism in a problem and it is very transparent in discovering the points where par-allelism is lost in a special architecture. It has successfully been used in a project on a survey of Computer Architecture for Image Processing and Pattern Analysis in Germany.
Modeling Approaches for Describing Microbial Population Heterogeneity
DEFF Research Database (Denmark)
Lencastre Fernandes, Rita
, ethanol and biomass throughout the reactor. This work has proven that the integration of CFD and population balance models, for describing the growth of a microbial population in a spatially heterogeneous reactor, is feasible, and that valuable insight on the interplay between flow and the dynamics......Although microbial populations are typically described by averaged properties, individual cells present a certain degree of variability. Indeed, initially clonal microbial populations develop into heterogeneous populations, even when growing in a homogeneous environment. A heterogeneous microbial......) to predict distributions of certain population properties including particle size, mass or volume, and molecular weight. Similarly, PBM allow for a mathematical description of distributed cell properties within microbial populations. Cell total protein content distributions (a measure of cell mass) have been...
Thermodynanmic relations between selected parameters describing unsaturated flow
Energy Technology Data Exchange (ETDEWEB)
Case, C M
1980-05-01
The first law of thermodynamics is applied to unsaturated flow by replacing the usual PdV term (P is pressure and V is volume) for chemical system which appears there by psi d theta/sub s/ (phi is matric suction and theta/sub s/ is the degree of saturation). If the assumption is made that hysteretic behavior of the moisture characteristic can be ignored, all the usual thermodynamic relations can be derived in which P is replaced by phi and V is replaced by theta/sub s/ and the various thermodynamic potentials, internal energy, U, entropy S, and so on, are understood to be normalized to unit void volume of the soil being considered. This leads to a thermodynamically derived theoretical expression for the slope of the moisture characteristic in terms of theta/sub s/, temperature, T, and the thermal expansivity of water, ..beta../sub l/. When hysteresis is considered, it is shown that for certain types of laboratory experiments the area enclosed by the main branches of the hysteresis loop in the phi - theta/sub s/ plane, or by extension any closed loop traversed by the system in the phi - theta/sub s/ plane, represents, to the extent that the sample temperature is kept constant during the adsorption-desorption process, the void volume of the sample multiplied by the integral of the temperature and the differential of the entropy generated by carrying out the cyclic adsorption-desorption process. These results when combined with an explicit representation of phi interms of an integral over the poor radius distribution allow an explicit calculation of the entropy change in terms of physical parameters.
Stability margin of linear systems with parameters described by fuzzy numbers.
Husek, Petr
2011-10-01
This paper deals with the linear systems with uncertain parameters described by fuzzy numbers. The problem of determining the stability margin of those systems with linear affine dependence of the coefficients of a characteristic polynomial on system parameters is studied. Fuzzy numbers describing the system parameters are allowed to be characterized by arbitrary nonsymmetric membership functions. An elegant solution, graphical in nature, based on generalization of the Tsypkin-Polyak plot is presented. The advantage of the presented approach over the classical robust concept is demonstrated on a control of the Fiat Dedra engine model and a control of the quarter car suspension model.
Describing dengue epidemics: Insights from simple mechanistic models
Aguiar, Maíra; Stollenwerk, Nico; Kooi, Bob W.
2012-09-01
We present a set of nested models to be applied to dengue fever epidemiology. We perform a qualitative study in order to show how much complexity we really need to add into epidemiological models to be able to describe the fluctuations observed in empirical dengue hemorrhagic fever incidence data offering a promising perspective on inference of parameter values from dengue case notifications.
An autocatalytic kinetic model for describing microbial growth during fermentation.
Ibarz, Albert; Augusto, Pedro E D
2015-01-01
The mathematical modelling of the behaviour of microbial growth is widely desired in order to control, predict and design food and bioproduct processing, stability and safety. This work develops and proposes a new semi-empirical mathematical model, based on an autocatalytic kinetic, to describe the microbial growth through its biomass concentration. The proposed model was successfully validated using 15 microbial growth patterns, covering the three most important types of microorganisms in food and biotechnological processing (bacteria, yeasts and moulds). Its main advantages and limitations are discussed, as well as the interpretation of its parameters. It is shown that the new model can be used to describe the behaviour of microbial growth.
Using Metaphorical Models for Describing Glaciers
Felzmann, Dirk
2014-01-01
To date, there has only been little conceptual change research regarding conceptions about glaciers. This study used the theoretical background of embodied cognition to reconstruct different metaphorical concepts with respect to the structure of a glacier. Applying the Model of Educational Reconstruction, the conceptions of students and scientists…
Dispersive models describing mosquitoes’ population dynamics
Yamashita, W. M. S.; Takahashi, L. T.; Chapiro, G.
2016-08-01
The global incidences of dengue and, more recently, zica virus have increased the interest in studying and understanding the mosquito population dynamics. Understanding this dynamics is important for public health in countries where climatic and environmental conditions are favorable for the propagation of these diseases. This work is based on the study of nonlinear mathematical models dealing with the life cycle of the dengue mosquito using partial differential equations. We investigate the existence of traveling wave solutions using semi-analytical method combining dynamical systems techniques and numerical integration. Obtained solutions are validated through numerical simulations using finite difference schemes.
Using Metaphorical Models for Describing Glaciers
Felzmann, Dirk
2014-11-01
To date, there has only been little conceptual change research regarding conceptions about glaciers. This study used the theoretical background of embodied cognition to reconstruct different metaphorical concepts with respect to the structure of a glacier. Applying the Model of Educational Reconstruction, the conceptions of students and scientists regarding glaciers were analysed. Students' conceptions were the result of teaching experiments whereby students received instruction about glaciers and ice ages and were then interviewed about their understandings. Scientists' conceptions were based on analyses of textbooks. Accordingly, four conceptual metaphors regarding the concept of a glacier were reconstructed: a glacier is a body of ice; a glacier is a container; a glacier is a reflexive body and a glacier is a flow. Students and scientists differ with respect to in which context they apply each conceptual metaphor. It was observed, however, that students vacillate among the various conceptual metaphors as they solve tasks. While the subject context of the task activates a specific conceptual metaphor, within the discussion about the solution, the students were able to adapt their conception by changing the conceptual metaphor. Educational strategies for teaching students about glaciers require specific language to activate the appropriate conceptual metaphors and explicit reflection regarding the various conceptual metaphors.
Hageseth, Gaylord T.
1982-02-01
Students under the supervision of a faculty member can collect data and fit the data to the theoretical mathematical model that describes the rate of isothermal seed germination. The best-fit parameters are interpreted as an initial substrate concentration, product concentration, and the autocatalytic reaction rate. The thermodynamic model enables one to calculate the activation energy for the substrate and product, the activation energy for the autocatalytic reaction, and changes in enthalpy, entropy, and the Gibb's free energy. Turnip, lettuce, soybean, and radish seeds have been investigated. All data fit the proposed model.
Double sigmoidal models describing the growth of coffee berries
Directory of Open Access Journals (Sweden)
Tales Jesus Fernandes
Full Text Available ABSTRACT: This study aimed to verify if the growth pattern of coffee berries, considering fresh mass accumulation over time, is double sigmoid and to select the most suitable nonlinear model to describe such behavior. Data used consisted of fourteen longitudinal observations of average fresh mass of coffee berries obtained in an experiment with the cultivar Obatã IAC 1669-20. The fits provided by the Logistic and Gompertz models were compared in their single and double versions. Parameters were estimated using the least squares method using the Gauss-Newton algorithm implemented in the nls function of the R software. It can be concluded that the growth pattern of the coffee fruit, in fresh mass accumulation, is double sigmoid. The double Gompertz and double Logistic models were adequate to describe such a growth curve, with a superiority of the double Logistic model.
Energy Technology Data Exchange (ETDEWEB)
Ibsen, Lars Bo; Liingaard, M.
2006-12-15
A lumped-parameter model represents the frequency dependent soil-structure interaction of a massless foundation placed on or embedded into an unbounded soil domain. In this technical report the steps of establishing a lumped-parameter model are presented. Following sections are included in this report: Static and dynamic formulation, Simple lumped-parameter models and Advanced lumped-parameter models. (au)
A more robust Boolean model describing inhibitor binding
Institute of Scientific and Technical Information of China (English)
Zhaoqian Steven XIE; Chao TANG
2008-01-01
From the first application of the Boolean model to the cell cycle regulation network of budding yeast, new regulative pathways have been discovered, par-ticularly in the G1/S transition circuit. This discovery called for finer modeling to study the essential biology, and the resulting outcomes are first introduced in the ar-ticle. A traditional Boolean network model set up for the new G1/S transition circuit shows that it cannot correctly simulate real biology unless the model parameters are fine tuned. The deficiency is caused by an overly coarse-grained description of the inhibitor binding process, which shall be overcome by a two-vector model proposed whose robustness is surveyed using random perturba-tions. Simulations show that the proposed two-vector model is much more robust in describing inhibitor binding processes within the Boolean framework.
Extended nonlinear feedback model for describing episodes of high inflation
Szybisz, Martín A.; Szybisz, Leszek
2017-01-01
An extension of the nonlinear feedback (NLF) formalism to describe regimes of hyper- and high-inflation in economy is proposed in the present work. In the NLF model the consumer price index (CPI) exhibits a finite time singularity of the type 1 /(tc - t) (1 - β) / β, with β > 0, predicting a blow up of the economy at a critical time tc. However, this model fails in determining tc in the case of weak hyperinflation regimes like, e.g., that occurred in Israel. To overcome this trouble, the NLF model is extended by introducing a parameter γ, which multiplies all terms with past growth rate index (GRI). In this novel approach the solution for CPI is also analytic being proportional to the Gaussian hypergeometric function 2F1(1 / β , 1 / β , 1 + 1 / β ; z) , where z is a function of β, γ, and tc. For z → 1 this hypergeometric function diverges leading to a finite time singularity, from which a value of tc can be determined. This singularity is also present in GRI. It is shown that the interplay between parameters β and γ may produce phenomena of multiple equilibria. An analysis of the severe hyperinflation occurred in Hungary proves that the novel model is robust. When this model is used for examining data of Israel a reasonable tc is got. High-inflation regimes in Mexico and Iceland, which exhibit weaker inflations than that of Israel, are also successfully described.
Assessment of parameters describing representativeness of air quality in-situ measurement sites
Directory of Open Access Journals (Sweden)
S. Henne
2010-04-01
Full Text Available The atmospheric layer closest to the ground is strongly influenced by variable surface fluxes (emissions, surface deposition and can therefore be very heterogeneous. In order to perform air quality measurements that are representative of a larger domain or a certain degree of pollution, observatories are placed away from population centres or within areas of specific population density. Sites are often categorised based on subjective criteria that are not uniformly applied by the atmospheric community within different administrative domains yielding an inconsistent global air quality picture. A novel approach for the assessment of parameters reflecting site representativeness is presented here, taking emissions, deposition and transport towards 34 sites covering Western and Central Europe into account. These parameters are directly inter-comparable among the sites and can be used to select sites that are, on average, more or less suitable for data assimilation and comparison with satellite and model data. Advection towards these sites was simulated by backward Lagrangian Particle Dispersion Modelling (LPDM to determine the sites' average catchment areas for the year 2005 and advection times of 12, 24 and 48 h. Only variations caused by emissions and transport during these periods were considered assuming that these dominate the short-term variability of most but especially short lived trace gases. The derived parameters describing representativeness were compared between sites and a novel, uniform and observation-independent categorisation of the sites based on a clustering approach was established. Six groups of European background sites were identified ranging from generally remote to more polluted agglomeration sites. These six categories explained 50 to 80% of the inter-site variability of median mixing ratios and their standard deviation for NO_{2} and O_{3}, while differences between group means of the longer
DEFF Research Database (Denmark)
Ibsen, Lars Bo; Liingaard, Morten
A lumped-parameter model represents the frequency dependent soil-structure interaction of a massless foundation placed on or embedded into an unbounded soil domain. The lumped-parameter model development have been reported by (Wolf 1991b; Wolf 1991a; Wolf and Paronesso 1991; Wolf and Paronesso 19...
Introducing enzyme selectivity: a quantitative parameter to describe enzymatic protein hydrolysis
Butré, C.I.; Sforza, S.; Gruppen, H.; Wierenga, P.A.
2014-01-01
Enzyme selectivity is introduced as a quantitative parameter to describe the rate at which individual cleavage sites in a protein substrate are hydrolyzed relative to other cleavage sites. Whey protein isolate was hydrolyzed by Bacillus licheniformis protease, which is highly specific for Glu and
Earthquake model describes traffic jams caused by imperfect driving styles
Járai-Szabó, Ferenc; Néda, Zoltán
2012-11-01
The wide modeling potential of the classical spring-block type system is illustrated by an interdisciplinary application. A simple one-dimensional spring-block chain with asymmetric spring forces is used to model idealized single-lane highway traffic and the emergence of phantom traffic jams. Based on the stop-time statistics of one car in the row, a proper order parameter is defined. By extensive computer simulations the parameter space of the model is explored, analyzed and interpreted. Existence of free and congested flow phases is confirmed and the transition between them is analyzed.
New model describing the dynamical behaviour of penetration rates
Tashiro, Tohru; Minagawa, Hiroe; Chiba, Michiko
2013-02-01
We propose a hierarchical logistic equation as a model to describe the dynamical behaviour of a penetration rate of a prevalent stuff. In this model, a memory, how many people who already possess it a person who does not process it yet met, is considered, which does not exist in the logistic model. As an application, we apply this model to iPod sales data, and find that this model can approximate the data much better than the logistic equation.
Icosahedral symmetry described by an incommensurately modulated crystal structure model
DEFF Research Database (Denmark)
Wolny, Janusz; Lebech, Bente
1986-01-01
A crystal structure model of an incommensurately modulated structure is presented. Although six different reciprocal vectors are used to describe the model, all calculations are done in three dimensions making calculation of the real-space structure trivial. Using this model, it is shown that both...
Model checking biological systems described using ambient calculus
DEFF Research Database (Denmark)
Mardare, Radu Iulian; Priami, Corrado; Qualia, Paola;
2005-01-01
Model checking biological systems described using ambient calculus. In Proc. of the second International Workshop on Computational Methods in Systems Biology (CMSB04), Lecture Notes in Bioinformatics 3082:85-103, Springer, 2005.......Model checking biological systems described using ambient calculus. In Proc. of the second International Workshop on Computational Methods in Systems Biology (CMSB04), Lecture Notes in Bioinformatics 3082:85-103, Springer, 2005....
Dynamic modelling of pectin extraction describing yield and functional characteristics
DEFF Research Database (Denmark)
Andersen, Nina Marianne; Cognet, T.; Santacoloma, P. A.
2017-01-01
A dynamic model of pectin extraction is proposed that describes pectin yield, degree of esterification and intrinsic viscosity. The dynamic model is one dimensional in the peel geometry and includes mass transport of pectin by diffusion and reaction kinetics of hydrolysis, degradation and de-esterification....... The model takes into account the effects of the process conditions such as temperature and acid concentration on extraction kinetics. It is shown that the model describes pectin bulk solution concentration, degree of esterification and intrinsic viscosity in pilot scale extractions from lime peel...
Hageseth, Gaylord T.
1982-01-01
Describes a project for students to collect and fit data to a theoretical mathematical model that describes the rate of isothermal seed germination, including activation energy for substrate and produce and the autocatalytic reaction, and changes in enthalpy, entropy, and the Gibb's free energy. (Author/SK)
Response model parameter linking
Barrett, Michelle Derbenwick
2015-01-01
With a few exceptions, the problem of linking item response model parameters from different item calibrations has been conceptualized as an instance of the problem of equating observed scores on different test forms. This thesis argues, however, that the use of item response models does not require
Describing urban evolution with the fractal parameters based on area-perimeter allometry
Chen, Yanguang
2015-01-01
The area-perimeter allometric scaling is a basic and important approach for researching fractal cities and has been studied for a long time. However, the boundary dimension of a city is always numerically overestimated by the traditional formula. An adjusting formula has been derived to revise the overestimated boundary dimension and estimate the form dimension, but the association between the global and local fractal parameters is not clear. This paper is devoted to describing the urban evolution by using the improved fractal parameters based on the area-perimeter measure relation. A system of 68 cities and towns in Yangtze River Delta, China, is taken as an example to make a case study. A discovery is that the average values of the local fractal parameters are approximately equal to the corresponding global fractal parameters of cities. This suggests that the local parameters are the decomposition of the global parameters. The novelty of this empirical study is as follows: first, the form dimension and boun...
Bao, Xingxian; Cao, Aixia; Zhang, Jing
2016-07-01
Modal parameters estimation plays an important role for structural health monitoring. Accurately estimating the modal parameters of structures is more challenging as the measured vibration response signals are contaminated with noise. This study develops a mathematical algorithm of solving the partially described inverse singular value problem (PDISVP) combined with the complex exponential (CE) method to estimate the modal parameters. The PDISVP solving method is to reconstruct an L2-norm optimized (filtered) data matrix from the measured (noisy) data matrix, when the prescribed data constraints are one or several sets of singular triplets of the matrix. The measured data matrix is Hankel structured, which is constructed based on the measured impulse response function (IRF). The reconstructed matrix must maintain the Hankel structure, and be lowered in rank as well. Once the filtered IRF is obtained, the CE method can be applied to extract the modal parameters. Two physical experiments, including a steel cantilever beam with 10 accelerometers mounted, and a steel plate with 30 accelerometers mounted, excited by an impulsive load, respectively, are investigated to test the applicability of the proposed scheme. In addition, the consistency diagram is proposed to exam the agreement among the modal parameters estimated from those different accelerometers. Results indicate that the PDISVP-CE method can significantly remove noise from measured signals and accurately estimate the modal frequencies and damping ratios.
Assessing the state of substitution models describing noncoding RNA evolution.
Allen, James E; Whelan, Simon
2014-01-01
Phylogenetic inference is widely used to investigate the relationships between homologous sequences. RNA molecules have played a key role in these studies because they are present throughout life and tend to evolve slowly. Phylogenetic inference has been shown to be dependent on the substitution model used. A wide range of models have been developed to describe RNA evolution, either with 16 states describing all possible canonical base pairs or with 7 states where the 10 mismatched nucleotides are reduced to a single state. Formal model selection has become a standard practice for choosing an inferential model and works well for comparing models of a specific type, such as comparisons within nucleotide models or within amino acid models. Model selection cannot function across different sized state spaces because the likelihoods are conditioned on different data. Here, we introduce statistical state-space projection methods that allow the direct comparison of likelihoods between nucleotide models and 7-state and 16-state RNA models. To demonstrate the general applicability of our new methods, we extract 287 RNA families from genomic alignments and perform model selection. We find that in 281/287 families, RNA models are selected in preference to nucleotide models, with simple 7-state RNA models selected for more conserved families with shorter stems and more complex 16-state RNA models selected for more divergent families with longer stems. Other factors, such as the function of the RNA molecule or the GC-content, have limited impact on model selection. Our models and model selection methods are freely available in the open-source PHASE 3.0 software.
New models for describing outliers in meta-analysis.
Baker, Rose; Jackson, Dan
2016-09-01
An unobserved random effect is often used to describe the between-study variation that is apparent in meta-analysis datasets. A normally distributed random effect is conventionally used for this purpose. When outliers or other unusual estimates are included in the analysis, the use of alternative random effect distributions has previously been proposed. Instead of adopting the usual hierarchical approach to modelling between-study variation, and so directly modelling the study specific true underling effects, we propose two new marginal distributions for modelling heterogeneous datasets. These two distributions are suggested because numerical integration is not needed to evaluate the likelihood. This makes the computation required when fitting our models much more robust. The properties of the new distributions are described, and the methodology is exemplified by fitting models to four datasets. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.
A new settling velocity model to describe secondary sedimentation
DEFF Research Database (Denmark)
Ramin, Elham; Wágner, Dorottya Sarolta; Yde, Lars
2014-01-01
distribution in SSTs can be predicted using computational fluid dynamics (CFD) tools. Despite extensive studies on the compression settling behaviour of activated sludge and the development of advanced settling velocity models for use in SST simulations, these models are not often used, due to the challenges...... associated with their calibration. In this study, we developed a new settling velocity model, including hindered, transient and compression settling, and showed that it can be calibrated to data from a simple, novel settling column experimental set-up using the Bayesian optimization method DREAM......(ZS). In addition, correlations between the Herschel-Bulkley rheological model parameters and sludge concentration were identified with data from batch rheological experiments. A 2-D axisymmetric CFD model of a circular SST containing the new settling velocity and rheological model was validated with full...
Statistical models describing the energy signature of buildings
DEFF Research Database (Denmark)
Bacher, Peder; Madsen, Henrik; Thavlov, Anders
2010-01-01
Approximately one third of the primary energy production in Denmark is used for heating in buildings. Therefore efforts to accurately describe and improve energy performance of the building mass are very important. For this purpose statistical models describing the energy signature of a building, i.......e. the heat dynamics of the building, have been developed. The models can be used to obtain rather detailed knowledge of the energy performance of the building and to optimize the control of the energy consumption for heating, which will be vital in conditions with increasing fluctuation of the energy supply...... or varying energy prices. The paper will give an overview of statistical methods and applied models based on experiments carried out in FlexHouse, which is an experimental building in SYSLAB, Risø DTU. The models are of different complexity and can provide estimates of physical quantities such as UA...
Digital clocks: simple Boolean models can quantitatively describe circadian systems.
Akman, Ozgur E; Watterson, Steven; Parton, Andrew; Binns, Nigel; Millar, Andrew J; Ghazal, Peter
2012-09-07
The gene networks that comprise the circadian clock modulate biological function across a range of scales, from gene expression to performance and adaptive behaviour. The clock functions by generating endogenous rhythms that can be entrained to the external 24-h day-night cycle, enabling organisms to optimally time biochemical processes relative to dawn and dusk. In recent years, computational models based on differential equations have become useful tools for dissecting and quantifying the complex regulatory relationships underlying the clock's oscillatory dynamics. However, optimizing the large parameter sets characteristic of these models places intense demands on both computational and experimental resources, limiting the scope of in silico studies. Here, we develop an approach based on Boolean logic that dramatically reduces the parametrization, making the state and parameter spaces finite and tractable. We introduce efficient methods for fitting Boolean models to molecular data, successfully demonstrating their application to synthetic time courses generated by a number of established clock models, as well as experimental expression levels measured using luciferase imaging. Our results indicate that despite their relative simplicity, logic models can (i) simulate circadian oscillations with the correct, experimentally observed phase relationships among genes and (ii) flexibly entrain to light stimuli, reproducing the complex responses to variations in daylength generated by more detailed differential equation formulations. Our work also demonstrates that logic models have sufficient predictive power to identify optimal regulatory structures from experimental data. By presenting the first Boolean models of circadian circuits together with general techniques for their optimization, we hope to establish a new framework for the systematic modelling of more complex clocks, as well as other circuits with different qualitative dynamics. In particular, we anticipate
Distributed Parameter Modelling Applications
DEFF Research Database (Denmark)
2011-01-01
Here the issue of distributed parameter models is addressed. Spatial variations as well as time are considered important. Several applications for both steady state and dynamic applications are given. These relate to the processing of oil shale, the granulation of industrial fertilizers and the d......Here the issue of distributed parameter models is addressed. Spatial variations as well as time are considered important. Several applications for both steady state and dynamic applications are given. These relate to the processing of oil shale, the granulation of industrial fertilizers...... sands processing. The fertilizer granulation model considers the dynamics of MAP-DAP (mono and diammonium phosphates) production within an industrial granulator, that involves complex crystallisation, chemical reaction and particle growth, captured through population balances. A final example considers...
Galactic Rotation Described with Bulge+Disk Gravitational Models
Gallo, C F
2008-01-01
Observations reveal that mature spiral galaxies consist of stars, gases and plasma approximately distributed in a thin disk of circular shape, usually with a central bulge. The rotation velocities quickly increase from the galactic center and then achieve a constant velocity from the core to the periphery. The basic dynamic behavior of a mature spiral galaxy, such as the Milky Way, is well described by simple models balancing Newtonian gravitational forces against the centrifugal forces associated with a rotating thin axisymmetric disk. In this research, we investigate the effects of adding central bulges to thin disk gravitational models. Even with the addition of substantial central bulges, all the critical essential features of our thin disk gravitational models are preserved. (1) Balancing Newtonian gravitational and centrifugal forces at every point within the disk yields computed radial mass distributions that describe the measured rotation velocity profiles of mature spiral galaxies successfully. (2) T...
Madurga, Rodrigo; Plaza, Gustavo R.; Blackledge, Todd A.; Guinea, Gustavo. V.; Elices, Manuel; Pérez-Rigueiro, José
2016-01-01
Spider major ampullate gland silks (MAS) vary greatly in material properties among species but, this variation is shown here to be confined to evolutionary shifts along a single universal performance trajectory. This reveals an underlying design principle that is maintained across large changes in both spider ecology and silk chemistry. Persistence of this design principle becomes apparent after the material properties are defined relative to the true alignment parameter, which describes the orientation and stretching of the protein chains in the silk fiber. Our results show that the mechanical behavior of all Entelegynae major ampullate silk fibers, under any conditions, are described by this single parameter that connects the sequential action of three deformation micromechanisms during stretching: stressing of protein-protein hydrogen bonds, rotation of the β-nanocrystals and growth of the ordered fraction. Conservation of these traits for over 230 million years is an indication of the optimal design of the material and gives valuable clues for the production of biomimetic counterparts based on major ampullate spider silk.
HERMES: A Model to Describe Deformation, Burning, Explosion, and Detonation
Energy Technology Data Exchange (ETDEWEB)
Reaugh, J E
2011-11-22
HERMES (High Explosive Response to MEchanical Stimulus) was developed to fill the need for a model to describe an explosive response of the type described as BVR (Burn to Violent Response) or HEVR (High Explosive Violent Response). Characteristically this response leaves a substantial amount of explosive unconsumed, the time to reaction is long, and the peak pressure developed is low. In contrast, detonations characteristically consume all explosive present, the time to reaction is short, and peak pressures are high. However, most of the previous models to describe explosive response were models for detonation. The earliest models to describe the response of explosives to mechanical stimulus in computer simulations were applied to intentional detonation (performance) of nearly ideal explosives. In this case, an ideal explosive is one with a vanishingly small reaction zone. A detonation is supersonic with respect to the undetonated explosive (reactant). The reactant cannot respond to the pressure of the detonation before the detonation front arrives, so the precise compressibility of the reactant does not matter. Further, the mesh sizes that were practical for the computer resources then available were large with respect to the reaction zone. As a result, methods then used to model detonations, known as {beta}-burn or program burn, were not intended to resolve the structure of the reaction zone. Instead, these methods spread the detonation front over a few finite-difference zones, in the same spirit that artificial viscosity is used to spread the shock front in inert materials over a few finite-difference zones. These methods are still widely used when the structure of the reaction zone and the build-up to detonation are unimportant. Later detonation models resolved the reaction zone. These models were applied both to performance, particularly as it is affected by the size of the charge, and to situations in which the stimulus was less than that needed for reliable
HERMES: A Model to Describe Deformation, Burning, Explosion, and Detonation
Energy Technology Data Exchange (ETDEWEB)
Reaugh, J E
2011-11-22
HERMES (High Explosive Response to MEchanical Stimulus) was developed to fill the need for a model to describe an explosive response of the type described as BVR (Burn to Violent Response) or HEVR (High Explosive Violent Response). Characteristically this response leaves a substantial amount of explosive unconsumed, the time to reaction is long, and the peak pressure developed is low. In contrast, detonations characteristically consume all explosive present, the time to reaction is short, and peak pressures are high. However, most of the previous models to describe explosive response were models for detonation. The earliest models to describe the response of explosives to mechanical stimulus in computer simulations were applied to intentional detonation (performance) of nearly ideal explosives. In this case, an ideal explosive is one with a vanishingly small reaction zone. A detonation is supersonic with respect to the undetonated explosive (reactant). The reactant cannot respond to the pressure of the detonation before the detonation front arrives, so the precise compressibility of the reactant does not matter. Further, the mesh sizes that were practical for the computer resources then available were large with respect to the reaction zone. As a result, methods then used to model detonations, known as {beta}-burn or program burn, were not intended to resolve the structure of the reaction zone. Instead, these methods spread the detonation front over a few finite-difference zones, in the same spirit that artificial viscosity is used to spread the shock front in inert materials over a few finite-difference zones. These methods are still widely used when the structure of the reaction zone and the build-up to detonation are unimportant. Later detonation models resolved the reaction zone. These models were applied both to performance, particularly as it is affected by the size of the charge, and to situations in which the stimulus was less than that needed for reliable
Applicability of different hydraulic parameters to describe soil detachment in eroding rills.
Wirtz, Stefan; Seeger, Manuel; Zell, Andreas; Wagner, Christian; Wagner, Jean-Frank; Ries, Johannes B
2013-01-01
This study presents the comparison of experimental results with assumptions used in numerical models. The aim of the field experiments is to test the linear relationship between different hydraulic parameters and soil detachment. For example correlations between shear stress, unit length shear force, stream power, unit stream power and effective stream power and the detachment rate does not reveal a single parameter which consistently displays the best correlation. More importantly, the best fit does not only vary from one experiment to another, but even between distinct measurement points. Different processes in rill erosion are responsible for the changing correlations. However, not all these procedures are considered in soil erosion models. Hence, hydraulic parameters alone are not sufficient to predict detachment rates. They predict the fluvial incising in the rill's bottom, but the main sediment sources are not considered sufficiently in its equations. The results of this study show that there is still a lack of understanding of the physical processes underlying soil erosion. Exerted forces, soil stability and its expression, the abstraction of the detachment and transport processes in shallow flowing water remain still subject of unclear description and dependence.
A new settling velocity model to describe secondary sedimentation.
Ramin, Elham; Wágner, Dorottya S; Yde, Lars; Binning, Philip J; Rasmussen, Michael R; Mikkelsen, Peter Steen; Plósz, Benedek Gy
2014-12-01
Secondary settling tanks (SSTs) are the most hydraulically sensitive unit operations in biological wastewater treatment plants. The maximum permissible inflow to the plant depends on the efficiency of SSTs in separating and thickening the activated sludge. The flow conditions and solids distribution in SSTs can be predicted using computational fluid dynamics (CFD) tools. Despite extensive studies on the compression settling behaviour of activated sludge and the development of advanced settling velocity models for use in SST simulations, these models are not often used, due to the challenges associated with their calibration. In this study, we developed a new settling velocity model, including hindered, transient and compression settling, and showed that it can be calibrated to data from a simple, novel settling column experimental set-up using the Bayesian optimization method DREAM(ZS). In addition, correlations between the Herschel-Bulkley rheological model parameters and sludge concentration were identified with data from batch rheological experiments. A 2-D axisymmetric CFD model of a circular SST containing the new settling velocity and rheological model was validated with full-scale measurements. Finally, it was shown that the representation of compression settling in the CFD model can significantly influence the prediction of sludge distribution in the SSTs under dry- and wet-weather flow conditions.
Energy Technology Data Exchange (ETDEWEB)
Keller, U.; Mueller, E.; Grabenbauer, G.; Sauer, R.; Distel, L. [Div. of Radiobiology, Dept. of Radiotherapy, Erlangen (Germany); Kuechler, A. [Div. of Radiotherapy, Dept. of Radiology, Jena (Germany); Inst. for Human Genetics and Anthropology, Jena (Germany); Liehr, T. [Inst. for Human Genetics and Anthropology, Jena (Germany)
2004-05-01
Background and purpose: analysis of radiation-induced chromosomal aberrations is regarded as the ''gold standard'' for classifying individual radiosensitivity. A variety of different parameters can be used. The crucial question, however, is to explore which parameter is suited best to describe the differences between patients with increased radiosensitivity and healthy individuals. Patients and methods: in this study, five patients with severe radiation-induced late effects of at least grade 3, classified according to the Radiation Therapy Oncology Group (RTOG), and eleven healthy individuals were examined retrospectively. Peripheral blood lymphocytes were irradiated in vitro with 0.7 Gy and 2.0 Gy prior to cultivation and stained by means of three-color fluorescence in situ hybridization (FISH). The detailed analysis was focused on the number of breaks per metaphase, on breaks from complex chromosomal rearrangements per metaphase, as well as on the percentage of translocations, dicentric chromosomes, breaks, and excess acentric fragments - each in comparison with the total number of mitoses analyzed. Results: using the number of breaks from complex chromosomal rearrangements after 2.0 Gy, radiosensitive patients as endpoint were clearly to be distinguished (p = 0.001) from healthy individuals. Translocations (p = 0.001) as well as breaks per metaphase (p = 0.002) were also suitable indicators for detecting differences between patients and healthy individuals. The parameters ''percentage of dicentric chromosomes'', ''breaks'', and ''excess acentric fragments'' in comparison to the total number of mitoses analyzed could neither serve as meaningful nor as significant criteria, since they showed a strong interindividual variability. Conclusion: to detect a difference in chromosomal aberrations between healthy and radiosensitive individuals, the parameters ''frequency of breaks
Institute of Scientific and Technical Information of China (English)
YANGWen-Xing; LIJia-Hua; LIWei-Bin; LUOJin-Ming; XIEXiao-Tao; WEIHua
2004-01-01
We present an efficient approach to studying the spectra and eigenstates for the model describing interactions among five bosonic modes without using the assumption of the Bethe ansatz. The exact analytical results of all the eigenstates and eigenvalues are in terms of a parameter A for a class of models describing five-mode multiphoton process. The parameter is determined by the roots of a polynomial and is solvable analytically or numerically.
Knowledge epidemics and population dynamics models for describing idea diffusion
Vitanov, Nikolay K
2012-01-01
The diffusion of ideas is often closely connected to the creation and diffusion of knowledge and to the technological evolution of society. Because of this, knowledge creation, exchange and its subsequent transformation into innovations for improved welfare and economic growth is briefly described from a historical point of view. Next, three approaches are discussed for modeling the diffusion of ideas in the areas of science and technology, through (i) deterministic, (ii) stochastic, and (iii) statistical approaches. These are illustrated through their corresponding population dynamics and epidemic models relative to the spreading of ideas, knowledge and innovations. The deterministic dynamical models are considered to be appropriate for analyzing the evolution of large and small societal, scientific and technological systems when the influence of fluctuations is insignificant. Stochastic models are appropriate when the system of interest is small but when the fluctuations become significant for its evolution...
Extended nonlinear feedback model for describing episodes of high inflation
Szybisz, M A; Szybisz, L.
2016-01-01
An extension of the nonlinear feedback (NLF) formalism to describe regimes of hyper- and high-inflation in economy is proposed in the present work. In the NLF model the consumer price index (CPI) exhibits a finite time singularity of the type $1/(t_c -t)^{(1- \\beta)/\\beta}$, with $\\beta>0$, predicting a blow up of the economy at a critical time $t_c$. However, this model fails in determining $t_c$ in the case of weak hyperinflation regimes like, e.g., that occurred in Israel. To overcome this...
Advanced Mathematical Model to Describe the Production of Biodiesel Process
Directory of Open Access Journals (Sweden)
Hikmat S. Al-Salim
2009-12-01
Full Text Available Advanced mathematical model was used to capture the batch reactor characteristics of reacting compounds. The model was applied to batch reactor for the production of bio-diesel from palm and kapok oils. Results of the model were compared with experimental data in terms of conversion of transesterification reaction for the production of bio-diesel under unsteady state. A good agreement was obtained between our model predictions and the experimental data. Both experimental and modeling results showed that the conversion of triglycerides to methyl ester was affected by the process conditions. The transesterification process with temperature of about 70 oC, and methanol ratio to the triglyceride of about 5 times its stoichiometry, and the NAOH catalyst of wt 0.4%, appear to be acceptable process conditions for bio diesel process production from palm oil and kapok oil. The model can be applied for endothermic batch process. © 2009 BCREC UNDIP. All rights reserved[Received: 12 August 2009, Revised: 15 October 2009; Accepted: 18 October 2009][How to Cite: A.S. Ibrehem, H. S. Al-Salim. (2009. Advanced Mathematical Model to Describe the Production of Biodiesel Process. Bulletin of Chemical Reaction Engineering and Catalysis, 4(2: 37-42. doi:10.9767/bcrec.4.2.28.37-42][How to Link/DOI: http://dx.doi.org/10.9767/bcrec.4.2.28.37-42
Describing pulsar wind nebulae with a simple leptonic model
Energy Technology Data Exchange (ETDEWEB)
Hahn, Joachim; Hoppe, Stefan; Domainko, Wilfried; Hofmann, Werner [Max-Planck-Institut fuer Kernphysik, Heidelberg (Germany); Egberts, Kathrin [Institut fuer Astro- und Teilchenphysik, Leopold-Franzens-Universitaet Innsbruck (Austria)
2010-07-01
In recent years, Cherenkov telescopes like e.g. H.E.S.S. have identified a large number of very-high-energy (VHE) gamma-ray sources as Pulsar wind nebulae (PWNe). The VHE-gamma-ray emission shows a rich diversity of spectral and spatial morphologies. Theoretical models can help to understand and interprete the observed source properties. A simple semi-analytical leptonic model describing VHE gamma-ray emission from PWNe is presented. It assumes diffusion with radiative cooling as the transport mechanism for electrons and their interaction with radiative and interstellar magnetic fields as the origin of electromagnetic radiation. In the framework of this model, spectral and spatial properties of the expected VHE gamma-ray emission from single PWNe may be estimated.
Connecting point defect parameters with bulk properties to describe diffusion in solids
Chroneos, A.
2016-12-01
Diffusion is a fundamental process that can have an impact on numerous technological applications, such as nanoelectronics, nuclear materials, fuel cells, and batteries, whereas its understanding is important across scientific fields including materials science and geophysics. In numerous systems, it is difficult to experimentally determine the diffusion properties over a range of temperatures and pressures. This gap can be bridged by the use of thermodynamic models that link point defect parameters to bulk properties, which are more easily accessible. The present review offers a discussion on the applicability of the cBΩ model, which assumes that the defect Gibbs energy is proportional to the isothermal bulk modulus and the mean volume per atom. This thermodynamic model was first introduced 40 years ago; however, consequent advances in computational modelling and experimental techniques have regenerated the interest of the community in using it to calculate diffusion properties, particularly under extreme conditions. This work examines recent characteristic examples, in which the model has been employed in semiconductor and nuclear materials. Finally, there is a discussion on future directions and systems that will possibly be the focus of studies in the decades to come.
Probabilistic models to describe the dynamics of migrating microbial communities.
Directory of Open Access Journals (Sweden)
Joanna L Schroeder
Full Text Available In all but the most sterile environments bacteria will reside in fluid being transported through conduits and some of these will attach and grow as biofilms on the conduit walls. The concentration and diversity of bacteria in the fluid at the point of delivery will be a mix of those when it entered the conduit and those that have become entrained into the flow due to seeding from biofilms. Examples include fluids through conduits such as drinking water pipe networks, endotracheal tubes, catheters and ventilation systems. Here we present two probabilistic models to describe changes in the composition of bulk fluid microbial communities as they are transported through a conduit whilst exposed to biofilm communities. The first (discrete model simulates absolute numbers of individual cells, whereas the other (continuous model simulates the relative abundance of taxa in the bulk fluid. The discrete model is founded on a birth-death process whereby the community changes one individual at a time and the numbers of cells in the system can vary. The continuous model is a stochastic differential equation derived from the discrete model and can also accommodate changes in the carrying capacity of the bulk fluid. These models provide a novel Lagrangian framework to investigate and predict the dynamics of migrating microbial communities. In this paper we compare the two models, discuss their merits, possible applications and present simulation results in the context of drinking water distribution systems. Our results provide novel insight into the effects of stochastic dynamics on the composition of non-stationary microbial communities that are exposed to biofilms and provides a new avenue for modelling microbial dynamics in systems where fluids are being transported.
A new settling velocity model to describe secondary sedimentation
DEFF Research Database (Denmark)
Ramin, Elham; Wágner, Dorottya Sarolta; Yde, Lars
2014-01-01
Secondary settling tanks (SSTs) are the most hydraulically sensitive unit operations in biological wastewater treatment plants. The maximum permissible inflow to the plant depends on the efficiency of SSTs in separating and thickening the activated sludge. The flow conditions and solids distribut......Secondary settling tanks (SSTs) are the most hydraulically sensitive unit operations in biological wastewater treatment plants. The maximum permissible inflow to the plant depends on the efficiency of SSTs in separating and thickening the activated sludge. The flow conditions and solids...... associated with their calibration. In this study, we developed a new settling velocity model, including hindered, transient and compression settling, and showed that it can be calibrated to data from a simple, novel settling column experimental set-up using the Bayesian optimization method DREAM......(ZS). In addition, correlations between the Herschel-Bulkley rheological model parameters and sludge concentration were identified with data from batch rheological experiments. A 2-D axisymmetric CFD model of a circular SST containing the new settling velocity and rheological model was validated with full...
Kinetic modeling can describe in vivo glycolysis in Entamoeba histolytica.
Saavedra, Emma; Marín-Hernández, Alvaro; Encalada, Rusely; Olivos, Alfonso; Mendoza-Hernández, Guillermo; Moreno-Sánchez, Rafael
2007-09-01
Glycolysis in the human parasite Entamoeba histolytica is characterized by the absence of cooperative modulation and the prevalence of pyrophosphate-dependent (over ATP-dependent) enzymes. To determine the flux-control distribution of glycolysis and understand its underlying control mechanisms, a kinetic model of the pathway was constructed by using the software gepasi. The model was based on the kinetic parameters determined in the purified recombinant enzymes, and the enzyme activities, and steady-state fluxes and metabolite concentrations determined in amoebal trophozoites. The model predicted, with a high degree of accuracy, the flux and metabolite concentrations found in trophozoites, but only when the pyrophosphate concentration was held constant; at variable pyrophosphate, the model was not able to completely account for the ATP production/consumption balance, indicating the importance of the pyrophosphate homeostasis for amoebal glycolysis. Control analysis by the model revealed that hexokinase exerted the highest flux control (73%), as a result of its low cellular activity and strong AMP inhibition. 3-Phosphoglycerate mutase also exhibited significant flux control (65%) whereas the other pathway enzymes showed little or no control. The control of the ATP concentration was also mainly exerted by ATP consuming processes and 3-phosphoglycerate mutase and hexokinase (in the producing block). The model also indicated that, in order to diminish the amoebal glycolytic flux by 50%, it was required to decrease hexokinase or 3-phosphoglycerate mutase by 24% and 55%, respectively, or by 18% for both enzymes. By contrast, to attain the same reduction in flux by inhibiting the pyrophosphate-dependent enzymes pyrophosphate-phosphofructokinase and pyruvate phosphate dikinase, they should be decreased > 70%. On the basis of metabolic control analysis, steps whose inhibition would have stronger negative effects on the energy metabolism of this parasite were identified
Analysis of a mathematical model describing necrotic tumor growth
Escher, Joachim; Matioc, Bogdan-Vasile
2010-01-01
In this paper we study a model describing the growth of necrotic tumors in different regimes of vascularisation. The tumor consists of a necrotic core of death cells and a surrounding nonnecrotic shell. The corresponding mathematical formulation is a moving boundary problem where both boundaries delimiting the nonnecrotic shell are allowed to evolve in time.We determine all radially symmetric stationary solutions of the problem and reduce the moving boundary problem into a nonlinear evolution. Parabolic theory provides us the perfect context in order to show local well-posed of the problem for small initial data.
Conceptual hierarchical modeling to describe wetland plant community organization
Little, A.M.; Guntenspergen, G.R.; Allen, T.F.H.
2010-01-01
Using multivariate analysis, we created a hierarchical modeling process that describes how differently-scaled environmental factors interact to affect wetland-scale plant community organization in a system of small, isolated wetlands on Mount Desert Island, Maine. We followed the procedure: 1) delineate wetland groups using cluster analysis, 2) identify differently scaled environmental gradients using non-metric multidimensional scaling, 3) order gradient hierarchical levels according to spatiotem-poral scale of fluctuation, and 4) assemble hierarchical model using group relationships with ordination axes and post-hoc tests of environmental differences. Using this process, we determined 1) large wetland size and poor surface water chemistry led to the development of shrub fen wetland vegetation, 2) Sphagnum and water chemistry differences affected fen vs. marsh / sedge meadows status within small wetlands, and 3) small-scale hydrologic differences explained transitions between forested vs. non-forested and marsh vs. sedge meadow vegetation. This hierarchical modeling process can help explain how upper level contextual processes constrain biotic community response to lower-level environmental changes. It creates models with more nuanced spatiotemporal complexity than classification and regression tree procedures. Using this process, wetland scientists will be able to generate more generalizable theories of plant community organization, and useful management models. ?? Society of Wetland Scientists 2009.
Advanced Mathematical Model to Describe the Production of Biodiesel Process
Directory of Open Access Journals (Sweden)
Ahmmed S. Ibrehem
2009-12-01
Full Text Available Advanced mathematical model was used to capture the batch reactor characteristics of reacting compounds. The model was applied to batch reactor for the production of bio-diesel from palm and kapok oils. Results of the model were compared with experimental data in terms of conversion of transesterification reaction for the production of bio-diesel under unsteady state. A good agreement was obtained between our model predictions and the experimental data. Both experimental and modeling results showed that the conversion of triglycerides to methyl ester was affected by the process conditions. The transesterification process with temperature of about 70 oC, and methanol ratio to the triglyceride of about 5 times its stoichiometry, and the NAOH catalyst of wt 0.4%, appear to be acceptable process conditions for bio diesel process production from palm oil and kapok oil. The model can be applied for endothermic batch process. © 2009 BCREC UNDIP. All rights reserved[Received: 12 August 2009, Revised: 15 October 2009; Accepted: 18 October 2009][How to Cite: A.S. Ibrehem, H. S. Al-Salim. (2009. Advanced Mathematical Model to Describe the Production of Biodiesel Process. Bulletin of Chemical Reaction Engineering and Catalysis, 4(2: 37-42. doi:10.9767/bcrec.4.2.7109.37-42][How to Link/DOI: http://dx.doi.org/10.9767/bcrec.4.2.7109.37-42 || or local: http://ejournal.undip.ac.id/index.php/bcrec/article/view/7109 ]
Directory of Open Access Journals (Sweden)
Szulc Andrzej
2007-12-01
Full Text Available Abstract Background The shape of the torso in patients with idiopathic scoliosis is considered to reflect the shape of the vertebral column, however the direct correlation between parameters describing clinical deformity and those characterizing radiological curvature was reported to be weak. It is not clear if the management proposed for scoliosis (physiotherapy, brace, surgery affects equally the shape of the axial skeleton and the surface of the body. The aim of the study was to compare clinical deformity of (1 idiopathic scoliosis girls being under brace treatment for radiological curves of 25 to 40 degrees and (2 non treated scoliotic girls matched for age and Cobb angle. Methods Cross-sectional study of 24 girls wearing the brace versus 26 girls without brace treatment, matched for age and Cobb angle. Hypothesis: Patients wearing the brace for more than 6 months, when comparing to patients without brace, may present different external morphology of the trunk, in spite of having similar Cobb angle. Material. Inclusion criteria: girls, idiopathic scoliosis, growing age (10–16 years, Cobb angle minimum 25°, maximum 40°. The braced group consisted of girls wearing a TLSO brace (Cheneau for more than 6 months with minimum of 16 hours per day. The non-braced group consisted of girls first seen for their spinal deformity, previously not treated. The groups presented similar curve pattern. Methods. Scoliometer exam: angle of trunk rotation at three levels of the spine: upper thoracic, main thoracic, lumbar or thoracolumbar. The maximal angle was noted at each level and the sum of three levels was calculated. Posterior trunk symmetry index (POTSI and Hump Sum were measured using surface topography. Results Cobb angle was 34.9° ± 4.8° in braced and 32.7° ± 4.9° in un-braced patients (difference not significant. The age was 14.1 ± 1.6 years in braced patients and 13.1 ± 1.9 years in un-braced group (p = 0.046. The value of angle of trunk
Models for describing the thermal characteristics of building components
DEFF Research Database (Denmark)
Jimenez, M.J.; Madsen, Henrik
2008-01-01
on the purpose of the modelling, existence of prior physical knowledge, the data and the available statistical tools. In this paper, a variety of models are outlined and compared, and a strong relationship among a large number of widely used linear and stationary stochastic models is mathematically demonstrated...
Can sigma models describe finite temperature chiral transitions?
Kocic, Aleksandar; Aleksandar KOCIC; John KOGUT
1995-01-01
Large-N expansions and computer simulations indicate that the universality class of the finite temperature chiral symmetry restoration transition in the 3D Gross-Neveu model is mean field theory. This is a counterexample to the standard 'sigma model' scenario which predicts the 2D Ising model universality class. We trace the breakdown of the standard scenario (dimensional reduction and universality) to the absence of canonical scalar fields in the model. We point out that our results could be generic for theories with dynamical symmetry breaking, such as Quantum Chromodynamics.
New model describes toppling of salt marsh banks
Wendel, JoAnna
2014-05-01
Salt marshes are coastal habitats that store important nutrients and serve as shelter for many estuarial species. These habitats are threatened by rising seas and human expansion, so it has become increasingly important to improve models of how these habitats degrade.
Simple Model for Describing and Estimating Wind Turbine Dynamic Inflow
DEFF Research Database (Denmark)
Knudsen, Torben; Bak, Thomas
2013-01-01
Wind turbines operate with sudden change in pitch angle, rotor or wind speed. In such cases the wake behind the turbine, achieve steady state conditions only after a certain delay. This phenomenon is commonly called dynamic inflow. There are many models for dynamic inflow. The most accurate use a...
Parameter counting in models with global symmetries
Energy Technology Data Exchange (ETDEWEB)
Berger, Joshua [Institute for High Energy Phenomenology, Newman Laboratory of Elementary Particle Physics, Cornell University, Ithaca, NY 14853 (United States)], E-mail: jb454@cornell.edu; Grossman, Yuval [Institute for High Energy Phenomenology, Newman Laboratory of Elementary Particle Physics, Cornell University, Ithaca, NY 14853 (United States)], E-mail: yuvalg@lepp.cornell.edu
2009-05-18
We present rules for determining the number of physical parameters in models with exact flavor symmetries. In such models the total number of parameters (physical and unphysical) needed to described a matrix is less than in a model without the symmetries. Several toy examples are studied in order to demonstrate the rules. The use of global symmetries in studying the minimally supersymmetric standard model (MSSM) is examined.
Collective Philanthropy: Describing and Modeling the Ecology of Giving
Gottesman, William L; Dodds, Peter Sheridan
2013-01-01
Reflective of income and wealth distributions, philanthropic gifting appears to follow an approximate power-law size distribution as measured by the size of gifts received by individual institutions. We explore the ecology of gifting by analysing data sets of individual gifts for a diverse group of institutions dedicated to education, medicine, art, public support, and religion. We find that the detailed forms of gift-size distributions differ across but are relatively constant within charity categories. We construct a model for how a donor's income affects their giving preferences in different charity categories, offering a mechanistic explanation for variations in institutional gift-size distributions. We discuss how knowledge of gift-sized distributions may be used to assess an institution's gift-giving profile, to help set fundraising goals, and to design an institution-specific giving pyramid.
Realistic f(T) model describing the de Sitter epoch of the dark energy dominated universe
Nassur, S B; Rodrigues, M E; Houndjo, M J S; Tossa, J
2015-01-01
We consider an exponential model within the so-called f(T) theory of gravity, where $T$ denotes the torsion scalar. We focus our work on a cosmological feature of such a model, checking whether it may describe the de Sitter stage of the current universe through the analysis of the redshift z. Our results shows that the model reproduces the de Sitter stage only for low-redshifts, where the perturbation function goes toward zero as the low values of the redshift are reached, whereas the effective parameter of equation of state goes to -1, which is the expected behavior for any model able to reproduce de Sitter stage.
Setting Parameters for Biological Models With ANIMO
Schivo, Stefano; Scholma, Jetse; Karperien, Hermanus Bernardus Johannes; Post, Janine Nicole; van de Pol, Jan Cornelis; Langerak, Romanus; André, Étienne; Frehse, Goran
2014-01-01
ANIMO (Analysis of Networks with Interactive MOdeling) is a software for modeling biological networks, such as e.g. signaling, metabolic or gene networks. An ANIMO model is essentially the sum of a network topology and a number of interaction parameters. The topology describes the interactions
A model to describe potential effects of chemotherapy on critical radiobiological treatments
Rodríguez-Pérez, D.; Desco, M. M.; Antoranz, J. C.
2016-08-01
Although chemo- and radiotherapy can annihilate tumors on their own. they are also used in coadjuvancy: improving local effects of radiotherapy using chemotherapy as a radiosensit.izer. The effects of radiotherapy are well described by current radiobiological models. The goal of this work is to describe a discrete radiotherapy model, that has been previously used describe high radiation dose response as well as unusual radio-responses of some types of tumors (e.g. prostate cancer), to obtain a model of chemo+radiotherapy that can describe how the outcome of their combination is a more efficient removal of the tumor. Our hypothesis is that, although both treatments haven different mechanisms, both affect similar key points of cell metabolism and regulation, that lead to cellular death. Hence, we will consider a discrete model where chemotherapy may affect a fraction of the same targets destroyed by radiotherapy. Although radiotherapy reaches all cells equally, chemotherapy diffuses through a tumor attaining lower concentration in its center and higher in its surface. With our simulations we study the enhanced effect of combined therapy treatment and how it depends on the tissue critical parameters (the parameters of the lion-extensive radiobiological model), the number of “targets” aimed at by chemotherapy, and the concentration and diffusion rate of the drug inside the tumor. The results show that an equivalent, cliemo-radio-dose can be computed that allows the prediction of the lower radiation dose that causes the same effect than a radio-only treatment.
Sensitivity analysis of a biofilm model describing mixed growth of nitrite oxidisers in a CSTR.
Kornaros, M; Dokianakis, S N; Lyberatos, G
2006-01-01
A simple kinetic model has been developed for describing nitrite oxidation by autotrophic aerobic nitrifiers in a CSTR reactor, in which mixed (suspended and attached) growth conditions are prevailing. In this work, a critical dimensionless parameter is identified containing both biofilm characteristics and microbial kinetic parameters, as well as the specific (per volume) surface of the reactor configuration used. Evaluation of this dimensionless parameter can easily provide information on whether or not wall attachment is critical, and should be taken into account either in kinetic studies or in reactor design, when specific pollutants are to be removed from the waste influent stream. The effect of bulk dissolved oxygen (DO) concentration on the validity of this model is addressed and minimum non-limiting DO concentrations are proposed depending on the reactor configuration.
Photovoltaic module parameters acquisition model
Cibira, Gabriel; Koščová, Marcela
2014-09-01
This paper presents basic procedures for photovoltaic (PV) module parameters acquisition using MATLAB and Simulink modelling. In first step, MATLAB and Simulink theoretical model are set to calculate I-V and P-V characteristics for PV module based on equivalent electrical circuit. Then, limited I-V data string is obtained from examined PV module using standard measurement equipment at standard irradiation and temperature conditions and stated into MATLAB data matrix as a reference model. Next, the theoretical model is optimized to keep-up with the reference model and to learn its basic parameters relations, over sparse data matrix. Finally, PV module parameters are deliverable for acquisition at different realistic irradiation, temperature conditions as well as series resistance. Besides of output power characteristics and efficiency calculation for PV module or system, proposed model validates computing statistical deviation compared to reference model.
Mode choice model parameters estimation
Strnad, Irena
2010-01-01
The present work focuses on parameter estimation of two mode choice models: multinomial logit and EVA 2 model, where four different modes and five different trip purposes are taken into account. Mode choice model discusses the behavioral aspect of mode choice making and enables its application to a traffic model. Mode choice model includes mode choice affecting trip factors by using each mode and their relative importance to choice made. When trip factor values are known, it...
Filippov, A T
2016-01-01
The dynamics of any spherical cosmology with a scalar field (`scalaron') coupling to gravity is described by the nonlinear second-order differential equations for two metric functions and the scalaron depending on the `time' parameter. The equations depend on the scalaron potential and on arbitrary gauge function that describes time parameterizations. This dynamical system can be integrated for flat, isotropic models with very special potentials. But, somewhat unexpectedly, replacing the independent variable $t$ by one of the metric functions allows us to completely integrate the general spherical theory in any gauge and with arbitrary potentials. In this approach, inflationary solutions can be easily identified, explicitly derived, and compared to the standard approximate expressions. This approach is also applicable to intrinsically anisotropic models with a massive vector field (`vecton') as well as to some non-inflationary models.
Core - Corona Model describes the Centrality Dependence of v_2/epsilon
Aichelin, J
2010-01-01
Event by event EPOS calculations in which the expansion of the system is described by {\\it ideal} hydrodynamics reproduce well the measured centrality dependence of $v_2/\\epsilon_{part}$, although it has been claimed that only viscous hydrodynamics can reproduce these data. This is due to the core - corona effect which manifests itself in the initial condition of the hydrodynamical expansion. The centrality dependence of $v_2/\\epsilon_{part}$ can be understood in the recently advanced core-corona model, a simple parameter free EPOS inspired model to describe the centrality dependence of different observables from SPS to RHIC energies. This model has already been successfully applied to understand the centrality dependence of multiplicities and of the average transverse momentum of identified particles.
Evaluation of mathematical models to describe growth of grazing young bulls
Directory of Open Access Journals (Sweden)
Henrique Jorge Fernandes
2012-02-01
Full Text Available The objective of this study was to evaluate the use of different mathematical models to describe growth of grazing beef cattle. Data of 20 Nellore bulls with initial weight of 129±28.1 kg and final weight of 405±62.0 kg were used. The animals were randomly divided into four plots and placed on B. decumbens Stapf pastures. Three plots received concentrate supplement with different protein profiles and the fourth plot received only mineral supplement. Animals were weighed every 28 days to design growth curve of full body weight. Five mathematical models were evaluated to describe animal growth: Multiphase, Linear, Logarithmic, Gompertz and Logistic models. Assessment of adequacy of the models was performed by using coefficient of determination, simultaneous F-test for identity of parameters, concordance correlation coefficient, root of the mean square error of prediction and partition of the mean square error of prediction. The analysis of the pairwise mean square error of prediction and the delta Akaike's information criterion were used to compare the models for accuracy and precision. Evaluation of all the tested models showed that all of them were able to predict variability among animals. However, Gompertz, Logarithmic and Logistic models created individual predictions that were not satisfactory. Models differed from each other concerning accuracy and precision; the best were in the following order: Multiphase, Linear, Gompertz, Logarithmic and Logistic. The Multiphase model was more efficient than the others for description of grazing beef cattle growth.
Berlijn, S.; Kvarngren, M.; Garnacho, F.; Simon, P; Gockenbach, E.; P. Werle; Hackemack, K.; Wong, K.C.P.; Watts, M.
1999-01-01
In this paper the present problems with the evaluation methods for lightning impulse parameters, as defined in IEC 60060-1, are described. Also the current practice of evaluation in many laboratories world-wide, that is obtained by a questionnaire, is presented. Some of the work performed up the present time and the initial conclusions are reported, then some recommendations are made for future work.
Describing Growth Pattern of Bali Cows Using Non-linear Regression Models
Directory of Open Access Journals (Sweden)
Mohd. Hafiz A.W
2016-12-01
Full Text Available The objective of this study was to evaluate the best fit non-linear regression model to describe the growth pattern of Bali cows. Estimates of asymptotic mature weight, rate of maturing and constant of integration were derived from Brody, von Bertalanffy, Gompertz and Logistic models which were fitted to cross-sectional data of body weight taken from 74 Bali cows raised in MARDI Research Station Muadzam Shah Pahang. Coefficient of determination (R2 and residual mean squares (MSE were used to determine the best fit model in describing the growth pattern of Bali cows. Von Bertalanffy model was the best model among the four growth functions evaluated to determine the mature weight of Bali cattle as shown by the highest R2 and lowest MSE values (0.973 and 601.9, respectively, followed by Gompertz (0.972 and 621.2, respectively, Logistic (0.971 and 648.4, respectively and Brody (0.932 and 660.5, respectively models. The correlation between rate of maturing and mature weight was found to be negative in the range of -0.170 to -0.929 for all models, indicating that animals of heavier mature weight had lower rate of maturing. The use of non-linear model could summarize the weight-age relationship into several biologically interpreted parameters compared to the entire lifespan weight-age data points that are difficult and time consuming to interpret.
Delineating Parameter Unidentifiabilities in Complex Models
Raman, Dhruva V; Papachristodoulou, Antonis
2016-01-01
Scientists use mathematical modelling to understand and predict the properties of complex physical systems. In highly parameterised models there often exist relationships between parameters over which model predictions are identical, or nearly so. These are known as structural or practical unidentifiabilities, respectively. They are hard to diagnose and make reliable parameter estimation from data impossible. They furthermore imply the existence of an underlying model simplification. We describe a scalable method for detecting unidentifiabilities, and the functional relations defining them, for generic models. This allows for model simplification, and appreciation of which parameters (or functions thereof) cannot be estimated from data. Our algorithm can identify features such as redundant mechanisms and fast timescale subsystems, as well as the regimes in which such approximations are valid. We base our algorithm on a novel quantification of regional parametric sensitivity: multiscale sloppiness. Traditional...
Directory of Open Access Journals (Sweden)
Lee Robert C
2005-11-01
Full Text Available Abstract Background Most epidemiological studies of major depression report period prevalence estimates. These are of limited utility in characterizing the longitudinal epidemiology of this condition. Markov models provide a methodological framework for increasing the utility of epidemiological data. Markov models relating incidence and recovery to major depression prevalence have been described in a series of prior papers. In this paper, the models are extended to describe the longitudinal course of the disorder. Methods Data from three national surveys conducted by the Canadian national statistical agency (Statistics Canada were used in this analysis. These data were integrated using a Markov model. Incidence, recurrence and recovery were represented as weekly transition probabilities. Model parameters were calibrated to the survey estimates. Results The population was divided into three categories: low, moderate and high recurrence groups. The size of each category was approximated using lifetime data from a study using the WHO Mental Health Composite International Diagnostic Interview (WMH-CIDI. Consistent with previous work, transition probabilities reflecting recovery were high in the initial weeks of the episodes, and declined by a fixed proportion with each passing week. Conclusion Markov models provide a framework for integrating psychiatric epidemiological data. Previous studies have illustrated the utility of Markov models for decomposing prevalence into its various determinants: incidence, recovery and mortality. This study extends the Markov approach by distinguishing several recurrence categories.
Fuzzy logic model to describe anesthetic effect and muscular influence on EEG Cerebral State Index.
Brás, S; Gouveia, S; Ribeiro, L; Ferreira, D A; Antunes, L; Nunes, C S
2013-06-01
The well-known Cerebral State Index (CSI) quantifies depth of anesthesia and is traditionally modeled with Hill equation and propofol effect-site concentration (Ce). This work brings out two novelties: introduction of electromyogram (EMG) and use of fuzzy logic models with ANFIS optimized parameters. The data were collected from dogs (n=27) during routine surgery considering two propofol administration protocols: constant infusion (G1, n=14) and bolus (G2, n=13). The median modeling error of the fuzzy logic model with Ce and EMG was lower or similar than that of the Hill with Ce (p=0.012-G1, p=0.522-G2). Furthermore, there was no significant performance impact due to model structure alteration (p=0.288-G1, p=0.330-G2) and EMG introduction increased or maintained the performance (p=0.036-G1, p=0.798-G2). Therefore, the new model can achieve higher performance than Hill model, mostly due to EMG information and not due to changes in the model structure. In conclusion, the fuzzy models adequately describe CSI data with advantages over traditional Hill models.
A flowing plasma model to describe drift waves in a cylindrical helicon discharge
Chang, L; Cormac, C S
2011-01-01
A two-fluid model developed originally to describe wave oscillations in the vacuum arc centrifuge, a cylindrical, rapidly rotating, low temperature and confined plasma column, is applied to interpret plasma oscillations in a RF generated linear magnetised plasma (WOMBAT), with similar density and field strength. Compared to typical centrifuge plasmas, WOMBAT plasmas have slower normalised rotation frequency, lower temperature and lower axial velocity. Despite these differences, the two-fluid model provides a consistent description of the WOMBAT plasma configuration and yields qualitative agreement between measured and predicted wave oscillation frequencies with axial field strength. In addition, the radial profile of the density perturbation predicted by this model is consistent with the data. Parameter scans show that the dispersion curve is sensitive to the axial field strength and the electron temperature, and the dependence of oscillation frequency with electron temperature matches the experiment. These r...
A Polydisperse Sphere Model Describing the Propagation of Light in Biological Tissue
Institute of Scientific and Technical Information of China (English)
WANG Qing-Hua; LI Zhen-Hua; LAI Jian-Cheng; HE An-Zhi
2007-01-01
A polydisperse sphere model with the complex refractive index is employed to describe the propagation of light in biological tissue.The scattering coefficient,absorption coefficient and scattering phase function are calculated.At the same time,the inverse problem on retrieving the particles size distribution,imaginary part of the refractive index and number density of scatterers is investigated.The result shows that the retrieval scheme together with the Chahine algorithm is effective in dealing with such an inverse problem.IT is also clarified that a group of parameters including the scattering coefficient,absorption coefficient and phase function are associated with another group including the refractive index,particle size distribution and number density of scatterers,which is a problem described in two different ways and the anisotropy factor is not an independent variable,but is determined by the phase function.
Improving uncertainty estimation in urban hydrological modeling by statistically describing bias
Directory of Open Access Journals (Sweden)
D. Del Giudice
2013-10-01
Full Text Available Hydrodynamic models are useful tools for urban water management. Unfortunately, it is still challenging to obtain accurate results and plausible uncertainty estimates when using these models. In particular, with the currently applied statistical techniques, flow predictions are usually overconfident and biased. In this study, we present a flexible and relatively efficient methodology (i to obtain more reliable hydrological simulations in terms of coverage of validation data by the uncertainty bands and (ii to separate prediction uncertainty into its components. Our approach acknowledges that urban drainage predictions are biased. This is mostly due to input errors and structural deficits of the model. We address this issue by describing model bias in a Bayesian framework. The bias becomes an autoregressive term additional to white measurement noise, the only error type accounted for in traditional uncertainty analysis. To allow for bigger discrepancies during wet weather, we make the variance of bias dependent on the input (rainfall or/and output (runoff of the system. Specifically, we present a structured approach to select, among five variants, the optimal bias description for a given urban or natural case study. We tested the methodology in a small monitored stormwater system described with a parsimonious model. Our results clearly show that flow simulations are much more reliable when bias is accounted for than when it is neglected. Furthermore, our probabilistic predictions can discriminate between three uncertainty contributions: parametric uncertainty, bias, and measurement errors. In our case study, the best performing bias description is the output-dependent bias using a log-sinh transformation of data and model results. The limitations of the framework presented are some ambiguity due to the subjective choice of priors for bias parameters and its inability to address the causes of model discrepancies. Further research should focus on
Roe, Byron
2013-01-01
The effect of correlations between model parameters and nuisance parameters is discussed, in the context of fitting model parameters to data. Modifications to the usual $\\chi^2$ method are required. Fake data studies, as used at present, will not be optimum. Problems will occur for applications of the Maltoni-Schwetz \\cite{ms} theorem. Neutrino oscillations are used as examples, but the problems discussed here are general ones, which are often not addressed.
Delineating parameter unidentifiabilities in complex models
Raman, Dhruva V.; Anderson, James; Papachristodoulou, Antonis
2017-03-01
Scientists use mathematical modeling as a tool for understanding and predicting the properties of complex physical systems. In highly parametrized models there often exist relationships between parameters over which model predictions are identical, or nearly identical. These are known as structural or practical unidentifiabilities, respectively. They are hard to diagnose and make reliable parameter estimation from data impossible. They furthermore imply the existence of an underlying model simplification. We describe a scalable method for detecting unidentifiabilities, as well as the functional relations defining them, for generic models. This allows for model simplification, and appreciation of which parameters (or functions thereof) cannot be estimated from data. Our algorithm can identify features such as redundant mechanisms and fast time-scale subsystems, as well as the regimes in parameter space over which such approximations are valid. We base our algorithm on a quantification of regional parametric sensitivity that we call `multiscale sloppiness'. Traditionally, the link between parametric sensitivity and the conditioning of the parameter estimation problem is made locally, through the Fisher information matrix. This is valid in the regime of infinitesimal measurement uncertainty. We demonstrate the duality between multiscale sloppiness and the geometry of confidence regions surrounding parameter estimates made where measurement uncertainty is non-negligible. Further theoretical relationships are provided linking multiscale sloppiness to the likelihood-ratio test. From this, we show that a local sensitivity analysis (as typically done) is insufficient for determining the reliability of parameter estimation, even with simple (non)linear systems. Our algorithm can provide a tractable alternative. We finally apply our methods to a large-scale, benchmark systems biology model of necrosis factor (NF)-κ B , uncovering unidentifiabilities.
Directory of Open Access Journals (Sweden)
Yarash K. Abuev
2017-01-01
Full Text Available Abstract. Objectives A computer simulation of the antiferromagnetic structures described by the three-vertex Potts model on a triangular lattice is performed, taking into account the antiferromagnetic exchange interactions between the nearest J1 and second J2 neighbours. The main goal of the computer simulation was to elucidate the effects of ground state and areas of frustration on the thermodynamic and magnetic properties of antiferromagnetic structures described by the lowdimensional Potts model. Method The computer simulation is based on the Monte Carlo method. This method is implemented using the Metropolis algorithm in combination with the Wolff claster algorithm. The computer simulation was carried out for low-dimensional systems with periodic boundary conditions and linear dimensions L = 24124. Results On the basis of heat capacity and entropy analysis, phase transitions were observed in the considered model to possess exchange interaction parameters J1 <0 and J2 <0 in the variation intervals 0r<0.2 and 1.0
Chen, Chang-Kun; Li, Zhi; Sun, Yun-Feng
A new model for describing the disaster system including instantaneous and continuous action synchronously has been developed. The model is composed of three primary parts, that is, the impact from its causative disaster events, stochastic noise of disaster node and self-healing function, and every part is modeled concretely in terms of their characteristics in practice. Some key parameters, namely link appearance probability, retardation coefficient, ultimate repair capacity of government, dynamical modes considering different disaster evolving chains, and the positions of link with the specific performance in disaster network system are involved. Combined with a case study, the proposed model is applied to a certain disaster evolution system, and the influence law of different parameters on disaster evolution process, in disaster networks with instantaneous-action and/or continuous-action, is presented and compared. The results indicate that the destructive impact in the networks by link in continuous action is far greater an order of magnitude than that in instantaneous action. If a link in continuous action emerges in the disaster network system, properties of the causative event for the link, link appearance probability and its position in the network all have a notable influence to the severity of the disaster network. In addition, some peculiar phenomena are also commendably observed in the disaster evolution process based on the model, such as the multipeaks emerging in the destroyed rate number curve for some crisis nodes caused by their various inducing paths together with the relevant retardation coefficients, the existence of the critical value for ultimate repair capacity to recover the disaster node, and so on.
A simple model describes large individual differences in simultaneous colour contrast.
Ekroll, Vebjørn; Faul, Franz
2009-09-01
We report experimental evidence for substantial individual differences in the susceptibility to simultaneous colour contrast. Interestingly, we found that not only the general amount of colour induction varies across observers, but also the general shape of the curves describing asymmetric matching data. A simple model based on von Kries adaptation and crispening describes the data rather well when we regard its free parameters as observer specific. We argue that the von Kries component reflects the action of a temporal adaptation mechanism, while the crispening component describes the action of the instantaneous, purely spatial mechanism most appropriately labeled simultaneous colour contrast. An interesting consequence of this view is that traditional ideas about the general characteristics of simultaneous contrast must be considered as misleading. According to Kirschmann's 4th law, for instance, the simultaneous contrast effect should increase with increasing saturation of the surround, but crispening predicts the converse. Based on this reasoning, we offer a plausible explanation for the mixed evidence on the validity of Kirschmann's 4th law. We also argue that simultaneous contrast, the crispening effect, Meyer's effect and the gamut expansion effect are just different names for the same basic phenomenon.
Estimation of Model Parameters for Steerable Needles
Park, Wooram; Reed, Kyle B.; Okamura, Allison M.; Chirikjian, Gregory S.
2010-01-01
Flexible needles with bevel tips are being developed as useful tools for minimally invasive surgery and percutaneous therapy. When such a needle is inserted into soft tissue, it bends due to the asymmetric geometry of the bevel tip. This insertion with bending is not completely repeatable. We characterize the deviations in needle tip pose (position and orientation) by performing repeated needle insertions into artificial tissue. The base of the needle is pushed at a constant speed without rotating, and the covariance of the distribution of the needle tip pose is computed from experimental data. We develop the closed-form equations to describe how the covariance varies with different model parameters. We estimate the model parameters by matching the closed-form covariance and the experimentally obtained covariance. In this work, we use a needle model modified from a previously developed model with two noise parameters. The modified needle model uses three noise parameters to better capture the stochastic behavior of the needle insertion. The modified needle model provides an improvement of the covariance error from 26.1% to 6.55%. PMID:21643451
Estimation of Model Parameters for Steerable Needles.
Park, Wooram; Reed, Kyle B; Okamura, Allison M; Chirikjian, Gregory S
2010-01-01
Flexible needles with bevel tips are being developed as useful tools for minimally invasive surgery and percutaneous therapy. When such a needle is inserted into soft tissue, it bends due to the asymmetric geometry of the bevel tip. This insertion with bending is not completely repeatable. We characterize the deviations in needle tip pose (position and orientation) by performing repeated needle insertions into artificial tissue. The base of the needle is pushed at a constant speed without rotating, and the covariance of the distribution of the needle tip pose is computed from experimental data. We develop the closed-form equations to describe how the covariance varies with different model parameters. We estimate the model parameters by matching the closed-form covariance and the experimentally obtained covariance. In this work, we use a needle model modified from a previously developed model with two noise parameters. The modified needle model uses three noise parameters to better capture the stochastic behavior of the needle insertion. The modified needle model provides an improvement of the covariance error from 26.1% to 6.55%.
On the modeling of internal parameters in hyperelastic biological materials
Giantesio, Giulia
2016-01-01
This paper concerns the behavior of hyperelastic energies depending on an internal parameter. First, the situation in which the internal parameter is a function of the gradient of the deformation is presented. Second, two models where the parameter describes the activation of skeletal muscle tissue are analyzed. In those models, the activation parameter depends on the strain and it is important to consider the derivative of the parameter with respect to the strain in order to capture the proper behavior of the stress.
NEW DOCTORAL DEGREE Parameter estimation problem in the Weibull model
Marković, Darija
2009-01-01
In this dissertation we consider the problem of the existence of best parameters in the Weibull model, one of the most widely used statistical models in reliability theory and life data theory. Particular attention is given to a 3-parameter Weibull model. We have listed some of the many applications of this model. We have described some of the classical methods for estimating parameters of the Weibull model, two graphical methods (Weibull probability plot and hazard plot), and two analyt...
Lambe, N R; Navajas, E A; Simm, G; Bünger, L
2006-10-01
This study compared the use of various models to describe growth in lambs of 2 contrasting breeds from birth to slaughter. Live BW records (n = 7559) from 240 Texel and 231 Scottish Blackface (SBF) lambs weighed at 2-wk intervals were modeled. Biologically relevant variables were estimated for each lamb from modified versions of the logistic, Gompertz, Richards, and exponential models, and from linear regression. In both breeds, all nonlinear models fitted the data well, with an average coefficient of determination (R2) of > 0.98. The linear model had a lower average R2 than any of the nonlinear models (growth patterns, but the Akaike's information criteria value (which weighs log-likelihood by number of parameters estimated) was similar to that of the Gompertz model. Variables A, B, C, and D were moderately to highly heritable in Texel lambs (h2 = 0.33 to 0.87), and genetic correlations between variables within-model ranged from -0.80 to 0.89, suggesting some flexibility to change the shape of the growth curve when selecting for different variables. In SBF lambs, only variables from the logistic and Gompertz models had moderate heritabilities (0.17 to 0.56), but with high genetic correlations between variables within each model ( 0.92). Selection on growth variables seems promising (in Texel more than SBF), but high genetic correlations between variables may restrict the possibilities to change the growth curve shape. A random regression model was also fitted to the data to allow predictions of growth rates at relevant time points. Heritabilities for growth rates differed markedly at various stages of growth and between the 2 breeds (Texel: 0.14 to 0.74; SBF: 0.07 to 0.34), with negative correlations between growth rate at 60 d of age and growth rate at finishing. Following these results, future studies should investigate genetic relationships between relevant growth curve variables and other important production traits, such as carcass composition and meat
National Research Council Canada - National Science Library
Yarash K. Abuev; Albert B. Babaev; Pharkhat E. Esetov
2017-01-01
Objectives A computer simulation of the antiferromagnetic structures described by the three-vertex Potts model on a triangular lattice is performed, taking into account the antiferromagnetic exchange...
Improving uncertainty estimation in urban hydrological modeling by statistically describing bias
Directory of Open Access Journals (Sweden)
D. Del Giudice
2013-04-01
Full Text Available Hydrodynamic models are useful tools for urban water management. Unfortunately, it is still challenging to obtain accurate results and plausible uncertainty estimates when using these models. In particular, with the currently applied statistical techniques, flow predictions are usually overconfident and biased. In this study, we present a flexible and computationally efficient methodology (i to obtain more reliable hydrological simulations in terms of coverage of validation data by the uncertainty bands and (ii to separate prediction uncertainty into its components. Our approach acknowledges that urban drainage predictions are biased. This is mostly due to input errors and structural deficits of the model. We address this issue by describing model bias in a Bayesian framework. The bias becomes an autoregressive term additional to white measurement noise, the only error type accounted for in traditional uncertainty analysis in urban hydrology. To allow for bigger discrepancies during wet weather, we make the variance of bias dependent on the input (rainfall or/and output (runoff of the system. Specifically, we present a structured approach to select, among five variants, the optimal bias description for a given urban or natural case study. We tested the methodology in a small monitored stormwater system described by means of a parsimonious model. Our results clearly show that flow simulations are much more reliable when bias is accounted for than when it is neglected. Furthermore, our probabilistic predictions can discriminate between three uncertainty contributions: parametric uncertainty, bias (due to input and structural errors, and measurement errors. In our case study, the best performing bias description was the output-dependent bias using a log-sinh transformation of data and model results. The limitations of the framework presented are some ambiguity due to the subjective choice of priors for bias parameters and its inability to directly
DEFF Research Database (Denmark)
Chambon, Julie Claire Claudia; Bjerg, Poul Løgstrup; Scheutz, Charlotte;
2013-01-01
Reductive dechlorination is a major degradation pathway of chlorinated ethenes in anaerobic subsurface environments, and reactive kinetic models describing the degradation process are needed in fate and transport models of these contaminants. However, reductive dechlorination is a complex biologi...
Native metastability in chalcogenide glasses described within configuration-coordinate model
Energy Technology Data Exchange (ETDEWEB)
Shpotyuk, M [Institute of Materials of Scientific Research Company ' Carat' , 202, Stryjska str., Lviv (Ukraine); Vakiv, M [Institute of Materials of Scientific Research Company ' Carat' , 202, Stryjska str., Lviv (Ukraine)
2007-08-15
It was created configuration-coordinate model for describing of native metastability in chalcogenide glasses. It was shown that potential should be at least triple-well. System of differential equations for describing transitions between the atomic states was made and solved within present configuration-coordinate model.
Butler–Volmer–Monod model for describing bio-anode polarization curves
Hamelers, H.V.M.; Heijne, ter A.; Stein, N.; Rozendal, R.A.; Buisman, C.J.N.
2011-01-01
A kinetic model of the bio-anode was developed based on a simple representation of the underlying biochemical conversions as described by enzyme kinetics, and electron transfer reactions as described by the Butler–Volmer electron transfer kinetics. This Butler–Volmer–Monod model was well able to des
Parameter Estimation and Experimental Design in Groundwater Modeling
Institute of Scientific and Technical Information of China (English)
SUN Ne-zheng
2004-01-01
This paper reviews the latest developments on parameter estimation and experimental design in the field of groundwater modeling. Special considerations are given when the structure of the identified parameter is complex and unknown. A new methodology for constructing useful groundwater models is described, which is based on the quantitative relationships among the complexity of model structure, the identifiability of parameter, the sufficiency of data, and the reliability of model application.
Energy Technology Data Exchange (ETDEWEB)
Powell, B A; Kersting, A; Zavarin, M; Zhao, P
2008-10-28
Due to their ubiquity in nature and chemical reactivity, aluminosilicate minerals play an important role in retarding actinide subsurface migration. However, very few studies have examined Pu interaction with clay minerals in sufficient detail to produce a credible mechanistic model of its behavior. In this work, Pu(IV) and Pu(V) interactions with silica, gibbsite (Aloxide), and Na-montmorillonite (smectite clay) were examined as a function of time and pH. Sorption of Pu(IV) and Pu(V) to gibbsite and silica increased with pH (4 to 10). The Pu(V) sorption edge shifted to lower pH values over time and approached that of Pu(IV). This behavior is apparently due to surface mediated reduction of Pu(V) to Pu(IV). Surface complexation constants describing Pu(IV)/Pu(V) sorption to aluminol and silanol groups were developed from the silica and gibbsite sorption experiments and applied to the montmorillonite dataset. The model provided an acceptable fit to the montmorillonite sorption data for Pu(V). In order to accurately predict Pu(IV) sorption to montmorillonite, the model required inclusion of ion exchange. The objective of this work is to measure the sorption of Pu(IV) and Pu(V) to silica, gibbsite, and smectite (montmorillonite). Aluminosilicate minerals are ubiquitous at the Nevada National Security Site and improving our understanding of Pu sorption to aluminosilicates (smectite clays in particular) is essential to the accurate prediction of Pu transport rates. These data will improve the mechanistic approach for modeling the hydrologic source term (HST) and provide sorption Kd parameters for use in CAU models. In both alluvium and tuff, aluminosilicates have been found to play a dominant role in the radionuclide retardation because their abundance is typically more than an order of magnitude greater than other potential sorbing minerals such as iron and manganese oxides (e.g. Vaniman et al., 1996). The sorption database used in recent HST models (Carle et al., 2006
Endorsement of Models Describing Sexual Response of Men and Women with a Sexual Partner
DEFF Research Database (Denmark)
Giraldi, Annamaria; Kristensen, Ellids; Sand, Michael
2015-01-01
INTRODUCTION: Several models have been used to describe men's and women's sexual responses. These models have been conceptualized as linear or circular models. The circular models were proposed to describe women's sexual function best. AIM: This study aims to determine whether men and women thought...... that current theoretical models of sexual responses accurately reflected their own sexual experience and to what extent this was influenced by sexual dysfunction. METHODS: A cross-sectional study of a large, broadly sampled, nonclinical population, cohort of Danish men and women. The Female Sexual Function...... Index, Female Sexual Distress Scale, and the International Index of Erectile Function were used to describe sexual function. Also, participants completed questionnaires with written descriptions of different sexual responses to describe their most experienced sexual response. MAIN OUTCOME MEASURE...
DEFF Research Database (Denmark)
Madsen, Henrik; Bacher, Peder; Andersen, Philip Hvidthøft Delff
2010-01-01
, existence of prior physical knowledge, the data and the available statistical soft- ware tools. The importance of statistical model validation is discussed, and some simple tools for that purpose are demonstrated. This paper also brieﬂy describes some of the most frequently used software tools for modelling......This paper describes a number of statistical methods and models for describing the thermal characteristics of buildings using frequent readings of heat consumption, ambient air temperature, and other available climate variables. For some of the methods frequent readings of the indoor air...
Modelling spin Hamiltonian parameters of molecular nanomagnets.
Gupta, Tulika; Rajaraman, Gopalan
2016-07-12
Molecular nanomagnets encompass a wide range of coordination complexes possessing several potential applications. A formidable challenge in realizing these potential applications lies in controlling the magnetic properties of these clusters. Microscopic spin Hamiltonian (SH) parameters describe the magnetic properties of these clusters, and viable ways to control these SH parameters are highly desirable. Computational tools play a proactive role in this area, where SH parameters such as isotropic exchange interaction (J), anisotropic exchange interaction (Jx, Jy, Jz), double exchange interaction (B), zero-field splitting parameters (D, E) and g-tensors can be computed reliably using X-ray structures. In this feature article, we have attempted to provide a holistic view of the modelling of these SH parameters of molecular magnets. The determination of J includes various class of molecules, from di- and polynuclear Mn complexes to the {3d-Gd}, {Gd-Gd} and {Gd-2p} class of complexes. The estimation of anisotropic exchange coupling includes the exchange between an isotropic metal ion and an orbitally degenerate 3d/4d/5d metal ion. The double-exchange section contains some illustrative examples of mixed valance systems, and the section on the estimation of zfs parameters covers some mononuclear transition metal complexes possessing very large axial zfs parameters. The section on the computation of g-anisotropy exclusively covers studies on mononuclear Dy(III) and Er(III) single-ion magnets. The examples depicted in this article clearly illustrate that computational tools not only aid in interpreting and rationalizing the observed magnetic properties but possess the potential to predict new generation MNMs.
PARAMETER ESTIMATION OF ENGINEERING TURBULENCE MODEL
Institute of Scientific and Technical Information of China (English)
钱炜祺; 蔡金狮
2001-01-01
A parameter estimation algorithm is introduced and used to determine the parameters in the standard k-ε two equation turbulence model (SKE). It can be found from the estimation results that although the parameter estimation method is an effective method to determine model parameters, it is difficult to obtain a set of parameters for SKE to suit all kinds of separated flow and a modification of the turbulence model structure should be considered. So, a new nonlinear k-ε two-equation model (NNKE) is put forward in this paper and the corresponding parameter estimation technique is applied to determine the model parameters. By implementing the NNKE to solve some engineering turbulent flows, it is shown that NNKE is more accurate and versatile than SKE. Thus, the success of NNKE implies that the parameter estimation technique may have a bright prospect in engineering turbulence model research.
Hoffman, Alexander F; Spivak, Charles E; Lupica, Carl R
2016-06-15
Fast-scan cyclic voltammetry (FSCV) using carbon fiber electrodes is widely used to rapidly monitor changes in dopamine (DA) levels in vitro and in vivo. Current analytical approaches utilize parameters such as peak oxidation current amplitude and decay times to estimate release and uptake processes, respectively. However, peak amplitude changes are often observed with uptake inhibitors, thereby confounding the interpretation of these parameters. To overcome this limitation, we demonstrate that a simple five-parameter, two-compartment model mathematically describes DA signals as a balance of release (r/ke) and uptake (ku), summed with adsorption (kads and kdes) of DA to the carbon electrode surface. Using nonlinear regression, we demonstrate that our model precisely describes measured DA signals obtained in brain slice recordings. The parameters extracted from these curves were then validated using pharmacological manipulations that selectively alter vesicular release or DA transporter (DAT)-mediated uptake. Manipulation of DA release through altering the Ca(2+)/Mg(2+) ratio or adding tetrodotoxin reduced the release parameter with no effect on the uptake parameter. DAT inhibitors methylenedioxypyrovalerone, cocaine, and nomifensine significantly reduced uptake and increased vesicular DA release. In contrast, a low concentration of amphetamine reduced uptake but had no effect on DA release. Finally, the kappa opioid receptor agonist U50,488 significantly reduced vesicular DA release but had no effect on uptake. Together, these data demonstrate a novel analytical approach to distinguish the effects of manipulations on DA release or uptake that can be used to interpret FSCV data.
A Meta-model Describing the Development Process of Mobile Learning
Wingkvist, Anna; Ericsson, Morgan
This paper presents a meta-model to describe the development process of mobile learning initiatives. These initiatives are often small scale trials that are not integrated in the intended setting, but carried out outside of the setting. This results in sustainability issues, i.e., problems to integrate the results of the initiative as learning aids. In order to address the sustainability issues, and in turn help to understand the scaling process, a meta-model is introduced. This meta-model divides the development into four areas of concern, and the life cycle of any mobile learning initiative into four stages. The meta-model was developed by analyzing and describing how a podcasting initiative was developed, and is currently being evaluated as a tool to both describe and evaluate mobile learning initiatives. The meta-model was developed based on a mobile learning initiative, but the meta-model itself is extendible to other forms of technology-enhanced learning.
WELL-POSEDNESS OF THE MODEL DESCRIBING A REPAIRABLE, STANDBY, HUMAN & MACHINE SYSTEM
Institute of Scientific and Technical Information of China (English)
Geni Gupur
2003-01-01
By using the strong continuous semigroup theory of linear operators we prove the existence of a unique positive time-dependent solution of the model describing a repairable, standby, human & machine system.
Accuracy Assessment for Cad Modeling of Freeform Surface Described by Equation
Directory of Open Access Journals (Sweden)
Golba Grzegorz
2015-06-01
Full Text Available This paper presents the results of comparative analysis of modeling accuracy the freeform surface constructed by using a variety of algorithms for surface modeling. Also determined the accuracy of mapping the theoretical freeform surface described by mathematical equation. To model surface objects used: SolidWorks 2012, CATIA v5 and Geomagic Studio 12. During the design process of CAD models were used: profile curves, fitting parametric surface and polygonal mesh. To assess the accuracy of the CAD models used Geomagic Qualify 12. On the basis of analyse defined the scope of application of each modeling techniques depending on the nature of the constructed object.
Directory of Open Access Journals (Sweden)
Mattia Gazzola
2009-12-01
Full Text Available Cytoplasmic transport of organelles, nucleic acids and proteins on microtubules is usually bidirectional with dynein and kinesin motors mediating the delivery of cargoes in the cytoplasm. Here we combine live cell microscopy, single virus tracking and trajectory segmentation to systematically identify the parameters of a stochastic computational model of cargo transport by molecular motors on microtubules. The model parameters are identified using an evolutionary optimization algorithm to minimize the Kullback-Leibler divergence between the in silico and the in vivo run length and velocity distributions of the viruses on microtubules. The present stochastic model suggests that bidirectional transport of human adenoviruses can be explained without explicit motor coordination. The model enables the prediction of the number of motors active on the viral cargo during microtubule-dependent motions as well as the number of motor binding sites, with the protein hexon as the binding site for the motors.
Gazzola, Mattia; Burckhardt, Christoph J; Bayati, Basil; Engelke, Martin; Greber, Urs F; Koumoutsakos, Petros
2009-12-01
Cytoplasmic transport of organelles, nucleic acids and proteins on microtubules is usually bidirectional with dynein and kinesin motors mediating the delivery of cargoes in the cytoplasm. Here we combine live cell microscopy, single virus tracking and trajectory segmentation to systematically identify the parameters of a stochastic computational model of cargo transport by molecular motors on microtubules. The model parameters are identified using an evolutionary optimization algorithm to minimize the Kullback-Leibler divergence between the in silico and the in vivo run length and velocity distributions of the viruses on microtubules. The present stochastic model suggests that bidirectional transport of human adenoviruses can be explained without explicit motor coordination. The model enables the prediction of the number of motors active on the viral cargo during microtubule-dependent motions as well as the number of motor binding sites, with the protein hexon as the binding site for the motors.
Hoeven, van der N.; Elsas, van J.D.; Heijnen, C.E.
1996-01-01
A computer simulation model was developed which describes growth and competition of bacteria in the soil environment. In the model, soil was assumed to contain millions of pores of a few different size classes. An introduced bacterial strain, e.g. a genetically modified micro-organism (GEMMO), was a
Dynamic behaviour of reactive distillation tray columns described with a non-equilibrium cell model
Baur, R.; Taylor, R.; Krishna, R.
2001-01-01
In this paper we develop a generic, dynamic, nonequilibrium (NEQ) cell model for reactive distillation (RD) tray columns. The features of our model are (1) the use of Maxwell–Stefan equations for describing mass transfer between fluid phases, (2) the reaction is assumed to take place in the liquid
Hoeven, van der N.; Elsas, van J.D.; Heijnen, C.E.
1996-01-01
A computer simulation model was developed which describes growth and competition of bacteria in the soil environment. In the model, soil was assumed to contain millions of pores of a few different size classes. An introduced bacterial strain, e.g. a genetically modified micro-organism (GEMMO), was a
Elsener, K; Schlatter, D; Siegrist, N
2011-01-01
The CLIC_ILD and CLIC_SiD detector concepts as used for the CDR Vol. 2 in 2011 exist both in GEANT4 simulation models and in engineering layout drawings. At this early stage of a conceptual design, there are inevitably differences between these models, which are described in this note.
Benchmarking of numerical models describing the dispersion of radionuclides in the Arctic Seas
Energy Technology Data Exchange (ETDEWEB)
Scott, E.M.; Harms, I. [Department of Statistics, University of Glasgow, Glasgow (United Kingdom); Gurbutt, P. [MAFF, Fisheries Laboratory, Lowestoft (United Kingdom); Heling, R. [KEMA, Arnhem (Netherlands); Nielsen, S.P. [Risoe National Laboratory, Roskilde (Denmark); Osvath, I. [IAEA Marine Environment Laboratory, Monaco (France); Preller, R. [Naval Research Laboratory, Stennis Space Center (United States); Sazykina, T. [SPA Typhoon, Obninsk (Russian Federation); Wada, A. [Department of Civil Engineering, College of Industrial Technology, Nihon University, Nihon (Japan); Sjoeblom, K.L. [IAEA Waste Management Division, Vienna (Austria)
1997-08-25
As part of the International Arctic Seas Assessment Project (IASAP) of the International Atomic Energy Agency (IAEA), a working group was created to model the dispersal and transfer of radionuclides released from radioactive waste disposed of in the Kara Sea. The objectives of this group are: (1) development of realistic and reliable assessment models for the dispersal of radioactive contaminants both within, and from, the Arctic ocean; and (2) evaluation of the contributions of different transfer mechanisms to contaminant dispersal and hence, ultimately, to the risks to human health and environment. With regard to the first objective, the modelling work has been directed towards assessment of model reliability and as one aspect of this, a benchmarking exercise has been carried out. This paper briefly describes the benchmark scenario, the models developed and used, and discusses some of the benchmarking results. The role of the exercise within the modelling programme of IASAP will be discussed and future work described.
Parameter redundancy in discrete state‐space and integrated models
McCrea, Rachel S.
2016-01-01
Discrete state‐space models are used in ecology to describe the dynamics of wild animal populations, with parameters, such as the probability of survival, being of ecological interest. For a particular parametrization of a model it is not always clear which parameters can be estimated. This inability to estimate all parameters is known as parameter redundancy or a model is described as nonidentifiable. In this paper we develop methods that can be used to detect parameter redundancy in discrete state‐space models. An exhaustive summary is a combination of parameters that fully specify a model. To use general methods for detecting parameter redundancy a suitable exhaustive summary is required. This paper proposes two methods for the derivation of an exhaustive summary for discrete state‐space models using discrete analogues of methods for continuous state‐space models. We also demonstrate that combining multiple data sets, through the use of an integrated population model, may result in a model in which all parameters are estimable, even though models fitted to the separate data sets may be parameter redundant. PMID:27362826
Parameter redundancy in discrete state-space and integrated models.
Cole, Diana J; McCrea, Rachel S
2016-09-01
Discrete state-space models are used in ecology to describe the dynamics of wild animal populations, with parameters, such as the probability of survival, being of ecological interest. For a particular parametrization of a model it is not always clear which parameters can be estimated. This inability to estimate all parameters is known as parameter redundancy or a model is described as nonidentifiable. In this paper we develop methods that can be used to detect parameter redundancy in discrete state-space models. An exhaustive summary is a combination of parameters that fully specify a model. To use general methods for detecting parameter redundancy a suitable exhaustive summary is required. This paper proposes two methods for the derivation of an exhaustive summary for discrete state-space models using discrete analogues of methods for continuous state-space models. We also demonstrate that combining multiple data sets, through the use of an integrated population model, may result in a model in which all parameters are estimable, even though models fitted to the separate data sets may be parameter redundant. © 2016 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Comparing non-linear mathematical models to describe growth of different animals
Directory of Open Access Journals (Sweden)
Jhony Tiago Teleken
2017-02-01
Full Text Available The main objective of this study was to compare the goodness of fit of five non-linear growth models, i.e. Brody, Gompertz, Logistic, Richards and von Bertalanffy in different animals. It also aimed to evaluate the influence of the shape parameter on the growth curve. To accomplish this task, published growth data of 14 different groups of animals were used and four goodness of fit statistics were adopted: coefficient of determination (R2, root mean square error (RMSE, Akaike information criterion (AIC and Bayesian information criterion (BIC. In general, the Richards growth equation provided better fits to experimental data than the other models. However, for some animals, different models exhibited better performance. It was obtained a possible interpretation for the shape parameter, in such a way that can provide useful insights to predict animal growth behavior.
A consilience model to describe N2O production during biological N removal
DEFF Research Database (Denmark)
Domingo Felez, Carlos; Smets, Barth F.
2016-01-01
(NO) and N2O dynamics have been proposed. Here, a first comprehensive model that considers all relevant NO and N2O production and consumption mechanisms is proposed. The model describes autotrophic NO production by ammonia oxidizing bacteria associated with ammonia oxidation and with nitrite reduction......Nitrous oxide (N2O), a potent greenhouse gas, is produced during biological nitrogen conversion in wastewater treatment operations. Complex mechanisms underlie N2O production by autotrophic and heterotrophic organisms, which continue to be unravelled. Mathematical models that describe nitric oxide......, followed by NO reduction to N2O. It also considers NO and N2O as intermediates in heterotrophic denitrification in a 4-step model. Three biological NO and N2O production pathways are accounted for, improving the capabilities of existing models while not increasing their complexity. Abiotic contributions...
Flexible and fixed mathematical models describing growth patterns of chukar partridges
Aygün, Ali; Narinç, Doǧan
2016-04-01
In animal science, the nonlinear regression models for growth curve analysis ofgrowth patterns are separated into two groups called fixed and flexible according to their point of inflection. The aims of this study were to compare fixed and flexible growth functions and to determine the best fit model for the growth data of chukar partridges. With this aim, the growth data of partridges were modeled with widely used models, such as Gompertz, Logistic, Von Bertalanffy as well as the flexible functions, such as, Richards, Janoschek, Levakovich. So as to evaluate growth functions, the R2 (coefficient of determination), adjusted R2 (adjusted coefficient of determination), MSE (mean square error), AIC (Akaike's information criterion) and BIC (Bayesian information criterion) goodness of fit criteria were used. It has been determined that the best fit model from the point of chukar partridge growth data according to mentioned goodness of fit criteria is Janoschek function which has a flexible structure. The Janoschek model is not only important because it has a higher number of parameters with biological meaning than the other functions (the mature weight and initial weight parameters), but also because it was not previously used in the modeling of the chukar partridge growth.
A Model to Describe the Magnetomechanical Behavior of Martensite in Magnetic Shape Memory Alloy
Directory of Open Access Journals (Sweden)
Zaoyang Guo
2014-01-01
Full Text Available A model to describe the constitutive behavior of magnetic shape memory alloy composed with pure martensite is proposed based on the analysis of variants reorientation. A hyperbolic tangent expression is given to describe the variants transition during magnetic and mechanical loading process. The main features of magnetic shape memory alloy, such as pseudoelastic and partially pseudoelastic behavior as well as minor hysteretic loops, can be successfully replicated with the proposed model. A good agreement is achieved between calculated results and experimental data for NiMnGa single crystal.
Bayesian estimation of parameters in a regional hydrological model
Directory of Open Access Journals (Sweden)
K. Engeland
2002-01-01
Full Text Available This study evaluates the applicability of the distributed, process-oriented Ecomag model for prediction of daily streamflow in ungauged basins. The Ecomag model is applied as a regional model to nine catchments in the NOPEX area, using Bayesian statistics to estimate the posterior distribution of the model parameters conditioned on the observed streamflow. The distribution is calculated by Markov Chain Monte Carlo (MCMC analysis. The Bayesian method requires formulation of a likelihood function for the parameters and three alternative formulations are used. The first is a subjectively chosen objective function that describes the goodness of fit between the simulated and observed streamflow, as defined in the GLUE framework. The second and third formulations are more statistically correct likelihood models that describe the simulation errors. The full statistical likelihood model describes the simulation errors as an AR(1 process, whereas the simple model excludes the auto-regressive part. The statistical parameters depend on the catchments and the hydrological processes and the statistical and the hydrological parameters are estimated simultaneously. The results show that the simple likelihood model gives the most robust parameter estimates. The simulation error may be explained to a large extent by the catchment characteristics and climatic conditions, so it is possible to transfer knowledge about them to ungauged catchments. The statistical models for the simulation errors indicate that structural errors in the model are more important than parameter uncertainties. Keywords: regional hydrological model, model uncertainty, Bayesian analysis, Markov Chain Monte Carlo analysis
Attributes of clinical role models as described by senior veterinary students in Australia.
Schull, Daniel N; Kyle, Greg J; Coleman, Glen T; Mills, Paul C
2012-01-01
Role models incite admiration and provide inspiration, contributing to learning as students aspire to emulate their example. The attributes of physician role models for medical trainees are well documented, but they remain largely unexplored in the context of veterinary medical training. The aim of the current study was to describe the attributes that final-year veterinary students (N=213) at the University of Queensland identified when reflecting on their clinical role models. Clinical role model descriptions provided by students were analyzed using concept-mapping software (Leximancer v. 2.25). The most frequent and highly connected concepts used by students when describing their role model(s) included clients, vet, and animal. Role models were described as good communicators who were skilled at managing relationships with clients, patients, and staff. They had exemplary knowledge, skills, and abilities, and they were methodical and conducted well-structured consultations. They were well respected and, in turn, demonstrated respect for clients, colleagues, staff, and students alike. They were also good teachers and able to tailor explanations to suit both clients and students. Findings from this study may serve to assist with faculty development and as a basis for further research in this area.
Directory of Open Access Journals (Sweden)
Zahra Ojaghi-Haghighi
2015-10-01
Full Text Available Background: Left ventricular (LV twist is due to oppositely directed apical and basal rotation and has been proposed as a sensitive marker of LV function. We sought to assess the impact of chronic pure mitral regurgitation (MR on the torsional mechanics of the left human ventricle using tissue Doppler imaging.Methods: Nineteen severe MR patients with a normal LV ejection fraction and 16 non-MR controls underwent conventional echocardiography and apical and basal short-axis color Doppler myocardial imaging (CDMI. LV rotation at the apical and basal short-axis levels was calculated from the averaged tangential velocities of the septal and lateral regions, corrected for the LV radius over time. LV twist was defined as the difference in LV rotation between the two levels, and the LV twist and twisting/untwisting rate profiles were analyzed throughout the cardiac cycle.Results: LV twist and LV torsion were significantly lower in the MR group than in the non-MR group (10.38˚ ± 4.04˚ vs.13.95˚ ± 4.27˚; p value = 0.020; and 1.29 ± 0.54 ˚/cm vs. 1.76 ± 0.56 ˚/cm; p value = 0.021, respectively, both suggesting incipient LV dysfunction in the MR group. Similarly, the untwisting rate was lower in the MR group (-79.74 ± 35.97 ˚/s vs.-110.96 ± 34.65 ˚/s; p value = 0.020, but there was statistically no significant difference in the LV twist rate.Conclusion: The evaluation of LV torsional parameters in MR patients with a normal LV ejection fraction suggests the potential role of these sensitive variables in assessing the early signs of ventricular dysfunction in asymptomatic patients
Describing, using 'recognition cones'. [parallel-series model with English-like computer program
Uhr, L.
1973-01-01
A parallel-serial 'recognition cone' model is examined, taking into account the model's ability to describe scenes of objects. An actual program is presented in an English-like language. The concept of a 'description' is discussed together with possible types of descriptive information. Questions regarding the level and the variety of detail are considered along with approaches for improving the serial representations of parallel systems.
Anomalously large capacitance of an ionic liquid described by the restricted primitive model
Loth, M S; Shklovskii, B I
2010-01-01
We use Monte Carlo simulations to examine the simplest model of an ionic liquid, called the restricted primitive model, at a metal surface. We find that at moderately low temperatures the capacitance of the metal/ionic liquid interface is so large that the effective thickness of the electrostatic double-layer is smaller than the ion radius. We suggest a semi-quantitative theory to describe these results.
Expected IPS variations due to a disturbance described by a 3-D MHD model
Tappin, S. J.; Dryer, M.; Han, S. M.; Wu, S. T.
1988-01-01
The variations of interplanetary scintillation due to a disturbance described by a three-dimensional, time-dependent, MHD model of the interplanetary medium are calculated. The resulting simulated IPS maps are compared with observations of real disturbances and it is found that there is some qualitative agreement. It is concluded that the MHD model with a more realistic choice of input conditions would probably provide a useful description of many interplanetary disturbances.
Gay, Guillaume; Courtheoux, Thibault; Reyes, Céline; Tournier, Sylvie; Gachet, Yannick
2012-01-01
In fission yeast, erroneous attachments of spindle microtubules to kinetochores are frequent in early mitosis. Most are corrected before anaphase onset by a mechanism involving the protein kinase Aurora B, which destabilizes kinetochore microtubules (ktMTs) in the absence of tension between sister chromatids. In this paper, we describe a minimal mathematical model of fission yeast chromosome segregation based on the stochastic attachment and detachment of ktMTs. The model accurately reproduce...
Walcott, Sam
2014-10-01
Molecular motors, by turning chemical energy into mechanical work, are responsible for active cellular processes. Often groups of these motors work together to perform their biological role. Motors in an ensemble are coupled and exhibit complex emergent behavior. Although large motor ensembles can be modeled with partial differential equations (PDEs) by assuming that molecules function independently of their neighbors, this assumption is violated when motors are coupled locally. It is therefore unclear how to describe the ensemble behavior of the locally coupled motors responsible for biological processes such as calcium-dependent skeletal muscle activation. Here we develop a theory to describe locally coupled motor ensembles and apply the theory to skeletal muscle activation. The central idea is that a muscle filament can be divided into two phases: an active and an inactive phase. Dynamic changes in the relative size of these phases are described by a set of linear ordinary differential equations (ODEs). As the dynamics of the active phase are described by PDEs, muscle activation is governed by a set of coupled ODEs and PDEs, building on previous PDE models. With comparison to Monte Carlo simulations, we demonstrate that the theory captures the behavior of locally coupled ensembles. The theory also plausibly describes and predicts muscle experiments from molecular to whole muscle scales, suggesting that a micro- to macroscale muscle model is within reach.
Shein, E. V.; Kokoreva, A. A.; Gorbatov, V. S.; Umarova, A. B.; Kolupaeva, V. N.; Perevertin, K. A.
2009-07-01
The water block of physically founded models of different levels (chromatographic PEARL models and dual-porosity MACRO models) was parameterized using laboratory experimental data and tested using the results of studying the water regime of loamy soddy-podzolic soil in large lysimeters of the Experimental Soil Station of Moscow State University. The models were adapted using a stepwise approach, which involved the sequential assessment and adjustment of each submodel. The models unadjusted for the water block underestimated the lysimeter flow and overestimated the soil water content. The theoretical necessity of the model adjustment was explained by the different scales of the experimental objects (soil samples) and simulated phenomenon (soil profile). The adjustment of the models by selecting the most sensitive hydrophysical parameters of the soils (the approximation parameters of the soil water retention curve (SWRC)) gave good agreement between the predicted moisture profiles and their actual values. In distinction from the PEARL model, the MARCO model reliably described the migration of a pesticide through the soil profile, which confirmed the necessity of physically founded models accounting for the separation of preferential flows in the pore space for the prediction, analysis, optimization, and management of modern agricultural technologies.
A model for describing the thermodynamics of multivalent host-guest interactions at interfaces
Huskens, Jurriaan; Mulder, A.; Auletta, T.; Nijhuis, C.A.; Ludden, M.J.W.; Reinhoudt, David
2004-01-01
A model has been described for interpreting the binding of multivalent molecules to interface-immobilized monovalent receptors through multiple, independent interactions. It is based on the concept of effective concentration, Ceff, which has been developed before for multivalent binding in solution
A transient-network model describing the rheological behaviour of concentrated dispersions
Kamphuis, H.; Jongschaap, R.J.J.; Mijnlieff, P.F.
1984-01-01
Attractive forces acting between particles in dispersions may cause a three-dimensional structure to be built up. A temporary-network model is postulated that describes the rheological behaviour of such systems. Chains of particles are assumed to be created and broken by thermal actions and by appli
Yu, H.; Erp, N. van; Bins, S.; Mathijssen, R.H.; Schellens, J.H.; Beijnen, J.H.; Steeghs, N.; Huitema, A.D.
2017-01-01
BACKGROUND AND OBJECTIVE: Pazopanib is a multi-targeted anticancer tyrosine kinase inhibitor. This study was conducted to develop a population pharmacokinetic (popPK) model describing the complex pharmacokinetics of pazopanib in cancer patients. METHODS: Pharmacokinetic data were available from 96
The objective of this work was to evaluate eight closed-form unimodal analytical expressions that describe the soil-water retention curve over the complete range of soil water contents. To meet this objective, the eight models were compared in terms of their accuracy (root mean square error, RMSE), ...
Robustness of a cross contamination model describing transfer of pathogens during grinding of meat
DEFF Research Database (Denmark)
Møller, Cleide Oliveira de Almeida; Sant’Ana, A. S.; Hansen, Solvej Katrine Holm
2016-01-01
This study aimed to evaluate a cross contamination model for its capability of describing transfer of Salmonella spp. and L. monocytogenes during grinding of varying sizes and numbers of pieces of meats in two grinder systems. Data from 19 trials were collected. Three evaluation approaches were...
Robustness of a cross contamination model describing transfer of pathogens during grinding of meat
DEFF Research Database (Denmark)
Møller, Cleide Oliveira de Almeida; Sant’Ana, A. S.; Hansen, Solvej Katrine Holm
2016-01-01
This study aimed to evaluate a cross contamination model for its capability of describing transfer of Salmonella spp. and L. monocytogenes during grinding of varying sizes and numbers of pieces of meats in two grinder systems. Data from 19 trials were collected. Three evaluation approaches were...
A transient-network model describing the rheological behaviour of concentrated dispersions
Kamphuis, H.; Jongschaap, R.J.J.; Mijnlieff, P.F.
1984-01-01
Attractive forces acting between particles in dispersions may cause a three-dimensional structure to be built up. A temporary-network model is postulated that describes the rheological behaviour of such systems. Chains of particles are assumed to be created and broken by thermal actions and by appli
Hawking Radiation of a Kaluza-Klein Black Hole Described by Landauer Transport Model
Institute of Scientific and Technical Information of China (English)
兰小刚; 韦联福
2012-01-01
We investigate the Hawking radiation of a Kaluza-Klein black hole by using one-dimensional(1D),non-equilibrium,Landauer transport model.The derived Hawking radiation temperature is in consistence with that obtained by using the usual anomaly method.With the Landauer transport model,we calculate the entropy flow out of the Kaluza-Klein black hole and the relevant entropy production rate.How these quantities depending on the physical parameters of the black hole is also discussed.
Robust estimation of hydrological model parameters
Directory of Open Access Journals (Sweden)
A. Bárdossy
2008-11-01
Full Text Available The estimation of hydrological model parameters is a challenging task. With increasing capacity of computational power several complex optimization algorithms have emerged, but none of the algorithms gives a unique and very best parameter vector. The parameters of fitted hydrological models depend upon the input data. The quality of input data cannot be assured as there may be measurement errors for both input and state variables. In this study a methodology has been developed to find a set of robust parameter vectors for a hydrological model. To see the effect of observational error on parameters, stochastically generated synthetic measurement errors were applied to observed discharge and temperature data. With this modified data, the model was calibrated and the effect of measurement errors on parameters was analysed. It was found that the measurement errors have a significant effect on the best performing parameter vector. The erroneous data led to very different optimal parameter vectors. To overcome this problem and to find a set of robust parameter vectors, a geometrical approach based on Tukey's half space depth was used. The depth of the set of N randomly generated parameters was calculated with respect to the set with the best model performance (Nash-Sutclife efficiency was used for this study for each parameter vector. Based on the depth of parameter vectors, one can find a set of robust parameter vectors. The results show that the parameters chosen according to the above criteria have low sensitivity and perform well when transfered to a different time period. The method is demonstrated on the upper Neckar catchment in Germany. The conceptual HBV model was used for this study.
Energy Technology Data Exchange (ETDEWEB)
Choi, Dooho [Department of Materials Science and Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, Pennsylvania 15213 (United States); Korea Railroad Research Institute, 360-1 Woulam, Uiwang, Kyunggi 437-757 (Korea, Republic of); Liu, Xuan [Department of Materials Science and Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, Pennsylvania 15213 (United States); Schelling, Patrick K. [Advanced Materials Processing and Analysis Center and Department of Physics, University of Central Florida, 4000 Central Florida Boulevard, Orlando, Florida 32816 (United States); Coffey, Kevin R. [Department of Materials Science and Engineering, University of Central Florida, 4000 Central Florida Boulevard, Orlando, Florida 32816 (United States); Barmak, Katayun [Department of Materials Science and Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, Pennsylvania 15213 (United States); Department of Applied Physics and Applied Mathematics, Columbia University, 500 West 120th Street, New York, New York 10027 (United States)
2014-03-14
The impact of electron scattering at surfaces and grain boundaries in nanometric polycrystalline tungsten (W) films was studied. A series of polycrystalline W films ranging in thickness from 10 to 310 nm and lateral grain size from 74 to 133 nm were prepared on thermally oxidized Si. The Fuchs-Sondheimer surface-scattering model and Mayadas-Shatzkes grain-boundary scattering model were employed for quantitative analyses. Predictions from the theoretical models were found to deviate systematically from the experimental data. Possible reasons for the failure of the theoretical models to describe the experimental data are explored. Finally, a discussion of the crucial features lacking from existing models is presented, along with possible avenues for improving the models to result in better agreement with experimental data.
Navarro-Barrientos, J-Emeterio; Rivera, Daniel E; Collins, Linda M
2011-01-12
We present a dynamical model incorporating both physiological and psychological factors that predicts changes in body mass and composition during the course of a behavioral intervention for weight loss. The model consists of a three-compartment energy balance integrated with a mechanistic psychological model inspired by the Theory of Planned Behavior (TPB). The latter describes how important variables in a behavioural intervention can influence healthy eating habits and increased physical activity over time. The novelty of the approach lies in representing the behavioural intervention as a dynamical system, and the integration of the psychological and energy balance models. Two simulation scenarios are presented that illustrate how the model can improve the understanding of how changes in intervention components and participant differences affect outcomes. Consequently, the model can be used to inform behavioural scientists in the design of optimised interventions for weight loss and body composition change.
A Revised Multi-Fickian Moisture Transport Model To Describe Non-Fickian Effects In Wood
DEFF Research Database (Denmark)
Frandsen, Henrik Lund; Svensson, Staffan; Damkilde, Lars
2007-01-01
This paper presents a study and a refinement of the sorption rate model in a so-called multi-Fickian or multiphase model. This type of model describes the complex moisture transport system in wood, which consists of separate water vapor and bound-water diffusion interacting through sorption....... At high relative humidities, the effect of this complex moisture transport system becomes apparent, and since a single Fickian diffusion equation fails to model the behavior, it has been referred to as non-Fickian or anomalous behavior. At low relative humidities, slow bound-water transport and fast...... conditions for the model are discussed, since discrepancies from corresponding models of moisture transport in paper products have been found....
A revised multi-Fickian moisture transport model to describe non-Fickian effects in wood
DEFF Research Database (Denmark)
Frandsen, Henrik Lund; Damkilde, Lars; Svensson, Staffan
2007-01-01
This paper presents a study and a refinement of the sorption rate model in a so-called multi-Fickian or multi-phase model. This type of model describes the complex moisture transport system in wood, which consists of separate water vapor and bound-water diffusion interacting through sorption....... At high relative humidities, the effect of this complex moisture transport system becomes apparent, and since a single Fickian diffusion equation fails to model the behavior, it has been referred to as non-Fickian or anomalous behavior. At low relative humidities, slow bound-water transport and fast...... conditions for the model are discussed, since discrepancies from corresponding models of moisture transport in paper products have been found. ©2007 by Walter de Gruyter....
Riahi, M H; Trelea, I C; Picque, D; Leclercq-Perlat, M-N; Hélias, A; Corrieu, G
2007-05-01
A mechanistic model for Debaryomyces hansenii growth and substrate consumption, lactose conversion into lactate by lactic acid bacteria, as well as lactose and lactate transfer from the core toward the rind was established. The model described the first step (14 d) of the ripening of a smear soft cheese and included the effects of temperature and relative humidity of the ripening chamber on the kinetic parameters. Experimental data were collected from experiments carried out in an aseptic pilot scale ripening chamber under 9 different combinations of temperature (8, 12, and 16 degrees C) and relative humidity (85, 93, and 99%) according to a complete experimental design. The model considered the cheese as a system with 2 compartments (rind and core) and included 5 state evolution equations and 16 parameters. The model succeeded in predicting D. hansenii growth and lactose and lactate concentrations during the first step of ripening (curd deacidification) in core and rind. The nonlinear data-fitting method allowed the determination of tight confidence intervals for the model parameters. The residual standard error (RSE) between model predictions and experimental data was close to the experimental standard deviation between repeated experiments.
Peckham, Scott
2016-04-01
Over the last decade, model coupling frameworks like CSDMS (Community Surface Dynamics Modeling System) and ESMF (Earth System Modeling Framework) have developed mechanisms that make it much easier for modelers to connect heterogeneous sets of process models in a plug-and-play manner to create composite "system models". These mechanisms greatly simplify code reuse, but must simultaneously satisfy many different design criteria. They must be able to mediate or compensate for differences between the process models, such as their different programming languages, computational grids, time-stepping schemes, variable names and variable units. However, they must achieve this interoperability in a way that: (1) is noninvasive, requiring only relatively small and isolated changes to the original source code, (2) does not significantly reduce performance, (3) is not time-consuming or confusing for a model developer to implement, (4) can very easily be updated to accommodate new versions of a given process model and (5) does not shift the burden of providing model interoperability to the model developers. In tackling these design challenges, model framework developers have learned that the best solution is to provide each model with a simple, standardized interface, i.e. a set of standardized functions that make the model: (1) fully-controllable by a caller (e.g. a model framework) and (2) self-describing with standardized metadata. Model control functions are separate functions that allow a caller to initialize the model, advance the model's state variables in time and finalize the model. Model description functions allow a caller to retrieve detailed information on the model's input and output variables, its computational grid and its timestepping scheme. If the caller is a modeling framework, it can use the self description functions to learn about each process model in a collection to be coupled and then automatically call framework service components (e.g. regridders
DEFF Research Database (Denmark)
Vangsgaard, Anna Katrine; Mutlu, Ayten Gizem; Gernaey, Krist
2013-01-01
-up. RESULTS: A model was calibrated using a step-wise procedure customized for the specific needs of the system. The important steps in the procedure were initialization, steady-state and dynamic calibration, and validation. A fast and effective initialization approach was developed to approximate pseudo...... screening of the parameter space proposed by Sin et al. (2008) - to find the best fit of the model to dynamic data. Finally, the calibrated model was validated with an independent data set. CONCLUSION: The presented calibration procedure is the first customized procedure for this type of system...... and is expected to contribute to achieve a fast and effective model calibration, an important enabling tool for various biochemical engineering design, control and operation problems....
A multi-scale model for describing cancer-therapeutic transport in the human lung
Erbertseder, Karin Maria
2012-01-01
This thesis proposes a multi-scale model for describing cancer-therapeutic transport in the human lung. The developed multi-scale model represents flow, transport and reaction processes: in the pulmonary macrocirculation on the organ scale, in the capillary bed around an alveolus, in the surrounding pulmonary tissue and in the tumor on the tissue scale, and in the tumor cell population and in the single cancer cells on the cells scale. The model concept is specialized for an alveolar cell car...
Energy Technology Data Exchange (ETDEWEB)
Cimpoesu, Dorin, E-mail: cdorin@uaic.ro; Stoleriu, Laurentiu; Stancu, Alexandru [Department of Physics, Alexandru Ioan Cuza University of Iasi, Iasi 700506 (Romania)
2013-12-14
We propose a generalized Stoner-Wohlfarth (SW) type model to describe various experimentally observed angular dependencies of the switching field in non-single-domain magnetic particles. Because the nonuniform magnetic states are generally characterized by complicated spin configurations with no simple analytical description, we maintain the macrospin hypothesis and we phenomenologically include the effects of nonuniformities only in the anisotropy energy, preserving as much as possible the elegance of SW model, the concept of critical curve and its geometric interpretation. We compare the results obtained with our model with full micromagnetic simulations in order to evaluate the performance and limits of our approach.
PARAMETER ESTIMATION IN BREAD BAKING MODEL
Hadiyanto Hadiyanto; AJB van Boxtel
2012-01-01
Bread product quality is highly dependent to the baking process. A model for the development of product quality, which was obtained by using quantitative and qualitative relationships, was calibrated by experiments at a fixed baking temperature of 200°C alone and in combination with 100 W microwave powers. The model parameters were estimated in a stepwise procedure i.e. first, heat and mass transfer related parameters, then the parameters related to product transformations and finally pro...
On parameter estimation in deformable models
DEFF Research Database (Denmark)
Fisker, Rune; Carstensen, Jens Michael
1998-01-01
Deformable templates have been intensively studied in image analysis through the last decade, but despite its significance the estimation of model parameters has received little attention. We present a method for supervised and unsupervised model parameter estimation using a general Bayesian...... method is based on a modified version of the EM algorithm. Experimental results for a deformable template used for textile inspection are presented...
Cosmological models with constant deceleration parameter
Energy Technology Data Exchange (ETDEWEB)
Berman, M.S.; de Mello Gomide, F.
1988-02-01
Berman presented elsewhere a law of variation for Hubble's parameter that yields constant deceleration parameter models of the universe. By analyzing Einstein, Pryce-Hoyle and Brans-Dicke cosmologies, we derive here the necessary relations in each model, considering a perfect fluid.
Directory of Open Access Journals (Sweden)
Jonathan R Karr
2015-05-01
Full Text Available Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.
Hoffman, Alexander F.; Spivak, Charles E.; Lupica, Carl R.
2016-01-01
Fast-scan cyclic voltammetry (FSCV) using carbon fiber electrodes is widely used to rapidly monitor changes in dopamine (DA) levels in vitro and in vivo. Current analytical approaches utilize parameters such as peak oxidation current amplitude and decay times to estimate release and uptake processes, respectively. However, peak amplitude changes are often observed with uptake inhibitors, thereby confounding the interpretation of these parameters. To overcome this limitation, we demonstrate that a simple, 5 parameter, two compartment model mathematically describes DA signals as a balance of release (r/ke) and uptake (ku), summed with adsorption (kads and kdes) of DA to the carbon electrode surface. Using non-linear regression, we demonstrate that our model precisely describes measured DA signals obtained in brain slice recordings. The parameters extracted from these curves were then validated using pharmacological manipulations that selectively alter vesicular release or DA transporter (DAT)-mediated uptake. Manipulation of DA release through altered Ca2+/Mg2+ ratio or tetrodotoxin (TTX), reduced the release parameter with no effect on the uptake parameter. The DAT inhibitors methylenedioxypyrovalerone (MDPV), cocaine, and nomifensine significantly reduced uptake and increased vesicular DA release. In contrast, a low concentration of amphetamine reduced uptake but had no effect on DA release. Finally, the kappa-opioid receptor (KOR) agonist U50,488 significantly reduced vesicular DA release but had no effect on uptake. Together, these data demonstrate a novel analytical approach to distinguish the effects of manipulations on DA release or uptake that can be used to interpret FSCV data. PMID:27018734
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.
Greco, Cristina; Yiang, Ying; Kremer, Kurt; Chen, Jeff; Daoulas, Kostas
Polymer liquid crystals, apart from traditional applications as high strength materials, are important for new technologies, e.g. Organic Electronics. Their studies often invoke mesoscale models, parameterized to reproduce thermodynamic properties of the real material. Such top-down strategies require advanced simulation techniques, predicting accurately the thermodynamics of mesoscale models as a function of characteristic features and parameters. Here a recently developed model describing nematic polymers as worm-like chains interacting with soft directional potentials is considered. We present a special thermodynamic integration scheme delivering free energies in particle-based Monte Carlo simulations of this model, avoiding thermodynamic singularities. Conformational and structural properties, as well as Helmholtz free energies are reported as a function of interaction strength. They are compared with state-of-art SCF calculations invoking a continuum analog of the same model, demonstrating the role of liquid-packing and fluctuations.
Energy Technology Data Exchange (ETDEWEB)
Belousov, V. I.; Ezhela, V. V.; Kuyanov, Yu. V., E-mail: Yu.Kuyanov@gmail.com; Tkachenko, N. P. [Institute for High Energy Physics, National Research Center Kurchatov Institute, COMPAS Group (Russian Federation)
2015-12-15
The experience of using the dynamic atlas of the experimental data and mathematical models of their description in the problems of adjusting parametric models of observable values depending on kinematic variables is presented. The functional possibilities of an image of a large number of experimental data and the models describing them are shown by examples of data and models of observable values determined by the amplitudes of elastic scattering of hadrons. The Internet implementation of an interactive tool DaMoScope and its interface with the experimental data and codes of adjusted parametric models with the parameters of the best description of data are schematically shown. The DaMoScope codes are freely available.
Numerical model describing optimization of fibres winding process on open and closed frame
Petrů, M.; Mlýnek, J.; Martinec, T.
2016-08-01
This article discusses a numerical model describing optimization of fibres winding process on open and closed frame. The quality production of said type of composite frame depends primarily on the correct winding of fibers on a polyurethane core. It is especially needed to ensure the correct angles of the fibers winding on the polyurethane core and the homogeneity of individual winding layers. The article describes mathematical model for use an industrial robot in filament winding and how to calculate the trajectory of the robot. When winding fibers on the polyurethane core which is fastened to the robot-end-effector so that during the winding process goes through a fibre-processing head on the basis of the suitably determined robot-end-effector trajectory. We use the described numerical model and matrix calculus to enumerate the trajectory of the robot-end-effector to determine the desired passage of the frame through the fibre-processing head. The calculation of the trajectory was programmed in the Delphi development environment. Relations of the numerical model are important for use a real solving of the passage of a polyurethane core through fibre-processing head.
Energy Technology Data Exchange (ETDEWEB)
Ibragimov, Nail H [Department of Mathematics and Science, Blekinge Institute of Technology, SE-371 79 Karlskrona (Sweden); Meleshko, Sergey V [School of Mathematics, Institute of Science, Suranaree University of Technology, Nakhon Ratchasima 30000 (Thailand); Rudenko, Oleg V, E-mail: nib@bth.se, E-mail: sergey@math.sut.ac.th, E-mail: rudenko@acs366.phys.msu.ru [Department of Physics, Moscow State University, 119991 Moscow (Russian Federation)
2011-08-05
The paper deals with an evolutionary integro-differential equation describing nonlinear waves. A particular choice of the kernel in the integral leads to well-known equations such as the Khokhlov-Zabolotskaya equation, the Kadomtsev-Petviashvili equation and others. Since the solutions of these equations describe many physical phenomena, the analysis of the general model studied in this paper is important. One of the methods for obtaining solutions of differential equations is provided by the Lie group analysis. However, this method is not applicable to integro-differential equations. Therefore, we discuss new approaches developed in modern group analysis and apply them to the general model considered in this paper. Reduced equations and exact solutions are also presented.
Trait Characteristics of Diffusion Model Parameters
Directory of Open Access Journals (Sweden)
Anna-Lena Schubert
2016-07-01
Full Text Available Cognitive modeling of response time distributions has seen a huge rise in popularity in individual differences research. In particular, several studies have shown that individual differences in the drift rate parameter of the diffusion model, which reflects the speed of information uptake, are substantially related to individual differences in intelligence. However, if diffusion model parameters are to reflect trait-like properties of cognitive processes, they have to qualify as trait-like variables themselves, i.e., they have to be stable across time and consistent over different situations. To assess their trait characteristics, we conducted a latent state-trait analysis of diffusion model parameters estimated from three response time tasks that 114 participants completed at two laboratory sessions eight months apart. Drift rate, boundary separation, and non-decision time parameters showed a great temporal stability over a period of eight months. However, the coefficients of consistency and reliability were only low to moderate and highest for drift rate parameters. These results show that the consistent variance of diffusion model parameters across tasks can be regarded as temporally stable ability parameters. Moreover, they illustrate the need for using broader batteries of response time tasks in future studies on the relationship between diffusion model parameters and intelligence.
Parameter identification in the logistic STAR model
DEFF Research Database (Denmark)
Ekner, Line Elvstrøm; Nejstgaard, Emil
We propose a new and simple parametrization of the so-called speed of transition parameter of the logistic smooth transition autoregressive (LSTAR) model. The new parametrization highlights that a consequence of the well-known identification problem of the speed of transition parameter is that th......We propose a new and simple parametrization of the so-called speed of transition parameter of the logistic smooth transition autoregressive (LSTAR) model. The new parametrization highlights that a consequence of the well-known identification problem of the speed of transition parameter...
Why simple regression models work so well describing 'risk behaviors' in the USA
Wallace, R.; R Fullilove
1999-01-01
The generalized anger created by individual experience of marginalization in the USA makes violent behavior frequent enough to become a 'typical' symbol, in the information-theoretic sense, for use in communicating along the damaged social networks of oppressed communities. Simple regression models relating violence and other risk behaviors to indices of relative deprivation emerge, after some mathematical development, as a natural consequence of this underlying dynamic, described elegantly b...
Self-Organizing Two-Temperature Ising Model Describing Human Segregation
Ódor, Géza
A two-temperature Ising-Schelling model is introduced and studied for describing human segregation. The self-organized Ising model with Glauber kinetics simulated by Müller et al. exhibits a phase transition between segregated and mixed phases mimicking the change of tolerance (local temperature) of individuals. The effect of external noise is considered here as a second temperature added to the decision of individuals who consider a change of accommodation. A numerical evidence is presented for a discontinuous phase transition of the magnetization.
Can percolation model describe the evolution of mechanical properties of compacts of binary systems?
Evesque, Pierre; Busignies, Virginie; Porion, Patrice; Leclerc, Bernard; Tchoreloff, Pierre
2009-06-01
In pharmaceutical field, the percolation theory is used to describe the change of tablet's properties with the relative density. It defines critical tablet densities from which the mechanical properties start to change. The exponent in the law is expected to be universal for a mechanical property and numerical values are proposed in the literature. In this work, the percolation model was applied to the tensile strength and the reduced modulus of elasticity of three compacted pharmaceutical excipients. This work showed that the exponent seems not universal and that the model must be used carefully.
NeamÅ£u, Mihaela; Stoian, Dana; Navolan, Dan Bogdan
2014-12-01
In the present paper we provide a mathematical model that describe the hypothalamus-pituitary-thyroid axis in autoimmune (Hashimoto's) thyroiditis. Since there is a spatial separation between thyroid and pituitary gland in the body, time is needed for transportation of thyrotropin and thyroxine between the glands. Thus, the distributed time delays are considered as both weak and Dirac kernels. The delayed model is analyzed regarding the stability and bifurcation behavior. The last part contains some numerical simulations to illustrate the effectiveness of our results and conclusions.
A Network Model to Describe the Terminal Differentiation of B Cells
Méndez, Akram; Mendoza, Luis
2016-01-01
Terminal differentiation of B cells is an essential process for the humoral immune response in vertebrates and is achieved by the concerted action of several transcription factors in response to antigen recognition and extracellular signals provided by T-helper cells. While there is a wealth of experimental data regarding the molecular and cellular signals involved in this process, there is no general consensus regarding the structure and dynamical properties of the underlying regulatory network controlling this process. We developed a dynamical model of the regulatory network controlling terminal differentiation of B cells. The structure of the network was inferred from experimental data available in the literature, and its dynamical behavior was analyzed by modeling the network both as a discrete and a continuous dynamical systems. The steady states of these models are consistent with the patterns of activation reported for the Naive, GC, Mem, and PC cell types. Moreover, the models are able to describe the patterns of differentiation from the precursor Naive to any of the GC, Mem, or PC cell types in response to a specific set of extracellular signals. We simulated all possible single loss- and gain-of-function mutants, corroborating the importance of Pax5, Bcl6, Bach2, Irf4, and Blimp1 as key regulators of B cell differentiation process. The model is able to represent the directional nature of terminal B cell differentiation and qualitatively describes key differentiation events from a precursor cell to terminally differentiated B cells. PMID:26751566
Energy Technology Data Exchange (ETDEWEB)
Moro, Erik A [Los Alamos National Laboratory; Puckett, Anthony D [Los Alamos National Laboratory; Todd, Michael D [UCSD
2011-01-24
The intensity distribution of a transmission from a single mode optical fiber is often approximated using a Gaussian-shaped curve. While this approximation is useful for some applications such as fiber alignment, it does not accurately describe transmission behavior off the axis of propagation. In this paper, another model is presented, which describes the intensity distribution of the transmission from a single mode optical fiber. A simple experimental setup is used to verify the model's accuracy, and agreement between model and experiment is established both on and off the axis of propagation. Displacement sensor designs based on the extrinsic optical lever architecture are presented. The behavior of the transmission off the axis of propagation dictates the performance of sensor architectures where large lateral offsets (25-1500 {micro}m) exist between transmitting and receiving fibers. The practical implications of modeling accuracy over this lateral offset region are discussed as they relate to the development of high-performance intensity modulated optical displacement sensors. In particular, the sensitivity, linearity, resolution, and displacement range of a sensor are functions of the relative positioning of the sensor's transmitting and receiving fibers. Sensor architectures with high combinations of sensitivity and displacement range are discussed. It is concluded that the utility of the accurate model is in its predicative capability and that this research could lead to an improved methodology for high-performance sensor design.
Parameter Estimation of Partial Differential Equation Models
Xun, Xiaolei
2013-09-01
Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown and need to be estimated from the measurements of the dynamic system in the presence of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from long-range infrared light detection and ranging data. Supplementary materials for this article are available online. © 2013 American Statistical Association.
Directory of Open Access Journals (Sweden)
H. Tonhati
2010-02-01
Full Text Available The objectives of this study were to estimate (covariance functions for additive genetic and permanent environmental effects, as well as the genetic parameters for milk yield over multiple parities, using random regressions models (RRM. Records of 4,757 complete lactations of Murrah breed buffaloes from 12 herds were analyzed. Ages at calving were between 2 and 11 years. The model included the additive genetic and permanent environmental random effects and the fixed effects of contemporary groups (herd, year and calving season and milking frequency (1 or 2. A cubic regression on Legendre orthogonal polynomials of ages was used to model the mean trend. The additive genetic and permanent environmental effects were modeled by Legendre orthogonal polynomials. Residual variances were considered homogenous or heterogeneous, modeled through variance functions or step functions with 5, 7 or 10 classes. Results from Akaike’s and Schwarz’s Bayesian information criterion indicated that a RRM considering a third order polynomial for the additive genetic and permanent environmental effects and a step function with 5 classes for residual variances fitted best. Heritability estimates obtained by this model varied from 0.10 to 0.28. Genetic correlations were high between consecutive ages, but decreased when intervals between ages increased
Monte Carlo simulation of Prussian blue analogs described by Heisenberg ternary alloy model
Yüksel, Yusuf
2015-11-01
Within the framework of Monte Carlo simulation technique, we simulate magnetic behavior of Prussian blue analogs based on Heisenberg ternary alloy model. We present phase diagrams in various parameter spaces, and we compare some of our results with those based on Ising counterparts. We clarify the variations of transition temperature and compensation phenomenon with mixing ratio of magnetic ions, exchange interactions, and exchange anisotropy in the present ferro-ferrimagnetic Heisenberg system. According to our results, thermal variation of the total magnetization curves may exhibit N, L, P, Q, R type behaviors based on the Néel classification scheme.
Application of lumped-parameter models
Energy Technology Data Exchange (ETDEWEB)
Ibsen, Lars Bo; Liingaard, M.
2006-12-15
This technical report concerns the lumped-parameter models for a suction caisson with a ratio between skirt length and foundation diameter equal to 1/2, embedded into an viscoelastic soil. The models are presented for three different values of the shear modulus of the subsoil. Subsequently, the assembly of the dynamic stiffness matrix for the foundation is considered, and the solution for obtaining the steady state response, when using lumped-parameter models is given. (au)
PARAMETER ESTIMATION IN BREAD BAKING MODEL
Directory of Open Access Journals (Sweden)
Hadiyanto Hadiyanto
2012-05-01
Full Text Available Bread product quality is highly dependent to the baking process. A model for the development of product quality, which was obtained by using quantitative and qualitative relationships, was calibrated by experiments at a fixed baking temperature of 200°C alone and in combination with 100 W microwave powers. The model parameters were estimated in a stepwise procedure i.e. first, heat and mass transfer related parameters, then the parameters related to product transformations and finally product quality parameters. There was a fair agreement between the calibrated model results and the experimental data. The results showed that the applied simple qualitative relationships for quality performed above expectation. Furthermore, it was confirmed that the microwave input is most meaningful for the internal product properties and not for the surface properties as crispness and color. The model with adjusted parameters was applied in a quality driven food process design procedure to derive a dynamic operation pattern, which was subsequently tested experimentally to calibrate the model. Despite the limited calibration with fixed operation settings, the model predicted well on the behavior under dynamic convective operation and on combined convective and microwave operation. It was expected that the suitability between model and baking system could be improved further by performing calibration experiments at higher temperature and various microwave power levels. Abstrak PERKIRAAN PARAMETER DALAM MODEL UNTUK PROSES BAKING ROTI. Kualitas produk roti sangat tergantung pada proses baking yang digunakan. Suatu model yang telah dikembangkan dengan metode kualitatif dan kuantitaif telah dikalibrasi dengan percobaan pada temperatur 200oC dan dengan kombinasi dengan mikrowave pada 100 Watt. Parameter-parameter model diestimasi dengan prosedur bertahap yaitu pertama, parameter pada model perpindahan masa dan panas, parameter pada model transformasi, dan
Tube-Load Model Parameter Estimation for Monitoring Arterial Hemodynamics
Directory of Open Access Journals (Sweden)
Guanqun eZhang
2011-11-01
Full Text Available A useful model of the arterial system is the uniform, lossless tube with parametric load. This tube-load model is able to account for wave propagation and reflection (unlike lumped-parameter models such as the Windkessel while being defined by only a few parameters (unlike comprehensive distributed-parameter models. As a result, the parameters may be readily estimated by accurate fitting of the model to available arterial pressure and flow waveforms so as to permit improved monitoring of arterial hemodynamics. In this paper, we review tube-load model parameter estimation techniques that have appeared in the literature for monitoring wave reflection, large artery compliance, pulse transit time, and central aortic pressure. We begin by motivating the use of the tube-load model for parameter estimation. We then describe the tube-load model, its assumptions and validity, and approaches for estimating its parameters. We next summarize the various techniques and their experimental results while highlighting their advantages over conventional techniques. We conclude the review by suggesting future research directions and describing potential applications.
Tube-Load Model Parameter Estimation for Monitoring Arterial Hemodynamics
Zhang, Guanqun; Hahn, Jin-Oh; Mukkamala, Ramakrishna
2011-01-01
A useful model of the arterial system is the uniform, lossless tube with parametric load. This tube-load model is able to account for wave propagation and reflection (unlike lumped-parameter models such as the Windkessel) while being defined by only a few parameters (unlike comprehensive distributed-parameter models). As a result, the parameters may be readily estimated by accurate fitting of the model to available arterial pressure and flow waveforms so as to permit improved monitoring of arterial hemodynamics. In this paper, we review tube-load model parameter estimation techniques that have appeared in the literature for monitoring wave reflection, large artery compliance, pulse transit time, and central aortic pressure. We begin by motivating the use of the tube-load model for parameter estimation. We then describe the tube-load model, its assumptions and validity, and approaches for estimating its parameters. We next summarize the various techniques and their experimental results while highlighting their advantages over conventional techniques. We conclude the review by suggesting future research directions and describing potential applications. PMID:22053157
The Transfer Function Model as a Tool to Study and Describe Space Weather Phenomena
Porter, Hayden S.; Mayr, Hans G.; Bhartia, P. K. (Technical Monitor)
2001-01-01
The Transfer Function Model (TFM) is a semi-analytical, linear model that is designed especially to describe thermospheric perturbations associated with magnetic storms and substorm. activity. It is a multi-constituent model (N2, O, He H, Ar) that accounts for wind induced diffusion, which significantly affects not only the composition and mass density but also the temperature and wind fields. Because the TFM adopts a semianalytic approach in which the geometry and temporal dependencies of the driving sources are removed through the use of height-integrated Green's functions, it provides physical insight into the essential properties of processes being considered, which are uncluttered by the accidental complexities that arise from particular source geometrie and time dependences. Extending from the ground to 700 km, the TFM eliminates spurious effects due to arbitrarily chosen boundary conditions. A database of transfer functions, computed only once, can be used to synthesize a wide range of spatial and temporal sources dependencies. The response synthesis can be performed quickly in real-time using only limited computing capabilities. These features make the TFM unique among global dynamical models. Given these desirable properties, a version of the TFM has been developed for personal computers (PC) using advanced platform-independent 3D visualization capabilities. We demonstrate the model capabilities with simulations for different auroral sources, including the response of ducted gravity waves modes that propagate around the globe. The thermospheric response is found to depend strongly on the spatial and temporal frequency spectra of the storm. Such varied behavior is difficult to describe in statistical empirical models. To improve the capability of space weather prediction, the TFM thus could be grafted naturally onto existing statistical models using data assimilation.
The mathematical model that describes the periodic spouting of a geyser induced by boiling
Kagami, Hiroyuki
2017-04-01
We have derived and modified the dynamical model of a geyser induced by gas inflow and regular or irregular spouting dynamics of geysers induced by gas inflow has been reproduced by the model. On the other hand, though we have derived the dynamical model of a geyser induced by boiling, periodic change between the spouting state and the pause state has not been adequately modeled by the model. In this connection, concerning a geyser induced by gas inflow we have proposed the model as described below. Because pressure in the spouting tube decreases obeying to the Bernoulli's theorem when the spouting state begins and water in the spouting tube begins to flow, inflow of groundwater into the spouting tube occurs. When the amount of this inflow reaches a certain amount, the spouting state transforms to the pause state. In this study, by applying this idea to the dynamical model of a geyser induced by boiling, the periodic change between the spouting state and the pause state could be reappeared. As a result, the whole picture of the spouting mechanism of a geyser induced by boiling became clear. This research results would give hints on engineering repair in order to prevent the weakening or the depletion of the geyser. And this study would be also useful for protection of geysers as tourism and environmental resources.
Assessment of diffusion models to describe drying of roof tiles using generalized coordinates
Farias, Vera S. O.; da Silva, Wilton Pereira; e Silva, Cleide M. D. P. S.; da Silva Júnior, Aluízio Freire; de Farias Aires, Juarez Everton; Rocha, Vicente P. T.
2016-07-01
This article aims to study the mass transient diffusion in solids with an arbitrary shape, highlighting boundary condition of the third kind. To this end, the numerical formalism to discretize the transient 3D diffusion equation written in generalized coordinates is presented. For the discretization, it was used the finite volume method with a fully implicit formulation. An application to drying of roof tiles has been done. Three models were used to describe the drying process: (1) the volume V and the effective mass diffusivity D are considered constant for the boundary condition of the first kind; (2) V and D are considered constant for the boundary condition of the third kind and (3) V and D are considered variable for the boundary condition of the third kind. For all models, the convective mass transfer coefficient h was considered constant. The analyses of the results obtained make it possible to affirm that the model 3 describes the drying process better than the other models.
A bottom-up model to describe consumers’ preferences towards late season peaches
Energy Technology Data Exchange (ETDEWEB)
Groot, E.; Albisu, L.M.
2015-07-01
Peaches are consumed in Mediterranean countries since ancient times. Nowadays there are few areas in Europe that produce peaches with Protected Designation of Origin (PDO), and the Calanda area is one of them. The aim of this work is to describe consumers’ preferences towards late season PDO Calanda peaches in the city of Zaragoza, Spain, by a bottom-up model. The bottom-up model proves greater amount of information than top-down models. In this approach it is estimated one utility function per consumer. Thus, it is not necessary to make assumptions about preference distributions and correlations across respondents. It was observed that preference distributions were neither normal nor independently distributed. If those preferences were estimated by top-down models, conclusions would be biased. This paper also explores a new way to describe preferences through individual utility functions. Results show that the largest behavioural group gathered origin sensitive consumers. Their utility increased if the peaches were produced in the Calanda area and, especially, when peaches had the PDO Calanda brand. In sequence, the second most valuable attribute for consumers was the price. Peach size and packaging were not so important on purchase choice decision. Nevertheless, it is advisable to avoid trading smallest size peaches (weighting around 160 g/fruit). Traders also have to be careful by using active packaging. It was found that a group of consumers disliked this kind of product, probably, because they perceived it as less natural. (Author)
Development of a model describing virus removal process in an activated sludge basin
Energy Technology Data Exchange (ETDEWEB)
Kim, T.; Shiragami, N. Unno, H. [Tokyo Institute of Technology, Tokyo (Japan)
1995-06-20
The virus removal process from the liquid phase in an activated sludge basin possibly consists of physicochemical processes, such as adsorption onto sludge flocs, biological processes such as microbial predating and inactivation by virucidal components excreted by microbes. To describe properly the virus behavior in an activated sludge basin, a simple model is proposed based on the experimental data obtained using a poliovirus type 1. A three-compartments model, which include the virus in the liquid phase and in the peripheral and inner regions of sludge flocs is employed. By using the model, the Virus removal process was successfully simulated to highlight the implication of its distribution in the activated sludge basin. 17 refs., 8 figs.
Sabio, E.; Zamora, F.; González-García, C. M.; Ledesma, B.; Álvarez-Murillo, A.; Román, S.
2016-12-01
In this work, the adsorption kinetics of p-nitrophenol (PNP) onto several commercial activated carbons (ACs) with different textural and geometrical characteristics was studied. For this aim, a homogeneous diffusion solid model (HDSM) was used, which does take the adsorbent shape into account. The HDSM was solved by means of the finite element method (FEM) using the commercial software COMSOL. The different kinetic patterns observed in the experiments carried out can be described by the developed model, which shows that the sharp drop of adsorption rate observed in some samples is caused by the formation of a concentration wave. The model allows one to visualize the changes in concentration taking place in both liquid and solid phases, which enables us to link the kinetic behaviour with the main features of the carbon samples.
Fitting mathematical models to describe the rheological behaviour of chocolate pastes
Barbosa, Carla; Diogo, Filipa; Alves, M. Rui
2016-06-01
The flow behavior is of utmost importance for the chocolate industry. The objective of this work was to study two mathematical models, Casson and Windhab models that can be used to fit chocolate rheological data and evaluate which better infers or previews the rheological behaviour of different chocolate pastes. Rheological properties (viscosity, shear stress and shear rates) were obtained with a rotational viscometer equipped with a concentric cylinder. The chocolate samples were white chocolate and chocolate with varying percentages in cacao (55%, 70% and 83%). The results showed that the Windhab model was the best to describe the flow behaviour of all the studied samples with higher determination coefficients (r2 > 0.9).
A simple model to describe intrinsic stellar noise for exoplanet detection around red giants
North, Thomas S H; Gilliland, Ronald L; Huber, Daniel; Campante, Tiago L; Handberg, Rasmus; Lund, Mikkel N; Veras, Dimitri; Kuszlewicz, James S; Farr, Will M
2016-01-01
In spite of the huge advances in exoplanet research provided by the NASA Kepler Mission, there remain only a small number of transit detections around evolved stars. Here we present a reformulation of the noise properties of red-giant stars, where the intrinsic stellar granulation, and the stellar oscillations described by asteroseismology play a key role. The new noise model is a significant improvement on the current Kepler results for evolved stars. Our noise model may be used to help understand planet detection thresholds for the ongoing K2 and upcoming TESS missions, and serve as a predictor of stellar noise for these missions. As an application of our noise model, we explore the minimum detectable planet radii for red giant stars, and find that Neptune sized planets should be detectable around low luminosity red giant branch stars.
Exploring the use of fuzzy logic models to describe the relation between SBP and RR values.
Gouveia, Sónia; Brás, Susana
2012-01-01
In this work, fuzzy logic based models are used to describe the relation between systolic blood pressure (SBP) and tachogram (RR) values as a function of the SBP level. The applicability of these methods is tested using real data in Lying (L) and Standing (S) conditions and generated surrogate data. The results indicate that fuzzy models exhibit a similar performance in both conditions, and their performance is significantly higher with real data than with surrogate data. These results point out the potential of a fuzzy logic approach to model properly the relation between SBP and RR values. As a future work, it remains to assess the clinical impact of these findings and inherent repercussion on the estimation of time domain baroreflex sensitivity indices.
Asymptotic behavior of nonlinear semigroup describing a model of selective cell growth regulation.
Arino, O; Kimmel, M
1991-01-01
A new scheme of regulation of cell population growth is considered, called the selective growth regulation. The principle is that cells are withdrawn from proliferation depending on their contents of certain biochemical species. The dynamics of the cell population structured by the contents of this species is described by the functional integral equation model, previously introduced by the authors. The solutions of the model equations generate a semigroup of nonlinear positive operators. The main problem solved in this paper concerns stability of the equilibria of the model. This requires stating and proving of an original abstract result on the spectral radius of a perturbation of a semigroup of positive linear operators. Biological applications are discussed.
A simple model to describe intrinsic stellar noise for exoplanet detection around red giants
North, Thomas S. H.; Chaplin, William J.; Gilliland, Ronald L.; Huber, Daniel; Campante, Tiago L.; Handberg, Rasmus; Lund, Mikkel N.; Veras, Dimitri; Kuszlewicz, James S.; Farr, Will M.
2017-02-01
In spite of the huge advances in exoplanet research provided by the NASA Kepler Mission, there remain only a small number of transit detections around evolved stars. Here, we present a reformulation of the noise properties of red-giant stars, where the intrinsic stellar granulation and the stellar oscillations described by asteroseismology play a key role. The new noise model is a significant improvement on the current Kepler results for evolved stars. Our noise model may be used to help understand planet detection thresholds for the ongoing K2 and upcoming TESSmissions, and serve as a predictor of stellar noise for these missions. As an application of our noise model, we explore the minimum detectable planet radii for red giant stars, and find that Neptune-sized planets should be detectable around low-luminosity red giant branch stars.
Ordinal regression models to describe tourist satisfaction with Sintra's world heritage
Mouriño, Helena
2013-10-01
In Tourism Research, ordinal regression models are becoming a very powerful tool in modelling the relationship between an ordinal response variable and a set of explanatory variables. In August and September 2010, we conducted a pioneering Tourist Survey in Sintra, Portugal. The data were obtained by face-to-face interviews at the entrances of the Palaces and Parks of Sintra. The work developed in this paper focus on two main points: tourists' perception of the entrance fees; overall level of satisfaction with this heritage site. For attaining these goals, ordinal regression models were developed. We concluded that tourist's nationality was the only significant variable to describe the perception of the admission fees. Also, Sintra's image among tourists depends not only on their nationality, but also on previous knowledge about Sintra's World Heritage status.
Gay, Guillaume; Courtheoux, Thibault; Reyes, Céline; Tournier, Sylvie; Gachet, Yannick
2012-03-19
In fission yeast, erroneous attachments of spindle microtubules to kinetochores are frequent in early mitosis. Most are corrected before anaphase onset by a mechanism involving the protein kinase Aurora B, which destabilizes kinetochore microtubules (ktMTs) in the absence of tension between sister chromatids. In this paper, we describe a minimal mathematical model of fission yeast chromosome segregation based on the stochastic attachment and detachment of ktMTs. The model accurately reproduces the timing of correct chromosome biorientation and segregation seen in fission yeast. Prevention of attachment defects requires both appropriate kinetochore orientation and an Aurora B-like activity. The model also reproduces abnormal chromosome segregation behavior (caused by, for example, inhibition of Aurora B). It predicts that, in metaphase, merotelic attachment is prevented by a kinetochore orientation effect and corrected by an Aurora B-like activity, whereas in anaphase, it is corrected through unbalanced forces applied to the kinetochore. These unbalanced forces are sufficient to prevent aneuploidy.
Development of a model and computer code to describe solar grade silicon production processes
Gould, R. K.; Srivastava, R.
1979-01-01
Two computer codes were developed for describing flow reactors in which high purity, solar grade silicon is produced via reduction of gaseous silicon halides. The first is the CHEMPART code, an axisymmetric, marching code which treats two phase flows with models describing detailed gas-phase chemical kinetics, particle formation, and particle growth. It can be used to described flow reactors in which reactants, mix, react, and form a particulate phase. Detailed radial gas-phase composition, temperature, velocity, and particle size distribution profiles are computed. Also, deposition of heat, momentum, and mass (either particulate or vapor) on reactor walls is described. The second code is a modified version of the GENMIX boundary layer code which is used to compute rates of heat, momentum, and mass transfer to the reactor walls. This code lacks the detailed chemical kinetics and particle handling features of the CHEMPART code but has the virtue of running much more rapidly than CHEMPART, while treating the phenomena occurring in the boundary layer in more detail.
Lueking, Angela D; Wang, Cheng-Yu; Sircar, Sarmishtha; Malencia, Christopher; Wang, Hao; Li, Jing
2016-03-14
Flexible gate-opening metal organic frameworks (GO-MOFs) expand or contract to minimize the overall free energy of the system upon accommodation of an adsorbate. The thermodynamics of the GO process are well described by a number of models, but the kinetics of the process are relatively unexplored. A flexible GO-MOF, RPM3-Zn, exhibits a significant induction period for opening by N2 and Ar at low temperatures, both above and below the GO pressure. A similar induction period is not observed for H2 or O2 at comparable pressures and temperatures, suggesting the rate of opening is strongly influenced by the gas-surface interaction rather than an external stress. The induction period leads to severe mass transfer limitations for adsorption and over-prediction of the gate-opening pressure. After review of a number of existing adsorption rate models, we find that none adequately describe the experimental rate data and similar timescales for diffusion and opening invalidate prior reaction-diffusion models. Statistically, the rate data are best described by a compressed exponential function. The resulting fitted parameters exceed the expectations for adsorption but fall within those expected for phase transition. By treating adsorption as a phase transition, we generalize the Avrami theory of phase transition kinetics to describe adsorption in both rigid and flexible hosts. The generalized theory is consistent with observed experimental trends relating to induction period, temperature, pressure, and gas-substrate interaction.
Statefinder parameters in two dark energy models
Panotopoulos, Grigoris
2007-01-01
The statefinder parameters ($r,s$) in two dark energy models are studied. In the first, we discuss in four-dimensional General Relativity a two fluid model, in which dark energy and dark matter are allowed to interact with each other. In the second model, we consider the DGP brane model generalized by taking a possible energy exchange between the brane and the bulk into account. We determine the values of the statefinder parameters that correspond to the unique attractor of the system at hand. Furthermore, we produce plots in which we show $s,r$ as functions of red-shift, and the ($s-r$) plane for each model.
Investigation of nonlinear models to describe long-term egg production in Japanese quail.
Narinc, Dogan; Karaman, Emre; Aksoy, Tulin; Firat, Mehmet Ziya
2013-06-01
In this study, long-term egg production was monitored in a Japanese quail flock, which had not undergone any genetic improvement, for 52 wk as of the age of sexual maturity. The study aimed to detect some traits with respect to egg production, to determine the cumulative hen-housed egg numbers, and to compare goodness of fit of different nonlinear models for the percentage of hen-day egg production. The mean age at first egg was 38.9 d and the age at 50% egg production was 45.3 d. The quail reached peak production at 15 wk of age (wk 9 of egg production period) when the percentage of hen-day egg production was found to be 94%. The cumulative hen-housed egg number for 52 wk as of the age of sexual maturity was 253.08. The monomolecular function, a nonsigmoid model, was used in the nonlinear regression analysis of the cumulative egg numbers. Parameters a, b, and c of the monomolecular model were estimated to be 461.70, 473.31, and 0.065, respectively. Gamma, McNally, Adams-Bell, and modified compartmental models, widely used in hens previously, were used in the nonlinear regression analysis of the percentages of hen-day egg production. The goodness of fit for these models was compared using the values of pseudo-R², Akaike's information criterion, and Bayesian information criterion. It was determined that all the models are adequate but that the Adams-Bell model displayed a slightly better fit for the percentage of hen-day egg production in Japanese quail than others.
Parameter Symmetry of the Interacting Boson Model
Shirokov, A M; Smirnov, Yu F; Shirokov, Andrey M.; Smirnov, Yu. F.
1998-01-01
We discuss the symmetry of the parameter space of the interacting boson model (IBM). It is shown that for any set of the IBM Hamiltonian parameters (with the only exception of the U(5) dynamical symmetry limit) one can always find another set that generates the equivalent spectrum. We discuss the origin of the symmetry and its relevance for physical applications.
A 3D model describing the initial structure of an artificial hydrological catchment
Maurer, T.; Schneider, A.; Buczko, U.; Gerke, H. H.
2009-04-01
The initial development stages of artificially constructed hydrologic catchments are characterized by the absence of vegetation, soil organic matter and soil horizons. This results in increased surface runoff and favors erosion processes that dominate the initial phase. Hydraulic conditions on artificial catchments thus are governed by rapidly changing surface structures as well as by the primary internal structural framework. Contemporary hydrological modeling does not consider any dynamic change of relevant structural features but rather assumes a stable, invariant landscape. The objective of this study was the digital visualization and quantitative description of the initial state and its early structural dynamics, exemplified for the small artificial hydrological catchment "Huehnerwasser" near Cottbus, Germany. Photogrammetric surveys of surface and internal structural units (clay basis liner) during the construction phase provided spatially and temporally resolved data for digital elevation models (DEM). Interpolated physical and chemical soil properties obtained at a borehole grid (e.g., texture) are used for the visualization of spatial distribution of relevant (hydraulic) parameters. The data are merged in a database and visualized in the 3D-GIS application GoCAD. The specific technological construction processes determines the internal structure of the artificial catchment. Resulting differences in bulk density and texture are supposed to have considerable impact on hydraulic properties. A structure generator program was implemented to reproduce the initial structure of the sediment layer as closely as possible. Results of the digital structure generation are checked with non-invasive geophysical measurements, on-site bore holes data and off-site 2D vertical spoil exploration. The accuracy of structure generator results will be compared with predictions of different interpolation methods. Thus, the structure model will serve as a basis for deriving the 3D
Refinement of a discontinuity-free edge-diffraction model describing focused wave fields.
Sedukhin, Andrey G
2010-03-01
Two equivalent forms of a refined discontinuity-free edge-diffraction model describing the structure of a stationary focused wave field are presented that are valid in the framework of the scalar Debye integral representation for a diffracted rotationally symmetric converging spherical wave of a limited yet not-too-low angular opening. The first form describes the field as the sum of a direct quasi-spherical wave and a plurality of edge quasi-conical waves of different orders, the optimum discontinuity-free angular spectrum functions of all the waves being dependent on the polar angle only. According to the second form, the focused field is fully characterized by only three components--the same quasi-spherical wave and two edge quasi-conical waves of the zero and first order, of which the optimum discontinuity-free angular spectrum functions are dependent on both the polar angle and the polar radius counted from the geometrical focus.
Wind Farm Decentralized Dynamic Modeling With Parameters
DEFF Research Database (Denmark)
Soltani, Mohsen; Shakeri, Sayyed Mojtaba; Grunnet, Jacob Deleuran;
2010-01-01
Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...
A Mulitivariate Statistical Model Describing the Compound Nature of Soil Moisture Drought
Manning, Colin; Widmann, Martin; Bevacqua, Emanuele; Maraun, Douglas; Van Loon, Anne; Vrac, Mathieu
2017-04-01
Soil moisture in Europe acts to partition incoming energy into sensible and latent heat fluxes, thereby exerting a large influence on temperature variability. Soil moisture is predominantly controlled by precipitation and evapotranspiration. When these meteorological variables are accumulated over different timescales, their joint multivariate distribution and dependence structure can be used to provide information of soil moisture. We therefore consider soil moisture drought as a compound event of meteorological drought (deficits of precipitation) and heat waves, or more specifically, periods of high Potential Evapotraspiration (PET). We present here a statistical model of soil moisture based on Pair Copula Constructions (PCC) that can describe the dependence amongst soil moisture and its contributing meteorological variables. The model is designed in such a way that it can account for concurrences of meteorological drought and heat waves and describe the dependence between these conditions at a local level. The model is composed of four variables; daily soil moisture (h); a short term and a long term accumulated precipitation variable (Y1 and Y_2) that account for the propagation of meteorological drought to soil moisture drought; and accumulated PET (Y_3), calculated using the Penman Monteith equation, which can represent the effect of a heat wave on soil conditions. Copula are multivariate distribution functions that allow one to model the dependence structure of given variables separately from their marginal behaviour. PCCs then allow in theory for the formulation of a multivariate distribution of any dimension where the multivariate distribution is decomposed into a product of marginal probability density functions and two-dimensional copula, of which some are conditional. We apply PCC here in such a way that allows us to provide estimates of h and their uncertainty through conditioning on the Y in the form h=h|y_1,y_2,y_3 (1) Applying the model to various
Yu, Huixin; van Erp, Nielka; Bins, Sander; Mathijssen, Ron H J; Schellens, Jan H M; Beijnen, Jos H; Steeghs, Neeltje; Huitema, Alwin D R
2017-03-01
Pazopanib is a multi-targeted anticancer tyrosine kinase inhibitor. This study was conducted to develop a population pharmacokinetic (popPK) model describing the complex pharmacokinetics of pazopanib in cancer patients. Pharmacokinetic data were available from 96 patients from three clinical studies. A multi-compartment model including (i) a complex absorption profile, (ii) the potential non-linear dose-concentration relationship and (iii) the potential long-term decrease in exposure was developed. A two-compartment model best described pazopanib pharmacokinetics. The absorption phase was modelled by two first-order processes: 36 % (relative standard error [RSE] 34 %) of the administered dose was absorbed with a relatively fast rate (0.4 h(-1) [RSE 31 %]); after a lag time of 1.0 h (RSE 6 %), the remaining dose was absorbed at a slower rate (0.1 h(-1) [RSE 28 %]). The relative bioavailability (rF) at a dose of 200 mg was fixed to 1. With an increasing dose, the rF was strongly reduced, which was modelled with an E max (maximum effect) model (E max was fixed to 1, the dose at half of maximum effect was estimated as 480 mg [RSE 23 %]). Interestingly, the plasma exposure to pazopanib also decreased over time, modelled on rF with a maximum magnitude of 50 % (RSE 27 %) and a first-order decay constant of 0.15 day(-1) (RSE 43 %). The inter-patient and intra-patient variability on rF were estimated as 36 % (RSE 16 %) and 75 % (RSE 22 %), respectively. A popPK model for pazopanib was developed that illustrated the complex absorption process, the non-linear dose-concentration relationship, the high inter-patient and intra-patient variability, and the first-order decay of pazopanib concentration over time. The developed popPK model can be used in clinical practice to screen covariates and guide therapeutic drug monitoring.
Heuijerjans, Ashley; Matikainen, Marko K.; Julkunen, Petro; Eliasson, Pernilla; Aspenberg, Per; Isaksson, Hanna
2015-01-01
Background Computational models of Achilles tendons can help understanding how healthy tendons are affected by repetitive loading and how the different tissue constituents contribute to the tendon’s biomechanical response. However, available models of Achilles tendon are limited in their description of the hierarchical multi-structural composition of the tissue. This study hypothesised that a poroviscoelastic fibre-reinforced model, previously successful in capturing cartilage biomechanical behaviour, can depict the biomechanical behaviour of the rat Achilles tendon found experimentally. Materials and Methods We developed a new material model of the Achilles tendon, which considers the tendon’s main constituents namely: water, proteoglycan matrix and collagen fibres. A hyperelastic formulation of the proteoglycan matrix enabled computations of large deformations of the tendon, and collagen fibres were modelled as viscoelastic. Specimen-specific finite element models were created of 9 rat Achilles tendons from an animal experiment and simulations were carried out following a repetitive tensile loading protocol. The material model parameters were calibrated against data from the rats by minimising the root mean squared error (RMS) between experimental force data and model output. Results and Conclusions All specimen models were successfully fitted to experimental data with high accuracy (RMS 0.42-1.02). Additional simulations predicted more compliant and soft tendon behaviour at reduced strain-rates compared to higher strain-rates that produce a stiff and brittle tendon response. Stress-relaxation simulations exhibited strain-dependent stress-relaxation behaviour where larger strains produced slower relaxation rates compared to smaller strain levels. Our simulations showed that the collagen fibres in the Achilles tendon are the main load-bearing component during tensile loading, where the orientation of the collagen fibres plays an important role for the tendon
Zhurbas, Nataliya; Kuzmina, Natalia; Lyzhkov, Dmitry; Izvekova, Yulia N.
2016-04-01
Interleaving models of pure thermohaline and baroclinic frontal zones of finite width are applied to describe intrusions at the fronts found in the upper part of the Deep Polar Water, the Eurasian basin, under stable-stable thermohaline stratification. It is assumed that differential mixing is the main mechanism of the intrusion formation. Different parameterizations of differential mixing (Merrryfield, 2002; Kuzmina et al., 2011) are used in the models. Important parameters of interleaving such as the growth rate, vertical scale, and slope of the most unstable modes are calculated. It is found that the interleaving model of a pure thermohaline front can satisfactory describe the important parameters of intrusions observed at a thermohaline, very low baroclinicity front in the Eurasian basin, just in accordance to Merryfield (2002) findings. In the case of baroclinic front, satisfactory agreement over all the interleaving parameters is found between the model calculations and observations provided that the vertical momentum diffusivity significantly exceeds the corresponding mass diffusivity. Under specific (reasonable) constraints of the vertical momentum diffusivity, the most unstable mode has a vertical scale approximately two-three times smaller than the vertical scale of the observed intrusions. A thorough discussion of the results is presented. References Kuzmina N., Rudels B., Zhurbas V., Stipa T. On the structure and dynamical features of intrusive layering in the Eurasian Basin in the Arctic Ocean. J. Geophys. Res., 2011, 116, C00D11, doi:10.1029/2010JC006920. Merryfield W. J. Intrusions in Double-Diffusively Stable Arctic Waters: Evidence for Differential mixing? J. Phys. Oceanogr., 2002, 32, 1452-1439.
Maurya, S. K.; Gupta, Y. K.
2012-08-01
A family of anisotropic fluid distributions is constructed using a space-time describing a family of charged perfect fluid distributions. The anisotropy parameter is taken to be twice the square of electric intensity used in the charged fluid distributions. As the anisotropy parameter (or the electric intensity) is zero at the centre and is monotonically increasing towards the pressure-free interface, we have utilized the anisotropic fluid distributions to create Boson-type neutron stars models which join smoothly to the Schwarzschild exterior metric. All the physical entities such as energy density, radial pressure, tangential pressure and velocity of sound are monotonically decreasing towards the surface. Different members of the above family are characterized by a positive integral number n. It is observed that the maximum mass (which is 5.8051 solar mass for n = 4) starts decreasing for n > 4. But this reaches a non-zero terminal value (2.8010 solar mass) as n tends to infinity.
On the well-posedness of a mathematical model describing water-mud interaction
Escher, Joachim
2012-01-01
In this paper we consider a mathematical model describing the two-phase interaction between water and mud in a water canal when the width of the canal is small compared to its depth. The mud is treated as a non-Netwonian fluid and the interface between the mud and fluid is allowed to move under the influence of gravity and surface tension. We reduce the mathematical formulation, for small boundary and initial data, to a fully nonlocal and nonlinear problem and prove its local well-posedness by using abstract parabolic theory.
Modeling approaches to describe H2O and CO2 exchange in mare ecosystems
Olchev, A.; Novenko, E.; Volkova, E.
2012-04-01
The modern climatic conditions is strongly influenced by both internal variability of climatic system, and various external natural and anthropogenic factors (IPCC 2007). Significant increase of concentration of greenhouse gases in the atmosphere and especially the growth of atmospheric CO2 due to human activity are considered as the main factors that are responsible for global warming and climate changes. A significant part of anthropogenic CO2 is absorbed from the atmosphere by land biota and especially by vegetation cover. However, it is still not completely clear what is the role of different land ecosystems and especially forests and mares in global cycles of H2O and CO2 and what is a sensitivity of these ecosystems to climate changes. Within the frameworks of this study the spatial and temporal variability of H2O and CO2 fluxes in different types of mare ecosystems of the forest-steppe zone in European part of Russia was described using modeling approaches and results of field measurements. For this modeling and experimental study the mare ecosystems of Tula region were selected. The Tula region is located mostly in the forest-steppe zone and it is unique area for such studies because almost all existed types of mare ecosystems of Northern Eurasia distinguished by a geomorphological position, water and mineral supply can be found there. Most mares in Tula region have a relatively small size and surrounded by very heterogeneous forests that make not possible an application of the classical measuring and modeling approaches e.g. an eddy covariance technique or one-dimensional H2O and CO2 exchange models for flux estimation in such sites. In our study to describe the radiation, sensible heat, H2O and CO2 exchange between such heterogeneous mare ecosystems and the atmosphere a three-dimensional model Forbog-3D and one-dimensional Mixfor-SVAT were applied. The main concept used in the Forbog-3D and Mixfor-SVAT models is an aggregated description of physical and
Analytical Model to Describe the Thermal Behavior of a Heat Discharge System in Roofs
Directory of Open Access Journals (Sweden)
Hernández-Gómez V.H.
2012-01-01
Full Text Available The present study proposes an analytical model which describes the thermal behavior of a heat discharge system in roof, when the surfaces that constitute it are not translucent. Such a model derives from a thermal balance carried out to a heat discharge system in roofs. To validate it, an experimental prototype that allows simulating the thermal behavior of a heat discharge system in wall and roof was used, and the results were compared to those obtained with the proposed analytical model. It was found that the thermal behavior of the analytical model is similar to the thermal behavior of the experimental prototype; a worthless variation was detected among their respective outcome (The difference of temperatures can be caused by the heat transfer coefficient, of which no studies defining its behavior accurately have been found. Therefore, it can be considered that the proposed analytical model can be employed to simulate the thermal behavior of a heat discharge system in roofs when the surfaces that constitute it are opaque.
A spatio-temporal model to describe the spread of Salmonella within a laying flock.
Zongo, Pascal; Viet, Anne-France; Magal, Pierre; Beaumont, Catherine
2010-12-21
Salmonella is one of the major sources of toxi-infection in humans, most often because of consumption of poultry products. The main reason for this association is the presence in hen flocks of silent carriers, i.e. animals harboring Salmonella without expressing any visible symptoms. Many prophylactic means have been developed to reduce the prevalence of Salmonella carrier-state. While none allows a total reduction of the risk, synergy could result in a drastic reduction of it. Evaluating the risk by modeling would be very useful to estimate such gain in food safety. Here, we propose an individual-based model which describes the spatio-temporal spread of Salmonella within a laying flock and takes into account the host response to bacterial infection. The model includes the individual bacterial load and the animals' ability to reduce it thanks to the immune response, i.e. maximum bacterial dose that the animals may resist without long term carriage and, when carriers, length of bacterial clearance. For model validation, we simulated the Salmonella spread under published experimental conditions. There was a good agreement between simulated and observed published data. This model will thus allow studying the effects, on the spatiotemporal distribution of the bacteria, of both mean and variability of different elements of host response.
The stay/switch model describes choice among magnitudes of reinforcers.
MacDonall, James S
2008-06-01
The stay/switch model is an alternative to the generalized matching law for describing choice in concurrent procedures. The purpose of the present experiment was to extend this model to choice among magnitudes of reinforcers. Rats were exposed to conditions in which the magnitude of reinforcers (number of food pellets) varied for staying at alternative 1, switching from alternative 1, staying at alternative 2 and switching from alternative 2. A changeover delay was not used. The results showed that the stay/switch model provided a good account of the data overall, and deviations from fits of the generalized matching law to response allocation data were in the direction predicted by the stay/switch model. In addition, comparisons among specific conditions suggested that varying the ratio of obtained reinforcers, as in the generalized matching law, was not necessary to change the response and time allocations. Other comparisons suggested that varying the ratio of obtained reinforcers was not sufficient to change response allocation. Taken together these results provide additional support for the stay/switch model of concurrent choice.
Directory of Open Access Journals (Sweden)
Windy A Boyd
Full Text Available BACKGROUND: The nematode Caenorhabditis elegans is being assessed as an alternative model organism as part of an interagency effort to develop better means to test potentially toxic substances. As part of this effort, assays that use the COPAS Biosort flow sorting technology to record optical measurements (time of flight (TOF and extinction (EXT of individual nematodes under various chemical exposure conditions are being developed. A mathematical model has been created that uses Biosort data to quantitatively and qualitatively describe C. elegans growth, and link changes in growth rates to biological events. Chlorpyrifos, an organophosphate pesticide known to cause developmental delays and malformations in mammals, was used as a model toxicant to test the applicability of the growth model for in vivo toxicological testing. METHODOLOGY/PRINCIPAL FINDINGS: L1 larval nematodes were exposed to a range of sub-lethal chlorpyrifos concentrations (0-75 microM and measured every 12 h. In the absence of toxicant, C. elegans matured from L1s to gravid adults by 60 h. A mathematical model was used to estimate nematode size distributions at various times. Mathematical modeling of the distributions allowed the number of measured nematodes and log(EXT and log(TOF growth rates to be estimated. The model revealed three distinct growth phases. The points at which estimated growth rates changed (change points were constant across the ten chlorpyrifos concentrations. Concentration response curves with respect to several model-estimated quantities (numbers of measured nematodes, mean log(TOF and log(EXT, growth rates, and time to reach change points showed a significant decrease in C. elegans growth with increasing chlorpyrifos concentration. CONCLUSIONS: Effects of chlorpyrifos on C. elegans growth and development were mathematically modeled. Statistical tests confirmed a significant concentration effect on several model endpoints. This confirmed that chlorpyrifos
Parameter Estimation, Model Reduction and Quantum Filtering
Chase, Bradley A
2009-01-01
This dissertation explores the topics of parameter estimation and model reduction in the context of quantum filtering. Chapters 2 and 3 provide a review of classical and quantum probability theory, stochastic calculus and filtering. Chapter 4 studies the problem of quantum parameter estimation and introduces the quantum particle filter as a practical computational method for parameter estimation via continuous measurement. Chapter 5 applies these techniques in magnetometry and studies the estimator's uncertainty scalings in a double-pass atomic magnetometer. Chapter 6 presents an efficient feedback controller for continuous-time quantum error correction. Chapter 7 presents an exact model of symmetric processes of collective qubit systems.
Cosmological models described by a mixture of van der Waals fluid and dark energy
Kremer, G M
2003-01-01
The Universe is modeled as a binary mixture whose constituents are described by a van der Waals fluid and by a dark energy density. The dark energy density is considered either as the quintessence or as the Chaplygin gas. The irreversible processes concerning the energy transfer between the van der Waals fluid and the gravitational field are taken into account. This model can simulate: (a) an inflationary period where the acceleration grows exponentially and the van der Waals fluid behaves like an inflaton; (b) an inflationary period where the acceleration is positive but it decreases and tends to zero whereas the energy density of the van der Waals fluid decays; (c) a decelerated period which corresponds to a matter dominated period with a non-negative pressure; and (d) a present accelerated period where the dark energy density outweighs the energy density of the van der Waals fluid.
Pinning Properties of Commercial Nb-Ti Wires Described by a 2-Components Model
Muzzi, L; Zignani, Chiarasole Fiamozzi; De Marzi, Gianluca; Muzzi, Luigi; Dominguez, Cesar Octavio; Bottura, Luca; Napolitano, Mathieu; Viola, Rosario; Affinito, Luigi; della Corte, Antonio; Le Naour, Sandrine
2010-01-01
We report on the magnetic and transport characterization of different NbTi commercial strands, carried out at variable temperature and magnetic field. From the critical current densities extracted from transport measurements and magnetization cycles we were able to calculate the normalized bulk pinning forces. The curves show good temperature scaling throughout the explored temperature range, and the reduced pinning force can be described by a simple two-components model system. The extension of the 2-components description of the pinning force to an expression for the critical current density gives a very good agreement with experimental measurements over the whole explored B, T range. The model works for all investigated samples, which are different in size, Cu:nonCu ratios, filament diameters and layouts. These results suggest that pinning mechanisms in conventional NbTi strands should be revised, since Nb-Ti composition gradients and grain boundaries seems to play a not negligible role.
Describing different brain computer interface systems through a unique model: a UML implementation.
Quitadamo, Lucia Rita; Marciani, Maria Grazia; Cardarilli, Gian Carlo; Bianchi, Luigi
2008-01-01
All the protocols currently implemented in brain computer interface (BCI) experiments are characterized by different structural and temporal entities. Moreover, due to the lack of a unique descriptive model for BCI systems, there is not a standard way to define the structure and the timing of a BCI experimental session among different research groups and there is also great discordance on the meaning of the most common terms dealing with BCI, such as trial, run and session. The aim of this paper is to provide a unified modeling language (UML) implementation of BCI systems through a unique dynamic model which is able to describe the main protocols defined in the literature (P300, mu-rhythms, SCP, SSVEP, fMRI) and demonstrates to be reasonable and adjustable according to different requirements. This model includes a set of definitions of the typical entities encountered in a BCI, diagrams which explain the structural correlations among them and a detailed description of the timing of a trial. This last represents an innovation with respect to the models already proposed in the literature. The UML documentation and the possibility of adapting this model to the different BCI systems built to date, make it a basis for the implementation of new systems and a mean for the unification and dissemination of resources. The model with all the diagrams and definitions reported in the paper are the core of the body language framework, a free set of routines and tools for the implementation, optimization and delivery of cross-platform BCI systems.
Ghyoot, Caroline; Lancelot, Christiane; Flynn, Kevin J.; Mitra, Aditee; Gypens, Nathalie
2017-04-01
Most biogeochemical/ecological models divide planktonic protists between phototrophs (phytoplankton) and heterotrophs (zooplankton). However, a large number of planktonic protists are able to combine several mechanisms of carbon and nutrient acquisition. Not representing these multiple mechanisms in biogeochemical/ecological models describing eutrophied coastal ecosystems can potentially lead to different conclusions regarding ecosystem functioning, especially regarding the success of harmful algae, which are often reported as mixotrophic. This modelling study investigates, for the first time, the implications for trophic dynamics of including 3 contrasting forms of mixotrophy, namely osmotrophy (using alkaline phosphatase activity, APA), non-constitutive mixotrophy (acquired phototrophy by microzooplankton) and also constitutive mixotrophy. The application is in the Southern North Sea, an ecosystem that faced, between 1985 and 2005, a significant increase in the nutrient supply N:P ratio (from 31 to 81 mole N:P). The comparison with a traditional model shows that, when the winter N:P ratio in the Southern North Sea is above 22 molN molP-1 (as occurred from mid-1990s), APA allows a 3 to 32% increase of annual gross primary production (GPP). In result of the higher GPP, the annual sedimentation increases as well as the bacterial production. By contrast, APA does not affect the export of matter to higher trophic levels because the increased GPP is mainly due to Phaeocystis colonies, which are not grazed by copepods. The effect of non-constitutive mixotrophy depends on light and affects the ecosystem functioning in terms of annual GPP, transfer to higher trophic levels, sedimentation, and nutrient remineralisation. Constitutive mixotrophy in nanoflagellates appears to have little influence on this ecosystem functioning. An important conclusion from this work is that different forms of mixotrophy have different impacts on system dynamics and it is thus important to
Relevance and limitations of crowding, fractal, and polymer models to describe nuclear architecture.
Huet, Sébastien; Lavelle, Christophe; Ranchon, Hubert; Carrivain, Pascal; Victor, Jean-Marc; Bancaud, Aurélien
2014-01-01
Chromosome architecture plays an essential role for all nuclear functions, and its physical description has attracted considerable interest over the last few years among the biophysics community. These researches at the frontiers of physics and biology have been stimulated by the demand for quantitative analysis of molecular biology experiments, which provide comprehensive data on chromosome folding, or of live cell imaging experiments that enable researchers to visualize selected chromosome loci in living or fixed cells. In this review our goal is to survey several nonmutually exclusive models that have emerged to describe the folding of DNA in the nucleus, the dynamics of proteins in the nucleoplasm, or the movements of chromosome loci. We focus on three classes of models, namely molecular crowding, fractal, and polymer models, draw comparisons, and discuss their merits and limitations in the context of chromosome structure and dynamics, or nuclear protein navigation in the nucleoplasm. Finally, we identify future challenges in the roadmap to a unified model of the nuclear environment.
An analytical model to describe the compression in turbomolecular pumps and roots blowers
Energy Technology Data Exchange (ETDEWEB)
Voss, G [Oerlikon Leybold Vacuum Bonner Str. 498, D - 50968 Cologne (Germany)], E-mail: gerhard.voss@oerlikon.com
2008-05-01
An analytical model is presented, useful in practice, for calculating and analysing the compression curves of classical turbomolecular pumps, wide range turbomolecular pumps and Roots blowers. It is demonstrated that the model, primarily proposed for classical turbomolecular pumps, can be applied to wide range turbomolecular pumps and Roots blowers as well. The model is based on an ordinary differential equation for the pressure as a function of position inside the pump. Solving the differential equation makes it possible both to calculate the compression curves for a finite gas throughput (Q > 0) and for zero gas throughput. A hypothesis is posed holding that the compression curve for zero gas throughput can be derived from a compression curve for a finite gas throughput, e.g., Q = 1 sccm in the case of turbomolecular pumps. In the case of Roots blowers a proposal is made how to describe the backleakage phenomenon quantitatively. For each type of vacuum pump mentioned above the comparison with experimental data shows that the model provides an excellent qualitative and quantitative reproduction of the observed phenomena in the whole relevant pressure range, i.e., perfect agreement over more than five pressure decades is achieved.
Parameter Estimation for Thurstone Choice Models
Energy Technology Data Exchange (ETDEWEB)
Vojnovic, Milan [London School of Economics (United Kingdom); Yun, Seyoung [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-04-24
We consider the estimation accuracy of individual strength parameters of a Thurstone choice model when each input observation consists of a choice of one item from a set of two or more items (so called top-1 lists). This model accommodates the well-known choice models such as the Luce choice model for comparison sets of two or more items and the Bradley-Terry model for pair comparisons. We provide a tight characterization of the mean squared error of the maximum likelihood parameter estimator. We also provide similar characterizations for parameter estimators defined by a rank-breaking method, which amounts to deducing one or more pair comparisons from a comparison of two or more items, assuming independence of these pair comparisons, and maximizing a likelihood function derived under these assumptions. We also consider a related binary classification problem where each individual parameter takes value from a set of two possible values and the goal is to correctly classify all items within a prescribed classification error. The results of this paper shed light on how the parameter estimation accuracy depends on given Thurstone choice model and the structure of comparison sets. In particular, we found that for unbiased input comparison sets of a given cardinality, when in expectation each comparison set of given cardinality occurs the same number of times, for a broad class of Thurstone choice models, the mean squared error decreases with the cardinality of comparison sets, but only marginally according to a diminishing returns relation. On the other hand, we found that there exist Thurstone choice models for which the mean squared error of the maximum likelihood parameter estimator can decrease much faster with the cardinality of comparison sets. We report empirical evaluation of some claims and key parameters revealed by theory using both synthetic and real-world input data from some popular sport competitions and online labor platforms.
Fordyce, James A.
2017-01-01
Among the greatest challenges facing the conservation of plants and animal species in protected areas are threats from a rapidly changing climate. An altered climate creates both challenges and opportunities for improving the management of protected areas in networks. Increasingly, quantitative tools like species distribution modeling are used to assess the performance of protected areas and predict potential responses to changing climates for groups of species, within a predictive framework. At larger geographic domains and scales, protected area network units have spatial geoclimatic properties that can be described in the gap analysis typically used to measure or aggregate the geographic distributions of species (stacked species distribution models, or S-SDM). We extend the use of species distribution modeling techniques in order to model the climate envelope (or “footprint”) of individual protected areas within a network of protected areas distributed across the 48 conterminous United States and managed by the US National Park System. In our approach we treat each protected area as the geographic range of a hypothetical endemic species, then use MaxEnt and 5 uncorrelated BioClim variables to model the geographic distribution of the climatic envelope associated with each protected area unit (modeling the geographic area of park units as the range of a species). We describe the individual and aggregated climate envelopes predicted by a large network of 163 protected areas and briefly illustrate how macroecological measures of geodiversity can be derived from our analysis of the landscape ecological context of protected areas. To estimate trajectories of change in the temporal distribution of climatic features within a protected area network, we projected the climate envelopes of protected areas in current conditions onto a dataset of predicted future climatic conditions. Our results suggest that the climate envelopes of some parks may be locally unique or
Robinson, Jason L; Fordyce, James A
2017-01-01
Among the greatest challenges facing the conservation of plants and animal species in protected areas are threats from a rapidly changing climate. An altered climate creates both challenges and opportunities for improving the management of protected areas in networks. Increasingly, quantitative tools like species distribution modeling are used to assess the performance of protected areas and predict potential responses to changing climates for groups of species, within a predictive framework. At larger geographic domains and scales, protected area network units have spatial geoclimatic properties that can be described in the gap analysis typically used to measure or aggregate the geographic distributions of species (stacked species distribution models, or S-SDM). We extend the use of species distribution modeling techniques in order to model the climate envelope (or "footprint") of individual protected areas within a network of protected areas distributed across the 48 conterminous United States and managed by the US National Park System. In our approach we treat each protected area as the geographic range of a hypothetical endemic species, then use MaxEnt and 5 uncorrelated BioClim variables to model the geographic distribution of the climatic envelope associated with each protected area unit (modeling the geographic area of park units as the range of a species). We describe the individual and aggregated climate envelopes predicted by a large network of 163 protected areas and briefly illustrate how macroecological measures of geodiversity can be derived from our analysis of the landscape ecological context of protected areas. To estimate trajectories of change in the temporal distribution of climatic features within a protected area network, we projected the climate envelopes of protected areas in current conditions onto a dataset of predicted future climatic conditions. Our results suggest that the climate envelopes of some parks may be locally unique or have
Scale-up model describing the impact of lubrication on tablet tensile strength.
Kushner, Joseph; Moore, Francis
2010-10-31
Lubrication of 2:1 and 1:1 blends of microcrystalline cellulose and spray-dried lactose or dibasic calcium phosphate (DCP) with 0.33% or 1% magnesium stearate, as model free-flowing pharmaceutical formulations, was performed in rotary drum blenders. Blender process parameters examined in this study included type (Bin, V, and Turbula), volume (0.75-Quart to 200-L), fraction of headspace in the blender after the blend is loaded (30-70%), speed (6-202 rpm), and time (up to 225 min). Based on analysis of the experimental data, the following model for the impact of the lubrication process on tablet tensile strength at 0.85 solid fraction, TS(SF=0.85), was obtained, TS(SF=0.85)=TS(SF=0.85,0) [βexp(-γ×V(1/3)×F(headspace)×r)+(1-β)], where V is blender volume, F(headspace) is the headspace fraction, r is the number of revolutions (i.e. speed × time), TS(SF=0.85,0) is the initial tensile strength of the blend, β is the sensitivity of the blend to lubrication, and γ is the lubrication rate constant of the formulation. This model can be used to maintain tensile strength during scale-up, by ensuring that (V(1/3)F(headspace)r)(1)=(V(1/3)F(headspace)r)(2). The model also suggests that formulations with DCP are less sensitive to lubrication and more slowly lubricated than formulations with spray-dried lactose (i.e. smaller β and γ values).
Towards predictive food process models: A protocol for parameter estimation.
Vilas, Carlos; Arias-Méndez, Ana; Garcia, Miriam R; Alonso, Antonio A; Balsa-Canto, E
2016-05-31
Mathematical models, in particular, physics-based models, are essential tools to food product and process design, optimization and control. The success of mathematical models relies on their predictive capabilities. However, describing physical, chemical and biological changes in food processing requires the values of some, typically unknown, parameters. Therefore, parameter estimation from experimental data is critical to achieving desired model predictive properties. This work takes a new look into the parameter estimation (or identification) problem in food process modeling. First, we examine common pitfalls such as lack of identifiability and multimodality. Second, we present the theoretical background of a parameter identification protocol intended to deal with those challenges. And, to finish, we illustrate the performance of the proposed protocol with an example related to the thermal processing of packaged foods.
SPATIAL MODELLING FOR DESCRIBING SPATIAL VARIABILITY OF SOIL PHYSICAL PROPERTIES IN EASTERN CROATIA
Directory of Open Access Journals (Sweden)
Igor Bogunović
2016-06-01
Full Text Available The objectives of this study were to characterize the field-scale spatial variability and test several interpolation methods to identify the best spatial predictor of penetration resistance (PR, bulk density (BD and gravimetric water content (GWC in the silty loam soil in Eastern Croatia. The measurements were made on a 25 x 25-m grid which created 40 individual grid cells. Soil properties were measured at the center of the grid cell deep 0-10 cm and 10-20 cm. Results demonstrated that PR and GWC displayed strong spatial dependence at 0-10 cm BD, while there was moderate and weak spatial dependence of PR, BD and GWC at depth of 10-20 cm. Semi-variogram analysis suggests that future sampling intervals for investigated parameters can be increased to 35 m in order to reduce research costs. Additionally, interpolation models recorded similar root mean square values with high predictive accuracy. Results suggest that investigated properties do not have uniform interpolation method implying the need for spatial modelling in the evaluation of these soil properties in Eastern Croatia.
Energy Technology Data Exchange (ETDEWEB)
Luigi, A.; Saputelli, B.; Carlas, M.; Canache, P.; Lopez, E. [DPVS Exploracion y Produccion (Venezuela)
1998-12-31
This study was designed to determine the activation energy ranges and frequency factor ranges in chemical reactions in heavy oils of the Orinoco Belt in Venezuela, in order to account for the kinetics of physical changes that occur in the morphology of gas-oil dispersion. A non-equilibrium reaction model was used to model foamy oil behaviour observed at SDZ-182 horizontal well in the Zuata field. Results showed that activation energy for the first reaction ranged from 0 to 0.01 BTU/lb-mol and frequency factor from 0.001 to 1000 l/day. For the second reaction the activation energy was 50x10{sub 3} BTU/lb-mol and the frequency factor 2.75x10{sub 1}2 l/day. The second reaction was highly sensitive to the modifications in activation energy and frequency factor. However, both the activation energy and frequency factor were independent of variations for the first reaction. In the case of the activation energy, the results showed that the high sensitivity of this parameter reflected the impact that temperature has on the representation of foamy oil behaviour. 8 refs., 2 tabs., 6 figs.
Systematic parameter inference in stochastic mesoscopic modeling
Lei, Huan; Yang, Xiu; Li, Zhen; Karniadakis, George Em
2017-02-01
We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are "sparse". The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space. Fully access to the response surfaces within the confidence range enables us to infer the optimal force parameters given the desirable values of target properties at the macroscopic scale. Moreover, it enables us to investigate the intrinsic relationship between the model parameters, identify possible degeneracies in the parameter space, and optimize the model by eliminating model redundancies. The proposed method provides an efficient alternative approach for constructing mesoscopic models by inferring model parameters to recover target properties of the physics systems (e.g., from experimental measurements), where those force field parameters and formulation cannot be derived from the microscopic level in a straight forward way.
A spatial age-structured model for describing sea lamprey (Petromyzon marinus) population dynamics
Robinson, Jason M.; Wilberg, Michael J.; Adams, Jean V.; Jones, Michael L.
2013-01-01
The control of invasive sea lampreys (Petromyzon marinus) presents large scale management challenges in the Laurentian Great Lakes. No modeling approach has been developed that describes spatial dynamics of lamprey populations. We developed and validated a spatial and age-structured model and applied it to a sea lamprey population in a large river in the Great Lakes basin. We considered 75 discrete spatial areas, included a stock-recruitment function, spatial recruitment patterns, natural mortality, chemical treatment mortality, and larval metamorphosis. Recruitment was variable, and an upstream shift in recruitment location was observed over time. From 1993–2011 recruitment, larval abundance, and the abundance of metamorphosing individuals decreased by 80, 84, and 86%, respectively. The model successfully identified areas of high larval abundance and showed that areas of low larval density contribute significantly to the population. Estimated treatment mortality was less than expected but had a large population-level impact. The results and general approach of this work have applications for sea lamprey control throughout the Great Lakes and for the restoration and conservation of native lamprey species globally.
Bignardi, Annaiza Braga; El Faro, Lenira; Pereira, Rodrigo Junqueira; Ayres, Denise Rocha; Machado, Paulo Fernando; de Albuquerque, Lucia Galvão; Santana, Mário Luiz
2015-10-01
Reaction norm models have been widely used to study genotype by environment interaction (G × E) in animal breeding. The objective of this study was to describe environmental sensitivity across first lactation in Brazilian Holstein cows using a reaction norm approach. A total of 50,168 individual monthly test day (TD) milk yields (10 test days) from 7476 complete first lactations of Holstein cattle were analyzed. The statistical models for all traits (10 TDs and for 305-day milk yield) included the fixed effects of contemporary group, age of cow (linear and quadratic effects), and days in milk (linear effect), except for 305-day milk yield. A hierarchical reaction norm model (HRNM) based on the unknown covariate was used. The present study showed the presence of G × E in milk yield across first lactation of Holstein cows. The variation in the heritability estimates implies differences in the response to selection depending on the environment where the animals of this population are evaluated. In the average environment, the heritabilities for all traits were rather similar, in range from 0.02 to 0.63. The scaling effect of G × E predominated throughout most of lactation. Particularly during the first 2 months of lactation, G × E caused reranking of breeding values. It is therefore important to include the environmental sensitivity of animals according to the phase of lactation in the genetic evaluations of Holstein cattle in tropical environments.
Application of lumped-parameter models
DEFF Research Database (Denmark)
Ibsen, Lars Bo; Liingaard, Morten
This technical report concerns the lumped-parameter models for a suction caisson with a ratio between skirt length and foundation diameter equal to 1/2, embedded into an viscoelastic soil. The models are presented for three different values of the shear modulus of the subsoil (section 1.1). Subse...
Models and parameters for environmental radiological assessments
Energy Technology Data Exchange (ETDEWEB)
Miller, C W [ed.
1984-01-01
This book presents a unified compilation of models and parameters appropriate for assessing the impact of radioactive discharges to the environment. Models examined include those developed for the prediction of atmospheric and hydrologic transport and deposition, for terrestrial and aquatic food-chain bioaccumulation, and for internal and external dosimetry. Chapters have been entered separately into the data base. (ACR)
Construction of constant-Q viscoelastic model with three parameters
Institute of Scientific and Technical Information of China (English)
SUN Cheng-yu; YIN Xing-yao
2007-01-01
The popularly used viscoelastic models have some shortcomings in describing relationship between quality factor (Q) and frequency, which is not consistent with the observation data. Based on the theory of viscoelasticity, a new approach to construct constant-Q viscoelastic model in given frequency band with three parameters is developed. The designed model describes the frequency-independence feature of quality factor very well, and the effect of viscoelasticity on seismic wave field can be studied relatively accurate in theory with this model. Furthermore, the number of required parameters in this model has been reduced fewer than that of other constant-Q models, this can simplify the solution of the viscoelastic problems to some extent. At last, the accuracy and application range have been analyzed through numerical tests. The effect of viscoelasticity on wave propagation has been briefly illustrated through the change of frequency spectra and waveform in several different viscoelastic models.
Institute of Scientific and Technical Information of China (English)
YanQuanying; ShangDeku; 等
1999-01-01
A two-dimensional mathematical model was built to describe the melting process of cylindrical basalt particle bed in a crucible.The melting processes with respect to the factors of thermal boundary conditions and particle sizes of basalt were simulated by using the numerical method (FDM).The governing equations were discretized in tridiagonal matrix form and were solved by using the tridiagonal matrix algorithm (TDMA) as well as the alternative direction implicit(ADI) solver.The temperature distribution,the moving law of the two dimensional phase-change boundaries the thermal current distribution were given through the numerical simulation.The results provided a theoretical basis for deciding heating procedure,for evaluating power import and controlling furnace temperature and for predicting basalt melting states etc.In the experiment,an electrical furnace was designed based on the computations.It has been proved that the simulation results are reasonably coincident with the experimental data.
Computer-aided Nonlinear Control System Design Using Describing Function Models
Nassirharand, Amir
2012-01-01
A systematic computer-aided approach provides a versatile setting for the control engineer to overcome the complications of controller design for highly nonlinear systems. Computer-aided Nonlinear Control System Design provides such an approach based on the use of describing functions. The text deals with a large class of nonlinear systems without restrictions on the system order, the number of inputs and/or outputs or the number, type or arrangement of nonlinear terms. The strongly software-oriented methods detailed facilitate fulfillment of tight performance requirements and help the designer to think in purely nonlinear terms, avoiding the expedient of linearization which can impose substantial and unrealistic model limitations and drive up the cost of the final product. Design procedures are presented in a step-by-step algorithmic format each step being a functional unit with outputs that drive the other steps. This procedure may be easily implemented on a digital computer with example problems from mecha...
The exotic characteristics of centauro-I: a model to describe Centauro-I
Energy Technology Data Exchange (ETDEWEB)
Ohsawa, Akinori [Institute for Cosmic Ray Research, University of Tokyo, Kashiwa, 277-8582 (Japan); Shibuya, Edison H [Instituto de Fisica, Universidade Estadual de Campinas, 13081 Campinas, Sao Paulo (Brazil); Tamada, Masanobu [School of Science and Engineering, Kinki University, Higashi-Osaka, 577-8502 (Japan)
2006-11-15
In our previous paper on Centauro-I (Ohsawa et al 2004 Phys. Rev. D 70 074028), we showed that the shower cluster, found in the block I12 of the lower chamber, is produced in the target layer by a number of hadrons with appreciable lateral spread. These hadrons are accompanied by no (or one at most) {gamma}-ray(s) with energy above detection threshold, and produce no shower in the upper chamber but 28 visible C-jets (with the visible energy more than 2 TeV) in the target layer. These characteristics are quite exotic and unable to be described by a fluctuation of ordinary atmospheric families. In the present paper, we propose a model of strange quark matter (SQM) among the primary cosmic rays to describe the exotic features of the event. A large SQM droplet enters the atmosphere and fragments into a bundle of small strangelets in the atmosphere without emission of {gamma}-rays, and these small strangelets explode into nucleons in the upper chamber. The number of collisions in the upper chamber is estimated to be as small as 3-4 in contrast to 20-30 collisions in the target layer. We discuss the intensity of Centauro-I together with the exotic events observed by the balloon and satellite experiments, which were also ascribed to strange quark matter.
Inclusion of models to describe severe accident conditions in the fuel simulation code DIONISIO
Energy Technology Data Exchange (ETDEWEB)
Lemes, Martín; Soba, Alejandro [Sección Códigos y Modelos, Gerencia Ciclo del Combustible Nuclear, Comisión Nacional de Energía Atómica, Avenida General Paz 1499, 1650 San Martín, Provincia de Buenos Aires (Argentina); Daverio, Hernando [Gerencia Reactores y Centrales Nucleares, Comisión Nacional de Energía Atómica, Avenida General Paz 1499, 1650 San Martín, Provincia de Buenos Aires (Argentina); Denis, Alicia [Sección Códigos y Modelos, Gerencia Ciclo del Combustible Nuclear, Comisión Nacional de Energía Atómica, Avenida General Paz 1499, 1650 San Martín, Provincia de Buenos Aires (Argentina)
2017-04-15
The simulation of fuel rod behavior is a complex task that demands not only accurate models to describe the numerous phenomena occurring in the pellet, cladding and internal rod atmosphere but also an adequate interconnection between them. In the last years several models have been incorporated to the DIONISIO code with the purpose of increasing its precision and reliability. After the regrettable events at Fukushima, the need for codes capable of simulating nuclear fuels under accident conditions has come forth. Heat removal occurs in a quite different way than during normal operation and this fact determines a completely new set of conditions for the fuel materials. A detailed description of the different regimes the coolant may exhibit in such a wide variety of scenarios requires a thermal-hydraulic formulation not suitable to be included in a fuel performance code. Moreover, there exist a number of reliable and famous codes that perform this task. Nevertheless, and keeping in mind the purpose of building a code focused on the fuel behavior, a subroutine was developed for the DIONISIO code that performs a simplified analysis of the coolant in a PWR, restricted to the more representative situations and provides to the fuel simulation the boundary conditions necessary to reproduce accidental situations. In the present work this subroutine is described and the results of different comparisons with experimental data and with thermal-hydraulic codes are offered. It is verified that, in spite of its comparative simplicity, the predictions of this module of DIONISIO do not differ significantly from those of the specific, complex codes.
Directory of Open Access Journals (Sweden)
Adam B. Sefkow
2006-09-01
Full Text Available Heavy ion drivers for warm dense matter and heavy ion fusion applications use intense charge bunches which must undergo transverse and longitudinal compression in order to meet the requisite high current densities and short pulse durations desired at the target. The neutralized drift compression experiment (NDCX at the Lawrence Berkeley National Laboratory is used to study the longitudinal neutralized drift compression of a space-charge-dominated ion beam, which occurs due to an imposed longitudinal velocity tilt and subsequent neutralization of the beam’s space charge by background plasma. Reduced theoretical models have been used in order to describe the realistic propagation of an intense charge bunch through the NDCX device. A warm-fluid model is presented as a tractable computational tool for investigating the nonideal effects associated with the experimental acceleration gap geometry and voltage waveform of the induction module, which acts as a means to pulse shape both the velocity and line density profiles. Self-similar drift compression solutions can be realized in order to transversely focus the entire charge bunch to the same focal plane in upcoming simultaneous transverse and longitudinal focusing experiments. A kinetic formalism based on the Vlasov equation has been employed in order to show that the peaks in the experimental current profiles are a result of the fact that only the central portion of the beam contributes effectively to the main compressed pulse. Significant portions of the charge bunch reside in the nonlinearly compressing part of the ion beam because of deviations between the experimental and ideal velocity tilts. Those regions form a pedestal of current around the central peak, thereby decreasing the amount of achievable longitudinal compression and increasing the pulse durations achieved at the focal plane. A hybrid fluid-Vlasov model which retains the advantages of both the fluid and kinetic approaches has been
Using the ecology model to describe the impact of asthma on patterns of health care
Directory of Open Access Journals (Sweden)
Yawn Barbara P
2005-05-01
Full Text Available Abstract Background Asthma changes both the volume and patterns of healthcare of affected people. Most studies of asthma health care utilization have been done in selected insured populations or in a single site such as the emergency department. Asthma is an ambulatory sensitive care condition making it important to understand the relationship between care in all sites across the health service spectrum. Asthma is also more common in people with fewer economic resources making it important to include people across all types of insurance and no insurance categories. The ecology of medical care model may provide a useful framework to describe the use of health services in people with asthma compared to those without asthma and identify subgroups with apparent gaps in care. Methods This is a case-control study using the 1999 U.S. Medical Expenditure Panel Survey. Cases are school-aged children (6 to 17 years and young adults (18 to 44 years with self-reported asthma. Controls are from the same age groups who have no self-reported asthma. Descriptive analyses and risk ratios are placed within the ecology of medical care model and used to describe and compare the healthcare contact of cases and controls across multiple settings. Results In 1999, the presence of asthma significantly increased the likelihood of an ambulatory care visit by 20 to 30% and more than doubled the likelihood of making one or more visits to the emergency department (ED. Yet, 18.8% of children and 14.5% of adults with asthma (over a million Americans had no ambulatory care visits for asthma. About one in 20 to 35 people with asthma (5.2% of children and 3.6% of adults were seen in the ED or hospital but had no prior or follow-up ambulatory care visits. These Americans were more likely to be uninsured, have no usual source of care and live in metropolitan areas. Conclusion The ecology model confirmed that having asthma changes the likelihood and pattern of care for Americans
Ghyoot, Caroline; Lancelot, Christiane; Flynn, Kevin J.; Mitra, Aditee; Gypens, Nathalie
2017-09-01
Most biogeochemical/ecological models divide planktonic protists between phototrophs (phytoplankton) and heterotrophs (zooplankton). However, a large number of planktonic protists are able to combine several mechanisms of carbon and nutrient acquisition. Not representing these multiple mechanisms in biogeochemical/ecological models describing eutrophied coastal ecosystems can potentially lead to different conclusions regarding ecosystem functioning, especially regarding the success of harmful algae, which are often reported as mixotrophic. This modelling study investigates the implications for trophic dynamics of including 3 contrasting forms of mixotrophy, namely osmotrophy (using alkaline phosphatase activity, APA), non-constitutive mixotrophy (acquired phototrophy by microzooplankton) and also constitutive mixotrophy. The application is in the Southern North Sea, an ecosystem that faced, between 1985 and 2005, a significant increase in the nutrient supply N:P ratio (from 31 to 81 mol N:P). The comparison with a traditional model shows that, when the winter N:P ratio in the Southern North Sea is above 22 molN molP-1 (as occurred from mid-1990s), APA allows a 3-32% increase of annual gross primary production (GPP). In result of the higher GPP, the annual sedimentation increases as well as the bacterial production. By contrast, APA does not affect the export of matter to higher trophic levels because the increased GPP is mainly due to Phaeocystis colonies, which are not grazed by copepods. Under high irradiance, non-constitutive mixotrophy appreciably increases annual GPP, transfer to higher trophic levels, sedimentation, and nutrient remineralisation. In this ecosystem, non-constitutive mixotrophy is also observed to have an indirect stimulating effect on diatoms. Constitutive mixotrophy in nanoflagellates appears to have little influence on this ecosystem functioning. An important conclusion from this work is that contrasting forms of mixotrophy have different
Woodward, Andrea; Torregrosa, Alicia; Madej, Mary Ann; Reichmuth, Michael; Fong, Darren
2014-01-01
The system dynamics model described in this report is the result of a collaboration between U.S. Geological Survey (USGS) scientists and National Park Service (NPS) San Francisco Bay Area Network (SFAN) staff, whose goal was to develop a methodology to integrate inventory and monitoring data to better understand ecosystem dynamics and trends using salmon in Olema Creek, Marin County, California, as an example case. The SFAN began monitoring multiple life stages of coho salmon (Oncorhynchus kisutch) in Olema Creek during 2003 (Carlisle and others, 2013), building on previous monitoring of spawning fish and redds. They initiated water-quality and habitat monitoring, and had access to flow and weather data from other sources. This system dynamics model of the freshwater portion of the coho salmon life cycle in Olema Creek integrated 8 years of existing monitoring data, literature values, and expert opinion to investigate potential factors limiting survival and production, identify data gaps, and improve monitoring and restoration prescriptions. A system dynamics model is particularly effective when (1) data are insufficient in time series length and/or measured parameters for a statistical or mechanistic model, and (2) the model must be easily accessible by users who are not modelers. These characteristics helped us meet the following overarching goals for this model: Summarize and synthesize NPS monitoring data with data and information from other sources to describe factors and processes affecting freshwater survival of coho salmon in Olema Creek. Provide a model that can be easily manipulated to experiment with alternative values of model parameters and novel scenarios of environmental drivers. Although the model describes the ecological dynamics of Olema Creek, these dynamics are structurally similar to numerous other coastal streams along the California coast that also contain anadromous fish populations. The model developed for Olema can be used, at least as a
Can Ising model and/or QKPZ equation properly describe reactive-wetting interface dynamics?
Efraim, Yael; Taitelbaum, Haim
2009-09-01
The reactive-wetting process, e.g. spreading of a liquid droplet on a reactive substrate is known as a complex, non-linear process with high sensitivity to minor fluctuations. The dynamics and geometry of the interface (triple line) between the materials is supposed to shed light on the main mechanisms of the process. We recently studied a room temperature reactive-wetting system of a small (˜ 150 μm) Hg droplet that spreads on a thin (˜ 4000 Å) Ag substrate. We calculated the kinetic roughening exponents (growth and roughness), as well as the persistence exponent of points on the advancing interface. In this paper we address the question whether there exists a well-defined model to describe the interface dynamics of this system, by performing two sets of numerical simulations. The first one is a simulation of an interface propagating according to the QKPZ equation, and the second one is a landscape of an Ising chain with ferromagnetic interactions in zero temperature. We show that none of these models gives a full description of the dynamics of the experimental reactivewetting system, but each one of them has certain common growth properties with it. We conjecture that this results from a microscopic behavior different from the macroscopic one. The microscopic mechanism, reflected by the persistence exponent, resembles the Ising behavior, while in the macroscopic scale, exemplified by the growth exponent, the dynamics looks more like the QKPZ dynamics.
Stochastic lattice gas model describing the dynamics of the SIRS epidemic process
de Souza, David R.; Tomé, Tânia
2010-03-01
We study a stochastic process describing the onset of spreading dynamics of an epidemic in a population composed of individuals of three classes: susceptible (S), infected (I), and recovered (R). The stochastic process is defined by local rules and involves the following cyclic process: S → I → R → S (SIRS). The open process S → I → R (SIR) is studied as a particular case of the SIRS process. The epidemic process is analyzed at different levels of description: by a stochastic lattice gas model and by a birth and death process. By means of Monte Carlo simulations and dynamical mean-field approximations we show that the SIRS stochastic lattice gas model exhibit a line of critical points separating the two phases: an absorbing phase where the lattice is completely full of S individuals and an active phase where S, I and R individuals coexist, which may or may not present population cycles. The critical line, that corresponds to the onset of epidemic spreading, is shown to belong in the directed percolation universality class. By considering the birth and death process we analyze the role of noise in stabilizing the oscillations.
Lieberman, M E; Gorski, J; Jordan, V C
1983-04-25
A hypothetical model of the ligand interaction with the estrogen receptor binding site has been developed to describe the structural features necessary to initiate or to inhibit prolactin synthesis in vitro. The biological potency of the binding ligands is directly related to their relative binding affinity (RBA) for the estrogen receptor. The relative potencies of antiestrogens to inhibit estradiol-stimulated prolactin synthesis was trans-monohydroxytamoxifen identical to cis-monohydroxytamoxifen identical to tamoxifen, consistent with their RBAs for uterine estrogen receptor. Similarly the relative potency of estrogens to stimulate prolactin synthesis was diethylstilbestrol identical to estradiol greater than ICI 77,949 greater than ICI 47,699 identical to zuclomiphene, consistent with their RBAs. The compound LY126412 (trioxifene without the aminoethoxy side chain) did not interact with the estrogen receptor at the concentrations tested (10(-8)--10(-6) M) or exhibit estrogenic or antiestrogenic properties using the prolactin synthesis assay. Overall, the ligand-receptor model stresses the structural requirement for high affinity binding and the critical positioning of the alkylamino-ethoxy side chain in space (in relation to the ligand-binding site on the estrogen receptor) to prevent prolactin synthesis.
Maas, Anne H; Rozendaal, Yvonne J W; van Pul, Carola; Hilbers, Peter A J; Cottaar, Ward J; Haak, Harm R; van Riel, Natal A W
2015-03-01
Current diabetes education methods are costly, time-consuming, and do not actively engage the patient. Here, we describe the development and verification of the physiological model for healthy subjects that forms the basis of the Eindhoven Diabetes Education Simulator (E-DES). E-DES shall provide diabetes patients with an individualized virtual practice environment incorporating the main factors that influence glycemic control: food, exercise, and medication. The physiological model consists of 4 compartments for which the inflow and outflow of glucose and insulin are calculated using 6 nonlinear coupled differential equations and 14 parameters. These parameters are estimated on 12 sets of oral glucose tolerance test (OGTT) data (226 healthy subjects) obtained from literature. The resulting parameter set is verified on 8 separate literature OGTT data sets (229 subjects). The model is considered verified if 95% of the glucose data points lie within an acceptance range of ±20% of the corresponding model value. All glucose data points of the verification data sets lie within the predefined acceptance range. Physiological processes represented in the model include insulin resistance and β-cell function. Adjusting the corresponding parameters allows to describe heterogeneity in the data and shows the capabilities of this model for individualization. We have verified the physiological model of the E-DES for healthy subjects. Heterogeneity of the data has successfully been modeled by adjusting the 4 parameters describing insulin resistance and β-cell function. Our model will form the basis of a simulator providing individualized education on glucose control.
An Optimization Model of Tunnel Support Parameters
Directory of Open Access Journals (Sweden)
Su Lijuan
2015-05-01
Full Text Available An optimization model was developed to obtain the ideal values of the primary support parameters of tunnels, which are wide-ranging in high-speed railway design codes when the surrounding rocks are at the III, IV, and V levels. First, several sets of experiments were designed and simulated using the FLAC3D software under an orthogonal experimental design. Six factors, namely, level of surrounding rock, buried depth of tunnel, lateral pressure coefficient, anchor spacing, anchor length, and shotcrete thickness, were considered. Second, a regression equation was generated by conducting a multiple linear regression analysis following the analysis of the simulation results. Finally, the optimization model of support parameters was obtained by solving the regression equation using the least squares method. In practical projects, the optimized values of support parameters could be obtained by integrating known parameters into the proposed model. In this work, the proposed model was verified on the basis of the Liuyang River Tunnel Project. Results show that the optimization model significantly reduces related costs. The proposed model can also be used as a reliable reference for other high-speed railway tunnels.
Feinberg, I; Thode, H C; Chugani, H T; March, J D
1990-01-23
We analyzed the available ontogenetic data (birth to 30 years of age) for: amplitude of delta EEG (DA) waves during sleep; cortical metabolic rate (CMR) measured with positron emission tomography; and synaptic density (SD) in frontal cortex. Each is at the adult level at birth, increases to about twice this level by 3 years of age, and then gradually falls back to the adult level over the next two decades. Statistical analyses revealed that individual gamma distribution models fit each data set as well as did the best ad hoc polynomial. A test of whether a single gamma distribution model could describe all three data sets gave good results for DA and CMR but the fit was unsatisfactory for SD. However, because so few data were available for SD, this test was not conclusive. We proposed the following model to account for these changes. First, cortical neurons are stimulated by birth to enter a proliferative state (PS) that creates many connections. Next, as a result of interactions in the PS, neurons are triggered into a transient organizational state (OS) in which they make enduring connections. The OS has a finite duration (minutes to years), and is characterized by high rates of information-processing and metabolism. Levels of CMR, SD and DA, therefore, are proportional to the number of neurons in the OS at any time. Thus, the cortex after birth duplicates, over a vastly greater time scale, the overproduction and regression of neural elements that occurs repeatedly in embryonic development. Finally, we discussed the implications of post-natal brain changes for normal and abnormal brain function. Mental disorders that have their onset after puberty (notably schizophrenia and manic-depressive psychoses) might be caused by errors in these late maturational processes. In addition to age of onset, this neurodevelopmental hypothesis might explain several other puzzling features of these subtle disorders.
Analysis of Modeling Parameters on Threaded Screws.
Energy Technology Data Exchange (ETDEWEB)
Vigil, Miquela S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brake, Matthew Robert [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vangoethem, Douglas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-06-01
Assembled mechanical systems often contain a large number of bolted connections. These bolted connections (joints) are integral aspects of the load path for structural dynamics, and, consequently, are paramount for calculating a structure's stiffness and energy dissipation prop- erties. However, analysts have not found the optimal method to model appropriately these bolted joints. The complexity of the screw geometry cause issues when generating a mesh of the model. This paper will explore different approaches to model a screw-substrate connec- tion. Model parameters such as mesh continuity, node alignment, wedge angles, and thread to body element size ratios are examined. The results of this study will give analysts a better understanding of the influences of these parameters and will aide in finding the optimal method to model bolted connections.
Pene Dumitrescu, T; Anic-Milic, T; Oreskovic, K; Padovan, J; Brouwer, K L R; Zuo, P; Schmith, V D
2013-07-01
Azithromycin (AZI), a broad-spectrum antibiotic, accumulates in polymorphonuclear cells and peripheral blood mononuclear cells. The distribution of AZI in proinflammatory cells may be important to the anti-inflammatory properties. Previous studies have described plasma AZI pharmacokinetics. The objective of this study was to describe the pharmacokinetics of AZI in whole blood (concentration in whole blood [Cb]) and plasma (concentration in plasma [Cp]) of healthy subjects. In this study, 12 subjects received AZI (500 mg once a day for 3 days). AZI Cb and Cp were quantified in serial samples collected up to 3 weeks after the last dose and analyzed using noncompartmental and compartmental methods. After the last dose, Cb was greater than Cp. Importantly, Cb, but not Cp, was quantifiable in all but one subject at 3 weeks. The blood area under the curve during a 24-h dosing interval (AUC24) was ∼2-fold greater than the plasma AUC24, but simulations suggested that Cb was not at steady state by day 3. Upon exploration of numerous models, an empirical 3-compartment model adequately described Cp and Cb, but Cp was somewhat underestimated. Intercompartmental clearance (CL; likely representing cells) was lower than apparent oral CL (18 versus 118 liters/h). Plasma, peripheral, and cell compartmental volumes were 439 liters, 2,980 liters, and 3,084 liters, respectively. Interindividual variability in CL was low (26.2%), while the volume of distribution variability was high (107%). This is the first report to describe AZI Cb in healthy subjects, the distribution parameters between Cp and Cb, and AZI retention in blood for up to 3 weeks following 3 daily doses. The model can be used to predict Cb from Cp for AZI under various dosing regimens. (This study has been registered at ClinicalTrials.gov under registration no. NCT01026064.).
Structure of a single model to describe plutonium and americium decorporation by DTPA treatments.
Fritsch, P; Sérandour, A L; Grémy, O; Phan, G; Tsapis, N; Fattal, E; Benech, H; Deverre, J R; Poncy, J L
2010-10-01
The aim of this study is to propose a single modeling structure to describe both plutonium and americium decorporation by DTPA, which is based on hypotheses mostly validated by experimental data. Decorporation efficacy of extracellular retention depends on the concentration ratio of DTPA vs. actinides and varies in each compartment according to the amount of biological ligands and their affinity for actinides. By contrast, because the relatively long residence time of DTPA after its cell internalization and the stability of actinide-DTPA complexes, intracellular decorporation efficacy is mainly controlled by a DTPA/actinide ratio, which is specific to each retention compartment. Although the affinity of DTPA is much lower for americium than for plutonium, a larger decorporation of americium can be obtained, which is explained by different biological ligands and/or their affinity for the actinide. Altogether, these results show that the relative contribution of intra vs. extracellular decorporation varies depending on the actinide, the chemical form of radionuclides, the galenic formulation of DTPA, and the treatment schedule.
Budiarto, E.; Keijzer, M.; Storchi, P. R.; Hoogeman, M. S.; Bondar, L.; Mutanga, T. F.; de Boer, H. C. J.; Heemink, A. W.
2011-02-01
Local motions and deformations of organs between treatment fractions introduce geometrical uncertainties into radiotherapy. These uncertainties are generally taken into account in the treatment planning by enlarging the radiation target by a margin around the clinical target volume. However, a practical method to fully include these uncertainties is still lacking. This paper proposes a model based on the principal component analysis to describe the patient-specific local probability distributions of voxel motions so that the average values and variances of the dose distribution can be calculated and fully used later in inverse treatment planning. As usually only a very limited number of data for new patients is available; in this paper the analysis is extended to use population data. A basic assumption (which is justified retrospectively in this paper) is that general movements and deformations of a specific organ are similar despite variations in the shapes of the organ over the population. A proof of principle of the method for deformations of the prostate and the seminal vesicles is presented.
Energy Technology Data Exchange (ETDEWEB)
Budiarto, E; Keijzer, M; Heemink, A W [Delft Institute of Applied Mathematics (DIAM), Technische Universiteit Delft, Mekelweg 4, 2628 CD Delft (Netherlands); Storchi, P R; Hoogeman, M S; Bondar, L; Mutanga, T F [Department of Radiation Oncology, Erasmus MC-Daniel den Hoed Cancer Centre. Groene Hilledijk 301, 3075 EA Rotterdam (Netherlands); De Boer, H C J, E-mail: e.budiarto@tudelft.nl [Department of Radiotherapy, Universitair Medisch Centrum Utrecht, Heidelberglaan 100, 3584 CX Utrecht (Netherlands)
2011-02-21
Local motions and deformations of organs between treatment fractions introduce geometrical uncertainties into radiotherapy. These uncertainties are generally taken into account in the treatment planning by enlarging the radiation target by a margin around the clinical target volume. However, a practical method to fully include these uncertainties is still lacking. This paper proposes a model based on the principal component analysis to describe the patient-specific local probability distributions of voxel motions so that the average values and variances of the dose distribution can be calculated and fully used later in inverse treatment planning. As usually only a very limited number of data for new patients is available; in this paper the analysis is extended to use population data. A basic assumption (which is justified retrospectively in this paper) is that general movements and deformations of a specific organ are similar despite variations in the shapes of the organ over the population. A proof of principle of the method for deformations of the prostate and the seminal vesicles is presented.
Weigand, M.; Kemna, A.
2016-06-01
Spectral induced polarization (SIP) data are commonly analysed using phenomenological models. Among these models the Cole-Cole (CC) model is the most popular choice to describe the strength and frequency dependence of distinct polarization peaks in the data. More flexibility regarding the shape of the spectrum is provided by decomposition schemes. Here the spectral response is decomposed into individual responses of a chosen elementary relaxation model, mathematically acting as kernel in the involved integral, based on a broad range of relaxation times. A frequently used kernel function is the Debye model, but also the CC model with some other a priorly specified frequency dispersion (e.g. Warburg model) has been proposed as kernel in the decomposition. The different decomposition approaches in use, also including conductivity and resistivity formulations, pose the question to which degree the integral spectral parameters typically derived from the obtained relaxation time distribution are biased by the approach itself. Based on synthetic SIP data sampled from an ideal CC response, we here investigate how the two most important integral output parameters deviate from the corresponding CC input parameters. We find that the total chargeability may be underestimated by up to 80 per cent and the mean relaxation time may be off by up to three orders of magnitude relative to the original values, depending on the frequency dispersion of the analysed spectrum and the proximity of its peak to the frequency range limits considered in the decomposition. We conclude that a quantitative comparison of SIP parameters across different studies, or the adoption of parameter relationships from other studies, for example when transferring laboratory results to the field, is only possible on the basis of a consistent spectral analysis procedure. This is particularly important when comparing effective CC parameters with spectral parameters derived from decomposition results.
Retrospective forecast of ETAS model with daily parameters estimate
Falcone, Giuseppe; Murru, Maura; Console, Rodolfo; Marzocchi, Warner; Zhuang, Jiancang
2016-04-01
We present a retrospective ETAS (Epidemic Type of Aftershock Sequence) model based on the daily updating of free parameters during the background, the learning and the test phase of a seismic sequence. The idea was born after the 2011 Tohoku-Oki earthquake. The CSEP (Collaboratory for the Study of Earthquake Predictability) Center in Japan provided an appropriate testing benchmark for the five 1-day submitted models. Of all the models, only one was able to successfully predict the number of events that really happened. This result was verified using both the real time and the revised catalogs. The main cause of the failure was in the underestimation of the forecasted events, due to model parameters maintained fixed during the test. Moreover, the absence in the learning catalog of an event similar to the magnitude of the mainshock (M9.0), which drastically changed the seismicity in the area, made the learning parameters not suitable to describe the real seismicity. As an example of this methodological development we show the evolution of the model parameters during the last two strong seismic sequences in Italy: the 2009 L'Aquila and the 2012 Reggio Emilia episodes. The achievement of the model with daily updated parameters is compared with that of same model where the parameters remain fixed during the test time.
The Lund Model at Nonzero Impact Parameter
Janik, R A; Janik, Romuald A.; Peschanski, Robi
2003-01-01
We extend the formulation of the longitudinal 1+1 dimensional Lund model to nonzero impact parameter using the minimal area assumption. Complete formulae for the string breaking probability and the momenta of the produced mesons are derived using the string worldsheet Minkowskian helicoid geometry. For strings stretched into the transverse dimension, we find probability distribution with slope linear in m_T similar to the statistical models but without any thermalization assumptions.
IMPROVEMENT OF FLUID PIPE LUMPED PARAMETER MODEL
Institute of Scientific and Technical Information of China (English)
Kong Xiaowu; Wei Jianhua; Qiu Minxiu; Wu Genmao
2004-01-01
The traditional lumped parameter model of fluid pipe is introduced and its drawbacks are pointed out.Furthermore, two suggestions are put forward to remove these drawbacks.Firstly, the structure of equivalent circuit is modified, and then the evaluation of equivalent fluid resistance is change to take the frequency-dependent friction into account.Both simulation and experiment prove that this model is precise to characterize the dynamic behaviors of fluid in pipe.
Parameter and Uncertainty Estimation in Groundwater Modelling
DEFF Research Database (Denmark)
Jensen, Jacob Birk
The data basis on which groundwater models are constructed is in general very incomplete, and this leads to uncertainty in model outcome. Groundwater models form the basis for many, often costly decisions and if these are to be made on solid grounds, the uncertainty attached to model results must...... be quantified. This study was motivated by the need to estimate the uncertainty involved in groundwater models.Chapter 2 presents an integrated surface/subsurface unstructured finite difference model that was developed and applied to a synthetic case study.The following two chapters concern calibration...... and uncertainty estimation. Essential issues relating to calibration are discussed. The classical regression methods are described; however, the main focus is on the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. The next two chapters describe case studies in which the GLUE methodology...
Consistent Stochastic Modelling of Meteocean Design Parameters
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Sterndorff, M. J.
2000-01-01
Consistent stochastic models of metocean design parameters and their directional dependencies are essential for reliability assessment of offshore structures. In this paper a stochastic model for the annual maximum values of the significant wave height, and the associated wind velocity, current...... velocity, and water level is presented. The stochastic model includes statistical uncertainty and dependency between the four stochastic variables. Further, a new stochastic model for annual maximum directional significant wave heights is presented. The model includes dependency between the maximum wave...... height from neighboring directional sectors. Numerical examples are presented where the models are calibrated using the Maximum Likelihood method to data from the central part of the North Sea. The calibration of the directional distributions is made such that the stochastic model for the omnidirectional...
Combined Estimation of Hydrogeologic Conceptual Model and Parameter Uncertainty
Energy Technology Data Exchange (ETDEWEB)
Meyer, Philip D.; Ye, Ming; Neuman, Shlomo P.; Cantrell, Kirk J.
2004-03-01
The objective of the research described in this report is the development and application of a methodology for comprehensively assessing the hydrogeologic uncertainties involved in dose assessment, including uncertainties associated with conceptual models, parameters, and scenarios. This report describes and applies a statistical method to quantitatively estimate the combined uncertainty in model predictions arising from conceptual model and parameter uncertainties. The method relies on model averaging to combine the predictions of a set of alternative models. Implementation is driven by the available data. When there is minimal site-specific data the method can be carried out with prior parameter estimates based on generic data and subjective prior model probabilities. For sites with observations of system behavior (and optionally data characterizing model parameters), the method uses model calibration to update the prior parameter estimates and model probabilities based on the correspondence between model predictions and site observations. The set of model alternatives can contain both simplified and complex models, with the requirement that all models be based on the same set of data. The method was applied to the geostatistical modeling of air permeability at a fractured rock site. Seven alternative variogram models of log air permeability were considered to represent data from single-hole pneumatic injection tests in six boreholes at the site. Unbiased maximum likelihood estimates of variogram and drift parameters were obtained for each model. Standard information criteria provided an ambiguous ranking of the models, which would not justify selecting one of them and discarding all others as is commonly done in practice. Instead, some of the models were eliminated based on their negligibly small updated probabilities and the rest were used to project the measured log permeabilities by kriging onto a rock volume containing the six boreholes. These four
Conceptual modeling of postmortem evaluation findings to describe dairy cow deaths.
McConnel, C S; Garry, F B; Hill, A E; Lombard, J E; Gould, D H
2010-01-01
Dairy cow mortality levels in the United States are excessive and increasing over time. To better define cause and effect and combat rising mortality, clearer definitions of the reasons that cows die need to be acquired through thorough necropsy-based postmortem evaluations. The current study focused on organizing information generated from postmortem evaluations into a monitoring system that is based on the fundamentals of conceptual modeling and that will potentially be translatable into on-farm relational databases. This observational study was conducted on 3 high-producing, commercial dairies in northern Colorado. Throughout the study period a thorough postmortem evaluation was performed by veterinarians on cows that died on each dairy. Postmortem data included necropsy findings, life-history features (e.g., birth date, lactation number, lactational and reproductive status), clinical history and treatments, and pertinent aspects of operational management that were subject to change and considered integral to the poor outcome. During this study, 174 postmortem evaluations were performed. Postmortem evaluation results were conceptually modeled to view each death within the context of the web of factors influencing the dairy and the cow. Categories were formulated describing mortality in terms of functional characteristics potentially amenable to easy performance evaluation, management oversight, and research. In total, 21 death categories with 7 category themes were created. Themes included specific disease processes with variable etiologies, failure of disease recognition or treatment, traumatic events, multifactorial failures linked to transition or negative energy balance issues, problems with feed management, miscellaneous events not amenable to prevention or treatment, and undetermined causes. Although postmortem evaluations provide the relevant information necessary for framing a cow's death, a restructuring of on-farm databases is needed to integrate this
Hirata, Yoshito; Aihara, Kazuyuki
2012-06-01
We introduce a low-dimensional description for a high-dimensional system, which is a piecewise affine model whose state space is divided by permutations. We show that the proposed model tends to predict wind speeds and photovoltaic outputs for the time scales from seconds to 100 s better than by global affine models. In addition, computations using the piecewise affine model are much faster than those of usual nonlinear models such as radial basis function models.
Białek, Agnieszka; Zagrodzki, Paweł; Tokarz, Andrzej
2016-03-01
We investigated how different doses of conjugated linoleic acids applied for various periods of time influence breast cancer risk and fatty acids profile in serum of rats treated or not with 7,12-dimethylbenz[a]anthracene (DMBA). We also search for interactions among parameters describing health conditions and cancer risk. Animals were divided into 18 groups with different diet modifications (vegetable oil, 1.0%, 2.0% additions of CLA) and different periods of supplementation. In groups treated with DMBA mammary adenocarcinomas appeared. Due to the complexity of experiment apart from statistical analysis a chemometric tool-Partial Least Square method was applied. Analysis of pairs of correlated parameters allowed to identify some regularities concerning the relationships between fatty acid profiles and clinical features of animals. Fatty acids profile was the result of prolonged exposure to high dose of CLA and DMBA administration. These two factors underlined the differences in fatty acids profiles among clusters of animals.
Order Parameters of the Dilute A Models
Warnaar, S O; Seaton, K A; Nienhuis, B
1993-01-01
The free energy and local height probabilities of the dilute A models with broken $\\Integer_2$ symmetry are calculated analytically using inversion and corner transfer matrix methods. These models possess four critical branches. The first two branches provide new realisations of the unitary minimal series and the other two branches give a direct product of this series with an Ising model. We identify the integrable perturbations which move the dilute A models away from the critical limit. Generalised order parameters are defined and their critical exponents extracted. The associated conformal weights are found to occur on the diagonal of the relevant Kac table. In an appropriate regime the dilute A$_3$ model lies in the universality class of the Ising model in a magnetic field. In this case we obtain the magnetic exponent $\\delta=15$ directly, without the use of scaling relations.
Testing Linear Models for Ability Parameters in Item Response Models
Glas, Cees A.W.; Hendrawan, Irene
2005-01-01
Methods for testing hypotheses concerning the regression parameters in linear models for the latent person parameters in item response models are presented. Three tests are outlined: A likelihood ratio test, a Lagrange multiplier test and a Wald test. The tests are derived in a marginal maximum like
A statistical case against the use of the Langmuir model for describing P sorption data
Sorption of P to soils is often investigated through batch experiments where sorption models are fit to the resultant sorption curve by least-squares regression. One of the most commonly used sorption models is the Langmuir model, a model which was originally developed for the study of gas sorption ...
A cohesive elements based model to describe fracture and cohesive healing in elastomers
Baldi, A.; Grande, A.M.; Bose, R.K.; Airoldi, A.; Garcia Espallargas, S.J.; Di Landro, L.; Van der Zwaag, S.
2013-01-01
Several polymeric systems with intrinsic Self-Healing (SH) capabilities have been reported in literature. Many of them showed healing upon contact across the crack interface. Different parameters such as contact time, temperature, pressure or chemical activity determine the degree of healing obtaine
Structural model requirements to describe microbial inactivation during a mild heat treatment.
Geeraerd, A H; Herremans, C H; Van Impe, J F
2000-09-10
The classical concept of D and z values, established for sterilisation processes, is unable to deal with the typical non-loglinear behaviour of survivor curves occurring during the mild heat treatment of sous vide or cook-chill food products. Structural model requirements are formulated, eliminating immediately some candidate model types. Promising modelling approaches are thoroughly analysed and, if applicable, adapted to the specific needs: two models developed by Casolari (1988), the inactivation model of Sapru et al. (1992), the model of Whiting (1993), the Baranyi and Roberts growth model (1994), the model of Chiruta et al. (1997), the model of Daughtry et al. (1997) and the model of Xiong et al. (1999). A range of experimental data of Bacillus cereus, Yersinia enterocolitica, Escherichia coli O157:H7, Listeria monocytogenes and Lactobacillus sake are used to illustrate the different models' performances. Moreover, a novel modelling approach is developed, fulfilling all formulated structural model requirements, and based on a careful analysis of literature knowledge of the shoulder and tailing phenomenon. Although a thorough insight in the occurrence of shoulders and tails is still lacking from a biochemical point of view, this newly developed model incorporates the possibility of a straightforward interpretation within this framework.
Directory of Open Access Journals (Sweden)
Dzierka M.
2015-12-01
Full Text Available In the paper, currently used methods for modeling the flow of the aqueous humor through eye structures are presented. Then a computational model based on rheological models of Newtonian and non-Newtonian fluids is proposed. The proposed model may be used for modeling the flow of the aqueous humor through the trabecular meshwork. The trabecular meshwork is modeled as an array of rectilinear parallel capillary tubes. The flow of Newtonian and non-Newtonian fluids is considered. As a results of discussion mathematical equations of permeability of porous media and velocity of fluid flow through porous media have been received.
Systematic parameter inference in stochastic mesoscopic modeling
Lei, Huan; Li, Zhen; Karniadakis, George
2016-01-01
We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are sparse. The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space....
Ternary interaction parameters in calphad solution models
Energy Technology Data Exchange (ETDEWEB)
Eleno, Luiz T.F., E-mail: luizeleno@usp.br [Universidade de Sao Paulo (USP), SP (Brazil). Instituto de Fisica; Schön, Claudio G., E-mail: schoen@usp.br [Universidade de Sao Paulo (USP), SP (Brazil). Computational Materials Science Laboratory. Department of Metallurgical and Materials Engineering
2014-07-01
For random, diluted, multicomponent solutions, the excess chemical potentials can be expanded in power series of the composition, with coefficients that are pressure- and temperature-dependent. For a binary system, this approach is equivalent to using polynomial truncated expansions, such as the Redlich-Kister series for describing integral thermodynamic quantities. For ternary systems, an equivalent expansion of the excess chemical potentials clearly justifies the inclusion of ternary interaction parameters, which arise naturally in the form of correction terms in higher-order power expansions. To demonstrate this, we carry out truncated polynomial expansions of the excess chemical potential up to the sixth power of the composition variables. (author)
Directory of Open Access Journals (Sweden)
GHOLAMALI TABARSA
2013-08-01
The importance and need for systematically evaluating and selecting potential foreign markets has been stressed by many researchers, and several models for selecting international markets had been prescribed. But, current model do not pass the test of reality, because they are not adapted with exporter decision making process and they are not consider important aspect of reality. Then, in this paper, we introduce a comprehensive international market attractiveness model that has four steps: demand attractiveness, attainment attractiveness, adaptation attractiveness and competition attractiveness. At last, according to tested model, a systematic support model is developed and is expected to introduce a new approach for Afghan exporters based on the upcoming suggestions.
An Identifiable State Model To Describe Light Intensity Influence on Microalgae Growth.
Bernardi, A; Perin, G; Sforza, E; Galvanin, F; Morosinotto, T; Bezzo, F
2014-04-23
Despite the high potential as feedstock for the production of fuels and chemicals, the industrial cultivation of microalgae still exhibits many issues. Yield in microalgae cultivation systems is limited by the solar energy that can be harvested. The availability of reliable models representing key phenomena affecting algae growth may help designing and optimizing effective production systems at an industrial level. In this work the complex influence of different light regimes on seawater alga Nannochloropsis salina growth is represented by first principles models. Experimental data such as in vivo fluorescence measurements are employed to develop the model. The proposed model allows description of all growth curves and fluorescence data in a reliable way. The model structure is assessed and modified in order to guarantee the model identifiability and the estimation of its parametric set in a robust and reliable way.
The water supercooled regime as described by four common water models
Malaspina, David C; Pereyra, Rodolfo G; Szleifer, Igal; Carignano, Marcelo A
2013-01-01
The temperature scale of simple water models in general does not coincide with the natural one. Therefore, in order to make a meaningful evaluation of different water models a temperature rescaling is necessary. In this paper we introduce a rescaling using the melting temperature and the temperature corresponding to the maximum of the heat capacity to evaluate four common water models (TIP4P-Ew, TIP4P-2005, TIP5P-Ew and Six-Sites) in the supercooled regime. Although all the models show the same general qualitative behavior, the TIP5P-Ew appears as the best representation of the supercooled regime when the rescaled temperature is used. We also analyze, using thermodynamic arguments, the critical nucleus size for ice growth. Finally, we speculate on the possible reasons why atomistic models do not usually crystalize while the coarse grained mW model do crystallize.
Modelling tourists arrival using time varying parameter
Suciptawati, P.; Sukarsa, K. G.; Kencana, Eka N.
2017-06-01
The importance of tourism and its related sectors to support economic development and poverty reduction in many countries increase researchers’ attentions to study and model tourists’ arrival. This work is aimed to demonstrate time varying parameter (TVP) technique to model the arrival of Korean’s tourists to Bali. The number of Korean tourists whom visiting Bali for period January 2010 to December 2015 were used to model the number of Korean’s tourists to Bali (KOR) as dependent variable. The predictors are the exchange rate of Won to IDR (WON), the inflation rate in Korea (INFKR), and the inflation rate in Indonesia (INFID). Observing tourists visit to Bali tend to fluctuate by their nationality, then the model was built by applying TVP and its parameters were approximated using Kalman Filter algorithm. The results showed all of predictor variables (WON, INFKR, INFID) significantly affect KOR. For in-sample and out-of-sample forecast with ARIMA’s forecasted values for the predictors, TVP model gave mean absolute percentage error (MAPE) as much as 11.24 percent and 12.86 percent, respectively.
Using a Model to Describe Students' Inductive Reasoning in Problem Solving
Canadas, Maria C.; Castro, Encarnacion; Castro, Enrique
2009-01-01
Introduction: We present some aspects of a wider investigation (Canadas, 2007), whose main objective is to describe and characterize inductive reasoning used by Spanish students in years 9 and 10 when they work on problems that involved linear and quadratic sequences. Method: We produced a test composed of six problems with different…
Mirror symmetry for two-parameter models, 1
Candelas, Philip; Font, A; Katz, S; Morrison, Douglas Robert Ogston; Candelas, Philip; Ossa, Xenia de la; Font, Anamaria; Katz, Sheldon; Morrison, David R.
1994-01-01
We study, by means of mirror symmetry, the quantum geometry of the K\\"ahler-class parameters of a number of Calabi-Yau manifolds that have $b_{11}=2$. Our main interest lies in the structure of the moduli space and in the loci corresponding to singular models. This structure is considerably richer when there are two parameters than in the various one-parameter models that have been studied hitherto. We describe the intrinsic structure of the point in the (compactification of the) moduli space that corresponds to the large complex structure or classical limit. The instanton expansions are of interest owing to the fact that some of the instantons belong to families with continuous parameters. We compute the Yukawa couplings and their expansions in terms of instantons of genus zero. By making use of recent results of Bershadsky et al. we compute also the instanton numbers for instantons of genus one. For particular values of the parameters the models become birational to certain models with one parameter. The co...
Zhang, J.; Nguyen Viet, T.; Wang, X.; Chen, H.; Gin, K. Y. H.
2014-12-01
The fate and transport processes of emerging contaminants in aquatic ecosystems are complex, which are not only determined by their own properties but also influenced by the environmental setting, physical, chemical and biological processes. A 3D-emerging contaminant model has been developed based on Delft3D water quality model and coupled with a hydrodynamic model and a catchment-scale 1D- hydrological and hydraulic model to study the possible fate and transport mechanisms of perfluorinated compounds (PFCs) in Marina Reservoir in Singapore. The main processes in the contaminant model include partitioning (among detritus, dissolved organic matter and phytoplankton), settling, resuspension and degradation. We used the integrated model to quantify the distribution of the total PFCs and two major components, namely perfluorooctanoate (PFOA) and perfluorooctane sulfonate (PFOS) in the water, sediments and organisms in the reservoir. The model yielded good agreement with the field measurements when evaluated based on the datasets in 2009 and 2010 as well as recent observations in 2013 and 2014. Our results elucidate that the model can be a useful tool to characterize the occurrence, sources, sinks and trends of PFCs both in the water column and in the sediments in the reservoir. Thisapproach provides a better understanding of mechanisms that influence the fate and transport of emerging contaminants and lays down a framework for future experiments to further explore how the dominant environmental factors change towards mitigation of emerging contaminants in the reservoirs.
Environmental Transport Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
M. Wasiolek
2004-09-10
This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment for the license application (TSPA-LA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA-LA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]) (TWP). This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA). This report is one of the five reports that develop input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the conceptual model and the mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed description of the model input parameters. The output of this report is used as direct input in the ''Nominal Performance Biosphere Dose Conversion Factor Analysis'' and in the ''Disruptive Event Biosphere Dose Conversion Factor Analysis'' that calculate the values of biosphere dose conversion factors (BDCFs) for the groundwater and volcanic ash exposure scenarios, respectively. The purpose of this analysis was to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or in volcanic ash). The analysis
How happy is your web browsing? A probabilistic model to describe user satisfaction
Banerji, Anirban
2009-01-01
We all go through scores of web-pages everyday, in search of required information. At times we become satisfied with the content of some pages, at time we fail to. An objective framework that attempts to model the user satisfaction when he searches for some desired piece of information, is essential for Human-Computer-Interaction. In the present work, a simple probabilistic model is constructed to achieve precisely the same. This realistic yet strictly mathematical study proposes a marker, the 'satisfaction retentivity quotient', to model the complex realm of user psychology as he attempts to find required information and forgets some bits of it here and there, simultaneously.
Treiber, Martin
2010-01-01
We propose a quantitative approach for calibrating and validating key features of traffic instabilities based on speed time series obtained from aggregated data of a series of neighboring stationary detectors. We apply the proposed criteria to historic traffic databases of several freeways in Germany containing about 400 occurrences of congestions thereby providing a reference for model calibration and quality assessment with respect to the spatiotemporal dynamics. First tests with microscopic and macroscopic models indicate that the criteria are both robust and discriminative, i.e., clearly distinguishes between models of higher and lower predictive power.
Parameter estimation, model reduction and quantum filtering
Chase, Bradley A.
This thesis explores the topics of parameter estimation and model reduction in the context of quantum filtering. The last is a mathematically rigorous formulation of continuous quantum measurement, in which a stream of auxiliary quantum systems is used to infer the state of a target quantum system. Fundamental quantum uncertainties appear as noise which corrupts the probe observations and therefore must be filtered in order to extract information about the target system. This is analogous to the classical filtering problem in which techniques of inference are used to process noisy observations of a system in order to estimate its state. Given the clear similarities between the two filtering problems, I devote the beginning of this thesis to a review of classical and quantum probability theory, stochastic calculus and filtering. This allows for a mathematically rigorous and technically adroit presentation of the quantum filtering problem and solution. Given this foundation, I next consider the related problem of quantum parameter estimation, in which one seeks to infer the strength of a parameter that drives the evolution of a probe quantum system. By embedding this problem in the state estimation problem solved by the quantum filter, I present the optimal Bayesian estimator for a parameter when given continuous measurements of the probe system to which it couples. For cases when the probe takes on a finite number of values, I review a set of sufficient conditions for asymptotic convergence of the estimator. For a continuous-valued parameter, I present a computational method called quantum particle filtering for practical estimation of the parameter. Using these methods, I then study the particular problem of atomic magnetometry and review an experimental method for potentially reducing the uncertainty in the estimate of the magnetic field beyond the standard quantum limit. The technique involves double-passing a probe laser field through the atomic system, giving
Imanidis, Georgios; Luetolf, Peter
2006-07-01
An extended model for iontophoretic enhancement of transdermal drug permeation under constant voltage is described based on the previously modified Nernst-Planck equation, which included the effect of convective solvent flow. This model resulted in an analytical expression for the enhancement factor as a function of applied voltage, convective flow velocity due to electroosmosis, ratio of lipid to aqueous pathway passive permeability, and weighted average net ionic valence of the permeant in the aqueous epidermis domain. The shift of pH in the epidermis compared to bulk caused by the electrical double layer at the lipid-aqueous domain interface was evaluated using the Poisson-Boltzmann equation. This was solved numerically for representative surface charge densities and yielded pH differences between bulk and epidermal aqueous domain between 0.05 and 0.4 pH units. The developed model was used to analyze the experimental enhancement of an amphoteric weak electrolyte measured in vitro using human cadaver epidermis and a voltage of 250 mV at different pH values. Parameter values characterizing the involved factors were determined that yielded the experimental enhancement factors and passive permeability coefficients at all pH values. The model provided a very good agreement between experimental and calculated enhancement and passive permeability. The deduced parameters showed (i) that the pH shift in the aqueous permeation pathway had a notable effect on the ionic valence and the partitioning of the drug in this domain for a high surface charge density and depending on the pK(a) and pI of the drug in relation to the bulk pH; (ii) the magnitude and the direction of convective transport due to electroosmosis typically reflected the density and sign, respectively, of surface charge of the tissue and its effect on enhancement was substantial for bulk pH values differing from the pI of epidermal tissue; (iii) the aqueous pathway predominantly determined passive
Inhalation Exposure Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
K. Rautenstrauch
2004-09-10
This analysis is one of 10 reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. Inhalation Exposure Input Parameters for the Biosphere Model is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the Technical Work Plan for Biosphere Modeling and Expert Support (BSC 2004 [DIRS 169573]). This analysis report defines and justifies values of mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception.
Environmental Transport Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
M. A. Wasiolek
2003-06-27
This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (TWP) (BSC 2003 [163602]). Some documents in Figure 1-1 may be under development and not available when this report is issued. This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA), but access to the listed documents is not required to understand the contents of this report. This report is one of the reports that develops input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2003 [160699]) describes the conceptual model, the mathematical model, and the input parameters. The purpose of this analysis is to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or volcanic ash). The analysis was performed in accordance with the TWP (BSC 2003 [163602]). This analysis develops values of parameters associated with many features, events, and processes (FEPs) applicable to the reference biosphere (DTN: M00303SEPFEPS2.000 [162452]), which are addressed in the biosphere model (BSC 2003 [160699]). The treatment of these FEPs is described in BSC (2003 [160699
A simple geometrical model describing shapes of soap films suspended on two rings
Herrmann, Felix J.; Kilvington, Charles D.; Wildenberg, Rebekah L.; Camacho, Franco E.; Walecki, Wojciech J.; Walecki, Peter S.; Walecki, Eve S.
2016-09-01
We measured and analysed the stability of two types of soap films suspended on two rings using the simple conical frusta-based model, where we use common definition of conical frustum as a portion of a cone that lies between two parallel planes cutting it. Using frusta-based we reproduced very well-known results for catenoid surfaces with and without a central disk. We present for the first time a simple conical frusta based spreadsheet model of the soap surface. This very simple, elementary, geometrical model produces results surprisingly well matching the experimental data and known exact analytical solutions. The experiment and the spreadsheet model can be used as a powerful teaching tool for pre-calculus and geometry students.
A linear canal-otolith interaction model to describe the human vestibulo-ocular reflex.
Crane, B T; Demer, J L
1999-08-01
A control systems model of the vestibulo-ocular reflex (VOR) originally derived for yaw rotation about an eccentric axis (Crane et al. 1997) was applied to data collected during ambulation and dynamic posturography. The model incorporates a linear summation of an otolith response due to head translation scaled by target distance, adding to a semi-circular canal response that depends only on angular head rotation. The results of the model were compared with human experimental data by supplying head angular velocity as determined by magnetic search coil recording as the input for the canal branch of the model and supplying linear acceleration as determined by flux gate magnetometer measurements of otolith position. The model was fit to data by determining otolith weighting that enabled the model to best fit the data. We fit to the model experimental data from normal subjects who were: standing quietly, walking, running, or making active sinusoidal head movements. We also fit data obtained during dynamic posturography tasks of: standing on a platform sliding in a horizontal plane at 0.2 Hz, standing directly on a platform tilting at 0.1 Hz, and standing on the tilting platform buffered by a 5-cm thick foam rubber cushion. Each task was done with the subject attending a target approximately 500, 100, or 50 cm distant, both in light and darkness. The model accurately predicted the observed VOR response during each test. Greater otolith weighting was required for near targets for nearly all activities, consistent with weights for the otolith component found in previous studies employing imposed rotations. The only exceptions were for vertical axis motion during standing, sliding, and tilting when the platform was buffered with foam rubber. In the horizontal axis, the model always fit near target data better with a higher otolith component. Otolith weights were similar with the target visible and in darkness. The model predicts eye movement during both passive whole
Describing the strongly interacting quark-gluon plasma through the Friedberg-Lee model
Shu, Song; Li, Jia-Rong
2010-10-01
The Friedberg-Lee (FL) model is studied at finite temperature and density. The soliton solutions of the FL model in the deconfinement phase transition are solved and thoroughly discussed for certain boundary conditions. We indicate that the solitons before and after the deconfinement have different physical meanings: the soliton before deconfinement represents hadrons, while the soliton after the deconfinement represents the bound state of quarks which leads to a strongly interacting quark-gluon plasma phase. The corresponding phase diagram is given.
A Stochastic Markov Chain Model to Describe Lung Cancer Growth and Metastasis
Newton, Paul K.; Jeremy Mason; Kelly Bethel; Bazhenova, Lyudmila A.; Jorge Nieva; Peter Kuhn
2012-01-01
A stochastic Markov chain model for metastatic progression is developed for primary lung cancer based on a network construction of metastatic sites with dynamics modeled as an ensemble of random walkers on the network. We calculate a transition matrix, with entries (transition probabilities) interpreted as random variables, and use it to construct a circular bi-directional network of primary and metastatic locations based on postmortem tissue analysis of 3827 autopsies on untreated patients d...
Alvaro, M; Bonilla, L L; Carretero, M; Melnik, R V N; Prabhakar, S
2013-08-21
In this paper we develop a kinetic model for the analysis of semiconductor superlattices, accounting for quantum effects. The model consists of a Boltzmann-Poisson type system of equations with simplified Bhatnagar-Gross-Krook collisions, obtained from the general time-dependent Schrödinger-Poisson model using Wigner functions. This system for superlattice transport is supplemented by the quantum mechanical part of the model based on the Ben-Daniel-Duke form of the Schrödinger equation for a cylindrical superlattice of finite radius. The resulting energy spectrum is used to characterize the Fermi-Dirac distribution that appears in the Bhatnagar-Gross-Krook collision, thereby coupling the quantum mechanical and kinetic parts of the model. The kinetic model uses the dispersion relation obtained by the generalized Kronig-Penney method, and allows us to estimate radii of quantum wire superlattices that have the same miniband widths as in experiments. It also allows us to determine more accurately the time-dependent characteristics of superlattices, in particular their current density. Results, for several experimentally grown superlattices, are discussed in the context of self-sustained coherent oscillations of the current density which are important in an increasing range of current and potential applications.
Baxter, Susan K; Blank, Lindsay; Woods, Helen Buckley; Payne, Nick; Rimmer, Melanie; Goyder, Elizabeth
2014-05-10
There is increasing interest in innovative methods to carry out systematic reviews of complex interventions. Theory-based approaches, such as logic models, have been suggested as a means of providing additional insights beyond that obtained via conventional review methods. This paper reports the use of an innovative method which combines systematic review processes with logic model techniques to synthesise a broad range of literature. The potential value of the model produced was explored with stakeholders. The review identified 295 papers that met the inclusion criteria. The papers consisted of 141 intervention studies and 154 non-intervention quantitative and qualitative articles. A logic model was systematically built from these studies. The model outlines interventions, short term outcomes, moderating and mediating factors and long term demand management outcomes and impacts. Interventions were grouped into typologies of practitioner education, process change, system change, and patient intervention. Short-term outcomes identified that may result from these interventions were changed physician or patient knowledge, beliefs or attitudes and also interventions related to changed doctor-patient interaction. A range of factors which may influence whether these outcomes lead to long term change were detailed. Demand management outcomes and intended impacts included content of referral, rate of referral, and doctor or patient satisfaction. The logic model details evidence and assumptions underpinning the complex pathway from interventions to demand management impact. The method offers a useful addition to systematic review methodologies. PROSPERO registration number: CRD42013004037.
Directory of Open Access Journals (Sweden)
Gholam Ali Tabarsa
2013-01-01
Full Text Available Literature review in international market attractiveness evaluation and operational practice inAfghanistan demonstrate that there are two approaches in international market selection:expansion and systematic approach. In expansion approach, firms gradually enter lowgeographical and psychic distance markets. But, in systematic approach, by considering somefactors and models, firms systematically evaluate and select foreign market(s. Theimportance and need for systematically evaluating and selecting potential foreign markets hasbeen stressed by many researchers, and several models for selecting international markets hadbeen prescribed. But, current models do not pass the test of reality, because they are notadapted with exporters’ decision making process and they do not consider the importantaspects of reality. Then, in this paper, we introduce a comprehensive international marketattractiveness model that has four steps: demand attractiveness, attainment attractiveness,adaptation attractiveness, and competition attractiveness. At last, according to tested model, asystematic support model is developed and is expected to introduce a new approach forAfghan exporters based on the upcoming suggestions.
Pan, Xu; Cornelissen, Johannes H C; Zhao, Wei-Wei; Liu, Guo-Fang; Hu, Yu-Kun; Prinzing, Andreas; Dong, Ming; Cornwell, William K
2014-09-01
Leaf litter decomposability is an important effect trait for ecosystem functioning. However, it is unknown how this effect trait evolved through plant history as a leaf 'afterlife' integrator of the evolution of multiple underlying traits upon which adaptive selection must have acted. Did decomposability evolve in a Brownian fashion without any constraints? Was evolution rapid at first and then slowed? Or was there an underlying mean-reverting process that makes the evolution of extreme trait values unlikely? Here, we test the hypothesis that the evolution of decomposability has undergone certain mean-reverting forces due to strong constraints and trade-offs in the leaf traits that have afterlife effects on litter quality to decomposers. In order to test this, we examined the leaf litter decomposability and seven key leaf traits of 48 tree species in the temperate area of China and fitted them to three evolutionary models: Brownian motion model (BM), Early burst model (EB), and Ornstein-Uhlenbeck model (OU). The OU model, which does not allow unlimited trait divergence through time, was the best fit model for leaf litter decomposability and all seven leaf traits. These results support the hypothesis that neither decomposability nor the underlying traits has been able to diverge toward progressively extreme values through evolutionary time. These results have reinforced our understanding of the relationships between leaf litter decomposability and leaf traits in an evolutionary perspective and may be a helpful step toward reconstructing deep-time carbon cycling based on taxonomic composition with more confidence.
Neuronal spike timing adaptation described with a fractional leaky integrate-and-fire model.
Directory of Open Access Journals (Sweden)
Wondimu Teka
2014-03-01
Full Text Available The voltage trace of neuronal activities can follow multiple timescale dynamics that arise from correlated membrane conductances. Such processes can result in power-law behavior in which the membrane voltage cannot be characterized with a single time constant. The emergent effect of these membrane correlations is a non-Markovian process that can be modeled with a fractional derivative. A fractional derivative is a non-local process in which the value of the variable is determined by integrating a temporal weighted voltage trace, also called the memory trace. Here we developed and analyzed a fractional leaky integrate-and-fire model in which the exponent of the fractional derivative can vary from 0 to 1, with 1 representing the normal derivative. As the exponent of the fractional derivative decreases, the weights of the voltage trace increase. Thus, the value of the voltage is increasingly correlated with the trajectory of the voltage in the past. By varying only the fractional exponent, our model can reproduce upward and downward spike adaptations found experimentally in neocortical pyramidal cells and tectal neurons in vitro. The model also produces spikes with longer first-spike latency and high inter-spike variability with power-law distribution. We further analyze spike adaptation and the responses to noisy and oscillatory input. The fractional model generates reliable spike patterns in response to noisy input. Overall, the spiking activity of the fractional leaky integrate-and-fire model deviates from the spiking activity of the Markovian model and reflects the temporal accumulated intrinsic membrane dynamics that affect the response of the neuron to external stimulation.
What is the "best" atomic charge model to describe through-space charge-transfer excitations?
Jacquemin, Denis; Le Bahers, Tangui; Adamo, Carlo; Ciofini, Ilaria
2012-04-28
We investigate the efficiency of several partial atomic charge models (Mulliken, Hirshfeld, Bader, Natural, Merz-Kollman and ChelpG) for investigating the through-space charge-transfer in push-pull organic compounds with Time-Dependent Density Functional Theory approaches. The results of these models are compared to benchmark values obtained by determining the difference of total densities between the ground and excited states. Both model push-pull oligomers and two classes of "real-life" organic dyes (indoline and diketopyrrolopyrrole) used as sensitisers in solar cell applications have been considered. Though the difference of dipole moments between the ground and excited states is reproduced by most approaches, no atomic charge model is fully satisfactory for reproducing the distance and amount of charge transferred that are provided by the density picture. Overall, the partitioning schemes fitting the electrostatic potential (e.g. Merz-Kollman) stand as the most consistent compromises in the framework of simulating through-space charge-transfer, whereas the other models tend to yield qualitatively inconsistent values.
A model, describing the influence of water management alternatives on dike stability
Lambert, J. W. M.; Vastenburg, E.; Roelofsen, F. J.
2015-11-01
The awareness is rising that economic effects of Land Subsidence are high. Nevertheless, quantifying these economic losses is difficult and, as far as known, not yet done in a sophisticated way. Also, to be able to decide about future strategies, for example to avoid or decrease subsidence, it is necessary to know the financial consequences of measures and possible solutions. As a first step to quantify these economic effects, a MODFLOW-SCR (coupled MODFLOW-Settlements model) is coupled with the model DAM. Based on the local stratigraphy, the shape and composition of the existing dike or levee, the level of the surface water and the surface level, macro-stability of the dike is calculated and - if the dike does not meet the required stability - adaptions are proposed. The model enables to separate effects that are caused by sea-level rise and the effects of subsidence. Coupling the DAM model with an economic model to calculate costs of these adaptions is under construction.
Improvement of Continuous Hydrologic Models and HMS SMA Parameters Reduction
Rezaeian Zadeh, Mehdi; Zia Hosseinipour, E.; Abghari, Hirad; Nikian, Ashkan; Shaeri Karimi, Sara; Moradzadeh Azar, Foad
2010-05-01
Hydrological models can help us to predict stream flows and associated runoff volumes of rainfall events within a watershed. There are many different reasons why we need to model the rainfall-runoff processes of for a watershed. However, the main reason is the limitation of hydrological measurement techniques and the costs of data collection at a fine scale. Generally, we are not able to measure all that we would like to know about a given hydrological systems. This is very particularly the case for ungauged catchments. Since the ultimate aim of prediction using models is to improve decision-making about a hydrological problem, therefore, having a robust and efficient modeling tool becomes an important factor. Among several hydrologic modeling approaches, continuous simulation has the best predictions because it can model dry and wet conditions during a long-term period. Continuous hydrologic models, unlike event based models, account for a watershed's soil moisture balance over a long-term period and are suitable for simulating daily, monthly, and seasonal streamflows. In this paper, we describe a soil moisture accounting (SMA) algorithm added to the hydrologic modeling system (HEC-HMS) computer program. As is well known in the hydrologic modeling community one of the ways for improving a model utility is the reduction of input parameters. The enhanced model developed in this study is applied to Khosrow Shirin Watershed, located in the north-west part of Fars Province in Iran, a data limited watershed. The HMS SMA algorithm divides the potential path of rainfall onto a watershed into five zones. The results showed that the output of HMS SMA is insensitive with the variation of many parameters such as soil storage and soil percolation rate. The study's objective is to remove insensitive parameters from the model input using Multi-objective sensitivity analysis. Keywords: Continuous Hydrologic Modeling, HMS SMA, Multi-objective sensitivity analysis, SMA Parameters
A Mathematic Model That Describes Modes of MdSGHV Transmission within House Fly Populations
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Celeste R. Vallejo
2013-11-01
Full Text Available In this paper it is proposed that one potential component by which the Musca domestica salivary gland hypertrophy virus (MdSGHV infects individual flies is through cuticular damage. Breaks in the cuticle allow entry of the virus into the hemocoel causing the infection. Male flies typically have a higher rate of infection and a higher rate of cuticular damage than females. A model for the transmission of MdSGHV was formulated assuming several potential and recognized means of transmission. The model yields results that are in agreement with field data that measured the infection rate in house flies on dairy farms in Florida. The results from this model indicate that MdSGHV will be maintained at a stable rate within house fly populations and support the future use of MdSGHV as a birth control agent in house fly management.
Describing the Neuron Axons Network of the Human Brain by Continuous Flow Models
Hizanidis, J.; Katsaloulis, P.; Verganelakis, D. A.; Provata, A.
2014-12-01
The multifractal spectrum Dq (Rényi dimensions) is used for the analysis and comparison between the Neuron Axons Network (NAN) of healthy and pathological human brains because it conveys information about the statistics in many scales, from the very rare to the most frequent network configurations. Comparison of the Fractional Anisotropy Magnetic Resonance Images between healthy and pathological brains is performed with and without noise reduction. Modelling the complex structure of the NAN in the human brain is undertaken using the dynamics of the Lorenz model in the chaotic regime. The Lorenz multifractal spectra capture well the human brain characteristics in the large negative q's which represent the rare network configurations. In order to achieve a closer approximation in the positive part of the spectrum (q > 0) two independent modifications are considered: a) redistribution of the dense parts of the Lorenz model's phase space into their neighbouring areas and b) inclusion of additive uniform noise in the Lorenz model. Both modifications, independently, drive the Lorenz spectrum closer to the human NAN one in the positive q region without destroying the already good correspondence of the negative spectra. The modelling process shows that the unmodified Lorenz model in its full chaotic regime has a phase space distribution with high fluctuations in its dense parts, while the fluctuations in the human brain NAN are smoother. The induced modifications (phase space redistribution or additive noise) moderate the fluctuations only in the positive part of the Lorenz spectrum leading to a faithful representation of the human brain axons network in all scales.
[Application of Bayesian spatio-temporal modeling in describing the brucellosis infections].
Zheng, Yang; Feng, Zi-jian; Li, Xiao-song
2011-01-01
Based on the number of brucellosis cases reported from the national infectious diseases reporting system in Inner Mongolia from 2000 to 2007, a model was developed. Theories of spatial statistics were used, together with knowledge on infectious disease epidemiology and the frame of Bayesian statistics, before the Bayesian spatio-temporal models were respectively set. The effects of space, time, space-time and the relative covariates were also considered. These models were applied to analyze the brucellosis distribution and time trend in Inner Mongolia during 2000-2007. The results of Bayesian spatio-temporal models was expressed by mapping of the disease and compared to the conventional statistical methods. Results showed that the Bayesian models, under consideration of space-time effect and the relative covariates (deviance information criterion, DIC=2388.000), seemed to be the best way to serve the purpose. The county-level spatial correlation of brucellosis epidemics was positive and quite strong in Inner Mongolia. However, the spatial correlation varied with time and the coefficients ranged from 0.968 to 0.973, having a weakening trend during 2000-2007. Types of region and number of stock (cattle and sheep) might be related to the brucellosis epidemics, and the effect on the number of cattle and sheep changed by year. Compared to conventional statistical methods, Bayesian spatio-temporal modeling could precisely estimate the incidence relative risk and was an important tool to analyze the epidemic distribution patterns of infectious diseases and to estimate the incidence relative risk.
The Rotation of Io Described by the Poincaré Model
Noyelles, Benoit
2012-05-01
We here study the rotation of the satellite of Jupiter Io, in considering core-mantle coupling. This satellite is particularly interesting because it experiences strong tidal dissipation inducing a very active surface. Moreover, the flow of the fluid inside its core is reputed to be unstable. We first elaborate 10 different models of the interior of Io, considering either a Fe or a FeS core, using measured values of the gravity coefficients J2 and C22, before studying their response to the 4-degrees of freedom Poincaré-Hough model. We then study the stability of the flow of the fluid. We show that these different models have a quite small influence on the longitudinal librations and the equilibrium obliquity, with amplitude of about 30 and 8 seconds of arc respectively, because of the relatively small inertia of the core. However, sulfur in the core can pump the tilt of the fluid constituting the core. Moreover, in all our models the flow in unstable with a growth time of about 1,000 years for a Fe core and 5,000 years for a FeS one.
Predictive model to describe water migration in cellular solid foods during storage
Voogt, J.A.; Hirte, A.; Meinders, M.B.J.
2011-01-01
BACKGROUND: Water migration in cellular solid foods during storage causes loss of crispness. To improve crispness retention, physical understanding of this process is needed. Mathematical models are suitable tools to gain this physical knowledge. RESULTS: Water migration in cellular solid foods
A pairwise maximum entropy model accurately describes resting-state human brain networks.
Watanabe, Takamitsu; Hirose, Satoshi; Wada, Hiroyuki; Imai, Yoshio; Machida, Toru; Shirouzu, Ichiro; Konishi, Seiki; Miyashita, Yasushi; Masuda, Naoki
2013-01-01
The resting-state human brain networks underlie fundamental cognitive functions and consist of complex interactions among brain regions. However, the level of complexity of the resting-state networks has not been quantified, which has prevented comprehensive descriptions of the brain activity as an integrative system. Here, we address this issue by demonstrating that a pairwise maximum entropy model, which takes into account region-specific activity rates and pairwise interactions, can be robustly and accurately fitted to resting-state human brain activities obtained by functional magnetic resonance imaging. Furthermore, to validate the approximation of the resting-state networks by the pairwise maximum entropy model, we show that the functional interactions estimated by the pairwise maximum entropy model reflect anatomical connexions more accurately than the conventional functional connectivity method. These findings indicate that a relatively simple statistical model not only captures the structure of the resting-state networks but also provides a possible method to derive physiological information about various large-scale brain networks.
Rajagopal, K. R.; Srinivasa, A. R.
2016-08-01
The aim of this paper is to develop a new unified class of 3D nonlinear anisotropic finite deformation inelasticity model that (1) exhibits rate-independent or dependent hysteretic response (i.e., response wherein reversal of the external stimuli does not cause reversal of the path in state space) with or without yield surfaces. The hysteresis persists with quasistatic loading. (2) Encompasses a wide range of different types of inelasticity models (such as Mullins effect in rubber, rock and soil mechanics, traditional metal plasticity, hysteretic behavior of shape memory materials) into a simple unified framework that is relatively easy to implement in computational schemes and (3) does not require any a priori particular notion of plastic strain or yield function. The core idea behind the approach is the development of an system of implicit rate equations that allow for the continuity of the response but with different rates along different directions. The theory, which is in purely mechanical setting, subsumes and generalizes many commonly used approaches for hypoelasticity and rate-independent plasticity. We illustrate its capability by modeling the Mullins effect which is the inelastic behavior of certain rubbery materials. We are able to simulate the entire cyclic response without the use of additional internal variables, i.e., the entire response is modeled by using an implicit function of stress and strain measures and their rates.
Predictive model to describe water migration in cellular solid foods during storage
Voogt, J.A.; Hirte, A.; Meinders, M.B.J.
2011-01-01
Background: Water migration in cellular solid foods during storage causes loss of crispness. To improve crispness retention, physical understanding of this process is needed. Mathematical models are suitable tools to gain this physical knowledge. Results: Water migration in cellular solid foods invo
Using a Structural Equation Model to Describe the Infusion of Civic Engagement in the Campus Culture
Billings, Meredith S.; Terkla, Dawn Geronimo
2011-01-01
This study assesses whether Tufts University's campus culture was successful at infusing civic-mindedness in all undergraduates. A structural equation model was developed, and findings revealed that the campus environment had a significant positive impact on civic values and beliefs and a positive indirect effect on civic engagement activities.…
Predictive model to describe water migration in cellular solid foods during storage
Voogt, J.A.; Hirte, A.; Meinders, M.B.J.
2011-01-01
BACKGROUND: Water migration in cellular solid foods during storage causes loss of crispness. To improve crispness retention, physical understanding of this process is needed. Mathematical models are suitable tools to gain this physical knowledge. RESULTS: Water migration in cellular solid foods invo
Benchmarking of numerical models describing the dispersion of radionuclides in the Arctic Seas
DEFF Research Database (Denmark)
Scott, E.M.; Gurbutt, P.; Harms, I.
1997-01-01
) development of realistic and reliable assessment models for the dispersal of radioactive contaminants both within, and from, the Arctic ocean; and (2) evaluation of the contributions of different transfer mechanisms to contaminant dispersal and hence, ultimately, to the risks to human health and environment...
Wijsman, J.W.M.; Smaal, A.C.
2011-01-01
A Dynamic Energy Budget (DEB) model for cockles is presented and calibrated using detailed data on cockle growth and water quality in the Oosterschelde. Cockles in the intertidal areas of the Oosterschelde have an important function as a food source for wading birds and as such for the natural value
An active oscillator model describes the statistics of spontaneous otoacoustic emissions.
Fruth, Florian; Jülicher, Frank; Lindner, Benjamin
2014-08-19
Even in the absence of external stimulation, the cochleas of most humans emit very faint sounds below the threshold of hearing, sounds that are known as spontaneous otoacoustic emissions. They are a signature of the active amplification mechanism in the cochlea. Emissions occur at frequencies that are unique for an individual and change little over time. The statistics of a population of ears exhibit characteristic features such as a preferred relative frequency distance between emissions (interemission intervals). We propose a simplified cochlea model comprising an array of active nonlinear oscillators coupled both hydrodynamically and viscoelastically. The oscillators are subject to a weak spatial disorder that lends individuality to the simulated cochlea. Our model captures basic statistical features of the emissions: distributions of 1), emission frequencies; 2), number of emissions per ear; and 3), interemission intervals. In addition, the model reproduces systematic changes of the interemission intervals with frequency. We show that the mechanism for the preferred interemission interval in our model is the occurrence of synchronized clusters of oscillators.
A mechanistic model to describe the spread of phocid distemper virus
Koeijer, A.A. de; Diekmann, O.; Reijnders, P.J.H.
1995-01-01
1. The 1988 epizootic among seals in N.W. Europe led to the death of more than half of the population. Several researchers have fitted data from the epidemic with the Kermack and McKendrick model for disease spread. 2. We argue that for animals living in herds or colonies, like seals, the mutual con
Exponential law as a more compatible model to describe orbits of planetary systems
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M Saeedi
2012-12-01
Full Text Available According to the Titus-Bode law, orbits of planets in the solar system obey a geometric progression. Many investigations have been launched to improve this law. In this paper, we apply square and exponential models to planets of solar system, moons of planets, and some extra solar systems, and compare them with each other.
Parameter optimization in S-system models
Directory of Open Access Journals (Sweden)
Vasconcelos Ana
2008-04-01
Full Text Available Abstract Background The inverse problem of identifying the topology of biological networks from their time series responses is a cornerstone challenge in systems biology. We tackle this challenge here through the parameterization of S-system models. It was previously shown that parameter identification can be performed as an optimization based on the decoupling of the differential S-system equations, which results in a set of algebraic equations. Results A novel parameterization solution is proposed for the identification of S-system models from time series when no information about the network topology is known. The method is based on eigenvector optimization of a matrix formed from multiple regression equations of the linearized decoupled S-system. Furthermore, the algorithm is extended to the optimization of network topologies with constraints on metabolites and fluxes. These constraints rejoin the system in cases where it had been fragmented by decoupling. We demonstrate with synthetic time series why the algorithm can be expected to converge in most cases. Conclusion A procedure was developed that facilitates automated reverse engineering tasks for biological networks using S-systems. The proposed method of eigenvector optimization constitutes an advancement over S-system parameter identification from time series using a recent method called Alternating Regression. The proposed method overcomes convergence issues encountered in alternate regression by identifying nonlinear constraints that restrict the search space to computationally feasible solutions. Because the parameter identification is still performed for each metabolite separately, the modularity and linear time characteristics of the alternating regression method are preserved. Simulation studies illustrate how the proposed algorithm identifies the correct network topology out of a collection of models which all fit the dynamical time series essentially equally well.
Modeling of Parameters of Subcritical Assembly SAD
Petrochenkov, S; Puzynin, I
2005-01-01
The accepted conceptual design of the experimental Subcritical Assembly in Dubna (SAD) is based on the MOX core with a nominal unit capacity of 25 kW (thermal). This corresponds to the multiplication coefficient $k_{\\rm eff} =0.95$ and accelerator beam power 1 kW. A subcritical assembly driven with the existing 660 MeV proton accelerator at the Joint Institute for Nuclear Research has been modelled in order to make choice of the optimal parameters for the future experiments. The Monte Carlo method was used to simulate neutron spectra, energy deposition and doses calculations. Some of the calculation results are presented in the paper.
Directory of Open Access Journals (Sweden)
Lezhnin Sergey
2017-01-01
Full Text Available The two-temperature model of the outflow from a vessel with initial supercritical parameters of medium has been realized. The model uses thermodynamic non-equilibrium relaxation approach to describe phase transitions. Based on a new asymptotic model for computing the relaxation time, the outflow of water with supercritical initial pressure and super- and subcritical temperatures has been calculated.
Shekhar, Karthik; Ferguson, Andrew L; Barton, John P; Kardar, Mehran; Chakraborty, Arup K
2013-01-01
Mutational escape from vaccine induced immune responses has thwarted the development of a successful vaccine against AIDS, whose causative agent is HIV, a highly mutable virus. Knowing the virus' fitness as a function of its proteomic sequence can enable rational design of potent vaccines, as this information can focus vaccine induced immune responses to target mutational vulnerabilities of the virus. Spin models have been proposed as a means to infer intrinsic fitness landscapes of HIV proteins from patient-derived viral protein sequences. These sequences are the product of non-equilibrium viral evolution driven by patient-specific immune responses, and are subject to phylogenetic constraints. How can such sequence data allow inference of intrinsic fitness landscapes? We combined computer simulations and variational theory \\'{a} la Feynman to show that, in most circumstances, spin models inferred from patient-derived viral sequences reflect the correct rank order of the fitness of mutant viral strains. Our f...
A benchmark simulation model to describe plant-wide phosphorus transformations in WWTPs
DEFF Research Database (Denmark)
Flores-Alsina, Xavier; Ikumi, D.; Kazadi-Mbamba, C.
It is more than 10 years since the publication of the BSM1 technical report (Copp, 2002). The main objective of BSM1 was to create a platform for benchmarking C and N removal strategies in activated sludge systems. The initial platform evolved into BSM1_LT and BSM2, which allowed for the evaluati...... to be addressed and presents the simulation results of the first software prototype....... of monitoring and plant-wide control strategies, respectively. In addition, researchers working within the IWA Task Group on Benchmarking of Control Strategies for Wastewater Treatment Plants developed other BSM related spin-off products, such as the dynamic influent generator, sensor/actuators/fault models......) pursue biological/chemical phosphorus removal. However, realistic descriptions of combined C, N and P removal, adds a major, but unavoidable degree of complexity in wastewater treatment process models. This paper identifies and discusses important issues that need to be addressed to upgrade the BSM2...
Shekhar, Karthik; Ruberman, Claire F.; Ferguson, Andrew L.; Barton, John P.; Kardar, Mehran; Chakraborty, Arup K.
2013-12-01
Mutational escape from vaccine-induced immune responses has thwarted the development of a successful vaccine against AIDS, whose causative agent is HIV, a highly mutable virus. Knowing the virus' fitness as a function of its proteomic sequence can enable rational design of potent vaccines, as this information can focus vaccine-induced immune responses to target mutational vulnerabilities of the virus. Spin models have been proposed as a means to infer intrinsic fitness landscapes of HIV proteins from patient-derived viral protein sequences. These sequences are the product of nonequilibrium viral evolution driven by patient-specific immune responses and are subject to phylogenetic constraints. How can such sequence data allow inference of intrinsic fitness landscapes? We combined computer simulations and variational theory á la Feynman to show that, in most circumstances, spin models inferred from patient-derived viral sequences reflect the correct rank order of the fitness of mutant viral strains. Our findings are relevant for diverse viruses.
Alfonso, M.; Cymberknop, L.; Armentano, R.; Pessana, F.; Wray, S.; Legnani, W.
2016-04-01
The representation of blood pressure pulse as a combination of solitons captures many of the phenomena observed during its propagation along the systemic circulation. The aim of this work is to analyze the applicability of a compartmental model for propagation regarding the pressure pulse amplification associated with arterial aging. The model was applied to blood pressure waveforms that were synthesized using solitons, and then validated by waveforms obtained from individuals from differentiated age groups. Morphological changes were verified in the blood pressure waveform as a consequence of the aging process (i.e. due to the increase in arterial stiffness). These changes are the result of both a nonlinear interaction and the phenomena present in the propagation of nonlinear mechanic waves.
Describing the structure of a research literature: spatial diffusion modelling in geography
Gatrell, A C
1984-01-01
A description of the structure of research specialities requires the definition of a series of sets and relations. A set of papers concerned with spatial diffusion modelling is defined, and the structure of the citation relation defined on that set is explored. A detailed reading of the texts of the papers allows us to extract a series of 'terms' (concepts, techniques, and so on), and problems of structuring these in a hierarchical scheme are discussed. The relation of papers to terms is then...
Simulation Evidence for Nonlocal Interface Models: Two Correlation Lengths Describe Complete Wetting
Pang, Lijun; Landau, D. P.; Binder, K.
2011-06-01
Monte Carlo simulations of (fluctuating) interfaces in Ising models confined between competing walls at temperatures above the wetting transition are presented and various correlation functions probing the interfacial fluctuation are computed. Evidence for the nonlocal interface Hamiltonian approach of A. O. Parry et al. [Phys. Rev. Lett. 93, 086104 (2004)PRLTAO0031-900710.1103/PhysRevLett.93.086104] is given. In particular, we show that two correlation lengths exist with different dependence on the distance D between the walls.
Directory of Open Access Journals (Sweden)
Sette Alessandro
2005-05-01
Full Text Available Abstract Background Many processes in molecular biology involve the recognition of short sequences of nucleic-or amino acids, such as the binding of immunogenic peptides to major histocompatibility complex (MHC molecules. From experimental data, a model of the sequence specificity of these processes can be constructed, such as a sequence motif, a scoring matrix or an artificial neural network. The purpose of these models is two-fold. First, they can provide a summary of experimental results, allowing for a deeper understanding of the mechanisms involved in sequence recognition. Second, such models can be used to predict the experimental outcome for yet untested sequences. In the past we reported the development of a method to generate such models called the Stabilized Matrix Method (SMM. This method has been successfully applied to predicting peptide binding to MHC molecules, peptide transport by the transporter associated with antigen presentation (TAP and proteasomal cleavage of protein sequences. Results Herein we report the implementation of the SMM algorithm as a publicly available software package. Specific features determining the type of problems the method is most appropriate for are discussed. Advantageous features of the package are: (1 the output generated is easy to interpret, (2 input and output are both quantitative, (3 specific computational strategies to handle experimental noise are built in, (4 the algorithm is designed to effectively handle bounded experimental data, (5 experimental data from randomized peptide libraries and conventional peptides can easily be combined, and (6 it is possible to incorporate pair interactions between positions of a sequence. Conclusion Making the SMM method publicly available enables bioinformaticians and experimental biologists to easily access it, to compare its performance to other prediction methods, and to extend it to other applications.
Pang, Lijun; Landau, D P; Binder, K
2011-06-10
Monte Carlo simulations of (fluctuating) interfaces in Ising models confined between competing walls at temperatures above the wetting transition are presented and various correlation functions probing the interfacial fluctuation are computed. Evidence for the nonlocal interface Hamiltonian approach of A. O. Parry et al. [Phys. Rev. Lett. 93, 086104 (2004)] is given. In particular, we show that two correlation lengths exist with different dependence on the distance D between the walls.
Baker Syed; Poskar C; Junker Björn
2011-01-01
Abstract In systems biology, experimentally measured parameters are not always available, necessitating the use of computationally based parameter estimation. In order to rely on estimated parameters, it is critical to first determine which parameters can be estimated for a given model and measurement set. This is done with parameter identifiability analysis. A kinetic model of the sucrose accumulation in the sugar cane culm tissue developed by Rohwer et al. was taken as a test case model. Wh...
Mirror symmetry for two parameter models, 2
Candelas, Philip; Katz, S; Morrison, Douglas Robert Ogston; Philip Candelas; Anamaria Font; Sheldon Katz; David R Morrison
1994-01-01
We describe in detail the space of the two K\\"ahler parameters of the Calabi--Yau manifold \\P_4^{(1,1,1,6,9)}[18] by exploiting mirror symmetry. The large complex structure limit of the mirror, which corresponds to the classical large radius limit, is found by studying the monodromy of the periods about the discriminant locus, the boundary of the moduli space corresponding to singular Calabi--Yau manifolds. A symplectic basis of periods is found and the action of the Sp(6,\\Z) generators of the modular group is determined. From the mirror map we compute the instanton expansion of the Yukawa couplings and the generalized N=2 index, arriving at the numbers of instantons of genus zero and genus one of each degree. We also investigate an SL(2,\\Z) symmetry that acts on a boundary of the moduli space.
Synchronous Generator Model Parameter Estimation Based on Noisy Dynamic Waveforms
Berhausen, Sebastian; Paszek, Stefan
2016-01-01
In recent years, there have occurred system failures in many power systems all over the world. They have resulted in a lack of power supply to a large number of recipients. To minimize the risk of occurrence of power failures, it is necessary to perform multivariate investigations, including simulations, of power system operating conditions. To conduct reliable simulations, the current base of parameters of the models of generating units, containing the models of synchronous generators, is necessary. In the paper, there is presented a method for parameter estimation of a synchronous generator nonlinear model based on the analysis of selected transient waveforms caused by introducing a disturbance (in the form of a pseudorandom signal) in the generator voltage regulation channel. The parameter estimation was performed by minimizing the objective function defined as a mean square error for deviations between the measurement waveforms and the waveforms calculated based on the generator mathematical model. A hybrid algorithm was used for the minimization of the objective function. In the paper, there is described a filter system used for filtering the noisy measurement waveforms. The calculation results of the model of a 44 kW synchronous generator installed on a laboratory stand of the Institute of Electrical Engineering and Computer Science of the Silesian University of Technology are also given. The presented estimation method can be successfully applied to parameter estimation of different models of high-power synchronous generators operating in a power system.
Institute of Scientific and Technical Information of China (English)
RAVINDRA SAMPATH WALGAMA; MYRON PHILLIP ZALUCKI
2006-01-01
Development data of eggs and pupae ofXyleborusfornicatus Eichh. (Coleoptera: Scolytidae), the shot-hole borer of tea in Sri Lanka, at constant temperatures were used to evaluate a linear and seven nonlinear models for insect development. Model evaluation was based on fit to data (residual sum of squares and coefficient of determination or coefficient of nonlinear regression), number of measurable parameters, the biological value of the fitted coefficients and accuracy in the estimation of thresholds. Of the nonlinear models, the Lactin model fitted experimental data well and along with the linear model, can be used to describe the temperature-dependent development of this species.
Excited Electronic States of Atoms described by the Model of Oscillations in a Chain System
Directory of Open Access Journals (Sweden)
Ries A.
2011-10-01
Full Text Available We analyzed the numerical values of half-lifes of excited electronic states of the H, He and Li atom, as well as the Li + ion. By means of a fractal scaling model originally published by Müller in this journal, we interprete these half-lifes as proton resonance periods. On the logarithmic scale, the half-lifes were expressed by short continued fractions, where all numerators are Euler’s number. From this representation it was concluded that the half-lifes are heavily located in nodes or sub-nodes of the spectrum of proton resonance periods.
Moose models with vanishing $S$ parameter
Casalbuoni, R; Dominici, Daniele
2004-01-01
In the linear moose framework, which naturally emerges in deconstruction models, we show that there is a unique solution for the vanishing of the $S$ parameter at the lowest order in the weak interactions. We consider an effective gauge theory based on $K$ SU(2) gauge groups, $K+1$ chiral fields and electroweak groups $SU(2)_L$ and $U(1)_Y$ at the ends of the chain of the moose. $S$ vanishes when a link in the moose chain is cut. As a consequence one has to introduce a dynamical non local field connecting the two ends of the moose. Then the model acquires an additional custodial symmetry which protects this result. We examine also the possibility of a strong suppression of $S$ through an exponential behavior of the link couplings as suggested by Randall Sundrum metric.
Model parameters for simulation of physiological lipids
McGlinchey, Nicholas
2016-01-01
Coarse grain simulation of proteins in their physiological membrane environment can offer insight across timescales, but requires a comprehensive force field. Parameters are explored for multicomponent bilayers composed of unsaturated lipids DOPC and DOPE, mixed‐chain saturation POPC and POPE, and anionic lipids found in bacteria: POPG and cardiolipin. A nonbond representation obtained from multiscale force matching is adapted for these lipids and combined with an improved bonding description of cholesterol. Equilibrating the area per lipid yields robust bilayer simulations and properties for common lipid mixtures with the exception of pure DOPE, which has a known tendency to form nonlamellar phase. The models maintain consistency with an existing lipid–protein interaction model, making the force field of general utility for studying membrane proteins in physiologically representative bilayers. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. PMID:26864972
Shogin, Dmitry; Amund Amundsen, Per
2016-10-01
We test the physical relevance of the full and the truncated versions of the Israel–Stewart (IS) theory of irreversible thermodynamics in a cosmological setting. Using a dynamical systems method, we determine the asymptotic future of plane symmetric Bianchi type I spacetimes with a viscous mathematical fluid, keeping track of the magnitude of the relative dissipative fluxes, which determines the applicability of the IS theory. We consider the situations where the dissipative mechanisms of shear and bulk viscosity are involved separately and simultaneously. It is demonstrated that the only case in the given model when the fluid asymptotically approaches local thermal equilibrium, and the underlying assumptions of the IS theory are therefore not violated, is that of a dissipative fluid with vanishing bulk viscosity. The truncated IS equations for shear viscosity are found to produce solutions which manifest pathological dynamical features and, in addition, to be strongly sensitive to the choice of initial conditions. Since these features are observed already in the case of an oversimplified mathematical fluid model, we have no reason to assume that the truncation of the IS transport equations will produce relevant results for physically more realistic fluids. The possible role of bulk and shear viscosity in cosmological evolution is also discussed.
Shekhar, Karthik; Ruberman, Claire F.; Ferguson, Andrew L.; Barton, John P.; Kardar, Mehran; Chakraborty, Arup K.
2017-01-01
Mutational escape from vaccine-induced immune responses has thwarted the development of a successful vaccine against AIDS, whose causative agent is HIV, a highly mutable virus. Knowing the virus’ fitness as a function of its proteomic sequence can enable rational design of potent vaccines, as this information can focus vaccine-induced immune responses to target mutational vulnerabilities of the virus. Spin models have been proposed as a means to infer intrinsic fitness landscapes of HIV proteins from patient-derived viral protein sequences. These sequences are the product of nonequilibrium viral evolution driven by patient-specific immune responses and are subject to phylogenetic constraints. How can such sequence data allow inference of intrinsic fitness landscapes? We combined computer simulations and variational theory á la Feynman to show that, in most circumstances, spin models inferred from patient-derived viral sequences reflect the correct rank order of the fitness of mutant viral strains. Our findings are relevant for diverse viruses. PMID:24483484
Loki, Io: New groundbased observations and a model describing the change from periodic overturn
Rathbun, J A; Rathbun, Julie A.; Spencer, John R.
2006-01-01
Loki Patera is the most powerful volcano in the solar system. We have obtained measurements of Loki's 3.5 micron brightness from NASA's Infrared Telescope Facility (IRTF) and have witnessed a change from the periodic behavior previously noted. While Loki brightened by a factor of several every 540 days prior to 2001, from 2001 through 2004 Loki remained at a constant, medium brightness. We have constructed a quantitative model of Loki as a basaltic lava lake whose solidified crust overturns when it becomes buoyantly unstable. By altering the speed at which the overturn propagates across the patera, we can match our groundbased brightness data. In addition, we can match other data taken at other times and wavelengths. By slowing the propagation speed dramatically, we can match the observations from 2001-2004. This slowing may be due to a small change in volatile content in the magma.
Shogin, Dmitry
2015-01-01
We test the physical relevance of the full and truncated versions of the Israel-Stewart theory of irreversible thermodynamics in a cosmological setting. Using a dynamical systems method, we determine the asymptotic future of plane symmetric Bianchi type I spacetimes filled with a viscous {\\gamma}-fluid, keeping track of the magnitude of relative dissipative fluxes, which determines the applicability of the Israel-Stewart theory. We consider the situations when the dissipative mechanisms of shear and bulk viscosity are involved separately and simultaneously. Also, we apply two different temperature models in the full version of the theory in order to compare the results. We demonstrate that the only case when the fluid asymptotically approaches local equilibrium, and the underlying assumptions of the IS theory are therefore not violated, is that of a dissipative fluid with vanishing bulk viscosity. The truncated Israel-Stewart equations for shear viscosity are found to produce solutions which manifest patholog...
Coupled gel spreading and diffusive transport models describing microbicidal drug delivery.
Funke, Claire; MacMillan, Kelsey; Ham, Anthony; Szeri, Andrew J; Katz, David F
2016-10-02
Gels are a drug delivery platform that is being evaluated for application of active pharmaceutical ingredients, termed microbicides, that act topically against vaginal and rectal mucosal infection by sexually transmitted HIV. Despite success in one Phase IIb trial of a vaginal gel delivering tenofovir, problems of user adherence to designed gel application scheduling have compromised results in two other trials. The microbicides field is responding to this dilemma by expanding behavioral analysis of the determinants of adherence while simultaneously improving the pharmacological, biochemical, and biophysical analyses of the determinants of microbicide drug delivery. The intent is to combine results of these two complementary perspectives on microbicide performance and epidemiological success to create an improved product design paradigm. Central to both user sensory perceptions and preferences, key factors that underlie adherence, and to vaginal gel mucosal drug delivery, that underlies anti-HIV efficacy, are gel properties (e.g. rheology) and volume. The specific engineering problem to be solved here is to develop a model for how gel rheology and volume, interacting with loaded drug concentration, govern the transport of the microbicide drug tenofovir into the vaginal mucosa to its stromal layer. These are factors that can be controlled in microbicide gel design. The analysis here builds upon our current understanding of vaginal gel deployment and drug delivery, incorporating key features of the gel's environment, the vaginal canal, fluid production and subsequent gel dilution, and vaginal wall elasticity. These have not previously been included in the modeling of drug delivery. We consider the microbicide drug tenofovir, which is the drug most completely studied for gels: in vitro, in animal studies in vivo, and in human clinical trials with both vaginal or rectal gel application. Our goal is to contribute to improved biophysical and pharmacological understanding
Zhao, Pei; Shao, Ming-an; Horton, Robert
2011-02-01
Soil particle-size distributions (PSD) have been used to estimate soil hydraulic properties. Various parametric PSD models have been proposed to describe the soil PSD from sparse experimental data. It is important to determine which PSD model best represents specific soils. Fourteen PSD models were examined in order to determine the best model for representing the deposited soils adjacent to dams in the China Loess Plateau; these were: Skaggs (S-1, S-2, and S-3), fractal (FR), Jaky (J), Lima and Silva (LS), Morgan (M), Gompertz (G), logarithm (L), exponential (E), log-exponential (LE), Weibull (W), van Genuchten type (VG) as well as Fredlund (F) models. Four-hundred and eighty samples were obtained from soils deposited in the Liudaogou catchment. The coefficient of determination (R 2), the Akaike's information criterion (AIC), and the modified AIC (mAIC) were used. Based upon R 2 and AIC, the three- and four-parameter models were both good at describing the PSDs of deposited soils, and the LE, FR, and E models were the poorest. However, the mAIC in conjunction with R 2 and AIC results indicated that the W model was optimum for describing PSD of the deposited soils for emphasizing the effect of parameter number. This analysis was also helpful for finding out which model is the best one. Our results are applicable to the China Loess Plateau.
Hysteresis in DNA compaction by Dps is described by an Ising model.
Vtyurina, Natalia N; Dulin, David; Docter, Margreet W; Meyer, Anne S; Dekker, Nynke H; Abbondanzieri, Elio A
2016-05-03
In all organisms, DNA molecules are tightly compacted into a dynamic 3D nucleoprotein complex. In bacteria, this compaction is governed by the family of nucleoid-associated proteins (NAPs). Under conditions of stress and starvation, an NAP called Dps (DNA-binding protein from starved cells) becomes highly up-regulated and can massively reorganize the bacterial chromosome. Although static structures of Dps-DNA complexes have been documented, little is known about the dynamics of their assembly. Here, we use fluorescence microscopy and magnetic-tweezers measurements to resolve the process of DNA compaction by Dps. Real-time in vitro studies demonstrated a highly cooperative process of Dps binding characterized by an abrupt collapse of the DNA extension, even under applied tension. Surprisingly, we also discovered a reproducible hysteresis in the process of compaction and decompaction of the Dps-DNA complex. This hysteresis is extremely stable over hour-long timescales despite the rapid binding and dissociation rates of Dps. A modified Ising model is successfully applied to fit these kinetic features. We find that long-lived hysteresis arises naturally as a consequence of protein cooperativity in large complexes and provides a useful mechanism for cells to adopt unique epigenetic states.
Coupled gel spreading and diffusive transport models describing microbicidal drug delivery
Funke, Claire; MacMillan, Kelsey; Ham, Anthony S.; Szeri, Andrew J.; Katz, David F.
2016-11-01
Gels are a drug delivery platform being evaluated for application of active pharmaceutical ingredients, termed microbicides, that act topically against infection by sexually transmitted HIV. Despite success in one Phase IIb trial of a vaginal gel delivering tenofovir, problems of user adherence to designed gel application regimen compromised results in two other trials. The microbicide field is responding to this issue by simultaneously analyzing behavioral determinants of adherence and pharmacological determinants of drug delivery. Central to both user adherence and mucosal drug delivery are gel properties (e.g. rheology) and applied volume. The specific problem to be solved here is to develop a model for how gel rheology and volume, interacting with loaded drug concentration, govern the transport of the microbicide drug tenofovir into the vaginal mucosa to its stromal layer. The analysis here builds upon our current understanding of vaginal gel deployment and drug delivery, incorporating key features of the gel's environment, fluid production and subsequent gel dilution, and vaginal wall elasticity. We consider the microbicide drug tenofovir as it is the most completely studied drug, in both in vitroand in vivostudies, for use in vaginal gel application. Our goal is to contribute to improved pharmacological understanding of gel functionality, providing a computational tool that can be used in future vaginal microbicide gel design.
Cognitive Models of Risky Choice: Parameter Stability and Predictive Accuracy of Prospect Theory
Glockner, Andreas; Pachur, Thorsten
2012-01-01
In the behavioral sciences, a popular approach to describe and predict behavior is cognitive modeling with adjustable parameters (i.e., which can be fitted to data). Modeling with adjustable parameters allows, among other things, measuring differences between people. At the same time, parameter estimation also bears the risk of overfitting. Are…
Hyland, D. C.
1983-01-01
A stochastic structural control model is described. In contrast to the customary deterministic model, the stochastic minimum data/maximum entropy model directly incorporates the least possible a priori parameter information. The approach is to adopt this model as the basic design model, thus incorporating the effects of parameter uncertainty at a fundamental level, and design mean-square optimal controls (that is, choose the control law to minimize the average of a quadratic performance index over the parameter ensemble).
Enhancing debris flow modeling parameters integrating Bayesian networks
Graf, C.; Stoffel, M.; Grêt-Regamey, A.
2009-04-01
Applied debris-flow modeling requires suitably constraint input parameter sets. Depending on the used model, there is a series of parameters to define before running the model. Normally, the data base describing the event, the initiation conditions, the flow behavior, the deposition process and mainly the potential range of possible debris flow events in a certain torrent is limited. There are only some scarce places in the world, where we fortunately can find valuable data sets describing event history of debris flow channels delivering information on spatial and temporal distribution of former flow paths and deposition zones. Tree-ring records in combination with detailed geomorphic mapping for instance provide such data sets over a long time span. Considering the significant loss potential associated with debris-flow disasters, it is crucial that decisions made in regard to hazard mitigation are based on a consistent assessment of the risks. This in turn necessitates a proper assessment of the uncertainties involved in the modeling of the debris-flow frequencies and intensities, the possible run out extent, as well as the estimations of the damage potential. In this study, we link a Bayesian network to a Geographic Information System in order to assess debris-flow risk. We identify the major sources of uncertainty and show the potential of Bayesian inference techniques to improve the debris-flow model. We model the flow paths and deposition zones of a highly active debris-flow channel in the Swiss Alps using the numerical 2-D model RAMMS. Because uncertainties in run-out areas cause large changes in risk estimations, we use the data of flow path and deposition zone information of reconstructed debris-flow events derived from dendrogeomorphological analysis covering more than 400 years to update the input parameters of the RAMMS model. The probabilistic model, which consistently incorporates this available information, can serve as a basis for spatial risk
On retrial queueing model with fuzzy parameters
Ke, Jau-Chuan; Huang, Hsin-I.; Lin, Chuen-Horng
2007-01-01
This work constructs the membership functions of the system characteristics of a retrial queueing model with fuzzy customer arrival, retrial and service rates. The α-cut approach is used to transform a fuzzy retrial-queue into a family of conventional crisp retrial queues in this context. By means of the membership functions of the system characteristics, a set of parametric non-linear programs is developed to describe the family of crisp retrial queues. A numerical example is solved successfully to illustrate the validity of the proposed approach. Because the system characteristics are expressed and governed by the membership functions, more information is provided for use by management. By extending this model to the fuzzy environment, fuzzy retrial-queue is represented more accurately and analytic results are more useful for system designers and practitioners.
Solar parameters for modeling interplanetary background
Bzowski, M; Tokumaru, M; Fujiki, K; Quemerais, E; Lallement, R; Ferron, S; Bochsler, P; McComas, D J
2011-01-01
The goal of the Fully Online Datacenter of Ultraviolet Emissions (FONDUE) Working Team of the International Space Science Institute in Bern, Switzerland, was to establish a common calibration of various UV and EUV heliospheric observations, both spectroscopic and photometric. Realization of this goal required an up-to-date model of spatial distribution of neutral interstellar hydrogen in the heliosphere, and to that end, a credible model of the radiation pressure and ionization processes was needed. This chapter describes the solar factors shaping the distribution of neutral interstellar H in the heliosphere. Presented are the solar Lyman-alpha flux and the solar Lyman-alpha resonant radiation pressure force acting on neutral H atoms in the heliosphere, solar EUV radiation and the photoionization of heliospheric hydrogen, and their evolution in time and the still hypothetical variation with heliolatitude. Further, solar wind and its evolution with solar activity is presented in the context of the charge excha...
Uncertainty Quantification for Optical Model Parameters
Lovell, A E; Sarich, J; Wild, S M
2016-01-01
Although uncertainty quantification has been making its way into nuclear theory, these methods have yet to be explored in the context of reaction theory. For example, it is well known that different parameterizations of the optical potential can result in different cross sections, but these differences have not been systematically studied and quantified. The purpose of this work is to investigate the uncertainties in nuclear reactions that result from fitting a given model to elastic-scattering data, as well as to study how these uncertainties propagate to the inelastic and transfer channels. We use statistical methods to determine a best fit and create corresponding 95\\% confidence bands. A simple model of the process is fit to elastic-scattering data and used to predict either inelastic or transfer cross sections. In this initial work, we assume that our model is correct, and the only uncertainties come from the variation of the fit parameters. We study a number of reactions involving neutron and deuteron p...
Numerical modeling of partial discharges parameters
Directory of Open Access Journals (Sweden)
Kartalović Nenad M.
2016-01-01
Full Text Available In recent testing of the partial discharges or the use for the diagnosis of insulation condition of high voltage generators, transformers, cables and high voltage equipment develops rapidly. It is a result of the development of electronics, as well as, the development of knowledge about the processes of partial discharges. The aim of this paper is to contribute the better understanding of this phenomenon of partial discharges by consideration of the relevant physical processes in isolation materials and isolation systems. Prebreakdown considers specific processes, and development processes at the local level and their impact on specific isolation material. This approach to the phenomenon of partial discharges needed to allow better take into account relevant discharge parameters as well as better numerical model of partial discharges.
Robust linear parameter varying induction motor control with polytopic models
Directory of Open Access Journals (Sweden)
Dalila Khamari
2013-01-01
Full Text Available This paper deals with a robust controller for an induction motor which is represented as a linear parameter varying systems. To do so linear matrix inequality (LMI based approach and robust Lyapunov feedback controller are associated. This new approach is related to the fact that the synthesis of a linear parameter varying (LPV feedback controller for the inner loop take into account rotor resistance and mechanical speed as varying parameter. An LPV flux observer is also synthesized to estimate rotor flux providing reference to cited above regulator. The induction motor is described as a polytopic model because of speed and rotor resistance affine dependence their values can be estimated on line during systems operations. The simulation results are presented to confirm the effectiveness of the proposed approach where robustness stability and high performances have been achieved over the entire operating range of the induction motor.
Connecting Global to Local Parameters in Barred Galaxy Models
Indian Academy of Sciences (India)
N. D. Caranicolas
2002-09-01
We present connections between global and local parameters in a realistic dynamical model, describing motion in a barred galaxy. Expanding the global model in the vicinity of a stable Lagrange point, we find the potential of a two-dimensional perturbed harmonic oscillator, which describes local motion near the centre of the global model. The frequencies of oscillations and the coefficients of the perturbing terms are not arbitrary but are connected to the mass, the angular rotation velocity, the scale length and the strength of the galactic bar. The local energy is also connected to the global energy. A comparison of the properties of orbits in the global and local potential is also made.
Agricultural and Environmental Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
K. Rasmuson; K. Rautenstrauch
2004-09-14
This analysis is one of 10 technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) (i.e., the biosphere model). It documents development of agricultural and environmental input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the ERMYN and its input parameters.
Prediction of interest rate using CKLS model with stochastic parameters
Energy Technology Data Exchange (ETDEWEB)
Ying, Khor Chia [Faculty of Computing and Informatics, Multimedia University, Jalan Multimedia, 63100 Cyberjaya, Selangor (Malaysia); Hin, Pooi Ah [Sunway University Business School, No. 5, Jalan Universiti, Bandar Sunway, 47500 Subang Jaya, Selangor (Malaysia)
2014-06-19
The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector φ{sup (j)} of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j′-th time point where j≤j′≤j+n. To model the variation of φ{sup (j)}, we assume that φ{sup (j)} depends on φ{sup (j−m)}, φ{sup (j−m+1)},…, φ{sup (j−1)} and the interest rate r{sub j+n} at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r{sub j+n+1} of the interest rate at the next time point when the value r{sub j+n} of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r{sub j+n+d} at the next d-th (d≥2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters.
DEFF Research Database (Denmark)
Alskär, Oskar; Bagger, Jonatan I; Røge, Rikke M.
2016-01-01
and gastric emptying after tests with varying glucose doses. The developed model's performance was compared to empirical models. To develop our model, data from oral and intravenous glucose challenges in patients with type 2 diabetes and healthy control subjects were used together with present knowledge......The integrated glucose-insulin (IGI) model is a previously published semimechanistic model that describes plasma glucose and insulin concentrations after glucose challenges. The aim of this work was to use knowledge of physiology to improve the IGI model's description of glucose absorption...
Inhalation Exposure Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
M. Wasiolek
2006-06-05
This analysis is one of the technical reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), referred to in this report as the biosphere model. ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. ''Inhalation Exposure Input Parameters for the Biosphere Model'' is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the biosphere model is presented in Figure 1-1 (based on BSC 2006 [DIRS 176938]). This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and how this analysis report contributes to biosphere modeling. This analysis report defines and justifies values of atmospheric mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of the biosphere model to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception. This
A robust methodology for kinetic model parameter estimation for biocatalytic reactions
DEFF Research Database (Denmark)
Al-Haque, Naweed; Andrade Santacoloma, Paloma de Gracia; Lima Afonso Neto, Watson;
2012-01-01
Effective estimation of parameters in biocatalytic reaction kinetic expressions are very important when building process models to enable evaluation of process technology options and alternative biocatalysts. The kinetic models used to describe enzyme-catalyzed reactions generally include several...
2012-01-01
Technology and means for automatic translation of FSM model parameters from Matlab application to human-machine interface application is proposed. The example of technology application to the electric apparatus model is described.
Zhang, Yu-Xia; Liao, Hao; Medo, Matus; Shang, Ming-Sheng; Yeung, Chi Ho
2016-05-01
In this paper we analyze the contrary behaviors of the informed investors and uniformed investors, and then construct a competition model with two groups of agents, namely agents who intend to stay in minority and those who intend to stay in majority. We find two kinds of competitions, inter- and intra-groups. The model shows periodic fluctuation feature. The average distribution of strategies illustrates a prominent central peak which is relevant to the peak-fat-tail character of price change distribution in stock markets. Furthermore, in the modified model the tolerance time parameter makes the agents diversified. Finally, we compare the strategies distribution with the price change distribution in real stock market, and we conclude that contrary behavior rules and tolerance time parameter are indeed valid in the description of market model.
Dijk, van C.; Boeriu, C.G.; Peter, F.; Stolle-Smits, T.; Tijskens, L.M.M.
2006-01-01
The aim of this research was to develop practical applicable models capable to describe and to predict the temperature dependent firmness and moisture loss of tomatoes during storage. To gather the required information to develop these models batches of 20 tomatoes (cv. Tradiro), each harvested at
Kuchinke, W.; Ohmann, C.; Verheij, R.A.; Veen, E.B. van; Arvanitis, T.N.; Taweel, A.; Delaney, B.C.
2014-01-01
Purpose: To develop a model describing core concepts and principles of data flow, data privacy and confidentiality, in a simple and flexible way, using concise process descriptions and a diagrammatic notation applied to research workflow processes. The model should help to generate robust data priva
Dijk, van C.; Boeriu, C.G.; Peter, F.; Stolle-Smits, T.; Tijskens, L.M.M.
2006-01-01
The aim of this research was to develop practical applicable models capable to describe and to predict the temperature dependent firmness and moisture loss of tomatoes during storage. To gather the required information to develop these models batches of 20 tomatoes (cv. Tradiro), each harvested at t
Parameter Optimisation for the Behaviour of Elastic Models over Time
DEFF Research Database (Denmark)
Mosegaard, Jesper
2004-01-01
Optimisation of parameters for elastic models is essential for comparison or finding equivalent behaviour of elastic models when parameters cannot simply be transferred or converted. This is the case with a large range of commonly used elastic models. In this paper we present a general method...... that will optimise parameters based on the behaviour of the elastic models over time....
Model Identification of Linear Parameter Varying Aircraft Systems
Fujimore, Atsushi; Ljung, Lennart
2007-01-01
This article presents a parameter estimation of continuous-time polytopic models for a linear parameter varying (LPV) system. The prediction error method of linear time invariant (LTI) models is modified for polytopic models. The modified prediction error method is applied to an LPV aircraft system whose varying parameter is the flight velocity and model parameters are the stability and control derivatives (SCDs). In an identification simulation, the polytopic model is more suitable for expre...
Helzel, Christiane
2016-07-22
We consider a kinetic model, which describes the sedimentation of rod-like particles in dilute suspensions under the influence of gravity, presented in Helzel and Tzavaras (submitted for publication). Here we restrict our considerations to shear flow and consider a simplified situation, where the particle orientation is restricted to the plane spanned by the direction of shear and the direction of gravity. For this simplified kinetic model we carry out a linear stability analysis and we derive two different nonlinear macroscopic models which describe the formation of clusters of higher particle density. One of these macroscopic models is based on a diffusive scaling, the other one is based on a so-called quasi-dynamic approximation. Numerical computations, which compare the predictions of the macroscopic models with the kinetic model, complete our presentation.
Ferreira, P Castelo
2010-01-01
Are discussed possible generalizations for many body systems of the recently suggested Expanding Locally Anisotropic (ELA) metric ansatz which describes local point-like matter distributions in the expanding universe. Considering a series expansion of the functional parameter of this metric to second order in the gravitational field it is developed a simple lattice model for galaxies based in the thin exponential disk approximation. As an example it is modeled the large galaxy UGC2885 and it is shown that, by fitting the values of the metric parameters, the flattening of the galaxy rotation curve is fully described by the ELA metric. The framework presented here clearly allows to theoretically test new gravitational interactions maintaining compatibility with both local physics and cosmological universe expansion.
Soil-Related Input Parameters for the Biosphere Model
Energy Technology Data Exchange (ETDEWEB)
A. J. Smith
2004-09-09
This report presents one of the analyses that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the details of the conceptual model as well as the mathematical model and the required input parameters. The biosphere model is one of a series of process models supporting the postclosure Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A schematic representation of the documentation flow for the Biosphere input to TSPA is presented in Figure 1-1. This figure shows the evolutionary relationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (TWP) (BSC 2004 [DIRS 169573]). This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil-Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. The purpose of this analysis was to develop the biosphere model parameters associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation or ash deposition and, as a direct consequence, radionuclide concentration in other environmental media that are affected by radionuclide concentrations in soil. The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573]) where the governing procedure
[Calculation of parameters in forest evapotranspiration model].
Wang, Anzhi; Pei, Tiefan
2003-12-01
Forest evapotranspiration is an important component not only in water balance, but also in energy balance. It is a great demand for the development of forest hydrology and forest meteorology to simulate the forest evapotranspiration accurately, which is also a theoretical basis for the management and utilization of water resources and forest ecosystem. Taking the broadleaved Korean pine forest on Changbai Mountain as an example, this paper constructed a mechanism model for estimating forest evapotranspiration, based on the aerodynamic principle and energy balance equation. Using the data measured by the Routine Meteorological Measurement System and Open-Path Eddy Covariance Measurement System mounted on the tower in the broadleaved Korean pine forest, the parameters displacement height d, stability functions for momentum phi m, and stability functions for heat phi h were ascertained. The displacement height of the study site was equal to 17.8 m, near to the mean canopy height, and the functions of phi m and phi h changing with gradient Richarson number R i were constructed.
Transfer function modeling of damping mechanisms in distributed parameter models
Slater, J. C.; Inman, D. J.
1994-01-01
This work formulates a method for the modeling of material damping characteristics in distributed parameter models which may be easily applied to models such as rod, plate, and beam equations. The general linear boundary value vibration equation is modified to incorporate hysteresis effects represented by complex stiffness using the transfer function approach proposed by Golla and Hughes. The governing characteristic equations are decoupled through separation of variables yielding solutions similar to those of undamped classical theory, allowing solution of the steady state as well as transient response. Example problems and solutions are provided demonstrating the similarity of the solutions to those of the classical theories and transient responses of nonviscous systems.
Relevant parameters in models of cell division control
Grilli, Jacopo; Osella, Matteo; Kennard, Andrew S.; Lagomarsino, Marco Cosentino
2017-03-01
A recent burst of dynamic single-cell data makes it possible to characterize the stochastic dynamics of cell division control in bacteria. Different models were used to propose specific mechanisms, but the links between them are poorly explored. The lack of comparative studies makes it difficult to appreciate how well any particular mechanism is supported by the data. Here, we describe a simple and generic framework in which two common formalisms can be used interchangeably: (i) a continuous-time division process described by a hazard function and (ii) a discrete-time equation describing cell size across generations (where the unit of time is a cell cycle). In our framework, this second process is a discrete-time Langevin equation with simple physical analogues. By perturbative expansion around the mean initial size (or interdivision time), we show how this framework describes a wide range of division control mechanisms, including combinations of time and size control, as well as the constant added size mechanism recently found to capture several aspects of the cell division behavior of different bacteria. As we show by analytical estimates and numerical simulations, the available data are described precisely by the first-order approximation of this expansion, i.e., by a "linear response" regime for the correction of size fluctuations. Hence, a single dimensionless parameter defines the strength and action of the division control against cell-to-cell variability (quantified by a single "noise" parameter). However, the same strength of linear response may emerge from several mechanisms, which are distinguished only by higher-order terms in the perturbative expansion. Our analytical estimate of the sample size needed to distinguish between second-order effects shows that this value is close to but larger than the values of the current datasets. These results provide a unified framework for future studies and clarify the relevant parameters at play in the control of
Model for a Universe described by a non-minimally coupled scalar field and interacting dark matter
Binder, J B
2006-01-01
In this work it is investigated the evolution of a Universe where a scalar field, non-minimally coupled to space-time curvature, plays the role of quintessence and drives the Universe to a present accelerated expansion. A non-relativistic dark matter constituent that interacts directly with dark energy is also considered, where the dark matter particle mass is assumed to be proportional to the value of the scalar field. Two models for dark matter pressure are considered: the usual one, pressureless, and another that comes from a thermodynamic theory and relates the pressure with the coupling between the scalar field and the curvature scalar. Although the model has a strong dependence on the initial conditions, it is shown that the mixture consisted of dark components plus baryonic matter and radiation can reproduce the expected red-shift behavior of the deceleration parameter, density parameters and luminosity distance.
2012-01-01
The traditional methods of the biology, based on illustrative descriptions and linear logic explanations, are discussed. This work aims to improve this approach by introducing alternative tools to describe and represent complex biological systems. Two models were developed, one mathematical and another computational, both were made in order to study the biological process between free radicals and antioxidants. Each model was used to study the same process but in different scenarios. The math...
Determining extreme parameter correlation in ground water models
DEFF Research Database (Denmark)
Hill, Mary Cole; Østerby, Ole
2003-01-01
In ground water flow system models with hydraulic-head observations but without significant imposed or observed flows, extreme parameter correlation generally exists. As a result, hydraulic conductivity and recharge parameters cannot be uniquely estimated. In complicated problems, such correlation...... correlation coefficients, but it required sensitivities that were one to two significant digits less accurate than those that required using parameter correlation coefficients; and (3) both the SVD and parameter correlation coefficients identified extremely correlated parameters better when the parameters...
The objective of this study was to develop a new approach using a one-step approach to directly construct predictive models for describing the growth of Salmonella Enteritidis (SE) in liquid egg white (LEW) and egg yolk (LEY). A five-strain cocktail of SE, induced to resist rifampicin at 100 mg/L, ...
Comparison of various models to describe the charge-pH dependence of poly(acrylic acid)
Lützenkirchen, J.; Male, van J.; Leermakers, F.A.M.; Sjöberg, S.
2011-01-01
The charge of poly(acrylic acid) (PAA) in dilute aqueous solutions depends on pH and ionic strength. We report new experimental data and test various models to describe the deprotonation of PAA in three different NaCl concentrations. A simple surface complexation approach is found to be very success
DEFF Research Database (Denmark)
Møller, Cleide Oliveira de Almeida; Hansen, Tina Beck; Aabo, Søren
2015-01-01
Introduction: The cross contamination model (Møller et al. 2012) was evaluated to investigate its capability of describing transfer of Salmonella spp. and Listeria monocytogenes during grinding of pork and beef of varying sizes (50 – 324 g) and numbers of pieces to be ground (10 – 100), in two...
DEFF Research Database (Denmark)
Olsen, Kjeld J.; Hansen, Johnny W.
is inadequately described by an RBE-factor, whereas the complete formulation of the probability of survival must be used, as survival depends on both radiation quality and dose. The theoretical model of track structure can be used in dose-effect calculations for neutron-, high-LET, and low-LET radiation applied...
How Mathematics Describes Life
Teklu, Abraham
2017-01-01
The circle of life is something we have all heard of from somewhere, but we don't usually try to calculate it. For some time we have been working on analyzing a predator-prey model to better understand how mathematics can describe life, in particular the interaction between two different species. The model we are analyzing is called the Holling-Tanner model, and it cannot be solved analytically. The Holling-Tanner model is a very common model in population dynamics because it is a simple descriptor of how predators and prey interact. The model is a system of two differential equations. The model is not specific to any particular set of species and so it can describe predator-prey species ranging from lions and zebras to white blood cells and infections. One thing all these systems have in common are critical points. A critical point is a value for both populations that keeps both populations constant. It is important because at this point the differential equations are equal to zero. For this model there are two critical points, a predator free critical point and a coexistence critical point. Most of the analysis we did is on the coexistence critical point because the predator free critical point is always unstable and frankly less interesting than the coexistence critical point. What we did is consider two regimes for the differential equations, large B and small B. B, A, and C are parameters in the differential equations that control the system where B measures how responsive the predators are to change in the population, A represents predation of the prey, and C represents the satiation point of the prey population. For the large B case we were able to approximate the system of differential equations by a single scalar equation. For the small B case we were able to predict the limit cycle. The limit cycle is a process of the predator and prey populations growing and shrinking periodically. This model has a limit cycle in the regime of small B, that we solved for
Oliveira, H R; Silva, F F; Siqueira, O H G B D; Souza, N O; Junqueira, V S; Resende, M D V; Borquis, R R A; Rodrigues, M T
2016-05-01
We proposed multiple-trait random regression models (MTRRM) combining different functions to describe milk yield (MY) and fat (FP) and protein (PP) percentage in dairy goat genetic evaluation by using Bayesian inference. A total of 3,856 MY, FP, and PP test-day records, measured between 2000 and 2014, from 535 first lactations of Saanen and Alpine goats, including their cross, were used in this study. The initial analyses were performed using the following single-trait random regression models (STRRM): third- and fifth-order Legendre polynomials (Leg3 and Leg5), linear B-splines with 3 and 5 knots, the Ali and Schaeffer function (Ali), and Wilmink function. Heterogeneity of residual variances was modeled considering 3 classes. After the selection of the best STRRM to describe each trait on the basis of the deviance information criterion (DIC) and posterior model probabilities (PMP), the functions were combined to compose the MTRRM. All combined MTRRM presented lower DIC values and higher PMP, showing the superiority of these models when compared to other MTRRM based only on the same function assumed for all traits. Among the combined MTRRM, those considering Ali to describe MY and PP and Leg5 to describe FP (Ali_Leg5_Ali model) presented the best fit. From the Ali_Leg5_Ali model, heritability estimates over time for MY, FP. and PP ranged from 0.25 to 0.54, 0.27 to 0.48, and 0.35 to 0.51, respectively. Genetic correlation between MY and FP, MY and PP, and FP and PP ranged from -0.58 to 0.03, -0.46 to 0.12, and 0.37 to 0.64, respectively. We concluded that combining different functions under a MTRRM approach can be a plausible alternative for joint genetic evaluation of milk yield and milk constituents in goats.
Garcia, Alvaro Juan Ojeda
2012-01-01
The traditional methods of the biology, based on illustrative descriptions and linear logic explanations, are discussed. This work aims to improve this approach by introducing alternative tools to describe and represent complex biological systems. Two models were developed, one mathematical and another computational, both were made in order to study the biological process between free radicals and antioxidants. Each model was used to study the same process but in different scenarios. The mathematical model was used to study the biological process in an epithelial cells culture; this model was validated with the experimental data of Anne Hanneken's research group from the Department of Molecular and Experimental Medicine, published by the journal Investigative Ophthalmology and Visual Science in July 2006. The computational model was used to study the same process in an individual. The model was made using C++ programming language, supported by the network theory of aging.
Model comparisons and genetic and environmental parameter ...
African Journals Online (AJOL)
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South African Journal of Animal Science 2005, 35 (1) ... Genetic and environmental parameters were estimated for pre- and post-weaning average daily gain ..... and BWT (and medium maternal genetic correlations) indicates that these traits ...
Energy Technology Data Exchange (ETDEWEB)
Dunn, Nicholas J. H.; Noid, W. G., E-mail: wnoid@chem.psu.edu [Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802 (United States)
2015-12-28
The present work investigates the capability of bottom-up coarse-graining (CG) methods for accurately modeling both structural and thermodynamic properties of all-atom (AA) models for molecular liquids. In particular, we consider 1, 2, and 3-site CG models for heptane, as well as 1 and 3-site CG models for toluene. For each model, we employ the multiscale coarse-graining method to determine interaction potentials that optimally approximate the configuration dependence of the many-body potential of mean force (PMF). We employ a previously developed “pressure-matching” variational principle to determine a volume-dependent contribution to the potential, U{sub V}(V), that approximates the volume-dependence of the PMF. We demonstrate that the resulting CG models describe AA density fluctuations with qualitative, but not quantitative, accuracy. Accordingly, we develop a self-consistent approach for further optimizing U{sub V}, such that the CG models accurately reproduce the equilibrium density, compressibility, and average pressure of the AA models, although the CG models still significantly underestimate the atomic pressure fluctuations. Additionally, by comparing this array of models that accurately describe the structure and thermodynamic pressure of heptane and toluene at a range of different resolutions, we investigate the impact of bottom-up coarse-graining upon thermodynamic properties. In particular, we demonstrate that U{sub V} accounts for the reduced cohesion in the CG models. Finally, we observe that bottom-up coarse-graining introduces subtle correlations between the resolution, the cohesive energy density, and the “simplicity” of the model.
Williams, Gareth; Toon, Andrew J
2010-12-01
Protein topology defined by the matrix of residue contacts has proved to be a fruitful basis for the study of protein dynamics. The widely implemented coarse-grained elastic network model of backbone fluctuations has been used to describe crystallographic temperature factors, allosteric couplings, and some aspects of the folding pathway. In the present study, we develop a model of protein dynamics based on the classical equations of motion of a damped network model (DNM) that describes the folding path from a completely unfolded state to the native conformation through a single-well potential derived purely from the native conformation. The kinetic energy gained through the collapse of the protein chain is dissipated through a friction term in the equations of motion that models the water bath. This approach is completely general and sufficiently fast that it can be applied to large proteins. Folding pathways for various proteins of different classes are described and shown to correlate with experimental observations and molecular dynamics and Monte Carlo simulations. Allosteric transitions between alternative protein structures are also modeled within the DNM through an asymmetric double-well potential.
Algar, C. K.
2015-12-01
Hydrogenotrophic methanogenesis is an important mode of metabolism in deep-sea hydrothermal vents. Diffuse vent fluids often show a depletion in hydrogen with a corresponding increase in methane relative to pure-mixing of end member fluid and seawater, and genomic surveys show an enrichment in genetic sequences associated with known methanogens. However, because we cannot directly sample the subseafloor habitat where these organisms are living, constraining the size and activity of these populations remains a challenge and limits our ability to quantify the role they play in vent biogeochemistry. Reactive-transport modeling may provide a useful tool for approaching this problem. Here we present a reactive-transport model describing methane production along the flow-path of hydrothermal fluid from its high temperature end-member to diffuse venting at the seafloor. The model is set up to reflect conditions at several diffuse vents in the Axial Seamount. The model describes the growth of the two dominant thermophilic methanogens, Methanothermococcus and Methanocaldococcus, observed at Axial seamount. Monod and Arrhenius constants for Methanothermococcus thermolithotrophicus and Methanocaldococcus jannaschii were obtained for the model using chemostat and bottle experiments at varying temperatures. The model is used to investigate the influence of different mixing regimes on the subseafloor populations of these methanogens. By varying the model flow path length and subseafloor cell concentrations, and fitting to observed hydrogen and methane concentrations in the venting fluid, the subseafloor biomass, fluid residence time, and methane production rate can be constrained.
Heineke, D.; Verhagen, H.J.
2007-01-01
To assess the hydraulic performance of coastal structures - viz. wave run-up, overtopping and reflection - and to evaluate the stability of the armour layers, use is made of the dimensionless surf similarity parameter, as introduced by Battjes (1974). The front side slope of the structure and the wa
Heineke, D.; Verhagen, H.J.
2007-01-01
To assess the hydraulic performance of coastal structures - viz. wave run-up, overtopping and reflection - and to evaluate the stability of the armour layers, use is made of the dimensionless surf similarity parameter, as introduced by Battjes (1974). The front side slope of the structure and the
Numerical model for thermal parameters in optical materials
Sato, Yoichi; Taira, Takunori
2016-04-01
Thermal parameters of optical materials, such as thermal conductivity, thermal expansion, temperature coefficient of refractive index play a decisive role for the thermal design inside laser cavities. Therefore, numerical value of them with temperature dependence is quite important in order to develop the high intense laser oscillator in which optical materials generate excessive heat across mode volumes both of lasing output and optical pumping. We already proposed a novel model of thermal conductivity in various optical materials. Thermal conductivity is a product of isovolumic specific heat and thermal diffusivity, and independent modeling of these two figures should be required from the viewpoint of a clarification of physical meaning. Our numerical model for thermal conductivity requires one material parameter for specific heat and two parameters for thermal diffusivity in the calculation of each optical material. In this work we report thermal conductivities of various optical materials as Y3Al5O12 (YAG), YVO4 (YVO), GdVO4 (GVO), stoichiometric and congruent LiTaO3, synthetic quartz, YAG ceramics and Y2O3 ceramics. The dependence on Nd3+-doping in laser gain media in YAG, YVO and GVO is also studied. This dependence can be described by only additional three parameters. Temperature dependence of thermal expansion and temperature coefficient of refractive index for YAG, YVO, and GVO: these are also included in this work for convenience. We think our numerical model is quite useful for not only thermal analysis in laser cavities or optical waveguides but also the evaluation of physical properties in various transparent materials.
Parameter optimization model in electrical discharge machining process
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
Electrical discharge machining (EDM) process, at present is still an experience process, wherein selected parameters are often far from the optimum, and at the same time selecting optimization parameters is costly and time consuming. In this paper,artificial neural network (ANN) and genetic algorithm (GA) are used together to establish the parameter optimization model. An ANN model which adapts Levenberg-Marquardt algorithm has been set up to represent the relationship between material removal rate (MRR) and input parameters, and GA is used to optimize parameters, so that optimization results are obtained. The model is shown to be effective, and MRR is improved using optimized machining parameters.
Stone, G; Chapman, B; Lovell, D
2009-11-01
In the commercial food industry, demonstration of microbiological safety and thermal process equivalence often involves a mathematical framework that assumes log-linear inactivation kinetics and invokes concepts of decimal reduction time (D(T)), z values, and accumulated lethality. However, many microbes, particularly spores, exhibit inactivation kinetics that are not log linear. This has led to alternative modeling approaches, such as the biphasic and Weibull models, that relax strong log-linear assumptions. Using a statistical framework, we developed a novel log-quadratic model, which approximates the biphasic and Weibull models and provides additional physiological interpretability. As a statistical linear model, the log-quadratic model is relatively simple to fit and straightforwardly provides confidence intervals for its fitted values. It allows a D(T)-like value to be derived, even from data that exhibit obvious "tailing." We also showed how existing models of non-log-linear microbial inactivation, such as the Weibull model, can fit into a statistical linear model framework that dramatically simplifies their solution. We applied the log-quadratic model to thermal inactivation data for the spore-forming bacterium Clostridium botulinum and evaluated its merits compared with those of popular previously described approaches. The log-quadratic model was used as the basis of a secondary model that can capture the dependence of microbial inactivation kinetics on temperature. This model, in turn, was linked to models of spore inactivation of Sapru et al. and Rodriguez et al. that posit different physiological states for spores within a population. We believe that the log-quadratic model provides a useful framework in which to test vitalistic and mechanistic hypotheses of inactivation by thermal and other processes.
Sensitivity of a Shallow-Water Model to Parameters
Kazantsev, Eugene
2011-01-01
An adjoint based technique is applied to a shallow water model in order to estimate the influence of the model's parameters on the solution. Among parameters the bottom topography, initial conditions, boundary conditions on rigid boundaries, viscosity coefficients Coriolis parameter and the amplitude of the wind stress tension are considered. Their influence is analyzed from three points of view: 1. flexibility of the model with respect to a parameter that is related to the lowest value of the cost function that can be obtained in the data assimilation experiment that controls this parameter; 2. possibility to improve the model by the parameter's control, i.e. whether the solution with the optimal parameter remains close to observations after the end of control; 3. sensitivity of the model solution to the parameter in a classical sense. That implies the analysis of the sensitivity estimates and their comparison with each other and with the local Lyapunov exponents that characterize the sensitivity of the mode...
Development of a mathematical model describing hydrolysis and co-fermentation of C6 and C5 sugars
DEFF Research Database (Denmark)
Morales Rodriguez, Ricardo; Gernaey, Krist; Meyer, Anne S.
2010-01-01
the degree of reliability. The mathematical model for the SSCF has been tested for a modified version of the process flowsheet proposed by the National Renewable Energy Laboratory (NREL). The model can now be used to evaluate different process configurations for 2G bioethanol production using corn stover......Reliable production of biofuels and specifically bioethanol has attracted a significant amount of research recently. Within this context, this study deals with dynamic simulation of bioethanol production processes and in particular aims at developing a mathematical model for describing simultaneous...... saccharification and co-fermentation (SSCF) of C6 and C5 sugars. Model construction has been carried out by combining existing mathematical models for enzymatic hydrolysis on the one hand and co-fermentation on the other hand. An inhibition of ethanol on cellulose conversion was introduced in order to increase...
Ferreira, Pedro O.; Pinho, Fernando T.; da Silva, Carlos B.
2016-12-01
A new subgrid-scale (SGS) model developed for large-eddy simulations (LES) of dilute polymer solutions, described by the finitely extensible nonlinear elastic constitutive equation closed with the Peterlin approximation, is presented. In this distortion similarity model (DSIM) the filtered conformation tensor evolution equation is based on the self-similarity of the polymer stretching terms, and on a global equilibrium of the trace of the conformation tensor, which is proportional to the elastic energy stored in the polymer molecules, while the SGS stresses are modelled with the classical Smagorinsky model. The DSIM closure is assessed in direct numerical simulations (DNS) of forced isotropic turbulence using classical a priori tests, and in a posteriori (LES) showing very good agreement with all the exact (filtered DNS) results. The DSIM model is simple to implement and computationally inexpensive and represents a major step forward in the numerical simulation of turbulent flows of Newtonian fluids with polymer additives.
Guz, Nataliia; Dokukin, Maxim; Kalaparthi, Vivekanand; Sokolov, Igor
2014-01-01
Here we investigated the question whether cells, being highly heterogeneous objects, could be described with the elastic modulus (effective Young’s modulus) in a self-consistent way. We performed a comparative analysis of the elastic modulus derived from the indentation data obtained with atomic force microscopy (AFM) on human cervical epithelial cells (both normal and cancerous). Both sharp (cone) and dull (2500-nm radius sphere) AFM probes were used. The indentation data were processed through different elastic models. The cell was approximated as a homogeneous elastic medium that had either 1), smooth hemispherical boundary (Hertz/Sneddon models) or 2), the boundary covered with a layer of glycocalyx and membrane protrusions (“brush” models). Consistency of these approximations was investigated. Specifically, we tested the independence of the elastic modulus of the indentation depth, which is assumed in these models. We demonstrated that only one model showed consistency in treating cells as a homogeneous elastic medium, namely, the brush model, when processing the indentation data collected with the dull AFM probe. The elastic modulus demonstrated strong depth dependence in all models: Hertz/Sneddon models (no brush taken into account), and when the brush model was applied to the data collected with sharp conical probes. We conclude that it is possible to describe the elastic properties of the cell body by means of an effective elastic modulus, used in a self-consistent way, when using the brush model to analyze data collected with a dull AFM probe. The nature of these results is discussed. PMID:25099796
Model description and kinetic parameter analysis of MTBE biodegradation in a packed bed reactor
DEFF Research Database (Denmark)
Waul, Christopher Kevin; Arvin, Erik; Schmidt, Jens Ejbye
2008-01-01
A dynamic modeling approach was used to estimate in-situ model parameters, which describe the degradation of methyl tert-butyl ether (MTBE) in a laboratory packed bed reactor. The measured dynamic response of MTBE pulses injected at the reactor's inlet was analyzed by least squares and parameter...
Estimation of shape model parameters for 3D surfaces
DEFF Research Database (Denmark)
Erbou, Søren Gylling Hemmingsen; Darkner, Sune; Fripp, Jurgen;
2008-01-01
Statistical shape models are widely used as a compact way of representing shape variation. Fitting a shape model to unseen data enables characterizing the data in terms of the model parameters. In this paper a Gauss-Newton optimization scheme is proposed to estimate shape model parameters of 3D s...
Compositional modelling of distributed-parameter systems
Maschke, Bernhard; Schaft, van der Arjan; Lamnabhi-Lagarrigue, F.; Loría, A.; Panteley, E.
2005-01-01
The Hamiltonian formulation of distributed-parameter systems has been a challenging reserach area for quite some time. (A nice introduction, especially with respect to systems stemming from fluid dynamics, can be found in [26], where also a historical account is provided.) The identification of the
Cortez, S; Alves, J L
2016-01-01
In articular cartilage the orientation of collagen fibres is not uniform, varying mostly with the depth on the tissue. Besides, the biomechanical response of each layer of the articular cartilage differs from the neighbouring ones, evolving through thickness as a function of the distribution, density and orientation of the collagen fibres. Based on a finite element implementation, a new continuum formulation is proposed to describe the remodelling and reorientation of the collagen fibres under arbitrary mechanical loads: the cartilaginous tissue is modelled based on a hyperelastic formulation, being the ground isotropic matrix described by a neo-Hookean law and the fibrillar anisotropic part modelled by a new anisotropic formulation introduced for the first time in the present work, in which both reorientation and remodelling are taken into account. To characterize the orientation of fibres, a structure tensor is defined to represent the expected distribution and orientation of fibres around a reference direc...
Bayesian approach to decompression sickness model parameter estimation.
Howle, L E; Weber, P W; Nichols, J M
2017-03-01
We examine both maximum likelihood and Bayesian approaches for estimating probabilistic decompression sickness model parameters. Maximum likelihood estimation treats parameters as fixed values and determines the best estimate through repeated trials, whereas the Bayesian approach treats parameters as random variables and determines the parameter probability distributions. We would ultimately like to know the probability that a parameter lies in a certain range rather than simply make statements about the repeatability of our estimator. Although both represent powerful methods of inference, for models with complex or multi-peaked likelihoods, maximum likelihood parameter estimates can prove more difficult to interpret than the estimates of the parameter distributions provided by the Bayesian approach. For models of decompression sickness, we show that while these two estimation methods are complementary, the credible intervals generated by the Bayesian approach are more naturally suited to quantifying uncertainty in the model parameters.
Institute of Scientific and Technical Information of China (English)
JIANG Wei; Veng-Cheong Lo
2005-01-01
Ferroelectric phase diagrams and the temperature dependence of polarization, dielectric properties of the three pseudo-spin in ferroelectric or ferro-antiferroelectric system described by a transverse Ising models are investigated on the basis of the effective-field theory with the differential operator technique. The effects of the transverse field and the coupling strength between the nearest-neighboring pseudo-spin on the physical properties are discussed in detail.
Weight-HbA1c-insulin-glucose model for describing disease progression of type 2 diabetes.
Choy, S; Kjellsson, M C; Karlsson, M O; de Winter, W
2016-01-01
A previous semi-mechanistic model described changes in fasting serum insulin (FSI), fasting plasma glucose (FPG), and glycated hemoglobin (HbA1c) in patients with type 2 diabetic mellitus (T2DM) by modeling insulin sensitivity and β-cell function. It was later suggested that change in body weight could affect insulin sensitivity, which this study evaluated in a population model to describe the disease progression of T2DM. Nonlinear mixed effects modeling was performed on data from 181 obese patients with newly diagnosed T2DM managed with diet and exercise for 67 weeks. Baseline β-cell function and insulin sensitivity were 61% and 25% of normal, respectively. Management with diet and exercise (mean change in body weight = -4.1 kg) was associated with an increase of insulin sensitivity (30.1%) at the end of the study. Changes in insulin sensitivity were associated with a decrease of FPG (range, 7.8-7.3 mmol/L) and HbA1c (6.7-6.4%). Weight change as an effector on insulin sensitivity was successfully evaluated in a semi-mechanistic population model.
Colomer, Maria Àngels; Margalida, Antoni; Pérez-Jiménez, Mario J
2013-01-01
Today, the volume of data and knowledge of processes necessitates more complex models that integrate all available information. This handicap has been solved thanks to the technological advances in both software and hardware. Computational tools available today have allowed developing a new family of models, known as computational models. The description of these models is difficult as they can not be expressed analytically, and it is therefore necessary to create protocols that serve as guidelines for future users. The Population Dynamics P systems models (PDP) are a novel and effective computational tool to model complex problems, are characterized by the ability to work in parallel (simultaneously interrelating different processes), are modular and have a high computational efficiency. However, the difficulty of describing these models therefore requires a protocol to unify the presentation and the steps to follow. We use two case studies to demonstrate the use and implementation of these computational models for population dynamics and ecological process studies, discussing briefly their potential applicability to simulate complex ecosystem dynamics.
Parameter estimation for stochastic hybrid model applied to urban traffic flow estimation
2015-01-01
This study proposes a novel data-based approach for estimating the parameters of a stochastic hybrid model describing the traffic flow in an urban traffic network with signalized intersections. The model represents the evolution of the traffic flow rate, measuring the number of vehicles passing a given location per time unit. This traffic flow rate is described using a mode-dependent first-order autoregressive (AR) stochastic process. The parameters of the AR process take different values dep...
Standard model parameters and the search for new physics
Energy Technology Data Exchange (ETDEWEB)
Marciano, W.J.
1988-04-01
In these lectures, my aim is to present an up-to-date status report on the standard model and some key tests of electroweak unification. Within that context, I also discuss how and where hints of new physics may emerge. To accomplish those goals, I have organized my presentation as follows: I discuss the standard model parameters with particular emphasis on the gauge coupling constants and vector boson masses. Examples of new physics appendages are also briefly commented on. In addition, because these lectures are intended for students and thus somewhat pedagogical, I have included an appendix on dimensional regularization and a simple computational example that employs that technique. Next, I focus on weak charged current phenomenology. Precision tests of the standard model are described and up-to-date values for the Cabibbo-Kobayashi-Maskawa (CKM) mixing matrix parameters are presented. Constraints implied by those tests for a 4th generation, supersymmetry, extra Z/prime/ bosons, and compositeness are also discussed. I discuss weak neutral current phenomenology and the extraction of sin/sup 2/ /theta//sub W/ from experiment. The results presented there are based on a recently completed global analysis of all existing data. I have chosen to concentrate that discussion on radiative corrections, the effect of a heavy top quark mass, and implications for grand unified theories (GUTS). The potential for further experimental progress is also commented on. I depart from the narrowest version of the standard model and discuss effects of neutrino masses and mixings. I have chosen to concentrate on oscillations, the Mikheyev-Smirnov- Wolfenstein (MSW) effect, and electromagnetic properties of neutrinos. On the latter topic, I will describe some recent work on resonant spin-flavor precession. Finally, I conclude with a prospectus on hopes for the future. 76 refs.
An automatic and effective parameter optimization method for model tuning
Directory of Open Access Journals (Sweden)
T. Zhang
2015-11-01
simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9 %. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameter tuning during the model development stage.
Baumer, Andreas; Bittermann, Kai; Klüver, Nils; Escher, Beate I
2017-07-19
In numerous studies on the toxicity of ionisable organic chemicals, it has been shown that the toxicity was typically higher, when larger fractions of the neutral species were present. This observation was explained in some cases by slower uptake of charged species. In other cases it was suggested that the neutral species has intrinsically higher toxicity than the charged species or is alone responsible for the toxicity. However, even permanently charged and organic chemicals with multiple acid and base functional groups and zwitterions are toxic. We set out to reconcile the divergent views and to compare the various existing models for describing the pH-dependence of toxicity with the goal to derive one model that is valid independent of the type and number of charges on the molecule. To achieve this goal we measured the cytotoxicity of 18 acidic, 15 basic and 9 multiprotic/zwitterionic pharmaceuticals at pH 5.5 to pH 9 with the bioluminescence inhibition test using Aliivibrio fischeri (Microtox assay). This assay is useful for an evaluation of various models to describe pH-dependent toxicity because the majority of chemicals act as baseline toxicants in this 30 min cytotoxicity assay. Therefore baseline toxicity with constant membrane concentrations of the sum of all chemical species of approximately 200 mmol kglip(-1) served for the validation of the suitability of the various tested models. We confirmed that most tested pharmaceuticals acted as baseline toxicants in this assay at all examined pH values, when toxicity was modeled with a mixture model of concentration addition between the neutral species and all charged species. An ion trapping model, that assumes that the membrane permeability of charged species is kinetically limited, improved model predictions for some pharmaceuticals and pH values. However, neither unhindered uptake nor no uptake of the charged species were ideal models; the reality lies presumably between the two limiting cases with a slower
Maĭmistov, A. I.
2003-02-01
We discuss propagation of an ultimately short (single-cycle) pulse of an electromagnetic field in a medium whose dispersion and nonlinear properties can be described by the cubic-quintic Duffing model, i.e., by an oscillator with third-and fifth-order anharmonicity. A system of equations governing the evolution of a unidirectional electromagnetic wave is analyzed without using the approximation of slowly varying envelopes. Three types of solutions of this system describing stationary propagation of a pulse in such a medium are found. When the signs of the anharmonicity constants are different, then the amplitude of a steady-state pulse is limited, but its energy may grow on account of an increase in its duration. The characteristics of such a pulse, referred to as an electromagnetic domain, are discussed.
Parameter estimation and error analysis in environmental modeling and computation
Kalmaz, E. E.
1986-01-01
A method for the estimation of parameters and error analysis in the development of nonlinear modeling for environmental impact assessment studies is presented. The modular computer program can interactively fit different nonlinear models to the same set of data, dynamically changing the error structure associated with observed values. Parameter estimation techniques and sequential estimation algorithms employed in parameter identification and model selection are first discussed. Then, least-square parameter estimation procedures are formulated, utilizing differential or integrated equations, and are used to define a model for association of error with experimentally observed data.
Estimation of Model and Parameter Uncertainty For A Distributed Rainfall-runoff Model
Engeland, K.
The distributed rainfall-runoff model Ecomag is applied as a regional model for nine catchments in the NOPEX area in Sweden. Ecomag calculates streamflow on a daily time resolution. The posterior distribution of the model parameters is conditioned on the observed streamflow in all nine catchments, and calculated using Bayesian statistics. The distribution is estimated by Markov chain Monte Carlo (MCMC). The Bayesian method requires a definition of the likelihood of the parameters. Two alter- native formulations are used. The first formulation is a subjectively chosen objective function describing the goodness of fit between the simulated and observed streamflow as it is used in the GLUE framework. The second formulation is to use a more statis- tically correct likelihood function that describes the simulation errors. The simulation error is defined as the difference between log-transformed observed and simulated streamflows. A statistical model for the simulation errors is constructed. Some param- eters are dependent on the catchment, while others depend on climate. The statistical and the hydrological parameters are estimated simultaneously. Confidence intervals, due to the uncertainty of the Ecomag parameters, for the simulated streamflow are compared for the two likelihood functions. Confidence intervals based on the statis- tical model for the simulation errors are also calculated. The results indicate that the parameter uncertainty depends on the formulation of the likelihood function. The sub- jectively chosen likelihood function gives relatively wide confidence intervals whereas the 'statistical' likelihood function gives more narrow confidence intervals. The statis- tical model for the simulation errors indicates that the structural errors of the model are as least as important as the parameter uncertainty.
Parameter estimation of hydrologic models using data assimilation
Kaheil, Y. H.
2005-12-01
The uncertainties associated with the modeling of hydrologic systems sometimes demand that data should be incorporated in an on-line fashion in order to understand the behavior of the system. This paper represents a Bayesian strategy to estimate parameters for hydrologic models in an iterative mode. The paper presents a modified technique called localized Bayesian recursive estimation (LoBaRE) that efficiently identifies the optimum parameter region, avoiding convergence to a single best parameter set. The LoBaRE methodology is tested for parameter estimation for two different types of models: a support vector machine (SVM) model for predicting soil moisture, and the Sacramento Soil Moisture Accounting (SAC-SMA) model for estimating streamflow. The SAC-SMA model has 13 parameters that must be determined. The SVM model has three parameters. Bayesian inference is used to estimate the best parameter set in an iterative fashion. This is done by narrowing the sampling space by imposing uncertainty bounds on the posterior best parameter set and/or updating the "parent" bounds based on their fitness. The new approach results in fast convergence towards the optimal parameter set using minimum training/calibration data and evaluation of fewer parameter sets. The efficacy of the localized methodology is also compared with the previously used Bayesian recursive estimation (BaRE) algorithm.
GIS-Based Hydrogeological-Parameter Modeling
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
A regression model is proposed to relate the variation of water well depth with topographic properties (area and slope), the variation of hydraulic conductivity and vertical decay factor. The implementation of this model in GIS environment (ARC/TNFO) based on known water data and DEM is used to estimate the variation of hydraulic conductivity and decay factor of different lithoiogy units in watershed context.
Cacciato, Marcello; Hoekstra, Henk
2013-01-01
The clustering of galaxies and the matter distribution around them can be described using the halo model complemented with a realistic description of the way galaxies populate dark matter haloes. This has been used successfully to describe statistical properties of samples of galaxies at z<0.2. Without adjusting any model parameters, we compare the predicted weak lensing signal induced by Luminous Red Galaxies to measurements from SDSS DR7 on much larger scales (up to ~90 h_{70}^{-1} Mpc) and at higher redshift (z~0.4). We find excellent agreement, suggesting that the model captures the main properties of the galaxy-dark matter connection. To extend the comparison to lenses at even higher redshifts we complement the SDSS data with shape measurements from the deeper RCS2, resulting in precise lensing measurements for lenses up to z~0.6. These measurements are also well described using the same model. Considering solely these weak lensing measurements, we robustly assess that, up to z~0.6, the number of cent...
Estimation of Kinetic Parameters in an Automotive SCR Catalyst Model
DEFF Research Database (Denmark)
Åberg, Andreas; Widd, Anders; Abildskov, Jens;
2016-01-01
A challenge during the development of models for simulation of the automotive Selective Catalytic Reduction catalyst is the parameter estimation of the kinetic parameters, which can be time consuming and problematic. The parameter estimation is often carried out on small-scale reactor tests, or p...
Accuracy of Parameter Estimation in Gibbs Sampling under the Two-Parameter Logistic Model.
Kim, Seock-Ho; Cohen, Allan S.
The accuracy of Gibbs sampling, a Markov chain Monte Carlo procedure, was considered for estimation of item and ability parameters under the two-parameter logistic model. Memory test data were analyzed to illustrate the Gibbs sampling procedure. Simulated data sets were analyzed using Gibbs sampling and the marginal Bayesian method. The marginal…
On linear models and parameter identifiability in experimental biological systems.
Lamberton, Timothy O; Condon, Nicholas D; Stow, Jennifer L; Hamilton, Nicholas A
2014-10-07
A key problem in the biological sciences is to be able to reliably estimate model parameters from experimental data. This is the well-known problem of parameter identifiability. Here, methods are developed for biologists and other modelers to design optimal experiments to ensure parameter identifiability at a structural level. The main results of the paper are to provide a general methodology for extracting parameters of linear models from an experimentally measured scalar function - the transfer function - and a framework for the identifiability analysis of complex model structures using linked models. Linked models are composed by letting the output of one model become the input to another model which is then experimentally measured. The linked model framework is shown to be applicable to designing experiments to identify the measured sub-model and recover the input from the unmeasured sub-model, even in cases that the unmeasured sub-model is not identifiable. Applications for a set of common model features are demonstrated, and the results combined in an example application to a real-world experimental system. These applications emphasize the insight into answering "where to measure" and "which experimental scheme" questions provided by both the parameter extraction methodology and the linked model framework. The aim is to demonstrate the tools' usefulness in guiding experimental design to maximize parameter information obtained, based on the model structure.
Institute of Scientific and Technical Information of China (English)
CHEN Ming; JIA Lai-Bing; YIN Xie-Zhen
2011-01-01
@@ Fish are supposed to be able to adapt to various underwater environments.The mechanical properties of the body of a fish is of essential importance in order to explore the source of high efficiency during fish swimming.We investigate the viscoelastic properties of the fins, muscle and skin of Crucian carp(carassius auratus).A fractional Zener model is used to fit the relaxation force and the results show that the model can describe the relaxation process well.With a Fourier transform, we discuss the response functions of the fins, muscle and skin of Crucian carp under the external excitation of a harmonic force.Comparison of these results with the cruising frequency of Crucian carp shows that the dissipation due to internal viscoelasticity during cruising is small.
Energy Technology Data Exchange (ETDEWEB)
Al-Nimr, Moh' d A.; Naji, Malak; Al-Wardat, Salem A. [Mechanical Engineering Department, Jordan University of Science and Technology, Irbid 22110, P.O. Box 3030 (Jordan)
2004-02-01
The thermal behavior of thin slab as described by the parabolic microscopic heat conduction model with variable thermal properties is investigated under two types of heating sources. These types are the unit step and the fluctuating harmonic heating sources. The considered thermal properties are the electron gas C{sub e} and the solid lattice C{sub L} total thermal capacities. It is found that the slab thermal behavior is more sensitive to the variation in C{sub e} as compared to the variation in C{sub L}. Assuming C{sub e} constant may cause an error of magnitude 19% while assuming C{sub L} constant causes an error of magnitude 5%. The sensitivity of the parabolic microscopic heat conduction model to the variation in C{sub e} is higher under the effect of a fluctuating heating source as compared to a unit step heating source. (authors)
Energy Technology Data Exchange (ETDEWEB)
Chavanis, Pierre-Henri [Laboratoire de Physique Théorique (IRSAMC), CNRS and UPS, Université de Toulouse (France)
2013-07-23
We construct a simple model of universe which 'unifies' vacuum energy and radiation on the one hand, and matter and dark energy on the other hand in the spirit of a generalized Chaplygin gas model. Specifically, the phases of early inflation and late accelerated expansion are described by a generalized equation of state p/c{sup 2} = αρ+kρ{sup 1+1/n} having a linear component p = αρc{sup 2} and a polytropic component p = kρ{sup 1+1/n}c{sup 2}. For α= 1/3, n= 1 and k=−4/(3ρ{sub P}), where ρ{sub P}= 5.1610{sup 99} g/m{sup 3} is the Planck density, this equation of state describes the transition between the vacuum energy era and the radiation era. For t≥ 0, the universe undergoes an inflationary expansion that brings it from the Planck size l{sub P}= 1.6210{sup −35} m to a size a{sub 1}= 2.6110{sup −6} m on a timescale of about 23.3 Planck times t{sub P}= 5.3910{sup −44} s (early inflation). When t > t{sub 1}= 23.3t{sub P}, the universe decelerates and enters in the radiation era. We interpret the transition from the vacuum energy era to the radiation era as a second order phase transition where the Planck constant ℏ plays the role of finite size effects (the standard Big Bang theory is recovered for ℏ= 0). For α= 0, n=−1 and k=−ρ{sub Λ}, where ρ{sub Λ}= 7.0210{sup −24} g/m{sup 3} is the cosmological density, the equation of state p/c{sup 2} = αρ+kρ{sup 1+1/n} describes the transition from a decelerating universe dominated by pressureless matter (baryonic and dark matter) to an accelerating universe dominated by dark energy (late inflation). This transition takes place at a size a{sub 2}= 0.204l{sub Λ}. corresponding to a time t{sub 2}= 0.203t{sub Λ} where l{sub Λ}= 4.38 10{sup 26} m is the cosmological length and t{sub Λ}= 1.46 10{sup 18} s the cosmological time. The present universe turns out to be just at the transition between these two periods (t{sub 0}∼t{sub 2}). Our model gives the same results as the standard
Parameter estimation and sensitivity analysis for a mathematical model with time delays of leukemia
Cândea, Doina; Halanay, Andrei; Rǎdulescu, Rodica; Tǎlmaci, Rodica
2017-01-01
We consider a system of nonlinear delay differential equations that describes the interaction between three competing cell populations: healthy, leukemic and anti-leukemia T cells involved in Chronic Myeloid Leukemia (CML) under treatment with Imatinib. The aim of this work is to establish which model parameters are the most important in the success or failure of leukemia remission under treatment using a sensitivity analysis of the model parameters. For the most significant parameters of the model which affect the evolution of CML disease during Imatinib treatment we try to estimate the realistic values using some experimental data. For these parameters, steady states are calculated and their stability is analyzed and biologically interpreted.
Biernacki, Piotr; Steinigeweg, Sven; Borchert, Axel; Uhlenhut, Frank
2013-01-01
Anaerobic digestion of organic waste plays an important role for the development of sustainable energy supply based on renewable resources. For further process optimization of anaerobic digestion, biogas production with the commonly used substrates, grass, maize, and green weed silage, together with industrial glycerine, were analyzed by the Weender analysis/van Soest method, and a simulation study was performed, based on the International Water Association's (IWA) Anaerobic Digestion Model No. 1 (ADM1). The simplex algorithm was applied to optimize kinetic constants for disintegration and hydrolysis steps for all examined substrates. Consequently, new parameters were determined for each evaluated substrate, tested against experimental cumulative biogas production results, and assessed against ADM1 default values for disintegration and hydrolysis kinetic constants, where the ADM1 values for mesophilic high rate and ADM1 values for solids were used. Results of the optimization lead to a precise prediction of the kinetics of anaerobic degradation of complex substrates.
CHAMP: Changepoint Detection Using Approximate Model Parameters
2014-06-01
positions as a Markov chain in which the transition probabilities are defined by the time since the last changepoint: p(τi+1 = t|τi = s) = g(t− s), (1...experimentally verified using artifi- cially generated data and are compared to those of Fearnhead and Liu [5]. 2 Related work Hidden Markov Models (HMMs) are...length α, and maximum number of particles M . Output: Viterbi path of changepoint times and models // Initialize data structures 1: max path, prev queue
WINKLER'S SINGLE-PARAMETER SUBGRADE MODEL FROM ...
African Journals Online (AJOL)
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[3, 9]. However, mainly due to the simplicity of Winkler's model in practical applications and .... this case, the coefficient B takes the dimension of a ... In plane-strain problems, the assumption of ... loaded circular region; s is the radial coordinate.
Wentworth, Mami Tonoe
Uncertainty quantification plays an important role when making predictive estimates of model responses. In this context, uncertainty quantification is defined as quantifying and reducing uncertainties, and the objective is to quantify uncertainties in parameter, model and measurements, and propagate the uncertainties through the model, so that one can make a predictive estimate with quantified uncertainties. Two of the aspects of uncertainty quantification that must be performed prior to propagating uncertainties are model calibration and parameter selection. There are several efficient techniques for these processes; however, the accuracy of these methods are often not verified. This is the motivation for our work, and in this dissertation, we present and illustrate verification frameworks for model calibration and parameter selection in the context of biological and physical models. First, HIV models, developed and improved by [2, 3, 8], describe the viral infection dynamics of an HIV disease. These are also used to make predictive estimates of viral loads and T-cell counts and to construct an optimal control for drug therapy. Estimating input parameters is an essential step prior to uncertainty quantification. However, not all the parameters are identifiable, implying that they cannot be uniquely determined by the observations. These unidentifiable parameters can be partially removed by performing parameter selection, a process in which parameters that have minimal impacts on the model response are determined. We provide verification techniques for Bayesian model calibration and parameter selection for an HIV model. As an example of a physical model, we employ a heat model with experimental measurements presented in [10]. A steady-state heat model represents a prototypical behavior for heat conduction and diffusion process involved in a thermal-hydraulic model, which is a part of nuclear reactor models. We employ this simple heat model to illustrate verification
Two parameters describing a superluminal neutrino%二参量描述的超光速中微子述的超光速中微子
Institute of Scientific and Technical Information of China (English)
倪光炯; 张操
2002-01-01
Based on the experimental data that the mass-square of neutrino might be negative, a quantum theory for superluminal neutrino is proposed. Two Weyl equations coupled together via a mass term respecting the maximum parity violation lead to a new equation which describes the superluminal motion of neutrino with permanent helicity. Various strange features of subluminal and superluminal particles can be ascribed to the relative variation of two contradictory fields superposing coherently inside the particle with the change of its speed u in the whole range (0＜u＜∞). Being compatible with the theory of special relativity, this theory may have various applications.%根据中微子质量平方是负值的实验数据,提出了一个关于超光速中微子的量子理论.用一个和最大宇称破坏相关的质量项将两个Weyl方程耦合在一起,得到一个描述具有永久螺旋度且超光速运动的中微子的新方程.超光速粒子的速度在 (0,∞)范围内变化,其内部相干迭加的两个矛盾场的相对变化导致亚光速粒子和超光速粒子的各种奇异特性.这个理论和狭义相对论是兼容的,因而可以有多方面的应用.
Improved Methodology for Parameter Inference in Nonlinear, Hydrologic Regression Models
Bates, Bryson C.
1992-01-01
A new method is developed for the construction of reliable marginal confidence intervals and joint confidence regions for the parameters of nonlinear, hydrologic regression models. A parameter power transformation is combined with measures of the asymptotic bias and asymptotic skewness of maximum likelihood estimators to determine the transformation constants which cause the bias or skewness to vanish. These optimized constants are used to construct confidence intervals and regions for the transformed model parameters using linear regression theory. The resulting confidence intervals and regions can be easily mapped into the original parameter space to give close approximations to likelihood method confidence intervals and regions for the model parameters. Unlike many other approaches to parameter transformation, the procedure does not use a grid search to find the optimal transformation constants. An example involving the fitting of the Michaelis-Menten model to velocity-discharge data from an Australian gauging station is used to illustrate the usefulness of the methodology.
A simulation of water pollution model parameter estimation
Kibler, J. F.
1976-01-01
A parameter estimation procedure for a water pollution transport model is elaborated. A two-dimensional instantaneous-release shear-diffusion model serves as representative of a simple transport process. Pollution concentration levels are arrived at via modeling of a remote-sensing system. The remote-sensed data are simulated by adding Gaussian noise to the concentration level values generated via the transport model. Model parameters are estimated from the simulated data using a least-squares batch processor. Resolution, sensor array size, and number and location of sensor readings can be found from the accuracies of the parameter estimates.
Linear Sigma Models With Strongly Coupled Phases -- One Parameter Models
Hori, Kentaro
2013-01-01
We systematically construct a class of two-dimensional $(2,2)$ supersymmetric gauged linear sigma models with phases in which a continuous subgroup of the gauge group is totally unbroken. We study some of their properties by employing a recently developed technique. The focus of the present work is on models with one K\\"ahler parameter. The models include those corresponding to Calabi-Yau threefolds, extending three examples found earlier by a few more, as well as Calabi-Yau manifolds of other dimensions and non-Calabi-Yau manifolds. The construction leads to predictions of equivalences of D-brane categories, systematically extending earlier examples. There is another type of surprise. Two distinct superconformal field theories corresponding to Calabi-Yau threefolds with different Hodge numbers, $h^{2,1}=23$ versus $h^{2,1}=59$, have exactly the same quantum K\\"ahler moduli space. The strong-weak duality plays a crucial r\\^ole in confirming this, and also is useful in the actual computation of the metric on t...
Parameter identification in tidal models with uncertain boundaries
Bagchi, Arunabha; ten Brummelhuis, P.G.J.; ten Brummelhuis, Paul
1994-01-01
In this paper we consider a simultaneous state and parameter estimation procedure for tidal models with random inputs, which is formulated as a minimization problem. It is assumed that some model parameters are unknown and that the random noise inputs only act upon the open boundaries. The
Exploring the interdependencies between parameters in a material model.
Energy Technology Data Exchange (ETDEWEB)
Silling, Stewart Andrew; Fermen-Coker, Muge
2014-01-01
A method is investigated to reduce the number of numerical parameters in a material model for a solid. The basis of the method is to detect interdependencies between parameters within a class of materials of interest. The method is demonstrated for a set of material property data for iron and steel using the Johnson-Cook plasticity model.
An Alternative Three-Parameter Logistic Item Response Model.
Pashley, Peter J.
Birnbaum's three-parameter logistic function has become a common basis for item response theory modeling, especially within situations where significant guessing behavior is evident. This model is formed through a linear transformation of the two-parameter logistic function in order to facilitate a lower asymptote. This paper discusses an…
Parameter identification in tidal models with uncertain boundaries
Bagchi, Arunabha; Brummelhuis, ten Paul
1994-01-01
In this paper we consider a simultaneous state and parameter estimation procedure for tidal models with random inputs, which is formulated as a minimization problem. It is assumed that some model parameters are unknown and that the random noise inputs only act upon the open boundaries. The hyperboli
A compact cyclic plasticity model with parameter evolution
DEFF Research Database (Denmark)
Krenk, Steen; Tidemann, L.
2017-01-01
, and it is demonstrated that this simple formulation enables very accurate representation of experimental results. An extension of the theory to account for model parameter evolution effects, e.g. in the form of changing yield level, is included in the form of extended evolution equations for the model parameters...
Determining Rheological Parameters of Generalized Yield-Power-Law Fluid Model
Directory of Open Access Journals (Sweden)
Stryczek Stanislaw
2004-09-01
Full Text Available The principles of determining rheological parameters of drilling muds described by a generalized yield-power-law are presented in the paper. Functions between tangent stresses and shear rate are given. The conditions of laboratory measurements of rheological parameters of generalized yield-power-law fluids are described and necessary mathematical relations for rheological model parameters given. With the block diagrams, the methodics of numerical solution of these relations has been presented. Rheological parameters of an exemplary drilling mud have been calculated with the use of this numerical program.
Regionalization of SWAT Model Parameters for Use in Ungauged Watersheds
Directory of Open Access Journals (Sweden)
Indrajeet Chaubey
2010-11-01
Full Text Available There has been a steady shift towards modeling and model-based approaches as primary methods of assessing watershed response to hydrologic inputs and land management, and of quantifying watershed-wide best management practice (BMP effectiveness. Watershed models often require some degree of calibration and validation to achieve adequate watershed and therefore BMP representation. This is, however, only possible for gauged watersheds. There are many watersheds for which there are very little or no monitoring data available, thus the question as to whether it would be possible to extend and/or generalize model parameters obtained through calibration of gauged watersheds to ungauged watersheds within the same region. This study explored the possibility of developing regionalized model parameter sets for use in ungauged watersheds. The study evaluated two regionalization methods: global averaging, and regression-based parameters, on the SWAT model using data from priority watersheds in Arkansas. Resulting parameters were tested and model performance determined on three gauged watersheds. Nash-Sutcliffe efficiencies (NS for stream flow obtained using regression-based parameters (0.53–0.83 compared well with corresponding values obtained through model calibration (0.45–0.90. Model performance obtained using global averaged parameter values was also generally acceptable (0.4 ≤ NS ≤ 0.75. Results from this study indicate that regionalized parameter sets for the SWAT model can be obtained and used for making satisfactory hydrologic response predictions in ungauged watersheds.
Azam, M.; Rahman, Z.; Talib, F.; Singh, K.J.
2012-01-01
PURPOSE: The purpose of this article is to identify and critically analyze healthcare establishment (HCE) quality parameters described in the literature. It aims to propose an integrated quality model that includes technical quality and associated supportive quality parameters to achieve optimum
Monte-Carlo Inversion of Travel-Time Data for the Estimation of Weld Model Parameters
Hunter, A. J.; Drinkwater, B. W.; Wilcox, P. D.
2011-06-01
The quality of ultrasonic array imagery is adversely affected by uncompensated variations in the medium properties. A method for estimating the parameters of a general model of an inhomogeneous anisotropic medium is described. The model is comprised of a number of homogeneous sub-regions with unknown anisotropy. Bayesian estimation of the unknown model parameters is performed via a Monte-Carlo Markov chain using the Metropolis-Hastings algorithm. Results are demonstrated using simulated weld data.
NWP model forecast skill optimization via closure parameter variations
Järvinen, H.; Ollinaho, P.; Laine, M.; Solonen, A.; Haario, H.
2012-04-01
We present results of a novel approach to tune predictive skill of numerical weather prediction (NWP) models. These models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. The current practice is to specify manually the numerical parameter values, based on expert knowledge. We developed recently a concept and method (QJRMS 2011) for on-line estimation of the NWP model parameters via closure parameter variations. The method called EPPES ("Ensemble prediction and parameter estimation system") utilizes ensemble prediction infra-structure for parameter estimation in a very cost-effective way: practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating an ensemble of predictions so that each member uses different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In this presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an ensemble prediction system emulator, based on the ECHAM5 atmospheric GCM show that the model tuning capability of EPPES scales up to realistic models and ensemble prediction systems. Finally, preliminary results of EPPES in the context of ECMWF forecasting system are presented.
Tian, Li-Ping; Liu, Lizhi; Wu, Fang-Xiang
2010-01-01
Derived from biochemical principles, molecular biological systems can be described by a group of differential equations. Generally these differential equations contain fractional functions plus polynomials (which we call improper fractional model) as reaction rates. As a result, molecular biological systems are nonlinear in both parameters and states. It is well known that it is challenging to estimate parameters nonlinear in a model. However, in fractional functions both the denominator and numerator are linear in the parameters while polynomials are also linear in parameters. Based on this observation, we develop an iterative linear least squares method for estimating parameters in biological systems modeled by improper fractional functions. The basic idea is to transfer optimizing a nonlinear least squares objective function into iteratively solving a sequence of linear least squares problems. The developed method is applied to the estimation of parameters in a metabolism system. The simulation results show the superior performance of the proposed method for estimating parameters in such molecular biological systems.
A Monte Carlo-adjusted goodness-of-fit test for parametric models describing spatial point patterns
Dao, Ngocanh
2014-04-03
Assessing the goodness-of-fit (GOF) for intricate parametric spatial point process models is important for many application fields. When the probability density of the statistic of the GOF test is intractable, a commonly used procedure is the Monte Carlo GOF test. Additionally, if the data comprise a single dataset, a popular version of the test plugs a parameter estimate in the hypothesized parametric model to generate data for theMonte Carlo GOF test. In this case, the test is invalid because the resulting empirical level does not reach the nominal level. In this article, we propose a method consisting of nested Monte Carlo simulations which has the following advantages: the bias of the resulting empirical level of the test is eliminated, hence the empirical levels can always reach the nominal level, and information about inhomogeneity of the data can be provided.We theoretically justify our testing procedure using Taylor expansions and demonstrate that it is correctly sized through various simulation studies. In our first data application, we discover, in agreement with Illian et al., that Phlebocarya filifolia plants near Perth, Australia, can follow a homogeneous Poisson clustered process that provides insight into the propagation mechanism of these plants. In our second data application, we find, in contrast to Diggle, that a pairwise interaction model provides a good fit to the micro-anatomy data of amacrine cells designed for analyzing the developmental growth of immature retina cells in rabbits. This article has supplementary material online. © 2013 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America.
Directory of Open Access Journals (Sweden)
Riionheimo Janne
2003-01-01
Full Text Available We describe a technique for estimating control parameters for a plucked string synthesis model using a genetic algorithm. The model has been intensively used for sound synthesis of various string instruments but the fine tuning of the parameters has been carried out with a semiautomatic method that requires some hand adjustment with human listening. An automated method for extracting the parameters from recorded tones is described in this paper. The calculation of the fitness function utilizes knowledge of the properties of human hearing.
DEFF Research Database (Denmark)
Traub, Franziska; Johansson, Roger; Holmqvist, Kenneth
Several studies have reported that spontaneous eye movements occur when visuospatial information is recalled from memory. Such gazes closely reflect the content and spatial relations from the original scene layout (e.g., Johansson et al., 2012). However, when someone has originally read a scene...... description, the memory of the physical layout of the text itself might compete with the memory of the spatial arrangement of the described scene. The present study was designed to address this fundamental issue by having participants read scene descriptions that were manipulated to be either congruent....... Recollection was performed orally while gazing at a blank screen. Results demonstrate that participant’s gaze patterns during recall more closely reflect the spatial layout of the scene than the physical locations of the text. We conclude that participants formed a mental model that represents the content...
Predictions for a Distributed Parameter Model Describing the Hepatic Processing of 2,3,7,8-TCDD
1999-02-15
currently valid OMB control number. 1. REPORT DATE 15 FEB 1999 2. REPORT TYPE 3. DATES COVERED 00-00-1999 to 00-00-1999 4. TITLE AND SUBTITLE...X’ !WTT$*6¡’C4’C®UKQ.D2ÀA’°��’C� 8R_GL=_B32¾Àè’D4�Ny-,BI/ 2C4’�¸·=J½�-?N#N\\2CE�’�6å’D) CBIG #<>0IR%Q=JB2¾-,.:@º4’C�DKBI<>GL=_B3’�E M
Some tests for parameter constancy in cointegrated VAR-models
DEFF Research Database (Denmark)
Hansen, Henrik; Johansen, Søren
1999-01-01
Some methods for the evaluation of parameter constancy in vector autoregressive (VAR) models are discussed. Two different ways of re-estimating the VAR model are proposed; one in which all parameters are estimated recursively based upon the likelihood function for the first observations, and anot...... be applied to test the constancy of the long-run parameters in the cointegrated VAR-model. All results are illustrated using a model for the term structure of interest rates on US Treasury securities. ...
Spatio-temporal modeling of nonlinear distributed parameter systems
Li, Han-Xiong
2011-01-01
The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein s
Le Saux, M.; Besson, J.; Carassou, S.
2015-11-01
A model is proposed to describe the mechanical behavior and the ductile failure at 25, 350 and 480 °C of Zircaloy-4 cladding tubes, as-received and hydrided up to 1200 wt. ppm (circumferential hydrides). The model is based on the Gurson-Tvergaard-Needleman model extended to account for plastic anisotropy and viscoplasticity. The model considers damage nucleation by both hydride cracking and debonding of the interface between the Laves phase precipitates and the matrix. The damage nucleation rate due to hydride cracking is directly deduced from quantitative microstructural observations. The other model parameters are identified from several experimental tests. Finite element simulations of axial tension, hoop tension, expansion due to compression and hoop plane strain tension experiments are performed to assess the model prediction capability. The calibrated model satisfactorily reproduces the effects of hydrogen and temperature on both the viscoplastic and the failure properties of the material. The results suggest that damage is anisotropic and influenced by the stress state for the non-hydrided or moderately hydrided material and becomes more isotropic for high hydrogen contents.
Directory of Open Access Journals (Sweden)
Baker Syed
2011-01-01
Full Text Available Abstract In systems biology, experimentally measured parameters are not always available, necessitating the use of computationally based parameter estimation. In order to rely on estimated parameters, it is critical to first determine which parameters can be estimated for a given model and measurement set. This is done with parameter identifiability analysis. A kinetic model of the sucrose accumulation in the sugar cane culm tissue developed by Rohwer et al. was taken as a test case model. What differentiates this approach is the integration of an orthogonal-based local identifiability method into the unscented Kalman filter (UKF, rather than using the more common observability-based method which has inherent limitations. It also introduces a variable step size based on the system uncertainty of the UKF during the sensitivity calculation. This method identified 10 out of 12 parameters as identifiable. These ten parameters were estimated using the UKF, which was run 97 times. Throughout the repetitions the UKF proved to be more consistent than the estimation algorithms used for comparison.
Baker, Syed Murtuza; Poskar, C Hart; Junker, Björn H
2011-10-11
In systems biology, experimentally measured parameters are not always available, necessitating the use of computationally based parameter estimation. In order to rely on estimated parameters, it is critical to first determine which parameters can be estimated for a given model and measurement set. This is done with parameter identifiability analysis. A kinetic model of the sucrose accumulation in the sugar cane culm tissue developed by Rohwer et al. was taken as a test case model. What differentiates this approach is the integration of an orthogonal-based local identifiability method into the unscented Kalman filter (UKF), rather than using the more common observability-based method which has inherent limitations. It also introduces a variable step size based on the system uncertainty of the UKF during the sensitivity calculation. This method identified 10 out of 12 parameters as identifiable. These ten parameters were estimated using the UKF, which was run 97 times. Throughout the repetitions the UKF proved to be more consistent than the estimation algorithms used for comparison.
Directory of Open Access Journals (Sweden)
G. Iordanou
2011-10-01
Full Text Available This work describes the developed of a lumped parameter model and demonstrates its practical application. The lumped parameter mathematical model is a useful instrument to be used for rapid determination of design dimensions and operational performance of solar collectors at the designing stage. Such model which incorporates data from relevant Computational Fluid Dynamics design and experimental investigations can provide an acceptable accuracy in predictions and can be used as an effective design tool. A computer algorithm validates the lumped parameter model via a window environment program.
Identification of hydrological model parameter variation using ensemble Kalman filter
Deng, Chao; Liu, Pan; Guo, Shenglian; Li, Zejun; Wang, Dingbao
2016-12-01
Hydrological model parameters play an important role in the ability of model prediction. In a stationary context, parameters of hydrological models are treated as constants; however, model parameters may vary with time under climate change and anthropogenic activities. The technique of ensemble Kalman filter (EnKF) is proposed to identify the temporal variation of parameters for a two-parameter monthly water balance model (TWBM) by assimilating the runoff observations. Through a synthetic experiment, the proposed method is evaluated with time-invariant (i.e., constant) parameters and different types of parameter variations, including trend, abrupt change and periodicity. Various levels of observation uncertainty are designed to examine the performance of the EnKF. The results show that the EnKF can successfully capture the temporal variations of the model parameters. The application to the Wudinghe basin shows that the water storage capacity (SC) of the TWBM model has an apparent increasing trend during the period from 1958 to 2000. The identified temporal variation of SC is explained by land use and land cover changes due to soil and water conservation measures. In contrast, the application to the Tongtianhe basin shows that the estimated SC has no significant variation during the simulation period of 1982-2013, corresponding to the relatively stationary catchment properties. The evapotranspiration parameter (C) has temporal variations while no obvious change patterns exist. The proposed method provides an effective tool for quantifying the temporal variations of the model parameters, thereby improving the accuracy and reliability of model simulations and forecasts.
Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model
Zuhdi, Shaifudin; Retno Sari Saputro, Dewi; Widyaningsih, Purnami
2017-06-01
A regression model is the representation of relationship between independent variable and dependent variable. The dependent variable has categories used in the logistic regression model to calculate odds on. The logistic regression model for dependent variable has levels in the logistics regression model is ordinal. GWOLR model is an ordinal logistic regression model influenced the geographical location of the observation site. Parameters estimation in the model needed to determine the value of a population based on sample. The purpose of this research is to parameters estimation of GWOLR model using R software. Parameter estimation uses the data amount of dengue fever patients in Semarang City. Observation units used are 144 villages in Semarang City. The results of research get GWOLR model locally for each village and to know probability of number dengue fever patient categories.
Universally sloppy parameter sensitivities in systems biology models.
Directory of Open Access Journals (Sweden)
Ryan N Gutenkunst
2007-10-01
Full Text Available Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.
Parameter estimation and investigation of a bolted joint model
Shiryayev, O. V.; Page, S. M.; Pettit, C. L.; Slater, J. C.
2007-11-01
Mechanical joints are a primary source of variability in the dynamics of built-up structures. Physical phenomena in the joint are quite complex and therefore too impractical to model at the micro-scale. This motivates the development of lumped parameter joint models with discrete interfaces so that they can be easily implemented in finite element codes. Among the most important considerations in choosing a model for dynamically excited systems is its ability to model energy dissipation. This translates into the need for accurate and reliable methods to measure model parameters and estimate their inherent variability from experiments. The adjusted Iwan model was identified as a promising candidate for representing joint dynamics. Recent research focused on this model has exclusively employed impulse excitation in conjunction with neural networks to identify the model parameters. This paper presents an investigation of an alternative parameter estimation approach for the adjusted Iwan model, which employs data from oscillatory forcing. This approach is shown to produce parameter estimates with precision similar to the impulse excitation method for a range of model parameters.
Modeling and Parameter Estimation of a Small Wind Generation System
Directory of Open Access Journals (Sweden)
Carlos A. Ramírez Gómez
2013-11-01
Full Text Available The modeling and parameter estimation of a small wind generation system is presented in this paper. The system consists of a wind turbine, a permanent magnet synchronous generator, a three phase rectifier, and a direct current load. In order to estimate the parameters wind speed data are registered in a weather station located in the Fraternidad Campus at ITM. Wind speed data were applied to a reference model programed with PSIM software. From that simulation, variables were registered to estimate the parameters. The wind generation system model together with the estimated parameters is an excellent representation of the detailed model, but the estimated model offers a higher flexibility than the programed model in PSIM software.
Parameter estimation of hidden periodic model in random fields
Institute of Scientific and Technical Information of China (English)
何书元
1999-01-01
Two-dimensional hidden periodic model is an important model in random fields. The model is used in the field of two-dimensional signal processing, prediction and spectral analysis. A method of estimating the parameters for the model is designed. The strong consistency of the estimators is proved.
Directory of Open Access Journals (Sweden)
Tjahyo NugrohoAdji
2013-07-01
The result shows that firstly, the aquifer within the research area can be grouped into several aquifer systems (i.e. denudational hill, colluvial plain, alluvial plain, and beach ridges from recharge to discharge which generally have potential groundwater resources in terms of the depth and fluctuation of groundwater table. Secondly, flownets analysis gives three flowpaths that are plausible to be modeled in order to describe their hydrogeochemical reactions. Thirdly, the Saturation Indices (SI analysis shows that there are a positive correlation between the mineral occurrence and composition and the value of SI from recharge to discharge. In addition, The Mass Balance Model indicates that dissolution and precipitation of aquifer minerals is dominantly change the chemical composition along flowpath and the rate of the mass transfer between two wells shows a discrepancy and be certain of the percentage of the nature of aquifer mineral. Lastly, there is an interesting characteristic of mass balance chemical reaction occurs which is the entire chemical reaction shows that the sum of smallest mineral fmmol/litre will firstly always totally be reacted.
Luzanov, Anatoliy V.; Plasser, Felix; Das, Anita; Lischka, Hans
2017-02-01
We present a verification and significant algorithmic improvement of the quasi-correlation tight-binding (QCTB) scheme (a Hückel-Hubbard-type model mimicking electron correlation) for describing effectively unpaired electrons in the spirit of Head-Gordon's approach [M. Head-Gordon, Chem. Phys. Lett. 380, 488 (2003)]. For comparison purposes, results based on the high-level ab initio multireference averaged quadratic coupled cluster method previously computed in our works are invoked. In doing so, typical polyaromatic hydrocarbons (polyacenes, periacenes, zethrenes, and the Clar goblet) are studied. The evaluation shows that the QCTB Hückel-like scheme extended for electron correlation effects provides a qualitatively and in several cases also quantitatively good picture of the unpairing electrons in formally closed-shell electronic systems. Additionally, fairly large nanographene systems of triangulene structure (C426) and a perforated nanoribbon (C8860) have been treated at QCTB level. Two analytical model problems in the framework of QCTB prove the ability of this approximation to give a correct description of natural orbital occupancy spectra. For the studied QCTB scheme, an efficient algorithm is elaborated, and large-scale calculations of radical characteristics for nanographene networks with thousands of carbon atoms are possible.
Identification of parameters of discrete-continuous models
Energy Technology Data Exchange (ETDEWEB)
Cekus, Dawid, E-mail: cekus@imipkm.pcz.pl; Warys, Pawel, E-mail: warys@imipkm.pcz.pl [Institute of Mechanics and Machine Design Foundations, Czestochowa University of Technology, Dabrowskiego 73, 42-201 Czestochowa (Poland)
2015-03-10
In the paper, the parameters of a discrete-continuous model have been identified on the basis of experimental investigations and formulation of optimization problem. The discrete-continuous model represents a cantilever stepped Timoshenko beam. The mathematical model has been formulated and solved according to the Lagrange multiplier formalism. Optimization has been based on the genetic algorithm. The presented proceeding’s stages make the identification of any parameters of discrete-continuous systems possible.
Estimating parameters for generalized mass action models with connectivity information
Directory of Open Access Journals (Sweden)
Voit Eberhard O
2009-05-01
Full Text Available Abstract Background Determining the parameters of a mathematical model from quantitative measurements is the main bottleneck of modelling biological systems. Parameter values can be estimated from steady-state data or from dynamic data. The nature of suitable data for these two types of estimation is rather different. For instance, estimations of parameter values in pathway models, such as kinetic orders, rate constants, flux control coefficients or elasticities, from steady-state data are generally based on experiments that measure how a biochemical system responds to small perturbations around the steady state. In contrast, parameter estimation from dynamic data requires time series measurements for all dependent variables. Almost no literature has so far discussed the combined use of both steady-state and transient data for estimating parameter values of biochemical systems. Results In this study we introduce a constrained optimization method for estimating parameter values of biochemical pathway models using steady-state information and transient measurements. The constraints are derived from the flux connectivity relationships of the system at the steady state. Two case studies demonstrate the estimation results with and without flux connectivity constraints. The unconstrained optimal estimates from dynamic data may fit the experiments well, but they do not necessarily maintain the connectivity relationships. As a consequence, individual fluxes may be misrepresented, which may cause problems in later extrapolations. By contrast, the constrained estimation accounting for flux connectivity information reduces this misrepresentation and thereby yields improved model parameters. Conclusion The method combines transient metabolic profiles and steady-state information and leads to the formulation of an inverse parameter estimation task as a constrained optimization problem. Parameter estimation and model selection are simultaneously carried out
Energy Technology Data Exchange (ETDEWEB)
Nicoulaud-Gouin, V.; Metivier, J.M.; Gonze, M.A. [Institut de Radioprotection et de Surete Nucleaire-PRP-ENV/SERIS/LM2E (France); Garcia-Sanchez, L. [Institut de Radioprotection et de Surete Nucleaire-PRPENV/SERIS/L2BT (France)
2014-07-01
The increasing spatial and temporal complexity of models demands methods capable of ranking the influence of their large numbers of parameters. This question specifically arises in assessment studies on the consequences of the Fukushima accident. Sensitivity analysis aims at measuring the influence of input variability on the output response. Generally, two main approaches are distinguished (Saltelli, 2001, Iooss, 2011): - Screening approach, less expensive in computation time and allowing to identify non influential parameters; - Measures of importance, introducing finer quantitative indices. In this category, there are regression-based methods, assuming a linear or monotonic response (Pearson coefficient, Spearman coefficient), and variance-based methods, without assumptions on the model but requiring an increasingly prohibitive number of evaluations when the number of parameters increases. These approaches are available in various statistical programs (notably R) but are still poorly integrated in modelling platforms of radioecological risk assessment. This work aimed at illustrating the benefits of sensitivity analysis in the course of radioecological risk assessments This study used two complementary state-of-art global sensitivity analysis methods: - The screening method of Morris (Morris, 1991; Campolongo et al., 2007) based on limited model evaluations with a one-at-a-time (OAT) design; - The variance-based Sobol' sensitivity analysis (Saltelli, 2002) based a large number of model evaluations in the parameter space with a quasi-random sampling (Owen, 2003). Sensitivity analyses were applied on a dynamic Soil-Plant Deposition Model (Gonze et al., submitted to this conference) predicting foliar concentration in weeds after atmospheric radionuclide fallout. The Soil-Plant Deposition Model considers two foliage pools and a root pool, and describes foliar biomass growth with a Verhulst model. The developed semi-analytic formulation of foliar concentration
Chakraborty, Snehasis; Rao, Pavuluri Srinivasa; Mishra, Hari Niwas
2015-10-15
High pressure inactivation of natural microbiota viz. aerobic mesophiles (AM), psychrotrophs (PC), yeasts and molds (YM), total coliforms (TC) and lactic acid bacteria (LAB) in pineapple puree was studied within the experimental domain of 0.1-600 MPa and 30-50 °C with a treatment time up to 20 min. A complete destruction of yeasts and molds was obtained at 500 MPa/50 °C/15 min; whereas no counts were detected for TC and LAB at 300 MPa/30 °C/15 min. A maximum of two log cycle reductions was obtained for YM during pulse pressurization at the severe process intensity of 600 MPa/50 °C/20 min. The Weibull model clearly described the non-linearity of the survival curves during the isobaric period. The tailing effect, as confirmed by the shape parameter (β) of the survival curve, was obtained in case of YM (β1) was observed for the other microbial groups. Analogous to thermal death kinetics, the activation energy (Ea, kJ·mol(-1)) and the activation volume (Va, mL·mol(-1)) values were computed further to describe the temperature and pressure dependencies of the scale parameter (δ, min), respectively. A higher δ value was obtained for each microbe at a lower temperature and it decreased with an increase in pressure. A secondary kinetic model was developed describing the inactivation rate (k, min(-1)) as a function of pressure (P, MPa) and temperature (T, K) including the dependencies of Ea and Va on P and T, respectively.
Estimation of the input parameters in the Feller neuronal model
Ditlevsen, Susanne; Lansky, Petr
2006-06-01
The stochastic Feller neuronal model is studied, and estimators of the model input parameters, depending on the firing regime of the process, are derived. Closed expressions for the first two moments of functionals of the first-passage time (FTP) through a constant boundary in the suprathreshold regime are derived, which are used to calculate moment estimators. In the subthreshold regime, the exponentiality of the FTP is utilized to characterize the input parameters. The methods are illustrated on simulated data. Finally, approximations of the first-passage-time moments are suggested, and biological interpretations and comparisons of the parameters in the Feller and the Ornstein-Uhlenbeck models are discussed.
An automatic and effective parameter optimization method for model tuning
Directory of Open Access Journals (Sweden)
T. Zhang
2015-05-01
Full Text Available Physical parameterizations in General Circulation Models (GCMs, having various uncertain parameters, greatly impact model performance and model climate sensitivity. Traditional manual and empirical tuning of these parameters is time consuming and ineffective. In this study, a "three-step" methodology is proposed to automatically and effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. Different from the traditional optimization methods, two extra steps, one determines parameter sensitivity and the other chooses the optimum initial value of sensitive parameters, are introduced before the downhill simplex method to reduce the computational cost and improve the tuning performance. Atmospheric GCM simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9%. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameters tuning during the model development stage.
Optimal parameters for the FFA-Beddoes dynamic stall model
Energy Technology Data Exchange (ETDEWEB)
Bjoerck, A.; Mert, M. [FFA, The Aeronautical Research Institute of Sweden, Bromma (Sweden); Madsen, H.A. [Risoe National Lab., Roskilde (Denmark)
1999-03-01
Unsteady aerodynamic effects, like dynamic stall, must be considered in calculation of dynamic forces for wind turbines. Models incorporated in aero-elastic programs are of semi-empirical nature. Resulting aerodynamic forces therefore depend on values used for the semi-empiricial parameters. In this paper a study of finding appropriate parameters to use with the Beddoes-Leishman model is discussed. Minimisation of the `tracking error` between results from 2D wind tunnel tests and simulation with the model is used to find optimum values for the parameters. The resulting optimum parameters show a large variation from case to case. Using these different sets of optimum parameters in the calculation of blade vibrations, give rise to quite different predictions of aerodynamic damping which is discussed. (au)
Do Lumped-Parameter Models Provide the Correct Geometrical Damping?
DEFF Research Database (Denmark)
Andersen, Lars
This paper concerns the formulation of lumped-parameter models for rigid footings on homogenous or stratified soil. Such models only contain a few degrees of freedom, which makes them ideal for inclusion in aero-elastic codes for wind turbines and other models applied to fast evaluation of struct......This paper concerns the formulation of lumped-parameter models for rigid footings on homogenous or stratified soil. Such models only contain a few degrees of freedom, which makes them ideal for inclusion in aero-elastic codes for wind turbines and other models applied to fast evaluation...... response during excitation and the geometrical damping related to free vibrations of a hexagonal footing. The optimal order of a lumped-parameter model is determined for each degree of freedom, i.e. horizontal and vertical translation as well as torsion and rocking. In particular, the necessity of coupling...... between horizontal sliding and rocking is discussed....
A New Approach for Parameter Optimization in Land Surface Model
Institute of Scientific and Technical Information of China (English)
LI Hongqi; GUO Weidong; SUN Guodong; ZHANG Yaocun; FU Congbin
2011-01-01
In this study,a new parameter optimization method was used to investigate the expansion of conditional nonlinear optimal perturbation (CNOP) in a land surface model (LSM) using long-term enhanced field observations at Tongyn station in Jilin Province,China,combined with a sophisticated LSM (common land model,CoLM).Tongyu station is a reference site of the international Coordinated Energy and Water Cycle Observations Project (CEOP) that has studied semiarid regions that have undergone desertification,salination,and degradation since late 1960s.In this study,three key land-surface parameters,namely,soil color,proportion of sand or clay in soil,and leaf-area index were chosen as parameters to be optimized.Our study comprised three experiments:First,a single-parameter optimization was performed,while the second and third experiments performed triple- and six-parameter optinizations,respectively.Notable improvements in simulating sensible heat flux (SH),latent heat flux (LH),soil temperature (TS),and moisture (MS) at shallow layers were achieved using the optimized parameters.The multiple-parameter optimization experiments performed better than the single-parameter experminent.All results demonstrate that the CNOP method can be used to optimize expanded parameters in an LSM.Moreover,clear mathematical meaning,simple design structure,and rapid computability give this method great potential for further application to parameter optimization in LSMs.
Three-dimensional FEM model of FBGs in PANDA fibers with experimentally determined model parameters
Lindner, Markus; Hopf, Barbara; Koch, Alexander W.; Roths, Johannes
2017-04-01
A 3D-FEM model has been developed to improve the understanding of multi-parameter sensing with Bragg gratings in attached or embedded polarization maintaining fibers. The material properties of the fiber, especially Young's modulus and Poisson's ratio of the fiber's stress applying parts, are crucial for accurate simulations, but are usually not provided by the manufacturers. A methodology is presented to determine the unknown parameters by using experimental characterizations of the fiber and iterative FEM simulations. The resulting 3D-Model is capable of describing the change in birefringence of the free fiber when exposed to longitudinal strain. In future studies the 3D-FEM model will be employed to study the interaction of PANDA fibers with the surrounding materials in which they are embedded.
Morton, Seth Michael; Jensen, Lasse
2011-10-07
A frequency-dependent quantum mechanics/molecular mechanics method for the calculation of response properties of molecules adsorbed on metal nanoparticles is presented. This discrete interaction model/quantum mechanics (DIM/QM) method represents the nanoparticle atomistically, thus accounting for the local environment of the nanoparticle surface on the optical properties of the adsorbed molecule. Using the DIM/QM method, we investigate the coupling between the absorption of a silver nanoparticle and of a substituted naphthoquinone. This system is chosen since it shows strong coupling due to a molecular absorption peak that overlaps with the plasmon excitation in the metal nanoparticle. We show that there is a strong dependence not only on the distance of the molecule from the metal nanoparticle but also on its orientation relative to the nanoparticle. We find that when the transition dipole moment of an excitation is oriented towards the nanoparticle there is a significant increase in the molecular absorption as a result of coupling to the metal nanoparticle. In contrast, we find that the molecular absorption is decreased when the transition dipole moment is oriented parallel to the metal nanoparticle. The coupling between the molecule and the metal nanoparticle is found to be surprisingly long range and important on a length scale comparable to the size of the metal nanoparticle. A simple analytical model that describes the molecule and the metal nanoparticle as two interacting point objects is found to be in excellent agreement with the full DIM/QM calculations over the entire range studied. The results presented here are important for understanding plasmon-exciton hybridization, plasmon enhanced photochemistry, and single-molecule surface-enhanced Raman scattering.
Parameter Estimation for a Computable General Equilibrium Model
DEFF Research Database (Denmark)
Arndt, Channing; Robinson, Sherman; Tarp, Finn
. Second, it permits incorporation of prior information on parameter values. Third, it can be applied in the absence of copious data. Finally, it supplies measures of the capacity of the model to reproduce the historical record and the statistical significance of parameter estimates. The method is applied...
Estimating winter wheat phenological parameters: Implications for crop modeling
Crop parameters, such as the timing of developmental events, are critical for accurate simulation results in crop simulation models, yet uncertainty often exists in determining the parameters. Factors contributing to the uncertainty include: a) sources of variation within a plant (i.e., within diffe...
New Values of Cross-Talk Parameters for Twisted Pair Model
Directory of Open Access Journals (Sweden)
Milos Kozak
2010-01-01
Full Text Available Near-end Crosstalk (NEXT and Far-end Crosstalk (FEXT of unshielded twisted pair (UTP cable are the main factors limiting the information capacity in data transmission. Crosstalk depends mostly on the frequency. Frequency dependent transfer functions and crosstalk attenuation may be obtained by measurement, but for the analytical description of the transmission channel's parameters is useful to define functions modelling the crosstalk. The paper describes the measuring facility, presents the measured waveforms and the values of model parameters.
Estimating Parameters for the PVsyst Version 6 Photovoltaic Module Performance Model
Energy Technology Data Exchange (ETDEWEB)
Hansen, Clifford [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
2015-10-01
We present an algorithm to determine parameters for the photovoltaic module perf ormance model encoded in the software package PVsyst(TM) version 6. Our method operates on current - voltage (I - V) measured over a range of irradiance and temperature conditions. We describe the method and illustrate its steps using data for a 36 cell crystalli ne silicon module. We qualitatively compare our method with one other technique for estimating parameters for the PVsyst(TM) version 6 model .
Bates, P. D.; Neal, J. C.; Fewtrell, T. J.
2012-12-01
In this we paper we consider two related questions. First, we address the issue of how much physical complexity is necessary in a model in order to simulate floodplain inundation to within validation data error. This is achieved through development of a single code/multiple physics hydraulic model (LISFLOOD-FP) where different degrees of complexity can be switched on or off. Different configurations of this code are applied to four benchmark test cases, and compared to the results of a number of industry standard models. Second we address the issue of how parameter sensitivity and transferability change with increasing complexity using numerical experiments with models of different physical and geometric intricacy. Hydraulic models are a good example system with which to address such generic modelling questions as: (1) they have a strong physical basis; (2) there is only one set of equations to solve; (3) they require only topography and boundary conditions as input data; and (4) they typically require only a single free parameter, namely boundary friction. In terms of complexity required we show that for the problem of sub-critical floodplain inundation a number of codes of different dimensionality and resolution can be found to fit uncertain model validation data equally well, and that in this situation Occam's razor emerges as a useful logic to guide model selection. We find also find that model skill usually improves more rapidly with increases in model spatial resolution than increases in physical complexity, and that standard approaches to testing hydraulic models against laboratory data or analytical solutions may fail to identify this important fact. Lastly, we find that in benchmark testing studies significant differences can exist between codes with identical numerical solution techniques as a result of auxiliary choices regarding the specifics of model implementation that are frequently unreported by code developers. As a consequence, making sound
Miano, Alberto Claudio; Ibarz, Albert; Augusto, Pedro Esteves Duarte
2016-03-01
The aim of this work was to demonstrate how ultrasound mechanisms (direct and indirect effects) improve the mass transfer phenomena in food processing, and which part of the process they are more effective in. Two model cases were evaluated: the hydration of sorghum grain (with two water activities) and the influx of a pigment into melon cylinders. Different treatments enabled us to evaluate and discriminate both direct (inertial flow and "sponge effect") and indirect effects (micro channel formation), alternating pre-treatments and treatments using an ultrasonic bath (20 kHz of frequency and 28 W/L of volumetric power) and a traditional water-bath. It was demonstrated that both the effects of ultrasound technology are more effective in food with higher water activity, the micro channels only forming in moist food. Moreover, micro channel formation could also be observed using agar gel cylinders, verifying the random formation of these due to cavitation. The direct effects were shown to be important in mass transfer enhancement not only in moist food, but also in dry food, this being improved by the micro channels formed and the porosity of the food. In conclusion, the improvement in mass transfer due to direct and indirect effects was firstly discriminated and described. It was proven that both phenomena are important for mass transfer in moist foods, while only the direct effects are important for dry foods. Based on these results, better processing using ultrasound technology can be obtained.
Le Saux, M.; Besson, J.; Carassou, S.; Poussard, C.; Averty, X.
2008-08-01
This paper presents a unified phenomenological model to describe the anisotropic viscoplastic mechanical behavior of cold-worked stress relieved (CWSR) Zircaloy-4 fuel claddings submitted to reactivity initiated accident (RIA) loading conditions. The model relies on a multiplicative viscoplastic formulation and reproduces strain hardening, strain rate sensitivity and plastic anisotropy of the material. It includes temperature, fluence and irradiation conditions dependences within RIA typical ranges. Model parameters have been tuned using axial tensile, hoop tensile and closed-end internal pressurization tests results essentially obtained from the PROMETRA program, dedicated to the study of zirconium alloys under RIA loading conditions. Once calibrated, the model provides a reliable description of the mechanical behavior of the fresh and irradiated (fluence up to 10×1025 nm or burnup up to 64 GWd/tU) material within large temperature (from 20 °C up to 1100 °C) and strain rate ranges (from 3×10-4 s up to 5 s), representative of the RIA spectrum. Finally, the model is used for the finite element analysis of the hoop tensile tests performed within the PROMETRA program.
Directory of Open Access Journals (Sweden)
Houda Salhi
2016-01-01
Full Text Available This paper deals with the parameter estimation problem for multivariable nonlinear systems described by MIMO state-space Wiener models. Recursive parameters and state estimation algorithms are presented using the least squares technique, the adjustable model, and the Kalman filter theory. The basic idea is to estimate jointly the parameters, the state vector, and the internal variables of MIMO Wiener models based on a specific decomposition technique to extract the internal vector and avoid problems related to invertibility assumption. The effectiveness of the proposed algorithms is shown by an illustrative simulation example.
Parameter Estimates in Differential Equation Models for Population Growth
Winkel, Brian J.
2011-01-01
We estimate the parameters present in several differential equation models of population growth, specifically logistic growth models and two-species competition models. We discuss student-evolved strategies and offer "Mathematica" code for a gradient search approach. We use historical (1930s) data from microbial studies of the Russian biologist,…
Dynamic Modeling and Parameter Identification of Power Systems
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
@@ The generator, the excitation system, the steam turbine and speed governor, and the load are the so called four key models of power systems. Mathematical modeling and parameter identification for the four key models are of great importance as the basis for designing, operating, and analyzing power systems.
Dynamic Load Model using PSO-Based Parameter Estimation
Taoka, Hisao; Matsuki, Junya; Tomoda, Michiya; Hayashi, Yasuhiro; Yamagishi, Yoshio; Kanao, Norikazu
This paper presents a new method for estimating unknown parameters of dynamic load model as a parallel composite of a constant impedance load and an induction motor behind a series constant reactance. An adequate dynamic load model is essential for evaluating power system stability, and this model can represent the behavior of actual load by using appropriate parameters. However, the problem of this model is that a lot of parameters are necessary and it is not easy to estimate a lot of unknown parameters. We propose an estimating method based on Particle Swarm Optimization (PSO) which is a non-linear optimization method by using the data of voltage, active power and reactive power measured at voltage sag.
Parameter Estimation for the Thurstone Case III Model.
Mackay, David B.; Chaiy, Seoil
1982-01-01
The ability of three estimation criteria to recover parameters of the Thurstone Case V and Case III models from comparative judgment data was investigated via Monte Carlo techniques. Significant differences in recovery are shown to exist. (Author/JKS)
Institute of Scientific and Technical Information of China (English)
Youlong XIA; Zong-Liang YANG; Paul L. STOFFA; Mrinal K. SEN
2005-01-01
Most previous land-surface model calibration studies have defined global ranges for their parameters to search for optimal parameter sets. Little work has been conducted to study the impacts of realistic versus global ranges as well as model complexities on the calibration and uncertainty estimates. The primary purpose of this paper is to investigate these impacts by employing Bayesian Stochastic Inversion (BSI)to the Chameleon Surface Model (CHASM). The CHASM was designed to explore the general aspects of land-surface energy balance representation within a common modeling framework that can be run from a simple energy balance formulation to a complex mosaic type structure. The BSI is an uncertainty estimation technique based on Bayes theorem, importance sampling, and very fast simulated annealing.The model forcing data and surface flux data were collected at seven sites representing a wide range of climate and vegetation conditions. For each site, four experiments were performed with simple and complex CHASM formulations as well as realistic and global parameter ranges. Twenty eight experiments were conducted and 50 000 parameter sets were used for each run. The results show that the use of global and realistic ranges gives similar simulations for both modes for most sites, but the global ranges tend to produce some unreasonable optimal parameter values. Comparison of simple and complex modes shows that the simple mode has more parameters with unreasonable optimal values. Use of parameter ranges and model complexities have significant impacts on frequency distribution of parameters, marginal posterior probability density functions, and estimates of uncertainty of simulated sensible and latent heat fluxes.Comparison between model complexity and parameter ranges shows that the former has more significant impacts on parameter and uncertainty estimations.
Kumar, B Shiva; Venkateswarlu, Ch
2014-08-01
The complex nature of biological reactions in biofilm reactors often poses difficulties in analyzing such reactors experimentally. Mathematical models could be very useful for their design and analysis. However, application of biofilm reactor models to practical problems proves somewhat ineffective due to the lack of knowledge of accurate kinetic models and uncertainty in model parameters. In this work, we propose an inverse modeling approach based on tabu search (TS) to estimate the parameters of kinetic and film thickness models. TS is used to estimate these parameters as a consequence of the validation of the mathematical models of the process with the aid of measured data obtained from an experimental fixed-bed anaerobic biofilm reactor involving the treatment of pharmaceutical industry wastewater. The results evaluated for different modeling configurations of varying degrees of complexity illustrate the effectiveness of TS for accurate estimation of kinetic and film thickness model parameters of the biofilm process. The results show that the two-dimensional mathematical model with Edward kinetics (with its optimum parameters as mu(max)rho(s)/Y = 24.57, Ks = 1.352 and Ki = 102.36) and three-parameter film thickness expression (with its estimated parameters as a = 0.289 x 10(-5), b = 1.55 x 10(-4) and c = 15.2 x 10(-6)) better describes the biofilm reactor treating the industry wastewater.
Quark and Lepton Mass Matrix Model with Only Six Family-Independent Parameters
Koide, Yoshio
2015-01-01
We propose a unified mass matrix model for quarks and leptons, in which sixteen observables of mass ratios and mixings of the quarks and neutrinos are described by using no family number-dependent parameters except for the charged lepton masses and only six family number-independent free parameters. The model is constructed by extending the so-called ``Yukawaon" model to a seesaw type model with the smallest number of possible family number-independent free parameters. As a result, once the six parameters is fixed by the quark mixing and the mass ratios of quarks and neutrinos, no free parameters are left in the lepton mixing matrix. The results are in excellent agreement with the neutrino mixing data. We predict $\\delta_{CP}^\\ell =-68^\\circ$ for the leptonic $CP$ violating phase and $\\langle m\\rangle\\simeq 21$ meV for the effective Majorana neutrino mass.
Comparing spatial and temporal transferability of hydrological model parameters
Patil, Sopan D.; Stieglitz, Marc
2015-06-01
Operational use of hydrological models requires the transfer of calibrated parameters either in time (for streamflow forecasting) or space (for prediction at ungauged catchments) or both. Although the effects of spatial and temporal parameter transfer on catchment streamflow predictions have been well studied individually, a direct comparison of these approaches is much less documented. Here, we compare three different schemes of parameter transfer, viz., temporal, spatial, and spatiotemporal, using a spatially lumped hydrological model called EXP-HYDRO at 294 catchments across the continental United States. Results show that the temporal parameter transfer scheme performs best, with lowest decline in prediction performance (median decline of 4.2%) as measured using the Kling-Gupta efficiency metric. More interestingly, negligible difference in prediction performance is observed between the spatial and spatiotemporal parameter transfer schemes (median decline of 12.4% and 13.9% respectively). We further demonstrate that the superiority of temporal parameter transfer scheme is preserved even when: (1) spatial distance between donor and receiver catchments is reduced, or (2) temporal lag between calibration and validation periods is increased. Nonetheless, increase in the temporal lag between calibration and validation periods reduces the overall performance gap between the three parameter transfer schemes. Results suggest that spatiotemporal transfer of hydrological model parameters has the potential to be a viable option for climate change related hydrological studies, as envisioned in the "trading space for time" framework. However, further research is still needed to explore the relationship between spatial and temporal aspects of catchment hydrological variability.
Parameter Estimation for Groundwater Models under Uncertain Irrigation Data.
Demissie, Yonas; Valocchi, Albert; Cai, Ximing; Brozovic, Nicholas; Senay, Gabriel; Gebremichael, Mekonnen
2015-01-01
The success of modeling groundwater is strongly influenced by the accuracy of the model parameters that are used to characterize the subsurface system. However, the presence of uncertainty and possibly bias in groundwater model source/sink terms may lead to biased estimates of model parameters and model predictions when the standard regression-based inverse modeling techniques are used. This study first quantifies the levels of bias in groundwater model parameters and predictions due to the presence of errors in irrigation data. Then, a new inverse modeling technique called input uncertainty weighted least-squares (IUWLS) is presented for unbiased estimation of the parameters when pumping and other source/sink data are uncertain. The approach uses the concept of generalized least-squares method with the weight of the objective function depending on the level of pumping uncertainty and iteratively adjusted during the parameter optimization process. We have conducted both analytical and numerical experiments, using irrigation pumping data from the Republican River Basin in Nebraska, to evaluate the performance of ordinary least-squares (OLS) and IUWLS calibration methods under different levels of uncertainty of irrigation data and calibration conditions. The result from the OLS method shows the presence of statistically significant (p irrigation pumping uncertainties during the calibration procedures, the proposed IUWLS is able to minimize the bias effectively without adding significant computational burden to the calibration processes.
Parameter estimation for groundwater models under uncertain irrigation data
Demissie, Yonas; Valocchi, Albert J.; Cai, Ximing; Brozovic, Nicholas; Senay, Gabriel; Gebremichael, Mekonnen
2015-01-01
The success of modeling groundwater is strongly influenced by the accuracy of the model parameters that are used to characterize the subsurface system. However, the presence of uncertainty and possibly bias in groundwater model source/sink terms may lead to biased estimates of model parameters and model predictions when the standard regression-based inverse modeling techniques are used. This study first quantifies the levels of bias in groundwater model parameters and predictions due to the presence of errors in irrigation data. Then, a new inverse modeling technique called input uncertainty weighted least-squares (IUWLS) is presented for unbiased estimation of the parameters when pumping and other source/sink data are uncertain. The approach uses the concept of generalized least-squares method with the weight of the objective function depending on the level of pumping uncertainty and iteratively adjusted during the parameter optimization process. We have conducted both analytical and numerical experiments, using irrigation pumping data from the Republican River Basin in Nebraska, to evaluate the performance of ordinary least-squares (OLS) and IUWLS calibration methods under different levels of uncertainty of irrigation data and calibration conditions. The result from the OLS method shows the presence of statistically significant (p irrigation pumping uncertainties during the calibration procedures, the proposed IUWLS is able to minimize the bias effectively without adding significant computational burden to the calibration processes.
Parameter estimation in stochastic rainfall-runoff models
DEFF Research Database (Denmark)
Jonsdottir, Harpa; Madsen, Henrik; Palsson, Olafur Petur
2006-01-01
the parameters, including the noise terms. The parameter estimation method is a maximum likelihood method (ML) where the likelihood function is evaluated using a Kalman filter technique. The ML method estimates the parameters in a prediction error settings, i.e. the sum of squared prediction error is minimized....... For a comparison the parameters are also estimated by an output error method, where the sum of squared simulation error is minimized. The former methodology is optimal for short-term prediction whereas the latter is optimal for simulations. Hence, depending on the purpose it is possible to select whether...... the parameter values are optimal for simulation or prediction. The data originates from Iceland and the model is designed for Icelandic conditions, including a snow routine for mountainous areas. The model demands only two input data series, precipitation and temperature and one output data series...
DEFF Research Database (Denmark)
Kiil, Søren
2011-01-01
A mathematical model, describing the curing behaviour of a two-component, solvent-based, thermoset coating, is used to conduct a parameter study. The model includes curing reactions, solvent intra-film diffusion and evaporation, film gelation, vitrification, and crosslinking. A case study with a ...
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 ...
Transformations among CE–CVM model parameters for multicomponent systems
Indian Academy of Sciences (India)
B Nageswara Sarma; Shrikant Lele
2005-06-01
In the development of thermodynamic databases for multicomponent systems using the cluster expansion–cluster variation methods, we need to have a consistent procedure for expressing the model parameters (CECs) of a higher order system in terms of those of the lower order subsystems and to an independent set of parameters which exclusively represent interactions of the higher order systems. Such a procedure is presented in detail in this communication. Furthermore, the details of transformations required to express the model parameters in one basis from those defined in another basis for the same system are also presented.
DEFF Research Database (Denmark)
Flores-Alsina, X.; Mbamba, C. Kazadi; Solon, K.;
There is a growing interest within the Wastewater Treatment Plant (WWTP) modelling community to correctly describe physico-chemical processes after many years of mainly focusing on biokinetics (Batstone et al., 2012). Indeed, future modelling needs, such as a plant-wide phosphorus (P) description......, require a major, but unavoidable, additional degree of complexity when representing cationic/anionic behaviour in Activated Sludge (AS)/Anaerobic Digestion (AD) systems (Ikumi et al., 2014). In this paper, a plant-wide aqueous phase chemistry module describing pH variations plus ion speciation......). Simulation results show pH predictions when describing Biological Nutrient Removal (BNR) by the activated sludge models (ASM) 1, 2d and 3 (Henze et al., 2000) comparing the performance of a nitrogen removal (WWTP1) and a combined nitrogen and phosphorus removal (WWTP2) treatment plant configuration under...
SPOTting Model Parameters Using a Ready-Made Python Package.
Houska, Tobias; Kraft, Philipp; Chamorro-Chavez, Alejandro; Breuer, Lutz
2015-01-01
The choice for specific parameter estimation methods is often more dependent on its availability than its performance. We developed SPOTPY (Statistical Parameter Optimization Tool), an open source python package containing a comprehensive set of methods typically used to calibrate, analyze and optimize parameters for a wide range of ecological models. SPOTPY currently contains eight widely used algorithms, 11 objective functions, and can sample from eight parameter distributions. SPOTPY has a model-independent structure and can be run in parallel from the workstation to large computation clusters using the Message Passing Interface (MPI). We tested SPOTPY in five different case studies to parameterize the Rosenbrock, Griewank and Ackley functions, a one-dimensional physically based soil moisture routine, where we searched for parameters of the van Genuchten-Mualem function and a calibration of a biogeochemistry model with different objective functions. The case studies reveal that the implemented SPOTPY methods can be used for any model with just a minimal amount of code for maximal power of parameter optimization. They further show the benefit of having one package at hand that includes number of well performing parameter search methods, since not every case study can be solved sufficiently with every algorithm or every objective function.
SPOTting Model Parameters Using a Ready-Made Python Package.
Directory of Open Access Journals (Sweden)
Tobias Houska
Full Text Available The choice for specific parameter estimation methods is often more dependent on its availability than its performance. We developed SPOTPY (Statistical Parameter Optimization Tool, an open source python package containing a comprehensive set of methods typically used to calibrate, analyze and optimize parameters for a wide range of ecological models. SPOTPY currently contains eight widely used algorithms, 11 objective functions, and can sample from eight parameter distributions. SPOTPY has a model-independent structure and can be run in parallel from the workstation to large computation clusters using the Message Passing Interface (MPI. We tested SPOTPY in five different case studies to parameterize the Rosenbrock, Griewank and Ackley functions, a one-dimensional physically based soil moisture routine, where we searched for parameters of the van Genuchten-Mualem function and a calibration of a biogeochemistry model with different objective functions. The case studies reveal that the implemented SPOTPY methods can be used for any model with just a minimal amount of code for maximal power of parameter optimization. They further show the benefit of having one package at hand that includes number of well performing parameter search methods, since not every case study can be solved sufficiently with every algorithm or every objective function.
Numerical modeling of piezoelectric transducers using physical parameters.
Cappon, Hans; Keesman, Karel J
2012-05-01
Design of ultrasonic equipment is frequently facilitated with numerical models. These numerical models, however, need a calibration step, because usually not all characteristics of the materials used are known. Characterization of material properties combined with numerical simulations and experimental data can be used to acquire valid estimates of the material parameters. In our design application, a finite element (FE) model of an ultrasonic particle separator, driven by an ultrasonic transducer in thickness mode, is required. A limited set of material parameters for the piezoelectric transducer were obtained from the manufacturer, thus preserving prior physical knowledge to a large extent. The remaining unknown parameters were estimated from impedance analysis with a simple experimental setup combined with a numerical optimization routine using 2-D and 3-D FE models. Thus, a full set of physically interpretable material parameters was obtained for our specific purpose. The approach provides adequate accuracy of the estimates of the material parameters, near 1%. These parameter estimates will subsequently be applied in future design simulations, without the need to go through an entire series of characterization experiments. Finally, a sensitivity study showed that small variations of 1% in the main parameters caused changes near 1% in the eigenfrequency, but changes up to 7% in the admittance peak, thus influencing the efficiency of the system. Temperature will already cause these small variations in response; thus, a frequency control unit is required when actually manufacturing an efficient ultrasonic separation system.
Parameter estimation and model selection in computational biology.
Directory of Open Access Journals (Sweden)
Gabriele Lillacci
2010-03-01
Full Text Available A central challenge in computational modeling of biological systems is the determination of the model parameters. Typically, only a fraction of the parameters (such as kinetic rate constants are experimentally measured, while the rest are often fitted. The fitting process is usually based on experimental time course measurements of observables, which are used to assign parameter values that minimize some measure of the error between these measurements and the corresponding model prediction. The measurements, which can come from immunoblotting assays, fluorescent markers, etc., tend to be very noisy and taken at a limited number of time points. In this work we present a new approach to the problem of parameter selection of biological models. We show how one can use a dynamic recursive estimator, known as extended Kalman filter, to arrive at estimates of the model parameters. The proposed method follows. First, we use a variation of the Kalman filter that is particularly well suited to biological applications to obtain a first guess for the unknown parameters. Secondly, we employ an a posteriori identifiability test to check the reliability of the estimates. Finally, we solve an optimization problem to refine the first guess in case it should not be accurate enough. The final estimates are guaranteed to be statistically consistent with the measurements. Furthermore, we show how the same tools can be used to discriminate among alternate models of the same biological process. We demonstrate these ideas by applying our methods to two examples, namely a model of the heat shock response in E. coli, and a model of a synthetic gene regulation system. The methods presented are quite general and may be applied to a wide class of biological systems where noisy measurements are used for parameter estimation or model selection.
An Effective Parameter Screening Strategy for High Dimensional Watershed Models
Khare, Y. P.; Martinez, C. J.; Munoz-Carpena, R.
2014-12-01
Watershed simulation models can assess the impacts of natural and anthropogenic disturbances on natural systems. These models have become important tools for tackling a range of water resources problems through their implementation in the formulation and evaluation of Best Management Practices, Total Maximum Daily Loads, and Basin Management Action Plans. For accurate applications of watershed models they need to be thoroughly evaluated through global uncertainty and sensitivity analyses (UA/SA). However, due to the high dimensionality of these models such evaluation becomes extremely time- and resource-consuming. Parameter screening, the qualitative separation of important parameters, has been suggested as an essential step before applying rigorous evaluation techniques such as the Sobol' and Fourier Amplitude Sensitivity Test (FAST) methods in the UA/SA framework. The method of elementary effects (EE) (Morris, 1991) is one of the most widely used screening methodologies. Some of the common parameter sampling strategies for EE, e.g. Optimized Trajectories [OT] (Campolongo et al., 2007) and Modified Optimized Trajectories [MOT] (Ruano et al., 2012), suffer from inconsistencies in the generated parameter distributions, infeasible sample generation time, etc. In this work, we have formulated a new parameter sampling strategy - Sampling for Uniformity (SU) - for parameter screening which is based on the principles of the uniformity of the generated parameter distributions and the spread of the parameter sample. A rigorous multi-criteria evaluation (time, distribution, spread and screening efficiency) of OT, MOT, and SU indicated that SU is superior to other sampling strategies. Comparison of the EE-based parameter importance rankings with those of Sobol' helped to quantify the qualitativeness of the EE parameter screening approach, reinforcing the fact that one should use EE only to reduce the resource burden required by FAST/Sobol' analyses but not to replace it.
Energy Technology Data Exchange (ETDEWEB)
Hamimid, M., E-mail: Hamimid_mourad@hotmail.com [Laboratoire de modelisation des systemes energetiques LMSE, Universite de Biskra, BP 145, 07000 Biskra (Algeria); Mimoune, S.M., E-mail: s.m.mimoune@mselab.org [Laboratoire de modelisation des systemes energetiques LMSE, Universite de Biskra, BP 145, 07000 Biskra (Algeria); Feliachi, M., E-mail: mouloud.feliachi@univ-nantes.fr [IREENA-IUT, CRTT, 37 Boulevard de l' Universite, BP 406, 44602 Saint Nazaire Cedex (France)
2012-07-01
In this present work, the minor hysteresis loops model based on parameters scaling of the modified Jiles-Atherton model is evaluated by using judicious expressions. These expressions give the minor hysteresis loops parameters as a function of the major hysteresis loop ones. They have exponential form and are obtained by parameters identification using the stochastic optimization method 'simulated annealing'. The main parameters influencing the data fitting are three parameters, the pinning parameter k, the mean filed parameter {alpha} and the parameter which characterizes the shape of anhysteretic magnetization curve a. To validate this model, calculated minor hysteresis loops are compared with measured ones and good agreements are obtained.
Morin, José A.; Ibarra, Borja; Cao, Francisco J.
2016-05-01
Single-molecule manipulation experiments of molecular motors provide essential information about the rate and conformational changes of the steps of the reaction located along the manipulation coordinate. This information is not always sufficient to define a particular kinetic cycle. Recent single-molecule experiments with optical tweezers showed that the DNA unwinding activity of a Phi29 DNA polymerase mutant presents a complex pause behavior, which includes short and long pauses. Here we show that different kinetic models, considering different connections between the active and the pause states, can explain the experimental pause behavior. Both the two independent pause model and the two connected pause model are able to describe the pause behavior of a mutated Phi29 DNA polymerase observed in an optical tweezers single-molecule experiment. For the two independent pause model all parameters are fixed by the observed data, while for the more general two connected pause model there is a range of values of the parameters compatible with the observed data (which can be expressed in terms of two of the rates and their force dependencies). This general model includes models with indirect entry and exit to the long-pause state, and also models with cycling in both directions. Additionally, assuming that detailed balance is verified, which forbids cycling, this reduces the ranges of the values of the parameters (which can then be expressed in terms of one rate and its force dependency). The resulting model interpolates between the independent pause model and the indirect entry and exit to the long-pause state model
MODELING OF FUEL SPRAY CHARACTERISTICS AND DIESEL COMBUSTION CHAMBER PARAMETERS
Directory of Open Access Journals (Sweden)
G. M. Kukharonak
2011-01-01
Full Text Available The computer model for coordination of fuel spray characteristics with diesel combustion chamber parameters has been created in the paper. The model allows to observe fuel sprays develоpment in diesel cylinder at any moment of injection, to calculate characteristics of fuel sprays with due account of a shape and dimensions of a combustion chamber, timely to change fuel injection characteristics and supercharging parameters, shape and dimensions of a combustion chamber. Moreover the computer model permits to determine parameters of holes in an injector nozzle that provides the required fuel sprays characteristics at the stage of designing a diesel engine. Combustion chamber parameters for 4ЧН11/12.5 diesel engine have been determined in the paper.
Mathematically Modeling Parameters Influencing Surface Roughness in CNC Milling
Directory of Open Access Journals (Sweden)
Engin Nas
2012-01-01
Full Text Available In this study, steel AISI 1050 is subjected to process of face milling in CNC milling machine and such parameters as cutting speed, feed rate, cutting tip, depth of cut influencing the surface roughness are investigated experimentally. Four different experiments are conducted by creating different combinations for parameters. In conducted experiments, cutting tools, which are coated by PVD method used in forcing steel and spheroidal graphite cast iron are used. Surface roughness values, which are obtained by using specified parameters with cutting tools, are measured and correlation between measured surface roughness values and parameters is modeled mathematically by using curve fitting algorithm. Mathematical models are evaluated according to coefficients of determination (R2 and the most ideal one is suggested for theoretical works. Mathematical models, which are proposed for each experiment, are estipulated.
Regionalization parameters of conceptual rainfall-runoff model
Osuch, M.
2003-04-01
Main goal of this study was to develop techniques for the a priori estimation parameters of hydrological model. Conceptual hydrological model CLIRUN was applied to around 50 catchment in Poland. The size of catchments range from 1 000 to 100 000 km2. The model was calibrated for a number of gauged catchments with different catchment characteristics. The parameters of model were related to different climatic and physical catchment characteristics (topography, land use, vegetation and soil type). The relationships were tested by comparing observed and simulated runoff series from the gauged catchment that were not used in the calibration. The model performance using regional parameters was promising for most of the calibration and validation catchments.
Weibull Parameters Estimation Based on Physics of Failure Model
DEFF Research Database (Denmark)
Kostandyan, Erik; Sørensen, John Dalsgaard
2012-01-01
Reliability estimation procedures are discussed for the example of fatigue development in solder joints using a physics of failure model. The accumulated damage is estimated based on a physics of failure model, the Rainflow counting algorithm and the Miner’s rule. A threshold model is used...... distribution. Methods from structural reliability analysis are used to model the uncertainties and to assess the reliability for fatigue failure. Maximum Likelihood and Least Square estimation techniques are used to estimate fatigue life distribution parameters....
MODELING PARAMETERS OF ARC OF ELECTRIC ARC FURNACE
Directory of Open Access Journals (Sweden)
R.N. Khrestin
2015-08-01
Full Text Available Purpose. The aim is to build a mathematical model of the electric arc of arc furnace (EAF. The model should clearly show the relationship between the main parameters of the arc. These parameters determine the properties of the arc and the possibility of optimization of melting mode. Methodology. We have built a fairly simple model of the arc, which satisfies the above requirements. The model is designed for the analysis of electromagnetic processes arc of varying length. We have compared the results obtained when testing the model with the results obtained on actual furnaces. Results. During melting in real chipboard under the influence of changes in temperature changes its properties arc plasma. The proposed model takes into account these changes. Adjusting the length of the arc is the main way to regulate the mode of smelting chipboard. The arc length is controlled by the movement of the drive electrode. The model reflects the dynamic changes in the parameters of the arc when changing her length. We got the dynamic current-voltage characteristics (CVC of the arc for the different stages of melting. We got the arc voltage waveform and identified criteria by which possible identified stage of smelting. Originality. In contrast to the previously known models, this model clearly shows the relationship between the main parameters of the arc EAF: arc voltage Ud, amperage arc id and length arc d. Comparison of the simulation results and experimental data obtained from real particleboard showed the adequacy of the constructed model. It was found that character of change of magnitude Md, helps determine the stage of melting. Practical value. It turned out that the model can be used to simulate smelting in EAF any capacity. Thus, when designing the system of control mechanism for moving the electrode, the model takes into account changes in the parameters of the arc and it can significantly reduce electrode material consumption and energy consumption
Chavanis, P. H.; Delfini, L.
2014-03-01
We study random transitions between two metastable states that appear below a critical temperature in a one-dimensional self-gravitating Brownian gas with a modified Poisson equation experiencing a second order phase transition from a homogeneous phase to an inhomogeneous phase [P. H. Chavanis and L. Delfini, Phys. Rev. E 81, 051103 (2010), 10.1103/PhysRevE.81.051103]. We numerically solve the N-body Langevin equations and the stochastic Smoluchowski-Poisson system, which takes fluctuations (finite N effects) into account. The system switches back and forth between the two metastable states (bistability) and the particles accumulate successively at the center or at the boundary of the domain. We explicitly show that these random transitions exhibit the phenomenology of the ordinary Kramers problem for a Brownian particle in a double-well potential. The distribution of the residence time is Poissonian and the average lifetime of a metastable state is given by the Arrhenius law; i.e., it is proportional to the exponential of the barrier of free energy ΔF divided by the energy of thermal excitation kBT. Since the free energy is proportional to the number of particles N for a system with long-range interactions, the lifetime of metastable states scales as eN and is considerable for N ≫1. As a result, in many applications, metastable states of systems with long-range interactions can be considered as stable states. However, for moderate values of N, or close to a critical point, the lifetime of the metastable states is reduced since the barrier of free energy decreases. In that case, the fluctuations become important and the mean field approximation is no more valid. This is the situation considered in this paper. By an appropriate change of notations, our results also apply to bacterial populations experiencing chemotaxis in biology. Their dynamics can be described by a stochastic Keller-Segel model that takes fluctuations into account and goes beyond the usual mean
Global-scale regionalization of hydrologic model parameters
Beck, Hylke E.; van Dijk, Albert I. J. M.; de Roo, Ad; Miralles, Diego G.; McVicar, Tim R.; Schellekens, Jaap; Bruijnzeel, L. Adrian
2016-05-01
Current state-of-the-art models typically applied at continental to global scales (hereafter called macroscale) tend to use a priori parameters, resulting in suboptimal streamflow (Q) simulation. For the first time, a scheme for regionalization of model parameters at the global scale was developed. We used data from a diverse set of 1787 small-to-medium sized catchments (10-10,000 km2) and the simple conceptual HBV model to set up and test the scheme. Each catchment was calibrated against observed daily Q, after which 674 catchments with high calibration and validation scores, and thus presumably good-quality observed Q and forcing data, were selected to serve as donor catchments. The calibrated parameter sets for the donors were subsequently transferred to 0.5° grid cells with similar climatic and physiographic characteristics, resulting in parameter maps for HBV with global coverage. For each grid cell, we used the 10 most similar donor catchments, rather than the single most similar donor, and averaged the resulting simulated Q, which enhanced model performance. The 1113 catchments not used as donors were used to independently evaluate the scheme. The regionalized parameters outperformed spatially uniform (i.e., averaged calibrated) parameters for 79% of the evaluation catchments. Substantial improvements were evident for all major Köppen-Geiger climate types and even for evaluation catchments > 5000 km distant from the donors. The median improvement was about half of the performance increase achieved through calibration. HBV with regionalized parameters outperformed nine state-of-the-art macroscale models, suggesting these might also benefit from the new regionalization scheme. The produced HBV parameter maps including ancillary data are available via www.gloh2o.org.
Bayesian parameter estimation for nonlinear modelling of biological pathways
Directory of Open Access Journals (Sweden)
Ghasemi Omid
2011-12-01
Full Text Available Abstract Background The availability of temporal measurements on biological experiments has significantly promoted research areas in systems biology. To gain insight into the interaction and regulation of biological systems, mathematical frameworks such as ordinary differential equations have been widely applied to model biological pathways and interpret the temporal data. Hill equations are the preferred formats to represent the reaction rate in differential equation frameworks, due to their simple structures and their capabilities for easy fitting to saturated experimental measurements. However, Hill equations are highly nonlinearly parameterized functions, and parameters in these functions cannot be measured easily. Additionally, because of its high nonlinearity, adaptive parameter estimation algorithms developed for linear parameterized differential equations cannot be applied. Therefore, parameter estimation in nonlinearly parameterized differential equation models for biological pathways is both challenging and rewarding. In this study, we propose a Bayesian parameter estimation algorithm to estimate parameters in nonlinear mathematical models for biological pathways using time series data. Results We used the Runge-Kutta method to transform differential equations to difference equations assuming a known structure of the differential equations. This transformation allowed us to generate predictions dependent on previous states and to apply a Bayesian approach, namely, the Markov chain Monte Carlo (MCMC method. We applied this approach to the biological pathways involved in the left ventricle (LV response to myocardial infarction (MI and verified our algorithm by estimating two parameters in a Hill equation embedded in the nonlinear model. We further evaluated our estimation performance with different parameter settings and signal to noise ratios. Our results demonstrated the effectiveness of the algorithm for both linearly and nonlinearly
Do Lumped-Parameter Models Provide the Correct Geometrical Damping?
DEFF Research Database (Denmark)
Andersen, Lars
2007-01-01
This paper concerns the formulation of lumped-parameter models for rigid footings on homogenous or stratified soil with focus on the horizontal sliding and rocking. Such models only contain a few degrees of freedom, which makes them ideal for inclusion in aero-elastic codes for wind turbines...
Muscle parameters for musculoskeletal modelling of the human neck
Borst, J.; Forbes, P.A.; Happee, R.; Veeger, H.E.J.
2011-01-01
Background: To study normal or pathological neuromuscular control, a musculoskeletal model of the neck has great potential but a complete and consistent anatomical dataset which comprises the muscle geometry parameters to construct such a model is not yet available. Methods: A dissection experiment
Do Lumped-Parameter Models Provide the Correct Geometrical Damping?
DEFF Research Database (Denmark)
Andersen, Lars
2007-01-01
This paper concerns the formulation of lumped-parameter models for rigid footings on homogenous or stratified soil with focus on the horizontal sliding and rocking. Such models only contain a few degrees of freedom, which makes them ideal for inclusion in aero-elastic codes for wind turbines...
Multiplicity Control in Structural Equation Modeling: Incorporating Parameter Dependencies
Smith, Carrie E.; Cribbie, Robert A.
2013-01-01
When structural equation modeling (SEM) analyses are conducted, significance tests for all important model relationships (parameters including factor loadings, covariances, etc.) are typically conducted at a specified nominal Type I error rate ([alpha]). Despite the fact that many significance tests are often conducted in SEM, rarely is…
Muscle parameters for musculoskeletal modelling of the human neck
Borst, J.; Forbes, P.A.; Happee, R.; Veeger, H.E.J.
2011-01-01
Background: To study normal or pathological neuromuscular control, a musculoskeletal model of the neck has great potential but a complete and consistent anatomical dataset which comprises the muscle geometry parameters to construct such a model is not yet available. Methods: A dissection experiment
Geometry parameters for musculoskeletal modelling of the shoulder system
Van der Helm, F C; Veeger, DirkJan (H. E. J.); Pronk, G M; Van der Woude, L H; Rozendal, R H
1992-01-01
A dynamical finite-element model of the shoulder mechanism consisting of thorax, clavicula, scapula and humerus is outlined. The parameters needed for the model are obtained in a cadaver experiment consisting of both shoulders of seven cadavers. In this paper, in particular, the derivation of geomet