Modelling distribution functions and fragmentation functions
Rodrigues, J; Mulders, P J
1995-01-01
We present examples for the calculation of the distribution and fragmentation functions using the representation in terms of non-local matrix elements of quark field operators. As specific examples, we use a simple spectator model to estimate the leading twist quark distribution functions and the fragmentation functions for a quark into a nucleon or a pion.
Rough function model and rough membership function
Institute of Scientific and Technical Information of China (English)
Wang Yun; Guan Yanyong; Huang Zhiqin
2008-01-01
Two pairs of approximation operators, which are the scale lower and upper approximations as well as the real line lower and upper approximations, are defined. Their properties and antithesis characteristics are analyzed. The rough function model is generalized based on rough set theory, and the scheme of rough function theory is made more distinct and complete. Therefore, the transformation of the real function analysis from real line to scale is achieved. A series of basic concepts in rough function model including rough numbers, rough intervals, and rough membership functions are defined in the new scheme of the rough function model. Operating properties of rough intervals similar to rough sets are obtained. The relationship of rough inclusion and rough equality of rough intervals is defined by two kinds of tools, known as the lower (upper) approximation operator in real numbers domain and rough membership functions. Their relative properties are analyzed and proved strictly, which provides necessary theoretical foundation and technical support for the further discussion of properties and practical application of the rough function model.
2015-01-01
This work aims at the exposition of two different results we have obtained in Functional Data Analysis. The first is a variable selection method in Functional Regression which is an adaptation of the well known Lasso technique. The second is a brand new Random Walk test for Functional Time Series. Being the results afferent to different areas of Functional Data Analysis, as well as of general Statistics, the introduction will be divided in three parts. Firstly we expose the fundament...
Statistical modelling with quantile functions
Gilchrist, Warren
2000-01-01
Galton used quantiles more than a hundred years ago in describing data. Tukey and Parzen used them in the 60s and 70s in describing populations. Since then, the authors of many papers, both theoretical and practical, have used various aspects of quantiles in their work. Until now, however, no one put all the ideas together to form what turns out to be a general approach to statistics.Statistical Modelling with Quantile Functions does just that. It systematically examines the entire process of statistical modelling, starting with using the quantile function to define continuous distributions. The author shows that by using this approach, it becomes possible to develop complex distributional models from simple components. A modelling kit can be developed that applies to the whole model - deterministic and stochastic components - and this kit operates by adding, multiplying, and transforming distributions rather than data.Statistical Modelling with Quantile Functions adds a new dimension to the practice of stati...
Functional Scaling of Musculoskeletal Models
DEFF Research Database (Denmark)
Lund, Morten Enemark; Andersen, Michael Skipper; de Zee, Mark;
The validity of the predictions from musculoskeletal models depends largely on how well the morphology of the model matches that of the patient. To address this problem, we present a novel method to scale a cadaver-based musculoskeletal model to match both the segment lengths and joint parameters...... orientations are then used to morph/scale a cadaver based musculoskeletal model using a set of radial basis functions (RBFs). Using the functional joint axes to scale musculoskeletal models provides a better fit to the marker data, and allows for representation of patients with considerable difference in bone...... geometry, without the need for MR/CT scans. However, more validation activities are needed to better understand the effect of morphing musculoskeletal models based on functional joint parameters....
A deterministic width function model
Directory of Open Access Journals (Sweden)
C. E. Puente
2003-01-01
Full Text Available Use of a deterministic fractal-multifractal (FM geometric method to model width functions of natural river networks, as derived distributions of simple multifractal measures via fractal interpolating functions, is reported. It is first demonstrated that the FM procedure may be used to simulate natural width functions, preserving their most relevant features like their overall shape and texture and their observed power-law scaling on their power spectra. It is then shown, via two natural river networks (Racoon and Brushy creeks in the United States, that the FM approach may also be used to closely approximate existing width functions.
Modeling psychometric functions in R.
Yssaad-Fesselier, Rosa; Knoblauch, Kenneth
2006-02-01
We demonstrate some procedures in the statistical computing environment R for obtaining maximum likelihood estimates of the parameters of a psychometric function by fitting a generalized nonlinear regression model to the data. A feature for fitting a linear model to the threshold (or other) parameters of several psychometric functions simultaneously provides a powerful tool for testing hypotheses about the data and, potentially, for reducing the number of parameters necessary to describe them. Finally, we illustrate procedures for treating one parameter as a random effect that would permit a simplified approach to modeling stimulus-independent variability due to factors such as lapses or interobserver differences. These tools will facilitate a more comprehensive and explicit approach to the modeling of psychometric data.
Estimating Functions and Semiparametric Models
DEFF Research Database (Denmark)
Labouriau, Rodrigo
1996-01-01
The thesis is divided in two parts. The first part treats some topics of the estimation theory for semiparametric models in general. There the classic optimality theory is reviewed and exposed in a suitable way for the further developments given after. Further the theory of estimating functions...... contained in this part of the thesis constitutes an original contribution. There can be found the detailed characterization of the class of regular estimating functions, a calculation of efficient regular asymptotic linear estimating sequences (\\ie the classical optimality theory) and a discussion...... of the attainability of the bounds for the concentration of regular asymptotic linear estimating sequences by estimators derived from estimating functions. The main class of models considered in the second part of the thesis (chapter 5) are constructed by assuming that the expectation of a number of given square...
Zhang functions and various models
Zhang, Yunong
2015-01-01
This book focuses on solving different types of time-varying problems. It presents various Zhang dynamics (ZD) models by defining various Zhang functions (ZFs) in real and complex domains. It then provides theoretical analyses of such ZD models and illustrates their results. It also uses simulations to substantiate their efficacy and show the feasibility of the presented ZD approach (i.e., different ZFs leading to different ZD models), which is further applied to the repetitive motion planning (RMP) of redundant robots, showing its application potential.
14 CFR 121.193 - Airplanes: Turbine engine powered: En route limitations: Two engines inoperative.
2010-01-01
... limitations: Two engines inoperative. 121.193 Section 121.193 Aeronautics and Space FEDERAL AVIATION... Performance Operating Limitations § 121.193 Airplanes: Turbine engine powered: En route limitations: Two... § 121.197. (2) Its weight, according to the two-engine-inoperative, en route, net flight path data in...
Transfer Function Identification Using Orthogonal Fourier Transform Modeling Functions
Morelli, Eugene A.
2013-01-01
A method for transfer function identification, including both model structure determination and parameter estimation, was developed and demonstrated. The approach uses orthogonal modeling functions generated from frequency domain data obtained by Fourier transformation of time series data. The method was applied to simulation data to identify continuous-time transfer function models and unsteady aerodynamic models. Model fit error, estimated model parameters, and the associated uncertainties were used to show the effectiveness of the method for identifying accurate transfer function models from noisy data.
Crossing Hazard Functions in Common Survival Models.
Zhang, Jiajia; Peng, Yingwei
2009-10-15
Crossing hazard functions have extensive applications in modeling survival data. However, existing studies in the literature mainly focus on comparing crossed hazard functions and estimating the time at which the hazard functions cross, and there is little theoretical work on conditions under which hazard functions from a model will have a crossing. In this paper, we investigate crossing status of hazard functions from the proportional hazards (PH) model, the accelerated hazard (AH) model, and the accelerated failure time (AFT) model. We provide and prove conditions under which the hazard functions from the AH and the AFT models have no crossings or a single crossing. A few examples are also provided to demonstrate how the conditions can be used to determine crossing status of hazard functions from the three models.
Functional Risk Modeling for Lunar Surface Systems
Thomson, Fraser; Mathias, Donovan; Go, Susie; Nejad, Hamed
2010-01-01
We introduce an approach to risk modeling that we call functional modeling , which we have developed to estimate the capabilities of a lunar base. The functional model tracks the availability of functions provided by systems, in addition to the operational state of those systems constituent strings. By tracking functions, we are able to identify cases where identical functions are provided by elements (rovers, habitats, etc.) that are connected together on the lunar surface. We credit functional diversity in those cases, and in doing so compute more realistic estimates of operational mode availabilities. The functional modeling approach yields more realistic estimates of the availability of the various operational modes provided to astronauts by the ensemble of surface elements included in a lunar base architecture. By tracking functional availability the effects of diverse backup, which often exists when two or more independent elements are connected together, is properly accounted for.
Functional model realizations for Schur functions on C+
Kurula, Mikael; Ball, Joseph A.; Staffans, Olof J.; Zwart, Hans
2014-01-01
For an arbitrary given operator Schur function defined on the complex right-half plane, we give a controllable energy-preserving and an observable co-energy-preserving de Branges-Rovnyak functional model realization. Topics appearing only in the right-half-plane setting, such as the extrapolation sp
Functional Behavioral Assessment: A School Based Model.
Asmus, Jennifer M.; Vollmer, Timothy R.; Borrero, John C.
2002-01-01
This article begins by discussing requirements for functional behavioral assessment under the Individuals with Disabilities Education Act and then describes a comprehensive model for the application of behavior analysis in the schools. The model includes descriptive assessment, functional analysis, and intervention and involves the participation…
The Credibility Models under LINEX Loss Functions
Institute of Scientific and Technical Information of China (English)
WEN Li-min; ZHANG Xian-kun; ZHENG Dan; FANG Jing
2012-01-01
LINEX(linear and exponential) loss function is a useful asymmetric loss function.The purpose of using a LINEX loss function in credibility models is to solve the problem of very high premium by suing a symmetric quadratic loss function in most of classical credibility models. The Bayes premium and the credibility premium are derived under LINEX loss function. The consistency of Bayes premium and credibility premium were also checked.Finally,the simulation was introduced to show the differences between the credibility estimator we derived and the classical one.
130 Modeling of the automobile suspension by the functional model
桐山, 啓; 角田, 鎭男; 長松, 昭男; 御法川, 学; 岩原, 光男; Kiriyama, Akira; Sumida, Shizuo; Nagamatsu, Akio; Minorikawa, Gaku; Iwahara, Mitsuo
2003-01-01
Modeling for an action simulation is performed focusing on the suspension system of a car using the modeling technique called the functional model that had been developed by one of the authors. Simulation analysis of the suspension system of a car was performed in the three dimensional field. It was shown that the method based on the modeling concept of functional model can express the general dynamic characteristic of the automobile suspension.
Modeling nuclear parton distribution functions
Honkanen, H; Guzey, V
2013-01-01
The presence of nuclear medium and collective phenomena which involve several nucleons modify the parton distribution functions of nuclei (nPDFs) compared to those of a free nucleon. These modifications have been investigated by different groups using global analyses of high energy nuclear reaction world data resulting in modern nPDF parametrizations with error estimates, such as EPS09(s), HKN07 and nDS. These phenomenological nPDF sets roughly agree within their uncertainty bands, but have antiquarks for large-$x$ and gluons for the whole $x$-range poorly constrained by the available data. In the kinematics accessible at the LHC this has negative impact on the interpretation of the heavy-ion collision data, especially for the $p + A$ benchmarking runs. The EMC region is also sensitive to the proper definition of $x$, where the nuclear binding effects have to be taken into account, and for heavy nuclei one also needs to take into account that a fraction of the nucleus momentum is carried by the equivalent pho...
A Software Reliability Model Using Quantile Function
Directory of Open Access Journals (Sweden)
Bijamma Thomas
2014-01-01
Full Text Available We study a class of software reliability models using quantile function. Various distributional properties of the class of distributions are studied. We also discuss the reliability characteristics of the class of distributions. Inference procedures on parameters of the model based on L-moments are studied. We apply the proposed model to a real data set.
A Multivariate Approach to Functional Neuro Modeling
DEFF Research Database (Denmark)
Mørch, Niels J.S.
1998-01-01
This Ph.D. thesis, A Multivariate Approach to Functional Neuro Modeling, deals with the analysis and modeling of data from functional neuro imaging experiments. A multivariate dataset description is provided which facilitates efficient representation of typical datasets and, more importantly...... and overall conditions governing the functional experiment, via associated micro- and macroscopic variables. The description facilitates an efficient microscopic re-representation, as well as a handle on the link between brain and behavior; the latter is achieved by hypothesizing variations in the micro...... a generalization theoretical framework centered around measures of model generalization error. - Only few, if any, examples of the application of generalization theory to functional neuro modeling currently exist in the literature. - Exemplification of the proposed generalization theoretical framework...
Neural modeling of prefrontal executive function
Energy Technology Data Exchange (ETDEWEB)
Levine, D.S. [Univ. of Texas, Arlington, TX (United States)
1996-12-31
Brain executive function is based in a distributed system whereby prefrontal cortex is interconnected with other cortical. and subcortical loci. Executive function is divided roughly into three interacting parts: affective guidance of responses; linkage among working memory representations; and forming complex behavioral schemata. Neural network models of each of these parts are reviewed and fit into a preliminary theoretical framework.
Modelling Strategies for Functional Magnetic Resonance Imaging
DEFF Research Database (Denmark)
Madsen, Kristoffer Hougaard
2009-01-01
This thesis collects research done on several models for the analysis of functional magnetic resonance neuroimaging (fMRI) data. Several extensions for unsupervised factor analysis type decompositions including explicit delay modelling as well as handling of spatial and temporal smoothness...
The NJL Model for Quark Fragmentation Functions
Energy Technology Data Exchange (ETDEWEB)
T. Ito, W. Bentz, I. Cloet, A W Thomas, K. Yazaki
2009-10-01
A description of fragmentation functions which satisfy the momentum and isospin sum rules is presented in an effective quark theory. Concentrating on the pion fragmentation function, we first explain the reason why the elementary (lowest order) fragmentation process q → qπ is completely inadequate to describe the empirical data, although the “crossed” process π → qq describes the quark distribution functions in the pion reasonably well. Then, taking into account cascade-like processes in a modified jet-model approach, we show that the momentum and isospin sum rules can be satisfied naturally without introducing any ad-hoc parameters. We present numerical results for the Nambu-Jona-Lasinio model in the invariant mass regularization scheme, and compare the results with the empirical parametrizations. We argue that this NJL-jet model provides a very useful framework to calculate the fragmentation functions in an effective chiral quark theory.
The NJL Model for Quark Fragmentation Functions
Energy Technology Data Exchange (ETDEWEB)
T. Ito, W. Bentz, I. Cloet, A W Thomas, K. Yazaki
2009-10-01
A description of fragmentation functions which satisfy the momentum and isospin sum rules is presented in an effective quark theory. Concentrating on the pion fragmentation function, we first explain the reason why the elementary (lowest order) fragmentation process q → qπ is completely inadequate to describe the empirical data, although the “crossed” process π → qq describes the quark distribution functions in the pion reasonably well. Then, taking into account cascade-like processes in a modified jet-model approach, we show that the momentum and isospin sum rules can be satisfied naturally without introducing any ad-hoc parameters. We present numerical results for the Nambu-Jona-Lasinio model in the invariant mass regularization scheme, and compare the results with the empirical parametrizations. We argue that this NJL-jet model provides a very useful framework to calculate the fragmentation functions in an effective chiral quark theory.
Structure functions in the chiral bag model
Energy Technology Data Exchange (ETDEWEB)
Sanjose, V.; Vento, V.
1989-07-13
We calculate the structure functions of an isoscalar nuclear target for the deep inelastic scattering by leptons in an extended version of the chiral bag model which incorporates the qanti q structure of the pions in the cloud. Bjorken scaling and Regge behavior are satisfied. The model calculation reproduces the low-x behavior of the data but fails to explain the medium- to large-x behavior. Evolution of the quark structure functions seem inevitable to attempt a connection between the low-energy models and the high-energy behavior of quantum chromodynamics. (orig.).
A Functional Version of the ARCH Model
Hormann, Siegfried; Reeder, Ron
2011-01-01
Improvements in data acquisition and processing techniques have lead to an almost continuous flow of information for financial data. High resolution tick data are available and can be quite conveniently described by a continuous time process. It is therefore natural to ask for possible extensions of financial time series models to a functional setup. In this paper we propose a functional version of the popular ARCH model. We will establish conditions for the existence of a strictly stationary solution, derive weak dependence and moment conditions, show consistency of the estimators and perform a small empirical study demonstrating how our model matches with real data.
Functional model of biological neural networks.
Lo, James Ting-Ho
2010-12-01
A functional model of biological neural networks, called temporal hierarchical probabilistic associative memory (THPAM), is proposed in this paper. THPAM comprises functional models of dendritic trees for encoding inputs to neurons, a first type of neuron for generating spike trains, a second type of neuron for generating graded signals to modulate neurons of the first type, supervised and unsupervised Hebbian learning mechanisms for easy learning and retrieving, an arrangement of dendritic trees for maximizing generalization, hardwiring for rotation-translation-scaling invariance, and feedback connections with different delay durations for neurons to make full use of present and past informations generated by neurons in the same and higher layers. These functional models and their processing operations have many functions of biological neural networks that have not been achieved by other models in the open literature and provide logically coherent answers to many long-standing neuroscientific questions. However, biological justifications of these functional models and their processing operations are required for THPAM to qualify as a macroscopic model (or low-order approximate) of biological neural networks.
Data Acquisition for Quality Loss Function Modelling
DEFF Research Database (Denmark)
Pedersen, Søren Nygaard; Howard, Thomas J.
2016-01-01
Quality loss functions can be a valuable tool when assessing the impact of variation on product quality. Typically, the input for the quality loss function would be a measure of the varying product performance and the output would be a measure of quality. While the unit of the input is given by t...... by the product function in focus, the quality output can be measured and quantified in a number of ways. In this article a structured approach for acquiring stakeholder satisfaction data for use in quality loss function modelling is introduced.......Quality loss functions can be a valuable tool when assessing the impact of variation on product quality. Typically, the input for the quality loss function would be a measure of the varying product performance and the output would be a measure of quality. While the unit of the input is given...
Data Acquisition for Quality Loss Function Modelling
DEFF Research Database (Denmark)
Pedersen, Søren Nygaard; Howard, Thomas J.
2016-01-01
Quality loss functions can be a valuable tool when assessing the impact of variation on product quality. Typically, the input for the quality loss function would be a measure of the varying product performance and the output would be a measure of quality. While the unit of the input is given by t...... by the product function in focus, the quality output can be measured and quantified in a number of ways. In this article a structured approach for acquiring stakeholder satisfaction data for use in quality loss function modelling is introduced.......Quality loss functions can be a valuable tool when assessing the impact of variation on product quality. Typically, the input for the quality loss function would be a measure of the varying product performance and the output would be a measure of quality. While the unit of the input is given...
Simple models of human brain functional networks.
Vértes, Petra E; Alexander-Bloch, Aaron F; Gogtay, Nitin; Giedd, Jay N; Rapoport, Judith L; Bullmore, Edward T
2012-04-10
Human brain functional networks are embedded in anatomical space and have topological properties--small-worldness, modularity, fat-tailed degree distributions--that are comparable to many other complex networks. Although a sophisticated set of measures is available to describe the topology of brain networks, the selection pressures that drive their formation remain largely unknown. Here we consider generative models for the probability of a functional connection (an edge) between two cortical regions (nodes) separated by some Euclidean distance in anatomical space. In particular, we propose a model in which the embedded topology of brain networks emerges from two competing factors: a distance penalty based on the cost of maintaining long-range connections; and a topological term that favors links between regions sharing similar input. We show that, together, these two biologically plausible factors are sufficient to capture an impressive range of topological properties of functional brain networks. Model parameters estimated in one set of functional MRI (fMRI) data on normal volunteers provided a good fit to networks estimated in a second independent sample of fMRI data. Furthermore, slightly detuned model parameters also generated a reasonable simulation of the abnormal properties of brain functional networks in people with schizophrenia. We therefore anticipate that many aspects of brain network organization, in health and disease, may be parsimoniously explained by an economical clustering rule for the probability of functional connectivity between different brain areas.
Functional uniform priors for nonlinear modeling.
Bornkamp, Björn
2012-09-01
This article considers the topic of finding prior distributions when a major component of the statistical model depends on a nonlinear function. Using results on how to construct uniform distributions in general metric spaces, we propose a prior distribution that is uniform in the space of functional shapes of the underlying nonlinear function and then back-transform to obtain a prior distribution for the original model parameters. The primary application considered in this article is nonlinear regression, but the idea might be of interest beyond this case. For nonlinear regression the so constructed priors have the advantage that they are parametrization invariant and do not violate the likelihood principle, as opposed to uniform distributions on the parameters or the Jeffrey's prior, respectively. The utility of the proposed priors is demonstrated in the context of design and analysis of nonlinear regression modeling in clinical dose-finding trials, through a real data example and simulation.
Nuclear Structure Functions from Constituent Quark Model
Arash, F; Arash, Firooz; Atashbar-Tehrani, Shahin
1999-01-01
We have used the notion of the constituent quark model of nucleon, where a constituent quark carries its own internal structure, and applied it to determine nuclear structure functions ratios. It is found that the description of experimental data require the inclusion of strong shadowing effect for $x<0.01$. Using the idea of vector meson dominance model and other ingredients this effect is calculated in the context of the constituent quark model. It is rather striking that the constituent quark model, used here, gives a good account of the data for a wide range of atomic mass number from A=4 to A=204.
Mathematical modeling and visualization of functional neuroimages
DEFF Research Database (Denmark)
Rasmussen, Peter Mondrup
This dissertation presents research results regarding mathematical modeling in the context of the analysis of functional neuroimages. Specifically, the research focuses on pattern-based analysis methods that recently have become popular analysis tools within the neuroimaging community. Such methods...... attempt to predict or decode experimentally defined cognitive states based on brain scans. The topics covered in the dissertation are divided into two broad parts: The first part investigates the relative importance of model selection on the brain patterns extracted form analysis models. Typical...... influence of model regularization parameter choices on the model generalization, the reliability of the spatial brain patterns extracted from the analysis model, and the ability of the model to identify relevant brain networks defining the underlying neural encoding of the experiment. We show that known...
Mathematical modeling and visualization of functional neuroimages
DEFF Research Database (Denmark)
Rasmussen, Peter Mondrup
This dissertation presents research results regarding mathematical modeling in the context of the analysis of functional neuroimages. Specifically, the research focuses on pattern-based analysis methods that recently have become popular within the neuroimaging community. Such methods attempt...... to predict or decode experimentally defined cognitive states based on brain scans. The topics covered in the dissertation are divided into two broad parts: The first part investigates the relative importance of model selection on the brain patterns extracted form analysis models. Typical neuroimaging data...... of model regularization parameter choices on the model generalization, the reliability of the spatial brain patterns extracted from the analysis model, and the ability of the resulting model to identify relevant brain networks defining the underlying neural encoding of the experiment. We show that known...
Generalized exponential function and discrete growth models
Souto Martinez, Alexandre; Silva González, Rodrigo; Lauri Espíndola, Aquino
2009-07-01
Here we show that a particular one-parameter generalization of the exponential function is suitable to unify most of the popular one-species discrete population dynamic models into a simple formula. A physical interpretation is given to this new introduced parameter in the context of the continuous Richards model, which remains valid for the discrete case. From the discretization of the continuous Richards’ model (generalization of the Gompertz and Verhulst models), one obtains a generalized logistic map and we briefly study its properties. Notice, however that the physical interpretation for the introduced parameter persists valid for the discrete case. Next, we generalize the (scramble competition) θ-Ricker discrete model and analytically calculate the fixed points as well as their stabilities. In contrast to previous generalizations, from the generalized θ-Ricker model one is able to retrieve either scramble or contest models.
Work Functions for Models of Scandate Surfaces
Mueller, Wolfgang
1997-01-01
The electronic structure, surface dipole properties, and work functions of scandate surfaces have been investigated using the fully relativistic scattered-wave cluster approach. Three different types of model surfaces are considered: (1) a monolayer of Ba-Sc-O on W(100), (2) Ba or BaO adsorbed on Sc2O3 + W, and (3) BaO on SC2O3 + WO3. Changes in the work function due to Ba or BaO adsorption on the different surfaces are calculated by employing the depolarization model of interacting surface dipoles. The largest work function change and the lowest work function of 1.54 eV are obtained for Ba adsorbed on the Sc-O monolayer on W(100). The adsorption of Ba on Sc2O3 + W does not lead to a low work function, but the adsorption of BaO results in a work function of about 1.6-1.9 eV. BaO adsorbed on Sc2O3 + WO3, or scandium tungstates, may also lead to low work functions.
Experimental model updating using frequency response functions
Hong, Yu; Liu, Xi; Dong, Xinjun; Wang, Yang; Pu, Qianhui
2016-04-01
In order to obtain a finite element (FE) model that can more accurately describe structural behaviors, experimental data measured from the actual structure can be used to update the FE model. The process is known as FE model updating. In this paper, a frequency response function (FRF)-based model updating approach is presented. The approach attempts to minimize the difference between analytical and experimental FRFs, while the experimental FRFs are calculated using simultaneously measured dynamic excitation and corresponding structural responses. In this study, the FRF-based model updating method is validated through laboratory experiments on a four-story shear-frame structure. To obtain the experimental FRFs, shake table tests and impact hammer tests are performed. The FRF-based model updating method is shown to successfully update the stiffness, mass and damping parameters of the four-story structure, so that the analytical and experimental FRFs match well with each other.
The Goodwin model: behind the Hill function.
Gonze, Didier; Abou-Jaoudé, Wassim
2013-01-01
The Goodwin model is a 3-variable model demonstrating the emergence of oscillations in a delayed negative feedback-based system at the molecular level. This prototypical model and its variants have been commonly used to model circadian and other genetic oscillators in biology. The only source of non-linearity in this model is a Hill function, characterizing the repression process. It was mathematically shown that to obtain limit-cycle oscillations, the Hill coefficient must be larger than 8, a value often considered unrealistic. It is indeed difficult to explain such a high coefficient with simple cooperative dynamics. We present here molecular models of the standard Goodwin model, based on single or multisite phosphorylation/dephosphorylation processes of a transcription factor, which have been previously shown to generate switch-like responses. We show that when the phosphorylation/dephosphorylation processes are fast enough, the limit-cycle obtained with a multisite phosphorylation-based mechanism is in very good quantitative agreement with the oscillations observed in the Goodwin model. Conditions in which the detailed mechanism is well approximated by the Goodwin model are given. A variant of the Goodwin model which displays sharp thresholds and relaxation oscillations is also explained by a double phosphorylation/dephosphorylation-based mechanism through a bistable behavior. These results not only provide rational support for the Goodwin model but also highlight the crucial role of the speed of post-translational processes, whose response curve are usually established at a steady state, in biochemical oscillators.
The Goodwin model: behind the Hill function.
Directory of Open Access Journals (Sweden)
Didier Gonze
Full Text Available The Goodwin model is a 3-variable model demonstrating the emergence of oscillations in a delayed negative feedback-based system at the molecular level. This prototypical model and its variants have been commonly used to model circadian and other genetic oscillators in biology. The only source of non-linearity in this model is a Hill function, characterizing the repression process. It was mathematically shown that to obtain limit-cycle oscillations, the Hill coefficient must be larger than 8, a value often considered unrealistic. It is indeed difficult to explain such a high coefficient with simple cooperative dynamics. We present here molecular models of the standard Goodwin model, based on single or multisite phosphorylation/dephosphorylation processes of a transcription factor, which have been previously shown to generate switch-like responses. We show that when the phosphorylation/dephosphorylation processes are fast enough, the limit-cycle obtained with a multisite phosphorylation-based mechanism is in very good quantitative agreement with the oscillations observed in the Goodwin model. Conditions in which the detailed mechanism is well approximated by the Goodwin model are given. A variant of the Goodwin model which displays sharp thresholds and relaxation oscillations is also explained by a double phosphorylation/dephosphorylation-based mechanism through a bistable behavior. These results not only provide rational support for the Goodwin model but also highlight the crucial role of the speed of post-translational processes, whose response curve are usually established at a steady state, in biochemical oscillators.
MULTIVARIATE VARYING COEFFICIENT MODEL FOR FUNCTIONAL RESPONSES.
Zhu, Hongtu; Li, Runze; Kong, Linglong
2012-10-01
Motivated by recent work studying massive imaging data in the neuroimaging literature, we propose multivariate varying coefficient models (MVCM) for modeling the relation between multiple functional responses and a set of covariates. We develop several statistical inference procedures for MVCM and systematically study their theoretical properties. We first establish the weak convergence of the local linear estimate of coefficient functions, as well as its asymptotic bias and variance, and then we derive asymptotic bias and mean integrated squared error of smoothed individual functions and their uniform convergence rate. We establish the uniform convergence rate of the estimated covariance function of the individual functions and its associated eigenvalue and eigenfunctions. We propose a global test for linear hypotheses of varying coefficient functions, and derive its asymptotic distribution under the null hypothesis. We also propose a simultaneous confidence band for each individual effect curve. We conduct Monte Carlo simulation to examine the finite-sample performance of the proposed procedures. We apply MVCM to investigate the development of white matter diffusivities along the genu tract of the corpus callosum in a clinical study of neurodevelopment.
Maximum entropy models of ecosystem functioning
Energy Technology Data Exchange (ETDEWEB)
Bertram, Jason, E-mail: jason.bertram@anu.edu.au [Research School of Biology, The Australian National University, Canberra ACT 0200 (Australia)
2014-12-05
Using organism-level traits to deduce community-level relationships is a fundamental problem in theoretical ecology. This problem parallels the physical one of using particle properties to deduce macroscopic thermodynamic laws, which was successfully achieved with the development of statistical physics. Drawing on this parallel, theoretical ecologists from Lotka onwards have attempted to construct statistical mechanistic theories of ecosystem functioning. Jaynes’ broader interpretation of statistical mechanics, which hinges on the entropy maximisation algorithm (MaxEnt), is of central importance here because the classical foundations of statistical physics do not have clear ecological analogues (e.g. phase space, dynamical invariants). However, models based on the information theoretic interpretation of MaxEnt are difficult to interpret ecologically. Here I give a broad discussion of statistical mechanical models of ecosystem functioning and the application of MaxEnt in these models. Emphasising the sample frequency interpretation of MaxEnt, I show that MaxEnt can be used to construct models of ecosystem functioning which are statistical mechanical in the traditional sense using a savanna plant ecology model as an example.
Maximum entropy models of ecosystem functioning
Bertram, Jason
2014-12-01
Using organism-level traits to deduce community-level relationships is a fundamental problem in theoretical ecology. This problem parallels the physical one of using particle properties to deduce macroscopic thermodynamic laws, which was successfully achieved with the development of statistical physics. Drawing on this parallel, theoretical ecologists from Lotka onwards have attempted to construct statistical mechanistic theories of ecosystem functioning. Jaynes' broader interpretation of statistical mechanics, which hinges on the entropy maximisation algorithm (MaxEnt), is of central importance here because the classical foundations of statistical physics do not have clear ecological analogues (e.g. phase space, dynamical invariants). However, models based on the information theoretic interpretation of MaxEnt are difficult to interpret ecologically. Here I give a broad discussion of statistical mechanical models of ecosystem functioning and the application of MaxEnt in these models. Emphasising the sample frequency interpretation of MaxEnt, I show that MaxEnt can be used to construct models of ecosystem functioning which are statistical mechanical in the traditional sense using a savanna plant ecology model as an example.
Symmetric Functional Model for Extensions of Hermitian
Ryzhov, V
2006-01-01
This paper offers the functional model of a class of non-selfadjoint extensions of a Hermitian operator with equal deficiency indices. The explicit form of dilation of a dissipative extension is offered and the symmetric form of Sz.Nagy-Foia\\c{s} model as developed by B.~Pavlov is constructed. A variant of functional model for a general non-selfadjoint non-dissipative extension is formulated. We illustrate the theory by two examples: singular perturbations of the Laplace operator in~$L_2(\\Real^3)$ by a finite number of point interactions, and the Schr\\"odinger operator on the half axis~$(0, \\infty)$ in the Weyl limit circle case at infinity.
Computer controlled operation of a two-engine xenon ion propulsion system
Brophy, John R.
1987-01-01
The development and testing of a computer control system for a two-engine xenon ion propulsion module is described. The computer system controls all aspects of the propulsion module operation including: start-up, steady-state operation, throttling and shutdown of the engines; start-up, operation and shutdown of the central neutralizer subsystem; control of the gimbal system for each engine; and operation of the valves in the propellant storage and distribution system. The most important engine control algorithms are described in detail. These control algorithms provide flexibility in the operation and throttling of ion engines which has never before been possible. This flexibility is made possible in large part through the use of flow controllers which maintain the total flow rate of propellant into the engine at the proper level. Data demonstrating the throttle capabilities of the engine and control system are presented.
Modeling of functionally graded piezoelectric ultrasonic transducers.
Rubio, Wilfredo Montealegre; Buiochi, Flávio; Adamowski, Julio Cezar; Silva, Emílio Carlos Nelli
2009-05-01
The application of functionally graded material (FGM) concept to piezoelectric transducers allows the design of composite transducers without interfaces, due to the continuous change of property values. Thus, large improvements can be achieved, as reduction of stress concentration, increasing of bonding strength, and bandwidth. This work proposes to design and to model FGM piezoelectric transducers and to compare their performance with non-FGM ones. Analytical and finite element (FE) modeling of FGM piezoelectric transducers radiating a plane pressure wave in fluid medium are developed and their results are compared. The ANSYS software is used for the FE modeling. The analytical model is based on FGM-equivalent acoustic transmission-line model, which is implemented using MATLAB software. Two cases are considered: (i) the transducer emits a pressure wave in water and it is composed of a graded piezoceramic disk, and backing and matching layers made of homogeneous materials; (ii) the transducer has no backing and matching layer; in this case, no external load is simulated. Time and frequency pressure responses are obtained through a transient analysis. The material properties are graded along thickness direction. Linear and exponential gradation functions are implemented to illustrate the influence of gradation on the transducer pressure response, electrical impedance, and resonance frequencies.
Bessel Function Model for Corneal Topography
Okrasiński, Wojciech
2011-01-01
In this paper we consider a new nonlinear mathematical model for corneal topography formulated as two-point boudary value problem. We derive it from first physical principles and provide some mathematical analysis. The existence and uniqeness theorems are proved as well as various estimates on exact solution. At the end we fit the simplified model based on Modified Bessel Function of the First Kind with the real corneal data consisting of matrix of 123x123 points and obtain an error of order of 1%.
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.
Functionalized anatomical models for EM-neuron Interaction modeling
Neufeld, Esra; Cassará, Antonino Mario; Montanaro, Hazael; Kuster, Niels; Kainz, Wolfgang
2016-06-01
The understanding of interactions between electromagnetic (EM) fields and nerves are crucial in contexts ranging from therapeutic neurostimulation to low frequency EM exposure safety. To properly consider the impact of in vivo induced field inhomogeneity on non-linear neuronal dynamics, coupled EM-neuronal dynamics modeling is required. For that purpose, novel functionalized computable human phantoms have been developed. Their implementation and the systematic verification of the integrated anisotropic quasi-static EM solver and neuronal dynamics modeling functionality, based on the method of manufactured solutions and numerical reference data, is described. Electric and magnetic stimulation of the ulnar and sciatic nerve were modeled to help understanding a range of controversial issues related to the magnitude and optimal determination of strength-duration (SD) time constants. The results indicate the importance of considering the stimulation-specific inhomogeneous field distributions (especially at tissue interfaces), realistic models of non-linear neuronal dynamics, very short pulses, and suitable SD extrapolation models. These results and the functionalized computable phantom will influence and support the development of safe and effective neuroprosthetic devices and novel electroceuticals. Furthermore they will assist the evaluation of existing low frequency exposure standards for the entire population under all exposure conditions.
Modeling of vibration for functionally graded beams
Directory of Open Access Journals (Sweden)
Yiğit Gülsemay
2016-01-01
Full Text Available In this study, a vibration problem of Euler-Bernoulli beam manufactured with Functionally Graded Material (FGM, which is modelled by fourth-order partial differential equations with variable coefficients, is examined by using the Adomian Decomposition Method (ADM.The method is one of the useful and powerful methods which can be easily applied to linear and nonlinear initial and boundary value problems. As to functionally graded materials, they are composites mixed by two or more materials at a certain rate. This mixture at a certain rate is expressed with an exponential function in order to try to minimize singularities from transition between different surfaces of materials as much as possible. According to the structure of the ADM in terms of initial conditions of the problem, a Fourier series expansion method is used along with the ADM for the solution of simply supported functionally graded Euler-Bernoulli beams. Finally, by choosing an appropriate mixture rate for the material, the results are shown in figures and compared with those of a standard (homogeneous Euler-Bernoulli beam.
Identifiability of Causal Graphs using Functional Models
Peters, Jonas; Janzing, Dominik; Schoelkopf, Bernhard
2012-01-01
This work addresses the following question: Under what assumptions on the data generating process can one infer the causal graph from the joint distribution? The approach taken by conditional independence-based causal discovery methods is based on two assumptions: the Markov condition and faithfulness. It has been shown that under these assumptions the causal graph can be identified up to Markov equivalence (some arrows remain undirected) using methods like the PC algorithm. In this work we propose an alternative by defining Identifiable Functional Model Classes (IFMOCs). As our main theorem we prove that if the data generating process belongs to an IFMOC, one can identify the complete causal graph. To the best of our knowledge this is the first identifiability result of this kind that is not limited to linear functional relationships. We discuss how the IFMOC assumption and the Markov and faithfulness assumptions relate to each other and explain why we believe that the IFMOC assumption can be tested more eas...
Frequency response function-based model updating using Kriging model
Wang, J. T.; Wang, C. J.; Zhao, J. P.
2017-03-01
An acceleration frequency response function (FRF) based model updating method is presented in this paper, which introduces Kriging model as metamodel into the optimization process instead of iterating the finite element analysis directly. The Kriging model is taken as a fast running model that can reduce solving time and facilitate the application of intelligent algorithms in model updating. The training samples for Kriging model are generated by the design of experiment (DOE), whose response corresponds to the difference between experimental acceleration FRFs and its counterpart of finite element model (FEM) at selected frequency points. The boundary condition is taken into account, and a two-step DOE method is proposed for reducing the number of training samples. The first step is to select the design variables from the boundary condition, and the selected variables will be passed to the second step for generating the training samples. The optimization results of the design variables are taken as the updated values of the design variables to calibrate the FEM, and then the analytical FRFs tend to coincide with the experimental FRFs. The proposed method is performed successfully on a composite structure of honeycomb sandwich beam, after model updating, the analytical acceleration FRFs have a significant improvement to match the experimental data especially when the damping ratios are adjusted.
Linearized Functional Minimization for Inverse Modeling
Energy Technology Data Exchange (ETDEWEB)
Wohlberg, Brendt [Los Alamos National Laboratory; Tartakovsky, Daniel M. [University of California, San Diego; Dentz, Marco [Institute of Environmental Assessment and Water Research, Barcelona, Spain
2012-06-21
Heterogeneous aquifers typically consist of multiple lithofacies, whose spatial arrangement significantly affects flow and transport. The estimation of these lithofacies is complicated by the scarcity of data and by the lack of a clear correlation between identifiable geologic indicators and attributes. We introduce a new inverse-modeling approach to estimate both the spatial extent of hydrofacies and their properties from sparse measurements of hydraulic conductivity and hydraulic head. Our approach is to minimize a functional defined on the vectors of values of hydraulic conductivity and hydraulic head fields defined on regular grids at a user-determined resolution. This functional is constructed to (i) enforce the relationship between conductivity and heads provided by the groundwater flow equation, (ii) penalize deviations of the reconstructed fields from measurements where they are available, and (iii) penalize reconstructed fields that are not piece-wise smooth. We develop an iterative solver for this functional that exploits a local linearization of the mapping from conductivity to head. This approach provides a computationally efficient algorithm that rapidly converges to a solution. A series of numerical experiments demonstrates the robustness of our approach.
Density functional theory and multiscale materials modeling
Indian Academy of Sciences (India)
Swapan K Ghosh
2003-01-01
One of the vital ingredients in the theoretical tools useful in materials modeling at all the length scales of interest is the concept of density. In the microscopic length scale, it is the electron density that has played a major role in providing a deeper understanding of chemical binding in atoms, molecules and solids. In the intermediate mesoscopic length scale, an appropriate picture of the equilibrium and dynamical processes has been obtained through the single particle number density of the constituent atoms or molecules. A wide class of problems involving nanomaterials, interfacial science and soft condensed matter has been addressed using the density based theoretical formalism as well as atomistic simulation in this regime. In the macroscopic length scale, however, matter is usually treated as a continuous medium and a description using local mass density, energy density and other related density functions has been found to be quite appropriate. A unique single unified theoretical framework that emerges through the density concept at these diverse length scales and is applicable to both quantum and classical systems is the so called density functional theory (DFT) which essentially provides a vehicle to project the many-particle picture to a single particle one. Thus, the central equation for quantum DFT is a one-particle Schrödinger-like Kohn–Sham equation, while the same for classical DFT consists of Boltzmann type distributions, both corresponding to a system of noninteracting particles in the field of a density-dependent effective potential. Selected illustrative applications of quantum DFT to microscopic modeling of intermolecular interaction and that of classical DFT to a mesoscopic modeling of soft condensed matter systems are presented.
A Prediction Model of the Capillary Pressure J-Function
Xu, W. S.; Luo, P. Y.; Sun, L.; Lin, N.
2016-01-01
The capillary pressure J-function is a dimensionless measure of the capillary pressure of a fluid in a porous medium. The function was derived based on a capillary bundle model. However, the dependence of the J-function on the saturation Sw is not well understood. A prediction model for it is presented based on capillary pressure model, and the J-function prediction model is a power function instead of an exponential or polynomial function. Relative permeability is calculated with the J-function prediction model, resulting in an easier calculation and results that are more representative. PMID:27603701
Genetically modified mouse models addressing gonadotropin function.
Ratner, Laura D; Rulli, Susana B; Huhtaniemi, Ilpo T
2014-03-01
The development of genetically modified animals has been useful to understand the mechanisms involved in the regulation of the gonadotropin function. It is well known that alterations in the secretion of a single hormone is capable of producing profound reproductive abnormalities. Human chorionic gonadotropin (hCG) is a glycoprotein hormone normally secreted by the human placenta, and structurally and functionally it is related to pituitary LH. LH and hCG bind to the same LH/hCG receptor, and hCG is often used as an analog of LH to boost gonadotropin action. There are many physiological and pathological conditions where LH/hCG levels and actions are elevated. In order to understand how elevated LH/hCG levels may impact on the hypothalamic-pituitary-gonadal axis we have developed a transgenic mouse model with chronic hCG hypersecretion. Female mice develop many gonadal and extragonadal phenotypes including obesity, infertility, hyperprolactinemia, and pituitary and mammary gland tumors. This article summarizes recent findings on the mechanisms involved in pituitary gland tumorigenesis and hyperprolactinemia in the female mice hypersecreting hCG, in particular the relationship of progesterone with the hyperprolactinemic condition of the model. In addition, we describe the role of hyperprolactinemia as the main cause of infertility and the phenotypic abnormalities in these mice, and the use of dopamine agonists bromocriptine and cabergoline to normalize these conditions. Copyright © 2014 Society for Biology of Reproduction & the Institute of Animal Reproduction and Food Research of Polish Academy of Sciences in Olsztyn. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.
An Improved Functional Hierarchy Frame Model for System Maintainability
Institute of Scientific and Technical Information of China (English)
CHEN Dai-Lin; CHEN Dong-lin; WANG Ru-gen; ZHU Xue-ping
2003-01-01
By means of analogy, this paper analyses the present functional hierarchy frame model for system maintainability, and presents an improved model. Practical application indicates that the improved model is visualized, more convenient and perfected over the pervious models.
Functional methods in the generalized Dicke model
Energy Technology Data Exchange (ETDEWEB)
Alcalde, M. Aparicio; Lemos, A.L.L. de; Svaiter, N.F. [Centro Brasileiro de Pesquisas Fisicas (CBPF), Rio de Janeiro, RJ (Brazil)]. E-mails: aparicio@cbpf.br; aluis@cbpf.br; nfuxsvai@cbpf.br
2007-07-01
The Dicke model describes an ensemble of N identical two-level atoms (qubits) coupled to a single quantized mode of a bosonic field. The fermion Dicke model should be obtained by changing the atomic pseudo-spin operators by a linear combination of Fermi operators. The generalized fermion Dicke model is defined introducing different coupling constants between the single mode of the bosonic field and the reservoir, g{sub 1} and g{sub 2} for rotating and counter-rotating terms respectively. In the limit N -> {infinity}, the thermodynamic of the fermion Dicke model can be analyzed using the path integral approach with functional method. The system exhibits a second order phase transition from normal to superradiance at some critical temperature with the presence of a condensate. We evaluate the critical transition temperature and present the spectrum of the collective bosonic excitations for the general case (g{sub 1} {ne} 0 and g{sub 2} {ne} 0). There is quantum critical behavior when the coupling constants g{sub 1} and g{sub 2} satisfy g{sub 1} + g{sub 2}=({omega}{sub 0} {omega}){sup 1/2}, where {omega}{sub 0} is the frequency of the mode of the field and {omega} is the energy gap between energy eigenstates of the qubits. Two particular situations are analyzed. First, we present the spectrum of the collective bosonic excitations, in the case g{sub 1} {ne} 0 and g{sub 2} {ne} 0, recovering the well known results. Second, the case g{sub 1} {ne} 0 and g{sub 2} {ne} 0 is studied. In this last case, it is possible to have a super radiant phase when only virtual processes are introduced in the interaction Hamiltonian. Here also appears a quantum phase transition at the critical coupling g{sub 2} ({omega}{sub 0} {omega}){sup 1/2}, and for larger values for the critical coupling, the system enter in this super radiant phase with a Goldstone mode. (author)
Mirror neurons: functions, mechanisms and models.
Oztop, Erhan; Kawato, Mitsuo; Arbib, Michael A
2013-04-12
Mirror neurons for manipulation fire both when the animal manipulates an object in a specific way and when it sees another animal (or the experimenter) perform an action that is more or less similar. Such neurons were originally found in macaque monkeys, in the ventral premotor cortex, area F5 and later also in the inferior parietal lobule. Recent neuroimaging data indicate that the adult human brain is endowed with a "mirror neuron system," putatively containing mirror neurons and other neurons, for matching the observation and execution of actions. Mirror neurons may serve action recognition in monkeys as well as humans, whereas their putative role in imitation and language may be realized in human but not in monkey. This article shows the important role of computational models in providing sufficient and causal explanations for the observed phenomena involving mirror systems and the learning processes which form them, and underlines the need for additional circuitry to lift up the monkey mirror neuron circuit to sustain the posited cognitive functions attributed to the human mirror neuron system. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Modeling Bamboo as a Functionally Graded Material
Silva, Emílio Carlos Nelli; Walters, Matthew C.; Paulino, Glaucio H.
2008-02-01
Natural fibers are promising for engineering applications due to their low cost. They are abundantly available in tropical and subtropical regions of the world, and they can be employed as construction materials. Among natural fibers, bamboo has been widely used for housing construction around the world. Bamboo is an optimized composite material which exploits the concept of Functionally Graded Material (FGM). Biological structures, such as bamboo, are composite materials that have complicated shapes and material distribution inside their domain, and thus the use of numerical methods such as the finite element method and multiscale methods such as homogenization, can help to further understanding of the mechanical behavior of these materials. The objective of this work is to explore techniques such as the finite element method and homogenization to investigate the structural behavior of bamboo. The finite element formulation uses graded finite elements to capture the varying material distribution through the bamboo wall. To observe bamboo behavior under applied loads, simulations are conducted considering a spatially-varying Young's modulus, an averaged Young's modulus, and orthotropic constitutive properties obtained from homogenization theory. The homogenization procedure uses effective, axisymmetric properties estimated from the spatially-varying bamboo composite. Three-dimensional models of bamboo cells were built and simulated under tension, torsion, and bending load cases.
School Teams up for SSP Functional Models
Pignolet, G.; Lallemand, R.; Celeste, A.; von Muldau, H.
2002-01-01
Space Solar Power systems appear increasingly as one of the major solutions to the upcoming global energy crisis, by collecting solar energy in space where this is most easy, and sending it by microwave beam to the surface of the planet, where the need for controlled energy is located. While fully operational systems are still decades away, the need for major development efforts is with us now. Yet, for many decision-makers and for most of the public, SSP often still sounds like science fiction. Six functional demonstration systems, based on the Japanese SPS-2000 concept, have been built as a result of a cooperation between France and Japan, and they are currently used extensively, in Japan, in Europe and in North America, for executive presentations as well as for public exhibitions. There is demand for more models, both for science museums and for use by energy dedicated groups, and a senior high school in La Reunion, France, has picked up the challenge to make the production of such models an integrated practical school project for pre-college students. In December 2001, the administration and the teachers of the school have evaluated the feasibility of the project and eventually taken the go decision for the school year 2002- 2003, when for education purposes a temporary "school business company" will be incorporated with the goal to study and manufacture a limited series of professional quality SSP demonstration models, and to sell them world- wide to institutions and advocacy groups concerned with energy problems and with the environment. The different sections of the school will act as the different services of an integrated business : based on the current existing models, the electronic section will redesign the energy management system and the microwave projector module, while the mechanical section of the school will adapt and re-conceive the whole packaging of the demonstrator. The French and foreign language sections will write up a technical manual for
Modelling with twice continuously differentiable functions
Directory of Open Access Journals (Sweden)
Sanjo Zlobec
2014-03-01
Full Text Available Many real life situations can be described using twice continuously differentiable functions over convex sets with interior points. Such functions have an interesting separation property: At every interior point of the set they separate particular classes of quadratic convex functions from classes of quadratic concave functions. Using this property we introduce new characterizations of the derivative and its zero points. The results are applied to the study of sensitivity of the Cobb-Douglas production function. They are also used to describe the least squares solutions in linear and nonlinear regression.
Application of pharmacokinetics local model to evaluate renal function
Institute of Scientific and Technical Information of China (English)
无
1999-01-01
The pharmacokinetics local model was used to evaluate renal function.Some typical kinds of renal function cases, normal or disorder, were selected to be imaged with SPECT and those data measured were treated by the pharmacokinetics local model computer program (PLM).The results indicated that parameters, including peak value, peak time, inflexion time, half-excretion time, and kinetic equation played and importantrole in judging renal function.The fact confirms that local model isvery useful in evaluating renal function.
A Functional Inspection Model for the Immeasurable Potential Failure State
Institute of Scientific and Technical Information of China (English)
ZHU Wen-ge; LI Shi-qi; ZHAO Di
2008-01-01
Functional inspection is a type of preventive maintenance of Reliability Centered Maintenance (RCM). We, in this paper, establish a functional inspection model(FIM)--the cost model and the availability model for the immeasurable potential failure state based on the delay time concept. This model can be used to determine the appropriate Functional Inspection Interval(FII) to achieve the goal of specific cost and availability and to assist in maintenance decision making.
Mathematical modeling and visualization of functional neuroimages
DEFF Research Database (Denmark)
Rasmussen, Peter Mondrup
influence of model regularization parameter choices on the model generalization, the reliability of the spatial brain patterns extracted from the analysis model, and the ability of the model to identify relevant brain networks defining the underlying neural encoding of the experiment. We show that known...... parts of brain networks can be overlooked in pursuing maximization of prediction accuracy. This supports the view that the quality of spatial patterns extracted from models cannot be assessed purely by focusing on prediction accuracy. Our results instead suggest that model regularization parameters must...
Functional renormalization group approach to the Kraichnan model.
Pagani, Carlo
2015-09-01
We study the anomalous scaling of the structure functions of a scalar field advected by a random Gaussian velocity field, the Kraichnan model, by means of functional renormalization group techniques. We analyze the symmetries of the model and derive the leading correction to the structure functions considering the renormalization of composite operators and applying the operator product expansion.
Predicting Transfer Performance: A Comparison of Competing Function Learning Models
McDaniel, Mark A.; Dimperio, Eric; Griego, Jacqueline A.; Busemeyer, Jerome R.
2009-01-01
The population of linear experts (POLE) model suggests that function learning and transfer are mediated by activation of a set of prestored linear functions that together approximate the given function (Kalish, Lewandowsky, & Kruschke, 2004). In the extrapolation-association (EXAM) model, an exemplar-based architecture associates trained input…
Functional state modelling approach validation for yeast and bacteria cultivations
Roeva, Olympia; Pencheva, Tania
2014-01-01
In this paper, the functional state modelling approach is validated for modelling of the cultivation of two different microorganisms: yeast (Saccharomyces cerevisiae) and bacteria (Escherichia coli). Based on the available experimental data for these fed-batch cultivation processes, three different functional states are distinguished, namely primary product synthesis state, mixed oxidative state and secondary product synthesis state. Parameter identification procedures for different local models are performed using genetic algorithms. The simulation results show high degree of adequacy of the models describing these functional states for both S. cerevisiae and E. coli cultivations. Thus, the local models are validated for the cultivation of both microorganisms. This fact is a strong structure model verification of the functional state modelling theory not only for a set of yeast cultivations, but also for bacteria cultivation. As such, the obtained results demonstrate the efficiency and efficacy of the functional state modelling approach. PMID:26740778
Functional state modelling approach validation for yeast and bacteria cultivations.
Roeva, Olympia; Pencheva, Tania
2014-09-03
In this paper, the functional state modelling approach is validated for modelling of the cultivation of two different microorganisms: yeast (Saccharomyces cerevisiae) and bacteria (Escherichia coli). Based on the available experimental data for these fed-batch cultivation processes, three different functional states are distinguished, namely primary product synthesis state, mixed oxidative state and secondary product synthesis state. Parameter identification procedures for different local models are performed using genetic algorithms. The simulation results show high degree of adequacy of the models describing these functional states for both S. cerevisiae and E. coli cultivations. Thus, the local models are validated for the cultivation of both microorganisms. This fact is a strong structure model verification of the functional state modelling theory not only for a set of yeast cultivations, but also for bacteria cultivation. As such, the obtained results demonstrate the efficiency and efficacy of the functional state modelling approach.
Study on Dielectric Function Models for Surface Plasmon Resonance Structure
Directory of Open Access Journals (Sweden)
Peyman Jahanshahi
2014-01-01
Full Text Available The most common permittivity function models are compared and identifying the best model for further studies is desired. For this study, simulations using several different models and an analytical analysis on a practical surface Plasmon structure were done with an accuracy of ∼94.4% with respect to experimental data. Finite element method, combined with dielectric properties extracted from the Brendel-Bormann function model, was utilized, the latter being chosen from a comparative study on four available models.
Practical Identification of Narmax Models Using Radial Basis Functions.
Chen, S.; Billings, S. A.; Cowan, C.F.N.; Grant, P.M.
1990-01-01
A wide class of discrete time non-linear systems can be represented by the non-linear autoregressive moving average model with exogenous inputs or NARMAX model. This paper develops a practical algorithm for identifying NARMAX models based on radial basis functions from noise corrupted data. The algorithm consists of an iterative orthogonal-forward-regression routine coupled with model validity tests. The orthogonal-forward-regression routine selects parsimonious radial-basis-function models w...
Practical identification of NARMAX models using radial basis functions
Chen, S.; S. A. Billings; Cowan, C.F.N.; Grant, P. M.
1990-01-01
A wide class of discrete time non-linear systems can be represented by the non-linear autoregressive moving average model with exogenous inputs or NARMAX model. This paper develops a practical algorithm for identifying NARMAX models based on radial basis functions from noise corrupted data. The algorithm consists of an iterative orthogonal-forward-regression routine coupled with model validity tests. The orthogonal-forward-regression routine selects parsimonious radial-basis-function models w...
A DSM-based framework for integrated function modelling
DEFF Research Database (Denmark)
Eisenbart, Boris; Gericke, Kilian; Blessing, Lucienne T. M.
2017-01-01
an integrated function modelling framework, which specifically aims at relating between the different function modelling perspectives prominently addressed in different disciplines. It uses interlinked matrices based on the concept of DSM and MDM in order to facilitate cross-disciplinary modelling and analysis...
Factorial Schur functions via the six vertex model
McNamara, Peter J
2009-01-01
For a particular set of Boltzmann weights and a particular boundary condition for the six vertex model in statistical mechanics, we compute explicitly the partition function and show it to be equal to a factorial Schur function.
Correlation Functions for Lattice Integrable Models
Directory of Open Access Journals (Sweden)
F. Smirnov
2008-01-01
Full Text Available In this lectures I consider the problem of calculating the correlation functions for XXZ spin chain. First, I explain in details the free fermion case. Then I show that for generic coupling constant the fermionic operators acting on the space of quasi-local fields can be introduced. In the basis generated by these fermionic operators the correlation functions are given by determinants as in the free fermion case.
On Support Functions for the Development of MFM Models
DEFF Research Database (Denmark)
Heussen, Kai; Lind, Morten
2012-01-01
a review of MFM applications, and contextualizes the model development with respect to process design and operation knowledge. Developing a perspective for an environment for MFM-oriented model- and application-development a tool-chain is outlined and relevant software functions are discussed....... With a perspective on MFM-modeling for existing processes and automation design, modeling stages and corresponding formal model properties are identified. Finally, practically feasible support functions and model-checks to support the model-development are suggested.......A modeling environment and methodology are necessary to ensure quality and reusability of models in any domain. For MFM in particular, as a tool for modeling complex systems, awareness has been increasing for this need. Introducing the context of modeling support functions, this paper provides...
Pattern formation and functionality in swarm models
Rauch, E M; Chialvo, D R; Rauch, Erik M; Millonas, Mark M; Chialvo, Dante R
1995-01-01
We explore a simplified class of models we call swarms, which are inspired by the collective behavior of social insects. We perform a mean-field stability analysis and perform numerical simulations of the model. Several interesting types of behavior emerge in the vicinity of a second-order phase transition in the model, including the formation of stable lines of traffic flow, and memory reconstitution and bootstrapping. In addition to providing an understanding of certain classes of biological behavior, these models bear a generic resemblance to a number of pattern formation processes in the physical sciences.
On the Potts Model Partition Function in an External Field
McDonald, Leslie M.; Moffatt, Iain
2012-03-01
We study the partition function of the Potts model in an external (magnetic) field, and its connections with the zero-field Potts model partition function. Using a deletion-contraction formulation for the partition function Z for this model, we show that it can be expanded in terms of the zero-field partition function. We also show that Z can be written as a sum over the spanning trees, and the spanning forests, of a graph G. Our results extend to Z the well-known spanning tree expansion for the zero-field partition function that arises though its connections with the Tutte polynomial.
Hydroacoustic forcing function modeling using DNS database
Zawadzki, I.; Gershfield, J. L.; Na, Y.; Wang, M.
1996-01-01
A wall pressure frequency spectrum model (Blake 1971 ) has been evaluated using databases from Direct Numerical Simulations (DNS) of a turbulent boundary layer (Na & Moin 1996). Good agreement is found for moderate to strong adverse pressure gradient flows in the absence of separation. In the separated flow region, the model underpredicts the directly calculated spectra by an order of magnitude. The discrepancy is attributed to the violation of the model assumptions in that part of the flow domain. DNS computed coherence length scales and the normalized wall pressure cross-spectra are compared with experimental data. The DNS results are consistent with experimental observations.
Spectral Functions for the Holstein Model
Robin, J. M.
1996-01-01
We perform an unitary transformation for the symmetric phonon mode of the Holstein molecular crystal hamiltonian. We show how to compute the electronic spectral functions by exact numerical diagonalisation of an effective hamiltonian fully taking account of the symmetric phonon mode, usually discarded.
Asymptotic modelling of some functionally graded materials
Wozniak, Czeslaw; Wagrowska, Monika
2010-01-01
International audience; The object of analysis is a multilayered functionally graded laminated heat conductor. Region occupied by this heat conductor is denoted by Ω=(0, L)× Ξ, where Ξ is a region on the 0ξ1ξ2 plane and x∈(0, L). Region Ω is divided into n layers of the same thicknesses λ ...
Multiscale adaptive basis function modeling of spatiotemporal vectorcardiogram signals.
Gang Liu; Hui Yang
2013-03-01
Mathematical modeling of cardiac electrical signals facilitates the simulation of realistic cardiac electrical behaviors, the evaluation of algorithms, and the characterization of underlying space-time patterns. However, there are practical issues pertinent to model efficacy, robustness, and generality. This paper presents a multiscale adaptive basis function modeling approach to characterize not only temporal but also spatial behaviors of vectorcardiogram (VCG) signals. Model parameters are adaptively estimated by the "best matching" projections of VCG characteristic waves onto a dictionary of nonlinear basis functions. The model performance is experimentally evaluated with respect to the number of basis functions, different types of basis function (i.e., Gaussian, Mexican hat, customized wavelet, and Hermitian wavelets), and various cardiac conditions, including 80 healthy controls and different myocardial infarctions (i.e., 89 inferior, 77 anterior-septal, 56 inferior-lateral, 47 anterior, and 43 anterior-lateral). Multiway analysis of variance shows that the basis function and the model complexity have significant effects on model performances while cardiac conditions are not significant. The customized wavelet is found to be an optimal basis function for the modeling of spacetime VCG signals. The comparison of QT intervals shows small relative errors (model representations and realworld VCG signals when the model complexity is greater than 10. The proposed model shows great potentials to model space-time cardiac pathological behaviors and can lead to potential benefits in feature extraction, data compression, algorithm evaluation, and disease prognostics.
Conceptual modelling approach of mechanical products based on functional surface
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
A modelling framework based on functional surface is presented to support conceptual design of mechanical products. The framework organizes product information in an abstract and multilevel manner. It consists of two mapping processes: function decomposition process and form reconstitution process. The steady mapping relationship from function to form (function-functional surface-form) is realized by taking functional surface as the middle layer. It farthest reduces the possibilities of combinatorial explosion that can occur during function decomposition and form reconstitution. Finally, CAD tools are developed and an auto-bender machine is applied to demonstrate the proposed approach.
A Functional Model of the Aesthetic Response
Directory of Open Access Journals (Sweden)
Daniel Conrad
2010-01-01
Full Text Available In a process of somatic evolution, the brain semi-randomly generates initially-unstable neural circuits that are selectively stabilized if they succeed in making sense out of raw sensory input. The human aesthetic response serves the function of stabilizing the circuits that successfully mediate perception and interpretation, making those faculties more agile, conferring selective advantage. It is triggered by structures in art and nature that provoke the making of sense. Art is deliberate human action aimed at triggering the aesthetic response in others; thus, if successful, it serves the same function of making perception and interpretation more agile. These few principles initiate a cascade of emergent phenomena which account for many observed qualities of aesthetics, including universality and idiosyncrasy of taste, the relevance of artists’ intentions, the virtues of openness and resonance, the dysfunction of formulaic art, and the fact that methods of art correspond to modes of perceptual transformation.
Applications of model theory to functional analysis
Iovino, Jose
2014-01-01
During the last two decades, methods that originated within mathematical logic have exhibited powerful applications to Banach space theory, particularly set theory and model theory. This volume constitutes the first self-contained introduction to techniques of model theory in Banach space theory. The area of research has grown rapidly since this monograph's first appearance, but much of this material is still not readily available elsewhere. For instance, this volume offers a unified presentation of Krivine's theorem and the Krivine-Maurey theorem on stable Banach spaces, with emphasis on the
Matrix models for β-ensembles from Nekrasov partition functions
Sułkowski, P.
2010-01-01
We relate Nekrasov partition functions, with arbitrary values of ∊ 1, ∊ 2 parameters, to matrix models for β-ensembles. We find matrix models encoding the instanton part of Nekrasov partition functions, whose measure, to the leading order in ∊ 2 expansion, is given by the Vandermonde determinant to
Damping Functions correct over-dissipation of the Smagorinsky Model
Pakzad, Ali
2016-01-01
This paper studies the time-averaged energy dissipation rate $\\langle \\varepsilon_{SMD} (u)\\rangle$ for the combination of the Smagorinsky model and damping function. The Smagorinsky model is well known to over-damp. One common correction is to include damping functions that reduce the effects of model viscosity near walls. Mathematical analysis is given here that allows evaluation of $\\langle \\varepsilon_{SMD} (u)\\rangle $ for any damping function. Moreover, the analysis motivates a modified van Driest damping. It is proven that the combination of the Smagorinsky with this modified damping function does not over dissipate and is also consistent with Kolmogorov phenomenology.
Functional summary statistics for the Johnson-Mehl model
DEFF Research Database (Denmark)
Møller, Jesper; Ghorbani, Mohammad
of functional summary statistics. This paper therefore invents four functional summary statistics adapted to the Johnson-Mehl model, with two of them based on the second-order properties and the other two on the nuclei-boundary distances for the associated Johnson-Mehl tessellation. The functional summary...... statistics theoretical properties are investigated, non-parametric estimators are suggested, and their usefulness for model checking is examined in a simulation study. The functional summary statistics are also used for checking fitted parametric Johnson-Mehl models for a neurotransmitters dataset....
Kajiwara, Tsuyoshi; Sasaki, Toru; Takeuchi, Yasuhiro
2015-02-01
We present a constructive method for Lyapunov functions for ordinary differential equation models of infectious diseases in vivo. We consider models derived from the Nowak-Bangham models. We construct Lyapunov functions for complex models using those of simpler models. Especially, we construct Lyapunov functions for models with an immune variable from those for models without an immune variable, a Lyapunov functions of a model with absorption effect from that for a model without absorption effect. We make the construction clear for Lyapunov functions proposed previously, and present new results with our method.
Improved parameter estimation for hydrological models using weighted object functions
Stein, A.; Zaadnoordijk, W.J.
1999-01-01
This paper discusses the sensitivity of calibration of hydrological model parameters to different objective functions. Several functions are defined with weights depending upon the hydrological background. These are compared with an objective function based upon kriging. Calibration is applied to pi
Refined functional relations for the elliptic SOS model
Galleas, W
2012-01-01
In this work we refine the method of [1] and obtain a novel kind of functional equation determining the partition function of the elliptic SOS model with domain wall boundaries. This functional relation is originated from the dynamical Yang-Baxter algebra and its solution is given in terms of multiple contour integrals.
A generalized trigonometric series function model for determining ionospheric delay
Institute of Scientific and Technical Information of China (English)
YUAN Yunbin; OU Jikun
2004-01-01
A generalized trigonometric series function (GTSF) model, with an adjustable number of parameters, is proposed and analyzed to study ionosphere by using GPS, especially to provide ionospheric delay correction for single frequency GPS users. The preliminary results show that, in comparison with the trigonometric series function (TSF) model and the polynomial (POLY) model, the GTSF model can more precisely describe the ionospheric variation and more efficiently provide the ionospheric correction when GPS data are used to investigate or extract the earth's ionospheric total electron content. It is also shown that the GTSF model can further improve the precision and accuracy of modeling local ionospheric delays.
Modeling dynamic functional connectivity using a wishart mixture model
DEFF Research Database (Denmark)
Nielsen, Søren Føns Vind; Madsen, Kristoffer Hougaard; Schmidt, Mikkel Nørgaard
2017-01-01
.e. the window length. In this work we use the Wishart Mixture Model (WMM) as a probabilistic model for dFC based on variational inference. The framework admits arbitrary window lengths and number of dynamic components and includes the static one-component model as a special case. We exploit that the WMM...
Partition function of nearest neighbour Ising models: Some new insights
Indian Academy of Sciences (India)
G Nandhini; M V Sangaranarayanan
2009-09-01
The partition function for one-dimensional nearest neighbour Ising models is estimated by summing all the energy terms in the Hamiltonian for N sites. The algebraic expression for the partition function is then employed to deduce the eigenvalues of the basic 2 × 2 matrix and the corresponding Hermitian Toeplitz matrix is derived using the Discrete Fourier Transform. A new recurrence relation pertaining to the partition function for two-dimensional Ising models in zero magnetic field is also proposed.
Reassessing Models of Basal Ganglia Function and Dysfunction
Nelson, Alexandra B.; Kreitzer, Anatol C.
2014-01-01
The basal ganglia are a series of interconnected subcortical nuclei. The function and dysfunction of these nuclei has been studied intensively as it pertains to motor control, but more recently our knowledge of these functions has broadened to include prominent roles in cognition and affective control. This review will summarize historical models of basal ganglia function, findings which have supported or conflicted with these models, and emphasize recent work in animals and humans directly t...
Correlation function of four spins in the percolation model
Dotsenko, Vladimir S.
2016-10-01
By using the Coulomb gas technics we calculate the four-spin correlation function in the percolation q → 1 limit of the Potts model. It is known that the four-point functions define the actual fusion rules of a particular model. In this respect, we find that fusion of two spins, of dimension Δσ =5/96, produce a new channel, in the 4-point function, which is due to the operator with dimension Δ = 5 / 8.
A model of synthesis based on functional reasoning
DEFF Research Database (Denmark)
Hansen, Claus Thorp; Zavbi, R.
2002-01-01
In this paper we propose a model of how to carry out functional reasoning. The model is based on the domain theory, and it links the stepwise determination of the artefact´s characteristics during the design process to different ways of carrying out functional reasoning found in the literature....... The model proposes of a set of the mental objects and a number of ways to carry out functional reasoning available to the engineering designer. The result of the research presented in this paper is the building of a hypothesis "in the form of a model" with explanatory power....
Transfer Function Model of Multirate Feedback Control Systems
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Based on the suitably defined multivariable version of Krancoperators and the extended input and output vectors, the multirate sampling plant is transformed to a equivalent time invariant single rate one, then the transfer function model of the multivariable multirate sampling plant is obtained. By combining this plant model with the time invariant description of the multirate controller in terms of extended vectors, the closed-loop transfer function model of the multirate feedback control system can be determinated. This transfer function model has a very simple structure, and can be used as a basis for the analysis and synthesis of the multirate sampling feedback control systems in the frequency domain.
Arrese, S; Alegria, A; Colmenero, J; Frick, B
2002-01-01
We present a preliminary investigation of the dynamics of glassy polycarbonate (PC) and polysulfone (PSF) by means of quasielastic neutron scattering and dielectric spectroscopy. Whereas the consideration of pure phenylene ring pi-flips is enough to explain the momentum-transfer (Q) dependence of the inelastic intensity measured for PSF, in the case of PC the Q dependence of both the coherent and the incoherent scattering functions reveal the existence in this polymer of some more complex motion of the phenylene ring. On the other hand, the similarity of the energy landscapes deduced from the different techniques points to a closely related molecular origin for all the relaxation/motions observed. (orig.)
Mathematical modeling and visualization of functional neuroimages
Rasmussen, Peter Mondrup; Hansen, Lars Kai; Madsen, Kristoffer Hougaard
2011-01-01
Denne afhandling præsenterer forskningsresultater omhandlende matematisk modellering indenfor analyse af funktionelle hjernescanningsbilleder. Specifikt fokuserer afhandlingen pa mønster-baserede analysemetoder, som nyligt er blevet populære indenfor hjerneforskning. Ved hjæp af sådanne modelleringsmetoderne forsger forskere at prdiktere en eksperimentelt defineret mental tilstand ud fra hjernescanningsdata. Afhandlingen omhandler emner, der kan inddeles i to dele.Første del undersger hvorled...
Functional Difference Equations and an Epidemic Model.
1980-06-09
ADDRESS 12. REPORT DATE AIR FORCE OFFICE OF SCIENTIFIC RESEARC 913 June 9, 1980 BOLLING AIR FORCE BASE , WASHINGTON, D.tI,3. NUMBEROFAGS 14. MONITORING...allowed spatial effects in an S - I model to arrive at the equation t S(t,x) = S(t,x).J B(;x, )S(t+6,0) dAdO in some region f cR. If X is the ordered
Robust classification of functional and quantitative image data using functional mixed models.
Zhu, Hongxiao; Brown, Philip J; Morris, Jeffrey S
2012-12-01
This article introduces new methods for performing classification of complex, high-dimensional functional data using the functional mixed model (FMM) framework. The FMM relates a functional response to a set of predictors through functional fixed and random effects, which allows it to account for various factors and between-function correlations. The methods include training and prediction steps. In the training steps we train the FMM model by treating class designation as one of the fixed effects, and in the prediction steps we classify the new objects using posterior predictive probabilities of class. Through a Bayesian scheme, we are able to adjust for factors affecting both the functions and the class designations. While the methods can be used in any FMM framework, we provide details for two specific Bayesian approaches: the Gaussian, wavelet-based FMM (G-WFMM) and the robust, wavelet-based FMM (R-WFMM). Both methods perform modeling in the wavelet space, which yields parsimonious representations for the functions, and can naturally adapt to local features and complex nonstationarities in the functions. The R-WFMM allows potentially heavier tails for features of the functions indexed by particular wavelet coefficients, leading to a down-weighting of outliers that makes the method robust to outlying functions or regions of functions. The models are applied to a pancreatic cancer mass spectroscopy data set and compared with other recently developed functional classification methods. © 2012, The International Biometric Society.
Modeling Dynamic Functional Neuroimaging Data Using Structural Equation Modeling
Price, Larry R.; Laird, Angela R.; Fox, Peter T.; Ingham, Roger J.
2009-01-01
The aims of this study were to present a method for developing a path analytic network model using data acquired from positron emission tomography. Regions of interest within the human brain were identified through quantitative activation likelihood estimation meta-analysis. Using this information, a "true" or population path model was then…
Thermoplasmonics modeling: A Green's function approach
Baffou, Guillaume; Quidant, Romain; Girard, Christian
2010-10-01
We extend the discrete dipole approximation (DDA) and the Green’s dyadic tensor (GDT) methods—previously dedicated to all-optical simulations—to investigate the thermodynamics of illuminated plasmonic nanostructures. This extension is based on the use of the thermal Green’s function and a original algorithm that we named Laplace matrix inversion. It allows for the computation of the steady-state temperature distribution throughout plasmonic systems. This hybrid photothermal numerical method is suited to investigate arbitrarily complex structures. It can take into account the presence of a dielectric planar substrate and is simple to implement in any DDA or GDT code. Using this numerical framework, different applications are discussed such as thermal collective effects in nanoparticles assembly, the influence of a substrate on the temperature distribution and the heat generation in a plasmonic nanoantenna. This numerical approach appears particularly suited for new applications in physics, chemistry, and biology such as plasmon-induced nanochemistry and catalysis, nanofluidics, photothermal cancer therapy, or phase-transition control at the nanoscale.
Calibrating the ECCO ocean general circulation model using Green's functions
Menemenlis, D.; Fu, L. L.; Lee, T.; Fukumori, I.
2002-01-01
Green's functions provide a simple, yet effective, method to test and calibrate General-Circulation-Model(GCM) parameterizations, to study and quantify model and data errors, to correct model biases and trends, and to blend estimates from different solutions and data products.
Tactile Teaching: Exploring Protein Structure/Function Using Physical Models
Herman, Tim; Morris, Jennifer; Colton, Shannon; Batiza, Ann; Patrick, Michael; Franzen, Margaret; Goodsell, David S.
2006-01-01
The technology now exists to construct physical models of proteins based on atomic coordinates of solved structures. We review here our recent experiences in using physical models to teach concepts of protein structure and function at both the high school and the undergraduate levels. At the high school level, physical models are used in a…
Models of neural networks with fuzzy activation functions
Nguyen, A. T.; Korikov, A. M.
2017-02-01
This paper investigates the application of a new form of neuron activation functions that are based on the fuzzy membership functions derived from the theory of fuzzy systems. On the basis of the results regarding neuron models with fuzzy activation functions, we created the models of fuzzy-neural networks. These fuzzy-neural network models differ from conventional networks that employ the fuzzy inference systems using the methods of neural networks. While conventional fuzzy-neural networks belong to the first type, fuzzy-neural networks proposed here are defined as the second-type models. The simulation results show that the proposed second-type model can successfully solve the problem of the property prediction for time – dependent signals. Neural networks with fuzzy impulse activation functions can be widely applied in many fields of science, technology and mechanical engineering to solve the problems of classification, prediction, approximation, etc.
Four-point function in the IOP matrix model
Michel, Ben; Polchinski, Joseph; Rosenhaus, Vladimir; Suh, S. Josephine
2016-05-01
The IOP model is a quantum mechanical system of a large- N matrix oscillator and a fundamental oscillator, coupled through a quartic interaction. It was introduced previously as a toy model of the gauge dual of an AdS black hole, and captures a key property that at infinite N the two-point function decays to zero on long time scales. Motivated by recent work on quantum chaos, we sum all planar Feynman diagrams contributing to the four-point function. We find that the IOP model does not satisfy the more refined criteria of exponential growth of the out-of-time-order four-point function.
Deep inelastic structure functions in the chiral bag model
Energy Technology Data Exchange (ETDEWEB)
Sanjose, V. (Valencia Univ. (Spain). Dept. de Didactica de las Ciencias Experimentales); Vento, V. (Valencia Univ. (Spain). Dept. de Fisica Teorica; Centro Mixto CSIC/Valencia Univ., Valencia (Spain). Inst. de Fisica Corpuscular)
1989-10-02
We calculate the structure functions for deep inelastic scattering on baryons in the cavity approximation to the chiral bag model. The behavior of these structure functions is analyzed in the Bjorken limit. We conclude that scaling is satisfied, but not Regge behavior. A trivial extension as a parton model can be achieved by introducing the structure function for the pion in a convolution picture. In this extended version of the model not only scaling but also Regge behavior is satisfied. Conclusions are drawn from the comparison of our results with experimental data. (orig.).
Four-point function in the IOP matrix model
Michel, Ben; Rosenhaus, Vladimir; Suh, S Josephine
2016-01-01
The IOP model is a quantum mechanical system of a large-$N$ matrix oscillator and a fundamental oscillator, coupled through a quartic interaction. It was introduced previously as a toy model of the gauge dual of an AdS black hole, and captures a key property that at infinite $N$ the two-point function decays to zero on long time scales. Motivated by recent work on quantum chaos, we sum all planar Feynman diagrams contributing to the four-point function. We find that the IOP model does not satisfy the more refined criteria of exponential growth of the out-of-time-order four-point function.
Product Modelling and Functional Reasoning in Conceptual Design
Institute of Scientific and Technical Information of China (English)
林志航; 宋慧军; 陈康宁
2004-01-01
In this paper, a product model in conceptual design, Domain Structure Template, is proposed, which combines the functional domain and the physical domain with the behaviour domain. Seven types of primary mappings units connecting functions, behaviours and carriers during conceptual design process are identified according to the characteristics of the conceptual design of mechanical products.Based on these seven primary mappings, a hierarchical functional reasoning framework characterizing the process of conceptual design is presented. A case study for the conceptual design of industry sewing machines with chain-stitch is described to demonstrate the product modelling and the scheme generation based on the presented model.
Functional Characterization of a Porcine Emphysema Model
DEFF Research Database (Denmark)
Bruun, Camilla Sichlau; Jensen, Louise Kruse; Leifsson, Páll Skuli
2013-01-01
Lung emphysema is a central feature of chronic obstructive pulmonary disease (COPD), a frequent human disease worldwide. Cigarette smoking is the major cause of COPD, but genetic predisposition seems to be an important factor. Mutations in surfactant protein genes have been linked to COPD...... develop age-related lung emphysema due to lack of ITGB6-TGF-β1 regulation of the MMP12 expression.A mutated pig phenotype characterized by age-related lung emphysema and resembling the ITGB6−/− mouse has been described previously. To investigate the emphysema pathogenesis in this pig model, we examined...... the expression of MMP2, MMP7, MMP9, MMP12, and TGF-β1 by quantitative PCR (qPCR). In addition, immunohistochemical stainings of the lungs with SP-B, SP-C, MMP9, and MMP12 antibodies were performed. The haematologic/immunologic status of the pigs also was studied.The qPCR study showed no difference between pigs...
Beretvas, S. Natasha; Walker, Cindy M.
2012-01-01
This study extends the multilevel measurement model to handle testlet-based dependencies. A flexible two-level testlet response model (the MMMT-2 model) for dichotomous items is introduced that permits assessment of differential testlet functioning (DTLF). A distinction is made between this study's conceptualization of DTLF and that of…
Probability density function modeling for sub-powered interconnects
Pater, Flavius; Amaricǎi, Alexandru
2016-06-01
This paper proposes three mathematical models for reliability probability density function modeling the interconnect supplied at sub-threshold voltages: spline curve approximations, Gaussian models,and sine interpolation. The proposed analysis aims at determining the most appropriate fitting for the switching delay - probability of correct switching for sub-powered interconnects. We compare the three mathematical models with the Monte-Carlo simulations of interconnects for 45 nm CMOS technology supplied at 0.25V.
Factorized domain wall partition functions in trigonometric vertex models
Foda, O; Zuparic, M
2007-01-01
We obtain factorized domain wall partition functions for two sets of trigonometric vertex models: 1. The N-state Deguchi-Akutsu models, for N = {2, 3, 4} (and conjecture the result for all N >= 5), and 2. The sl(r+1|s+1) Perk-Schultz models, for {r, s = \\N}, where (given the symmetries of these models) the result is independent of {r, s}.
Functional models of power electronic components for system studies
Tam, Kwa-Sur; Yang, Lifeng; Dravid, Narayan
1991-01-01
A novel approach to model power electronic circuits has been developed to facilitate simulation studies of system-level issues. The underlying concept for this approach is to develop an equivalent circuit, the functional model, that performs the same functions as the actual circuit but whose operation can be simulated by using larger time step size and the reduction in model complexity, the computation time required by a functional model is significantly shorter than that required by alternative approaches. The authors present this novel modeling approach and discuss the functional models of two major power electronic components, the DC/DC converter unit and the load converter, that are being considered by NASA for use in the Space Station Freedom electric power system. The validity of these models is established by comparing the simulation results with available experimental data and other simulation results obtained by using a more established modeling approach. The usefulness of this approach is demonstrated by incorporating these models into a power system model and simulating the system responses and interactions between components under various conditions.
Importance of predictor variables for models of chemical function
U.S. Environmental Protection Agency — Importance of random forest predictors for all classification models of chemical function. This dataset is associated with the following publication: Isaacs , K., M....
Applying Functional Modeling for Accident Management of Nuclear Power Plant
DEFF Research Database (Denmark)
Lind, Morten; Zhang, Xinxin
2014-01-01
The paper investigate applications of functional modeling for accident management in complex industrial plant with special reference to nuclear power production. Main applications for information sharing among decision makers and decision support are identified. An overview of Multilevel Flow...
FUNCTIONAL MODELLING FOR FAULT DIAGNOSIS AND ITS APPLICATION FOR NPP
Directory of Open Access Journals (Sweden)
MORTEN LIND
2014-12-01
Full Text Available The paper presents functional modelling and its application for diagnosis in nuclear power plants. Functional modelling is defined and its relevance for coping with the complexity of diagnosis in large scale systems like nuclear plants is explained. The diagnosis task is analyzed and it is demonstrated that the levels of abstraction in models for diagnosis must reflect plant knowledge about goals and functions which is represented in functional modelling. Multilevel flow modelling (MFM, which is a method for functional modelling, is introduced briefly and illustrated with a cooling system example. The use of MFM for reasoning about causes and consequences is explained in detail and demonstrated using the reasoning tool, the MFMSuite. MFM applications in nuclear power systems are described by two examples: a PWR; and an FBR reactor. The PWR example show how MFM can be used to model and reason about operating modes. The FBR example illustrates how the modelling development effort can be managed by proper strategies including decomposition and reuse.
Enhancements to the SSME transfer function modeling code
Irwin, R. Dennis; Mitchell, Jerrel R.; Bartholomew, David L.; Glenn, Russell D.
1995-01-01
This report details the results of a one year effort by Ohio University to apply the transfer function modeling and analysis tools developed under NASA Grant NAG8-167 (Irwin, 1992), (Bartholomew, 1992) to attempt the generation of Space Shuttle Main Engine High Pressure Turbopump transfer functions from time domain data. In addition, new enhancements to the transfer function modeling codes which enhance the code functionality are presented, along with some ideas for improved modeling methods and future work. Section 2 contains a review of the analytical background used to generate transfer functions with the SSME transfer function modeling software. Section 2.1 presents the 'ratio method' developed for obtaining models of systems that are subject to single unmeasured excitation sources and have two or more measured output signals. Since most of the models developed during the investigation use the Eigensystem Realization Algorithm (ERA) for model generation, Section 2.2 presents an introduction of ERA, and Section 2.3 describes how it can be used to model spectral quantities. Section 2.4 details the Residue Identification Algorithm (RID) including the use of Constrained Least Squares (CLS) and Total Least Squares (TLS). Most of this information can be found in the report (and is repeated for convenience). Section 3 chronicles the effort of applying the SSME transfer function modeling codes to the a51p394.dat and a51p1294.dat time data files to generate transfer functions from the unmeasured input to the 129.4 degree sensor output. Included are transfer function modeling attempts using five methods. The first method is a direct application of the SSME codes to the data files and the second method uses the underlying trends in the spectral density estimates to form transfer function models with less clustering of poles and zeros than the models obtained by the direct method. In the third approach, the time data is low pass filtered prior to the modeling process in an
EFFICIENCY MODELS OF THE CROSS-FUNCTIONAL TEAMS
Directory of Open Access Journals (Sweden)
Dinca Laura
2013-04-01
Full Text Available Cross-functional teams represent a characteristic of the new organization form of the enterprises, imposed by the complexity of the present environment. Regardless their kind, the new organization forms are based on the cross-functional teams as an innovation source and reunion of competences. Only by the medium of the cross-functional teams, the new organizational partnerships obtain flexibility in their actions and fastness in their reactions. By their features, the cross-functional teams should be differentiated from any kind of work-group. What makes them different is the common effort carried to reach the common objective of the team. The present paper presents two research models for the efficiency of the cross-functional teams, respectively input-process-output and input-mediator-outcome models. These show the factors on which cross-functional teams’ managers should action to obtain superior economic performances.
Fragmentation Functions for Heavy Baryons in the Recombination Model
Institute of Scientific and Technical Information of China (English)
彭茹
2011-01-01
Using the shower parton distributions determined by the recombination model, we predict the fragmentation functions for heavy baryons. Then we obtain the completed fragmentation functions of heavy quarks (c and b) splitting into their hadrons (mesons and baryons containing one heavy valence quark). The calculated process shows that the fragmentation functions for mesons and baryons are not independent if the hadronization of the shower partons is taken into account.%Using the shower parton distributions determined by the recombination model,we predict the fragmentation functions for heavy baryons.Then we obtain the completed fragmentation functions of heavy quarks(c and b)splitting into their hadrons(mesons and baryons containing one heavy valence quark).The calculated process shows that the fragmentation functions for mesons and baryons are not independent if the hadronization of the shower partons is taken into account.
Conventional modeling of the multilayer perceptron using polynomial basis functions
Chen, Mu-Song; Manry, Michael T.
1993-01-01
A technique for modeling the multilayer perceptron (MLP) neural network, in which input and hidden units are represented by polynomial basis functions (PBFs), is presented. The MLP output is expressed as a linear combination of the PBFs and can therefore be expressed as a polynomial function of its inputs. Thus, the MLP is isomorphic to conventional polynomial discriminant classifiers or Volterra filters. The modeling technique was successfully applied to several trained MLP networks.
A no extensive statistical model for the nucleon structure function
Trevisan, Luis A.; Mirez, Carlos
2013-03-01
We studied an application of nonextensive thermodynamics to describe the structure function of nucleon, in a model where the usual Fermi-Dirac and Bose-Einstein energy distribution were replaced by the equivalent functions of the q-statistical. The parameters of the model are given by an effective temperature T, the q parameter (from Tsallis statistics), and two chemical potentials given by the corresponding up (u) and down (d) quark normalization in the nucleon.
Generalized Functional Linear Models With Semiparametric Single-Index Interactions
Li, Yehua
2010-06-01
We introduce a new class of functional generalized linear models, where the response is a scalar and some of the covariates are functional. We assume that the response depends on multiple covariates, a finite number of latent features in the functional predictor, and interaction between the two. To achieve parsimony, the interaction between the multiple covariates and the functional predictor is modeled semiparametrically with a single-index structure. We propose a two step estimation procedure based on local estimating equations, and investigate two situations: (a) when the basis functions are pre-determined, e.g., Fourier or wavelet basis functions and the functional features of interest are known; and (b) when the basis functions are data driven, such as with functional principal components. Asymptotic properties are developed. Notably, we show that when the functional features are data driven, the parameter estimates have an increased asymptotic variance, due to the estimation error of the basis functions. Our methods are illustrated with a simulation study and applied to an empirical data set, where a previously unknown interaction is detected. Technical proofs of our theoretical results are provided in the online supplemental materials.
Features of Functioning the Integrated Building Thermal Model
Directory of Open Access Journals (Sweden)
Morozov Maxim N.
2017-01-01
Full Text Available A model of the building heating system, consisting of energy source, a distributed automatic control system, elements of individual heating unit and heating system is designed. Application Simulink of mathematical package Matlab is selected as a platform for the model. There are the specialized application Simscape libraries in aggregate with a wide range of Matlab mathematical tools allow to apply the “acausal” modeling concept. Implementation the “physical” representation of the object model gave improving the accuracy of the models. Principle of operation and features of the functioning of the thermal model is described. The investigations of building cooling dynamics were carried out.
Efficient vector hysteresis modeling using rotationally coupled step functions
Energy Technology Data Exchange (ETDEWEB)
Adly, A.A., E-mail: adlyamr@gmail.com; Abd-El-Hafiz, S.K., E-mail: sabdelhafiz@gmail.com
2012-05-01
Vector hysteresis models are usually used as sub-modules of field computation software tools. When dealing with a massive field computation problem, computational efficiency and practicality of such models become crucial. In this paper, generalization of a recently proposed computationally efficient vector hysteresis model based upon interacting step functions is presented. More specifically, the model is generalized to cover vector hysteresis modeling of both isotropic and anisotropic magnetic media. Model configuration details as well as experimental testing and simulation results are given in the paper.
Spin Structure Functions in a Covariant Spectator Quark Model
Energy Technology Data Exchange (ETDEWEB)
G. Ramalho, Franz Gross and M. T. Peña
2010-12-01
We apply the covariant spectator quark–diquark model, already probed in the description of the nucleon elastic form factors, to the calculation of the deep inelastic scattering (DIS) spin-independent and spin-dependent structure functions of the nucleon. The nucleon wave function is given by a combination of quark–diquark orbital states, corresponding to S, D and P-waves. A simple form for the quark distribution function associated to the P and D waves is tested.
Longitudinal mixed-effects models for latent cognitive function
Hout, van den Ardo; Fox, Jean-Paul; Muniz-Terrera, Graciela
2015-01-01
A mixed-effects regression model with a bent-cable change-point predictor is formulated to describe potential decline of cognitive function over time in the older population. For the individual trajectories, cognitive function is considered to be a latent variable measured through an item response t
Correlation function of four spins in the percolation model
Directory of Open Access Journals (Sweden)
Vladimir S. Dotsenko
2016-10-01
It is known that the four-point functions define the actual fusion rules of a particular model. In this respect, we find that fusion of two spins, of dimension Δσ=596, produce a new channel, in the 4-point function, which is due to the operator with dimension Δ=5/8.
Cost damping and functional form in transport models
DEFF Research Database (Denmark)
Rich, Jeppe; Mabit, Stefan Lindhard
2015-01-01
take different forms and be represented as a non-linear-in-parameter form such as the well-known Box–Cox function. However, it could also be specified as non-linear-in-cost but linear-in-parameter forms, which are easier to estimate and improve model fit without increasing the number of parameters....... The specific contributions of the paper are as follows. Firstly, we discuss the phenomenon of cost damping in details and specifically why it occurs. Secondly, we provide a test of damping and an easy assessment of the (linear) damping rate for any variable by estimating two auxiliary linear models. This turns......Transport models allowing for cost damping are characterised by marginally decreasing cost sensitivities in demand. As a result, cost damping is a model extension of the simple linear-in-cost model requiring an appropriate non-linear link function between utility and cost. The link function may...
Cost damping and functional form in transport models
DEFF Research Database (Denmark)
Rich, Jeppe; Mabit, Stefan Lindhard
2016-01-01
Transport models allowing for cost damping are characterised by marginally decreasing cost sensitivities in demand. As a result, cost damping is a model extension of the simple linear-in-cost model requiring an appropriate non-linear link function between utility and cost. The link function may...... take different forms and be represented as a non-linear-in-parameter form such as the well-known Box–Cox function. However, it could also be specified as non-linear-in-cost but linear-in-parameter forms, which are easier to estimate and improve model fit without increasing the number of parameters....... The specific contributions of the paper are as follows. Firstly, we discuss the phenomenon of cost damping in details and specifically why it occurs. Secondly, we provide a test of damping and an easy assessment of the (linear) damping rate for any variable by estimating two auxiliary linear models. This turns...
Jellium-with-gap model applied to semilocal kinetic functionals
Constantin, Lucian A.; Fabiano, Eduardo; Śmiga, Szymon; Della Sala, Fabio
2017-03-01
We investigate a highly nonlocal generalization of the Lindhard function, given by the jellium-with-gap model. We find a band-gap-dependent gradient expansion of the kinetic energy, which performs noticeably well for large atoms. Using the static linear response theory and the simplest semilocal model for the local band gap, we derive a nonempirical generalized gradient approximation (GGA) of the kinetic energy. This GGA kinetic-energy functional is remarkably accurate for the description of weakly interacting molecular systems within the subsystem formulation of density functional theory.
Approximating the partition function of the ferromagnetic Potts model
Goldberg, Leslie Ann
2010-01-01
We provide evidence that it is computationally difficult to approximate the partition function of the ferromagnetic q-state Potts model when q>2. Specifically we show that the partition function is hard for the complexity class #RHPi_1 under approximation-preserving reducibility. Thus, it is as hard to approximate the partition function as it is to find approximate solutions to a wide range of counting problems, including that of determining the number of independent sets in a bipartite graph. Our proof exploits the second order phase transition of the "random cluster" model, which is a probability distribution on graphs that is closely related to the q-state Potts
A new analytical edge spread function fitting model for modulation transfer function measurement
Institute of Scientific and Technical Information of China (English)
Tiecheng Li; Huajun Feng; Zhihai Xu
2011-01-01
@@ We propose a new analytical edge spread function (ESF) fitting model to measure the modulation transfer function (MTF).The ESF data obtained from a slanted-edge image are fitted to our model through the non-linear least squares (NLLSQ) method.The differentiation of the ESF yields the line spread function (LSF), the Fourier transform of which gives the profile of two-dimensional MTF.Compared with the previous methods, the MTF estimate determined by our method conforms more closely to the reference.A practical application of our MTF measurement in degraded image restoration also validates the accuracy of our model.%We propose a new analytical edge spread function (ESF) fitting model to measure the modulation transfer function (MTF). The ESF data obtained from a slanted-edge image are fitted to our model through the non-linear least squares (NLLSQ) method. The differentiation of the ESF yields the line spread function (LSF), the Fourier transform of which gives the profile of two-dimensional MTF. Compared with the previous methods, the MTF estimate determined by our method conforms more closely to the reference. A practical application of our MTF measurement in degraded image restoration also validates the accuracy of our model.
Invention software support by integrating function and mathematical modeling
Chechurin, L.S.; Wits, Wessel Willems; Bakker, H.M.
2015-01-01
New idea generation is imperative for successful product innovation and technology development. This paper presents the development of a novel type of invention support software. The support tool integrates both function modeling and mathematical modeling, thereby enabling quantitative analyses on a
Diet models with linear goal programming: impact of achievement functions
Gerdessen, J.C.; Vries, de J.H.M.
2015-01-01
Background/Objectives: Diet models based on goal programming (GP) are valuable tools in designing diets that comply with nutritional, palatability and cost constraints. Results derived from GP models are usually very sensitive to the type of achievement function that is chosen. This paper aims to pr
Invention software support by integrating function and mathematical modeling
Chechurin, L.S.; Wits, W.W.; Bakker, H.M.
2015-01-01
New idea generation is imperative for successful product innovation and technology development. This paper presents the development of a novel type of invention support software. The support tool integrates both function modeling and mathematical modeling, thereby enabling quantitative analyses on a
The McMaster Model of Family Functioning.
Epstein, Nathan B; And Others
1978-01-01
The model of family functioning being presented is the product of over 20 years of research in clinical work with family units. The model uses a general systems theory approach in an attempt to describe the structure, organization, and transactional patterns of the family unit. (Author)
Hazard identification by extended multilevel flow modelling with function roles
DEFF Research Database (Denmark)
Wu, Jing; Zhang, Laibin; Jørgensen, Sten Bay
2014-01-01
HAZOP studies are widely accepted in chemical and petroleum industries as the method for conducting process hazard analysis related to design, maintenance and operation of th e systems. In this paper, a HAZOP reasoning method based on function-oriented modelling, multilevel flow modelling (MFM) i...
FUNCTIONAL-COEFFICIENT REGRESSION MODEL AND ITS ESTIMATION
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
In this paper,a class of functional-coefficient regression models is proposed and an estimation procedure based on the locally weighted least equares is suggested. This class of models,with the proposed estimation method,is a powerful means for exploratory data analysis.
Gluon fragmentation functions in the Nambu-Jona-Lasinio model
Yang, Dong-Jing
2016-01-01
We derive gluon fragmentation functions in the Nambu-Jona-Lasinio (NJL) model by treating a gluon as a pair of color lines formed by fictitious quark and anti-quark ($q\\bar q$). Gluon elementary fragmentation functions are obtained from the quark and anti-quark elementary fragmentation functions for emitting specific mesons in the NJL model under the requirement that the $q\\bar q$ pair maintains in the flavor-singlet state after meson emissions. An integral equation, which iterates the gluon elementary fragmentation functions to all orders, is then solved to yield the gluon fragmentation functions at a model scale. It is observed that these solutions are stable with respect to variation of relevant model parameters, especially after QCD evolution to a higher scale is implemented. We show that the inclusion of the gluon fragmentation functions into the theoretical predictions from only the quark fragmentation functions greatly improves the agreement with the SLD data for the pion and kaon productions in $e^+e^...
Density Functional Theory and Materials Modeling at Atomistic Length Scales
Directory of Open Access Journals (Sweden)
Swapan K. Ghosh
2002-04-01
Full Text Available Abstract: We discuss the basic concepts of density functional theory (DFT as applied to materials modeling in the microscopic, mesoscopic and macroscopic length scales. The picture that emerges is that of a single unified framework for the study of both quantum and classical systems. While for quantum DFT, the central equation is a one-particle Schrodinger-like Kohn-Sham equation, the classical DFT consists of Boltzmann type distributions, both corresponding to a system of noninteracting particles in the field of a density-dependent effective potential, the exact functional form of which is unknown. One therefore approximates the exchange-correlation potential for quantum systems and the excess free energy density functional or the direct correlation functions for classical systems. Illustrative applications of quantum DFT to microscopic modeling of molecular interaction and that of classical DFT to a mesoscopic modeling of soft condensed matter systems are highlighted.
Functionally Unidimensional Item Response Models for Multivariate Binary Data.
Ip, Edward H; Molenberghs, Geert; Chen, Shyh-Huei; Goegebeur, Yuri; De Boeck, Paul
2013-07-01
The problem of fitting unidimensional item response models to potentially multidimensional data has been extensively studied. The focus of this article is on response data that have a strong dimension but also contain minor nuisance dimensions. Fitting a unidimensional model to such multidimensional data is believed to result in ability estimates that represent a combination of the major and minor dimensions. We conjecture that the underlying dimension for the fitted unidimensional model, which we call the functional dimension, represents a nonlinear projection. In this article we investigate 2 issues: (a) can a proposed nonlinear projection track the functional dimension well, and (b) what are the biases in the ability estimate and the associated standard error when estimating the functional dimension? To investigate the second issue, the nonlinear projection is used as an evaluative tool. An example regarding a construct of desire for physical competency is used to illustrate the functional unidimensional approach.
Joint Modelling of Structural and Functional Brain Networks
DEFF Research Database (Denmark)
Andersen, Kasper Winther; Herlau, Tue; Mørup, Morten
Functional and structural magnetic resonance imaging have become the most important noninvasive windows to the human brain. A major challenge in the analysis of brain networks is to establish the similarities and dissimilarities between functional and structural connectivity. We formulate a non...... significant structures that are consistently shared across subjects and data splits. This provides an unsupervised approach for modeling of structure-function relations in the brain and provides a general framework for multimodal integration.......-parametric Bayesian network model which allows for joint modelling and integration of multiple networks. We demonstrate the model’s ability to detect vertices that share structure across networks jointly in functional MRI (fMRI) and diffusion MRI (dMRI) data. Using two fMRI and dMRI scans per subject, we establish...
Model Penentuan Nilai Target Functional Requirement Berbasis Utilitas
Directory of Open Access Journals (Sweden)
Cucuk Nur Rosyidi
2012-01-01
Full Text Available In a product design and development process, a designer faces a problem to decide functional requirement (FR target values. That decision is made under a risk since it is conducted in the early design phase using incomplete information. Utility function can be used to reflect the decision maker attitude towards the risk in making such decision. In this research, we develop a utility-based model to determine FR target values using quadratic utility function and information from Quality Function Deployment (QFD. A pencil design is used as a numerical example using quadratic utility function for each FR. The model can be applied for balancing customer and designer interest in determining FR target values.
The mass and temperature functions in a moving barrier model
Popolo, A D
2002-01-01
In this paper, I use the extension of the excursion set model of Sheth & Tormen (2002) and the barrier shape obtained in Del Popolo & Gambera (1998) to calculate the unconditional halo mass function, and the conditional mass function in several cosmological models. I show that the barrier obtained in Del Popolo & Gambera (1998), which takes account of tidal interaction between proto-haloes, is a better description of the mass functions than the spherical collapse and is in good agreement with numerical simulations (Tozzi & Governato 1998, and Governato et al. 1999). The results are also in good agreement with those obtained by Sheth & Tormen (2002), only slight differences are observed expecially at the low mass end. I moreover calculate, and compare with simulations, the temperature function obtained by means of the mass functions previously calculated and also using an improved version of the M-T relation, which accounts for the fact that massive clusters accrete matter quasi-continuousl...
Sloppy nuclear energy density functionals: effective model reduction
Niksic, Tamara
2016-01-01
Concepts from information geometry are used to analyse parameter sensitivity for a nuclear energy density functional, representative of a class of semi-empirical functionals that start from a microscopically motivated ansatz for the density dependence of the energy of a system of protons and neutrons. It is shown that such functionals are sloppy, characterized by an exponential range of sensitivity to parameter variations. Responsive to only a few stiff parameter combinations, they exhibit an exponential decrease of sensitivity to variations of the remaining soft parameters. By interpreting the space of model predictions as a manifold embedded in the data space, with the parameters of the functional as coordinates on the manifold, it is also shown that the exponential distribution of model manifold widths corresponds to the distribution of parameter sensitivity. Using the Manifold Boundary Approximation Method, we illustrate how to systematically construct effective nuclear density functionals of successively...
Modelling of multidimensional quantum systems by the numerical functional integration
Energy Technology Data Exchange (ETDEWEB)
Lobanov, Yu.Yu.; Zhidkov, E.P. (Joint Inst. for Nuclear Research, Dubna (USSR)); Shahbagian, R.R. (Yerevan Physics Inst., Erevan (USSR))
1990-01-01
The employment of the numerical functional integration for the description of multidimensional systems in quantum and statistical physics is considered. For the multiple functional integrals with respect to Gaussian measures in the full separable metric spaces the new approximation formulas exact on a class of polynomial functionals of a given summary degree are constructed. The use of the formulas is demonstrated on example of computation of the Green function and the ground state energy in multidimensional Calogero model. The comparison of numerical results with the data obtained by the other authors which used the Monte Carlo method combined with iterative algorithms indicates that our formulas provide the higher efficiency of computations.
Partially linear varying coefficient models stratified by a functional covariate
Maity, Arnab
2012-10-01
We consider the problem of estimation in semiparametric varying coefficient models where the covariate modifying the varying coefficients is functional and is modeled nonparametrically. We develop a kernel-based estimator of the nonparametric component and a profiling estimator of the parametric component of the model and derive their asymptotic properties. Specifically, we show the consistency of the nonparametric functional estimates and derive the asymptotic expansion of the estimates of the parametric component. We illustrate the performance of our methodology using a simulation study and a real data application.
Delta-function Approximation SSC Model in 3C 273
Indian Academy of Sciences (India)
S. J. Kang; Y. G. Zheng; Q. Wu
2014-09-01
We obtain an approximate analytical solution using approximate calculation on the traditional one-zone synchrotron self-Compton (SSC) model. In this model, we describe the electron energy distribution by a broken power-law function with a sharp cut-off, and non-thermal photons are produced by both synchrotron and inverse Compton scattering of synchrotron photons. We calculate the radiation energy spectrum of electrons by the function. We apply this model to the multi-wavelength Spectral Energy Distributions (SED) of the 3C 273 in different states, and obtain excellent fits to the observed spectra of this source.
Functional Modelling for Fault Diagnosis and its application for NPP
DEFF Research Database (Denmark)
Lind, Morten; Zhang, Xinxin
2014-01-01
The paper presents functional modelling and its application for diagnosis in nuclear power plants.Functional modelling is defined and it is relevance for coping with the complexity of diagnosis in large scale systems like nuclear plants is explained. The diagnosis task is analyzed....... The use of MFM for reasoning about causes and consequences is explained in detail and demonstrated using the reasoning tool the MFM Suite. MFM applications in nuclear power systems are described by two examples a PWR and a FBRreactor. The PWR example show how MFM can be used to model and reason about...
Partially Linear Varying Coefficient Models Stratified by a Functional Covariate.
Maity, Arnab; Huang, Jianhua Z
2012-10-01
We consider the problem of estimation in semiparametric varying coefficient models where the covariate modifying the varying coefficients is functional and is modeled nonparametrically. We develop a kernel-based estimator of the nonparametric component and a profiling estimator of the parametric component of the model and derive their asymptotic properties. Specifically, we show the consistency of the nonparametric functional estimates and derive the asymptotic expansion of the estimates of the parametric component. We illustrate the performance of our methodology using a simulation study and a real data application.
The SWISS-MODEL Repository—new features and functionality
Bienert, Stefan; Waterhouse, Andrew; de Beer, Tjaart A. P.; Tauriello, Gerardo; Studer, Gabriel; Bordoli, Lorenza; Schwede, Torsten
2017-01-01
SWISS-MODEL Repository (SMR) is a database of annotated 3D protein structure models generated by the automated SWISS-MODEL homology modeling pipeline. It currently holds >400 000 high quality models covering almost 20% of Swiss-Prot/UniProtKB entries. In this manuscript, we provide an update of features and functionalities which have been implemented recently. We address improvements in target coverage, model quality estimates, functional annotations and improved in-page visualization. We also introduce a new update concept which includes regular updates of an expanded set of core organism models and UniProtKB-based targets, complemented by user-driven on-demand update of individual models. With the new release of the modeling pipeline, SMR has implemented a REST-API and adopted an open licencing model for accessing model coordinates, thus enabling bulk download for groups of targets fostering re-use of models in other contexts. SMR can be accessed at https://swissmodel.expasy.org/repository. PMID:27899672
Meneses, Domingos De Sousa; Rousseau, Benoit; Echegut, Patrick; Matzen, Guy
2007-06-01
A new expression of dielectric function model based on piecewise polynomials is introduced. Its association with spline and more recent shape preserving interpolation algorithms allows easy reproduction of every kind of experimental spectra and thus retrieval of all the linear optical functions of a material. Based on a pure mathematical framework, the expression of the model is always applicable and does not necessitate any knowledge of the microscopic mechanisms of absorption responsible for the optical response. The potential of piecewise polynomial dielectric functions is shown through synthetic examples and the analysis of experimental spectra.
Applying Functional Modeling for Accident Management of Nucler Power Plant
DEFF Research Database (Denmark)
Lind, Morten; Zhang, Xinxin
2014-01-01
The paper investigates applications of functional modeling for accident management in complex industrial plant with special reference to nuclear power production. Main applications for information sharing among decision makers and decision support are identified. An overview of Multilevel Flow...... for information sharing and decision support in accidents beyond design basis is also indicated. A modelling example demonstrating the application of Multilevel Flow Modelling and reasoning for a PWR LOCA is presented....
Functional State Modelling of Cultivation Processes: Dissolved Oxygen Limitation State
Directory of Open Access Journals (Sweden)
Olympia Roeva
2015-04-01
Full Text Available A new functional state, namely dissolved oxygen limitation state for both bacteria Escherichia coli and yeast Saccharomyces cerevisiae fed-batch cultivation processes is presented in this study. Functional state modelling approach is applied to cultivation processes in order to overcome the main disadvantages of using global process model, namely complex model structure and a big number of model parameters. Alongwith the newly introduced dissolved oxygen limitation state, second acetate production state and first acetate production state are recognized during the fed-batch cultivation of E. coli, while mixed oxidative state and first ethanol production state are recognized during the fed-batch cultivation of S. cerevisiae. For all mentioned above functional states both structural and parameter identification is here performed based on experimental data of E. coli and S. cerevisiae fed-batch cultivations.
Embedded systems development from functional models to implementations
Zeng, Haibo; Natale, Marco; Marwedel, Peter
2014-01-01
This book offers readers broad coverage of techniques to model, verify and validate the behavior and performance of complex distributed embedded systems. The authors attempt to bridge the gap between the three disciplines of model-based design, real-time analysis and model-driven development, for a better understanding of the ways in which new development flows can be constructed, going from system-level modeling to the correct and predictable generation of a distributed implementation, leveraging current and future research results. Describes integration of heterogeneous models; Discusses synthesis of task model implementations and code implementations; Compares model-based design vs. model-driven approaches; Explains how to enforce correctness by construction in the functional and time domains; Includes optimization techniques for control performance.
Density functionals and dimensional renormalization for an exactly solvable model
Kais, S.; Herschbach, D. R.; Handy, N. C.; Murray, C. W.; Laming, G. J.
1993-07-01
We treat an analytically solvable version of the ``Hooke's Law'' model for a two-electron atom, in which the electron-electron repulsion is Coulombic but the electron-nucleus attraction is replaced by a harmonic oscillator potential. Exact expressions are obtained for the ground-state wave function and electron density, the Hartree-Fock solution, the correlation energy, the Kohn-Sham orbital, and, by inversion, the exchange and correlation functionals. These functionals pertain to the ``intermediate'' density regime (rs≥1.4) for an electron gas. As a test of customary approximations employed in density functional theory, we compare our exact density, exchange, and correlation potentials and energies with results from two approximations. These use Becke's exchange functional and either the Lee-Yang-Parr or the Perdew correlation functional. Both approximations yield rather good results for the density and the exchange and correlation energies, but both deviate markedly from the exact exchange and correlation potentials. We also compare properties of the Hooke's Law model with those of two-electron atoms, including the large dimension limit. A renormalization procedure applied to this very simple limit yields correlation energies as good as those obtained from the approximate functionals, for both the model and actual atoms.
Functionally unidimensional item response models for multivariate binary data
DEFF Research Database (Denmark)
Ip, Edward; Molenberghs, Geert; Chen, Shyh-Huei;
2013-01-01
The problem of fitting unidimensional item response models to potentially multidimensional data has been extensively studied. The focus of this article is on response data that have a strong dimension but also contain minor nuisance dimensions. Fitting a unidimensional model to such multidimensio......The problem of fitting unidimensional item response models to potentially multidimensional data has been extensively studied. The focus of this article is on response data that have a strong dimension but also contain minor nuisance dimensions. Fitting a unidimensional model...... to such multidimensional data is believed to result in ability estimates that represent a combination of the major and minor dimensions. We conjecture that the underlying dimension for the fitted unidimensional model, which we call the functional dimension, represents a nonlinear projection. In this article we investigate...... tool. An example regarding a construct of desire for physical competency is used to illustrate the functional unidimensional approach....
Using computational models to relate structural and functional brain connectivity.
Hlinka, Jaroslav; Coombes, Stephen
2012-07-01
Modern imaging methods allow a non-invasive assessment of both structural and functional brain connectivity. This has lead to the identification of disease-related alterations affecting functional connectivity. The mechanism of how such alterations in functional connectivity arise in a structured network of interacting neural populations is as yet poorly understood. Here we use a modeling approach to explore the way in which this can arise and to highlight the important role that local population dynamics can have in shaping emergent spatial functional connectivity patterns. The local dynamics for a neural population is taken to be of the Wilson-Cowan type, whilst the structural connectivity patterns used, describing long-range anatomical connections, cover both realistic scenarios (from the CoComac database) and idealized ones that allow for more detailed theoretical study. We have calculated graph-theoretic measures of functional network topology from numerical simulations of model networks. The effect of the form of local dynamics on the observed network state is quantified by examining the correlation between structural and functional connectivity. We document a profound and systematic dependence of the simulated functional connectivity patterns on the parameters controlling the dynamics. Importantly, we show that a weakly coupled oscillator theory explaining these correlations and their variation across parameter space can be developed. This theoretical development provides a novel way to characterize the mechanisms for the breakdown of functional connectivity in diseases through changes in local dynamics.
Modeling particle size distributions by the Weibull distribution function
Energy Technology Data Exchange (ETDEWEB)
Fang, Zhigang (Rogers Tool Works, Rogers, AR (United States)); Patterson, B.R.; Turner, M.E. Jr (Univ. of Alabama, Birmingham, AL (United States))
1993-10-01
A method is proposed for modeling two- and three-dimensional particle size distributions using the Weibull distribution function. Experimental results show that, for tungsten particles in liquid phase sintered W-14Ni-6Fe, the experimental cumulative section size distributions were well fit by the Weibull probability function, which can also be used to compute the corresponding relative frequency distributions. Modeling the two-dimensional section size distributions facilitates the use of the Saltykov or other methods for unfolding three-dimensional (3-D) size distributions with minimal irregularities. Fitting the unfolded cumulative 3-D particle size distribution with the Weibull function enables computation of the statistical distribution parameters from the parameters of the fit Weibull function.
Improved Wave-vessel Transfer Functions by Uncertainty Modelling
DEFF Research Database (Denmark)
Nielsen, Ulrik Dam; Fønss Bach, Kasper; Iseki, Toshio
2016-01-01
This paper deals with uncertainty modelling of wave-vessel transfer functions used to calculate or predict wave-induced responses of a ship in a seaway. Although transfer functions, in theory, can be calculated to exactly reflect the behaviour of the ship when exposed to waves, uncertainty in input...... variables, notably speed, draft and relative wave eading, often compromises results. In this study, uncertling is applied to improve theoretically calculated transfer functions, so they better fit the corresponding experimental, full-scale ones. Based on a vast amount of full-scale measurements data......, it is shown that uncertainty modelling can be successfully used to improve accuracy (and reliability) of theoretical transfer functions....
Cluster density functional theory for lattice models based on the theory of Möbius functions
Lafuente, Luis; Cuesta, José A.
2005-08-01
Rosenfeld's fundamental-measure theory for lattice models is given a rigorous formulation in terms of the theory of Möbius functions of partially ordered sets. The free-energy density functional is expressed as an expansion in a finite set of lattice clusters. This set is endowed with a partial order, so that the coefficients of the cluster expansion are connected to its Möbius function. Because of this, it is rigorously proven that a unique such expansion exists for any lattice model. The low-density analysis of the free-energy functional motivates a redefinition of the basic clusters (zero-dimensional cavities) which guarantees a correct zero-density limit of the pair and triplet direct correlation functions. This new definition extends Rosenfeld's theory to lattice models with any kind of short-range interaction (repulsive or attractive, hard or soft, one or multicomponent ...). Finally, a proof is given that these functionals have a consistent dimensional reduction, i.e. the functional for dimension d' can be obtained from that for dimension d (d' < d) if the latter is evaluated at a density profile confined to a d'-dimensional subset.
Cluster density functional theory for lattice models based on the theory of Moebius functions
Energy Technology Data Exchange (ETDEWEB)
Lafuente, Luis; Cuesta, Jose A [Grupo Interdisciplinar de Sistemas Complejos (GISC), Departamento de Matematicas, Universidad Carlos III de Madrid, 28911 Leganes, Madrid (Spain)
2005-08-26
Rosenfeld's fundamental-measure theory for lattice models is given a rigorous formulation in terms of the theory of Moebius functions of partially ordered sets. The free-energy density functional is expressed as an expansion in a finite set of lattice clusters. This set is endowed with a partial order, so that the coefficients of the cluster expansion are connected to its Moebius function. Because of this, it is rigorously proven that a unique such expansion exists for any lattice model. The low-density analysis of the free-energy functional motivates a redefinition of the basic clusters (zero-dimensional cavities) which guarantees a correct zero-density limit of the pair and triplet direct correlation functions. This new definition extends Rosenfeld's theory to lattice models with any kind of short-range interaction (repulsive or attractive, hard or soft, one or multicomponent ...). Finally, a proof is given that these functionals have a consistent dimensional reduction, i.e. the functional for dimension d' can be obtained from that for dimension d (d' < d) if the latter is evaluated at a density profile confined to a d'-dimensional subset.
Wind-Wave Model with an Optimized Source Function
Polnikov, Vladislav
2010-01-01
On the basis of the author's earlier results, a new source function for a numerical wind-wave model optimized by the criterion of accuracy and speed of calculation is substantiated. The proposed source function includes (a) an optimized version of the discrete interaction approximation for parametrization of the nonlinear evolution mechanism, (b) a generalized empirical form of the input term modified by adding a special block of the dynamic boundary layer of the atmosphere, and (c) a dissipation term quadratic in the wave spectrum. Particular attention is given to a theoretical substantiation of the least investigated dissipation term. The advantages of the proposed source function are discussed by its comparison to the analogues used in the widespread models of the third generation WAM and WAVEWATCH. At the initial stage of assessing the merits of the proposed model, the results of its testing by the system of academic tests are presented. In the course of testing, some principals of this procedure are form...
Bread dough rheology: Computing with a damage function model
Tanner, Roger I.; Qi, Fuzhong; Dai, Shaocong
2015-01-01
We describe an improved damage function model for bread dough rheology. The model has relatively few parameters, all of which can easily be found from simple experiments. Small deformations in the linear region are described by a gel-like power-law memory function. A set of large non-reversing deformations - stress relaxation after a step of shear, steady shearing and elongation beginning from rest, and biaxial stretching, is used to test the model. With the introduction of a revised strain measure which includes a Mooney-Rivlin term, all of these motions can be well described by the damage function described in previous papers. For reversing step strains, larger amplitude oscillatory shearing and recoil reasonable predictions have been found. The numerical methods used are discussed and we give some examples.
The transverse momentum dependent distribution functions in the bag model
Energy Technology Data Exchange (ETDEWEB)
Avakian, Harut; Efremov, Anatoly; Schweitzer, Peter; Yuan, Feng
2010-01-29
Leading and subleading twist transverse momentum dependent parton distribution functions (TMDs) are studied in a quark model framework provided by the bag model. A complete set of relations among different TMDs is derived, and the question is discussed how model-(in)dependent such relations are. A connection of the pretzelosity distribution and quark orbital angular momentum is derived. Numerical results are presented, and applications for phenomenology discussed. In particular, it is shown that in the valence-x region the bag model supports a Gaussian Ansatz for the transverse momentum dependence of TMDs.
Transverse momentum dependent distribution functions in the bag model
Energy Technology Data Exchange (ETDEWEB)
Avakian, Harut A. [Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States); Efremov, A. V. [Joint Inst. for Nuclear Research (JINR), Dubna (Russian Federation); Schweitzer, P. [Univ. of Connecticut, Storrs, CT (United States); Yuan, F. [Brookhaven National Lab. (BNL), Upton, NY (United States). RIKEN Research Center; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
2010-04-01
Leading and subleading twist transverse momentum dependent parton distribution functions (TMDs) are studied in a quark model framework provided by the bag model. A complete set of relations among different TMDs is derived, and the question is discussed how model-(in)dependent such relations are. A connection of the pretzelosity distribution and quark orbital angular momentum is derived. Numerical results are presented, and applications for phenomenology discussed. In particular, it is shown that in the valence-x region the bag model supports a Gaussian Ansatz for the transverse momentum dependence of TMDs.
Testing the Conditional Mean Function of Autoregressive Conditional Duration Models
DEFF Research Database (Denmark)
Hautsch, Nikolaus
be subject to censoring structures. In an empirical study based on financial transaction data we present an application of the model to estimate conditional asset price change probabilities. Evaluating the forecasting properties of the model, it is shown that the proposed approach is a promising competitor...... function. The dynamic properties of the model as well as an assessment of the estimation quality is investigated in a Monte Carlo study. It is illustrated that the model is a useful approach to estimate conditional failure probabilities based on (persistent) serial dependent duration data which might...
Advances on statistical/thermodynamical models for unpolarized structure functions
Trevisan, Luis A.; Mirez, Carlos; Tomio, Lauro
2013-03-01
During the eights and nineties many statistical/thermodynamical models were proposed to describe the nucleons' structure functions and distribution of the quarks in the hadrons. Most of these models describe the compound quarks and gluons inside the nucleon as a Fermi / Bose gas respectively, confined in a MIT bag[1] with continuous energy levels. Another models considers discrete spectrum. Some interesting features of the nucleons are obtained by these models, like the sea asymmetries ¯d/¯u and ¯d-¯u.
Applying Functional Modeling for Accident Management of Nuclear Power Plant
Energy Technology Data Exchange (ETDEWEB)
Lind, Morten; Zhang Xinxin [Harbin Engineering University, Harbin (China)
2014-08-15
The paper investigate applications of functional modeling for accident management in complex industrial plant with special reference to nuclear power production. Main applications for information sharing among decision makers and decision support are identified. An overview of Multilevel Flow Modeling is given and a detailed presentation of the foundational means-end concepts is presented and the conditions for proper use in modelling accidents are identified. It is shown that Multilevel Flow Modeling can be used for modelling and reasoning about design basis accidents. Its possible role for information sharing and decision support in accidents beyond design basis is also indicated. A modelling example demonstrating the application of Multilevel Flow Modelling and reasoning for a PWR LOCA is presented.
Generating function of correlators in the $sl_2$ Gaudin model
Sklyanin, E K
1997-01-01
For the sl_2 Gaudin model (degenerated quantum integrable XXX spin chain) an exponential generating function of correlators is calculated explicitely. The calculation relies on the Gauss decomposition for the SL_2 loop group. From the generating function a new explicit expression for the correlators is derived from which the determinant formulas for the norms of Bethe eigenfunctions due to Richardson and Gaudin are obtained.
Functional dynamic factor models with application to yield curve forecasting
Hays, Spencer
2012-09-01
Accurate forecasting of zero coupon bond yields for a continuum of maturities is paramount to bond portfolio management and derivative security pricing. Yet a universal model for yield curve forecasting has been elusive, and prior attempts often resulted in a trade-off between goodness of fit and consistency with economic theory. To address this, herein we propose a novel formulation which connects the dynamic factor model (DFM) framework with concepts from functional data analysis: a DFM with functional factor loading curves. This results in a model capable of forecasting functional time series. Further, in the yield curve context we show that the model retains economic interpretation. Model estimation is achieved through an expectation- maximization algorithm, where the time series parameters and factor loading curves are simultaneously estimated in a single step. Efficient computing is implemented and a data-driven smoothing parameter is nicely incorporated. We show that our model performs very well on forecasting actual yield data compared with existing approaches, especially in regard to profit-based assessment for an innovative trading exercise. We further illustrate the viability of our model to applications outside of yield forecasting.
Testing galaxy formation models with galaxy stellar mass functions
Lim, S. H.; Mo, H. J.; Lan, Ting-Wen; Ménard, Brice
2016-10-01
We compare predictions of a number of empirical models and numerical simulations of galaxy formation to the conditional stellar mass functions (CSMF) of galaxies in groups of different masses obtained recently by Lan et al. to test how well different models accommodate the data. The observational data clearly prefer a model in which star formation in low-mass halos changes behavior at a characteristic redshift zc ˜ 2. There is also tentative evidence that this characteristic redshift depends on environment, becoming zc ˜ 4 in regions that eventually evolve into rich clusters of galaxies. The constrained model is used to understand how galaxies form and evolve in dark matter halos, and to make predictions for other statistical properties of the galaxy population, such as the stellar mass functions of galaxies at high z, the star formation and stellar mass assembly histories in dark matter halos. A comparison of our model predictions with those of other empirical models shows that different models can make vastly different predictions, even though all of them are tuned to match the observed stellar mass functions of galaxies.
Testing galaxy formation models with galaxy stellar mass functions
Lim, S. H.; Mo, H. J.; Lan, T.-W.; Ménard, B.
2017-01-01
We compare predictions of a number of empirical models and numerical simulations of galaxy formation to the conditional stellar mass functions of galaxies in groups of different masses obtained recently by Lan et al. to test how well different models accommodate the data. The observational data clearly prefer a model in which star formation in low-mass haloes changes behaviour at a characteristic redshift zc ˜ 2. There is also tentative evidence that this characteristic redshift depends on environment, becoming zc ˜ 4 in regions that eventually evolve into rich clusters of galaxies. The constrained model is used to understand how galaxies form and evolve in dark matter haloes, and to make predictions for other statistical properties of the galaxy population, such as the stellar mass functions of galaxies at high z, the star formation, and stellar mass assembly histories in dark matter haloes. A comparison of our model predictions with those of other empirical models shows that different models can make vastly different predictions, even though all of them are tuned to match the observed stellar mass functions of galaxies.
Conserved Functional Motifs and Homology Modeling to Predict Hidden Moonlighting Functional Sites
Wong, Aloysius Tze
2015-06-09
Moonlighting functional centers within proteins can provide them with hitherto unrecognized functions. Here, we review how hidden moonlighting functional centers, which we define as binding sites that have catalytic activity or regulate protein function in a novel manner, can be identified using targeted bioinformatic searches. Functional motifs used in such searches include amino acid residues that are conserved across species and many of which have been assigned functional roles based on experimental evidence. Molecules that were identified in this manner seeking cyclic mononucleotide cyclases in plants are used as examples. The strength of this computational approach is enhanced when good homology models can be developed to test the functionality of the predicted centers in silico, which, in turn, increases confidence in the ability of the identified candidates to perform the predicted functions. Computational characterization of moonlighting functional centers is not diagnostic for catalysis but serves as a rapid screening method, and highlights testable targets from a potentially large pool of candidates for subsequent in vitro and in vivo experiments required to confirm the functionality of the predicted moonlighting centers.
Conserved functional motifs and homology modelling to predict hidden moonlighting functional sites
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Helen R Irving
2015-06-01
Full Text Available Moonlighting functional centers within proteins can provide them with hitherto unrecognized functions. Here we review how hidden moonlighting functional centers which we define as binding sites that have catalytic activity or regulate protein function in a novel manner, can be identified using targeted bioinformatic searches. Functional motifs used in such searches include amino acid residues that are conserved across species and many of which have been assigned functional roles based on experimental evidence. Molecules that were identified in this manner seeking cyclic mononucleotide cyclases in plants are used as examples. The strength of this computational approach is enhanced when good homology models can be developed to test the functionality of the predicted centers in silico which in turn, increases confidence in the ability of the identified candidates to perform the predicted functions. Computational characterization of moonlighting functional centers is not diagnostic for catalysis but serves as a rapid screening method, and highlights testable targets from a potentially large pool of candidates for subsequent in vitro and in vivo experiments required to confirm the functionality of the predicted moonlighting centers.
Enabling Cross-Discipline Collaboration Via a Functional Data Model
Lindholm, D. M.; Wilson, A.; Baltzer, T.
2016-12-01
Many research disciplines have very specialized data models that are used to express the detailed semantics that are meaningful to that community and easily utilized by their data analysis tools. While invaluable to members of that community, such expressive data structures and metadata are of little value to potential collaborators from other scientific disciplines. Many data interoperability efforts focus on the difficult task of computationally mapping concepts from one domain to another to facilitate discovery and use of data. Although these efforts are important and promising, we have found that a great deal of discovery and dataset understanding still happens at the level of less formal, personal communication. However, a significant barrier to inter-disciplinary data sharing that remains is one of data access.Scientists and data analysts continue to spend inordinate amounts of time simply trying to get data into their analysis tools. Providing data in a standard file format is often not sufficient since data can be structured in many ways. Adhering to more explicit community standards for data structure and metadata does little to help those in other communities.The Functional Data Model specializes the Relational Data Model (used by many database systems)by defining relations as functions between independent (domain) and dependent (codomain) variables. Given that arrays of data in many scientific data formats generally represent functionally related parameters (e.g. temperature as a function of space and time), the Functional Data Model is quite relevant for these datasets as well. The LaTiS software framework implements the Functional Data Model and provides a mechanism to expose an existing data source as a LaTiS dataset. LaTiS datasets can be manipulated using a Functional Algebra and output in any number of formats.LASP has successfully used the Functional Data Model and its implementation in the LaTiS software framework to bridge the gap between
Using special functions to model the propagation of airborne diseases
Bolaños, Daniela
2014-06-01
Some special functions of the mathematical physics are using to obtain a mathematical model of the propagation of airborne diseases. In particular we study the propagation of tuberculosis in closed rooms and we model the propagation using the error function and the Bessel function. In the model, infected individual emit pathogens to the environment and this infect others individuals who absorb it. The evolution in time of the concentration of pathogens in the environment is computed in terms of error functions. The evolution in time of the number of susceptible individuals is expressed by a differential equation that contains the error function and it is solved numerically for different parametric simulations. The evolution in time of the number of infected individuals is plotted for each numerical simulation. On the other hand, the spatial distribution of the pathogen around the source of infection is represented by the Bessel function K0. The spatial and temporal distribution of the number of infected individuals is computed and plotted for some numerical simulations. All computations were made using software Computer algebra, specifically Maple. It is expected that the analytical results that we obtained allow the design of treatment rooms and ventilation systems that reduce the risk of spread of tuberculosis.
ABOUT COMPLEX APPROACH TO MODELLING OF TECHNOLOGICAL MACHINES FUNCTIONING
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A. A. Honcharov
2015-01-01
Full Text Available Problems arise in the process of designing, production and investigation of a complicated technological machine. These problems concern not only properties of some types of equipment but they have respect to regularities of control object functioning as a whole. A technological machine is thought of as such technological complex where it is possible to lay emphasis on a control system (or controlling device and a controlled object. The paper analyzes a number of existing approaches to construction of models for controlling devices and their functioning. A complex model for a technological machine operation has been proposed in the paper; in other words it means functioning of a controlling device and a controlled object of the technological machine. In this case models of the controlling device and the controlled object of the technological machine can be represented as aggregate combination (elements of these models. The paper describes a conception on realization of a complex model for a technological machine as a model for interaction of units (elements in the controlling device and the controlled object. When a control activation is given to the controlling device of the technological machine its modelling is executed at an algorithmic or logic level and the obtained output signals are interpreted as events and information about them is transferred to executive mechanisms.The proposed scheme of aggregate integration considers element models as object classes and the integration scheme is presented as a combination of object property values (combination of a great many input and output contacts and combination of object interactions (in the form of an integration operator. Spawn of parent object descendants of the technological machine model and creation of their copies in various project parts is one of the most important means of the distributed technological machine modelling that makes it possible to develop complicated models of
Gluon Sivers function in a light-cone spectator model
Lu, Zhun
2016-01-01
We calculate the gluon Sivers function of the proton in the valence-$x$ region using a light-cone spectator model with the presence of the gluon degree of freedom. We obtain the values of the parameters by fitting the model resulting gluon density distribution to the known parametrization. We find that our results agree with the recent phenomenological extraction of the gluon Sivers function after considering the evolution effect. We also estimate the mean transverse momentum of the gluon in a transversely polarized proton and find that it is within the range implied by the Burkardt sum rule.
Control architecture of power systems: Modeling of purpose and function
DEFF Research Database (Denmark)
Heussen, Kai; Saleem, Arshad; Lind, Morten
2009-01-01
for semantically consistent modeling of control architecture is presented. The method, called Multilevel Flow Modeling (MFM), is applied to the case of system balancing. It was found that MFM is capable of capturing implicit control knowledge, which is otherwise difficult to formalize. The method has possible...... of power systems and it is necessary to identify requirements and functions. How does new control architecture fit with the old architecture? How can power system functions be specified independent of technology? What is the purpose of control in power systems? In this paper, a method suitable...
Identification of Multimodel LPV Models with Asymmetric Gaussian Weighting Function
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Jie You
2013-01-01
Full Text Available This paper is concerned with the identification of linear parameter varying (LPV systems by utilizing a multimodel structure. To improve the approximation capability of the LPV model, asymmetric Gaussian weighting functions are introduced and compared with commonly used symmetric Gaussian functions. By this mean, locations of operating points can be selected freely. It has been demonstrated through simulations with a high purity distillation column that the identified models provide more satisfactory approximation. Moreover, an experiment is performed on real HVAC (heating, ventilation, and air-conditioning to further validate the effectiveness of the proposed approach.
Modeling of Ionospheric Delay for SBAS Using Spherical Harmonics Functions
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Deokhwa Han
2013-06-01
Full Text Available In SBAS (satellite-based augmentation system, it is important to estimate ionospheric delay accurately to guarantee user's accuracy and integrity. Grid based ionospheric models are generally used to estimate ionospheric delay for SBAS. In grid based model, SBAS broadcasts vertical ionospheric delays at the grid point, and users get their ionospheric delay by interpolating those values. Ionospheric model based on spherical harmonics function is another method to estimate ionospheric delay. This is a function based approach and spherical harmonics function is a 2-D fourier series, containing the product of latitude dependent associated Legendre functions and the sum of the longitude dependent sine and cosine terms. Using ionospheric delay measurements, coefficients for each spherical harmonics functions are estimated. If these coefficients are known, user can reconstruct ionospheric delay. In this paper, we consider the spherical harmonics based model and propose a ionospheric delay estimation strategy for SBAS that can be used to mitigate ionospheric delay estimation error, especially in storm condition. First, coefficients are estimated under initial order and degree. Then residual errors for each measurement are modeled by higher order and degree terms, then coefficients for these terms are estimated. Because SBAS message capacity is limited, in normal condition, initial order terms are only used to estimate ionospheric delay. If ionospheric storm is detected and there is need to mitigate the error, higher order terms are also used and error can be decreased. To compare the accuracy of spherical harmonics based model with grid based model, some post-processing test results are presented. Raw observation data is obtained from RINEX format and the root mean square(RMS and max value of residual errors are presented.
A Joint Density Function in the Renewal Risk Model
Institute of Scientific and Technical Information of China (English)
XU HUAI; TANG LING; Wang De-hui
2013-01-01
In this paper,we consider a general expression for (Φ)(u,x,y),the joint density function of the surplus prior to ruin and the deficit at ruin when the initial surplus is u.In the renewal risk model,this density function is expressed in terms of the corresponding density function when the initial surplus is 0.In the compound Poisson risk process with phase-type claim size,we derive an explicit expression for (Φ)(u,x,y).Finally,we give a numerical example to illustrate the application of these results.
Controller design for TS models using delayed nonquadratic Lyapunov functions.
Lendek, Zsofia; Guerra, Thierry-Marie; Lauber, Jimmy
2015-03-01
In the last few years, nonquadratic Lyapunov functions have been more and more frequently used in the analysis and controller design for Takagi-Sugeno fuzzy models. In this paper, we developed relaxed conditions for controller design using nonquadratic Lyapunov functions and delayed controllers and give a general framework for the use of such Lyapunov functions. The two controller design methods developed in this framework outperform and generalize current state-of-the-art methods. The proposed methods are extended to robust and H∞ control and α -sample variation.
Distributed Global Function Model Finding for Wireless Sensor Network Data
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Song Deng
2016-01-01
Full Text Available Function model finding has become an important tool for analysis of data collected from wireless sensor networks (WSNs. With the development of WSNs, a large number of sensors have been widely deployed so that the collected data show the characteristics of distribution and mass. For distributed and massive sensor data, traditional centralized function model finding algorithms would lead to a significant decrease in performance. To solve this problem, this paper proposes a distributed global function model finding algorithm for wireless sensor network data (DGFMF-WSND. In DGFMF-WSND, on the basis of gene expression programming (GEP, an adaptive population generation strategy based on sub-population associated evolution is applied to improve the convergence speed of GEP. Secondly, to solve the generation of global function model in distributed wireless sensor networks data, this paper provides a global model generation algorithm based on unconstrained nonlinear least squares. Four representative datasets are used to evaluate the performance of the proposed algorithm. The comparative results show that the improved GEP with adaptive population generation strategy outperforms all other algorithms on the average convergence speed, time-consumption, value of R-square, and prediction accuracy. Meanwhile, experimental results also show that DGFMF-WSND has a clear advantage in terms of time-consumption and error of fitting. Moreover, with increasing of dataset size, DGFMF-WSND also demonstrates good speed-up ratio and scale-up ratio.
Hypnosis as a model of functional neurologic disorders.
Deeley, Q
2017-01-01
In the 19th century it was recognized that neurologic symptoms could be caused by "morbid ideation" as well as organic lesions. The subsequent observation that hysteric (now called "functional") symptoms could be produced and removed by hypnotic suggestion led Charcot to hypothesize that suggestion mediated the effects of ideas on hysteric symptoms through as yet unknown effects on brain activity. The advent of neuroimaging 100 years later revealed strikingly similar neural correlates in experiments matching functional symptoms with clinical analogs created by suggestion. Integrative models of suggested and functional symptoms regard these alterations in brain function as the endpoint of a broader set of changes in information processing due to suggestion. These accounts consider that suggestions alter experience by mobilizing representations from memory systems, and altering causal attributions, during preconscious processing which alters the content of what is provided to our highly edited subjective version of the world. Hypnosis as a model for functional symptoms draws attention to how radical alterations in experience and behavior can conform to the content of mental representations through effects on cognition and brain function. Experimental study of functional symptoms and their suggested counterparts in hypnosis reveals the distinct and shared processes through which this can occur.
A two phase harmonic model for left ventricular function
Dubi, S; Dubi, Y
2006-01-01
A minimal model for mechanical motion of the left ventricle is proposed. The model assumes the left ventricle to be a harmonic oscillator with two distinct phases, simulating the systolic and diastolic phases, at which both the amplitude and the elastic constant of the oscillator are different. Taking into account the pressure within the left ventricle, the model shows qualitative agreement with functional parameters of the left ventricle. The model allows for a natural explanation of heart failure with preserved systolic left ventricular function, also termed diastolic heart failure. Specifically, the rise in left ventricular filling pressures following increased left-ventricular wall stiffness is attributed to a mechanism aimed at preserving heart rate and cardiac output.
Quantum canonical tensor model and an exact wave function
Sasakura, Naoki
2013-01-01
Tensor models in various forms are being studied as models of quantum gravity. Among them the canonical tensor model has a canonical pair of rank-three tensors as dynamical variables, and is a pure constraint system with first-class constraints. The Poisson algebra of the first-class constraints has structure functions, and provides an algebraically consistent way of discretizing the Dirac first-class constraint algebra for general relativity. This paper successfully formulates the Wheeler-DeWitt scheme of quantization of the canonical tensor model; the ordering of operators in the constraints is determined without ambiguity by imposing Hermiticity and covariance on the constraints, and the commutation algebra of constraints takes essentially the same from as the classical Poisson algebra, i.e. is first-class. Thus one could consistently obtain, at least locally in the configuration space, wave functions of "universe" by solving the partial differential equations representing the constraints, i.e. the Wheeler...
Lyapunov functions for a dengue disease transmission model
Energy Technology Data Exchange (ETDEWEB)
Tewa, Jean Jules [Department of Mathematics, Faculty of Science, University of Yaounde I, P.O. Box 812, Yaounde (Cameroon)], E-mail: tewa@univ-metz.fr; Dimi, Jean Luc [Department of Mathematics, Faculty of Science, University Marien Ngouabi, P.O. Box 69, Brazzaville (Congo, The Democratic Republic of the)], E-mail: jldimi@yahoo.fr; Bowong, Samuel [Department of Mathematics and Computer Science, Faculty of Science, University of Douala, P.O. Box 24157, Douala (Cameroon)], E-mail: samuelbowong@yahoo.fr
2009-01-30
In this paper, we study a model for the dynamics of dengue fever when only one type of virus is present. For this model, Lyapunov functions are used to show that when the basic reproduction ratio is less than or equal to one, the disease-free equilibrium is globally asymptotically stable, and when it is greater than one there is an endemic equilibrium which is also globally asymptotically stable.
An integral representation of functions in gas-kinetic models
Perepelitsa, Misha
2016-08-01
Motivated by the theory of kinetic models in gas dynamics, we obtain an integral representation of lower semicontinuous functions on {{{R}}^d,} {d≥1}. We use the representation to study the problem of compactness of a family of the solutions of the discrete time BGK model for the compressible Euler equations. We determine sufficient conditions for strong compactness of moments of kinetic densities, in terms of the measures from their integral representations.
Functional imaging and modeling of the heart. Proceedings
Energy Technology Data Exchange (ETDEWEB)
Sachse, F.B. [Utah Univ., Salt Lake City, UT (United States). Nora Eccles Harrison Cardiovascular Research and Training Institute; Seemann, G. (eds.) [Karlsruhe Univ. (Germany). Inst. fuer Biomedizinische Technik
2007-07-01
Functional imaging and modeling constitute important research approaches to gaining insights into physiology and pathophysiology of the human heart. Applications of these approaches are promising to support clinical diagnosis and therapy of cardiac diseases, which are the most common cause of death in the western world and a major health problem in Asia. The book contains 48 contributions concerning the following topics: Imaging and image analysis, cardiac electrophysiology, electro- and magnetocardiography, cardiac mechanics and clinical applications, imaging and anatomic modeling.
Predicting plants -modeling traits as a function of environment
Franklin, Oskar
2016-04-01
A central problem in understanding and modeling vegetation dynamics is how to represent the variation in plant properties and function across different environments. Addressing this problem there is a strong trend towards trait-based approaches, where vegetation properties are functions of the distributions of functional traits rather than of species. Recently there has been enormous progress in in quantifying trait variability and its drivers and effects (Van Bodegom et al. 2012; Adier et al. 2014; Kunstler et al. 2015) based on wide ranging datasets on a small number of easily measured traits, such as specific leaf area (SLA), wood density and maximum plant height. However, plant function depends on many other traits and while the commonly measured trait data are valuable, they are not sufficient for driving predictive and mechanistic models of vegetation dynamics -especially under novel climate or management conditions. For this purpose we need a model to predict functional traits, also those not easily measured, and how they depend on the plants' environment. Here I present such a mechanistic model based on fitness concepts and focused on traits related to water and light limitation of trees, including: wood density, drought response, allocation to defense, and leaf traits. The model is able to predict observed patterns of variability in these traits in relation to growth and mortality, and their responses to a gradient of water limitation. The results demonstrate that it is possible to mechanistically predict plant traits as a function of the environment based on an eco-physiological model of plant fitness. References Adier, P.B., Salguero-Gómez, R., Compagnoni, A., Hsu, J.S., Ray-Mukherjee, J., Mbeau-Ache, C. et al. (2014). Functional traits explain variation in plant lifehistory strategies. Proc. Natl. Acad. Sci. U. S. A., 111, 740-745. Kunstler, G., Falster, D., Coomes, D.A., Hui, F., Kooyman, R.M., Laughlin, D.C. et al. (2015). Plant functional traits
Regional differences in prediction models of lung function in Germany
Directory of Open Access Journals (Sweden)
Schäper Christoph
2010-04-01
Full Text Available Abstract Background Little is known about the influencing potential of specific characteristics on lung function in different populations. The aim of this analysis was to determine whether lung function determinants differ between subpopulations within Germany and whether prediction equations developed for one subpopulation are also adequate for another subpopulation. Methods Within three studies (KORA C, SHIP-I, ECRHS-I in different areas of Germany 4059 adults performed lung function tests. The available data consisted of forced expiratory volume in one second, forced vital capacity and peak expiratory flow rate. For each study multivariate regression models were developed to predict lung function and Bland-Altman plots were established to evaluate the agreement between predicted and measured values. Results The final regression equations for FEV1 and FVC showed adjusted r-square values between 0.65 and 0.75, and for PEF they were between 0.46 and 0.61. In all studies gender, age, height and pack-years were significant determinants, each with a similar effect size. Regarding other predictors there were some, although not statistically significant, differences between the studies. Bland-Altman plots indicated that the regression models for each individual study adequately predict medium (i.e. normal but not extremely high or low lung function values in the whole study population. Conclusions Simple models with gender, age and height explain a substantial part of lung function variance whereas further determinants add less than 5% to the total explained r-squared, at least for FEV1 and FVC. Thus, for different adult subpopulations of Germany one simple model for each lung function measures is still sufficient.
Energy Technology Data Exchange (ETDEWEB)
Sumida, S. [U-shin Ltd., Tokyo (Japan); Nagamatsu, M.; Maruyama, K. [Hokkaido Institute of Technology, Sapporo (Japan); Hiramatsu, S. [Mazda Motor Corp., Hiroshima (Japan)
1997-10-01
A new approach on modeling is put forward in order to compose the virtual prototype which is indispensable for fully computer integrated concurrent development of automobile product. A basic concept of the hierarchical functional model is proposed as the concrete form of this new modeling technology. This model is used mainly for explaining and simulating functions and efficiencies of both the parts and the total product of automobile. All engineers who engage themselves in design and development of automobile can collaborate with one another using this model. Some application examples are shown, and usefulness of this model is demonstrated. 5 refs., 5 figs.
Directory of Open Access Journals (Sweden)
Solomencevs Artūrs
2016-05-01
Full Text Available The approach called “Topological Functioning Model for Software Engineering” (TFM4SE applies the Topological Functioning Model (TFM for modelling the business system in the context of Model Driven Architecture. TFM is a mathematically formal computation independent model (CIM. TFM4SE is compared to an approach that uses BPMN as a CIM. The comparison focuses on CIM modelling and on transformation to UML Sequence diagram on the platform independent (PIM level. The results show the advantages and drawbacks the formalism of TFM brings into the development.
Regulator Loss Functions and Hierarchical Modeling for Safety Decision Making.
Hatfield, Laura A; Baugh, Christine M; Azzone, Vanessa; Normand, Sharon-Lise T
2017-07-01
Regulators must act to protect the public when evidence indicates safety problems with medical devices. This requires complex tradeoffs among risks and benefits, which conventional safety surveillance methods do not incorporate. To combine explicit regulator loss functions with statistical evidence on medical device safety signals to improve decision making. In the Hospital Cost and Utilization Project National Inpatient Sample, we select pediatric inpatient admissions and identify adverse medical device events (AMDEs). We fit hierarchical Bayesian models to the annual hospital-level AMDE rates, accounting for patient and hospital characteristics. These models produce expected AMDE rates (a safety target), against which we compare the observed rates in a test year to compute a safety signal. We specify a set of loss functions that quantify the costs and benefits of each action as a function of the safety signal. We integrate the loss functions over the posterior distribution of the safety signal to obtain the posterior (Bayes) risk; the preferred action has the smallest Bayes risk. Using simulation and an analysis of AMDE data, we compare our minimum-risk decisions to a conventional Z score approach for classifying safety signals. The 2 rules produced different actions for nearly half of hospitals (45%). In the simulation, decisions that minimize Bayes risk outperform Z score-based decisions, even when the loss functions or hierarchical models are misspecified. Our method is sensitive to the choice of loss functions; eliciting quantitative inputs to the loss functions from regulators is challenging. A decision-theoretic approach to acting on safety signals is potentially promising but requires careful specification of loss functions in consultation with subject matter experts.
Function-weighted frequency response function sensitivity method for analytical model updating
Lin, R. M.
2017-09-01
Since the frequency response function (FRF) sensitivity method was first proposed [26], it has since become a most powerful and practical method for analytical model updating. Nevertheless, the original formulation of the FRF sensitivity method does suffer the limitation that the initial analytical model to be updated should be reasonably close to the final updated model to be sought, due the assumed mathematical first order approximation implicit to most sensitivity based methods. Convergence to correct model is not guaranteed when large modelling errors exist and blind application often leads to optimal solutions which are truly sought. This paper seeks to examine all the important numerical characteristics of the original FRF sensitivity method including frequency data selection, numerical balance and convergence performance. To further improve the applicability of the method to cases of large modelling errors, a new novel function-weighted sensitivity method is developed. The new method has shown much superior performance on convergence even in the presence of large modelling errors. Extensive numerical case studies based on a mass-spring system and a GARTEUR structure have been conducted and very encouraging results have been achieved. Effect of measurement noise has been examined and the method works reasonably well in the presence of measurement uncertainties. The new method removes the restriction of modelling error magnitude being of second order in Euclidean norm as compared with that of system matrices, thereby making it a truly general method applicable to most practical model updating problems.
Functional response models to estimate feeding rates of wading birds
Collazo, J.A.; Gilliam, J.F.; Miranda-Castro, L.
2010-01-01
Forager (predator) abundance may mediate feeding rates in wading birds. Yet, when modeled, feeding rates are typically derived from the purely prey-dependent Holling Type II (HoII) functional response model. Estimates of feeding rates are necessary to evaluate wading bird foraging strategies and their role in food webs; thus, models that incorporate predator dependence warrant consideration. Here, data collected in a mangrove swamp in Puerto Rico in 1994 were reanalyzed, reporting feeding rates for mixed-species flocks after comparing fits of the HoII model, as used in the original work, to the Beddington-DeAngelis (BD) and Crowley-Martin (CM) predator-dependent models. Model CM received most support (AIC c wi = 0.44), but models BD and HoII were plausible alternatives (AIC c ??? 2). Results suggested that feeding rates were constrained by predator abundance. Reductions in rates were attributed to interference, which was consistent with the independently observed increase in aggression as flock size increased (P rates. However, inferences derived from the HoII model, as used in the original work, were sound. While Holling's Type II and other purely prey-dependent models have fostered advances in wading bird foraging ecology, evaluating models that incorporate predator dependence could lead to a more adequate description of data and processes of interest. The mechanistic bases used to derive models used here lead to biologically interpretable results and advance understanding of wading bird foraging ecology.
Park, Yu Rang; Lee, Hye Won; Cho, Sung Bum; Kim, Ju Han
2007-01-01
The development of functional genomics including transcriptomics, proteomics and metabolomics allow us to monitor a large number of key cellular pathways simultaneously. Several technology-specific data models have been introduced for the representation of functional genomics experimental data, including the MicroArray Gene Expression-Object Model (MAGE-OM), the Proteomics Experiment Data Repository (PEDRo), and the Tissue MicroArray-Object Model (TMA-OM). Despite the increasing number of cancer studies using multiple functional genomics technologies, there is still no integrated data model for multiple functional genomics experimental and clinical data. We propose an object-oriented data model for cancer genomics research, Cancer Genomics Object Model (CaGe-OM). We reference four data models: Functional Genomic-Object Model, MAGE-OM, TMAOM and PEDRo. The clinical and histopathological information models are created by analyzing cancer management workflow and referencing the College of American Pathology Cancer Protocols and National Cancer Institute Common Data Elements. The CaGe-OM provides a comprehensive data model for integrated storage and analysis of clinical and multiple functional genomics data.
Synthetic self-assembled models with biomimetic functions
Fiammengo, Roberto; Crego-Calama, Mercedes; Reinhoudt, David N.
2001-01-01
Self-assembly can be considered a powerful tool in the hand of chemists for the understanding, modeling and mimicking of biological systems. The possibility of reproducing biological functions in synthetic systems obtained by self-assembly is envisioned as a modest but very important step towards th
Predicting functional brain ROIs via fiber shape models.
Zhang, Tuo; Guo, Lei; Li, Kaiming; Zhu, Dajing; Cui, Guangbin; Liu, Tianming
2011-01-01
Study of structural and functional connectivities of the human brain has received significant interest and effort recently. A fundamental question arises when attempting to measure the structural and/or functional connectivities of specific brain networks: how to best identify possible Regions of Interests (ROIs)? In this paper, we present a novel ROI prediction framework that localizes ROIs in individual brains based on learned fiber shape models from multimodal task-based fMRI and diffusion tensor imaging (DTI) data. In the training stage, ROIs are identified as activation peaks in task-based fMRI data. Then, shape models of white matter fibers emanating from these functional ROIs are learned. In addition, ROIs' location distribution model is learned to be used as an anatomical constraint. In the prediction stage, functional ROIs are predicted in individual brains based on DTI data. The ROI prediction is formulated and solved as an energy minimization problem, in which the two learned models are used as energy terms. Our experiment results show that the average ROI prediction error is 3.45 mm, in comparison with the benchmark data provided by working memory task-based fMRI. Promising results were also obtained on the ADNI-2 longitudinal DTI dataset.
Kostka polynomials and energy functions in solvable lattice models
Nakayashiki, A; Nakayashiki, Atsushi; Yamada, Yasuhiko
1995-01-01
The relation between the charge of Lascoux-Schuzenberger and the energy function in solvable lattice models is clarified. As an application, A.N.Kirillov's conjecture on the expression of the branching coefficient of {\\widehat {sl_n}}/{sl_n} as a limit of Kostka polynomials is proved.
From dynamics to structure and function of model biomolecular systems
Fontaine-Vive-Curtaz, F.
2007-01-01
The purpose of this thesis was to extend recent works on structure and dynamics of hydrogen bonded crystals to model biomolecular systems and biological processes. The tools that we have used are neutron scattering (NS) and density functional theory (DFT) and force field (FF) based simulation method
Functional ingredient production: application of global metabolic models
Smid, E.J.; Molenaar, D.; Hugenholtz, J.; Vos, de W.M.; Teusink, B.
2005-01-01
The biotechnology industry continuously explores new ways to improve the performance of microbial strains in fermentation processes. Recent focus has been on new genome-wide modelling approaches in functional genomics, which aim to take full advantage of genome sequence data, transcription profiling
Structural and functional models for [NiFe] hydrogenase
Angamuthu, Raja
2009-01-01
The main goal of the research presented in this thesis is the synthesis of suitable structural and functional models for the enzyme [NiFe] hydrogenase, which can reduce protons into dihydrogen. A brief survey of the roles of all the known nickel containing enzymes in biological systems with a focus
Functional Integrals and Collective Excitations in Boson-Fermion Model
Institute of Scientific and Technical Information of China (English)
YAN Jun
2006-01-01
In this paper, collective excitations in the boson-fermion model are investigated by means of functional integration method. The equations of energy gap and excitation spectrum are derived. Moreover, the Bose energy spectrum of zero wave vector Fermi fields is also calculated.
Gene Discovery and Functional Analyses in the Model Plant Arabidopsis
Institute of Scientific and Technical Information of China (English)
Cai-Ping Feng; John Mundy
2006-01-01
The present mini-review describes newer methods and strategies, including transposon and T-DNA insertions,TILLING, Deleteagene, and RNA interference, to functionally analyze genes of interest in the model plant Arabidopsis. The relative advantages and disadvantages of the systems are also discussed.
Gene Discovery and Functional Analyses in the Model Plant Arabidopsis
DEFF Research Database (Denmark)
Feng, Cai-ping; Mundy, J.
2006-01-01
The present mini-review describes newer methods and strategies, including transposon and T-DNA insertions, TILLING, Deleteagene, and RNA interference, to functionally analyze genes of interest in the model plant Arabidopsis. The relative advantages and disadvantages of the systems are also...
On matrix model partition functions for QCD with chemical potential
Akemann, G; Vernizzi, G
2004-01-01
Partition functions of two different matrix models for QCD with chemical potential are computed for an arbitrary number of quark and complex conjugate anti-quark flavors. In the large-N limit of weak nonhermiticity complete agreement is found between the two models. This supports the universality of such fermionic partition functions, that is of products of characteristic polynomials in the complex plane. In the strong nonhermiticity limit agreement is found for an equal number of quark and conjugate flavours. For a general flavor content the equality of partition functions holds only for small chemical potential. The chiral phase transition is analyzed for an arbitrary number of quarks, where the free energy presents a discontinuity of first order at a critical chemical potential. In the case of nondegenerate flavors there is first order phase transition for each separate mass scale.
Baryon Wave Functions in Covariant Relativistic Quark Models
Dillig, M
2002-01-01
We derive covariant baryon wave functions for arbitrary Lorentz boosts. Modeling baryons as quark-diquark systems, we reduce their manifestly covariant Bethe-Salpeter equation to a covariant 3-dimensional form by projecting on the relative quark-diquark energy. Guided by a phenomenological multigluon exchange representation of a covariant confining kernel, we derive for practical applications explicit solutions for harmonic confinement and for the MIT Bag Model. We briefly comment on the interplay of boosts and center-of-mass corrections in relativistic quark models.
Development on electromagnetic impedance function modeling and its estimation
Energy Technology Data Exchange (ETDEWEB)
Sutarno, D., E-mail: Sutarno@fi.itb.ac.id [Earth Physics and Complex System Division Faculty of Mathematics and Natural Sciences Institut Teknologi Bandung (Indonesia)
2015-09-30
Today the Electromagnetic methods such as magnetotellurics (MT) and controlled sources audio MT (CSAMT) is used in a broad variety of applications. Its usefulness in poor seismic areas and its negligible environmental impact are integral parts of effective exploration at minimum cost. As exploration was forced into more difficult areas, the importance of MT and CSAMT, in conjunction with other techniques, has tended to grow continuously. However, there are obviously important and difficult problems remaining to be solved concerning our ability to collect process and interpret MT as well as CSAMT in complex 3D structural environments. This talk aim at reviewing and discussing the recent development on MT as well as CSAMT impedance functions modeling, and also some improvements on estimation procedures for the corresponding impedance functions. In MT impedance modeling, research efforts focus on developing numerical method for computing the impedance functions of three dimensionally (3-D) earth resistivity models. On that reason, 3-D finite elements numerical modeling for the impedances is developed based on edge element method. Whereas, in the CSAMT case, the efforts were focused to accomplish the non-plane wave problem in the corresponding impedance functions. Concerning estimation of MT and CSAMT impedance functions, researches were focused on improving quality of the estimates. On that objective, non-linear regression approach based on the robust M-estimators and the Hilbert transform operating on the causal transfer functions, were used to dealing with outliers (abnormal data) which are frequently superimposed on a normal ambient MT as well as CSAMT noise fields. As validated, the proposed MT impedance modeling method gives acceptable results for standard three dimensional resistivity models. Whilst, the full solution based modeling that accommodate the non-plane wave effect for CSAMT impedances is applied for all measurement zones, including near-, transition
Bessel functions in mass action modeling of memories and remembrances
Energy Technology Data Exchange (ETDEWEB)
Freeman, Walter J. [Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720-3206 (United States); Capolupo, Antonio [Dipartimento di Fisica, E.R. Caianiello Universitá di Salerno, and INFN Gruppo collegato di Salerno, Fisciano 84084 (Italy); Kozma, Robert [Department of Mathematics, Memphis University, Memphis, TN 38152 (United States); Olivares del Campo, Andrés [The Blackett Laboratory, Imperial College London, Prince Consort Road, London SW7 2BZ (United Kingdom); Vitiello, Giuseppe, E-mail: vitiello@sa.infn.it [Dipartimento di Fisica, E.R. Caianiello Universitá di Salerno, and INFN Gruppo collegato di Salerno, Fisciano 84084 (Italy)
2015-10-02
Data from experimental observations of a class of neurological processes (Freeman K-sets) present functional distribution reproducing Bessel function behavior. We model such processes with couples of damped/amplified oscillators which provide time dependent representation of Bessel equation. The root loci of poles and zeros conform to solutions of K-sets. Some light is shed on the problem of filling the gap between the cellular level dynamics and the brain functional activity. Breakdown of time-reversal symmetry is related with the cortex thermodynamic features. This provides a possible mechanism to deduce lifetime of recorded memory. - Highlights: • We consider data from observations of impulse responses of cortex to electric shocks. • These data are fitted by Bessel functions which may be represented by couples of damped/amplified oscillators. • We study the data by using couples of damped/amplified oscillators. • We discuss lifetime and other properties of the considered brain processes.
Universality of Correlation Functions in Random Matrix Models of QCD
Jackson, A D; Verbaarschot, J J M
1997-01-01
We demonstrate the universality of the spectral correlation functions of a QCD inspired random matrix model that consists of a random part having the chiral structure of the QCD Dirac operator and a deterministic part which describes a schematic temperature dependence. We calculate the correlation functions analytically using the technique of Itzykson-Zuber integrals for arbitrary complex super-matrices. An alternative exact calculation for arbitrary matrix size is given for the special case of zero temperature, and we reproduce the well-known Laguerre kernel. At finite temperature, the microscopic limit of the correlation functions are calculated in the saddle point approximation. The main result of this paper is that the microscopic universality of correlation functions is maintained even though unitary invariance is broken by the addition of a deterministic matrix to the ensemble.
How to Maximize the Likelihood Function for a DSGE Model
DEFF Research Database (Denmark)
Andreasen, Martin Møller
This paper extends two optimization routines to deal with objective functions for DSGE models. The optimization routines are i) a version of Simulated Annealing developed by Corana, Marchesi & Ridella (1987), and ii) the evolutionary algorithm CMA-ES developed by Hansen, Müller & Koumoutsakos (2003......). Following these extensions, we examine the ability of the two routines to maximize the likelihood function for a sequence of test economies. Our results show that the CMA- ES routine clearly outperforms Simulated Annealing in its ability to find the global optimum and in efficiency. With 10 unknown...... structural parameters in the likelihood function, the CMA-ES routine finds the global optimum in 95% of our test economies compared to 89% for Simulated Annealing. When the number of unknown structural parameters in the likelihood function increases to 20 and 35, then the CMA-ES routine finds the global...
Functional Somatic Syndromes: Emerging Biomedical Models and Traditional Chinese Medicine
Directory of Open Access Journals (Sweden)
Steven Tan
2004-01-01
Full Text Available The so-called functional somatic syndromes comprise a group of disorders that are primarily symptom-based, multisystemic in presentation and probably involve alterations in mind-brain-body interactions. The emerging neurobiological models of allostasis/allostatic load and of the emotional motor system show striking similarities with concepts used by Traditional Chinese Medicine (TCM to understand the functional somatic disorders and their underlying pathogenesis. These models incorporate a macroscopic perspective, accounting for the toll of acute and chronic traumas, physical and emotional stressors and the complex interactions between the mind, brain and body. The convergence of these biomedical models with the ancient paradigm of TCM may provide a new insight into scientifically verifiable diagnostic and therapeutic approaches for these common disorders.
ING function in apoptosis in diverse model systems.
Shah, Sitar; Smith, Heather; Feng, Xiaolan; Rancourt, Derrick E; Riabowol, Karl
2009-02-01
Genetic studies in model organisms have shown that programmed cell death (apoptosis) plays a significant role during development, where a deficiency in apoptosis results in severe and diverse diseases. Dysregulation of apoptosis also contributes to a variety of human diseases, such as cancer and autoimmune diseases. ING family proteins (ING1-ING5) are involved in many cellular processes, and appear to play a significant role in apoptosis. Loss or downregulation of ING protein function is frequently observed in different tumour types, many of which are resistant to apoptosis, thus warranting their classification as type II tumour suppressors. Several different in vitro and in vivo models have explored the role of ING proteins in regulating apoptosis. In this review, we discuss the progress that has been made in understanding ING protein function in apoptosis using in vitro studies and Mus musculus, Xenopus laevis, and Caenorhabditis elegans experimental models, with an emphasis on ING1 and ING3.
Future of Plant Functional Types in Terrestrial Biosphere Models
Wullschleger, S. D.; Euskirchen, E. S.; Iversen, C. M.; Rogers, A.; Serbin, S.
2015-12-01
Earth system models describe the physical, chemical, and biological processes that govern our global climate. While it is difficult to single out one component as being more important than another in these sophisticated models, terrestrial vegetation is a critical player in the biogeochemical and biophysical dynamics of the Earth system. There is much debate, however, as to how plant diversity and function should be represented in these models. Plant functional types (PFTs) have been adopted by modelers to represent broad groupings of plant species that share similar characteristics (e.g. growth form) and roles (e.g. photosynthetic pathway) in ecosystem function. In this review the PFT concept is traced from its origin in the early 1800s to its current use in regional and global dynamic vegetation models (DVMs). Special attention is given to the representation and parameterization of PFTs and to validation and benchmarking of predicted patterns of vegetation distribution in high-latitude ecosystems. These ecosystems are sensitive to changing climate and thus provide a useful test case for model-based simulations of past, current, and future distribution of vegetation. Models that incorporate the PFT concept predict many of the emerging patterns of vegetation change in tundra and boreal forests, given known processes of tree mortality, treeline migration, and shrub expansion. However, representation of above- and especially belowground traits for specific PFTs continues to be problematic. Potential solutions include developing trait databases and replacing fixed parameters for PFTs with formulations based on trait co-variance and empirical trait-environment relationships. Surprisingly, despite being important to land-atmosphere interactions of carbon, water, and energy, PFTs such as moss and lichen are largely absent from DVMs. Close collaboration among those involved in modelling with the disciplines of taxonomy, biogeography, ecology, and remote sensing will be
Reducing equifinality of hydrological models by integrating Functional Streamflow Disaggregation
Lüdtke, Stefan; Apel, Heiko; Nied, Manuela; Carl, Peter; Merz, Bruno
2014-05-01
A universal problem of the calibration of hydrological models is the equifinality of different parameter sets derived from the calibration of models against total runoff values. This is an intrinsic problem stemming from the quality of the calibration data and the simplified process representation by the model. However, discharge data contains additional information which can be extracted by signal processing methods. An analysis specifically developed for the disaggregation of runoff time series into flow components is the Functional Streamflow Disaggregation (FSD; Carl & Behrendt, 2008). This method is used in the calibration of an implementation of the hydrological model SWIM in a medium sized watershed in Thailand. FSD is applied to disaggregate the discharge time series into three flow components which are interpreted as base flow, inter-flow and surface runoff. In addition to total runoff, the model is calibrated against these three components in a modified GLUE analysis, with the aim to identify structural model deficiencies, assess the internal process representation and to tackle equifinality. We developed a model dependent (MDA) approach calibrating the model runoff components against the FSD components, and a model independent (MIA) approach comparing the FSD of the model results and the FSD of calibration data. The results indicate, that the decomposition provides valuable information for the calibration. Particularly MDA highlights and discards a number of standard GLUE behavioural models underestimating the contribution of soil water to river discharge. Both, MDA and MIA yield to a reduction of the parameter ranges by a factor up to 3 in comparison to standard GLUE. Based on these results, we conclude that the developed calibration approach is able to reduce the equifinality of hydrological model parameterizations. The effect on the uncertainty of the model predictions is strongest by applying MDA and shows only minor reductions for MIA. Besides
A propositional representation model of anatomical and functional brain data.
Maturana, Pablo; Batrancourt, Bénédicte
2011-01-01
Networks can represent a large number of systems. Recent advances in the domain of networks have been transferred to the field of neuroscience. For example, the graph model has been used in neuroscience research as a methodological tool to examine brain networks organization, topology and complex dynamics, as well as a framework to test the structure-function hypothesis using neuroimaging data. In the current work we propose a graph-theoretical framework to represent anatomical, functional and neuropsychological assessment instruments information. On the one hand, interrelationships between anatomic elements constitute an anatomical graph. On the other hand, a functional graph contains several cognitive functions and their more elementary cognitive processes. Finally, the neuropsychological assessment instruments graph includes several neuropsychological tests and scales linked with their different sub-tests and variables. The two last graphs are connected by relations of type "explore" linking a particular instrument with the cognitive function it explores. We applied this framework to a sample of patients with focal brain damage. Each patient was related to: (i) the cerebral entities injured (assessed with structural neuroimaging data) and (ii) the neusopsychological assessment tests carried out (weight by performance). Our model offers a suitable platform to visualize patients' relevant information, facilitating the representation, standardization and sharing of clinical data. At the same time, the integration of a large number of patients in this framework will make possible to explore relations between anatomy (injured entities) and function (performance in different tests assessing different cognitive functions) and the use of neurocomputational tools for graph analysis may help diagnostic and contribute to the comprehension of neural bases of cognitive functions.
Function modeling improves the efficiency of spatial modeling using big data from remote sensing
John Hogland; Nathaniel Anderson
2017-01-01
Spatial modeling is an integral component of most geographic information systems (GISs). However, conventional GIS modeling techniques can require substantial processing time and storage space and have limited statistical and machine learning functionality. To address these limitations, many have parallelized spatial models using multiple coding libraries and have...
A Comparison of Functional Models for Use in the Function-Failure Design Method
Stock, Michael E.; Stone, Robert B.; Tumer, Irem Y.
2006-01-01
When failure analysis and prevention, guided by historical design knowledge, are coupled with product design at its conception, shorter design cycles are possible. By decreasing the design time of a product in this manner, design costs are reduced and the product will better suit the customer s needs. Prior work indicates that similar failure modes occur with products (or components) with similar functionality. To capitalize on this finding, a knowledge base of historical failure information linked to functionality is assembled for use by designers. One possible use for this knowledge base is within the Elemental Function-Failure Design Method (EFDM). This design methodology and failure analysis tool begins at conceptual design and keeps the designer cognizant of failures that are likely to occur based on the product s functionality. The EFDM offers potential improvement over current failure analysis methods, such as FMEA, FMECA, and Fault Tree Analysis, because it can be implemented hand in hand with other conceptual design steps and carried throughout a product s design cycle. These other failure analysis methods can only truly be effective after a physical design has been completed. The EFDM however is only as good as the knowledge base that it draws from, and therefore it is of utmost importance to develop a knowledge base that will be suitable for use across a wide spectrum of products. One fundamental question that arises in using the EFDM is: At what level of detail should functional descriptions of components be encoded? This paper explores two approaches to populating a knowledge base with actual failure occurrence information from Bell 206 helicopters. Functional models expressed at various levels of detail are investigated to determine the necessary detail for an applicable knowledge base that can be used by designers in both new designs as well as redesigns. High level and more detailed functional descriptions are derived for each failed component based
Testing galaxy formation models with galaxy stellar mass functions
Lim, Seunghwan; Lan, Ting-Wen; Ménard, Brice
2016-01-01
We compare predictions of a number of empirical models and numerical simulations of galaxy formation to the conditional stellar mass functions (CSMF) of galaxies in groups of different masses obtained recently by Lan et al. to test how well different models accommodate the data. Among all the models considered, only the model of Lu et al. can match the observational data; all other models fail to reproduce the faint-end upturn seen in the observation. The CSMFs are used to update the halo-based empirical model of Lu et al., and the model parameters obtained are very similar to those inferred by Lu et al. from a completely different set of observational constraints. The observational data clearly prefer a model in which star formation in low-mass halos changes behavior at a characteristic redshift $z_c \\sim 2$. There is also tentative evidence that this characteristic redshift depends on environments, becoming $z_c \\sim 4$ in regions that eventually evolve into rich clusters of galaxies. The constrained model ...
Cheng, Longlong; Zhang, Guangju; Wan, Baikun; Hao, Linlin; Qi, Hongzhi; Ming, Dong
2009-01-01
Functional electrical stimulation (FES) has been widely used in the area of neural engineering. It utilizes electrical current to activate nerves innervating extremities affected by paralysis. An effective combination of a traditional PID controller and a neural network, being capable of nonlinear expression and adaptive learning property, supply a more reliable approach to construct FES controller that help the paraplegia complete the action they want. A FES system tuned by Radial Basis Function (RBF) Neural Network-based Proportional-Integral-Derivative (PID) model was designed to control the knee joint according to the desired trajectory through stimulation of lower limbs muscles in this paper. Experiment result shows that the FES system with RBF Neural Network-based PID model get a better performance when tracking the preset trajectory of knee angle comparing with the system adjusted by Ziegler- Nichols tuning PID model.
A new algebraic transition model based on stress length function
Xiao, Meng-Juan; She, Zhen-Su
2016-11-01
Transition, as one of the two biggest challenges in turbulence research, is of critical importance for engineering application. For decades, the fundamental research seems to be unable to capture the quantitative details in real transition process. On the other hand, numerous empirical parameters in engineering transition models provide no unified description of the transition under varying physical conditions. Recently, we proposed a symmetry-based approach to canonical wall turbulence based on stress length function, which is here extended to describe the transition via a new algebraic transition model. With a multi-layer analytic form of the stress length function in both the streamwise and wall normal directions, the new model gives rise to accurate description of the mean field and friction coefficient, comparing with both the experimental and DNS results at different inlet conditions. Different types of transition process, such as the transition with varying incoming turbulence intensities or that with blow and suck disturbance, are described by only two or three model parameters, each of which has their own specific physical interpretation. Thus, the model enables one to extract physical information from both experimental and DNS data to reproduce the transition process, which may prelude to a new class of generalized transition model for engineering applications.
Prostaglandin signaling suppresses beneficial microglial function in Alzheimer's disease models.
Johansson, Jenny U; Woodling, Nathaniel S; Wang, Qian; Panchal, Maharshi; Liang, Xibin; Trueba-Saiz, Angel; Brown, Holden D; Mhatre, Siddhita D; Loui, Taylor; Andreasson, Katrin I
2015-01-01
Microglia, the innate immune cells of the CNS, perform critical inflammatory and noninflammatory functions that maintain normal neural function. For example, microglia clear misfolded proteins, elaborate trophic factors, and regulate and terminate toxic inflammation. In Alzheimer's disease (AD), however, beneficial microglial functions become impaired, accelerating synaptic and neuronal loss. Better understanding of the molecular mechanisms that contribute to microglial dysfunction is an important objective for identifying potential strategies to delay progression to AD. The inflammatory cyclooxygenase/prostaglandin E2 (COX/PGE2) pathway has been implicated in preclinical AD development, both in human epidemiology studies and in transgenic rodent models of AD. Here, we evaluated murine models that recapitulate microglial responses to Aβ peptides and determined that microglia-specific deletion of the gene encoding the PGE2 receptor EP2 restores microglial chemotaxis and Aβ clearance, suppresses toxic inflammation, increases cytoprotective insulin-like growth factor 1 (IGF1) signaling, and prevents synaptic injury and memory deficits. Our findings indicate that EP2 signaling suppresses beneficial microglia functions that falter during AD development and suggest that inhibition of the COX/PGE2/EP2 immune pathway has potential as a strategy to restore healthy microglial function and prevent progression to AD.
System identification and model reduction using modulating function techniques
Shen, Yan
1993-01-01
Weighted least squares (WLS) and adaptive weighted least squares (AWLS) algorithms are initiated for continuous-time system identification using Fourier type modulating function techniques. Two stochastic signal models are examined using the mean square properties of the stochastic calculus: an equation error signal model with white noise residuals, and a more realistic white measurement noise signal model. The covariance matrices in each model are shown to be banded and sparse, and a joint likelihood cost function is developed which links the real and imaginary parts of the modulated quantities. The superior performance of above algorithms is demonstrated by comparing them with the LS/MFT and popular predicting error method (PEM) through 200 Monte Carlo simulations. A model reduction problem is formulated with the AWLS/MFT algorithm, and comparisons are made via six examples with a variety of model reduction techniques, including the well-known balanced realization method. Here the AWLS/MFT algorithm manifests higher accuracy in almost all cases, and exhibits its unique flexibility and versatility. Armed with this model reduction, the AWLS/MFT algorithm is extended into MIMO transfer function system identification problems. The impact due to the discrepancy in bandwidths and gains among subsystem is explored through five examples. Finally, as a comprehensive application, the stability derivatives of the longitudinal and lateral dynamics of an F-18 aircraft are identified using physical flight data provided by NASA. A pole-constrained SIMO and MIMO AWLS/MFT algorithm is devised and analyzed. Monte Carlo simulations illustrate its high-noise rejecting properties. Utilizing the flight data, comparisons among different MFT algorithms are tabulated and the AWLS is found to be strongly favored in almost all facets.
Multidimensional Model of Disability and Role Functioning in Rheumatoid Arthritis.
Ormseth, Sarah R; Draper, Taylor L; Irwin, Michael R; Weisman, Michael H; Aréchiga, Adam E; Hartoonian, Narineh; Bui, Thuy; Nicassio, Perry M
2015-12-01
To examine a model addressing the roles of rheumatoid arthritis (RA) disease burden, mood disturbance, and disability as determinants of impairments in role functioning. In a cross-sectional design, 103 RA patients recruited from the community to participate in a clinical trial completed assessments of self-assessed disease burden (total joint pain and disease activity), mood disturbance (Center for Epidemiological Studies Depression Scale depressed mood, somatic symptoms, lack of positive affect, and interpersonal problems), disability (Health Assessment Questionnaire disability index gross and fine motor), and role functioning (Short Form 36 health survey physical and social). Structural equation modeling (SEM) was used to examine direct and indirect mechanisms linking disease burden to role functioning. SEM results indicated that the model had excellent fit: S-Bχ(2)(30) = 38.59, P = 0.135; comparative fit index = 0.977, standardized root mean residual = 0.062, and root mean square error of approximation = 0.053. Mediational analyses demonstrated that, while disease burden was associated with poor role functioning, its effects were jointly mediated by mood disturbance and disability. After the effects of mood disturbance and disability were taken into account, the effect of disease burden on role functioning was not significant. The results indicate that mood disturbance and disability may serve as important pathways through which RA disease burden affects role functioning. Future longitudinal research is suggested to replicate these findings and further explore the mediational mechanisms examined in this study. © 2015, American College of Rheumatology.
The Schroedinger functional for Gross-Neveu models
Energy Technology Data Exchange (ETDEWEB)
Leder, B.
2007-04-18
Gross-Neveu type models with a finite number of fermion flavours are studied on a two-dimensional Euclidean space-time lattice. The models are asymptotically free and are invariant under a chiral symmetry. These similarities to QCD make them perfect benchmark systems for fermion actions used in large scale lattice QCD computations. The Schroedinger functional for the Gross-Neveu models is defined for both, Wilson and Ginsparg-Wilson fermions, and shown to be renormalisable in 1-loop lattice perturbation theory. In two dimensions four fermion interactions of the Gross-Neveu models have dimensionless coupling constants. The symmetry properties of the four fermion interaction terms and the relations among them are discussed. For Wilson fermions chiral symmetry is explicitly broken and additional terms must be included in the action. Chiral symmetry is restored up to cut-off effects by tuning the bare mass and one of the couplings. The critical mass and the symmetry restoring coupling are computed to second order in lattice perturbation theory. This result is used in the 1-loop computation of the renormalised couplings and the associated beta-functions. The renormalised couplings are defined in terms of suitable boundary-to-boundary correlation functions. In the computation the known first order coefficients of the beta-functions are reproduced. One of the couplings is found to have a vanishing betafunction. The calculation is repeated for the recently proposed Schroedinger functional with exact chiral symmetry, i.e. Ginsparg-Wilson fermions. The renormalisation pattern is found to be the same as in the Wilson case. Using the regularisation dependent finite part of the renormalised couplings, the ratio of the Lambda-parameters is computed. (orig.)
Neural Network Hydrological Modelling: Linear Output Activation Functions?
Abrahart, R. J.; Dawson, C. W.
2005-12-01
The power to represent non-linear hydrological processes is of paramount importance in neural network hydrological modelling operations. The accepted wisdom requires non-polynomial activation functions to be incorporated in the hidden units such that a single tier of hidden units can thereafter be used to provide a 'universal approximation' to whatever particular hydrological mechanism or function is of interest to the modeller. The user can select from a set of default activation functions, or in certain software packages, is able to define their own function - the most popular options being logistic, sigmoid and hyperbolic tangent. If a unit does not transform its inputs it is said to possess a 'linear activation function' and a combination of linear activation functions will produce a linear solution; whereas the use of non-linear activation functions will produce non-linear solutions in which the principle of superposition does not hold. For hidden units, speed of learning and network complexities are important issues. For the output units, it is desirable to select an activation function that is suited to the distribution of the target values: e.g. binary targets (logistic); categorical targets (softmax); continuous-valued targets with a bounded range (logistic / tanh); positive target values with no known upper bound (exponential; but beware of overflow); continuous-valued targets with no known bounds (linear). It is also standard practice in most hydrological applications to use the default software settings and to insert a set of identical non-linear activation functions in the hidden layer and output layer processing units. Mixed combinations have nevertheless been reported in several hydrological modelling papers and the full ramifications of such activities requires further investigation and assessment i.e. non-linear activation functions in the hidden units connected to linear or clipped-linear activation functions in the output unit. There are two
Molecular modeling of mechanosensory ion channel structural and functional features.
Gessmann, Renate; Kourtis, Nikos; Petratos, Kyriacos; Tavernarakis, Nektarios
2010-09-16
The DEG/ENaC (Degenerin/Epithelial Sodium Channel) protein family comprises related ion channel subunits from all metazoans, including humans. Members of this protein family play roles in several important biological processes such as transduction of mechanical stimuli, sodium re-absorption and blood pressure regulation. Several blocks of amino acid sequence are conserved in DEG/ENaC proteins, but structure/function relations in this channel class are poorly understood. Given the considerable experimental limitations associated with the crystallization of integral membrane proteins, knowledge-based modeling is often the only route towards obtaining reliable structural information. To gain insight into the structural characteristics of DEG/ENaC ion channels, we derived three-dimensional models of MEC-4 and UNC-8, based on the available crystal structures of ASIC1 (Acid Sensing Ion Channel 1). MEC-4 and UNC-8 are two DEG/ENaC family members involved in mechanosensation and proprioception respectively, in the nematode Caenorhabditis elegans. We used these models to examine the structural effects of specific mutations that alter channel function in vivo. The trimeric MEC-4 model provides insight into the mechanism by which gain-of-function mutations cause structural alterations that result in increased channel permeability, which trigger cell degeneration. Our analysis provides an introductory framework to further investigate the multimeric organization of the DEG/ENaC ion channel complex.
Molecular modeling of mechanosensory ion channel structural and functional features.
Directory of Open Access Journals (Sweden)
Renate Gessmann
Full Text Available The DEG/ENaC (Degenerin/Epithelial Sodium Channel protein family comprises related ion channel subunits from all metazoans, including humans. Members of this protein family play roles in several important biological processes such as transduction of mechanical stimuli, sodium re-absorption and blood pressure regulation. Several blocks of amino acid sequence are conserved in DEG/ENaC proteins, but structure/function relations in this channel class are poorly understood. Given the considerable experimental limitations associated with the crystallization of integral membrane proteins, knowledge-based modeling is often the only route towards obtaining reliable structural information. To gain insight into the structural characteristics of DEG/ENaC ion channels, we derived three-dimensional models of MEC-4 and UNC-8, based on the available crystal structures of ASIC1 (Acid Sensing Ion Channel 1. MEC-4 and UNC-8 are two DEG/ENaC family members involved in mechanosensation and proprioception respectively, in the nematode Caenorhabditis elegans. We used these models to examine the structural effects of specific mutations that alter channel function in vivo. The trimeric MEC-4 model provides insight into the mechanism by which gain-of-function mutations cause structural alterations that result in increased channel permeability, which trigger cell degeneration. Our analysis provides an introductory framework to further investigate the multimeric organization of the DEG/ENaC ion channel complex.
Information gating: an evolutionary model of personality function and dysfunction.
Nash, W P
1998-01-01
Utilizing principles of evolutionary biology, a model is developed which defines the essential adaptive functions of personality as a whole, and describes how failure in those functions produces the maladaptations characteristic of personality disorders. In this model, personality is hypothesized to have evolved specifically to make human culture possible by managing the flow of information within the culture, especially by mediating teaching and learning, competition and cooperation, and leading and following. These essential culture-forming capacities of personality have at their root the more basic function of information gating, which is defined here as the continuous regulation by personality of its openness for the bidirectional flow of sensory, cognitive, emotional, and motor information between internal self and external social systems, to best meet the needs of both in various situations. The maladaptations characteristic of personality disorders are postulated to be due to their being chronically and frequently too open or too closed for expressing or assimilating social information, given their circumstances. The relationship of this model to other evolutionary models of personality is discussed, as are its clinical and research implications.
Photonic encryption : modeling and functional analysis of all optical logic.
Energy Technology Data Exchange (ETDEWEB)
Tang, Jason D.; Schroeppel, Richard Crabtree; Robertson, Perry J.
2004-10-01
With the build-out of large transport networks utilizing optical technologies, more and more capacity is being made available. Innovations in Dense Wave Division Multiplexing (DWDM) and the elimination of optical-electrical-optical conversions have brought on advances in communication speeds as we move into 10 Gigabit Ethernet and above. Of course, there is a need to encrypt data on these optical links as the data traverses public and private network backbones. Unfortunately, as the communications infrastructure becomes increasingly optical, advances in encryption (done electronically) have failed to keep up. This project examines the use of optical logic for implementing encryption in the photonic domain to achieve the requisite encryption rates. This paper documents the innovations and advances of work first detailed in 'Photonic Encryption using All Optical Logic,' [1]. A discussion of underlying concepts can be found in SAND2003-4474. In order to realize photonic encryption designs, technology developed for electrical logic circuits must be translated to the photonic regime. This paper examines S-SEED devices and how discrete logic elements can be interconnected and cascaded to form an optical circuit. Because there is no known software that can model these devices at a circuit level, the functionality of S-SEED devices in an optical circuit was modeled in PSpice. PSpice allows modeling of the macro characteristics of the devices in context of a logic element as opposed to device level computational modeling. By representing light intensity as voltage, 'black box' models are generated that accurately represent the intensity response and logic levels in both technologies. By modeling the behavior at the systems level, one can incorporate systems design tools and a simulation environment to aid in the overall functional design. Each black box model takes certain parameters (reflectance, intensity, input response), and models the optical ripple
Coupled vibro-acoustic model updating using frequency response functions
Nehete, D. V.; Modak, S. V.; Gupta, K.
2016-03-01
Interior noise in cavities of motorized vehicles is of increasing significance due to the lightweight design of these structures. Accurate coupled vibro-acoustic FE models of such cavities are required so as to allow a reliable design and analysis. It is, however, experienced that the vibro-acoustic predictions using these models do not often correlate acceptably well with the experimental measurements and hence require model updating. Both the structural and the acoustic parameters addressing the stiffness as well as the damping modeling inaccuracies need to be considered simultaneously in the model updating framework in order to obtain an accurate estimate of these parameters. It is also noted that the acoustic absorption properties are generally frequency dependent. This makes use of modal data based methods for updating vibro-acoustic FE models difficult. In view of this, the present paper proposes a method based on vibro-acoustic frequency response functions that allow updating of a coupled FE model by considering simultaneously the parameters associated with both the structural as well as the acoustic model of the cavity. The effectiveness of the proposed method is demonstrated through numerical studies on a 3D rectangular box cavity with a flexible plate. Updating parameters related to the material property, stiffness of joints between the plate and the rectangular cavity and the properties of absorbing surfaces of the acoustic cavity are considered. The robustness of the method under presence of noise is also studied.
APP physiological and pathophysiological functions:insights from animal models
Institute of Scientific and Technical Information of China (English)
Qinxi Guo; Zilai Wang; Hongmei Li; Mary Wiese; Hui Zheng
2012-01-01
The amyloid precursor protein (APP) has been under intensive study in recent years,mainly due to its critical role in the pathogenesis of Alzheimer's disease (AD).β-Amyloid (Aβ) peptides generated from APP proteolytic cleavage can aggregate,leading to plaque formation in human AD brains.Point mutations of APP affecting Aβ production are found to be causal for hereditary early onset familial AD.It is very likely that elucidating the physiological properties of APP will greatly facilitate the understanding of its role in AD pathogenesis.A number of APP loss- and gainof-function models have been established in model organisms including Caenorhabditis elegans,Drosophila,zebrafish and mouse.These in vivo models provide us valuable insights into APP physiological functions.In addition,several knock-in mouse models expressing mutant APP at a physiological level are available to allow us to study AD pathogenesis without APP overexpression.This article will review the current physiological and pathophysiological animal models of APP.
Modeling of sensor function for piezoelectric bender elements
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
An analytical sandwich beam model for piezoelectric bender elements is derived based on the first-order shear deformation theory (FSDT), which assumes a single rotation angle for the whole cross-section and a quadratic distribution for coupled electric potential in piezoelectric layers. Shear coefficient is introduced to correct the effect of transverse shear strain on shear force and the electric displacement integration. Static and free vibration analyses of simply-supported bender elements are carried out for the sensor function. The results illustrate the high accuracy of the present model compared with the exact 2D solutions.
Estimating Stochastic Volatility Models using Prediction-based Estimating Functions
DEFF Research Database (Denmark)
Lunde, Asger; Brix, Anne Floor
In this paper prediction-based estimating functions (PBEFs), introduced in Sørensen (2000), are reviewed and PBEFs for the Heston (1993) stochastic volatility model are derived. The finite sample performance of the PBEF based estimator is investigated in a Monte Carlo study, and compared to the p......In this paper prediction-based estimating functions (PBEFs), introduced in Sørensen (2000), are reviewed and PBEFs for the Heston (1993) stochastic volatility model are derived. The finite sample performance of the PBEF based estimator is investigated in a Monte Carlo study, and compared...... to the performance of the GMM estimator based on conditional moments of integrated volatility from Bollerslev and Zhou (2002). The case where the observed log-price process is contaminated by i.i.d. market microstructure (MMS) noise is also investigated. First, the impact of MMS noise on the parameter estimates from...
Probability Distribution Function of Passive Scalars in Shell Models
Institute of Scientific and Technical Information of China (English)
LIU Chun-Ping; ZHANG Xiao-Qiang; LIU Yu-Rong; WANG Guang-Rui; HE Da-Ren; CHEN Shi-Gang; ZHU Lu-Jin
2008-01-01
A shell-model version of passive scalar problem is introduced, which is inspired by the model of K. Ohkitani and M. Yakhot [K. Ohkitani and M. Yakhot, Phys. Rev. Lett. 60 (1988) 983; K. Ohkitani and M. Yakhot, Prog. Theor. Phys. 81 (1988) 329]. As in the original problem, the prescribed random velocity field is Gaussian and 5 correlated in time. Deterministic differential equations are regarded as nonlinear Langevin equation. Then, the Fokker-Planck equations of PDF for passive scalars axe obtained and solved numerically. In energy input range (n < 5, n is the shell number.), the probability distribution function (PDF) of passive scalars is near the Gaussian distribution. In inertial range (5 < n < 16) and dissipation range (n ≥ 17), the probability distribution function (PDF) of passive scalars has obvious intermittence. And the scaling power of passive scalar is anomalous. The results of numerical simulations are compared with experimental measurements.
Model of local temperature changes in brain upon functional activation.
Collins, Christopher M; Smith, Michael B; Turner, Robert
2004-12-01
Experimental results for changes in brain temperature during functional activation show large variations. It is, therefore, desirable to develop a careful numerical model for such changes. Here, a three-dimensional model of temperature in the human head using the bioheat equation, which includes effects of metabolism, perfusion, and thermal conduction, is employed to examine potential temperature changes due to functional activation in brain. It is found that, depending on location in brain and corresponding baseline temperature relative to blood temperature, temperature may increase or decrease on activation and concomitant increases in perfusion and rate of metabolism. Changes in perfusion are generally seen to have a greater effect on temperature than are changes in metabolism, and hence active brain is predicted to approach blood temperature from its initial temperature. All calculated changes in temperature for reasonable physiological parameters have magnitudes <0.12 degrees C and are well within the range reported in recent experimental studies involving human subjects.
Potts model partition functions on two families of fractal lattices
Gong, Helin; Jin, Xian'an
2014-11-01
The partition function of q-state Potts model, or equivalently the Tutte polynomial, is computationally intractable for regular lattices. The purpose of this paper is to compute partition functions of q-state Potts model on two families of fractal lattices. Based on their self-similar structures and by applying the subgraph-decomposition method, we divide their Tutte polynomials into two summands, and for each summand we obtain a recursive formula involving the other summand. As a result, the number of spanning trees and their asymptotic growth constants, and a lower bound of the number of connected spanning subgraphs or acyclic root-connected orientations for each of such two lattices are obtained.
Modeling and Reconstruction of Mixed Functional and Molecular Patterns
Directory of Open Access Journals (Sweden)
2006-01-01
Full Text Available Functional medical imaging promises powerful tools for the visualization and elucidation of important disease-causing biological processes in living tissue. Recent research aims to dissect the distribution or expression of multiple biomarkers associated with disease progression or response, where the signals often represent a composite of more than one distinct source independent of spatial resolution. Formulating the task as a blind source separation or composite signal factorization problem, we report here a statistically principled method for modeling and reconstruction of mixed functional or molecular patterns. The computational algorithm is based on a latent variable model whose parameters are estimated using clustered component analysis. We demonstrate the principle and performance of the approaches on the breast cancer data sets acquired by dynamic contrast-enhanced magnetic resonance imaging.
Functional connectivity mapping using the ferromagnetic Potts spin model.
Stanberry, Larissa; Murua, Alejandro; Cordes, Dietmar
2008-04-01
An unsupervised stochastic clustering method based on the ferromagnetic Potts spin model is introduced as a powerful tool to determine functionally connected regions. The method provides an intuitively simple approach to clustering and makes no assumptions of the number of clusters in the data or their underlying distribution. The performance of the method and its dependence on the intrinsic parameters (size of the neighborhood, form of the interaction term, etc.) is investigated on the simulated data and real fMRI data acquired during a conventional periodic finger tapping task. The merits of incorporating Euclidean information into the connectivity analysis are discussed. The ability of the Potts model clustering to uncover the hidden structure in the complex data is demonstrated through its application to the resting-state data to determine functional connectivity networks of the anterior and posterior cingulate cortices for the group of nine healthy male subjects. (c) 2007 Wiley-Liss, Inc.
Modeling of state parameter and hardening function for granular materials
Institute of Scientific and Technical Information of China (English)
彭芳乐; 李建中
2004-01-01
A modified plastic strain energy as hardening state parameter for dense sand was proposed, based on the results from a series of drained plane strain tests on saturated dense Japanese Toyoura sand with precise stress and strain measurements along many stress paths. In addition, a unique hardening function between the plastic strain energy and the instantaneous stress path was also presented, which was independent of stress history. The proposed state parameter and hardening function was directly verified by the simple numerical integration method. It is shown that the proposed hardening function is independent of stress history and stress path and is appropriate to be used as the hardening rule in constitutive modeling for dense sand, and it is also capable of simulating the effects on the deformation characteristics of stress history and stress path for dense sand.
PGO models in the envelope function and effective mass approximations
Paulescu, M.; Tulcan-Paulescu, E.; Gravila, P.
2011-03-01
A recipe to design quantum devices that exhibit the theoretical pseudo-Gaussian oscillator electronic states properties is given. The algorithm is described en detail and is illustrated by the computation of a Mn x Cd1- x Te ternary alloy pseudo-Gaussian heterostructure. The numerical procedure reaches beyond of pseudo-Gaussian models and can be used for designing epitaxial growth devices with desired electronic states structure. The calculations are carried out in the envelope function and effective mass approximations.
Structure and Function of a Nonruminant Gut: A Porcine Model
DEFF Research Database (Denmark)
Tajima, Kiyoshi; Aminov, Rustam
2015-01-01
In many aspects, the anatomical, physiological, and microbial diversity features of the ruminant gut are different from that of the monogastric animals. Thus, the main aim of this chapter is to give a comparative overview of the structure and function of the gastrointestinal tract of a nonruminan...... gut; (iv) effects of various feed additives including antibiotics, phages, probiotics, and prebiotics on pigs; and (v) the use of the porcine model in translational medicine....
Modeling the allosteric modulation of CCR5 function by Maraviroc.
Lagane, Bernard; Garcia-Perez, Javier; Kellenberger, Esther
2013-01-01
Maraviroc is a non-peptidic, low molecular weight CC chemokine receptor 5 (CCR5) ligand that has recently been marketed for the treatment of HIV infected individuals. This review discusses recent molecular modeling studies of CCR5 by homology to CXC chemokine receptor 4, their contribution to the understanding of the allosteric mode of action of the inhibitor and their potential for the development of future drugs with improved efficiency and preservation of CCR5 biological functions.
Product Representation of Dyon Partition Function in CHL Models
David, J R; Sen, A; David, Justin R.; Jatkar, Dileep P.; Sen, Ashoke
2006-01-01
A formula for the exact partition function of 1/4 BPS dyons in a class of CHL models has been proposed earlier. The formula involves inverse of Siegel modular forms of subgroups of Sp(2,Z). In this paper we propose product formulae for these modular forms. This generalizes the result of Gritsenko and Nikulin for the weight 10 cusp form of the full Sp(2,Z) group.
Product representation of dyon partition function in CHL models
David, Justin R.; Jatkar, Dileep P.; Sen, Ashoke
2006-06-01
A formula for the exact partition function of 1/4 BPS dyons in a class of CHL models has been proposed earlier. The formula involves inverse of Siegel modular forms of subgroups of Sp(2,Bbb Z). In this paper we propose product formulae for these modular forms. This generalizes the result of Borcherds and Gritsenko and Nikulin for the weight 10 cusp form of the full Sp(2,Bbb Z) group.
Wave functions in SUSY cosmological models with matter
Energy Technology Data Exchange (ETDEWEB)
Ortiz, C. [Instituto de Fisica de la Universidad de Guanajuato, A.P. E-143, C.P. 37150, Leon, Guanajuato (Mexico); Rosales, J.J. [Facultad de Ingenieria Mecanica Electrica y Electronica, Universidad de Guanajuato, Prolongacion Tampico 912, Bellavista, Salamanca, Guanajuato (Mexico); Socorro, J. [Instituto de Fisica de la Universidad de Guanajuato, A.P. E-143, C.P. 37150, Leon, Guanajuato (Mexico)]. E-mail: socorro@fisica.ugto.mx; Torres, J. [Instituto de Fisica de la Universidad de Guanajuato, A.P. E-143, C.P. 37150, Leon, Guanajuato (Mexico); Tkach, V.I. [Instituto de Fisica de la Universidad de Guanajuato, A.P. E-143, C.P. 37150, Leon, Guanajuato (Mexico)
2005-06-06
In this work we consider the n=2 supersymmetric superfield approach for the FRW cosmological model and the corresponding term of matter content, perfect fluid with barotropic state equation p={gamma}{rho}. We are able to obtain a normalizable wave function (at zero energy) of the universe. Besides, the mass parameter spectrum is found for the closed FRW case in the Schrodinger picture, being similar to those obtained by other methods, using a black hole system.
Modeling Marine Electromagnetic Survey with Radial Basis Function Networks
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Agus Arif
2014-11-01
Full Text Available A marine electromagnetic survey is an engineering endeavour to discover the location and dimension of a hydrocarbon layer under an ocean floor. In this kind of survey, an array of electric and magnetic receivers are located on the sea floor and record the scattered, refracted and reflected electromagnetic wave, which has been transmitted by an electric dipole antenna towed by a vessel. The data recorded in receivers must be processed and further analysed to estimate the hydrocarbon location and dimension. To conduct those analyses successfuly, a radial basis function (RBF network could be employed to become a forward model of the input-output relationship of the data from a marine electromagnetic survey. This type of neural networks is working based on distances between its inputs and predetermined centres of some basis functions. A previous research had been conducted to model the same marine electromagnetic survey using another type of neural networks, which is a multi layer perceptron (MLP network. By comparing their validation and training performances (mean-squared errors and correlation coefficients, it is concluded that, in this case, the MLP network is comparatively better than the RBF network[1].[1] This manuscript is an extended version of our previous paper, entitled Radial Basis Function Networks for Modeling Marine Electromagnetic Survey, which had been presented on 2011 International Conference on Electrical Engineering and Informatics, 17-19 July 2011, Bandung, Indonesia.
A Mathematical Modeling Framework for Analysis of Functional Clothing
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Xiaolin Man
2007-11-01
Full Text Available In the analysis and design of functional clothing systems, it is helpful to quantify the effects of a system on a wearer’s physical performance capabilities. Toward this end, a clothing modeling framework for quantifying the mechanical interactions between a given clothing system design and a specific wearer performing defined physical tasks is proposed. The modeling framework consists of three interacting modules: (1 a macroscale fabric mechanics/dynamics model; (2 a collision detection and contact correction module; and (3 a human motion module. In the proposed framework, the macroscopic fabric model is based on a rigorous large deformation continuum-degenerated shell theory representation. Material models that capture the stress-strain behavior of different clothing fabrics are used in the continuum shell framework. The collision and contact module enforces the impenetrability constraint between the fabric and human body and computes the associated contact forces between the two. The human body is represented in the current framework as an assemblage of overlapping ellipsoids that undergo rigid body motions consistent with human motions while performing actions such as walking, running, or jumping. The transient rigid body motions of each ellipsoidal body segment in time are determined using motion capture technology. The integrated modeling framework is then exercised to quantify the resistance that the clothing exerts on the wearer during the specific activities under consideration. Current results from the framework are presented and its intended applications are discussed along with some of the key challenges remaining in clothing system modeling.
Confronting species distribution model predictions with species functional traits.
Wittmann, Marion E; Barnes, Matthew A; Jerde, Christopher L; Jones, Lisa A; Lodge, David M
2016-02-01
Species distribution models are valuable tools in studies of biogeography, ecology, and climate change and have been used to inform conservation and ecosystem management. However, species distribution models typically incorporate only climatic variables and species presence data. Model development or validation rarely considers functional components of species traits or other types of biological data. We implemented a species distribution model (Maxent) to predict global climate habitat suitability for Grass Carp (Ctenopharyngodon idella). We then tested the relationship between the degree of climate habitat suitability predicted by Maxent and the individual growth rates of both wild (N = 17) and stocked (N = 51) Grass Carp populations using correlation analysis. The Grass Carp Maxent model accurately reflected the global occurrence data (AUC = 0.904). Observations of Grass Carp growth rate covered six continents and ranged from 0.19 to 20.1 g day(-1). Species distribution model predictions were correlated (r = 0.5, 95% CI (0.03, 0.79)) with observed growth rates for wild Grass Carp populations but were not correlated (r = -0.26, 95% CI (-0.5, 0.012)) with stocked populations. Further, a review of the literature indicates that the few studies for other species that have previously assessed the relationship between the degree of predicted climate habitat suitability and species functional traits have also discovered significant relationships. Thus, species distribution models may provide inferences beyond just where a species may occur, providing a useful tool to understand the linkage between species distributions and underlying biological mechanisms.
Biomechanical considerations in the modeling of muscle function.
Andrews, J G; Hay, J G
1983-09-01
The instantaneous functional role of a voluntary muscle in the neighborhood of a joint is often described in clinical terms (e.g. flexor; abductor; external rotator; agonist; contracting concentrically and isokinetically) that seen sufficiently explicit and clear in certain simple situations, but have not yet been carefully defined in precise biomechanical terminology for the general case. In order to describe the functional role of a voluntary muscle as its acts to change and/or maintain the configuration of a joint, it is necessary to make certain modeling assumptions. These include modeling the joint, modeling the muscle force line of action in the joint neighborhood, and establishing the location and orientation of the three joint axes for all possible joint configurations. Modeling the joint as a point leads to simple and sensible definitions which are consistent with clinical practice. The straight line model is most conveniently used to establish the muscle force line of action. A RHO coordinate system embedded in the distal joint segment with origin at the joint center point, and with intersecting axes coincident with the F/E, A/A and I/XR axes when the joint is in the anatomical position, is the joint coordinate system of choice to describe the turning effects of the muscle about the joint. Sensible and simple biomechanical definitions for clinical terms describing muscular contractions (i.e. concentric; eccentric; isometric; isokinetic; isotonic) were presented and appear to be relatively uncontroversial. Alternative biomechanical definitions for agonistic and antagonistic muscular activity were also presented, as were arguments for choosing a simple definition based on using the joint resultant moment as the criterion measure relative to which the individual muscle's moment about J should be compared. Biomechanical definitions for determining when a muscle functions as a joint flexor or extensor, abductor or adductor, and internal or external rotator
Colour-independent partition functions in coloured vertex models
Energy Technology Data Exchange (ETDEWEB)
Foda, O., E-mail: omar.foda@unimelb.edu.au [Dept. of Mathematics and Statistics, University of Melbourne, Parkville, VIC 3010 (Australia); Wheeler, M., E-mail: mwheeler@lpthe.jussieu.fr [Laboratoire de Physique Théorique et Hautes Energies, CNRS UMR 7589 (France); Université Pierre et Marie Curie – Paris 6, 4 place Jussieu, 75252 Paris cedex 05 (France)
2013-06-11
We study lattice configurations related to S{sub n}, the scalar product of an off-shell state and an on-shell state in rational A{sub n} integrable vertex models, n∈{1,2}. The lattice lines are colourless and oriented. The state variables are n conserved colours that flow along the line orientations, but do not necessarily cover every bond in the lattice. Choosing boundary conditions such that the positions where the colours flow into the lattice are fixed, and where they flow out are summed over, we show that the partition functions of these configurations, with these boundary conditions, are n-independent. Our results extend to trigonometric A{sub n} models, and to all n. This n-independence explains, in vertex-model terms, results from recent studies of S{sub 2} (Caetano and Vieira, 2012, [1], Wheeler, (arXiv:1204.2089), [2]). Namely, 1.S{sub 2}, which depends on two sets of Bethe roots, {b_1} and {b_2}, and cannot (as far as we know) be expressed in single determinant form, degenerates in the limit {b_1}→∞, and/or {b_2}→∞, into a product of determinants, 2. Each of the latter determinants is an A{sub 1} vertex-model partition function.
Modeling of Functional Properties of Porous Shape Memory Alloy
Directory of Open Access Journals (Sweden)
Volkov Aleksandr E.
2015-01-01
Full Text Available A model accounting for the microstructure of porous TiNi shape memory alloy samples fabricated by self-propagating high temperature synthesis has been proposed for simulation of their functional-mechanical properties. Structural elements of a porous sample have been approximated by curved beams. An analysis of shapes and sizes of pores and ligaments permitted to identify characteristic sizes of the beams. A mathematical object consisting of rigidly connected small curve beams has been considered. The stress-strain state of a beam was estimated by the classical methods of strength of materials. The microstructural model was used for calculation of the phase deformation of the shape memory material. Simulation of stress-strain curves and phase deformation of a porous TiNi sample on cooling and heating under a constant stress has shown a good correspondence between the experimental data and the results of modeling.
Plant lessons: exploring ABCB functionality through structural modeling
Directory of Open Access Journals (Sweden)
Aurélien eBailly
2012-01-01
Full Text Available In contrast to mammalian ABCB1 proteins, narrow substrate specificity has been extensively documented for plant orthologs shown to catalyze the transport of the plant hormone, auxin. Using the crystal structures of the multidrug exporters Sav1866 and MmABCB1 as templates, we have developed structural models of plant ABCB proteins with a common architecture. Comparisons of these structures identified kingdom-specific candidate substrate-binding regions within the translocation chamber formed by the transmembrane domains of ABCBs from the model plant Arabidopsis. These results suggest an early evolutionary divergence of plant and mammalian ABCBs. Validation of these models becomes a priority for efforts to elucidate ABCB function and manipulate this class of transporters to enhance plant productivity and quality.
Preliminary Functional-Structural Modeling on Poplar (Salicaceae)
Liu, Dongxiang; Letort, Véronique; Xing, Meijun; Gang, Yang; Huang, Xinyuan; Cao, Weiqun
2010-01-01
Poplar is one of the best fast-growing trees in the world, widely used for windbreak and wood product. Although architecture of poplar has direct impact on its applications, it has not been descried in previous poplar models, probably because of the difficulties raised by measurement, data processing and parameterization. In this paper, the functional-structural model GreenLab is calibrated by using poplar data of 3, 4, 5, 6 years old. The data was acquired by simplifying measurement. The architecture was also simplified by classifying the branches into several types (physiological age) using clustering analysis, which decrease the number of parameters. By multi-fitting the sampled data of each tree, the model parameters were identified and the plant architectures at different tree ages were simulated.
A marked correlation function for constraining modified gravity models
White, Martin
2016-01-01
Future large scale structure surveys will provide increasingly tight constraints on our cosmological model. These surveys will report results on the distance scale and growth rate of perturbations through measurements of Baryon Acoustic Oscillations and Redshift-Space Distortions. It is interesting to ask: what further analyses should become routine, so as to test as-yet-unknown models of cosmic acceleration? Models which aim to explain the accelerated expansion rate of the Universe by modifications to General Relativity often invoke screening mechanisms which can imprint a non-standard density dependence on their predictions. This suggests density-dependent clustering as a `generic' constraint. This paper argues that a density-marked correlation function provides a density-dependent statistic which is easy to compute and report and requires minimal additional infrastructure beyond what is routinely available to such survey analyses. We give one realization of this idea and study it using low order perturbati...
Control of Weierstrass-Mandelbrot Function Model with Morlet Wavelets
Zhang, Li; Liu, Shutang; Yu, Chenglong
A Weierstrass-Mandelbrot function (WMF) model with Morlet wavelets is investigated. Its control relationships are derived quantitatively after proving the convergence of the controlled WMF model. Based on these relationships, it is shown that the scope of the WMF series increases with three parameters of the Morlet wavelets. But other parameters have opposite effect on the scope of the series. The results of simulated examples demonstrate the effectiveness of the control method. Moreover, two statistical characteristics of the series are obtained as the parameters change: One is multifractality of the series of the controlled WMF model, and the other is the Hurst exponent whose value stands for the long-time memory effect on the series.
Model parameters for representative wetland plant functional groups
Williams, Amber S.; Kiniry, James R.; Mushet, David M.; Smith, Loren M.; McMurry, Scott T.; Attebury, Kelly; Lang, Megan; McCarty, Gregory W.; Shaffer, Jill A.; Effland, William R.; Johnson, Mari-Vaughn V.
2017-01-01
Wetlands provide a wide variety of ecosystem services including water quality remediation, biodiversity refugia, groundwater recharge, and floodwater storage. Realistic estimation of ecosystem service benefits associated with wetlands requires reasonable simulation of the hydrology of each site and realistic simulation of the upland and wetland plant growth cycles. Objectives of this study were to quantify leaf area index (LAI), light extinction coefficient (k), and plant nitrogen (N), phosphorus (P), and potassium (K) concentrations in natural stands of representative plant species for some major plant functional groups in the United States. Functional groups in this study were based on these parameters and plant growth types to enable process-based modeling. We collected data at four locations representing some of the main wetland regions of the United States. At each site, we collected on-the-ground measurements of fraction of light intercepted, LAI, and dry matter within the 2013–2015 growing seasons. Maximum LAI and k variables showed noticeable variations among sites and years, while overall averages and functional group averages give useful estimates for multisite simulation modeling. Variation within each species gives an indication of what can be expected in such natural ecosystems. For P and K, the concentrations from highest to lowest were spikerush (Eleocharis macrostachya), reed canary grass (Phalaris arundinacea), smartweed (Polygonum spp.), cattail (Typha spp.), and hardstem bulrush (Schoenoplectus acutus). Spikerush had the highest N concentration, followed by smartweed, bulrush, reed canary grass, and then cattail. These parameters will be useful for the actual wetland species measured and for the wetland plant functional groups they represent. These parameters and the associated process-based models offer promise as valuable tools for evaluating environmental benefits of wetlands and for evaluating impacts of various agronomic practices in
Allometric functional response model: body masses constrain interaction strengths.
Vucic-Pestic, Olivera; Rall, Björn C; Kalinkat, Gregor; Brose, Ulrich
2010-01-01
1. Functional responses quantify the per capita consumption rates of predators depending on prey density. The parameters of these nonlinear interaction strength models were recently used as successful proxies for predicting population dynamics, food-web topology and stability. 2. This study addressed systematic effects of predator and prey body masses on the functional response parameters handling time, instantaneous search coefficient (attack coefficient) and a scaling exponent converting type II into type III functional responses. To fully explore the possible combinations of predator and prey body masses, we studied the functional responses of 13 predator species (ground beetles and wolf spiders) on one small and one large prey resulting in 26 functional responses. 3. We found (i) a power-law decrease of handling time with predator mass with an exponent of -0.94; (ii) an increase of handling time with prey mass (power-law with an exponent of 0.83, but only three prey sizes were included); (iii) a hump-shaped relationship between instantaneous search coefficients and predator-prey body-mass ratios; and (iv) low scaling exponents for low predator-prey body mass ratios in contrast to high scaling exponents for high predator-prey body-mass ratios. 4. These scaling relationships suggest that nonlinear interaction strengths can be predicted by knowledge of predator and prey body masses. Our results imply that predators of intermediate size impose stronger per capita top-down interaction strengths on a prey than smaller or larger predators. Moreover, the stability of population and food-web dynamics should increase with increasing body-mass ratios in consequence of increases in the scaling exponents. 5. Integrating these scaling relationships into population models will allow predicting energy fluxes, food-web structures and the distribution of interaction strengths across food web links based on knowledge of the species' body masses.
Adaptive cyclic physiologic noise modeling and correction in functional MRI.
Beall, Erik B
2010-03-30
Physiologic noise in BOLD-weighted MRI data is known to be a significant source of the variance, reducing the statistical power and specificity in fMRI and functional connectivity analyses. We show a dramatic improvement on current noise correction methods in both fMRI and fcMRI data that avoids overfitting. The traditional noise model is a Fourier series expansion superimposed on the periodicity of parallel measured breathing and cardiac cycles. Correction using this model results in removal of variance matching the periodicity of the physiologic cycles. Using this framework allows easy modeling of noise. However, using a large number of regressors comes at the cost of removing variance unrelated to physiologic noise, such as variance due to the signal of functional interest (overfitting the data). It is our hypothesis that there are a small variety of fits that describe all of the significantly coupled physiologic noise. If this is true, we can replace a large number of regressors used in the model with a smaller number of the fitted regressors and thereby account for the noise sources with a smaller reduction in variance of interest. We describe these extensions and demonstrate that we can preserve variance in the data unrelated to physiologic noise while removing physiologic noise equivalently, resulting in data with a higher effective SNR than with current corrections techniques. Our results demonstrate a significant improvement in the sensitivity of fMRI (up to a 17% increase in activation volume for fMRI compared with higher order traditional noise correction) and functional connectivity analyses.
Linearization models for parabolic dynamical systems via Abel's functional equation
Elin, Mark; Reich, Simeon; Shoikhet, David
2009-01-01
We study linearization models for continuous one-parameter semigroups of parabolic type. In particular, we introduce new limit schemes to obtain solutions of Abel's functional equation and to study asymptotic behavior of such semigroups. The crucial point is that these solutions are univalent functions convex in one direction. In a parallel direction, we find analytic conditions which determine certain geometric properties of those functions, such as the location of their images in either a half-plane or a strip, and their containing either a half-plane or a strip. In the context of semigroup theory these geometric questions may be interpreted as follows: is a given one-parameter continuous semigroup either an outer or an inner conjugate of a group of automorphisms? In other words, the problem is finding a fractional linear model of the semigroup which is defined by a group of automorphisms of the open unit disk. Our results enable us to establish some new important analytic and geometric characteristics of t...
Obtaining and Visualization of the Topological Functioning Model from the UML Model
Directory of Open Access Journals (Sweden)
Ovchinnikova Viktoria
2015-12-01
Full Text Available A domain model can provide compact information about its corresponding software system for business people. If the software system exists without its domain model and documentation it is time-consuming to understand its behavior and structure only from the code. Reverse Engineering (RE tools can be used for obtaining behavior and structure of the software system from source code. After that the domain model can be created. A short overview and an example of obtaining the domain model, Topological Functioning Model (TFM, from source code are provided in the paper. Positive and negative effects of the process of TFM backward derivation are also discussed.
Stress field models from Maxwell stress functions: southern California
Bird, Peter
2017-08-01
The lithospheric stress field is formally divided into three components: a standard pressure which is a function of elevation (only), a topographic stress anomaly (3-D tensor field) and a tectonic stress anomaly (3-D tensor field). The boundary between topographic and tectonic stress anomalies is somewhat arbitrary, and here is based on the modeling tools available. The topographic stress anomaly is computed by numerical convolution of density anomalies with three tensor Green's functions provided by Boussinesq, Cerruti and Mindlin. By assuming either a seismically estimated or isostatic Moho depth, and by using Poisson ratio of either 0.25 or 0.5, I obtain four alternative topographic stress models. The tectonic stress field, which satisfies the homogeneous quasi-static momentum equation, is obtained from particular second derivatives of Maxwell vector potential fields which are weighted sums of basis functions representing constant tectonic stress components, linearly varying tectonic stress components and tectonic stress components that vary harmonically in one, two and three dimensions. Boundary conditions include zero traction due to tectonic stress anomaly at sea level, and zero traction due to the total stress anomaly on model boundaries at depths within the asthenosphere. The total stress anomaly is fit by least squares to both World Stress Map data and to a previous faulted-lithosphere, realistic-rheology dynamic model of the region computed with finite-element program Shells. No conflict is seen between the two target data sets, and the best-fitting model (using an isostatic Moho and Poisson ratio 0.5) gives minimum directional misfits relative to both targets. Constraints of computer memory, execution time and ill-conditioning of the linear system (which requires damping) limit harmonically varying tectonic stress to no more than six cycles along each axis of the model. The primary limitation on close fitting is that the Shells model predicts very sharp
Exact Maps in Density Functional Theory for Lattice Models
Dimitrov, Tanja; Fuks, Johanna I; Rubio, Angel
2015-01-01
In the present work, we employ exact diagonalization for model systems on a real-space lattice to explicitly construct the exact density-to-potential and for the first time the exact density-to-wavefunction map that underly the Hohenberg-Kohn theorem in density functional theory. Having the explicit wavefunction-to- density map at hand, we are able to construct arbitrary observables as functionals of the ground-state density. We analyze the density-to-potential map as the distance between the fragments of a system increases and the correlation in the system grows. We observe a feature that gradually develops in the density-to-potential map as well as in the density-to-wavefunction map. This feature is inherited by arbitrary expectation values as functional of the ground-state density. We explicitly show the excited-state energies, the excited-state densities, and the correlation entropy as functionals of the ground-state density. All of them show this exact feature that sharpens as the coupling of the fragmen...
Wall functions for numerical modeling of laminar MHD flows
Widlund, O
2003-01-01
general wall function treatment is presented for the numerical modeling of laminar magnetohydrodynamic (MHD) flows. The wall function expressions are derived analytically from the steady-state momentum and electric potential equations, making use only of local variables of the numerical solution. No assumptions are made regarding the orientation of the magnetic field relative to the wall, nor of the magnitude of the Hartmann number, or the wall conductivity. The wall functions are used for defining implicit boundary conditions for velocity and electric potential, and for computing mass flow and electrical currents in near wall-cells. The wall function treatment was validated in a finite volume formulation, and compared with an analytic solution for a fully developed channel flow in a transverse magnetic field. For the case with insulating walls, a uniform 20 x 20 grid, and Hartmann numbers Ha = [10,30,100], the accuracy of pressure drop and wall shear stress predictions was [1.1%,1.6%,0.5%], respectively. Com...
Experimental assessment of presumed filtered density function models
Stetsyuk, V.; Soulopoulos, N.; Hardalupas, Y.; Taylor, A. M. K. P.
2015-06-01
Measured filtered density functions (FDFs) as well as assumed beta distribution model of mixture fraction and "subgrid" scale (SGS) scalar variance z '' 2 ¯ , used typically in large eddy simulations, were studied by analysing experimental data, obtained from two-dimensional planar, laser induced fluorescence measurements in isothermal swirling turbulent flows at a constant Reynolds number of 29 000 for different swirl numbers (0.3, 0.58, and 1.07). Two-dimensional spatial filtering, by using a box filter, was performed in order to obtain the filtered variables, namely, resolved mean and "subgrid" scale scalar variance. These were used as inputs for assumed beta distribution of mixture fraction and top-hat FDF shape estimates. The presumed beta distribution model, top-hat FDF, and the measured filtered density functions were used to integrate a laminar flamelet solution in order to calculate the corresponding resolved temperature. The experimentally measured FDFs varied with the flow swirl number and both axial and radial positions in the flow. The FDFs were unimodal at flow regions with low SGS scalar variance, z '' 2 ¯ 0.02. Bimodal FDF could be observed for a filter size of approximately 1.5-2 times the Batchelor scale. Unimodal FDF could be observed for a filter size as large as four times the Batchelor scale under well-mixed conditions. In addition, two common computational models (a gradient assumption and a scale similarity model) for the SGS scalar variance were used with the aim to evaluate their validity through comparison with the experimental data. It was found that the gradient assumption model performed generally better than the scale similarity one.
Genetic models for the study of luteinizing hormone receptor function
Directory of Open Access Journals (Sweden)
Prema eNarayan
2015-09-01
Full Text Available The luteinizing hormone/chorionic gonadotropin receptor, LHCGR, is essential for fertility in men and women. LHCGR binds luteinizing hormone (LH as well as the highly homologous chorionic gonadotropin (CG. Signaling from LHCGR is required for steroidogenesis and gametogenesis in males and females and for sexual differentiation in the male. The importance of LHCGR in reproductive physiology is underscored by the large number of naturally occurring inactivating and activating mutations in the receptor that result in reproductive disorders. Consequently, several genetically modified mouse models have been developed for the study of LHCGR function. They include targeted deletion of LH and LHCGR that mimic inactivating mutations in hormone and receptor, expression of a constitutively active mutant in LHCGR that mimics activating mutations associated with familial male-limited precocious puberty and transgenic models of LH and hCG overexpression. This review summarizes the salient findings from these models and their utility in understanding the physiological and pathological consequences of loss and gain of function in LHCGR signaling.
Advanced Modelling and Functional Characterization of B2 Bradykinin Receptor
Directory of Open Access Journals (Sweden)
Muhammad Saad Khan
2015-06-01
Full Text Available Hereditary angioedema (giant hives is an autosomal dominant malady characterized by repetitive episodes of probably life-threatening angioedema due to a partial deficiency of C1 inhibitor. B2 Bradykinin Receptor's (BKRB2 amino acid sequence is deposited within UniProt under accession number P30411. The Physicochemical properties of BKRB2 sequence are determined by using ProtParam. BKRB2's secondary structure was predicted through PROTEUS. Pfam domain was used for functional characterization of BKRB2. PSI-BLAST was used to find homologs of known structure. Modelling by satisfaction of spatial restraints, either uses distance geometry or optimization techniques to satisfy spatial restraints performed by MODELLER. The quality of the generated model was evaluated with PROCHECK by Ramachandran plot analysis. Validation of the generated models was further performed by WHAT IF. ProSA was used for the analysis of Z-scores and energy plots. The 3D structures of the modeled proteins were analyzed using UCSF Chimera. Clustal Omega is used for multiple sequence alignment that uses seeded guide trees and HMM profile-profile techniques to generate alignments.
Relativistic effects in model calculations of double parton distribution function
Rinaldi, Matteo
2016-01-01
In this paper we consider double parton distribution functions (dPDFs) which are the main non perturbative ingredients appearing in the double parton scattering cross section formula in hadronic collisions. By using recent calculation of dPDFs by means of constituent quark models within the so called Light-Front approach, we investigate the role of relativistic effects on dPDFs. We find, in particular, that the so called Melosh operators, which allow to properly convert the LF spin into the canonical one and incorporate a proper treatment of boosts, produce sizeable effects on dPDFs. We discuss specific partonic correlations induced by these operators in transverse plane which are relevant to the proton structure and study under which conditions these results are stable against variations in the choice of the proton wave function.
Modeling the evolution of the cerebellum: from macroevolution to function.
Smaers, Jeroen B
2014-01-01
The purpose of this contribution is to explore how macroevolutionary studies of the cerebellum can contribute to theories on cerebellar function and connectivity. New approaches in modeling the evolution of biological traits have provided new insights in the evolutionary pathways that underlie cerebellar evolution. These approaches reveal patterns of coordinated size changes among brain structures across evolutionary time, demonstrate how particular lineages/species stand out, and what the rate and timing of neuroanatomical changes were in evolutionary history. Using these approaches, recent studies demonstrated that changes in the relative size of the posterior cerebellar cortex and associated cortical areas indicate taxonomic differences in great apes and humans. Considering comparative differences in behavioral capacity, macroevolutionary results are discussed in the context of theories on cerebellar function and learning. © 2014 Elsevier B.V. All rights reserved.
Nonequilibrium Anderson model made simple with density functional theory
Kurth, S.; Stefanucci, G.
2016-12-01
The single-impurity Anderson model is studied within the i-DFT framework, a recently proposed extension of density functional theory (DFT) for the description of electron transport in the steady state. i-DFT is designed to give both the steady current and density at the impurity, and it requires the knowledge of the exchange-correlation (xc) bias and on-site potential (gate). In this work we construct an approximation for both quantities which is accurate in a wide range of temperatures, gates, and biases, thus providing a simple and unifying framework to calculate the differential conductance at negligible computational cost in different regimes. Our results mark a substantial advance for DFT and may inform the construction of functionals applicable to other correlated systems.
Function Interface Models for Hardware Compilation: Types, Signatures, Protocols
Ghica, Dan R
2009-01-01
The problem of synthesis of gate-level descriptions of digital circuits from behavioural specifications written in higher-level programming languages (hardware compilation) has been studied for a long time yet a definitive solution has not been forthcoming. The argument of this essay is mainly methodological, bringing a perspective that is informed by recent developments in programming-language theory. We argue that one of the major obstacles in the way of hardware compilation becoming a useful and mature technology is the lack of a well defined function interface model, i.e. a canonical way in which functions communicate with arguments. We discuss the consequences of this problem and propose a solution based on new developments in programming language theory. We conclude by presenting a prototype implementation and some examples illustrating our principles.
On estimation of survival function under random censoring model
Institute of Scientific and Technical Information of China (English)
JIANG; Jiancheng(蒋建成); CHENG; Bo(程博); WU; Xizhi(吴喜之)
2002-01-01
We study an estimator of the survival function under the random censoring model. Bahadur-type representation of the estimator is obtained and asymptotic expression for its mean squared errors is given, which leads to the consistency and asymptotic normality of the estimator. A data-driven local bandwidth selection rule for the estimator is proposed. It is worth noting that the estimator is consistent at left boundary points, which contrasts with the cases of density and hazard rate estimation. A Monte Carlo comparison of different estimators is made and it appears that the proposed data-driven estimators have certain advantages over the common Kaplan-Meier estmator.
Transfer function modeling of damping mechanisms in viscoelastic plates
Slater, J. C.; Inman, D. J.
1991-01-01
This work formulates a method for the modeling of material damping characteristics in plates. The Sophie German equation of classical plate theory is modified to incorporate hysteresis effects represented by complex stiffness using the transfer function approach proposed by Golla and Hughes, (1985). However, this procedure is not limited to this representation. The governing characteristic equation is decoupled through separation of variables, yielding a solution similar to that of undamped classical plate theory, allowing solution of the steady state as well as the transient response problem.
Dynamics Model Abstraction Scheme Using Radial Basis Functions
Directory of Open Access Journals (Sweden)
Silvia Tolu
2012-01-01
Full Text Available This paper presents a control model for object manipulation. Properties of objects and environmental conditions influence the motor control and learning. System dynamics depend on an unobserved external context, for example, work load of a robot manipulator. The dynamics of a robot arm change as it manipulates objects with different physical properties, for example, the mass, shape, or mass distribution. We address active sensing strategies to acquire object dynamical models with a radial basis function neural network (RBF. Experiments are done using a real robot’s arm, and trajectory data are gathered during various trials manipulating different objects. Biped robots do not have high force joint servos and the control system hardly compensates all the inertia variation of the adjacent joints and disturbance torque on dynamic gait control. In order to achieve smoother control and lead to more reliable sensorimotor complexes, we evaluate and compare a sparse velocity-driven versus a dense position-driven control scheme.
Confidence Intervals of Variance Functions in Generalized Linear Model
Institute of Scientific and Technical Information of China (English)
Yong Zhou; Dao-ji Li
2006-01-01
In this paper we introduce an appealing nonparametric method for estimating variance and conditional variance functions in generalized linear models (GLMs), when designs are fixed points and random variables respectively. Bias-corrected confidence bands are proposed for the (conditional) variance by local linear smoothers. Nonparametric techniques are developed in deriving the bias-corrected confidence intervals of the (conditional) variance. The asymptotic distribution of the proposed estimator is established and show that the bias-corrected confidence bands asymptotically have the correct coverage properties. A small simulation is performed when unknown regression parameter is estimated by nonparametric quasi-likelihood. The results are also applicable to nonparametric autoregressive times series model with heteroscedastic conditional variance.
Exact maps in density functional theory for lattice models
Dimitrov, Tanja; Appel, Heiko; Fuks, Johanna I.; Rubio, Angel
2016-08-01
In the present work, we employ exact diagonalization for model systems on a real-space lattice to explicitly construct the exact density-to-potential and graphically illustrate the complete exact density-to-wavefunction map that underly the Hohenberg-Kohn theorem in density functional theory. Having the explicit wavefunction-to-density map at hand, we are able to construct arbitrary observables as functionals of the ground-state density. We analyze the density-to-potential map as the distance between the fragments of a system increases and the correlation in the system grows. We observe a feature that gradually develops in the density-to-potential map as well as in the density-to-wavefunction map. This feature is inherited by arbitrary expectation values as functional of the ground-state density. We explicitly show the excited-state energies, the excited-state densities, and the correlation entropy as functionals of the ground-state density. All of them show this exact feature that sharpens as the coupling of the fragments decreases and the correlation grows. We denominate this feature as intra-system steepening and discuss how it relates to the well-known inter-system derivative discontinuity. The inter-system derivative discontinuity is an exact concept for coupled subsystems with degenerate ground state. However, the coupling between subsystems as in charge transfer processes can lift the degeneracy. An important conclusion is that for such systems with a near-degenerate ground state, the corresponding cut along the particle number N of the exact density functionals is differentiable with a well-defined gradient near integer particle number.
DEFF Research Database (Denmark)
Øjelund, Henrik; Sadegh, Payman
2000-01-01
, constraints are introduced to ensure the conformity of the estimates to a gien global structure. Hierarchical models are then utilized as a tool to ccomodate global model uncertainties via parametric variabilities within the structure. The global parameters and their associated uncertainties are estimated...... simultaneously with the (local estimates of) function values. The approach is applied to modelling of a linear time variant dynamic system under prior linear time invariant structure where local regression fails as a result of high dimensionality.......Local function approximations concern fitting low order models to weighted data in neighbourhoods of the points where the approximations are desired. Despite their generality and convenience of use, local models typically suffer, among others, from difficulties arising in physical interpretation...
Models for predicting objective function weights in prostate cancer IMRT
Energy Technology Data Exchange (ETDEWEB)
Boutilier, Justin J., E-mail: j.boutilier@mail.utoronto.ca; Lee, Taewoo [Department of Mechanical and Industrial Engineering, University of Toronto, 5 King’s College Road, Toronto, Ontario M5S 3G8 (Canada); Craig, Tim [Radiation Medicine Program, UHN Princess Margaret Cancer Centre, 610 University of Avenue, Toronto, Ontario M5T 2M9, Canada and Department of Radiation Oncology, University of Toronto, 148 - 150 College Street, Toronto, Ontario M5S 3S2 (Canada); Sharpe, Michael B. [Radiation Medicine Program, UHN Princess Margaret Cancer Centre, 610 University of Avenue, Toronto, Ontario M5T 2M9 (Canada); Department of Radiation Oncology, University of Toronto, 148 - 150 College Street, Toronto, Ontario M5S 3S2 (Canada); Techna Institute for the Advancement of Technology for Health, 124 - 100 College Street, Toronto, Ontario M5G 1P5 (Canada); Chan, Timothy C. Y. [Department of Mechanical and Industrial Engineering, University of Toronto, 5 King’s College Road, Toronto, Ontario M5S 3G8, Canada and Techna Institute for the Advancement of Technology for Health, 124 - 100 College Street, Toronto, Ontario M5G 1P5 (Canada)
2015-04-15
Purpose: To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization objective function weights from patient geometry for intensity-modulated radiation therapy of prostate cancer. Methods: A previously developed inverse optimization method was applied retrospectively to determine optimal objective function weights for 315 treated patients. The authors used an overlap volume ratio (OV) of bladder and rectum for different PTV expansions and overlap volume histogram slopes (OVSR and OVSB for the rectum and bladder, respectively) as explanatory variables that quantify patient geometry. Using the optimal weights as ground truth, the authors trained and applied three prediction models: logistic regression (LR), multinomial logistic regression (MLR), and weighted K-nearest neighbor (KNN). The population average of the optimal objective function weights was also calculated. Results: The OV at 0.4 cm and OVSR at 0.1 cm features were found to be the most predictive of the weights. The authors observed comparable performance (i.e., no statistically significant difference) between LR, MLR, and KNN methodologies, with LR appearing to perform the best. All three machine learning models outperformed the population average by a statistically significant amount over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and dose to the bladder, rectum, CTV, and PTV. When comparing the weights directly, the LR model predicted bladder and rectum weights that had, on average, a 73% and 74% relative improvement over the population average weights, respectively. The treatment plans resulting from the LR weights had, on average, a rectum V70Gy that was 35% closer to the clinical plan and a bladder V70Gy that was 29% closer, compared to the population average weights. Similar results were observed for all other clinical metrics. Conclusions: The authors demonstrated that the KNN and MLR
Passive ventricular mechanics modelling using MRI of structure and function.
Wang, V Y; Lam, H I; Ennis, D B; Young, A A; Nash, M P
2008-01-01
Patients suffering from dilated cardiomyopathy or myocardial infarction can develop left ventricular (LV) diastolic impairment. The LV remodels its structure and function to adapt to pathophysiological changes in geometry and loading conditions and this remodeling process can alter the passive ventricular mechanics. In order to better understand passive ventricular mechanics, a LV finite element model was developed to incorporate physiological and mechanical information derived from in vivo magnetic resonance imaging (MRI) tissue tagging, in vivo LV cavity pressure recording and ex vivo diffusion tensor MRI (DTMRI) of a canine heart. MRI tissue tagging enables quantitative evaluation of cardiac mechanical function with high spatial and temporal resolution, whilst the direction of maximum water diffusion (the primary eigenvector) in each voxel of a DTMRI directly correlates with the myocardial fibre orientation. This model was customized to the geometry of the canine LV during diastasis by fitting the segmented epicardial and endocardial surface data from tagged MRI using nonlinear finite element fitting techniques. Myofibre orientations, extracted from DTMRI of the same heart, were incorporated into this geometric model using a free form deformation methodology. Pressure recordings, temporally synchronized to the tissue tagging MRI data, were used to simulate the LV deformation during diastole. Simulation of the diastolic LV mechanics allowed us to estimate the stiffness of the passive LV myocardium based on kinematic data obtained from tagged MRI. This integrated physiological model will allow more insight into the regional passive diastolic mechanics of the LV on an individualized basis, thereby improving our understanding of the underlying structural basis of mechanical dysfunction in pathological conditions.
Modeling functional piezoelectricity in perovskite superlattices with competing instabilities
Swartz, Charles; Wu, Xifan
2012-02-01
Multi-component Perovskite Superlattices (SLs) of the form ABO3, provide a very promising avenue for the design of materials with multifunctional properties. Furthermore the interfaces of such multi-component SLs are home to competing anti-ferrodistortive and ferroelectric instabilities which can produce unexpected functionalities. However, at present first principles calculations exceeding more than 10 units cells, are particularly costly as they scale with the valence electrons as N^3. We present a first-principles modeling technique that allows us to accurately model the piezoelectric strains of paraelectric/ferroelectric SLs, BaTiO3/CaTiO3 and PbTiO3/SrTiO3, under a fixed displacement field. The model is based on a maximally localized wannier center layer polarization technique, as well as a truncated cluster expansion, that makes use of the fact that such PE/FE SLs have been shown to have highly localized ionic and electronic interface effects. The prediction of the piezoelectricity for a SL of an arbitrary stacking sequence will be demonstrated. We also use our model to conduct a systemic study of the interface effects on piezoelectric response in the above SLs paying special attention to a strong non-linear effect observed in Bulk SrTiO3.
The integrated Earth System Model Version 1: formulation and functionality
Energy Technology Data Exchange (ETDEWEB)
Collins, William D.; Craig, Anthony P.; Truesdale, John E.; Di Vittorio, Alan; Jones, Andrew D.; Bond-Lamberty, Benjamin; Calvin, Katherine V.; Edmonds, James A.; Kim, Son H.; Thomson, Allison M.; Patel, Pralit L.; Zhou, Yuyu; Mao, Jiafu; Shi, Xiaoying; Thornton, Peter E.; Chini, Louise M.; Hurtt, George C.
2015-07-23
The integrated Earth System Model (iESM) has been developed as a new tool for pro- jecting the joint human/climate system. The iESM is based upon coupling an Integrated Assessment Model (IAM) and an Earth System Model (ESM) into a common modeling in- frastructure. IAMs are the primary tool for describing the human–Earth system, including the sources of global greenhouse gases (GHGs) and short-lived species, land use and land cover change, and other resource-related drivers of anthropogenic climate change. ESMs are the primary scientific tools for examining the physical, chemical, and biogeochemical impacts of human-induced changes to the climate system. The iESM project integrates the economic and human dimension modeling of an IAM and a fully coupled ESM within a sin- gle simulation system while maintaining the separability of each model if needed. Both IAM and ESM codes are developed and used by large communities and have been extensively applied in recent national and international climate assessments. By introducing heretofore- omitted feedbacks between natural and societal drivers, we can improve scientific under- standing of the human–Earth system dynamics. Potential applications include studies of the interactions and feedbacks leading to the timing, scale, and geographic distribution of emissions trajectories and other human influences, corresponding climate effects, and the subsequent impacts of a changing climate on human and natural systems. This paper de- scribes the formulation, requirements, implementation, testing, and resulting functionality of the first version of the iESM released to the global climate community.
Informing soil models using pedotransfer functions: challenges and perspectives
Pachepsky, Yakov; Romano, Nunzio
2015-04-01
Pedotransfer functions (PTFs) are empirical relationships between parameters of soil models and more easily obtainable data on soil properties. PTFs have become an indispensable tool in modeling soil processes. As alternative methods to direct measurements, they bridge the data we have and data we need by using soil survey and monitoring data to enable modeling for real-world applications. Pedotransfer is extensively used in soil models addressing the most pressing environmental issues. The following is an attempt to provoke a discussion by listing current issues that are faced by PTF development. 1. As more intricate biogeochemical processes are being modeled, development of PTFs for parameters of those processes becomes essential. 2. Since the equations to express PTF relationships are essentially unknown, there has been a trend to employ highly nonlinear equations, e.g. neural networks, which in theory are flexible enough to simulate any dependence. This, however, comes with the penalty of large number of coefficients that are difficult to estimate reliably. A preliminary classification applied to PTF inputs and PTF development for each of the resulting groups may provide simple, transparent, and more reliable pedotransfer equations. 3. The multiplicity of models, i.e. presence of several models producing the same output variables, is commonly found in soil modeling, and is a typical feature in the PTF research field. However, PTF intercomparisons are lagging behind PTF development. This is aggravated by the fact that coefficients of PTF based on machine-learning methods are usually not reported. 4. The existence of PTFs is the result of some soil processes. Using models of those processes to generate PTFs, and more general, developing physics-based PTFs remains to be explored. 5. Estimating the variability of soil model parameters becomes increasingly important, as the newer modeling technologies such as data assimilation, ensemble modeling, and model
GDP model for Chinese energy modeling based on empirical production function
Institute of Scientific and Technical Information of China (English)
HiroshiYAGITA; BaorenWEI; AtsushiINABA; MasayukiSAGISAKA; KeikoHIROTA; KiyoyukiMINATO
2003-01-01
In many energy models, GDP is an exogenous variable, so that variables within energy model are not able to change the value of GDP. Based on empirical production function, a GDP model has been established in this paper using capital stock, urbanization rate and population size as independent variables. It has been found that urbanization rate is a kind of integrated indicator of labor quantity and the education level of labors in China. And it also takes away the labor surplus in rural area in China. The forecasting results show that the model is robust. The results have the same tendency as the results from famous CGE model and the results from responsible Chinese authorities, and the numbers of GDP growth rates are also similar in 50 years. It has been concluded that the model is a good candidate for energy model as an endogenous vadable.
Hybrid model decomposition of speech and noise in a radial basis function neural model framework
DEFF Research Database (Denmark)
Sørensen, Helge Bjarup Dissing; Hartmann, Uwe
1994-01-01
applied is based on a combination of the hidden Markov model (HMM) decomposition method, for speech recognition in noise, developed by Varga and Moore (1990) from DRA and the hybrid (HMM/RBF) recognizer containing hidden Markov models and radial basis function (RBF) neural networks, developed by Singer...... and Lippmann (1992) from MIT Lincoln Lab. The present authors modified the hybrid recognizer to fit into the decomposition method to achieve high performance speech recognition in noisy environments. The approach has been denoted the hybrid model decomposition method and it provides an optimal method...... for decomposition of speech and noise by using a set of speech pattern models and a noise model(s), each realized as an HMM/RBF pattern model...
Holonomy spin foam models: Asymptotic geometry of the partition function
Hellmann, Frank
2013-01-01
We study the asymptotic geometry of the spin foam partition function for a large class of models, including the models of Barrett and Crane, Engle, Pereira, Rovelli and Livine, and, Freidel and Krasnov. The asymptotics is taken with respect to the boundary spins only, no assumption of large spins is made in the interior. We give a sufficient criterion for the existence of the partition function. We find that geometric boundary data is suppressed unless its interior continuation satisfies certain accidental curvature constraints. This means in particular that most Regge manifolds are suppressed in the asymptotic regime. We discuss this explicitly for the case of the configurations arising in the 3-3 Pachner move. We identify the origin of these accidental curvature constraints as an incorrect twisting of the face amplitude upon introduction of the Immirzi parameter and propose a way to resolve this problem, albeit at the price of losing the connection to the SU(2) boundary Hilbert space. The key methodological...
Modeling and Simulations of Particulate Flows through Functionalized Porous Media
Li, Chunhui; Dutta, Prashanta; Liu, Jin
2016-11-01
Transport of particulate fluid through a functionalized porous material is of significant interest in many industrial applications, such as earth sciences, battery designs and water/air purifications. The entire process is complex, which involves the convection of fluid, diffusion of reactants as well as reversible chemical reactions at the fluid-solid interface In this work we present a convection-diffusion-reaction model and simulate the transport of particulate fluid through a functionalized porous media. The porous structures are generated and manipulated through the quartet structure generation set method. The Navier-Stokes with convection-diffusion equations are solved using the lattice Boltzmann method. The chemical reactions at the interface are modeled by an absorption-desorption process and treated as the boundary conditions for above governing equations. Through our simulations we study the effects of porous structures, including porosity, pore orientation, and pore size as well as the kinetic rates of surface reactions on the overall performance of removal efficiency of the species from the solution. Our results show that whole process is highly affected by both the porous structures and absorption rate. The optimal parameters can be achieved by proper design. This work is supported by NSF Grants: CBET-1250107 and CBET -1604211.
Modeling Marine Electromagnetic Survey with Radial Basis Function Networks
Directory of Open Access Journals (Sweden)
Agus Arif
2011-08-01
Full Text Available A marine electromagnetic survey is an engineering endeavour to discover the location and dimension of a hydrocarbon layer under an ocean floor. In this kind of survey, an array of electric and magnetic receivers are located on the sea floor and record the scattered, refracted and reflected electromagnetic wave, which has been transmitted by an electric dipole antenna towed by a vessel. The data recorded in receivers must be processed and further analysed to estimate the hydrocarbon location and dimension. To conduct those analyses successfuly, a radial basis function (RBF network could be employed to become a forward model of the input-output relationship of the data from a marine electromagnetic survey. This type of neural networks is working based on distances between its inputs and predetermined centres of some basis functions. A previous research had been conducted to model the same marine electromagnetic survey using another type of neural networks, which is a multi layer perceptron (MLP network. By comparing their validation and training performances (mean-squared errors and correlation coefficients, it is concluded that, in this case, the MLP network is comparatively better than the RBF network
Longitudinal functional principal component modelling via Stochastic Approximation Monte Carlo
Martinez, Josue G.
2010-06-01
The authors consider the analysis of hierarchical longitudinal functional data based upon a functional principal components approach. In contrast to standard frequentist approaches to selecting the number of principal components, the authors do model averaging using a Bayesian formulation. A relatively straightforward reversible jump Markov Chain Monte Carlo formulation has poor mixing properties and in simulated data often becomes trapped at the wrong number of principal components. In order to overcome this, the authors show how to apply Stochastic Approximation Monte Carlo (SAMC) to this problem, a method that has the potential to explore the entire space and does not become trapped in local extrema. The combination of reversible jump methods and SAMC in hierarchical longitudinal functional data is simplified by a polar coordinate representation of the principal components. The approach is easy to implement and does well in simulated data in determining the distribution of the number of principal components, and in terms of its frequentist estimation properties. Empirical applications are also presented.
Minimal models on Riemann surfaces: The partition functions
Energy Technology Data Exchange (ETDEWEB)
Foda, O. (Katholieke Univ. Nijmegen (Netherlands). Inst. voor Theoretische Fysica)
1990-06-04
The Coulomb gas representation of the A{sub n} series of c=1-6/(m(m+1)), m{ge}3, minimal models is extended to compact Riemann surfaces of genus g>1. An integral representation of the partition functions, for any m and g is obtained as the difference of two gaussian correlation functions of a background charge, (background charge on sphere) x (1-g), and screening charges integrated over the surface. The coupling constant x (compacitification radius){sup 2} of the gaussian expressions are, as on the torus, m(m+1), and m/(m+1). The partition functions obtained are modular invariant, have the correct conformal anomaly and - restricting the propagation of states to a single handle - one can verify explicitly the decoupling of the null states. On the other hand, they are given in terms of coupled surface integrals, and it remains to show how they degenerate consistently to those on lower-genus surfaces. In this work, this is clear only at the lattice level, where no screening charges appear. (orig.).
Plant functional type mapping for earth system models
Directory of Open Access Journals (Sweden)
B. Poulter
2011-08-01
Full Text Available The sensitivity of global carbon and water cycling to climate variability is coupled directly to land cover and the distribution of vegetation. To investigate biogeochemistry-climate interactions, earth system models require a representation of vegetation distributions that are either prescribed from remote sensing data or simulated via biogeography models. However, the abstraction of earth system state variables in models means that data products derived from remote sensing need to be post-processed for model-data assimilation. Dynamic global vegetation models (DGVM rely on the concept of plant functional types (PFT to group shared traits of thousands of plant species into just several classes. Available databases of observed PFT distributions must be relevant to existing satellite sensors and their derived products, and to the present day distribution of managed lands. Here, we develop four PFT datasets based on land-cover information from three satellite sensors (EOS-MODIS 1 km and 0.5 km, SPOT4-VEGETATION 1 km, and ENVISAT-MERIS 0.3 km spatial resolution that are merged with spatially-consistent Köppen-Geiger climate zones. Using a beta (β diversity metric to assess reclassification similarity, we find that the greatest uncertainty in PFT classifications occur most frequently between cropland and grassland categories, and in dryland systems between shrubland, grassland and forest categories because of differences in the minimum threshold required for forest cover. The biogeography-biogeochemistry DGVM, LPJmL, is used in diagnostic mode with the four PFT datasets prescribed to quantify the effect of land-cover uncertainty on climatic sensitivity of gross primary productivity (GPP and transpiration fluxes. Our results show that land-cover uncertainty has large effects in arid regions, contributing up to 30 % (20 % uncertainty in the sensitivity of GPP (transpiration to precipitation. The availability of plant functional type datasets that
Loss Function Based Ranking in Two-Stage, Hierarchical Models
Lin, Rongheng; Louis, Thomas A.; Paddock, Susan M.; Ridgeway, Greg
2009-01-01
Performance evaluations of health services providers burgeons. Similarly, analyzing spatially related health information, ranking teachers and schools, and identification of differentially expressed genes are increasing in prevalence and importance. Goals include valid and efficient ranking of units for profiling and league tables, identification of excellent and poor performers, the most differentially expressed genes, and determining “exceedances” (how many and which unit-specific true parameters exceed a threshold). These data and inferential goals require a hierarchical, Bayesian model that accounts for nesting relations and identifies both population values and random effects for unit-specific parameters. Furthermore, the Bayesian approach coupled with optimizing a loss function provides a framework for computing non-standard inferences such as ranks and histograms. Estimated ranks that minimize Squared Error Loss (SEL) between the true and estimated ranks have been investigated. The posterior mean ranks minimize SEL and are “general purpose,” relevant to a broad spectrum of ranking goals. However, other loss functions and optimizing ranks that are tuned to application-specific goals require identification and evaluation. For example, when the goal is to identify the relatively good (e.g., in the upper 10%) or relatively poor performers, a loss function that penalizes classification errors produces estimates that minimize the error rate. We construct loss functions that address this and other goals, developing a unified framework that facilitates generating candidate estimates, comparing approaches and producing data analytic performance summaries. We compare performance for a fully parametric, hierarchical model with Gaussian sampling distribution under Gaussian and a mixture of Gaussians prior distributions. We illustrate approaches via analysis of standardized mortality ratio data from the United States Renal Data System. Results show that SEL
Epistasis analysis for quantitative traits by functional regression model.
Zhang, Futao; Boerwinkle, Eric; Xiong, Momiao
2014-06-01
The critical barrier in interaction analysis for rare variants is that most traditional statistical methods for testing interactions were originally designed for testing the interaction between common variants and are difficult to apply to rare variants because of their prohibitive computational time and poor ability. The great challenges for successful detection of interactions with next-generation sequencing (NGS) data are (1) lack of methods for interaction analysis with rare variants, (2) severe multiple testing, and (3) time-consuming computations. To meet these challenges, we shift the paradigm of interaction analysis between two loci to interaction analysis between two sets of loci or genomic regions and collectively test interactions between all possible pairs of SNPs within two genomic regions. In other words, we take a genome region as a basic unit of interaction analysis and use high-dimensional data reduction and functional data analysis techniques to develop a novel functional regression model to collectively test interactions between all possible pairs of single nucleotide polymorphisms (SNPs) within two genome regions. By intensive simulations, we demonstrate that the functional regression models for interaction analysis of the quantitative trait have the correct type 1 error rates and a much better ability to detect interactions than the current pairwise interaction analysis. The proposed method was applied to exome sequence data from the NHLBI's Exome Sequencing Project (ESP) and CHARGE-S study. We discovered 27 pairs of genes showing significant interactions after applying the Bonferroni correction (P-values < 4.58 × 10(-10)) in the ESP, and 11 were replicated in the CHARGE-S study.
Melittin restores proteasome function in an animal model of ALS
Directory of Open Access Journals (Sweden)
Lee Sang Min
2011-06-01
Full Text Available Abstract Amyotrophic lateral sclerosis (ALS is a paralyzing disorder characterized by the progressive degeneration and death of motor neurons and occurs both as a sporadic and familial disease. Mutant SOD1 (mtSOD1 in motor neurons induces vulnerability to the disease through protein misfolding, mitochondrial dysfunction, oxidative damage, cytoskeletal abnormalities, defective axonal transport- and growth factor signaling, excitotoxicity, and neuro-inflammation. Melittin is a 26 amino acid protein and is one of the components of bee venom which is used in traditional Chinese medicine to inhibit of cancer cell proliferation and is known to have anti-inflammatory and anti-arthritic effects. The purpose of the present study was to determine if melittin could suppress motor neuron loss and protein misfolding in the hSOD1G93A mouse, which is commonly used as a model for inherited ALS. Meltittin was injected at the 'ZuSanLi' (ST36 acupuncture point in the hSOD1G93A animal model. Melittin-treated animals showed a decrease in the number of microglia and in the expression level of phospho-p38 in the spinal cord and brainstem. Interestingly, melittin treatment in symptomatic ALS animals improved motor function and reduced the level of neuron death in the spinal cord when compared to the control group. Furthermore, we found increased of α-synuclein modifications, such as phosphorylation or nitration, in both the brainstem and spinal cord in hSOD1G93A mice. However, melittin treatment reduced α-synuclein misfolding and restored the proteasomal activity in the brainstem and spinal cord of symptomatic hSOD1G93A transgenic mice. Our research suggests a potential functional link between melittin and the inhibition of neuroinflammation in an ALS animal model.
A functional-structural modelling approach to autoregulation of nodulation.
Han, Liqi; Gresshoff, Peter M; Hanan, Jim
2011-04-01
Autoregulation of nodulation is a long-distance shoot-root signalling regulatory system that regulates nodule meristem proliferation in legume plants. However, due to the intricacy and subtleness of the signalling nature in plants, molecular and biochemical details underlying mechanisms of autoregulation of nodulation remain largely unknown. The purpose of this study is to use functional-structural plant modelling to investigate the complexity of this signalling system. There are two major challenges to be met: modelling the 3D architecture of legume roots with nodulation and co-ordinating signalling-developmental processes with various rates. Soybean (Glycine max) was chosen as the target legume. Its root system was observed to capture lateral root branching and nodule distribution patterns. L-studio, a software tool supporting context-sensitive L-system modelling, was used for the construction of the architectural model and integration with the internal signalling. A branching pattern with regular radial angles was found between soybean lateral roots, from which a root mapping method was developed to characterize the laterals. Nodules were mapped based on 'nodulation section' to reveal nodule distribution. A root elongation algorithm was then developed for simulation of root development. Based on the use of standard sub-modules, a synchronization algorithm was developed to co-ordinate multi-rate signalling and developmental processes. The modelling methods developed here not only allow recreation of legume root architecture with lateral branching and nodulation details, but also enable parameterization of internal signalling to produce different regulation results. This provides the basis for using virtual experiments to help in investigating the signalling mechanisms at work.
Modelling the Transfer Function for the Dark Energy Survey
Chang, C; Wechsler, R H; Refregier, A; Amara, A; Rykoff, E; Becker, M R; Bruderer, C; Gamper, L; Leistedt, B; Peiris, H; Abbott, T; Abdalla, F B; Banerji, M; Bernstein, R A; Bertin, E; Brooks, D; Rosell, A Carnero; Desai, S; da Costa, L N; Cunha, C E; Eifler, T; Evrard, A E; Neto, A Fausti; Gerdes, D; Gruen, D; James, D; Kuehn, K; Maia, M A G; Makler, M; Ogando, R; Plazas, A; Sanchez, E; Schubnell, M; Sevilla-Noarbe, I; Smith, C; Soares-Santos, M; Suchyta, E; Swanson, M E C; Tarle, G; Zuntz, J
2014-01-01
We present a forward-modelling simulation framework designed to model the data products from the Dark Energy Survey (DES). This forward-model process can be thought of as a transfer function -- a mapping from cosmological and astronomical signals to the final data products used by the scientists. Using output from the cosmological simulations (the Blind Cosmology Challenge), we generate simulated images (the Ultra Fast Image Simulator, Berge et al. 2013) and catalogs representative of the DES data. In this work we simulate the 244 sq. deg coadd images and catalogs in 5 bands for the DES Science Verification (SV) data. The simulation output is compared with the corresponding data to show that major characteristics of the images and catalogs can be captured. We also point out several directions of future improvements. Two practical examples, star/galaxy classification and proximity effects on object detection, are then used to demonstrate how one can use the simulations to address systematics issues in data ana...
Colour-independent partition functions in coloured vertex models
Foda, O
2013-01-01
We study lattice configurations related to S_n, the scalar product of an off-shell state and an on-shell state in rational A_n integrable vertex models, n = {1, 2}. The lattice lines are colourless and oriented. The state variables are n conserved colours that flow along the line orientations, but do not necessarily cover every bond in the lattice. Choosing boundary conditions such that the positions where the colours flow into the lattice are fixed, and where they flow out are summed over, we show that the partition functions of these configurations, with these boundary conditions, are n-independent. Our results extend to trigonometric A_n models, and to all n. This n-independence explains, in vertex-model terms, results from recent studies of S_2 [1, 2]. Namely, 1. S_2 which depends on two sets of Bethe roots, b_1 and b_2, and cannot (as far as we know) be expressed in single determinant form, degenerates in the limit b_1 -> infinity, and/or b_2 -> infinity, into a product of determinants, 2. Each of the la...
Applying fuzzy analytic network process in quality function deployment model
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Mohammad Ali Afsharkazemi
2012-08-01
Full Text Available In this paper, we propose an empirical study of QFD implementation when fuzzy numbers are used to handle the uncertainty associated with different components of the proposed model. We implement fuzzy analytical network to find the relative importance of various criteria and using fuzzy numbers we calculate the relative importance of these factors. The proposed model of this paper uses fuzzy matrix and house of quality to study the products development in QFD and also the second phase i.e. part deployment. In most researches, the primary objective is only on CRs to implement the quality function deployment and some other criteria such as production costs, manufacturing costs etc were disregarded. The results of using fuzzy analysis network process based on the QFD model in Daroupat packaging company to develop PVDC show that the most important indexes are being waterproof, resistant pill packages, and production cost. In addition, the PVDC coating is the most important index in terms of company experts’ point of view.
Exact Potts model partition functions on ladder graphs
Shrock, Robert
2000-08-01
We present exact calculations of the partition function Z of the q-state Potts model and its generalization to real q, for arbitrary temperature on n-vertex ladder graphs, i.e., strips of the square lattice with width Ly=2 and arbitrary length Lx, with free, cyclic, and Möbius longitudinal boundary conditions. These partition functions are equivalent to Tutte/Whitney polynomials for these graphs. The free energy is calculated exactly for the infinite-length limit of these ladder graphs and the thermodynamics is discussed. By comparison with strip graphs of other widths, we analyze how the singularities at the zero-temperature critical point of the ferromagnet on infinite-length, finite-width strips depend on the width. We point out and study the following noncommutativity at certain special values q s: lim n→∞ limq→q s Z 1/n≠ limq→q s limn→∞ Z 1/n. It is shown that the Potts antiferromagnet on both the infinite-length line and ladder graphs with cyclic or Möbius boundary conditions exhibits a phase transition at finite temperature if 0< q<2, but with unphysical properties, including negative specific heat and non-existence, in the low-temperature phase, of an n→∞ limit for thermodynamic functions that is independent of boundary conditions. Considering the full generalization to arbitrary complex q and temperature, we determine the singular locus B in the corresponding C2 space, arising as the accumulation set of partition function zeros as n→∞. In particular, we study the connection with the T=0 limit of the Potts antiferromagnet where B reduces to the accumulation set of chromatic zeros. Certain properties of the complex-temperature phase diagrams are shown to exhibit close connections with those of the model on the square lattice, showing that exact solutions on infinite-length strips provide a way of gaining insight into these complex-temperature phase diagrams.
Functional test of FOOTPRINT pedotransfer functions for the dual-permeability model MACRO
Moeys, J.; Jarvis, N. J.; Stenemo, F.; Hollis, J. M.; Dubus, I. G.; Larsbo, M.; Brown, C. D.; Bromilow, R.; Coquet, Y.; Vachier, P.
2009-04-01
Our ability to assess and predict pollution risks for surface waters and groundwater across larger areas (e.g. catchment and regional scales) relies on our capacity to estimate soil physical and hydrological properties and crop characteristics that are generally required as model parameters. ‘Pedotransfer' functions (PTF) can be used to estimate model parameters from more easily available soil survey data. The EU-FP6 European project FOOTPRINT (www.eu-footprint.org) has supported the development of a full set of PTF's to completely parameterise the pesticide fate model MACRO from only easily available site and soil data for a range of European agronomic, climatic and pedological scenarios The work presented here aimed at assessing the performance of the parameterisation procedures developed in the FOOTPRINT project for MACRO, from a functional point of view. We present a comparison of measured and simulated tracer leaching in medium- to long-term (2 months to 2 years) experiments driven by natural-transient rainfall conditions on 41 lysimeters, representing 15 soil types, located in Sweden, UK and France. For each experiment, the only information used to parameterize the model was a soil profile description, in which each horizon is characterized by its thickness, FAO master horizon type, texture class, organic carbon content and bulk density and knowledge of the tillage (till, no-till, harrowed) and cropping practices (crop type, and sowing dates). The average depth of the lysimeters was 1 meter, each profile containing an average of 4.6 horizons. The soil properties covered a large range of textures (1 to 78% clay), organic matter contents (0 to 29%) and bulk densities (550 to 1870 kg.m-3). Simulations were first conducted without any calibration of parameters. In a second step, we conducted simulations where two crop parameters were optimized (root depth and root water uptake efficiency), in order to estimate the impact of errors in the simulated water balance
Modeling root reinforcement using root-failure Weibull survival function
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M. Schwarz
2013-03-01
Full Text Available Root networks contribute to slope stability through complicated interactions that include mechanical compression and tension. Due to the spatial heterogeneity of root distribution and the dynamic of root turnover, the quantification of root reinforcement on steep slope is challenging and consequently the calculation of slope stability as well. Although the considerable advances in root reinforcement modeling, some important aspect remain neglected. In this study we address in particular to the role of root strength variability on the mechanical behaviors of a root bundle. Many factors may contribute to the variability of root mechanical properties even considering a single class of diameter. This work presents a new approach for quantifying root reinforcement that considers the variability of mechanical properties of each root diameter class. Using the data of laboratory tensile tests and field pullout tests, we calibrate the parameters of the Weibull survival function to implement the variability of root strength in a numerical model for the calculation of root reinforcement (RBMw. The results show that, for both laboratory and field datasets, the parameters of the Weibull distribution may be considered constant with the exponent equal to 2 and the normalized failure displacement equal to 1. Moreover, the results show that the variability of root strength in each root diameter class has a major influence on the behavior of a root bundle with important implications when considering different approaches in slope stability calculation. Sensitivity analysis shows that the calibration of the tensile force and the elasticity of the roots are the most important equations, as well as the root distribution. The new model allows the characterization of root reinforcement in terms of maximum pullout force, stiffness, and energy. Moreover, it simplifies the implementation of root reinforcement in slope stability models. The realistic quantification of root
Dynamic density functional theory of solid tumor growth: Preliminary models
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Arnaud Chauviere
2012-03-01
Full Text Available Cancer is a disease that can be seen as a complex system whose dynamics and growth result from nonlinear processes coupled across wide ranges of spatio-temporal scales. The current mathematical modeling literature addresses issues at various scales but the development of theoretical methodologies capable of bridging gaps across scales needs further study. We present a new theoretical framework based on Dynamic Density Functional Theory (DDFT extended, for the first time, to the dynamics of living tissues by accounting for cell density correlations, different cell types, phenotypes and cell birth/death processes, in order to provide a biophysically consistent description of processes across the scales. We present an application of this approach to tumor growth.
Linear $\\Sigma$ Model in the Gaussian Functional Approximation
Nakamura, I
2001-01-01
We apply a self-consistent relativistic mean-field variational ``Gaussian functional'' (or Hartree) approximation to the linear $\\sigma$ model with spontaneously and explicitly broken chiral O(4) symmetry. We set up the self-consistency, or ``gap'' and the Bethe-Salpeter equations. We check and confirm the chiral Ward-Takahashi identities, among them the Nambu-Goldstone theorem and the (partial) axial current conservation [CAC], both in and away from the chiral limit. With explicit chiral symmetry breaking we confirm the Dashen relation for the pion mass and partial CAC. We solve numerically the gap and Bethe-Salpeter equations, discuss the solutions' properties and the particle content of the theory.
Stand diameter distribution modelling and prediction based on Richards function.
Directory of Open Access Journals (Sweden)
Ai-guo Duan
Full Text Available The objective of this study was to introduce application of the Richards equation on modelling and prediction of stand diameter distribution. The long-term repeated measurement data sets, consisted of 309 diameter frequency distributions from Chinese fir (Cunninghamia lanceolata plantations in the southern China, were used. Also, 150 stands were used as fitting data, the other 159 stands were used for testing. Nonlinear regression method (NRM or maximum likelihood estimates method (MLEM were applied to estimate the parameters of models, and the parameter prediction method (PPM and parameter recovery method (PRM were used to predict the diameter distributions of unknown stands. Four main conclusions were obtained: (1 R distribution presented a more accurate simulation than three-parametric Weibull function; (2 the parameters p, q and r of R distribution proved to be its scale, location and shape parameters, and have a deep relationship with stand characteristics, which means the parameters of R distribution have good theoretical interpretation; (3 the ordinate of inflection point of R distribution has significant relativity with its skewness and kurtosis, and the fitted main distribution range for the cumulative diameter distribution of Chinese fir plantations was 0.4∼0.6; (4 the goodness-of-fit test showed diameter distributions of unknown stands can be well estimated by applying R distribution based on PRM or the combination of PPM and PRM under the condition that only quadratic mean DBH or plus stand age are known, and the non-rejection rates were near 80%, which are higher than the 72.33% non-rejection rate of three-parametric Weibull function based on the combination of PPM and PRM.
Stand diameter distribution modelling and prediction based on Richards function.
Duan, Ai-guo; Zhang, Jian-guo; Zhang, Xiong-qing; He, Cai-yun
2013-01-01
The objective of this study was to introduce application of the Richards equation on modelling and prediction of stand diameter distribution. The long-term repeated measurement data sets, consisted of 309 diameter frequency distributions from Chinese fir (Cunninghamia lanceolata) plantations in the southern China, were used. Also, 150 stands were used as fitting data, the other 159 stands were used for testing. Nonlinear regression method (NRM) or maximum likelihood estimates method (MLEM) were applied to estimate the parameters of models, and the parameter prediction method (PPM) and parameter recovery method (PRM) were used to predict the diameter distributions of unknown stands. Four main conclusions were obtained: (1) R distribution presented a more accurate simulation than three-parametric Weibull function; (2) the parameters p, q and r of R distribution proved to be its scale, location and shape parameters, and have a deep relationship with stand characteristics, which means the parameters of R distribution have good theoretical interpretation; (3) the ordinate of inflection point of R distribution has significant relativity with its skewness and kurtosis, and the fitted main distribution range for the cumulative diameter distribution of Chinese fir plantations was 0.4∼0.6; (4) the goodness-of-fit test showed diameter distributions of unknown stands can be well estimated by applying R distribution based on PRM or the combination of PPM and PRM under the condition that only quadratic mean DBH or plus stand age are known, and the non-rejection rates were near 80%, which are higher than the 72.33% non-rejection rate of three-parametric Weibull function based on the combination of PPM and PRM.
Plant functional type mapping for earth system models
Directory of Open Access Journals (Sweden)
B. Poulter
2011-11-01
Full Text Available The sensitivity of global carbon and water cycling to climate variability is coupled directly to land cover and the distribution of vegetation. To investigate biogeochemistry-climate interactions, earth system models require a representation of vegetation distributions that are either prescribed from remote sensing data or simulated via biogeography models. However, the abstraction of earth system state variables in models means that data products derived from remote sensing need to be post-processed for model-data assimilation. Dynamic global vegetation models (DGVM rely on the concept of plant functional types (PFT to group shared traits of thousands of plant species into usually only 10–20 classes. Available databases of observed PFT distributions must be relevant to existing satellite sensors and their derived products, and to the present day distribution of managed lands. Here, we develop four PFT datasets based on land-cover information from three satellite sensors (EOS-MODIS 1 km and 0.5 km, SPOT4-VEGETATION 1 km, and ENVISAT-MERIS 0.3 km spatial resolution that are merged with spatially-consistent Köppen-Geiger climate zones. Using a beta (ß diversity metric to assess reclassification similarity, we find that the greatest uncertainty in PFT classifications occur most frequently between cropland and grassland categories, and in dryland systems between shrubland, grassland and forest categories because of differences in the minimum threshold required for forest cover. The biogeography-biogeochemistry DGVM, LPJmL, is used in diagnostic mode with the four PFT datasets prescribed to quantify the effect of land-cover uncertainty on climatic sensitivity of gross primary productivity (GPP and transpiration fluxes. Our results show that land-cover uncertainty has large effects in arid regions, contributing up to 30% (20% uncertainty in the sensitivity of GPP (transpiration to precipitation. The availability of PFT datasets that are consistent
Empirical evaluation of scoring functions for Bayesian network model selection.
Liu, Zhifa; Malone, Brandon; Yuan, Changhe
2012-01-01
In this work, we empirically evaluate the capability of various scoring functions of Bayesian networks for recovering true underlying structures. Similar investigations have been carried out before, but they typically relied on approximate learning algorithms to learn the network structures. The suboptimal structures found by the approximation methods have unknown quality and may affect the reliability of their conclusions. Our study uses an optimal algorithm to learn Bayesian network structures from datasets generated from a set of gold standard Bayesian networks. Because all optimal algorithms always learn equivalent networks, this ensures that only the choice of scoring function affects the learned networks. Another shortcoming of the previous studies stems from their use of random synthetic networks as test cases. There is no guarantee that these networks reflect real-world data. We use real-world data to generate our gold-standard structures, so our experimental design more closely approximates real-world situations. A major finding of our study suggests that, in contrast to results reported by several prior works, the Minimum Description Length (MDL) (or equivalently, Bayesian information criterion (BIC)) consistently outperforms other scoring functions such as Akaike's information criterion (AIC), Bayesian Dirichlet equivalence score (BDeu), and factorized normalized maximum likelihood (fNML) in recovering the underlying Bayesian network structures. We believe this finding is a result of using both datasets generated from real-world applications rather than from random processes used in previous studies and learning algorithms to select high-scoring structures rather than selecting random models. Other findings of our study support existing work, e.g., large sample sizes result in learning structures closer to the true underlying structure; the BDeu score is sensitive to the parameter settings; and the fNML performs pretty well on small datasets. We also
Bidirectional texture function modeling: a state of the art survey.
Filip, Jirí; Haindl, Michal
2009-11-01
An ever-growing number of real-world computer vision applications require classification, segmentation, retrieval, or realistic rendering of genuine materials. However, the appearance of real materials dramatically changes with illumination and viewing variations. Thus, the only reliable representation of material visual properties requires capturing of its reflectance in as wide range of light and camera position combinations as possible. This is a principle of the recent most advanced texture representation, the Bidirectional Texture Function (BTF). Multispectral BTF is a seven-dimensional function that depends on view and illumination directions as well as on planar texture coordinates. BTF is typically obtained by measurement of thousands of images covering many combinations of illumination and viewing angles. However, the large size of such measurements has prohibited their practical exploitation in any sensible application until recently. During the last few years, the first BTF measurement, compression, modeling, and rendering methods have emerged. In this paper, we categorize, critically survey, and psychophysically compare such approaches, which were published in this newly arising and important computer vision and graphics area.
Drosophila provides rapid modeling of renal development, function, and disease.
Dow, Julian A T; Romero, Michael F
2010-12-01
The evolution of specialized excretory cells is a cornerstone of the metazoan radiation, and the basic tasks performed by Drosophila and human renal systems are similar. The development of the Drosophila renal (Malpighian) tubule is a classic example of branched tubular morphogenesis, allowing study of mesenchymal-to-epithelial transitions, stem cell-mediated regeneration, and the evolution of a glomerular kidney. Tubule function employs conserved transport proteins, such as the Na(+), K(+)-ATPase and V-ATPase, aquaporins, inward rectifier K(+) channels, and organic solute transporters, regulated by cAMP, cGMP, nitric oxide, and calcium. In addition to generation and selective reabsorption of primary urine, the tubule plays roles in metabolism and excretion of xenobiotics, and in innate immunity. The gene expression resource FlyAtlas.org shows that the tubule is an ideal tissue for the modeling of renal diseases, such as nephrolithiasis and Bartter syndrome, or for inborn errors of metabolism. Studies are assisted by uniquely powerful genetic and transgenic resources, the widespread availability of mutant stocks, and low-cost, rapid deployment of new transgenics to allow manipulation of renal function in an organotypic context.
Homology Modeling: Generating Structural Models to Understand Protein Function and Mechanism
Ramachandran, Srinivas; Dokholyan, Nikolay V.
Geneticists and molecular and cell biologists routinely uncover new proteins important in specific biological processes/pathways. However, either the molecular functions or the functional mechanisms of many of these proteins are unclear due to a lack of knowledge of their atomic structures. Yet, determining experimental structures of many proteins presents technical challenges. The current methods for obtaining atomic-resolution structures of biomolecules (X-ray crystallography and NMR spectroscopy) require pure preparations of proteins at concentrations much higher than those at which the proteins exist in a physiological environment. Additionally, NMR has size limitations, with current technology limited to the determination of structures of proteins with masses of up to 15 kDa. Due to these reasons, atomic structures of many medically and biologically important proteins do not exist. However, the structures of these proteins are essential for several purposes, including in silico drug design [1], understanding the effects of disease mutations [2], and designing experiments to probe the functional mechanisms of proteins. Comparative modeling has gained importance as a tool for bridging the gap between sequence and structure space, allowing researchers to build structural models of proteins that are difficult to crystallize or for which structure determination by NMR spectroscopy is not tractable. Comparative modeling, or homology modeling, exploits the fact that two proteins whose sequences are evolutionarily connected display similar structural features [3]. Thus, the known structure of a protein (template) can be used to generate a molecular model of the protein (query) whose experimental structure is notknown.
Applying the luminosity function statistics in the fireshell model
Rangel Lemos, L. J.; Bianco, C. L.; Ruffini, R.
2015-12-01
The luminosity function (LF) statistics applied to the data of BATSE, GBM/Fermi and BAT/Swift is the theme approached in this work. The LF is a strong statistical tool to extract useful information from astrophysical samples, and the key point of this statistical analysis is in the detector sensitivity, where we have performed careful analysis. We applied the tool of the LF statistics to three GRB classes predicted by the Fireshell model. We produced, by LF statistics, predicted distributions of: peak ux N(Fph pk), redshift N(z) and peak luminosity N(Lpk) for the three GRB classes predicted by Fireshell model; we also used three GRB rates. We looked for differences among the distributions, and in fact we found. We performed a comparison between the distributions predicted and observed (with and without redshifts), where we had to build a list with 217 GRBs with known redshifts. Our goal is transform the GRBs in a standard candle, where a alternative is find a correlation between the isotropic luminosity and the Band peak spectral energy (Liso - Epk).
Databases, models, and algorithms for functional genomics: a bioinformatics perspective.
Singh, Gautam B; Singh, Harkirat
2005-02-01
A variety of patterns have been observed on the DNA and protein sequences that serve as control points for gene expression and cellular functions. Owing to the vital role of such patterns discovered on biological sequences, they are generally cataloged and maintained within internationally shared databases. Furthermore,the variability in a family of observed patterns is often represented using computational models in order to facilitate their search within an uncharacterized biological sequence. As the biological data is comprised of a mosaic of sequence-levels motifs, it is significant to unravel the synergies of macromolecular coordination utilized in cell-specific differential synthesis of proteins. This article provides an overview of the various pattern representation methodologies and the surveys the pattern databases available for use to the molecular biologists. Our aim is to describe the principles behind the computational modeling and analysis techniques utilized in bioinformatics research, with the objective of providing insight necessary to better understand and effectively utilize the available databases and analysis tools. We also provide a detailed review of DNA sequence level patterns responsible for structural conformations within the Scaffold or Matrix Attachment Regions (S/MARs).
Stochastic analysis of response functions in environmental modeling
Energy Technology Data Exchange (ETDEWEB)
Tumeo, M.A.
1988-01-01
Development of a new mathematical technique to include stochasticity in environmental models used of resource management and public health risk analysis is reported. The technique is based on the expansion of basic governing equations to include stochastic terms. The stochastic terms are then separated from the non-fluctuating terms, and the resulting set of equations solved simultaneously. The solutions of this set of equations are used to calculate the moments of the output variables. In addition, the moments are used in conjunction with the Fokker-Planck Equation to produce an analytical solution for the probability density functions of the dependent variables. The technique is applied in two examples. The first example is an application to the Streeter-Phelps BOD-OD Equations. Results of the analysis are compared to field data as well as to results of a Monte Carlo model and to moments derived using a Stochastic Differential Equations approach. The second application involves analysis of health risks associated with waterborne diseases. Results are compared to the results of a Monte Carlo simulation of a similar system of equations.
Neocaridina denticulata: A Decapod Crustacean Model for Functional Genomics.
Mykles, Donald L; Hui, Jerome H L
2015-11-01
A decapod crustacean model is needed for understanding the molecular mechanisms underlying physiological processes, such as reproduction, sex determination, molting and growth, immunity, regeneration, and response to stress. Criteria for selection are: life-history traits, adult size, availability and ease of culture, and genomics and genetic manipulation. Three freshwater species are considered: cherry shrimp, Neocaridina denticulata; red swamp crayfish, Procambarus clarkii; and redclaw crayfish, Cherax quadricarinatus. All three are readily available, reproduce year round, and grow rapidly. The crayfish species require more space for culture than does N. denticulata. The transparent cuticle of cherry shrimp provides for direct assessment of reproductive status, stage of molt, and tissue-specific expression of reporter genes, and facilitates screening of mutations affecting phenotype. Moreover, a preliminary genome of N. denticulata is available and efforts toward complete genome sequencing and transcriptome sequencing have been initiated. Neocaridina denticulata possesses the best combination of traits that make it most suitable as a model for functional genomics. The next step is to obtain the complete genome sequence and to develop molecular technologies for the screening of mutants and for manipulating tissue-specific gene expression.
Functional renormalization for antiferromagnetism and superconductivity in the Hubbard model
Energy Technology Data Exchange (ETDEWEB)
Friederich, Simon
2010-12-08
Despite its apparent simplicity, the two-dimensional Hubbard model for locally interacting fermions on a square lattice is widely considered as a promising approach for the understanding of Cooper pair formation in the quasi two-dimensional high-T{sub c} cuprate materials. In the present work this model is investigated by means of the functional renormalization group, based on an exact flow equation for the effective average action. In addition to the fermionic degrees of freedom of the Hubbard Hamiltonian, bosonic fields are introduced which correspond to the different possible collective orders of the system, for example magnetism and superconductivity. The interactions between bosons and fermions are determined by means of the method of ''rebosonization'' (or ''flowing bosonization''), which can be described as a continuous, scale-dependent Hubbard-Stratonovich transformation. This method allows an efficient parameterization of the momentum-dependent effective two-particle interaction between fermions (four-point vertex), and it makes it possible to follow the flow of the running couplings into the regimes exhibiting spontaneous symmetry breaking, where bosonic fluctuations determine the types of order which are present on large length scales. Numerical results for the phase diagram are presented, which include the mutual influence of different, competing types of order. (orig.)
Function of Hexagenia (Mayfly) Burrows: Fluid Model Suggests Bacterial Gardening
Traynham, B.; Furbish, D.; Miller, M.; White, D.
2006-12-01
Lake and stream bottoms experience an array of physical, chemical, and biological processes that create spatial variations both in the fluid column and in the sediment that provide a physical template for distinct niches. Burrowing insects are major ecological engineers of communities where they structure large areas of the benthic habitat through bioturbation and other activities including respiration, feeding, and defecation. The burrowing mayfly Hexagenia, when present in high densities, has a large impact on food-web dynamics and provides essential ecosystem services within the fluid column and benthic substrate, including sediment mixing, nutrient cycling, and ultimately, energy flow through the freshwater food web. It has long been recognized that particular benthic species are important in linking detrital energy resources to higher trophic levels and for determining how organic matter is processed in freshwater ecosystems; however, the unique contributions made by individual benthic species is largely absent from the literature. Here we present a model that describes the structure and function of a Hexagenia burrow. If testing supports this hypothesis, the model suggests that when high food concentration is available to Hexagenia, there exists a favorable tube length for harvesting bacteria that grow on the burrow walls. The burrow microhabitat created by Hexagenia serves as a case-study in understanding the influence of benthic burrowers on both energy flow through freshwater food webs and nutrient cycling.
Simple analytic functions for modeling three-dimensional flow in layered aquifers
Fitts, Charles R.
1989-05-01
Analytic functions are presented for modeling three-dimensional steady groundwater flow in stratified aquifers. The functions create discontinuity in the potential across an infinite plane while maintaining continuity of the potential gradient across the plane. These functions may be superimposed with other analytic functions to model three-dimensional flow in stratified aquifers under a variety of boundary conditions. An interface between two layers of different hydraulic conductivity, an impermeable boundary, or a thin leaky layer may be modeled using such functions. These functions are simple compared to functions for doublet distributions over finite plane panels and are suitable for efficient modeling.
DEFF Research Database (Denmark)
Rytter, Hana Malá; Mogensen, Jesper
The REF (Reorganization of Elementary Functions) model suggests mechanisms of posttraumatic reorganization, and resolves the contradiction between localization and functional recovery. In the process of developing this model, we have reconceptualised the term ‘function’ and introduced a concept...
Passive Remote Sensing of Oceanic Whitecaps: Updated Geophysical Model Function
Anguelova, M. D.; Bettenhausen, M. H.; Johnston, W.; Gaiser, P. W.
2016-12-01
Many air-sea interaction processes are quantified in terms of whitecap fraction W because oceanic whitecaps are the most visible and direct way of observing breaking of wind waves in the open ocean. Enhanced by breaking waves, surface fluxes of momentum, heat, and mass are critical for ocean-atmosphere coupling and thus affect the accuracy of models used to forecast weather, predict storm intensification, and study climate change. Whitecap fraction has been traditionally measured from photographs or video images collected from towers, ships, and aircrafts. Satellite-based passive remote sensing of whitecap fraction is a recent development that allows long term, consistent observations of whitecapping on a global scale. The method relies on changes of ocean surface emissivity at microwave frequencies (e.g., 6 to 37 GHz) due to presence of sea foam on a rough sea surface. These changes at the ocean surface are observed from the satellite as brightness temperature TB. A year-long W database built with this algorithm has proven useful in analyzing and quantifying the variability of W, as well as estimating fluxes of CO2 and sea spray production. The algorithm to obtain W from satellite observations of TB was developed at the Naval Research Laboratory within the framework of WindSat mission. The W(TB) algorithm estimates W by minimizing the differences between measured and modeled TB data. A geophysical model function (GMF) calculates TB at the top of the atmosphere as contributions from the atmosphere and the ocean surface. The ocean surface emissivity combines the emissivity of rough sea surface and the emissivity of areas covered with foam. Wind speed and direction, sea surface temperature, water vapor, and cloud liquid water are inputs to the atmospheric, roughness and foam models comprising the GMF. The W(TB) algorithm has been recently updated to use new sources and products for the input variables. We present new version of the W(TB) algorithm that uses updated
Annotation and retrieval system of CAD models based on functional semantics
Wang, Zhansong; Tian, Ling; Duan, Wenrui
2014-11-01
CAD model retrieval based on functional semantics is more significant than content-based 3D model retrieval during the mechanical conceptual design phase. However, relevant research is still not fully discussed. Therefore, a functional semantic-based CAD model annotation and retrieval method is proposed to support mechanical conceptual design and design reuse, inspire designer creativity through existing CAD models, shorten design cycle, and reduce costs. Firstly, the CAD model functional semantic ontology is constructed to formally represent the functional semantics of CAD models and describe the mechanical conceptual design space comprehensively and consistently. Secondly, an approach to represent CAD models as attributed adjacency graphs(AAG) is proposed. In this method, the geometry and topology data are extracted from STEP models. On the basis of AAG, the functional semantics of CAD models are annotated semi-automatically by matching CAD models that contain the partial features of which functional semantics have been annotated manually, thereby constructing CAD Model Repository that supports model retrieval based on functional semantics. Thirdly, a CAD model retrieval algorithm that supports multi-function extended retrieval is proposed to explore more potential creative design knowledge in the semantic level. Finally, a prototype system, called Functional Semantic-based CAD Model Annotation and Retrieval System(FSMARS), is implemented. A case demonstrates that FSMARS can successfully botain multiple potential CAD models that conform to the desired function. The proposed research addresses actual needs and presents a new way to acquire CAD models in the mechanical conceptual design phase.
Annotation and Retrieval System of CAD Models Based on Functional Semantics
Institute of Scientific and Technical Information of China (English)
WANG Zhansong; TIAN Ling; DUAN Wenrui
2014-01-01
CAD model retrieval based on functional semantics is more significant than content-based 3D model retrieval during the mechanical conceptual design phase. However, relevant research is still not fully discussed. Therefore, a functional semantic-based CAD model annotation and retrieval method is proposed to support mechanical conceptual design and design reuse, inspire designer creativity through existing CAD models, shorten design cycle, and reduce costs. Firstly, the CAD model functional semantic ontology is constructed to formally represent the functional semantics of CAD models and describe the mechanical conceptual design space comprehensively and consistently. Secondly, an approach to represent CAD models as attributed adjacency graphs(AAG) is proposed. In this method, the geometry and topology data are extracted from STEP models. On the basis of AAG, the functional semantics of CAD models are annotated semi-automatically by matching CAD models that contain the partial features of which functional semantics have been annotated manually, thereby constructing CAD Model Repository that supports model retrieval based on functional semantics. Thirdly, a CAD model retrieval algorithm that supports multi-function extended retrieval is proposed to explore more potential creative design knowledge in the semantic level. Finally, a prototype system, called Functional Semantic-based CAD Model Annotation and Retrieval System(FSMARS), is implemented. A case demonstrates that FSMARS can successfully botain multiple potential CAD models that conform to the desired function. The proposed research addresses actual needs and presents a new way to acquire CAD models in the mechanical conceptual design phase.
New model of load transfer function for pile analysis based on disturbed state model
Institute of Scientific and Technical Information of China (English)
LIU Qijian; YANG Linde; WU Jun
2007-01-01
Based on the disturbed state concept (DSC),a new model of load transfer function for pile analysis is established by the idea that the deformed material between pile and soil can be treated as a mixture of two constituent parts,which are in intact or critical state and assumed to obey random distribution.Starting from the homogenization theory of heterogeneous materials and statistics method,a parameter D to describe the disturbance degree is proposed,and a formula to determine the parameter has been derived by using the plastic displacement of a pile as distribution variable.In the model,shear intensity of elements in an intact state are simulated by Duncan-Zhang model and that in a critical state by Mohr-Coulomb criterion.The model of this paper has few parameters,which can reflect the aspects of load transfer function,such as hardening,softening and the effects of confining pressure.The well agreement between the in-situ data and the predicted shows that the validity of the model herein.So the proposed model in this paper is easy to be used in engineering practice.
Bethea, Cynthia L; Kim, Aaron; Cameron, Judy L
2013-02-01
A body of knowledge implicates an increase in output from the locus ceruleus (LC) during stress. We questioned the innervation and function of the LC in our macaque model of Functional Hypothalamic Amenorrhea, also known as Stress-Induced Amenorrhea. Cohorts of macaques were initially characterized as highly stress resilient (HSR) or stress-sensitive (SS) based upon the presence or absence of ovulation during a protocol involving 2 menstrual cycles with psychosocial and metabolic stress. Afterwards, the animals were rested until normal menstrual cycles resumed and then euthanized on day 5 of a new menstrual cycle [a] in the absence of further stress; or [b] after 5 days of resumed psychosocial and metabolic stress. In this study, parameters of the LC were examined in HSR and SS animals in the presence and absence of stress (2×2 block design) using ICC and image analysis. Tyrosine hydroxylase (TH) is the rate-limiting enzyme for the synthesis of catecholamines; and the TH level was used to assess by inference, NE output. The pixel area of TH-positive dendrites extending outside the medial border of the LC was significantly increased by stress to a similar degree in both HSR and SS animals (p<0.0001). There is a significant CRF innervation of the LC. The positive pixel area of CRF boutons, lateral to the LC, was higher in SS than HSR animals in the absence of stress. Five days of moderate stress significantly increased the CRF-positive bouton pixel area in the HSR group (p<0.02), but not in the SS group. There is also a significant serotonin innervation of the LC. A marked increase in medial serotonin dendrite swelling and beading was observed in the SS+stress group, which may be a consequence of excitotoxicity. The dendrite beading interfered with analysis of axonal boutons. However, at one anatomical level, the serotonin-positive bouton area was obtained between the LC and the superior cerebellar peduncle. Serotonin-positive bouton pixel area was significantly
GSK-3: functional insights from cell biology and animal models
Directory of Open Access Journals (Sweden)
Oksana eKaidanovich-Beilin
2011-11-01
Full Text Available Glycogen synthase kinase-3 (GSK-3 is a widely expressed and highly conserved serine/threonine protein kinase encoded in mammals by two genes that generate two related proteins: GSK-3α and GSK-3β. GSK-3 is active in cells under resting conditions and is primarily regulated through inhibition or diversion of its activity. While GSK-3 is one of the few protein kinases that can be inactivated by phosphorylation, the mechanisms of GSK-3 regulation are more varied and not fully understood. Precise control appears to be achieved by a combination of phosphorylation, localization, and sequestration by a number of GSK-3-binding proteins. GSK-3 lies downstream of several major signaling pathways including the phosphatidylinositol 3’ kinase pathway, the Wnt pathway, Hedgehog signaling and Notch. Specific pools of GSK-3, which differ in intracellular localization, binding partner affinity and relative amount are differentially sensitized to several distinct signaling pathways and these sequestration mechanisms contribute to pathway insulation and signal specificity. Dysregulation of signaling pathways involving GSK-3 is associated with the pathogenesis of numerous neurological and psychiatric disorders and there are data suggesting GSK-3 isoform-selective roles in several of these. Here, we review the current knowledge of GSK-3 regulation and targets and discuss the various animal models that have been employed to dissect the functions of GSK-3 in brain development and function through the use of conventional or conditional knock-out mice as well as transgenic mice. These studies have revealed fundamental roles for these protein kinases in memory, behavior and neuronal fate determination and provide insights into possible therapeutic interventions.
Wang, Pengwei; Wang, Zhishun; He, Lianghua
2012-03-30
Functional Magnetic Resonance Imaging (fMRI), measuring Blood Oxygen Level-Dependent (BOLD), is a widely used tool to reveal spatiotemporal pattern of neural activity in human brain. Standard analysis of fMRI data relies on a general linear model and the model is constructed by convolving the task stimuli with a hypothesized hemodynamic response function (HRF). To capture possible phase shifts in the observed BOLD response, the informed basis functions including canonical HRF and its temporal derivative, have been proposed to extend the hypothesized hemodynamic response in order to obtain a good fitting model. Different t contrasts are constructed from the estimated model parameters for detecting the neural activity between different task conditions. However, the estimated model parameters corresponding to the orthogonal basis functions have different physical meanings. It remains unclear how to combine the neural features detected by the two basis functions and construct t contrasts for further analyses. In this paper, we have proposed a novel method for representing multiple basis functions in complex domain to model the task-driven fMRI data. Using this method, we can treat each pair of model parameters, corresponding respectively to canonical HRF and its temporal derivative, as one complex number for each task condition. Using the specific rule we have defined, we can conveniently perform arithmetical operations on the estimated model parameters and generate different t contrasts. We validate this method using the fMRI data acquired from twenty-two healthy participants who underwent an auditory stimulation task.
From Boolean Network Model to Continuous Model Helps in Design of Functional Circuits
Zhang, Dongliang; Wu, Jiayi; Ouyang, Qi
2015-01-01
Computational circuit design with desired functions in a living cell is a challenging task in synthetic biology. To achieve this task, numerous methods that either focus on small scale networks or use evolutionary algorithms have been developed. Here, we propose a two-step approach to facilitate the design of functional circuits. In the first step, the search space of possible topologies for target functions is reduced by reverse engineering using a Boolean network model. In the second step, continuous simulation is applied to evaluate the performance of these topologies. We demonstrate the usefulness of this method by designing an example biological function: the SOS response of E. coli. Our numerical results show that the desired function can be faithfully reproduced by candidate networks with different parameters and initial conditions. Possible circuits are ranked according to their robustness against perturbations in parameter and gene expressions. The biological network is among the candidate networks, yet novel designs can be generated. Our method provides a scalable way to design robust circuits that can achieve complex functions, and makes it possible to uncover design principles of biological networks. PMID:26061094
Application of Gaussian Process Modeling to Analysis of Functional Unreliability
Energy Technology Data Exchange (ETDEWEB)
R. Youngblood
2014-06-01
This paper applies Gaussian Process (GP) modeling to analysis of the functional unreliability of a “passive system.” GPs have been used widely in many ways [1]. The present application uses a GP for emulation of a system simulation code. Such an emulator can be applied in several distinct ways, discussed below. All applications illustrated in this paper have precedents in the literature; the present paper is an application of GP technology to a problem that was originally analyzed [2] using neural networks (NN), and later [3, 4] by a method called “Alternating Conditional Expectations” (ACE). This exercise enables a multifaceted comparison of both the processes and the results. Given knowledge of the range of possible values of key system variables, one could, in principle, quantify functional unreliability by sampling from their joint probability distribution, and performing a system simulation for each sample to determine whether the function succeeded for that particular setting of the variables. Using previously available system simulation codes, such an approach is generally impractical for a plant-scale problem. It has long been recognized, however, that a well-trained code emulator or surrogate could be used in a sampling process to quantify certain performance metrics, even for plant-scale problems. “Response surfaces” were used for this many years ago. But response surfaces are at their best for smoothly varying functions; in regions of parameter space where key system performance metrics may behave in complex ways, or even exhibit discontinuities, response surfaces are not the best available tool. This consideration was one of several that drove the work in [2]. In the present paper, (1) the original quantification of functional unreliability using NN [2], and later ACE [3], is reprised using GP; (2) additional information provided by the GP about uncertainty in the limit surface, generally unavailable in other representations, is discussed
A modelling framework to simulate foliar fungal epidemics using functional-structural plant models.
Garin, Guillaume; Fournier, Christian; Andrieu, Bruno; Houlès, Vianney; Robert, Corinne; Pradal, Christophe
2014-09-01
Sustainable agriculture requires the identification of new, environmentally responsible strategies of crop protection. Modelling of pathosystems can allow a better understanding of the major interactions inside these dynamic systems and may lead to innovative protection strategies. In particular, functional-structural plant models (FSPMs) have been identified as a means to optimize the use of architecture-related traits. A current limitation lies in the inherent complexity of this type of modelling, and thus the purpose of this paper is to provide a framework to both extend and simplify the modelling of pathosystems using FSPMs. Different entities and interactions occurring in pathosystems were formalized in a conceptual model. A framework based on these concepts was then implemented within the open-source OpenAlea modelling platform, using the platform's general strategy of modelling plant-environment interactions and extending it to handle plant interactions with pathogens. New developments include a generic data structure for representing lesions and dispersal units, and a series of generic protocols to communicate with objects representing the canopy and its microenvironment in the OpenAlea platform. Another development is the addition of a library of elementary models involved in pathosystem modelling. Several plant and physical models are already available in OpenAlea and can be combined in models of pathosystems using this framework approach. Two contrasting pathosystems are implemented using the framework and illustrate its generic utility. Simulations demonstrate the framework's ability to simulate multiscaled interactions within pathosystems, and also show that models are modular components within the framework and can be extended. This is illustrated by testing the impact of canopy architectural traits on fungal dispersal. This study provides a framework for modelling a large number of pathosystems using FSPMs. This structure can accommodate both
A quantitative confidence signal detection model: 1. Fitting psychometric functions.
Yi, Yongwoo; Merfeld, Daniel M
2016-04-01
Perceptual thresholds are commonly assayed in the laboratory and clinic. When precision and accuracy are required, thresholds are quantified by fitting a psychometric function to forced-choice data. The primary shortcoming of this approach is that it typically requires 100 trials or more to yield accurate (i.e., small bias) and precise (i.e., small variance) psychometric parameter estimates. We show that confidence probability judgments combined with a model of confidence can yield psychometric parameter estimates that are markedly more precise and/or markedly more efficient than conventional methods. Specifically, both human data and simulations show that including confidence probability judgments for just 20 trials can yield psychometric parameter estimates that match the precision of those obtained from 100 trials using conventional analyses. Such an efficiency advantage would be especially beneficial for tasks (e.g., taste, smell, and vestibular assays) that require more than a few seconds for each trial, but this potential benefit could accrue for many other tasks. Copyright © 2016 the American Physiological Society.
Dicentric chromosomes: unique models to study centromere function and inactivation.
Stimpson, Kaitlin M; Matheny, Justyne E; Sullivan, Beth A
2012-07-01
Dicentric chromosomes are products of genome rearrangement that place two centromeres on the same chromosome. Depending on the organism, dicentric stability varies after formation. In humans, dicentrics occur naturally in a substantial portion of the population and usually segregate successfully in mitosis and meiosis. Their stability has been attributed to inactivation of one of the two centromeres, creating a functionally monocentric chromosome that can segregate normally during cell division. The molecular basis for centromere inactivation is not well understood, although studies in model organisms and in humans suggest that genomic and epigenetic mechanisms can be involved. Furthermore, constitutional dicentric chromosomes ascertained in patients presumably represent the most stable chromosomes, so the spectrum of dicentric fates, if it exists, is not entirely clear. Studies of engineered or induced dicentrics in budding yeast and plants have provided significant insight into the fate of dicentric chromosomes. And, more recently, studies have shown that dicentrics in humans can also undergo multiple fates after formation. Here, we discuss current experimental evidence from various organisms that has deepened our understanding of dicentric behavior and the intriguingly complex process of centromere inactivation.
Evaluation of Rational Function Model for Geometric Modeling of CHANG'E-1 CCD Images
Liu, Y.; Di, K.
2011-08-01
Rational Function Model (RFM) is a generic geometric model that has been widely used in geometric processing of high-resolution earth-observation satellite images, due to its generality and excellent capability of fitting complex rigorous sensor models. In this paper, the feasibility and precision of RFM for geometric modeling of China's Chang'E-1 (CE-1) lunar orbiter images is presented. The RFM parameters of forward-, nadir- and backward-looking CE-1 images are generated though least squares solution using virtual control points derived from the rigorous sensor model. The precision of the RFM is evaluated by comparing with the rigorous sensor model in both image space and object space. Experimental results using nine images from three orbits show that RFM can precisely fit the rigorous sensor model of CE-1 CCD images with a RMS residual error of 1/100 pixel level in image space and less than 5 meters in object space. This indicates that it is feasible to use RFM to describe the imaging geometry of CE-1 CCD images and spacecraft position and orientation. RFM will enable planetary data centers to have an option to supply RFM parameters of orbital images while keeping the original orbit trajectory data confidential.
EFFICIENCY MODELS OF THE CROSS-FUNCTIONAL TEAMS
Dinca Laura; Criveanu Radu
2013-01-01
Cross-functional teams represent a characteristic of the new organization form of the enterprises, imposed by the complexity of the present environment. Regardless their kind, the new organization forms are based on the cross-functional teams as an innovation source and reunion of competences. Only by the medium of the cross-functional teams, the new organizational partnerships obtain flexibility in their actions and fastness in their reactions. By their features, the cross-functional teams s...
Tumthong, Suwut; Piriyasurawong, Pullop; Jeerangsuwan, Namon
2016-01-01
This research proposes a functional competency development model for academic personnel based on international professional qualification standards in computing field and examines the appropriateness of the model. Specifically, the model consists of three key components which are: 1) functional competency development model, 2) blended training…
Bioinorganic Chemistry Modeled with the TPSSh Density Functional
DEFF Research Database (Denmark)
Kepp, Kasper Planeta
2008-01-01
In this work, the TPSSh density functional has been benchmarked against a test set of experimental structures and bond energies for 80 transition-metal-containing diatomics. It is found that the TPSSh functional gives structures of the same quality as other commonly used hybrid and nonhybrid func...... promising density functional for use and further development within the field of bioinorganic chemistry....
Goldstein, Harvey; Leckie, George; Charlton, Christopher; Tilling, Kate; Browne, William J
2017-01-01
Aim To present a flexible model for repeated measures longitudinal growth data within individuals that allows trends over time to incorporate individual-specific random effects. These may reflect the timing of growth events and characterise within-individual variability which can be modelled as a function of age. Subjects and methods A Bayesian model is developed that includes random effects for the mean growth function, an individual age-alignment random effect and random effects for the within-individual variance function. This model is applied to data on boys' heights from the Edinburgh longitudinal growth study and to repeated weight measurements of a sample of pregnant women in the Avon Longitudinal Study of Parents and Children cohort. Results The mean age at which the growth curves for individual boys are aligned is 11.4 years, corresponding to the mean 'take off' age for pubertal growth. The within-individual variance (standard deviation) is found to decrease from 0.24 cm(2) (0.50 cm) at 9 years for the 'average' boy to 0.07 cm(2) (0.25 cm) at 16 years. Change in weight during pregnancy can be characterised by regression splines with random effects that include a large woman-specific random effect for the within-individual variation, which is also correlated with overall weight and weight gain. Conclusions The proposed model provides a useful extension to existing approaches, allowing considerable flexibility in describing within- and between-individual differences in growth patterns.
Universal triple I fuzzy reasoning algorithm of function model based on quotient space
Institute of Scientific and Technical Information of China (English)
Lu Qiang; Shen Guanting; and Liu Xiaoping
2012-01-01
Aiming at the deficiencies of analysis capacity from different levels and fuzzy treating method in product function modeling of conceptual design, the theory of quotient space and universal triple I fuzzy reasoning method are introduced, and then the function modeling algorithm based on the universal triple I fuzzy reasoning method is proposed. Firstly, the product function granular model based on the quotient space theory is built, with its function granular representation and computing rules defined at the same time. Secondly, in order to quickly achieve function granular model from function requirement, the function modeling method based on universal triple I fuzzy reasoning is put forward. Within the fuzzy reasoning of universal triple I method, the small-distance-activating method is proposed as the kernel of fuzzy reasoning; how to change function requirements to fuzzy ones, fuzzy computing methods, and strategy of fuzzy reasoning are respectively investigated as well; the function modeling algorithm based on the universal triple I fuzzy reasoning method is achieved. Lastly, the validity of the function granular model and function modeling algorithm is validated. Through our method, the reasonable function granular model can be quickly achieved from function requirements, and the fuzzy character of conceptual design can be well handled, which greatly improves conceptual design.
Goal-Programming Model Based on the Utility Function of the Decision-maker
Institute of Scientific and Technical Information of China (English)
WANG Zhi-jiang
2001-01-01
Based on the analysis of the problems in traditional GP model, this paper provides the model with the utility function of the decision-maker and compares this model with the one presented in reference article [1].
Mitchell, Christine M.
1990-01-01
The design, implementation, and empirical evaluation of task-analytic models and intelligent aids for operators in the control of complex dynamic systems, specifically aerospace systems, are studied. Three related activities are included: (1) the models of operator decision making in complex and predominantly automated space systems were used and developed; (2) the Operator Function Model (OFM) was used to represent operator activities; and (3) Operator Function Model Expert System (OFMspert), a stand-alone knowledge-based system was developed, that interacts with a human operator in a manner similar to a human assistant in the control of aerospace systems. OFMspert is an architecture for an operator's assistant that uses the OFM as its system and operator knowledge base and a blackboard paradigm of problem solving to dynamically generate expectations about upcoming operator activities and interpreting actual operator actions. An experiment validated the OFMspert's intent inferencing capability and showed that it inferred the intentions of operators in ways comparable to both a human expert and operators themselves. OFMspert was also augmented with control capabilities. An interface allowed the operator to interact with OFMspert, delegating as much or as little control responsibility as the operator chose. With its design based on the OFM, OFMspert's control capabilities were available at multiple levels of abstraction and allowed the operator a great deal of discretion over the amount and level of delegated control. An experiment showed that overall system performance was comparable for teams consisting of two human operators versus a human operator and OFMspert team.
Random regression models using different functions to model milk flow in dairy cows.
Laureano, M M M; Bignardi, A B; El Faro, L; Cardoso, V L; Tonhati, H; Albuquerque, L G
2014-09-12
We analyzed 75,555 test-day milk flow records from 2175 primiparous Holstein cows that calved between 1997 and 2005. Milk flow was obtained by dividing the mean milk yield (kg) of the 3 daily milking by the total milking time (min) and was expressed as kg/min. Milk flow was grouped into 43 weekly classes. The analyses were performed using a single-trait Random Regression Models that included direct additive genetic, permanent environmental, and residual random effects. In addition, the contemporary group and linear and quadratic effects of cow age at calving were included as fixed effects. Fourth-order orthogonal Legendre polynomial of days in milk was used to model the mean trend in milk flow. The additive genetic and permanent environmental covariance functions were estimated using random regression Legendre polynomials and B-spline functions of days in milk. The model using a third-order Legendre polynomial for additive genetic effects and a sixth-order polynomial for permanent environmental effects, which contained 7 residual classes, proved to be the most adequate to describe variations in milk flow, and was also the most parsimonious. The heritability in milk flow estimated by the most parsimonious model was of moderate to high magnitude.
Collins fragmentation function for pions and kaons in a spectator model
Energy Technology Data Exchange (ETDEWEB)
Bacchetta, A. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Gamberg, L.P. [Penn State Univ., Berks, PA (United States). Dept. of Physics; Goldstein, G.R. [Tufts Univ., Medford, MA (United States). Dept. of Physics and Astronomy; Mukherjee, A. [Indian Institute of Technology Bombay, Mumbai (India). Physics Dept.
2007-07-15
We calculate the Collins fragmentation function in the framework of a spectator model with pseudoscalar pion-quark coupling and a Gaussian form factor at the vertex. We determine the model parameters by fitting the unpolarized fragmentation function for pions and kaons. We show that the Collins function for the pions in this model is in reasonable agreement with recent parametrizations obtained by fits of the available data. In addition, we compute for the first time the Collins function for the kaons. (orig.)
Kim, Soo Rin; Lee, Ki-Sung; Kong, In Iok; Lesmana, Anastashia; Lee, Won-Heong; Seo, Jin-Ho; Kweon, Dae-Hyuk; Jin, Yong-Su
2013-03-10
Saccharomyces cerevisiae can be engineered for xylose fermentation through introduction of wild type or mutant genes (XYL1/XYL1 (R276H), XYL2, and XYL3) coding for xylose metabolic enzymes from Scheffersomyces stipitis. The resulting engineered strains, however, often yielded undesirable phenotypes such as slow xylose assimilation and xylitol accumulation. In this study, we performed the mating of two engineered strains that exhibit suboptimal xylose-fermenting phenotypes in order to develop an improved xylose-fermenting diploid strain. Specifically, we obtained two engineered haploid strains (YSX3 and SX3). The YSX3 strain consumed xylose rapidly and produced a lot of xylitol. On the contrary, the SX3 strain consumed xylose slowly with little xylitol production. After converting the mating type of SX3 from alpha to a, the resulting strain (SX3-2) was mated with YSX3 to construct a heterozygous diploid strain (KSM). The KSM strain assimilated xylose (0.25gxyloseh(-1)gcells(-1)) as fast as YSX3 and accumulated a small amount of xylitol (0.03ggxylose(-1)) as low as SX3, resulting in an improved ethanol yield (0.27ggxylose(-1)). We found that the improvement in xylose fermentation by the KSM strain was not because of heterozygosity or genome duplication but because of the complementation of the two xylose-metabolic pathways. This result suggested that mating of suboptimal haploid strains is a promising strategy to develop engineered yeast strains with improved xylose fermenting capability.
Benson, A J
2014-01-01
We constrain a highly simplified semi-analytic model of galaxy formation using the $z\\approx 0$ stellar mass function of galaxies. Particular attention is paid to assessing the role of random and systematic errors in the determination of stellar masses, to systematic uncertainties in the model, and to correlations between bins in the measured and modeled stellar mass functions, in order to construct a realistic likelihood function. We derive constraints on model parameters and explore which aspects of the observational data constrain particular parameter combinations. We find that our model, once constrained, provides a remarkable match to the measured evolution of the stellar mass function to $z=1$, although fails dramatically to match the local galaxy HI mass function. Several "nuisance parameters" contribute significantly to uncertainties in model predictions. In particular, systematic errors in stellar mass estimate are the dominant source of uncertainty in model predictions at $z\\approx 1$, with addition...
Crustal structure beneath northeast India inferred from receiver function modeling
Borah, Kajaljyoti; Bora, Dipok K.; Goyal, Ayush; Kumar, Raju
2016-09-01
We estimated crustal shear velocity structure beneath ten broadband seismic stations of northeast India, by using H-Vp/Vs stacking method and a non-linear direct search approach, Neighbourhood Algorithm (NA) technique followed by joint inversion of Rayleigh wave group velocity and receiver function, calculated from teleseismic earthquakes data. Results show significant variations of thickness, shear velocities (Vs) and Vp/Vs ratio in the crust of the study region. The inverted shear wave velocity models show crustal thickness variations of 32-36 km in Shillong Plateau (North), 36-40 in Assam Valley and ∼44 km in Lesser Himalaya (South). Average Vp/Vs ratio in Shillong Plateau is less (1.73-1.77) compared to Assam Valley and Lesser Himalaya (∼1.80). Average crustal shear velocity beneath the study region varies from 3.4 to 3.5 km/s. Sediment structure beneath Shillong Plateau and Assam Valley shows 1-2 km thick sediment layer with low Vs (2.5-2.9 km/s) and high Vp/Vs ratio (1.8-2.1), while it is observed to be of greater thickness (4 km) with similar Vs and high Vp/Vs (∼2.5) in RUP (Lesser Himalaya). Both Shillong Plateau and Assam Valley show thick upper and middle crust (10-20 km), and thin (4-9 km) lower crust. Average Vp/Vs ratio in Assam Valley and Shillong Plateau suggest that the crust is felsic-to-intermediate and intermediate-to-mafic beneath Shillong Plateau and Assam Valley, respectively. Results show that lower crust rocks beneath the Shillong Plateau and Assam Valley lies between mafic granulite and mafic garnet granulite.
Validation of a functional model for integration of safety into process system design
DEFF Research Database (Denmark)
Wu, J.; Lind, M.; Zhang, X.
2015-01-01
Qualitative modeling paradigm offers process systems engineering a potential for developing effective tools for handling issues related to Process Safety. A qualitative functional modeling environment can accommodate different levels of abstraction for capturing knowledge associated...... with the process system functionalities as required for the intended safety applications. To provide the scientific rigor and facilitate the acceptance of qualitative modelling, this contribution focuses on developing a scientifically based validation method for functional models. The Multilevel Flow Modeling (MFM......) methodology is adopted in the paper as a formalized qualitative functional modeling methodology for dynamic process systems. A functional model validation procedure is proposed to assess whether the intended modeling purpose indeed represents a relevant proposal and whether the model represents the system...
Object-oriented models of functionally integrated computer systems
Kaasbøll, Jens
1994-01-01
Functional integration is the compatibility between the structure, culture and competence of an organization and its computer systems, specifically the availability of data and functionality and the consistency of user interfaces. Many people use more than one computer program in their work, and they experience problems relating to functional integration. Various solutions can be considered for different tasks and technology; e.g. to design a common userinterface shell for several application...
Menke, William
2017-02-01
We prove that the problem of inverting Rayleigh wave phase velocity functions c( k ) , where k is wavenumber, for density ρ ( z ) , rigidity μ ( z ) and Lamé parameter λ ( z ) , where z is depth, is fully non-unique, at least in the highly-idealized case where the base Earth model is an isotropic half space. The model functions completely trade off. This is one special case of a common inversion scenario in which one seeks to determine several model functions from a single data function. We explore the circumstances under which this broad class of problems is unique, starting with very simple scenarios, building up to the somewhat more complicated (and common) case where data and model functions are related by convolutions, and then finally, to scale-independent problems (which include the Rayleigh wave problem). The idealized cases that we examine analytically provide insight into the kinds of nonuniqueness that are inherent in the much more complicated problems encountered in modern geophysical imaging (though they do not necessarily provide methods for solving those problems). We also define what is meant by a Backus and Gilbert resolution kernel in this kind of inversion and show under what circumstances a unique localized average of a single model function can be constructed.
Menke, William
2017-04-01
We prove that the problem of inverting Rayleigh wave phase velocity functions c( k ), where k is wavenumber, for density ρ ( z ), rigidity μ ( z ) and Lamé parameter λ ( z ), where z is depth, is fully non-unique, at least in the highly-idealized case where the base Earth model is an isotropic half space. The model functions completely trade off. This is one special case of a common inversion scenario in which one seeks to determine several model functions from a single data function. We explore the circumstances under which this broad class of problems is unique, starting with very simple scenarios, building up to the somewhat more complicated (and common) case where data and model functions are related by convolutions, and then finally, to scale-independent problems (which include the Rayleigh wave problem). The idealized cases that we examine analytically provide insight into the kinds of nonuniqueness that are inherent in the much more complicated problems encountered in modern geophysical imaging (though they do not necessarily provide methods for solving those problems). We also define what is meant by a Backus and Gilbert resolution kernel in this kind of inversion and show under what circumstances a unique localized average of a single model function can be constructed.
Energy Technology Data Exchange (ETDEWEB)
Thienpont, Benedicte; Barata, Carlos [Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA, CSIC), Jordi Girona, 18-26, 08034 Barcelona (Spain); Raldúa, Demetrio, E-mail: drpqam@cid.csic.es [Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA, CSIC), Jordi Girona, 18-26, 08034 Barcelona (Spain); Maladies Rares: Génétique et Métabolisme (MRGM), University of Bordeaux, EA 4576, F-33400 Talence (France)
2013-06-01
Maternal thyroxine (T4) plays an essential role in fetal brain development, and even mild and transitory deficits in free-T4 in pregnant women can produce irreversible neurological effects in their offspring. Women of childbearing age are daily exposed to mixtures of chemicals disrupting the thyroid gland function (TGFDs) through the diet, drinking water, air and pharmaceuticals, which has raised the highest concern for the potential additive or synergic effects on the development of mild hypothyroxinemia during early pregnancy. Recently we demonstrated that zebrafish eleutheroembryos provide a suitable alternative model for screening chemicals impairing the thyroid hormone synthesis. The present study used the intrafollicular T4-content (IT4C) of zebrafish eleutheroembryos as integrative endpoint for testing the hypotheses that the effect of mixtures of TGFDs with a similar mode of action [inhibition of thyroid peroxidase (TPO)] was well predicted by a concentration addition concept (CA) model, whereas the response addition concept (RA) model predicted better the effect of dissimilarly acting binary mixtures of TGFDs [TPO-inhibitors and sodium-iodide symporter (NIS)-inhibitors]. However, CA model provided better prediction of joint effects than RA in five out of the six tested mixtures. The exception being the mixture MMI (TPO-inhibitor)-KClO{sub 4} (NIS-inhibitor) dosed at a fixed ratio of EC{sub 10} that provided similar CA and RA predictions and hence it was difficult to get any conclusive result. There results support the phenomenological similarity criterion stating that the concept of concentration addition could be extended to mixture constituents having common apical endpoints or common adverse outcomes. - Highlights: • Potential synergic or additive effect of mixtures of chemicals on thyroid function. • Zebrafish as alternative model for testing the effect of mixtures of goitrogens. • Concentration addition seems to predict better the effect of
Elliptic solid-on-solid model's partition function as a single determinant
Galleas, W
2016-01-01
In this work we express the partition function of the integrable elliptic solid-on-solid model with domain-wall boundary conditions as a single determinant. This representation appears naturally as the solution of a system of functional equations governing the model's partition function.
Modeling function calls in program control flow in terms of Petri Nets
Directory of Open Access Journals (Sweden)
Dmitriy Kharitonov
Full Text Available This article presents a method for representing the C/C++ function call in terms of compositional Petri Nets. Principles of modeling function and function call in the program are described. Formal composition operations to construct program model from mod ...
Mittag-Leffler function for discrete fractional modelling
Directory of Open Access Journals (Sweden)
Guo-Cheng Wu
2016-01-01
Full Text Available From the difference equations on discrete time scales, this paper numerically investigates one discrete fractional difference equation in the Caputo delta’s sense which has an explicit solution in form of the discrete Mittag-Leffler function. The exact numerical values of the solutions are given in comparison with the truncated Mittag-Leffler function.
Minimal models for N-K-functions(infinity)
Dijksma, Aad; Luger, Annemarie; Shondin, Yuri; Langer, M; Luger, A; Woracek, H
2006-01-01
We present explicit realizations in terms of self-adjoint operators and linear relations for a non-zero scalar generalized Nevanlinna function N(z) and the function (N) over cap (z) = -1/N(z) under the assumption that N(z) has exactly one generalized pole which is not of positive type namely at z =
EFFICIENT ESTIMATION OF FUNCTIONAL-COEFFICIENT REGRESSION MODELS WITH DIFFERENT SMOOTHING VARIABLES
Institute of Scientific and Technical Information of China (English)
Zhang Riquan; Li Guoying
2008-01-01
In this article, a procedure for estimating the coefficient functions on the functional-coefficient regression models with different smoothing variables in different co-efficient functions is defined. First step, by the local linear technique and the averaged method, the initial estimates of the coefficient functions are given. Second step, based on the initial estimates, the efficient estimates of the coefficient functions are proposed by a one-step back-fitting procedure. The efficient estimators share the same asymptotic normalities as the local linear estimators for the functional-coefficient models with a single smoothing variable in different functions. Two simulated examples show that the procedure is effective.
Nonparametric modeling of dynamic functional connectivity in fmri data
DEFF Research Database (Denmark)
Nielsen, Søren Føns Vind; Madsen, Kristoffer H.; Røge, Rasmus
2015-01-01
in Bayesian statistical modeling we use the predictive likelihood to investigate if the model can discriminate between a motor task and rest both within and across subjects. We further investigate what drives dynamic states using the model on the entire data collated across subjects and task/rest. We find...
Transmission function models of finite population genetic algorithms
Kemenade, C.H.M. van; Kok, J.N.; La Poutré, J.A.; Thierens, D.
1998-01-01
Infinite population models show a deterministic behaviour. Genetic algorithms with finite populations behave non-deterministicly. For small population sizes, the results obtained with these models differ strongly from the results predicted by the infinite population model. When the population size i
Models of the Protocellular Structures, Functions and Evolution
Pohorille, Andrew; New, Michael; Keefe, Anthony; Szostak, Jack W.; Lanyi, Janos F.; DeVincenzi, Donald L. (Technical Monitor)
2000-01-01
In the absence of extinct or extant record of protocells, the most direct way to test our understanding of the origin of cellular life is to construct laboratory models that capture important features of protocellular systems. Such efforts are currently underway in a collaborative project between NASA-Ames, Harvard medical School and University of California. They are accompanied by computational studies aimed at explaining self-organization of simple molecules into ordered structures. The centerpiece of this project is a method for the in vitro evolution of protein enzymes toward arbitrary catalytic targets. A similar approach has already been developed for nucleic acids: First, a very large population of candidate molecules is generated using a random synthetic approach. Next, the small numbers of molecules that can accomplish the desired task are selected. These molecules are next vastly multiplied using the polymerase chain reaction. A mutagenic approach, in which the sequences of selected molecules are randomly altered, can yield further improvements in performance or alterations of specificities. Unfortunately, the catalytic potential of nucleic acids is rather limited. Proteins are more catalytically capable but cannot be directly amplified. In the new technique, this problem is circumvented by covalently linking each protein of the initial, diverse, pool to the RNA sequence that codes for it. Then, selection is performed on the proteins, but the nucleic acids are replicated. To date, we have obtained "a proof of concept" by evolving simple, novel proteins capable of selectively binding adenosine tri-phosphate (ATP). Our next goal is to create an enzyme that can phosphorylate amino acids and another to catalyze the formation of peptide bonds in the absence of nucleic acid templates. This latter reaction does not take place in contemporary cells. once developed, these enzymes will be encapsulated in liposomes so that they will function in a simulated cellular
论生产函数调整模型%Study on adjustable production function model
Institute of Scientific and Technical Information of China (English)
葛新权
2003-01-01
Cobb-Douglas production function is a nonlinear model which is most frequently used and can beenchanged into linear model. There is no doubt for the reasonability of this logarithm linearization. Thispaper gives an new proposition on the basis of deeper analysis that there is a defect with this linearization,hence adjustable production function model is proposed to eliminate it.
A characterization of edge reflection positive partition functions of vertex coloring models
G. Regts (Guus)
2013-01-01
htmlabstractSzegedy (B. Szegedy, Edge coloring models and reflection positivity, Journal of the American Mathematical Society 20, 2007, 969-988.) showed that the partition function of any vertex coloring model is equal to the partition function of a complex edge coloring model. Using some results in
A characterization of edge-reflection positive partition functions of vertex-coloring models
G. Regts (Guus); J. Nešetřil (Jaroslav); M Pellegrini
2013-01-01
htmlabstractSzegedy (B. Szegedy, Edge coloring models and reflection positivity, Journal of the American Mathematical Society 20, 2007, 969-988.) showed that the partition function of any vertex coloring model is equal to the partition function of a complex edge coloring model. Using some results in
Functional Integrals and Free Energy in sine-Gordon-Thirring Model with Impurity Coupling
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
The free energy at low temperature in ID sine-Gordon-Thirring model with impurity coupling is studied by means of functional integrals method. For massive free sine-Gordon-Thirring model, free energy is obtained from perturbation expansion of functional determinant. Moreover, the free energy of massive model is calculated by use of an auxiliary Bose Geld method.
Kidney compartment model. [Mathematical model for iodohippurate distribution as a function of time
Energy Technology Data Exchange (ETDEWEB)
Gullberg, G.T.
1976-09-01
A multiparameter kidney compartment model which quantitates the amount of iodohippurate concentration as a function of time in the blood, tissue, kidneys and bladder is developed from a system of differential equations which represent first order kinetics. The kinetic data are obtained using a gamma camera and an HP5407 computer system which allows one to delineate areas of interest for the blood and tissue, kidneys, and bladder thus separating the data into four data sets. The estimated tubular transit times have a high ratio of the signal to the variance whereas the estimates of the amount of iodohippurate in the blood, tissue and kidneys have a low ratio of the signal to the variance. Application of this model to patient data requires better statistics than available with conventional /sup 131/I-hippurate doses; thus a true test of the efficacy awaits availability of /sup 123/I-hippurate.
Gutmann, Ethan D.; Small, Eric E.
2007-01-01
Soil hydraulic properties (SHPs) regulate the movement of water in the soil. This in turn plays an important role in the water and energy cycles at the land surface. At present, SHPS are commonly defined by a simple pedotransfer function from soil texture class, but SHPs vary more within a texture class than between classes. To examine the impact of using soil texture class to predict SHPS, we run the Noah land surface model for a wide variety of measured SHPs. We find that across a range of vegetation cover (5 - 80% cover) and climates (250 - 900 mm mean annual precipitation), soil texture class only explains 5% of the variance expected from the real distribution of SHPs. We then show that modifying SHPs can drastically improve model performance. We compare two methods of estimating SHPs: (1) inverse method, and (2) soil texture class. Compared to texture class, inverse modeling reduces errors between measured and modeled latent heat flux from 88 to 28 w/m(exp 2). Additionally we find that with increasing vegetation cover the importance of SHPs decreases and that the van Genuchten m parameter becomes less important, while the saturated conductivity becomes more important.
Bayes Estimation for Inverse Rayleigh Model under Different Loss Functions
Directory of Open Access Journals (Sweden)
Guobing Fan
2015-04-01
Full Text Available The inverse Rayleigh distribution plays an important role in life test and reliability domain. The aim of this article is study the Bayes estimation of parameter of inverse Rayleigh distribution. Bayes estimators are obtained under squared error loss, LINEX loss and entropy loss functions on the basis of quasi-prior distribution. Comparisons in terms of risks with the estimators of parameter under three loss functions are also studied. Finally, a numerical example is used to illustrate the results.
DEFF Research Database (Denmark)
Kjeldsen, Tinne Hoff; Blomhøj, Morten
2013-01-01
Mathematical models and mathematical modeling play different roles in the different areas and problems in which they are used. The function and status of mathematical modeling and models in the different areas depend on the scientific practice as well as the underlying philosophical and theoretical...... position held by the modeler(s) and the practitioners in the extra-mathematical domain. For students to experience the significance of different scientific practices and cultures for the function and status of mathematical modeling in other sciences, students need to be placed in didactical situations...... in situations in which they can experience and be challenged to reflect upon and criticize, the use of modeling and the significance of the context for the function and status of modeling and models in scientific practices. We present Nicolas Rashevsky’s model of cell division from the 1930s together...
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...
Cosmological Models with Fractional Derivatives and Fractional Action Functional
Institute of Scientific and Technical Information of China (English)
V.K. Shchigolev
2011-01-01
Cosmological models of a scalar field with dynamical equations containing fractional derivatives or derived from the Einstein-Hilbert action of fractional order, are constructed. A number of exact solutions to those equations of fractional cosmological models in both eases is given.
A Functional Model for the Treatment of Primary Enuresis.
Goldstein, Sam; Book, Robert
1983-01-01
The present model, based upon Alexander and Barton's two-phase model for family therapy, was developed to provide the practicing school psychologist with an efficient, manageable program maximizing successful outcome. The program enables psychologists to adapt primary enuresis intervention strategies to suit their styles and the individual needs…
Modelling Transformations of Quadratic Functions: A Proposal of Inductive Inquiry
Sokolowski, Andrzej
2013-01-01
This paper presents a study about using scientific simulations to enhance the process of mathematical modelling. The main component of the study is a lesson whose major objective is to have students mathematise a trajectory of a projected object and then apply the model to formulate other trajectories by using the properties of function…
Testing the Conditional Mean Function of Autoregressive Conditional Duration Models
DEFF Research Database (Denmark)
Hautsch, Nikolaus
be subject to censoring structures. In an empirical study based on financial transaction data we present an application of the model to estimate conditional asset price change probabilities. Evaluating the forecasting properties of the model, it is shown that the proposed approach is a promising competitor...
Jolivet, L.; Cohen, M.; Ruas, A.
2015-01-01
Landscape influences fauna movement at different levels, from habitat selection to choices of movements' direction. Our goal is to provide a development frame in order to test simulation functions for animal's movement. We describe our approach for such simulations and we compare two types of functions to calculate trajectories. To do so, we first modelled the role of landscape elements to differentiate between elements that facilitate movements and the ones being hindrances. Different influe...
Polymer as a function of monomer: Analytical quantum modeling
Nakhaee, Mohammad
2016-01-01
To identify an analytical relation between the properties of polymers and their's monomer a Metal-Molecule-Metal (MMM) junction has been presented as an interesting and widely used object of research in which the molecule is a polymer which is able to conduct charge. The method used in this study is based on the Green's function approach in the tight-binding approximation using basic properties of matrices. For a polymer base MMM system, transmission, density of states (DOS) and local density of states (LDOS) have been calculated as a function of the hamiltonian of the monomer. After that, we have obtained a frequency for LDOS variations in pass from a subunit to the next one which is a function of energy.
Modelling graphene quantum dot functionalization via ethylene-dinitrobenzoyl
Energy Technology Data Exchange (ETDEWEB)
Noori, Keian; Giustino, Feliciano [Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PH (United Kingdom); Hübener, Hannes [Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PH (United Kingdom); Nano-Bio Spectroscopy Group and European Theoretical Spectroscopy Facility (ETSF), Universidad del País Vasco CFM CSIC-UPV/EHU-MPC & DIPC, Av. Tolosa 72, 20018 San Sebastián (Spain); Kymakis, Emmanuel [Center of Materials Technology and Photonics & Electrical Engineering Department, Technological Educational Institute (TEI) of Crete, Heraklion, 71004 Crete (Greece)
2016-03-21
Ethylene-dinitrobenzoyl (EDNB) linked to graphene oxide has been shown to improve the performance of graphene/polymer organic photovoltaics. Its binding conformation on graphene, however, is not yet clear, nor have its effects on work function and optical absorption been explored more generally for graphene quantum dots. In this report, we clarify the linkage of EDNB to GQDs from first principles and show that the binding of the molecule increases the work function of graphene, while simultaneously modifying its absorption in the ultraviolet region.
Substance-field Model for Functional Pneumatic Design
Xu, Z. G.; Yang, D. Y.; Shen, W. D.; Liu, T. T.
2017-07-01
The Substance-field analysis is put forward. The functional analysis method is studied to find out the problem, and an improved algorithm is put forward. The internal combustion engine is taken as an example, the harmful function is recognized, and is improved, i.e, high pressure gas is introduced to remove polluted air. The working principle of pneumatic engine is described, the thermodynamic engineering is analyzed, the energy release amounts are analyzed in the isothermal, polymorphism and adiabatic processes. It is concluded that, the isothermal process releases the most energy than the others. The expansion process of the pneumatic engine should be as close as possible to the isothermal process.
The boundary states and correlation functions of the tricritical Ising model
Balaska, S
2006-01-01
We consider the minimal model describing the tricritical Ising model on the upper half plane or equivalently on an infinite strip of finite width and we determine its consistents boundary states as well as its 1-point correlation functions.
Coverage Modeling and Reliability Analysis Using Multi-state Function
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Fault tree analysis is an effective method for predicting the reliability of a system. It gives a pictorial representation and logical framework for analyzing the reliability. Also, it has been used for a long time as an effective method for the quantitative and qualitative analysis of the failure modes of critical systems. In this paper, we propose a new general coverage model (GCM) based on hardware independent faults. Using this model, an effective software tool can be constructed to detect, locate and recover fault from the faulty system. This model can be applied to identify the key component that can cause the failure of the system using failure mode effect analysis (FMEA).
Modeling non-monotone risk aversion using SAHARA utility functions
A. Chen; A. Pelsser; M. Vellekoop
2011-01-01
We develop a new class of utility functions, SAHARA utility, with the distinguishing feature that it allows absolute risk aversion to be non-monotone and implements the assumption that agents may become less risk averse for very low values of wealth. The class contains the well-known exponential and
QTL Analysis and Functional Genomics of Animal Model
DEFF Research Database (Denmark)
Farajzadeh, Leila
In recent years, the use of functional genomics and next-generation sequencing technologies has increased the probability of success in studies of complex properties. The integration of large data sets from association studies, DNA resequencing, gene expression profiles and phenotypic data...
THE CRUSTAL STRUCTURE OF ELLESMERE ISLAND FROM RECEIVER FUNCTION MODELLING
DEFF Research Database (Denmark)
Schiffer, Christian; Stephenson, Randell Alexander; Oakey, Gordon
. Preliminary results give estimates of Moho depths and crustal velocity structure and these are discussed with a focus on the relationship to topography, regional geological units and fault zones. The receiver functions reveal crustal roots underneath the Victoria and Albert Mountains (45km) and the Grantland...
Rational polynomial functions for modeling E. coli and bromide breakthrough
Fecal bacteria peak concentrations and breakthrough times through preferential flow to tile drainage systems following irrigation or rainfall events are important when assessing the risk of contamination. Process-based, convective-dispersive modeling of microbial organism transport through preferent...
Functional Testing Protocols for Commercial Building Efficiency Baseline Modeling Software
Energy Technology Data Exchange (ETDEWEB)
Jump, David; Price, Phillip N.; Granderson, Jessica; Sohn, Michael
2013-09-06
This document describes procedures for testing and validating proprietary baseline energy modeling software accuracy in predicting energy use over the period of interest, such as a month or a year. The procedures are designed according to the methodology used for public domain baselining software in another LBNL report that was (like the present report) prepared for Pacific Gas and Electric Company: ?Commercial Building Energy Baseline Modeling Software: Performance Metrics and Method Testing with Open Source Models and Implications for Proprietary Software Testing Protocols? (referred to here as the ?Model Analysis Report?). The test procedure focuses on the quality of the software?s predictions rather than on the specific algorithms used to predict energy use. In this way the software vendor is not required to divulge or share proprietary information about how their software works, while enabling stakeholders to assess its performance.
Dynamical model for biological functions of DNA molecules
Institute of Scientific and Technical Information of China (English)
PANGXiao-fengI; YANGYao
2004-01-01
We proposed a dynamic model of DNA to study its nonlinear excitation and duplication and transcription in the basis of molecular structure and changes of conformation of DNA under influence of bioenergy.
Consistent Evolution of Software Artifacts and Non-Functional Models
2014-11-14
Ruscio D., Pierantonio A., Arcelli D., Eramo R., Trubiani C., Tucci M. Dipartimento di Ingegneria e Scienze dell’Informazione e Matematica ...Models (SRMs), and ( ii ) antipattern solutions as Target Role Models (TRMs). Hence, SRM-TRM pairs represent new instruments in the hands of developers to...helps to identify the antipatterns that more heavily contribute to the violation of performance requirements [10], and ( ii ) another one aimed at
Modeling of Tilting-Pad Journal Bearings with Transfer Functions
Directory of Open Access Journals (Sweden)
J. A. Vázquez
2001-01-01
Full Text Available Tilting-pad journal bearings are widely used to promote stability in modern rotating machinery. However, the dynamics associated with pad motion alters this stabilizing capacity depending on the operating speed of the machine and the bearing geometric parameters, particularly the bearing preload. In modeling the dynamics of the entire rotor-bearing system, the rotor is augmented with a model of the bearings. This model may explicitly include the pad degrees of freedom or may implicitly include them by using dynamic matrix reduction methods. The dynamic reduction models may be represented as a set of polynomials in the eigenvalues of the system used to determine stability. All tilting-pad bearings can then be represented by a fixed size matrix with polynomial elements interacting with the rotor. This paper presents a procedure to calculate the coefficients of polynomials for implicit bearing models. The order of the polynomials changes to reflect the number of pads in the bearings. This results in a very compact and computationally efficient method for fully including the dynamics of tilting-pad bearings or other multiple degrees of freedom components that interact with rotors. The fixed size of the dynamic reduction matrices permits the method to be easily incorporated into rotor dynamic stability codes. A recursive algorithm is developed and presented for calculating the coefficients of the polynomials. The method is applied to stability calculations for a model of a typical industrial compressor.
Modeling of pharmaceuticals mixtures toxicity with deviation ratio and best-fit functions models.
Wieczerzak, Monika; Kudłak, Błażej; Yotova, Galina; Nedyalkova, Miroslava; Tsakovski, Stefan; Simeonov, Vasil; Namieśnik, Jacek
2016-11-15
The present study deals with assessment of ecotoxicological parameters of 9 drugs (diclofenac (sodium salt), oxytetracycline hydrochloride, fluoxetine hydrochloride, chloramphenicol, ketoprofen, progesterone, estrone, androstenedione and gemfibrozil), present in the environmental compartments at specific concentration levels, and their mutual combinations by couples against Microtox® and XenoScreen YES/YAS® bioassays. As the quantitative assessment of ecotoxicity of drug mixtures is an complex and sophisticated topic in the present study we have used two major approaches to gain specific information on the mutual impact of two separate drugs present in a mixture. The first approach is well documented in many toxicological studies and follows the procedure for assessing three types of models, namely concentration addition (CA), independent action (IA) and simple interaction (SI) by calculation of a model deviation ratio (MDR) for each one of the experiments carried out. The second approach used was based on the assumption that the mutual impact in each mixture of two drugs could be described by a best-fit model function with calculation of weight (regression coefficient or other model parameter) for each of the participants in the mixture or by correlation analysis. It was shown that the sign and the absolute value of the weight or the correlation coefficient could be a reliable measure for the impact of either drug A on drug B or, vice versa, of B on A. Results of studies justify the statement, that both of the approaches show similar assessment of the mode of mutual interaction of the drugs studied. It was found that most of the drug mixtures exhibit independent action and quite few of the mixtures show synergic or dependent action. Copyright © 2016. Published by Elsevier B.V.
Kelderman, Henk; Macready, George B.
1990-01-01
Loglinear latent class models are used to detect differential item functioning (DIF). These models are formulated in such a manner that the attribute to be assessed may be continuous, as in a Rasch model, or categorical, as in Latent Class Mastery models. Further, an item may exhibit DIF with respec
DEFF Research Database (Denmark)
Saleem, Arshad
2007-01-01
The purpose of this paper is to present a Multilevel Flow Model (MFM) of an industrial heat pump system and its use for diagnostic reasoning. MFM is functional modeling language supporting an explicit means-ends intelligent control strategy for large industrial process plants. The model is used...
DEFF Research Database (Denmark)
Saleem, Arshad
2007-01-01
The purpose of this paper is to present a Multilevel Flow Model (MFM) of an industrial heat pump system and its use for diagnostic reasoning. MFM is functional modeling language supporting an explicit means-ends intelligent control strategy for large industrial process plants. The model is used...
Logic functions and equations binary models for computer science
Posthoff, Christian
2004-01-01
Logic functions and equations are (some of) the most important concepts of Computer Science with many applications such as Binary Arithmetics, Coding, Complexity, Logic Design, Programming, Computer Architecture and Artificial Intelligence. They are very often studied in a minimum way prior to or together with their respective applications. Based on our long-time teaching experience, a comprehensive presentation of these concepts is given, especially emphasising a thorough understanding as well as numerical and computer-based solution methods. Any applications and examples from all the respective areas are given that can be dealt with in a unified way. They offer a broad understanding of the recent developments in Computer Science and are directly applicable in professional life. Logic Functions and Equations is highly recommended for a one- or two-semester course in many Computer Science or computer Science-oriented programmes. It allows students an easy high-level access to these methods and enables sophist...
Exactly solvable model for the time response function of RPCs
Energy Technology Data Exchange (ETDEWEB)
Mangiarotti, A. [Dipartimento di Fisica and Sezione INFN, Universita degli Studi di Firenze, Largo Enrico Fermi 2, 50125 Florence (Italy)]. E-mail: mangiaro@fi.infn.it; Fonte, P. [Laboratorio de Instrumentacao e Fisica Experimental de Particulas, 3004-516 Coimbra (Portugal); Instituto Superior de Engenharia de Coimbra, Rua Pedro Nunes, 3030-199 Coimbra (Portugal); Gobbi, A. [Gesellschaft fuer Schwerionenforschung, Planckstr. 1, 64291 Darmstadt (Germany)
2004-11-01
The fluctuation theory for the growth of several avalanches is briefly summarized and extended to include the case of electronegative gas mixtures. Based on such physical picture, the intrinsic time response function of an RPC can be calculated in a closed form and its average and rms extracted from series representations. The corresponding timing resolution, expressed in units of 1/(({alpha}-{eta})vd), is a universal function of the mean number of 'effective' clusters n0 reduced by electron attachment: n0(1-{eta}/{alpha}). A comparison to a few selected good-quality experimental data is attempted for the timing resolution of both 1-gap and 4-gaps RPCs, finding a reasonable agreement.
Buckled graphene: A model study based on density functional theory
Khan, Mohammad A.
2010-09-01
We make use of ab initio calculations within density functional theory to investigate the influence of buckling on the electronic structure of single layer graphene. Our systematic study addresses a wide range of bond length and bond angle variations in order to obtain insights into the energy scale associated with the formation of ripples in a graphene sheet. © 2010 Elsevier B.V. All rights reserved.
QTL Analysis and Functional Genomics of Animal Model
DEFF Research Database (Denmark)
Farajzadeh, Leila
In recent years, the use of functional genomics and next-generation sequencing technologies has increased the probability of success in studies of complex properties. The integration of large data sets from association studies, DNA resequencing, gene expression profiles and phenotypic data......, for example, has enabled scientists to examine more complex interactions in connection with studies of properties and diseases. In her PhD project, Leila Farajzadeh integrated different organisational levels in biology, including genotype, phenotype, association studies, transcription profiles and genetic...
Dicentric chromosomes: unique models to study centromere function and inactivation
Kaitlin M Stimpson; Matheny, Justyne E.; Sullivan, Beth A.
2012-01-01
Dicentric chromosomes are products of genome rearrangement that place two centromeres on the same chromosome. Depending on the organism, dicentric stability varies after formation. In humans, dicentrics occur naturally in a substantial portion of the population and usually segregate successfully in mitosis and meiosis. Their stability has been attributed to inactivation of one of the two centromeres, creating a functionally monocentric chromosome that can segregate normally during cell divisi...
The quantum Ising model: finite sums and hyperbolic functions
Damski, Bogdan
2015-10-01
We derive exact closed-form expressions for several sums leading to hyperbolic functions and discuss their applicability for studies of finite-size Ising spin chains. We show how they immediately lead to closed-form expressions for both fidelity susceptibility characterizing the quantum critical point and the coefficients of the counterdiabatic Hamiltonian enabling arbitrarily quick adiabatic driving of the system. Our results generalize and extend the sums presented in the popular Gradshteyn and Ryzhik Table of Integrals, Series, and Products.
The quantum Ising model: finite sums and hyperbolic functions
Bogdan Damski
2015-01-01
We derive exact closed-form expressions for several sums leading to hyperbolic functions and discuss their applicability for studies of finite-size Ising spin chains. We show how they immediately lead to closed-form expressions for both fidelity susceptibility characterizing the quantum critical point and the coefficients of the counterdiabatic Hamiltonian enabling arbitrarily quick adiabatic driving of the system. Our results generalize and extend the sums presented in the popular Gradshteyn...
Design, Fabrication, Characterization and Modeling of Integrated Functional Materials
2012-10-01
purpose of this project is to develop the novel science base both in the areas of multi-scale dimensional integration as well as multiple functional...iron oxide nanoparticles have been widely explored because of their potential applications in various fields, including storage media, environmental... Wold , J. Solid State Chem. 1972, 5, 136. 44. A. A. Gippius, K.S. Okhotnikov, M. Baeritz, A. V. Shevelkov, Solid State Phenomena 2009, 152, 287. 45. C
The Distance-Decay Function of Geographical Gravity Model: Power Law or Exponential Law?
Chen, Yanguang
2015-01-01
The distance-decay function of the geographical gravity model is originally an inverse power law, which suggests a scaling process in spatial interaction. However, the distance exponent of the model cannot be explained with the ideas from Euclidean geometry. This results in what is called dimension dilemma. In particular, the gravity model based on power law could not be derived from general principles by traditional ways. Consequently, a negative exponential function substituted for the inverse power function to serve for a distance-decay function for the gravity model. However, the exponential-based gravity model goes against the first law of geography. This paper is devoted to solve these kinds of problems by mathematical reasoning and empirical analysis. First, it can be proved that the distance exponent of the gravity model is essentially a fractal dimension. Thus the dimensional dilemma of the power-based gravity model can be resolved using the concepts from fractal geometry. Second, the exponential fun...
Evaluation of Analytical Modeling Functions for the Phonation Onset Process.
Petermann, Simon; Kniesburges, Stefan; Ziethe, Anke; Schützenberger, Anne; Döllinger, Michael
2016-01-01
The human voice originates from oscillations of the vocal folds in the larynx. The duration of the voice onset (VO), called the voice onset time (VOT), is currently under investigation as a clinical indicator for correct laryngeal functionality. Different analytical approaches for computing the VOT based on endoscopic imaging were compared to determine the most reliable method to quantify automatically the transient vocal fold oscillations during VO. Transnasal endoscopic imaging in combination with a high-speed camera (8000 fps) was applied to visualize the phonation onset process. Two different definitions of VO interval were investigated. Six analytical functions were tested that approximate the envelope of the filtered or unfiltered glottal area waveform (GAW) during phonation onset. A total of 126 recordings from nine healthy males and 210 recordings from 15 healthy females were evaluated. Three criteria were analyzed to determine the most appropriate computation approach: (1) reliability of the fit function for a correct approximation of VO; (2) consistency represented by the standard deviation of VOT; and (3) accuracy of the approximation of VO. The results suggest the computation of VOT by a fourth-order polynomial approximation in the interval between 32.2 and 67.8% of the saturation amplitude of the filtered GAW.
On tau functions for orthogonal polynomials and matrix models
Blower, Gordon
2010-01-01
Let v be a real polynomial of even degree, and let \\rho be the equilibrium probability measure for v with support S; so that v(x)\\geq 2\\int \\log |x-y| \\rho (dy)+C_v for some constant C_v with support S. Then S is the union of finitely many bounded intervals with endpoints delta_j, and \\rho is given by an algebrais weight w(x) on S. The system of orthogonal polynomials for w gives rise to the Magnus--Schlesinger differential equations. This paper identifies the tau function of this system with the Hankel determinant det[\\in x^{j+k}\\rho (dx)] of \\rho. The solutions of the Magnus--Schlesinger equations are realised by a linear system, which is used to compute the tau function in terms of a Gelfand--Levitan equaiton. The tau function is associated with a potential q and a scattering problem for the Schrodinger operator with potential q. For some algebro-geometric potentials, the paper solves the scattering problem in terms of linear systems. The theory extends naturally to elliptic curves and resolves the case wh...
Evaluation of Analytical Modeling Functions for the Phonation Onset Process
Directory of Open Access Journals (Sweden)
Simon Petermann
2016-01-01
Full Text Available The human voice originates from oscillations of the vocal folds in the larynx. The duration of the voice onset (VO, called the voice onset time (VOT, is currently under investigation as a clinical indicator for correct laryngeal functionality. Different analytical approaches for computing the VOT based on endoscopic imaging were compared to determine the most reliable method to quantify automatically the transient vocal fold oscillations during VO. Transnasal endoscopic imaging in combination with a high-speed camera (8000 fps was applied to visualize the phonation onset process. Two different definitions of VO interval were investigated. Six analytical functions were tested that approximate the envelope of the filtered or unfiltered glottal area waveform (GAW during phonation onset. A total of 126 recordings from nine healthy males and 210 recordings from 15 healthy females were evaluated. Three criteria were analyzed to determine the most appropriate computation approach: (1 reliability of the fit function for a correct approximation of VO; (2 consistency represented by the standard deviation of VOT; and (3 accuracy of the approximation of VO. The results suggest the computation of VOT by a fourth-order polynomial approximation in the interval between 32.2 and 67.8% of the saturation amplitude of the filtered GAW.
Reich, P. B.; Butler, E. E.
2015-12-01
This project will advance global land models by shifting from the current plant functional type approach to one that better utilizes what is known about the importance and variability of plant traits, within a framework of simultaneously improving fundamental physiological relations that are at the core of model carbon cycling algorithms. Existing models represent the global distribution of vegetation types using the Plant Functional Typeconcept. Plant Functional Types are classes of plant species with similar evolutionary and life history withpresumably similar responses to environmental conditions like CO2, water and nutrient availability. Fixedproperties for each Plant Functional Type are specified through a collection of physiological parameters, or traits.These traits, mostly physiological in nature (e.g., leaf nitrogen and longevity) are used in model algorithms to estimate ecosystem properties and/or drive calculated process rates. In most models, 5 to 15 functional types represent terrestrial vegetation; in essence, they assume there are a total of only 5 to 15 different kinds of plants on the entire globe. This assumption of constant plant traits captured within the functional type concept has serious limitations, as a single set of traits does not reflect trait variation observed within and between species and communities. While this simplification was necessary decades past, substantial improvement is now possible. Rather than assigning a small number of constant parameter values to all grid cells in a model, procedures will be developed that predict a frequency distribution of values for any given grid cell. Thus, the mean and variance, and how these change with time, will inform and improve model performance. The trait-based approach will improve land modeling by (1) incorporating patterns and heterogeneity of traits into model parameterization, thus evolving away from a framework that considers large areas of vegetation to have near identical trait
Inflorescence development in tomato: gene functions within a zigzag model.
Directory of Open Access Journals (Sweden)
Claire ePérilleux
2014-03-01
Full Text Available Tomato is a major crop plant and several mutants have been selected for breeding but also for isolating important genes that regulate flowering and sympodial growth. Besides, current research in developmental biology aims at revealing mechanisms that account for diversity in inflorescence architectures. We therefore found timely to review the current knowledge of the genetic control of flowering in tomato and to integrate the emerging network into modeling attempts. We developped a kinetic model of the tomato inflorescence development where each meristem was represented by its ‘vegetativeness’ (V, reflecting its maturation state towards flower initiation. The model followed simple rules: maturation proceeded continuously at the same rate in every meristem (dV; floral transition and floral commitment occurred at threshold levels of V; lateral meristems were initiated with a gain of V (ΔV relative to the V level of the meristem from which they derived. This last rule created a link between successive meristems and gave to the model its zigzag shape. We next exploited the model to explore the diversity of morphotypes that could be generated by varying dV and ΔV and matched them with existing mutant phenotypes. This approach, focused on the development of the primary inflorescence, allowed us to elaborate on the genetic regulation of the kinetic model of inflorescence development. We propose that the lateral inflorescence meristem fate in tomato is closer to an immature flower meristem than to the inflorescence meristem of Arabidopsis. In the last part of our paper, we extend our thought to spatial regulators that should be integrated in a next step for unraveling the relationships between the different meristems that participate to sympodial growth.
EWnFM: An Environment States Oriented Web Service Non-Functional Property Model
Directory of Open Access Journals (Sweden)
Yin Zhang
2015-01-01
Full Text Available A proper model of Web service non-functional properties is the key foundation to the evaluation of non-functional properties of Adaptive Service Based Software (ASBS systems. As the environment in which a Web service is deployed may keep changing, environmental factors would affect the non-functional properties of a Web service a lot. However, available non-functional property models usually ignore the impact of environmental factors, leading to insufficient modeling power of non-functional properties, limited effect of system wide non-functional property evaluation based on these models, and the inability to support environment states oriented specifications of ASBS. This paper propose an environment states oriented Web service non-functional property model. By considering the differences of a non-functional property under different environment states, environment states of a Web service is analyzed using a Dirichlet process based method. With such a foundation, an environment states oriented Web service non-functional property model is introduced, together with the parameter estimation methods based on historical monitor data. Experiment results have shown that compared to the evaluated methods, our model could generate data that are much close to real monitored data.
Magis, David
2015-01-01
The purpose of this note is to study the equivalence of observed and expected (Fisher) information functions with polytomous item response theory (IRT) models. It is established that observed and expected information functions are equivalent for the class of divide-by-total models (including partial credit, generalized partial credit, rating…
Food supply and demand, a simulation model of the functional response of grazing ruminants
Smallegange, I.M.; Brunsting, A.M.H.
2002-01-01
A dynamic model of the functional response is a first prerequisite to be able to bridge the gap between local feeding ecology and grazing rules that pertain to larger scales. A mechanistic model is presented that simulates the functional response, growth and grazing time of ruminants. It is based on
Boundary Correlation Functions of the gl(1|1) Supersymmetric Vertex Model
Institute of Scientific and Technical Information of China (English)
ZHANG Chen-Jun; ZHOU Jian-Hua; YUE Rui-Hong
2008-01-01
The gl(1|1) supersymmetric vertex model with domain wall boundary conditions (DWBC) on an N×N square lattice is considered.We derive the reduction formulae for the one-point boundary correlation functions of the model.The determinant representation for the boundary correlation functions is also obtained.
Computer-controlled mechanical lung model for application in pulmonary function studies
A.F.M. Verbraak (Anton); J.E.W. Beneken; J.M. Bogaard (Jan); A. Versprille (Adrian)
1995-01-01
textabstractA computer controlled mechanical lung model has been developed for testing lung function equipment, validation of computer programs and simulation of impaired pulmonary mechanics. The construction, function and some applications are described. The physical model is constructed from two
Food supply and demand, a simulation model of the functional response of grazing ruminants
Smallegange, I.M.; Brunsting, A.M.H.
2002-01-01
A dynamic model of the functional response is a first prerequisite to be able to bridge the gap between local feeding ecology and grazing rules that pertain to larger scales. A mechanistic model is presented that simulates the functional response, growth and grazing time of ruminants. It is based on
Group-ICA model order highlights patterns of functional brain connectivity
Directory of Open Access Journals (Sweden)
Ahmed eAbou Elseoud
2011-06-01
Full Text Available Resting-state networks (RSNs can be reliably and reproducibly detected using independent component analysis (ICA at both individual subject and group levels. Altering ICA dimensionality (model order estimation can have a significant impact on the spatial characteristics of the RSNs as well as their parcellation into sub-networks. Recent evidence from several neuroimaging studies suggests that the human brain has a modular hierarchical organization which resembles the hierarchy depicted by different ICA model orders. We hypothesized that functional connectivity between-group differences measured with ICA might be affected by model order selection. We investigated differences in functional connectivity using so-called dual-regression as a function of ICA model order in a group of unmedicated seasonal affective disorder (SAD patients compared to normal healthy controls. The results showed that the detected disease-related differences in functional connectivity alter as a function of ICA model order. The volume of between-group differences altered significantly as a function of ICA model order reaching maximum at model order 70 (which seems to be an optimal point that conveys the largest between-group difference then stabilized afterwards. Our results show that fine-grained RSNs enable better detection of detailed disease-related functional connectivity changes. However, high model orders show an increased risk of false positives that needs to be overcome. Our findings suggest that multilevel ICA exploration of functional connectivity enables optimization of sensitivity to brain disorders.
An exactly solvable model of an oscillator with nonlinear coupling and zeros of Bessel functions
Dodonov, V. V.; Klimov, A. B.
1993-01-01
We consider an oscillator model with nonpolynomial interaction. The model admits exact solutions for two situations: for energy eigenvalues in terms of zeros of Bessel functions, that were considered as functions of the continuous index; and for the corresponding eigenstates in terms of Lommel polynomials.
Stallinga, S.; Rieger, B.
2012-01-01
We introduce a method for determining the position and orientation of fixed dipole emitters based on a combination of polarimetry and spot shape detection. A key element is an effective Point Spread Function model based on Hermite functions. The model offers a good description of the shape variation
Psychometric Properties on Lecturers' Beliefs on Teaching Function: Rasch Model Analysis
Mofreh, Samah Ali Mohsen; Ghafar, Mohammed Najib Abdul; Omar, Abdul Hafiz Hj; Mosaku, Monsurat; Ma'ruf, Amar
2014-01-01
This paper focuses on the psychometric analysis of lecturers' beliefs on teaching function (LBTF) survey using Rasch Model analysis. The sample comprised 34 Community Colleges' lecturers. The Rasch Model is applied to produce specific measurements on the lecturers' beliefs on teaching function in order to generalize results and inferential…
Secure and Resilient Functional Modeling for Navy Cyber-Physical Systems
2017-05-24
release; distribution is unlimited. Page 1 of 4 Secure & Resilient Functional Modeling for Navy Cyber -Physical Systems FY17 Quarter 2 Technical Progress...team defined the following attack models for cyber -physical systems: - 6 basic attacks targeting signals. - 1 basic attack targeting control... Cyber -Physical Systems” and submitted for publication to IEEE Conference on Automation Science and Engineering (CASE) 2017. Functional Editor (SCCT
Spreading Speed for a Periodic Reaction-diffusion Model with Nonmonotone Birth Function
Institute of Scientific and Technical Information of China (English)
HUANG Ye-hui; WENG Pei-xuan
2012-01-01
A reaction-diffusion model for a single spccies with age structure and nonlocal reaction for periodic time t is derived.Some results about the model with monotone birth function are firstly introduced,and then by constructing two auxiliary equations and squeezing method,the spreading speed for the system with nonmonotone birth function is obtained.
Secure and Resilient Functional Modeling for Navy Cyber-Physical Systems
2017-05-24
diversification techniques, isolation and restoration techniques, separation of information for protection against side channel attacks). For the design of the...functional models, which is paired with a database that is used to store these functional models. The web application is being developed in HTML5 and
Efficient Quantile Estimation for Functional-Coefficient Partially Linear Regression Models
Institute of Scientific and Technical Information of China (English)
Zhangong ZHOU; Rong JIANG; Weimin QIAN
2011-01-01
The quantile estimation methods are proposed for functional-coefficient partially linear regression (FCPLR) model by combining nonparametric and functional-coefficient regression (FCR) model.The local linear scheme and the integrated method are used to obtain local quantile estimators of all unknown functions in the FCPLR model.These resulting estimators are asymptotically normal,but each of them has big variance.To reduce variances of these quantile estimators,the one-step backfitting technique is used to obtain the efficient quantile estimators of all unknown functions,and their asymptotic normalities are derived.Two simulated examples are carried out to illustrate the proposed estimation methodology.
Functional scale-free networks in the two-dimensional Abelian sandpile model
Zarepour, M.; Niry, M. D.; Valizadeh, A.
2015-07-01
Recently, the similarity of the functional network of the brain and the Ising model was investigated by Chialvo [Nat. Phys. 6, 744 (2010), 10.1038/nphys1803]. This similarity supports the idea that the brain is a self-organized critical system. In this study we derive a functional network of the two-dimensional Bak-Tang-Wiesenfeld sandpile model as a self-organized critical model, and compare its characteristics with those of the functional network of the brain, obtained from functional magnetic resonance imaging.
Simple model for low-frequency guitar function
DEFF Research Database (Denmark)
Christensen, Ove; Vistisen, Bo B.
1980-01-01
The frequency response of sound pressure and top plate mobility is studied around the two first resonances of the guitar. These resonances are shown to result from a coupling between the fundamental top plate mode and the Helmholtz resonance of the cavity. A simple model is proposed for low...
Covariance Functions and Random Regression Models in the ...
African Journals Online (AJOL)
ARC-IRENE
modelled to account for heterogeneity of variance by AY. ... Results suggest that selection for CW could be effective and that RRM could be .... permanent environmental effects; and εij is the temporary environmental effect or measurement error. .... (1999), however, obtained correlations that were variable as low as 0.23 ...
A Functional Model of Sensemaking in a Neurocognitive Architecture
Directory of Open Access Journals (Sweden)
Christian Lebiere
2013-01-01
Full Text Available Sensemaking is the active process of constructing a meaningful representation (i.e., making sense of some complex aspect of the world. In relation to intelligence analysis, sensemaking is the act of finding and interpreting relevant facts amongst the sea of incoming reports, images, and intelligence. We present a cognitive model of core information-foraging and hypothesis-updating sensemaking processes applied to complex spatial probability estimation and decision-making tasks. While the model was developed in a hybrid symbolic-statistical cognitive architecture, its correspondence to neural frameworks in terms of both structure and mechanisms provided a direct bridge between rational and neural levels of description. Compared against data from two participant groups, the model correctly predicted both the presence and degree of four biases: confirmation, anchoring and adjustment, representativeness, and probability matching. It also favorably predicted human performance in generating probability distributions across categories, assigning resources based on these distributions, and selecting relevant features given a prior probability distribution. This model provides a constrained theoretical framework describing cognitive biases as arising from three interacting factors: the structure of the task environment, the mechanisms and limitations of the cognitive architecture, and the use of strategies to adapt to the dual constraints of cognition and the environment.
A functional model of sensemaking in a neurocognitive architecture.
Lebiere, Christian; Pirolli, Peter; Thomson, Robert; Paik, Jaehyon; Rutledge-Taylor, Matthew; Staszewski, James; Anderson, John R
2013-01-01
Sensemaking is the active process of constructing a meaningful representation (i.e., making sense) of some complex aspect of the world. In relation to intelligence analysis, sensemaking is the act of finding and interpreting relevant facts amongst the sea of incoming reports, images, and intelligence. We present a cognitive model of core information-foraging and hypothesis-updating sensemaking processes applied to complex spatial probability estimation and decision-making tasks. While the model was developed in a hybrid symbolic-statistical cognitive architecture, its correspondence to neural frameworks in terms of both structure and mechanisms provided a direct bridge between rational and neural levels of description. Compared against data from two participant groups, the model correctly predicted both the presence and degree of four biases: confirmation, anchoring and adjustment, representativeness, and probability matching. It also favorably predicted human performance in generating probability distributions across categories, assigning resources based on these distributions, and selecting relevant features given a prior probability distribution. This model provides a constrained theoretical framework describing cognitive biases as arising from three interacting factors: the structure of the task environment, the mechanisms and limitations of the cognitive architecture, and the use of strategies to adapt to the dual constraints of cognition and the environment.
Yang, Wu; Liu, Li; Zhou, Si-Da; Ma, Zhi-Sai
2015-10-01
This work proposes a Moving Kriging (MK) shape function modeling method for modal identification of linear time-varying (LTV) structural systems based on vector time-dependent autoregressive moving average (VTARMA) models. It aims to avoid the functional subspaces selection of the conventional functional series VTARMA (FS-VTARMA) models. Instead of the common basis functions, it constructs the time-varying coefficients on the time nodes with the MK shape functions in a compact support domain. The merit of the MK shape function is to determine its shape parameters upon vector random vibration signals adaptively. Model identification is effectively dealt with through an optimization scheme that decomposes the identification problem into two subproblems: estimating model parameters via two-stage least squares (2SLS) method and estimating shape function parameters via a discrete-continuous-variable hybrid optimization. In addition, the model order selection is achieved by the optimization scheme. This method has been validated by a Monte Carlo study of simulation case and further by an experimental test case, and the performance and potential advantages are illustrated.
Density Functional Modelling of Elastic Properties of Elemental Semiconductors
Directory of Open Access Journals (Sweden)
M. Verma
2011-01-01
Full Text Available The expressions for bulk modulus, its first and second pressure derivatives for elemental semiconductors are derived using the ab initio pseudopotential approach to the total crystal energy within the framework of local Density Functional formalism. The expression for the second pressure derivative of the bulk modulus for four-fold crystal structures are derived for the first time within the pseudopotential framework. The computed results for the semiconductors under study are very close to the available experimental data and will be useful in the study of equation of states.
Reinterpreting space, time lags, and functional responses in ecological models.
Keeling, M J; Wilson, H B; Pacala, S W
2000-12-01
Natural enemy-victim interactions are of major applied importance and of fundamental interest to ecologists. A key question is what stabilizes these interactions, allowing the long-term coexistence of the two species. Three main theoretical explanations have been proposed: behavioral responses, time-dependent factors such as delayed density dependence, and spatial heterogeneity. Here, using the powerful moment-closure technique, we show a fundamental equivalence between these three elements. Limited movement by organisms is a ubiquitous feature of ecological systems, allowing spatial structure to develop; we show that the effects of this can be naturally described in terms of time lags or within-generation functional responses.
Modeling behavior: the quest to link mechanisms to function.
Janus, C; Dubnau, J
2003-02-01
T. Dobzhansky (1973) has been credited with saying: 'nothing in biology makes sense, except in the light of evolution'. The evolutionary conservation of gene function, as well as remarkable conservation of elemental behavioral mechanisms, guarantees that much of what we learn in one organism will inform our understanding of behavior in all animals, including humans. This insight has permitted behavior-geneticists to choose organisms based on experimental tractability for a given scientific question. IBANGS as a society has clearly embraced this Dobzhanskian worldview. As a result, the intellectual synergy of cross-species behavior-genetic analysis was palpable at the IBANGS meeting in Tours, France.
Stellar and HI Mass Functions Predicted by a Simple Preheating Galaxy Formation Model
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
According to the new preheating mechanism of galaxy formation suggested by Mo et al., we construct a simple model of formation of disk galaxies within the current paradigm of galaxy formation. It incorporates preheating, gas cooling, bulge formation and star formation. The predicted stellar and HI mass functions of galaxies are discussed and compared with the observations. It is found that our model can roughly match both the observed galaxy luminosity function and the observed HI-mass function.
A Model-Based Approach to Constructing Music Similarity Functions
Directory of Open Access Journals (Sweden)
Lamere Paul
2007-01-01
Full Text Available Several authors have presented systems that estimate the audio similarity of two pieces of music through the calculation of a distance metric, such as the Euclidean distance, between spectral features calculated from the audio, related to the timbre or pitch of the signal. These features can be augmented with other, temporally or rhythmically based features such as zero-crossing rates, beat histograms, or fluctuation patterns to form a more well-rounded music similarity function. It is our contention that perceptual or cultural labels, such as the genre, style, or emotion of the music, are also very important features in the perception of music. These labels help to define complex regions of similarity within the available feature spaces. We demonstrate a machine-learning-based approach to the construction of a similarity metric, which uses this contextual information to project the calculated features into an intermediate space where a music similarity function that incorporates some of the cultural information may be calculated.
Rolling in the Higgs Model and Elliptic Functions
Arefeva, I Ya; Volovich, I V
2012-01-01
Asymptotic methods in nonlinear dynamics are used usually to improve perturbation theory results in the oscillations regime. However, for some problems of nonlinear dynamics, particularly in the case of Higgs (Duffing) equation and the Friedmann cosmological equations, not only small oscillations regime is of interest but also the regime of rolling (claiming), more precisely the rolling from a top (claiming to the top). In the Friedman cosmology, where the slow rolling regime is often used, the rolling from a top (not necessary slow) is of interest too. In the present work a method for approximate solution to the Higgs equation in the rolling regime is presented. It is shown that in order to improve perturbation theory in the rolling regime it turns out to be effective not to use an expansion in trigonometric functions as it is done in case of small oscillations but use expansions in hyperbolic functions instead. This regime is investigated using the representation of the solution in terms of elliptic functio...
Emissivity as a Function of Surface Roughness: A Computer Model.
1986-08-29
dependance on surface roughness sheds some light on ship wake measurements (8] , and corrects some of the analysis of spatial sea surface temperature...variation recently reported in (6) . The wind wave spectral dependance of surface emissivity also indicates that shorter wavelengths, such as...definition, a power spectrum contains no phase dependance . Therefore, in order to create a reasonable model of the surface elevation, we assume that the
A Distance Function Model with Good and Bad Outputs
2014-01-01
We present an approach that pursues an adequate representation of product transformation possibilities for a technology generating, in addition to marketed (good) products, some environmentally detrimental non-marketed byproducts (bad outputs). As the shadow price of a non-marketed output depends on its marginal transformation rates with marketed outputs, representation of technological relationships between different groups of outputs deserves a particular attention. We model the technology ...
Statistical Quark Model for the Nucleon Structure Function
Mirez, Carlos; Tomio, Lauro; Trevisan, Luis A.; Frederico, Tobias
2009-06-01
A statistical quark model, with quark energy levels given by a central linear confining potential is used to obtain the light sea-quark asymmetry, d¯/ū, and also for the ratio d/u, inside the nucleon. After adjusting a temperature parameter by the Gottfried sum rule violation, and chemical potentials by the valence up and down quark normalizations, the results are compared with experimental data available.
Modeled Microgravity Affects Fibroblast Functions Related to Wound Healing
Cialdai, Francesca; Vignali, Leonardo; Morbidelli, Lucia; Colciago, Alessandra; Celotti, Fabio; Santi, Alice; Caselli, Anna; Cirri, Paolo; Monici, Monica
2017-02-01
Wound healing is crucial for the survival of an organism. Therefore, in the perspective of space exploration missions, it is important to understand if and how microgravity conditions affect the behavior of the cell populations involved in wound healing and the evolution of the process. Since fibroblasts are the major players in tissue repair, this study was focused on the behavior of fibroblasts in microgravity conditions, modeled by a RCCS. Cell cytoskeleton was studied by immunofluorescence microscopy, the ability to migrate was assessed by microchemotaxis and scratch assay, and the expression of markers of fibroblast activation, angiogenesis, and inflammation was assessed by western blot. Results revealed that after cell exposure to modeled microgravity conditions, a thorough rearrangement of microtubules occurred and α-SMA bundles were replaced by a tight network of faulty and disorganized filaments. Exposure to modeled microgravity induced a decrease in α-SMA and E-CAD expressions. Also, the expression of the pro-angiogenic protein VEGF decreased, while that of the inflammatory signal COX-2 increased. Fibroblast ability to adhere, migrate, and respond to chemoattractants (PRP), closely related to cytoskeleton integrity and membrane junctions, was significantly impaired. Nevertheless, PRP was able to partially restore fibroblast migration.
Functional mathematical model of dual pathway AV nodal conduction.
Climent, A M; Guillem, M S; Zhang, Y; Millet, J; Mazgalev, T N
2011-04-01
Dual atrioventricular (AV) nodal pathway physiology is described as two different wave fronts that propagate from the atria to the His bundle: one with a longer effective refractory period [fast pathway (FP)] and a second with a shorter effective refractory period [slow pathway (SP)]. By using His electrogram alternance, we have developed a mathematical model of AV conduction that incorporates dual AV nodal pathway physiology. Experiments were performed on five rabbit atrial-AV nodal preparations to develop and test the presented model. His electrogram alternances from the inferior margin of the His bundle were used to identify fast and slow wave front propagations. The ability to predict AV conduction time and the interaction between FP and SP wave fronts have been analyzed during regular and irregular atrial rhythms (e.g., atrial fibrillation). In addition, the role of dual AV nodal pathway wave fronts in the generation of Wenckebach periodicities has been illustrated. Finally, AV node ablative modifications have been evaluated. The model accurately reproduced interactions between FP and SP during regular and irregular atrial pacing protocols. In all experiments, specificity and sensitivity higher than 85% were obtained in the prediction of the pathway responsible for conduction. It has been shown that, during atrial fibrillation, the SP ablation significantly increased the mean HH interval (204 ± 39 vs. 274 ± 50 ms, P AV node mechanisms and should be considered as a step forward in the studies of AV nodal conduction.
Modeled Microgravity Affects Fibroblast Functions Related to Wound Healing
Cialdai, Francesca; Vignali, Leonardo; Morbidelli, Lucia; Colciago, Alessandra; Celotti, Fabio; Santi, Alice; Caselli, Anna; Cirri, Paolo; Monici, Monica
2017-01-01
Wound healing is crucial for the survival of an organism. Therefore, in the perspective of space exploration missions, it is important to understand if and how microgravity conditions affect the behavior of the cell populations involved in wound healing and the evolution of the process. Since fibroblasts are the major players in tissue repair, this study was focused on the behavior of fibroblasts in microgravity conditions, modeled by a RCCS. Cell cytoskeleton was studied by immunofluorescence microscopy, the ability to migrate was assessed by microchemotaxis and scratch assay, and the expression of markers of fibroblast activation, angiogenesis, and inflammation was assessed by western blot. Results revealed that after cell exposure to modeled microgravity conditions, a thorough rearrangement of microtubules occurred and α-SMA bundles were replaced by a tight network of faulty and disorganized filaments. Exposure to modeled microgravity induced a decrease in α-SMA and E-CAD expressions. Also, the expression of the pro-angiogenic protein VEGF decreased, while that of the inflammatory signal COX-2 increased. Fibroblast ability to adhere, migrate, and respond to chemoattractants (PRP), closely related to cytoskeleton integrity and membrane junctions, was significantly impaired. Nevertheless, PRP was able to partially restore fibroblast migration.
Modeling the Near-Infrared Luminosity Function of Young Stellar Clusters
Muench, A. A.; Lada, E. A.; Lada, C. J.
1999-12-01
We present the results of numerical experiments designed to evaluate the usefulness of near-infrared luminosity functions for constraining the Initial Mass Function (IMF) of young (0-10 Myr) stellar populations. Using Monte Carlo techniques, we create a suite of model luminosity functions systematically varying each of these basic underlying relations: the underlying IMF, cluster star forming history, and theoretical pre-main sequence mass-to-luminosity relations. Our modeling techniques also allow us to explore the effects of unresolved binaries, infrared excess emission from circumstellar disks, and interstellar extinction on the cluster luminosity function. From this numerical modeling, we find that the luminosity function of a young stellar population is considerably more sensitive to variations in the underlying initial mass function than to either variations in the star forming history or assumed pre-main-sequence (PMS) mass-to-luminosity relation. To illustrate the potential effectiveness of using the KLF of a young cluster to constrain its IMF, we model the observed K band luminosity function of the nearby Trapezium cluster. Our derived mass function for the Trapezium spans two orders of magnitude in stellar mass (5>Msun>0.02) and has a peak near the hydrogen burning limit. Below the hydrogen burning limit, the mass function steadily decreases with decreasing mass throughout the brown dwarf regime. We also test the hypothesis of a space varying IMF by performing model fits to the K band luminosity functions of several other young clusters.
Performance Evaluation of Color Models in the Fusion of Functional and Anatomical Images.
Ganasala, Padma; Kumar, Vinod; Prasad, A D
2016-05-01
Fusion of the functional image with an anatomical image provides additional diagnostic information. It is widely used in diagnosis, treatment planning, and follow-up of oncology. Functional image is a low-resolution pseudo color image representing the uptake of radioactive tracer that gives the important metabolic information. Whereas, anatomical image is a high-resolution gray scale image that gives structural details. Fused image should consist of all the anatomical details without any changes in the functional content. This is achieved through fusion in de-correlated color model and the choice of color model has greater impact on the fusion outcome. In the present work, suitability of different color models for functional and anatomical image fusion is studied. After converting the functional image into de-correlated color model, the achromatic component of functional image is fused with an anatomical image by using proposed nonsubsampled shearlet transform (NSST) based image fusion algorithm to get new achromatic component with all the anatomical details. This new achromatic and original chromatic channels of functional image are converted to RGB format to get fused functional and anatomical image. Fusion is performed in different color models. Different cases of SPECT-MRI images are used for this color model study. Based on visual and quantitative analysis of fused images, the best color model for the stated purpose is determined.
Directory of Open Access Journals (Sweden)
L. Jolivet
2015-08-01
Full Text Available Landscape influences fauna movement at different levels, from habitat selection to choices of movements’ direction. Our goal is to provide a development frame in order to test simulation functions for animal’s movement. We describe our approach for such simulations and we compare two types of functions to calculate trajectories. To do so, we first modelled the role of landscape elements to differentiate between elements that facilitate movements and the ones being hindrances. Different influences are identified depending on landscape elements and on animal species. Knowledge were gathered from ecologists, literature and observation datasets. Second, we analysed the description of animal movement recorded with GPS at fine scale, corresponding to high temporal frequency and good location accuracy. Analysing this type of data provides information on the relation between landscape features and movements. We implemented an agent-based simulation approach to calculate potential trajectories constrained by the spatial environment and individual’s behaviour. We tested two functions that consider space differently: one function takes into account the geometry and the types of landscape elements and one cost function sums up the spatial surroundings of an individual. Results highlight the fact that the cost function exaggerates the distances travelled by an individual and simplifies movement patterns. The geometry accurate function represents a good bottom-up approach for discovering interesting areas or obstacles for movements.
Warren, Jeffrey M; Hanson, Paul J; Iversen, Colleen M; Kumar, Jitendra; Walker, Anthony P; Wullschleger, Stan D
2015-01-01
There is wide breadth of root function within ecosystems that should be considered when modeling the terrestrial biosphere. Root structure and function are closely associated with control of plant water and nutrient uptake from the soil, plant carbon (C) assimilation, partitioning and release to the soils, and control of biogeochemical cycles through interactions within the rhizosphere. Root function is extremely dynamic and dependent on internal plant signals, root traits and morphology, and the physical, chemical and biotic soil environment. While plant roots have significant structural and functional plasticity to changing environmental conditions, their dynamics are noticeably absent from the land component of process-based Earth system models used to simulate global biogeochemical cycling. Their dynamic representation in large-scale models should improve model veracity. Here, we describe current root inclusion in models across scales, ranging from mechanistic processes of single roots to parameterized root processes operating at the landscape scale. With this foundation we discuss how existing and future root functional knowledge, new data compilation efforts, and novel modeling platforms can be leveraged to enhance root functionality in large-scale terrestrial biosphere models by improving parameterization within models, and introducing new components such as dynamic root distribution and root functional traits linked to resource extraction.
SCAN-based hybrid and double-hybrid density functionals from models without fitted parameters
Hui, Kerwin; Chai, Jeng-Da
2015-01-01
By incorporating the nonempirical SCAN semilocal density functional [Sun, Ruzsinszky, and Perdew, Phys. Rev. Lett. 115, 036402 (2015)] in the underlying expression of four existing hybrid and double-hybrid models, we propose one hybrid (SCAN0) and three double-hybrid (SCAN0-DH, SCAN-QIDH, and SCAN0-2) density functionals, which are free from any fitted parameters. The SCAN-based double-hybrid functionals consistently outperform their parent SCAN semilocal functional for self-interaction probl...
Energy Technology Data Exchange (ETDEWEB)
Walraven, Jeremy Allen; Blecke, Jill; Baker, Michael Sean; Clemens, Rebecca C.; Mitchell, John Anthony; Brake, Matthew Robert; Epp, David S.; Wittwer, Jonathan W.
2008-10-01
This report summarizes the functional, model validation, and technology readiness testing of the Sandia MEMS Passive Shock Sensor in FY08. Functional testing of a large number of revision 4 parts showed robust and consistent performance. Model validation testing helped tune the models to match data well and identified several areas for future investigation related to high frequency sensitivity and thermal effects. Finally, technology readiness testing demonstrated the integrated elements of the sensor under realistic environments.
Alternative Functional In Vitro Models of Human Intestinal Epithelia
Directory of Open Access Journals (Sweden)
Amanda L Kauffman
2013-07-01
Full Text Available Physiologically relevant sources of absorptive intestinal epithelial cells are crucial for human drug transport studies. Human adenocarcinoma-derived intestinal cell lines, such as Caco-2, offer conveniences of easy culture maintenance and scalability, but do not fully recapitulate in vivo intestinal phenotypes. Additional sources of renewable physiologically relevant human intestinal cells would provide a much needed tool for drug discovery and intestinal physiology. We sought to evaluate and compare two alternative sources of human intestinal cells, commercially available primary human intestinal epithelial cells (hInEpCs and induced pluripotent stem cell (iPSC-derived intestinal cells to Caco-2, for use in in vitro transwell monolayer intestinal transport assays. To achieve this for iPSC-derived cells, our previously described 3-dimensional intestinal organogenesis method was adapted to transwell differentiation. Intestinal cells were assessed by marker expression through immunocytochemical and mRNA expression analyses, monolayer integrity through Transepithelial Electrical Resistance (TEER measurements and molecule permeability, and functionality by taking advantage the well-characterized intestinal transport mechanisms. In most cases, marker expression for primary hInEpCs and iPSC-derived cells appeared to be as good as or better than Caco-2. Furthermore, transwell monolayers exhibited high TEER with low permeability. Primary hInEpCs showed molecule efflux indicative of P-glycoprotein transport. Primary hInEpCs and iPSC-derived cells also showed neonatal Fc receptor-dependent binding of immunoglobulin G variants. Primary hInEpCs and iPSC-derived intestinal cells exhibit expected marker expression and demonstrate basic functional monolayer formation, similar to or better than Caco-2. These cells could offer an alternative source of human intestinal cells for understanding normal intestinal epithelial physiology and drug transport.
Gene function classification using Bayesian models with hierarchy-based priors
Directory of Open Access Journals (Sweden)
Neal Radford M
2006-10-01
Full Text Available Abstract Background We investigate whether annotation of gene function can be improved using a classification scheme that is aware that functional classes are organized in a hierarchy. The classifiers look at phylogenic descriptors, sequence based attributes, and predicted secondary structure. We discuss three Bayesian models and compare their performance in terms of predictive accuracy. These models are the ordinary multinomial logit (MNL model, a hierarchical model based on a set of nested MNL models, and an MNL model with a prior that introduces correlations between the parameters for classes that are nearby in the hierarchy. We also provide a new scheme for combining different sources of information. We use these models to predict the functional class of Open Reading Frames (ORFs from the E. coli genome. Results The results from all three models show substantial improvement over previous methods, which were based on the C5 decision tree algorithm. The MNL model using a prior based on the hierarchy outperforms both the non-hierarchical MNL model and the nested MNL model. In contrast to previous attempts at combining the three sources of information in this dataset, our new approach to combining data sources produces a higher accuracy rate than applying our models to each data source alone. Conclusion Together, these results show that gene function can be predicted with higher accuracy than previously achieved, using Bayesian models that incorporate suitable prior information.
A transient energy function for power systems including the induction motor model
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
A construction method for power system transient energy function is studied in the paper, which is simple and universal, and can unify the forms of some current energy functions. A transient energy function including the induction motor model is derived using the method. The unintegrable term is dealt with to get an approximate energy function. Simulations in a 3-bus system and in the WSCC 4-generator system verify the validity of the proposed energy function. The function can be applied to direct transient stability analysis of multi-machine large power systems and provides a tool for analysis of the interaction between the generator angle stability and the load voltage stability.
SysML model of exoplanet archive functionality and activities
Ramirez, Solange
2016-08-01
The NASA Exoplanet Archive is an online service that serves data and information on exoplanets and their host stars to help astronomical research related to search for and characterization of extra-solar planetary systems. In order to provide the most up to date data sets to the users, the exoplanet archive performs weekly updates that include additions into the database and updates to the services as needed. These weekly updates are complex due to interfaces within the archive. I will be presenting a SysML model that helps us perform these update activities in a weekly basis.
Sakschewski, B.; Bloh, von W.; Boit, A.; Rammig, A.; Kattge, J.; Poorter, L.; Peñualeas, J.; Thonicke, K.
2015-01-01
Functional diversity is critical for ecosystem dynamics, stability and productivity. However, dynamic global vegetation models (DGVMs) which are increasingly used to simulate ecosystem functions under global change, condense functional diversity to plant functional types (PFTs) with constant paramet
Configurational study of amino-functionalized silica surfaces: A density functional theory modeling.
Hozhabr Araghi, Samira; Entezari, Mohammad H; Sadeghi Googheri, Mohammad Sadegh
2015-06-01
Despite extensive studies of the amino-functionalized silica surfaces, a comprehensive investigation of the effects of configuration and hydrolysis of 3-aminopropyltriethoxysilan (APTES) molecules attached on silica has not been studied yet. Therefore, the methods of quantum mechanics were used for the study of configuration and hydrolysis forms of APTES molecules attached on the surface. For this purpose, five different categories based on the number of hydrolyzed ethoxy groups including 16 configurations were designed and analyzed by the density functional theory (DFT) method. The steric hindrance as an effective factor on the stability order was extracted from structural analysis. Other impressive parameters such as the effects of hydrogen bond and electron delocalization energy were obtained by using the atoms in molecules (AIM) and natural bond orbitals (NBO) theories. Consequently, it was found that the stability of configurations was attributed to steric effects, hydrogen bond numbers and electron delocalization energy. The maximum stability was achieved when at least two of these parameters cooperate with each other.
Ishima, R; Yamasaki, K; Nagayama, K
1995-12-01
Parameters used in model-free analysis were related to simulated spectral density functions in a frequency region experimentally obtained by quasi-spectral density function analysis of (15)N nuclei. Five kinds of motional models used in recent model-free analyses were characterized by a simple classification of the experimental spectral density function. We demonstrate advantages and limitations of each of the motional models. To verify the character of the models, model selection using experimental spectral density functions was examined.
Energy Technology Data Exchange (ETDEWEB)
Olivero, J.; Toxopeus, A.G.; Skidmore, A.K.; Real, R.
2016-07-01
Statistical downscaling is used to improve the knowledge of spatial distributions from broad–scale to fine–scale maps with higher potential for conservation planning. We assessed the effectiveness of downscaling in two commonly used species distribution models: Maximum Entropy (MaxEnt) and the Favourability Function (FF). We used atlas data (10 x 10 km) of the fire salamander Salamandra salamandra distribution in southern Spain to derive models at a 1 x 1 km resolution. Downscaled models were assessed using an independent dataset of the species’ distribution at 1 x 1 km. The Favourability model showed better downscaling performance than the MaxEnt model, and the models that were based on linear combinations of environmental variables performed better than models allowing higher flexibility. The Favourability model minimized model overfitting compared to the MaxEnt model. (Author)
Validation of a functional model for integration of safety into process system design
DEFF Research Database (Denmark)
Wu, J.; Lind, M.; Zhang, X.
2015-01-01
with the process system functionalities as required for the intended safety applications. To provide the scientific rigor and facilitate the acceptance of qualitative modelling, this contribution focuses on developing a scientifically based validation method for functional models. The Multilevel Flow Modeling (MFM......Qualitative modeling paradigm offers process systems engineering a potential for developing effective tools for handling issues related to Process Safety. A qualitative functional modeling environment can accommodate different levels of abstraction for capturing knowledge associated...... behavior sufficiently well. With the reasoning capability provided by the MFM syntax and semantics, the validation procedure is illustrated on a three-phase separator system of an MFM model. The MFM model reasoning results successfully compares against analysis results from API RP. 14-C....
Assessment of large basis shell model wave functions for the Li isotopes
Energy Technology Data Exchange (ETDEWEB)
Karataglidis, S.; Brown, B.A. [Michigan State Univ., East Lansing, MI (United States); Dortmans, P.J.; Amos, K. [Melbourne Univ., Parkville, VIC (Australia). School of Physics
1997-06-01
The Li isotopes are good examples with which the shell model can be tested for cluster-like behaviour, as large space (no core) shell model wave functions may be constructed. The cross sections and analysing power for the inelastic scattering of electron and proton scattering data for {sup 6,7}Li ground states were analysed using the same shell model wave functions. It was found that the results obtained by using 0{Dirac_h}{omega} structure model wave functions is unable to reproduce the magnitude of the data. Meanwhile, those obtained by using the larger space models are able to reproduce the low-angle part of the cross section, but all model results severely underestimate the cross section above 20 deg. Meanwhile, in the case of analysing power, all model calculations give reasonable representation of the data. 13 refs., 3 figs.
Directory of Open Access Journals (Sweden)
Tetiana A. Vakaliuk
2017-06-01
Full Text Available The article summarizes the essence of the category "model". There are presented the main types of models used in educational research: structural, functional, structural and functional model as well as basic requirements for building these types of models. The national experience in building models and designing cloud-based learning environment of educational institutions (both higher and secondary is analyzed. It is presented structural and functional model of cloud-based learning environment for Bachelor of Informatics. Also we describe each component of cloud-based learning environment model for bachelors of informatics training: target, managerial, organizational, content and methodical, communication, technological and productive. It is summarized, that COLE should solve all major tasks that relate to higher education institutions.
Momentum Fractions carried by quarks and gluons in models of proton structure functions at small $x$
Choudhury, D K; Kalita, K
2016-01-01
The paper reports analysis of momentum fractions carried by quarks and gluons in models of Proton structure functions at small $x$. First, we analyze the model proposed by Lastovicka based on self-similarity sometime back. We then make a similar analysis for a second model based on the same notion which is also free from singularity in $x$ : $0
Aircraft/Air Traffic Management Functional Analysis Model. Version 2.0; User's Guide
Etheridge, Melvin; Plugge, Joana; Retina, Nusrat
1998-01-01
The Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 (FAM 2.0), is a discrete event simulation model designed to support analysis of alternative concepts in air traffic management and control. FAM 2.0 was developed by the Logistics Management Institute (LMI) a National Aeronautics and Space Administration (NASA) contract. This document provides a guide for using the model in analysis. Those interested in making enhancements or modification to the model should consult the companion document, Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 Technical Description.
Directory of Open Access Journals (Sweden)
Mustafa Koroglu
2016-02-01
Full Text Available This paper considers a functional-coefficient spatial Durbin model with nonparametric spatial weights. Applying the series approximation method, we estimate the unknown functional coefficients and spatial weighting functions via a nonparametric two-stage least squares (or 2SLS estimation method. To further improve estimation accuracy, we also construct a second-step estimator of the unknown functional coefficients by a local linear regression approach. Some Monte Carlo simulation results are reported to assess the finite sample performance of our proposed estimators. We then apply the proposed model to re-examine national economic growth by augmenting the conventional Solow economic growth convergence model with unknown spatial interactive structures of the national economy, as well as country-specific Solow parameters, where the spatial weighting functions and Solow parameters are allowed to be a function of geographical distance and the countries’ openness to trade, respectively.
Object oriented Full Function Point Analysis: A Model for Real Time Application
Directory of Open Access Journals (Sweden)
Sheeba Praveen
2012-09-01
Full Text Available this research work focused on determining the functional size of real time application at early stage. This paper will describe how to estimate the functional size of real time system using OO methodology. In this research we are proposing a Model which is very useful for estimating the size of real time system. And this model is fully based on Object oriented development Methodology due to the adaptation of the Function Point Analysis (FPA to Object Point Analysis (OPA. This model is for Real Time Application due to that have to take the FFP metric because FFP is best for size measurement of real time system. So the mapping is done in between Full Function Point metrics (FFP to Object Oriented Function Point metrics (OOFP and finally we are proposing a new metrics known as OOFFP and the based analysis is known as Object Oriented Full Function Point Analysis (OOFFPA.
Assembly and mechanosensory function of focal adhesions: experiments and models.
Bershadsky, Alexander D; Ballestrem, Christoph; Carramusa, Letizia; Zilberman, Yuliya; Gilquin, Benoit; Khochbin, Saadi; Alexandrova, Antonina Y; Verkhovsky, Alexander B; Shemesh, Tom; Kozlov, Michael M
2006-04-01
Initial integrin-mediated cell-matrix adhesions (focal complexes) appear underneath the lamellipodia, in the regions of the "fast" centripetal flow driven by actin polymerization. Once formed, these adhesions convert the flow behind them into a "slow", myosin II-driven mode. Some focal complexes then turn into elongated focal adhesions (FAs) associated with contractile actomyosin bundles (stress fibers). Myosin II inhibition does not suppress formation of focal complexes but blocks their conversion into mature FAs and further FA growth. Application of external pulling force promotes FA growth even under conditions when myosin II activity is blocked. Thus, individual FAs behave as mechanosensors responding to the application of force by directional assembly. We proposed a thermodynamic model for the mechanosensitivity of FAs, taking into account that an elastic molecular aggregate subject to pulling forces tends to grow in the direction of force application by incorporating additional subunits. This simple model can explain a variety of processes typical of FA behavior. Assembly of FAs is triggered by the small G-protein Rho via activation of two major targets, Rho-associated kinase (ROCK) and the formin homology protein, Dia1. ROCK controls creation of myosin II-driven forces, while Dia1 is involved in the response of FAs to these forces. Expression of the active form of Dia1, allows the external force-induced assembly of mature FAs, even in conditions when Rho is inhibited. Conversely, downregulation of Dia1 by siRNA prevents FA maturation even if Rho is activated. Dia1 and other formins cap barbed (fast growing) ends of actin filaments, allowing insertion of the new actin monomers. We suggested a novel mechanism of such "leaky" capping based on an assumption of elasticity of the formin/barbed end complex. Our model predicts that formin-mediated actin polymerization should be greatly enhanced by application of external pulling force. Thus, the formin-actin complex
Standard Model with extra dimensions and its zeta function regularization
García-Jiménez, I; Martínez-Pascual, E; Nápoles-Cañedo, G I; Novales-Sánchez, H; Toscano, J J
2016-01-01
We start from a field theory governed by the extra-dimensional $ISO(1,3+n)$ Poincar\\'e group and by the extended SM gauge group, $G({\\cal M}^{4+n})$. Then we construct an effective field theory whose symmetry groups are $ISO(1,3)$ and $G({\\cal M}^{4})$. The transition is carried out via two canonical transformations: a map that preserves, but it hides, the $SO(1,3+n)$ symmetry; and a transformation, given by Fourier series, that explicitly breaks $ISO(1,3+n)$ into $ISO(1,3)$, but conserves and hides the gauge symmetry $G({\\cal M}^{4+n})$, which manifests through nonstandard gauge transformations. From the 4-dimensional perspective, a particle that propagates in compact extra dimensions unfolds into a family of fields that reduces to the SM field if the size of the compact manifold is negligible. We include a full catalogue of Lagrangian terms that can be used to derive Feynman rules. The divergent character of the theory at one-loop is studied. A regularization scheme, based on the Epstein zeta function (EZF)...
Model approach to starch functionality in bread making.
Goesaert, Hans; Leman, Pedro; Delcour, Jan A
2008-08-13
We used modified wheat starches in gluten-starch flour models to study the role of starch in bread making. Incorporation of hydroxypropylated starch in the recipe reduced loaf volume and initial crumb firmness and increased crumb gas cell size. Firming rate and firmness after storage increased for loaves containing the least hydroxypropylated starch. Inclusion of cross-linked starch had little effect on loaf volume or crumb structure but increased crumb firmness. The firming rate was mostly similar to that of control samples. Presumably, the moment and extent of starch gelatinization and the concomitant water migration influence the structure formation during baking. Initial bread firmness seems determined by the rigidity of the gelatinized granules and leached amylose. Amylopectin retrogradation and strengthening of a long-range network by intensifying the inter- and intramolecular starch-starch and possibly also starch-gluten interactions (presumably because of water incorporation in retrograded amylopectin crystallites) play an important role in firming.
Impaired executive functions in experimental model of temporal lobe epilepsy
Directory of Open Access Journals (Sweden)
Fabiane Ochai Ramos
2016-06-01
Full Text Available ABSTRACT Objective The present study aimed to investigate cognitive and behavioural changes consistent with attention deficit hyperactivity disorder (ADHD -like behavior in male Wistar rats with temporal lobe epilepsy (TLE. Method Male Wistar rats at 25 day of age were submitted to animal model of TLE by pilocarpine injection (350 mg/kg, ip and a control group received saline 0.9%. The animals were continuously video monitored up to the end of experiments. The behavioural tests (open field, elevated plus maze and operant conditioning box started from 60 days postnatal. Results Animals with TLE exhibited elevated locomotor activity, reduced level of anxiety-related behavior, impulsivity and impaired visuospatial working memory. Conclusion Taken as a whole, we concluded that animals with TLE exhibited some cognitive and behavioural changes consistent with ADHD-like behavior.
A Note on the Item Information Function of the Four-Parameter Logistic Model
Magis, David
2013-01-01
This article focuses on four-parameter logistic (4PL) model as an extension of the usual three-parameter logistic (3PL) model with an upper asymptote possibly different from 1. For a given item with fixed item parameters, Lord derived the value of the latent ability level that maximizes the item information function under the 3PL model. The…
A Note on the Item Information Function of the Four-Parameter Logistic Model
Magis, David
2013-01-01
This article focuses on four-parameter logistic (4PL) model as an extension of the usual three-parameter logistic (3PL) model with an upper asymptote possibly different from 1. For a given item with fixed item parameters, Lord derived the value of the latent ability level that maximizes the item information function under the 3PL model. The…
Matzke, Orville R.
The purpose of this study was to formulate a linear programming model to simulate a foundation type support program and to apply this model to a state support program for the public elementary and secondary school districts in the State of Iowa. The model was successful in producing optimal solutions to five objective functions proposed for…
Function of the hemochromatosis protein HFE: Lessons from animal models
Institute of Scientific and Technical Information of China (English)
Kostas Pantopoulos
2008-01-01
Hereditary hemochromatosis (HH) is caused by chronic hyperabsorption of dietary iron. Progressive accumulation of excess iron within tissue parenchymal cells may lead to severe organ damage. The most prevalent type of HH is linked to mutations in the HFE gene, encoding an atypical major histocompatibility complex class Ⅰ molecule. Shortly after its discovery in 1996, the hemochromatosis protein HFE was shown to physically interact with transferrin receptor 1 (TfR1)and impair the uptake of transferrin-bound iron in cells. However, these findings provided no clue why /-/FE mutations associate with systemic iron overload.It was later established that all forms of HH result from misregulation of hepcidin expression. This liverderived circulating peptide hormone controls iron efflux from duodenal enterocytes and reticuloendothelial macrophages by promoting the degradation of the iron exporter ferroportin. Recent studies with animal models of HH uncover a crucial role of HFE as a hepatocyte iron sensor and upstream regulator of helpcidin. Thus,hepatocyte HFE is indispensable for signaling to hepcidin, presumably as a constituent of a larger ironsensing complex. A working model postulates that the signaling activity of HFE is silenced when the protein is bound to TfR1. An increase in the iron saturation of plasma transferrin leads to displacement of TfR1 from HFE and assembly of the putative iron-sensing complex.In this way, iron uptake by the hepatocyte is translated into upregulation of hepcidin, reinforcing the concept that the liver is the major regulatory site for systemic iron homeostasis, and not merely an iron storage depot.
Reduced Rank Mixed Effects Models for Spatially Correlated Hierarchical Functional Data
Zhou, Lan
2010-03-01
Hierarchical functional data are widely seen in complex studies where sub-units are nested within units, which in turn are nested within treatment groups. We propose a general framework of functional mixed effects model for such data: within unit and within sub-unit variations are modeled through two separate sets of principal components; the sub-unit level functions are allowed to be correlated. Penalized splines are used to model both the mean functions and the principal components functions, where roughness penalties are used to regularize the spline fit. An EM algorithm is developed to fit the model, while the specific covariance structure of the model is utilized for computational efficiency to avoid storage and inversion of large matrices. Our dimension reduction with principal components provides an effective solution to the difficult tasks of modeling the covariance kernel of a random function and modeling the correlation between functions. The proposed methodology is illustrated using simulations and an empirical data set from a colon carcinogenesis study. Supplemental materials are available online.
Wirth, Erin A.; Long, Maureen D.; Moriarty, John C.
2017-01-01
Teleseismic receiver functions contain information regarding Earth structure beneath a seismic station. P-to-SV converted phases are often used to characterize crustal and upper-mantle discontinuities and isotropic velocity structures. More recently, P-to-SH converted energy has been used to interrogate the orientation of anisotropy at depth, as well as the geometry of dipping interfaces. Many studies use a trial-and-error forward modeling approach for the interpretation of receiver functions, generating synthetic receiver functions from a user-defined input model of Earth structure and amending this model until it matches major features in the actual data. While often successful, such an approach makes it impossible to explore model space in a systematic and robust manner, which is especially important given that solutions are likely non-unique. Here, we present a Markov chain Monte Carlo algorithm with Gibbs sampling for the interpretation of anisotropic receiver functions. Synthetic examples are used to test the viability of the algorithm, suggesting that it works well for models with a reasonable number of free parameters (<˜20). Additionally, the synthetic tests illustrate that certain parameters are well constrained by receiver function data, while others are subject to severe trade-offs-an important implication for studies that attempt to interpret Earth structure based on receiver function data. Finally, we apply our algorithm to receiver function data from station WCI in the central United States. We find evidence for a change in anisotropic structure at mid-lithospheric depths, consistent with previous work that used a grid search approach to model receiver function data at this station. Forward modeling of receiver functions using model space search algorithms, such as the one presented here, provide a meaningful framework for interrogating Earth structure from receiver function data.
DEFF Research Database (Denmark)
Karunarathna, Anurudda Kumara; Kawamoto, Ken; Møldrup, Per
2010-01-01
Soil-water content (θ) and soil organic carbon (SOC) are key factors controlling the occurrence and magnitude of soil-water repellency (WR). Although expressions have recently been proposed to describe the nonlinear variation of WR with θ, the inclusion of easily measurable parameters in predictive...... conditions for 19 soils were used to test the model. The beta function successfully reproduced all the measured soil-water repellency characteristic, α(θ), curves. Significant correlations were found between model parameters and SOC content (1%-14%). The model was independently tested against data...... for further three soils and performed accurately for all three. Consequently, we suggest that the α(θ) model represents a useful strategy to predict the entire soil-water repellency characteristic curve, and thus potential risks for enhanced runoff and preferential (fingered) soil-water flow at given initial...
Redefining the Attraction Measure, Scaling Exponent and Impedance Function of the Gravity Model
Chen, Yanguang
2013-01-01
The attraction measure, scaling exponent, and impedance function of the gravity model are redefined using the concepts from fractals and spatial complexity. Firstly, the attraction measure of spatial interaction in human systems is defined by the product of traffic inflow and outflow. Based on the new definition, the gravity model originating from the Newtonian analogy is differentiated from Wilson's spatial interaction model deriving from entropy-maximizing principle. Secondly, the scaling exponent of the gravity model based on the inverse distance relationship is revealed to be the ratio of the fractal dimension of networks of cities to that of hierarchies of cities. The value of the scaling exponent is then shown to approach to 2, which corresponds to the value of the power exponent of the law of gravity in classical physics. Thirdly, the inverse power function is demonstrated to be more acceptable than the negative exponential function as an impedance function of the gravity model. The limits of applicati...
Infinite Relational Modeling of Functional Connectivity in Resting State fMRI
DEFF Research Database (Denmark)
Mørup, Morten; Madsen, Kristoffer H.; Dogonowski, Anne Marie
2010-01-01
of resting state as functional coherent groups we search for functional units of the brain that communicate with other parts of the brain in a coherent manner as measured by mutual information. We use the infinite relational model (IRM) to quantify functional coherent groups of resting state networks......Functional magnetic resonance imaging (fMRI) can be applied to study the functional connectivity of the neural elements which form complex network at a whole brain level. Most analyses of functional resting state networks (RSN) have been based on the analysis of correlation between the temporal...... dynamics of various regions of the brain. While these models can identify coherently behaving groups in terms of correlation they give little insight into how these groups interact. In this paper we take a different view on the analysis of functional resting state networks. Starting from the definition...
Employee subjective well-being and physiological functioning: An integrative model.
Kuykendall, Lauren; Tay, Louis
2015-01-01
Research shows that worker subjective well-being influences physiological functioning-an early signal of poor health outcomes. While several theoretical perspectives provide insights on this relationship, the literature lacks an integrative framework explaining the relationship. We develop a conceptual model explaining the link between subjective well-being and physiological functioning in the context of work. Integrating positive psychology and occupational stress perspectives, our model explains the relationship between subjective well-being and physiological functioning as a result of the direct influence of subjective well-being on physiological functioning and of their common relationships with work stress and personal resources, both of which are influenced by job conditions.
Optimal Penalty Functions Based on MCMC for Testing Homogeneity of Mixture Models
Directory of Open Access Journals (Sweden)
Rahman Farnoosh
2012-07-01
Full Text Available This study is intended to provide an estimation of penalty function for testing homogeneity of mixture models based on Markov chain Monte Carlo simulation. The penalty function is considered as a parametric function and parameter of determinative shape of the penalty function in conjunction with parameters of mixture models are estimated by a Bayesian approach. Different mixture of uniform distribution are used as prior. Some simulation examples are perform to confirm the efficiency of the present work in comparison with the previous approaches.
Hou, Likun; de la Torre, Jimmy; Nandakumar, Ratna
2014-01-01
Analyzing examinees' responses using cognitive diagnostic models (CDMs) has the advantage of providing diagnostic information. To ensure the validity of the results from these models, differential item functioning (DIF) in CDMs needs to be investigated. In this article, the Wald test is proposed to examine DIF in the context of CDMs. This study…
Azzopardi, George; Petkov, Nicolai
Simple cells in primary visual cortex are believed to extract local contour information from a visual scene. The 2D Gabor function (GF) model has gained particular popularity as a computational model of a simple cell. However, it short-cuts the LGN, it cannot reproduce a number of properties of real
A neuron model with trainable activation function (TAF) and its MFNN supervised learning
Institute of Scientific and Technical Information of China (English)
吴佑寿; 赵明生
2001-01-01
This paper addresses a new kind of neuron model, which has trainable activation function (TAF) in addition to only trainable weights in the conventional M-P model. The final neuron activation function can be derived from a primitive neuron activation function by training. The BP like learning algorithm has been presented for MFNN constructed by neurons of TAF model. Several simulation examples are given to show the network capacity and performance advantages of the new MFNN in comparison with that of conventional sigmoid MFNN.
The polarized structure function of the nucleons with a non-extensive statistical quark model
Trevisan, Luis A.; Mirez, Carlos
2013-05-01
We studied an application of nonextensive thermodynamics to describe the polarized structure function of nucleon, in a model where the usual Fermi-Dirac and Bose-Einstein energy distribution, often used in the statistical models, were replaced by the equivalent functions of the q-statistical. The parameters of the model are given by an effective temperature T, the q parameter (from Tsallis statistics), and the chemical potentials given by the corresponding up (u) and down (d) quark normalization in the nucleon and by Δu and Δd of the polarized functions.
New data model with better functionality for VLab
da Silveira, P. R.; Wentzcovitch, R. M.; Karki, B. B.
2009-12-01
The VLab infrastructure and architecture was further developed to allow for several new features. First, workflows for first principles calculations of thermodynamics properties and static elasticity programmed in Java as Web Services can now be executed by multiple users. Second, jobs generated by these workflows can now be executed in batch in multiple servers. A simple internal schedule was implemented to handle hundreds of execution packages generated by multiple users and avoid the overload on servers. Third, a new data model was implemented to guarantee integrity of a project (workflow execution) in case of failure. The latter can happen in an execution package or in a workflow phase. By recording all executed steps of a project, its execution can be resumed after dynamic alteration of parameters through the VLab Portal. Fourth, batch jobs can also be monitored through the portal. Now, better and faster interaction with servers is achieved using Ajax technology. Finally, plots are now created on the Vlab server using Gnuplot 4.2.2. Research supported by NSF grants ATM 0428774 (VLab). Vlab is hosted by the Minnesota Supercomputing Institute.
Analysis and Application of Mechanical System Reliability Model Based on Copula Function
Directory of Open Access Journals (Sweden)
An Hai
2016-10-01
Full Text Available There is complicated correlations in mechanical system. By using the advantages of copula function to solve the related issues, this paper proposes the mechanical system reliability model based on copula function. And makes a detailed research for the serial and parallel mechanical system model and gets their reliability function respectively. Finally, the application research is carried out for serial mechanical system reliability model to prove its validity by example. Using Copula theory to make mechanical system reliability modeling and its expectation, studying the distribution of the random variables (marginal distribution of the mechanical product’ life and associated structure of variables separately, can reduce the difficulty of multivariate probabilistic modeling and analysis to make the modeling and analysis process more clearly.
Predictive functional control based on fuzzy T-S model for HVAC systems temperature control
Institute of Scientific and Technical Information of China (English)
Hongli L(U); Lei JIA; Shulan KONG; Zhaosheng ZHANG
2007-01-01
In heating,ventilating and air-conditioning(HVAC)systems,there exist severe nonlinearity,time-varying nature,disturbances and uncertainties.A new predictive functional control based on Takagi-Sugeno(T-S)fuzzy model was proposed to control HVAC systems.The T-S fuzzy model of stabilized controlled process was obtained using the least squares method,then on the basis of global linear predictive model from T-S fuzzy model,the process was controlled by the predictive functional controller.Especially the feedback regulation part was developed to compensate uncertainties of fuzzy predictive model.Finally simulation test results in HVAC systems control applications showed that the proposed fuzzy model predictive functional control improves tracking effect and robustness.Compared with the conventional PID controller,this control strategy has the advantages of less overshoot and shorter setting time,etc.
Chen, Yongsheng; Persaud, Bhagwant
2014-09-01
Crash modification factors (CMFs) for road safety treatments are developed as multiplicative factors that are used to reflect the expected changes in safety performance associated with changes in highway design and/or the traffic control features. However, current CMFs have methodological drawbacks. For example, variability with application circumstance is not well understood, and, as important, correlation is not addressed when several CMFs are applied multiplicatively. These issues can be addressed by developing safety performance functions (SPFs) with components of crash modification functions (CM-Functions), an approach that includes all CMF related variables, along with others, while capturing quantitative and other effects of factors and accounting for cross-factor correlations. CM-Functions can capture the safety impact of factors through a continuous and quantitative approach, avoiding the problematic categorical analysis that is often used to capture CMF variability. There are two formulations to develop such SPFs with CM-Function components - fully specified models and hierarchical models. Based on sample datasets from two Canadian cities, both approaches are investigated in this paper. While both model formulations yielded promising results and reasonable CM-Functions, the hierarchical model was found to be more suitable in retaining homogeneity of first-level SPFs, while addressing CM-Functions in sub-level modeling. In addition, hierarchical models better capture the correlations between different impact factors.
Hong, X; Harris, C J
2000-01-01
This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bézier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bézier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bézier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bézier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.
2016-01-01
Statistical downscaling is used to improve the knowledge of spatial distributions from broad–scale to fine–scale maps with higher potential for conservation planning. We assessed the effectiveness of downscaling in two commonly used species distribution models: Maximum Entropy (MaxEnt) and the Favourability Function (FF). We used atlas data (10 x 10 km) of the fire salamander Salamandra salamandra distribution in southern Spain to derive models at a 1 x 1 km resolution. Downscaled models were...
Flexible parametric modelling of the cause-specific cumulative incidence function.
Lambert, Paul C; Wilkes, Sally R; Crowther, Michael J
2016-12-22
Competing risks arise with time-to-event data when individuals are at risk of more than one type of event and the occurrence of one event precludes the occurrence of all other events. A useful measure with competing risks is the cause-specific cumulative incidence function (CIF), which gives the probability of experiencing a particular event as a function of follow-up time, accounting for the fact that some individuals may have a competing event. When modelling the cause-specific CIF, the most common model is a semi-parametric proportional subhazards model. In this paper, we propose the use of flexible parametric survival models to directly model the cause-specific CIF where the effect of follow-up time is modelled using restricted cubic splines. The models provide smooth estimates of the cause-specific CIF with the important advantage that the approach is easily extended to model time-dependent effects. The models can be fitted using standard survival analysis tools by a combination of data expansion and introducing time-dependent weights. Various link functions are available that allow modelling on different scales and have proportional subhazards, proportional odds and relative absolute risks as particular cases. We conduct a simulation study to evaluate how well the spline functions approximate subhazard functions with complex shapes. The methods are illustrated using data from the European Blood and Marrow Transplantation Registry showing excellent agreement between parametric estimates of the cause-specific CIF and those obtained from a semi-parametric model. We also fit models relaxing the proportional subhazards assumption using alternative link functions and/or including time-dependent effects. Copyright © 2016 John Wiley & Sons, Ltd.
Links, Jonathan M; Schwartz, Brian S; Lin, Sen; Kanarek, Norma; Mitrani-Reiser, Judith; Sell, Tara Kirk; Watson, Crystal R; Ward, Doug; Slemp, Cathy; Burhans, Robert; Gill, Kimberly; Igusa, Tak; Zhao, Xilei; Aguirre, Benigno; Trainor, Joseph; Nigg, Joanne; Inglesby, Thomas; Carbone, Eric; Kendra, James M
2017-06-21
Policy-makers and practitioners have a need to assess community resilience in disasters. Prior efforts conflated resilience with community functioning, combined resistance and recovery (the components of resilience), and relied on a static model for what is inherently a dynamic process. We sought to develop linked conceptual and computational models of community functioning and resilience after a disaster. We developed a system dynamics computational model that predicts community functioning after a disaster. The computational model outputted the time course of community functioning before, during, and after a disaster, which was used to calculate resistance, recovery, and resilience for all US counties. The conceptual model explicitly separated resilience from community functioning and identified all key components for each, which were translated into a system dynamics computational model with connections and feedbacks. The components were represented by publicly available measures at the county level. Baseline community functioning, resistance, recovery, and resilience evidenced a range of values and geographic clustering, consistent with hypotheses based on the disaster literature. The work is transparent, motivates ongoing refinements, and identifies areas for improved measurements. After validation, such a model can be used to identify effective investments to enhance community resilience.(Disaster Med Public Health Preparedness. 2017;page 1 of 11).
Theoretical model for mesoscopic-level scale-free self-organization of functional brain networks.
Piersa, Jaroslaw; Piekniewski, Filip; Schreiber, Tomasz
2010-11-01
In this paper, we provide theoretical and numerical analysis of a geometric activity flow network model which is aimed at explaining mathematically the scale-free functional graph self-organization phenomena emerging in complex nervous systems at a mesoscale level. In our model, each unit corresponds to a large number of neurons and may be roughly seen as abstracting the functional behavior exhibited by a single voxel under functional magnetic resonance imaging (fMRI). In the course of the dynamics, the units exchange portions of formal charge, which correspond to waves of activity in the underlying microscale neuronal circuit. The geometric model abstracts away the neuronal complexity and is mathematically tractable, which allows us to establish explicit results on its ground states and the resulting charge transfer graph modeling functional graph of the network. We show that, for a wide choice of parameters and geometrical setups, our model yields a scale-free functional connectivity with the exponent approaching 2, which is in agreement with previous empirical studies based on fMRI. The level of universality of the presented theory allows us to claim that the model does shed light on mesoscale functional self-organization phenomena of the nervous system, even without resorting to closer details of brain connectivity geometry which often remain unknown. The material presented here significantly extends our previous work where a simplified mean-field model in a similar spirit was constructed, ignoring the underlying network geometry.
Operator functional state estimation based on EEG-data-driven fuzzy model.
Zhang, Jianhua; Yin, Zhong; Yang, Shaozeng; Wang, Rubin
2016-10-01
This paper proposed a max-min-entropy-based fuzzy partition method for fuzzy model based estimation of human operator functional state (OFS). The optimal number of fuzzy partitions for each I/O variable of fuzzy model is determined by using the entropy criterion. The fuzzy models were constructed by using Wang-Mendel method. The OFS estimation results showed the practical usefulness of the proposed fuzzy modeling approach.
Wismueller, Axel; Lange, Oliver; Auer, Dorothee; Leinsinger, Gerda
2010-03-01
Slowly varying temporally correlated activity fluctuations between functionally related brain areas have been identified by functional magnetic resonance imaging (fMRI) research in recent years. These low-frequency oscillations of less than 0.08 Hz appear to play a major role in various dynamic functional brain networks, such as the so-called 'default mode' network. They also have been observed as a property of symmetric cortices, and they are known to be present in the motor cortex among others. These low-frequency data are difficult to detect and quantify in fMRI. Traditionally, user-based regions of interests (ROI) or 'seed clusters' have been the primary analysis method. In this paper, we propose unsupervised clustering algorithms based on various distance measures to detect functional connectivity in resting state fMRI. The achieved results are evaluated quantitatively for different distance measures. The Euclidian metric implemented by standard unsupervised clustering approaches is compared with a non-metric topographic mapping of proximities based on the the mutual prediction error between pixel-specific signal dynamics time-series. It is shown that functional connectivity in the motor cortex of the human brain can be detected based on such model-free analysis methods for resting state fMRI.
Directory of Open Access Journals (Sweden)
Y. Kakinami
2009-08-01
Full Text Available Empirical models of Total Electron Content (TEC based on functional fitting over Taiwan (120° E, 24° N have been constructed using data of the Global Positioning System (GPS from 1998 to 2007 during geomagnetically quiet condition (D_{st}>−30 nT. The models provide TEC as functions of local time (LT, day of year (DOY and the solar activity (F, which are represented by 1–162 days mean of F10.7 and EUV. Other models based on median values have been also constructed and compared with the models based on the functional fitting. Under same values of F parameter, the models based on the functional fitting show better accuracy than those based on the median values in all cases. The functional fitting model using daily EUV is the most accurate with 9.2 TECu of root mean square error (RMS than the 15-days running median with 10.4 TECu RMS and the model of International Reference Ionosphere 2007 (IRI2007 with 14.7 TECu RMS. IRI2007 overestimates TEC when the solar activity is low, and underestimates TEC when the solar activity is high. Though average of 81 days centered running mean of F10.7 and daily F10.7 is often used as indicator of EUV, our result suggests that average of F10.7 mean from 1 to 54 day prior and current day is better than the average of 81 days centered running mean for reproduction of TEC. This paper is for the first time comparing the median based model with the functional fitting model. Results indicate the functional fitting model yielding a better performance than the median based one. Meanwhile we find that the EUV radiation is essential to derive an optimal TEC.
Effects of Interactive Function Forms in a Self-Organized Critical Model Based on Neural Networks
Institute of Scientific and Technical Information of China (English)
ZHAOXiao-Wei; ZHOULi-Ming; CHENTian-Lun
2003-01-01
Based on the standard self-organizing map neural network model and an integrate-and-fire mechanism, we introduce a kind of coupled map lattice system to investigate scale-invariance behavior in the activity of model neural populations. We let the parameter β, which together with α represents the interactive strength between neurons, have different function forms, and we find the function forms and their parameters are very important to our model''s avalanche dynamical behaviors, especially to the emergence of different avalanche behaviors in different areas of our system.
A new kind of neuron model with a tunable activation function and its applications
Institute of Scientific and Technical Information of China (English)
吴佑寿; 赵明生; 丁晓青
1997-01-01
A new neuron model with a tunable activation function, denoted by the TAF model, and its application are addressed. The activation function as well as the connection weights of the neuron model can be adjusted in the training process The two-spiral problem was used as an example to show how to deduce the adjustable activation function required, and how to construct and train the network by the use of the a priori knowledge of the problem. Due to the incorporation of constraints known a priori into the activation function, many novel aspects are revealed, such as small network size, fast learning and good performances. It is believed that the introduction of the new neuron model will pave a new way in ANN studies.
Gauge Coupling Beta Functions in the Standard Model to Three Loops
Mihaila, Luminita N; Steinhauser, Matthias
2012-01-01
In this paper we compute the three-loop corrections to the beta functions of the three gauge couplings in the Standard Model of particle physics using the minimal subtraction scheme and taking into account Yukawa and Higgs self couplings.
Real-time Estimation of UAS Performance Using Efficient Sampling of Functional Models Project
National Aeronautics and Space Administration — Numerica proposes to developed advanced algorithms for constructing a UAS vehicle model from ATC surveillance data in real-time. Using functional descriptions of...
On Bayes linear unbiased estimation of estimable functions for the singular linear model
Institute of Scientific and Technical Information of China (English)
ZHANG Weiping; WEI Laisheng
2005-01-01
The unique Bayes linear unbiased estimator (Bayes LUE) of estimable functions is derived for the singular linear model. The superiority of Bayes LUE over ordinary best linear unbiased estimator is investigated under mean square error matrix (MSEM)criterion.
Loredo, Alexandre
2013-01-01
A multilayered plate theory which uses transverse shear warping functions issued from three-dimensional elasticity is presented. Two methods to obtain these transverse shear warping functions are detailed. The warping functions are issued from the variations of transverse shear stresses computed at special location points for a simply supported bending problem. The first method considers an exact 3D solution of the problem. The second method uses the solution provided by the model itself: the transverse shear stresses are computed by the integration of equilibrium equations. Hence, an iterative process is applied, the model being updated with the new warping functions, and so on. These two models are compared to other models and to analytical solutions for the bending of simply supported plates. Four different laminates and a sandwich are considered, length-to-thickness values varying from 2 to 100. An additional analytical solution that simulates the behavior of laminates under the plane stress hypothesis - ...
A conceptual model of food quality management functions based on a techno-managerial approach
Luning, P.A.; Marcelis, W.J.
2007-01-01
In agribusiness and food industry quality management problems are commonly approached by applying control systems and procedures. However, assuming predictable food systems and people following procedures seems too straightforward. This paper introduces a model of food quality management functions t
Wan, Songlin; Zhang, Xiangchao; He, Xiaoying; Xu, Min
2016-12-20
Computer controlled optical surfacing requires an accurate tool influence function (TIF) for reliable path planning and deterministic fabrication. Near the edge of the workpieces, the TIF has a nonlinear removal behavior, which will cause a severe edge-roll phenomenon. In the present paper, a new edge pressure model is developed based on the finite element analysis results. The model is represented as the product of a basic pressure function and a correcting function. The basic pressure distribution is calculated according to the surface shape of the polishing pad, and the correcting function is used to compensate the errors caused by the edge effect. Practical experimental results demonstrate that the new model can accurately predict the edge TIFs with different overhang ratios. The relative error of the new edge model can be reduced to 15%.
A conceptual model of food quality management functions based on a techno-managerial approach
Luning, P.A.; Marcelis, W.J.
2007-01-01
In agribusiness and food industry quality management problems are commonly approached by applying control systems and procedures. However, assuming predictable food systems and people following procedures seems too straightforward. This paper introduces a model of food quality management functions
Energy Technology Data Exchange (ETDEWEB)
Lind, M. [Oersted - DTU, Kgs. Lyngby (Denmark)
2005-10-01
Multilevel Flow Modeling (MFM) has proven to be an effective modeling tool for reasoning about plant failure and control strategies and is currently exploited for operator support in diagnosis and on-line alarm analysis. Previous MFM research was focussed on representing goals and functions of process plants which generate, transform and distribute mass and energy. However, only a limited consideration has been given to the problems of modeling the control systems. Control functions are indispensable for operating any industrial plant. But modeling of control system functions has proven to be a more challenging problem than modeling functions of energy and mass processes. The problems were discussed by Lind and tentative solutions has been proposed but have not been investigated in depth until recently, partly due to the lack of an appropriate theoretical foundation. The purposes of the present report are to show that such a theoretical foundation for modeling goals and functions of control systems can be built from concepts and theories of action developed by Von Wright and to show how the theoretical foundation can be used to extend MFM with concepts for modeling control systems. The theoretical foundations has been presented in detail elsewhere by the present author without the particular focus on modeling control actions and MFM adopted here. (au)
Modeling the Near-Infrared Luminosity Functions of Young Stellar Clusters
Münch, A; Lada, C J; Muench, August A.; Lada, Elizabeth A.; Lada, Charles J.
1999-01-01
We present the results of numerical experiments designed to evaluate the usefulness of near-infrared luminosity functions for constraining the Initial Mass Function (IMF) of young stellar populations. From this numerical modeling, we find that the luminosity function of a young stellar population is considerably more sensitive to variations in the underlying initial mass function than to either variations in the star forming history or assumed pre-main-sequence (PMS) mass-to-luminosity relation. To illustrate the potential effectiveness of using the KLF of a young cluster to constrain its IMF, we model the observed K band luminosity function of the nearby Trapezium cluster. Our derived mass function for the Trapezium spans two orders of magnitude in stellar mass (5 Msun to 0.02 Msun), has a peak near the hydrogen burning limit, and has an IMF for Brown Dwarfs which steadily decreases with decreasing mass.