Functional Generalized Additive Models.
McLean, Mathew W; Hooker, Giles; Staicu, Ana-Maria; Scheipl, Fabian; Ruppert, David
2014-01-01
We introduce the functional generalized additive model (FGAM), a novel regression model for association studies between a scalar response and a functional predictor. We model the link-transformed mean response as the integral with respect to t of F{X(t), t} where F(·,·) is an unknown regression function and X(t) is a functional covariate. Rather than having an additive model in a finite number of principal components as in Müller and Yao (2008), our model incorporates the functional predictor directly and thus our model can be viewed as the natural functional extension of generalized additive models. We estimate F(·,·) using tensor-product B-splines with roughness penalties. A pointwise quantile transformation of the functional predictor is also considered to ensure each tensor-product B-spline has observed data on its support. The methods are evaluated using simulated data and their predictive performance is compared with other competing scalar-on-function regression alternatives. We illustrate the usefulness of our approach through an application to brain tractography, where X(t) is a signal from diffusion tensor imaging at position, t, along a tract in the brain. In one example, the response is disease-status (case or control) and in a second example, it is the score on a cognitive test. R code for performing the simulations and fitting the FGAM can be found in supplemental materials available online.
Modeling mitochondrial function.
Balaban, Robert S
2006-12-01
The mitochondrion represents a unique opportunity to apply mathematical modeling to a complex biological system. Understanding mitochondrial function and control is important since this organelle is critical in energy metabolism as well as playing key roles in biochemical synthesis, redox control/signaling, and apoptosis. A mathematical model, or hypothesis, provides several useful insights including a rigorous test of the consensus view of the operation of a biological process as well as providing methods of testing and creating new hypotheses. The advantages of the mitochondrial system for applying a mathematical model include the relative simplicity and understanding of the matrix reactions, the ability to study the mitochondria as a independent contained organelle, and, most importantly, one can dynamically measure many of the internal reaction intermediates, on line. The developing ability to internally monitor events within the metabolic network, rather than just the inflow and outflow, is extremely useful in creating critical bounds on complex mathematical models using the individual reaction mechanisms available. However, many serious problems remain in creating a working model of mitochondrial function including the incomplete definition of metabolic pathways, the uncertainty of using in vitro enzyme kinetics, as well as regulatory data in the intact system and the unknown chemical activities of relevant molecules in the matrix. Despite these formidable limitations, the advantages of the mitochondrial system make it one of the best defined mammalian metabolic networks that can be used as a model system for understanding the application and use of mathematical models to study biological systems.
Modelling of graphene functionalization.
Pykal, Martin; Jurečka, Petr; Karlický, František; Otyepka, Michal
2016-03-01
Graphene has attracted great interest because of its remarkable properties and numerous potential applications. A comprehensive understanding of its structural and dynamic properties and those of its derivatives will be required to enable the design and optimization of sophisticated new nanodevices. While it is challenging to perform experimental studies on nanoscale systems at the atomistic level, this is the 'native' scale of computational chemistry. Consequently, computational methods are increasingly being used to complement experimental research in many areas of chemistry and nanotechnology. However, it is difficult for non-experts to get to grips with the plethora of computational tools that are available and their areas of application. This perspective briefly describes the available theoretical methods and models for simulating graphene functionalization based on quantum and classical mechanics. The benefits and drawbacks of the individual methods are discussed, and we provide numerous examples showing how computational methods have provided new insights into the physical and chemical features of complex systems including graphene and graphene derivatives. We believe that this overview will help non-expert readers to understand this field and its great potential. PMID:26323438
Modeling Protein Domain Function
ERIC Educational Resources Information Center
Baker, William P.; Jones, Carleton "Buck"; Hull, Elizabeth
2007-01-01
This simple but effective laboratory exercise helps students understand the concept of protein domain function. They use foam beads, Styrofoam craft balls, and pipe cleaners to explore how domains within protein active sites interact to form a functional protein. The activity allows students to gain content mastery and an understanding of the…
Computational Models for Neuromuscular Function
Valero-Cuevas, Francisco J.; Hoffmann, Heiko; Kurse, Manish U.; Kutch, Jason J.; Theodorou, Evangelos A.
2011-01-01
Computational models of the neuromuscular system hold the potential to allow us to reach a deeper understanding of neuromuscular function and clinical rehabilitation by complementing experimentation. By serving as a means to distill and explore specific hypotheses, computational models emerge from prior experimental data and motivate future experimental work. Here we review computational tools used to understand neuromuscular function including musculoskeletal modeling, machine learning, control theory, and statistical model analysis. We conclude that these tools, when used in combination, have the potential to further our understanding of neuromuscular function by serving as a rigorous means to test scientific hypotheses in ways that complement and leverage experimental data. PMID:21687779
Neural modeling and functional neuroimaging.
Horwitz, B; Sporns, O
1994-01-01
Two research areas that so far have had little interaction with one another are functional neuroimaging and computational neuroscience. The application of computational models and techniques to the inherently rich data sets generated by "standard" neurophysiological methods has proven useful for interpreting these data sets and for providing predictions and hypotheses for further experiments. We suggest that both theory- and data-driven computational modeling of neuronal systems can help to interpret data generated by functional neuroimaging methods, especially those used with human subjects. In this article, we point out four sets of questions, addressable by computational neuroscientists whose answere would be of value and interest to those who perform functional neuroimaging. The first set consist of determining the neurobiological substrate of the signals measured by functional neuroimaging. The second set concerns developing systems-level models of functional neuroimaging data. The third set of questions involves integrating functional neuroimaging data across modalities, with a particular emphasis on relating electromagnetic with hemodynamic data. The last set asks how one can relate systems-level models to those at the neuronal and neural ensemble levels. We feel that there are ample reasons to link functional neuroimaging and neural modeling, and that combining the results from the two disciplines will result in furthering our understanding of the central nervous system. © 1994 Wiley-Liss, Inc. This Article is a US Goverment work and, as such, is in the public domain in the United State of America.
NASA Astrophysics Data System (ADS)
Hibbard, Bill
2012-05-01
Orseau and Ring, as well as Dewey, have recently described problems, including self-delusion, with the behavior of agents using various definitions of utility functions. An agent's utility function is defined in terms of the agent's history of interactions with its environment. This paper argues, via two examples, that the behavior problems can be avoided by formulating the utility function in two steps: 1) inferring a model of the environment from interactions, and 2) computing utility as a function of the environment model. Basing a utility function on a model that the agent must learn implies that the utility function must initially be expressed in terms of specifications to be matched to structures in the learned model. These specifications constitute prior assumptions about the environment so this approach will not work with arbitrary environments. But the approach should work for agents designed by humans to act in the physical world. The paper also addresses the issue of self-modifying agents and shows that if provided with the possibility to modify their utility functions agents will not choose to do so, under some usual assumptions.
Neuronal models of cognitive functions.
Changeux, J P; Dehaene, S
1989-11-01
Understanding the neural bases of cognition has become a scientifically tractable problem, and neurally plausible models are proposed to establish a causal link between biological structure and cognitive function. To this end, levels of organization have to be defined within the functional architecture of neuronal systems. Transitions from any one of these interacting levels to the next are viewed in an evolutionary perspective. They are assumed to involve: (1) the production of multiple transient variations and (2) the selection of some of them by higher levels via the interaction with the outside world. The time-scale of these "evolutions" is expected to differ from one level to the other. In the course of development and in the adult this internal evolution is epigenetic and does not require alteration of the structure of the genome. A selective stabilization (and elimination) of synaptic connections by spontaneous and/or evoked activity in developing neuronal networks is postulated to contribute to the shaping of the adult connectivity within an envelope of genetically encoded forms. At a higher level, models of mental representations, as states of activity of defined populations of neurons, are discussed in terms of statistical physics, and their storage is viewed as a process of selection among variable and transient pre-representations. Theoretical models illustrate that cognitive functions such as short-term memory and handling of temporal sequences may be constrained by "microscopic" physical parameters. Finally, speculations are offered about plausible neuronal models and selectionist implementations of intentions. PMID:2691185
Transfer Function Identification Using Orthogonal Fourier Transform Modeling Functions
NASA Technical Reports Server (NTRS)
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.
Function Model for Community Health Service Information
NASA Astrophysics Data System (ADS)
Yang, Peng; Pan, Feng; Liu, Danhong; Xu, Yongyong
In order to construct a function model of community health service (CHS) information for development of CHS information management system, Integration Definition for Function Modeling (IDEF0), an IEEE standard which is extended from Structured Analysis and Design(SADT) and now is a widely used function modeling method, was used to classifying its information from top to bottom. The contents of every level of the model were described and coded. Then function model for CHS information, which includes 4 super-classes, 15 classes and 28 sub-classed of business function, 43 business processes and 168 business activities, was established. This model can facilitate information management system development and workflow refinement.
Belief Function Model for Information Retrieval.
ERIC Educational Resources Information Center
Silva, Wagner Teixeira da; Milidiu, Ruy Luiz
1993-01-01
Describes the Belief Function Model for automatic indexing and ranking of documents which is based on a controlled vocabulary and on term frequencies in each document. Belief Function Theory is explained, and the Belief Function Model is compared to the Standard Vector Space Model. (17 references) (LRW)
Crossing Hazard Functions in Common Survival Models
Zhang, Jiajia; Peng, Yingwei
2010-01-01
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. PMID:20613974
Functional Risk Modeling for Lunar Surface Systems
NASA Technical Reports Server (NTRS)
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 volumes modeling: theory and preliminary assessment.
Fox, P T; Lancaster, J L; Parsons, L M; Xiong, J H; Zamarripa, F
1997-01-01
A construct for metanalytic modeling of the functional organization of the human brain, termed functional volumes modeling (FVM), is presented and preliminarily tested. FVM uses the published literature to model brain functional areas as spatial probability distributions. The FVM statistical model estimates population variance (i.e., among individuals) from the variance observed among group-mean studies, these being the most prevalent type of study in the functional imaging literature. The FVM modeling strategy is tested by: (1) constructing an FVM of the mouth region of primary motor cortex using published, group-mean, functional imaging reports as input, and (2) comparing the confidence bounds predicted by that FVM with those observed in 10 normal subjects performing overt-speech tasks. The FVM model correctly predicted the mean location and spatial distribution of per-subject functional responses. FVM has a wide range of applications, including hypothesis testing for statistical parametric images.
Bootstrapped models for intrinsic random functions
Campbell, K.
1988-08-01
Use of intrinsic random function stochastic models as a basis for estimation in geostatistical work requires the identification of the generalized covariance function of the underlying process. The fact that this function has to be estimated from data introduces an additional source of error into predictions based on the model. This paper develops the sample reuse procedure called the bootstrap in the context of intrinsic random functions to obtain realistic estimates of these errors. Simulation results support the conclusion that bootstrap distributions of functionals of the process, as well as their kriging variance, provide a reasonable picture of variability introduced by imperfect estimation of the generalized covariance function.
Bootstrapped models for intrinsic random functions
Campbell, K.
1987-01-01
The use of intrinsic random function stochastic models as a basis for estimation in geostatistical work requires the identification of the generalized covariance function of the underlying process, and the fact that this function has to be estimated from the data introduces an additional source of error into predictions based on the model. This paper develops the sample reuse procedure called the ''bootstrap'' in the context of intrinsic random functions to obtain realistic estimates of these errors. Simulation results support the conclusion that bootstrap distributions of functionals of the process, as well as of their ''kriging variance,'' provide a reasonable picture of the variability introduced by imperfect estimation of the generalized covariance function.
Modeling of functional brain imaging data
NASA Astrophysics Data System (ADS)
Horwitz, Barry
1999-03-01
The richness and complexity of data sets obtained from functional neuroimaging studies of human cognitive behavior, using techniques such as positron emission tomography and functional magnetic resonance imaging, have until recently not been exploited by computational neural modeling methods. In this article, following a brief introduction to functional neuroimaging methodology, two neural modeling approaches for use with functional brain imaging data are described. One, which uses structural equation modeling, examines the effective functional connections between various brain regions during specific cognitive tasks. The second employs large-scale neural modeling to relate functional neuroimaging signals in multiple, interconnected brain regions to the underlying neurobiological time-varying activities in each region. These two modeling procedures are illustrated using a visual processing paradigm.
Computational Modeling of Mitochondrial Function
Cortassa, Sonia; Aon, Miguel A.
2012-01-01
The advent of techniques with the ability to scan massive changes in cellular makeup (genomics, proteomics, etc.) has revealed the compelling need for analytical methods to interpret and make sense of those changes. Computational models built on sound physico-chemical mechanistic basis are unavoidable at the time of integrating, interpreting, and simulating high-throughput experimental data. Another powerful role of computational models is predicting new behavior provided they are adequately validated. Mitochondrial energy transduction has been traditionally studied with thermodynamic models. More recently, kinetic or thermo-kinetic models have been proposed, leading the path toward an understanding of the control and regulation of mitochondrial energy metabolism and its interaction with cytoplasmic and other compartments. In this work, we outline the methods, step-by-step, that should be followed to build a computational model of mitochondrial energetics in isolation or integrated to a network of cellular processes. Depending on the question addressed by the modeler, the methodology explained herein can be applied with different levels of detail, from the mitochondrial energy producing machinery in a network of cellular processes to the dynamics of a single enzyme during its catalytic cycle. PMID:22057575
Nonlinear aerodynamic modeling using multivariate orthogonal functions
NASA Technical Reports Server (NTRS)
Morelli, Eugene A.
1993-01-01
A technique was developed for global modeling of nonlinear aerodynamic coefficients using multivariate orthogonal functions based on the data. Each orthogonal function retained in the model was decomposed into an expansion of ordinary polynomials in the independent variables, so that the final model could be interpreted as selectively retained terms from a multivariable power series expansion. A predicted squared-error metric was used to determine the orthogonal functions to be retained in the model; analytical derivatives were easily computed. The approach was demonstrated on the Z-body axis aerodynamic force coefficient (Cz) wind tunnel data for an F-18 research vehicle which came from a tabular wind tunnel and covered the entire subsonic flight envelope. For a realistic case, the analytical model predicted experimental values of Cz very well. The modeling technique is shown to be capable of generating a compact, global analytical representation of nonlinear aerodynamics. The polynomial model has good predictive capability, global validity, and analytical differentiability.
Response Surface Modeling Using Multivariate Orthogonal Functions
NASA Technical Reports Server (NTRS)
Morelli, Eugene A.; DeLoach, Richard
2001-01-01
A nonlinear modeling technique was used to characterize response surfaces for non-dimensional longitudinal aerodynamic force and moment coefficients, based on wind tunnel data from a commercial jet transport model. Data were collected using two experimental procedures - one based on modem design of experiments (MDOE), and one using a classical one factor at a time (OFAT) approach. The nonlinear modeling technique used multivariate orthogonal functions generated from the independent variable data as modeling functions in a least squares context to characterize the response surfaces. Model terms were selected automatically using a prediction error metric. Prediction error bounds computed from the modeling data alone were found to be- a good measure of actual prediction error for prediction points within the inference space. Root-mean-square model fit error and prediction error were less than 4 percent of the mean response value in all cases. Efficacy and prediction performance of the response surface models identified from both MDOE and OFAT experiments were investigated.
The NJL Model for Quark Fragmentation Functions
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.
Functional model of biological neural networks
2010-01-01
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. PMID:22132040
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.
Understanding human functioning using graphical models
2010-01-01
Background Functioning and disability are universal human experiences. However, our current understanding of functioning from a comprehensive perspective is limited. The development of the International Classification of Functioning, Disability and Health (ICF) on the one hand and recent developments in graphical modeling on the other hand might be combined and open the door to a more comprehensive understanding of human functioning. The objective of our paper therefore is to explore how graphical models can be used in the study of ICF data for a range of applications. Methods We show the applicability of graphical models on ICF data for different tasks: Visualization of the dependence structure of the data set, dimension reduction and comparison of subpopulations. Moreover, we further developed and applied recent findings in causal inference using graphical models to estimate bounds on intervention effects in an observational study with many variables and without knowing the underlying causal structure. Results In each field, graphical models could be applied giving results of high face-validity. In particular, graphical models could be used for visualization of functioning in patients with spinal cord injury. The resulting graph consisted of several connected components which can be used for dimension reduction. Moreover, we found that the differences in the dependence structures between subpopulations were relevant and could be systematically analyzed using graphical models. Finally, when estimating bounds on causal effects of ICF categories on general health perceptions among patients with chronic health conditions, we found that the five ICF categories that showed the strongest effect were plausible. Conclusions Graphical Models are a flexible tool and lend themselves for a wide range of applications. In particular, studies involving ICF data seem to be suited for analysis using graphical models. PMID:20149230
Rational transfer function models for biofilm reactors
Wik, T.; Breitholtz, C.
1998-12-01
Design of controllers and optimization of plants using biofilm reactors often require dynamic models and efficient simulation methods. Standard model assumptions were used to derive nonrational transfer functions describing the fast dynamics of stirred-tank reactors with zero- or first-order reactions inside the biofilm. A method based on the location of singularities was used to derive rational transfer functions that approximate nonrational ones. These transfer functions can be used in efficient simulation routines and in standard methods of controller design. The order of the transfer functions can be chosen in a natural way, and changes in physical parameters may directly be related to changes in the transfer functions. Further, the mass balances used and, hence, the transfer functions, are applicable to catalytic reactors with porous catalysts as well. By applying the methods to a nitrifying trickling filter, reactor parameters are estimated from residence-time distributions and low-order rational transfer functions are achieved. Simulated effluent dynamics, using these transfer functions, agree closely with measurements.
Incorporating covariates in skewed functional data models.
Li, Meng; Staicu, Ana-Maria; Bondell, Howard D
2015-07-01
We introduce a class of covariate-adjusted skewed functional models (cSFM) designed for functional data exhibiting location-dependent marginal distributions. We propose a semi-parametric copula model for the pointwise marginal distributions, which are allowed to depend on covariates, and the functional dependence, which is assumed covariate invariant. The proposed cSFM framework provides a unifying platform for pointwise quantile estimation and trajectory prediction. We consider a computationally feasible procedure that handles densely as well as sparsely observed functional data. The methods are examined numerically using simulations and is applied to a new tractography study of multiple sclerosis. Furthermore, the methodology is implemented in the R package cSFM, which is publicly available on CRAN.
Functional Error Models to Accelerate Nested Sampling
NASA Astrophysics Data System (ADS)
Josset, L.; Elsheikh, A. H.; Demyanov, V.; Lunati, I.
2014-12-01
The main challenge in groundwater problems is the reliance on large numbers of unknown parameters with wide rage of associated uncertainties. To translate this uncertainty to quantities of interest (for instance the concentration of pollutant in a drinking well), a large number of forward flow simulations is required. To make the problem computationally tractable, Josset et al. (2013, 2014) introduced the concept of functional error models. It consists in two elements: a proxy model that is cheaper to evaluate than the full physics flow solver and an error model to account for the missing physics. The coupling of the proxy model and the error models provides reliable predictions that approximate the full physics model's responses. The error model is tailored to the problem at hand by building it for the question of interest. It follows a typical approach in machine learning where both the full physics and proxy models are evaluated for a training set (subset of realizations) and the set of responses is used to construct the error model using functional data analysis. Once the error model is devised, a prediction of the full physics response for a new geostatistical realization can be obtained by computing the proxy response and applying the error model. We propose the use of functional error models in a Bayesian inference context by combining it to the Nested Sampling (Skilling 2006; El Sheikh et al. 2013, 2014). Nested Sampling offers a mean to compute the Bayesian Evidence by transforming the multidimensional integral into a 1D integral. The algorithm is simple: starting with an active set of samples, at each iteration, the sample with the lowest likelihood is kept aside and replaced by a sample of higher likelihood. The main challenge is to find this sample of higher likelihood. We suggest a new approach: first the active set is sampled, both proxy and full physics models are run and the functional error model is build. Then, at each iteration of the Nested
Generalized exponential function and discrete growth models
NASA Astrophysics Data System (ADS)
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
NASA Technical Reports Server (NTRS)
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
NASA Astrophysics Data System (ADS)
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.
Food Protein Functionality--A New Model.
Foegeding, E Allen
2015-12-01
Proteins in foods serve dual roles as nutrients and structural building blocks. The concept of protein functionality has historically been restricted to nonnutritive functions--such as creating emulsions, foams, and gels--but this places sole emphasis on food quality considerations and potentially overlooks modifications that may also alter nutritional quality or allergenicity. A new model is proposed that addresses the function of proteins in foods based on the length scale(s) responsible for the function. Properties such as flavor binding, color, allergenicity, and digestibility are explained based on the structure of individual molecules; placing this functionality at the nano/molecular scale. At the next higher scale, applications in foods involving gelation, emulsification, and foam formation are based on how proteins form secondary structures that are seen at the nano and microlength scales, collectively called the mesoscale. The macroscale structure represents the arrangements of molecules and mesoscale structures in a food. Macroscale properties determine overall product appearance, stability, and texture. The historical approach of comparing among proteins based on forming and stabilizing specific mesoscale structures remains valid but emphasis should be on a common means for structure formation to allow for comparisons across investigations. For applications in food products, protein functionality should start with identification of functional needs across scales. Those needs are then evaluated relative to how processing and other ingredients could alter desired molecular scale properties, or proper formation of mesoscale structures. This allows for a comprehensive approach to achieving the desired function of proteins in foods.
Functional integral approach to the Lipkin model
Kaneko, K.
1988-07-01
A quantum-mechanical formulation involving both collective and independent-particle motions in many-fermion systems is proposed by using the path-integral technique. A semiclassical method of evaluating the functional integral over both fields is described. As an illustration, the Lipkin model is utilized.
Mixture Models for Distance Sampling Detection Functions
Miller, David L.; Thomas, Len
2015-01-01
We present a new class of models for the detection function in distance sampling surveys of wildlife populations, based on finite mixtures of simple parametric key functions such as the half-normal. The models share many of the features of the widely-used “key function plus series adjustment” (K+A) formulation: they are flexible, produce plausible shapes with a small number of parameters, allow incorporation of covariates in addition to distance and can be fitted using maximum likelihood. One important advantage over the K+A approach is that the mixtures are automatically monotonic non-increasing and non-negative, so constrained optimization is not required to ensure distance sampling assumptions are honoured. We compare the mixture formulation to the K+A approach using simulations to evaluate its applicability in a wide set of challenging situations. We also re-analyze four previously problematic real-world case studies. We find mixtures outperform K+A methods in many cases, particularly spiked line transect data (i.e., where detectability drops rapidly at small distances) and larger sample sizes. We recommend that current standard model selection methods for distance sampling detection functions are extended to include mixture models in the candidate set. PMID:25793744
Enzyme function prediction with interpretable models.
Syed, Umar; Yona, Golan
2009-01-01
Enzymes play central roles in metabolic pathways, and the prediction of metabolic pathways in newly sequenced genomes usually starts with the assignment of genes to enzymatic reactions. However, genes with similar catalytic activity are not necessarily similar in sequence, and therefore the traditional sequence similarity-based approach often fails to identify the relevant enzymes, thus hindering efforts to map the metabolome of an organism.Here we study the direct relationship between basic protein properties and their function. Our goal is to develop a new tool for functional prediction (e.g., prediction of Enzyme Commission number), which can be used to complement and support other techniques based on sequence or structure information. In order to define this mapping we collected a set of 453 features and properties that characterize proteins and are believed to be related to structural and functional aspects of proteins. We introduce a mixture model of stochastic decision trees to learn the set of potentially complex relationships between features and function. To study these correlations, trees are created and tested on the Pfam classification of proteins, which is based on sequence, and the EC classification, which is based on enzymatic function. The model is very effective in learning highly diverged protein families or families that are not defined on the basis of sequence. The resulting tree structures highlight the properties that are strongly correlated with structural and functional aspects of protein families, and can be used to suggest a concise definition of a protein family.
A rational model of function learning.
Lucas, Christopher G; Griffiths, Thomas L; Williams, Joseph J; Kalish, Michael L
2015-10-01
Theories of how people learn relationships between continuous variables have tended to focus on two possibilities: one, that people are estimating explicit functions, or two that they are performing associative learning supported by similarity. We provide a rational analysis of function learning, drawing on work on regression in machine learning and statistics. Using the equivalence of Bayesian linear regression and Gaussian processes, which provide a probabilistic basis for similarity-based function learning, we show that learning explicit rules and using similarity can be seen as two views of one solution to this problem. We use this insight to define a rational model of human function learning that combines the strengths of both approaches and accounts for a wide variety of experimental results.
Maximum entropy models of ecosystem functioning
NASA Astrophysics Data System (ADS)
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.
Maximum entropy models of ecosystem functioning
Bertram, Jason
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.
Modelling the ecological niche from functional traits
Kearney, Michael; Simpson, Stephen J.; Raubenheimer, David; Helmuth, Brian
2010-01-01
The niche concept is central to ecology but is often depicted descriptively through observing associations between organisms and habitats. Here, we argue for the importance of mechanistically modelling niches based on functional traits of organisms and explore the possibilities for achieving this through the integration of three theoretical frameworks: biophysical ecology (BE), the geometric framework for nutrition (GF) and dynamic energy budget (DEB) models. These three frameworks are fundamentally based on the conservation laws of thermodynamics, describing energy and mass balance at the level of the individual and capturing the prodigious predictive power of the concepts of ‘homeostasis’ and ‘evolutionary fitness’. BE and the GF provide mechanistic multi-dimensional depictions of climatic and nutritional niches, respectively, providing a foundation for linking organismal traits (morphology, physiology, behaviour) with habitat characteristics. In turn, they provide driving inputs and cost functions for mass/energy allocation within the individual as determined by DEB models. We show how integration of the three frameworks permits calculation of activity constraints, vital rates (survival, development, growth, reproduction) and ultimately population growth rates and species distributions. When integrated with contemporary niche theory, functional trait niche models hold great promise for tackling major questions in ecology and evolutionary biology. PMID:20921046
A Generic Modeling Process to Support Functional Fault Model Development
NASA Technical Reports Server (NTRS)
Maul, William A.; Hemminger, Joseph A.; Oostdyk, Rebecca; Bis, Rachael A.
2016-01-01
Functional fault models (FFMs) are qualitative representations of a system's failure space that are used to provide a diagnostic of the modeled system. An FFM simulates the failure effect propagation paths within a system between failure modes and observation points. These models contain a significant amount of information about the system including the design, operation and off nominal behavior. The development and verification of the models can be costly in both time and resources. In addition, models depicting similar components can be distinct, both in appearance and function, when created individually, because there are numerous ways of representing the failure space within each component. Generic application of FFMs has the advantages of software code reuse: reduction of time and resources in both development and verification, and a standard set of component models from which future system models can be generated with common appearance and diagnostic performance. This paper outlines the motivation to develop a generic modeling process for FFMs at the component level and the effort to implement that process through modeling conventions and a software tool. The implementation of this generic modeling process within a fault isolation demonstration for NASA's Advanced Ground System Maintenance (AGSM) Integrated Health Management (IHM) project is presented and the impact discussed.
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.
A Green's function quantum average atom model
Starrett, Charles Edward
2015-05-21
A quantum average atom model is reformulated using Green's functions. This allows integrals along the real energy axis to be deformed into the complex plane. The advantage being that sharp features such as resonances and bound states are broadened by a Lorentzian with a half-width chosen for numerical convenience. An implementation of this method therefore avoids numerically challenging resonance tracking and the search for weakly bound states, without changing the physical content or results of the model. A straightforward implementation results in up to a factor of 5 speed-up relative to an optimized orbital based code.
Mathematical Models of Cardiac Pacemaking Function
NASA Astrophysics Data System (ADS)
Li, Pan; Lines, Glenn T.; Maleckar, Mary M.; Tveito, Aslak
2013-10-01
Over the past half century, there has been intense and fruitful interaction between experimental and computational investigations of cardiac function. This interaction has, for example, led to deep understanding of cardiac excitation-contraction coupling; how it works, as well as how it fails. However, many lines of inquiry remain unresolved, among them the initiation of each heartbeat. The sinoatrial node, a cluster of specialized pacemaking cells in the right atrium of the heart, spontaneously generates an electro-chemical wave that spreads through the atria and through the cardiac conduction system to the ventricles, initiating the contraction of cardiac muscle essential for pumping blood to the body. Despite the fundamental importance of this primary pacemaker, this process is still not fully understood, and ionic mechanisms underlying cardiac pacemaking function are currently under heated debate. Several mathematical models of sinoatrial node cell membrane electrophysiology have been constructed as based on different experimental data sets and hypotheses. As could be expected, these differing models offer diverse predictions about cardiac pacemaking activities. This paper aims to present the current state of debate over the origins of the pacemaking function of the sinoatrial node. Here, we will specifically review the state-of-the-art of cardiac pacemaker modeling, with a special emphasis on current discrepancies, limitations, and future challenges.
A general phenomenological model for work function
NASA Astrophysics Data System (ADS)
Brodie, I.; Chou, S. H.; Yuan, H.
2014-07-01
A general phenomenological model is presented for obtaining the zero Kelvin work function of any crystal facet of metals and semiconductors, both clean and covered with a monolayer of electropositive atoms. It utilizes the known physical structure of the crystal and the Fermi energy of the two-dimensional electron gas assumed to form on the surface. A key parameter is the number of electrons donated to the surface electron gas per surface lattice site or adsorbed atom, which is taken to be an integer. Initially this is found by trial and later justified by examining the state of the valence electrons of the relevant atoms. In the case of adsorbed monolayers of electropositive atoms a satisfactory justification could not always be found, particularly for cesium, but a trial value always predicted work functions close to the experimental values. The model can also predict the variation of work function with temperature for clean crystal facets. The model is applied to various crystal faces of tungsten, aluminium, silver, and select metal oxides, and most demonstrate good fits compared to available experimental values.
The Pleiades mass function: Models versus observations
NASA Astrophysics Data System (ADS)
Moraux, E.; Kroupa, P.; Bouvier, J.
2004-10-01
Two stellar-dynamical models of binary-rich embedded proto-Orion-Nebula-type clusters that evolve to Pleiades-like clusters are studied with an emphasis on comparing the stellar mass function with observational constraints. By the age of the Pleiades (about 100 Myr) both models show a similar degree of mass segregation which also agrees with observational constraints. This thus indicates that the Pleiades is well relaxed and that it is suffering from severe amnesia. It is found that the initial mass function (IMF) must have been indistinguishable from the standard or Galactic-field IMF for stars with mass m ≲ 2 M⊙, provided the Pleiades precursor had a central density of about 104.8 stars/pc3. A denser model with 105.8 stars/pc3 also leads to reasonable agreement with observational constraints, but owing to the shorter relaxation time of the embedded cluster it evolves through energy equipartition to a mass-segregated condition just prior to residual-gas expulsion. This model consequently preferentially loses low-mass stars and brown dwarfs (BDs), but the effect is not very pronounced. The empirical data indicate that the Pleiades IMF may have been steeper than the Salpeter for stars with m⪆ 2 M⊙.
Transfer function modeling of damping mechanisms in distributed parameter models
NASA Technical Reports Server (NTRS)
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
NASA Astrophysics Data System (ADS)
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.
Inverse Modeling Via Linearized Functional Minimization
NASA Astrophysics Data System (ADS)
Barajas-Solano, D. A.; Wohlberg, B.; Vesselinov, V. V.; Tartakovsky, D. M.
2014-12-01
We present a novel parameter estimation methodology for transient models of geophysical systems with uncertain, spatially distributed, heterogeneous and piece-wise continuous parameters.The methodology employs a bayesian approach to propose an inverse modeling problem for the spatial configuration of the model parameters.The likelihood of the configuration is formulated using sparse measurements of both model parameters and transient states.We propose using total variation regularization (TV) as the prior reflecting the heterogeneous, piece-wise continuity assumption on the parameter distribution.The maximum a posteriori (MAP) estimator of the parameter configuration is then computed by minimizing the negative bayesian log-posterior using a linearized functional minimization approach. The computation of the MAP estimator is a large-dimensional nonlinear minimization problem with two sources of nonlinearity: (1) the TV operator, and (2) the nonlinear relation between states and parameters provided by the model's governing equations.We propose a a hybrid linearized functional minimization (LFM) algorithm in two stages to efficiently treat both sources of nonlinearity.The relation between states and parameters is linearized, resulting in a linear minimization sub-problem equipped with the TV operator; this sub-problem is then minimized using the Alternating Direction Method of Multipliers (ADMM). The methodology is illustrated with a transient saturated groundwater flow application in a synthetic domain, stimulated by external point-wise loadings representing aquifer pumping, together with an array of discrete measurements of hydraulic conductivity and transient measurements of hydraulic head.We show that our inversion strategy is able to recover the overall large-scale features of the parameter configuration, and that the reconstruction is improved by the addition of transient information of the state variable.
Caustics in asymptotic Green Function transmission models
NASA Astrophysics Data System (ADS)
Roberts, R. A.
2000-05-01
Green Function-based beam transmission models are attractive due to their ability to explicitly handle transmission through complicated geometrical surfaces, such as flat-to-circular arc compound profiles. The beam model considered in this paper integrates the field generated by a point source positioned within a solid body over a radiating aperture surface (transducer face) in a fluid medium exterior to the solid body. In full generality, evaluation of the Green function at a point on the aperture surface requires an integration over the component surface (solid-water interface). For geometries of practical interest, this integration can be effectively evaluated by applying high-frequency asymptotic techniques (stationary phase analysis=ray theory). However, first-order asymptotic methods fail at focusing caustics, that is, when the component surface curvature focuses the field generated by the interior point source onto the aperture surface. Uniform asymptotic methods are available to treat such problems. However, implementation of uniform expansion methods in an algorithm applicable to arbitrarily curved component surfaces entails a complexity that outweighs algorithm utility. Past algorithms have therefore evaluated the Green function in these anomalous cases by performing an explicit numerical integration over the component surface. Work reported here hypothesizes that the singularity in the Green function amplitude from first-order analysis is an integrable singularity, and hence can be handled in the aperture surface integration through appropriate integration variable transformation. It is shown that an effective transformation of variables is provided by the ray coordinates which map the interior source location to points on the component surface, then onto points on the aperture surface. It is seen that zeros in the Jacobian of the surface aperture coordinate-to-ray coordinate mapping mollify the singularities in the first-order analysis Green function
Linear functional minimization for inverse modeling
Barajas-Solano, David A.; Wohlberg, Brendt Egon; Vesselinov, Velimir Valentinov; Tartakovsky, Daniel M.
2015-06-01
In this paper, we present a novel inverse modeling strategy to estimate spatially distributed parameters of nonlinear models. The maximum a posteriori (MAP) estimators of these parameters are based on a likelihood functional, which contains spatially discrete measurements of the system parameters and spatiotemporally discrete measurements of the transient system states. The piecewise continuity prior for the parameters is expressed via Total Variation (TV) regularization. The MAP estimator is computed by minimizing a nonquadratic objective equipped with the TV operator. We apply this inversion algorithm to estimate hydraulic conductivity of a synthetic confined aquifer from measurements of conductivity and hydraulic head. The synthetic conductivity field is composed of a low-conductivity heterogeneous intrusion into a high-conductivity heterogeneous medium. Our algorithm accurately reconstructs the location, orientation, and extent of the intrusion from the steady-state data only. Finally, addition of transient measurements of hydraulic head improves the parameter estimation, accurately reconstructing the conductivity field in the vicinity of observation locations.
Mouse models of p53 functions.
Lozano, Guillermina
2010-04-01
Studies in mice have yielded invaluable insight into our understanding of the p53 pathway. Mouse models with activated p53, no p53, and mutant p53 have queried the role of p53 in development and tumorigenesis. In these models, p53 is activated and stabilized via redundant posttranslational modifications. On activation, p53 initiates two major responses: inhibition of proliferation (via cell-cycle arrest, quiescence, senescence, and differentiation) and induction of apoptosis. Importantly, these responses are cell-type and tumor-type-specific. The analysis of mutant p53 alleles has established a gain-of-function role for p53 mutants in metastasis. The development of additional models that can precisely time the oncogenic events in single cells will provide further insight into the evolution of tumors, the importance of the stroma, and the cooperating events that lead to disruption of the p53 pathway. Ultimately, these models should serve to study the effects of novel drugs on tumor response as well as normal homeostasis.
Modeling the three-point correlation function
Marin, Felipe; Wechsler, Risa; Frieman, Joshua A.; Nichol, Robert; /Portsmouth U., ICG
2007-04-01
We present new theoretical predictions for the galaxy three-point correlation function (3PCF) using high-resolution dissipationless cosmological simulations of a flat {Lambda}CDM Universe which resolve galaxy-size halos and subhalos. We create realistic mock galaxy catalogs by assigning luminosities and colors to dark matter halos and subhalos, and we measure the reduced 3PCF as a function of luminosity and color in both real and redshift space. As galaxy luminosity and color are varied, we find small differences in the amplitude and shape dependence of the reduced 3PCF, at a level qualitatively consistent with recent measurements from the SDSS and 2dFGRS. We confirm that discrepancies between previous 3PCF measurements can be explained in part by differences in binning choices. We explore the degree to which a simple local bias model can fit the simulated 3PCF. The agreement between the model predictions and galaxy 3PCF measurements lends further credence to the straightforward association of galaxies with CDM halos and subhalos.
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.
Linearized Functional Minimization for Inverse Modeling
Wohlberg, Brendt; Tartakovsky, Daniel M.; Dentz, Marco
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.
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
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
Models of Protocellular Structure, Function and Evolution
NASA Technical Reports Server (NTRS)
New, Michael H.; Pohorille, Andrew; Szostak, Jack W.; Keefe, Tony; Lanyi, Janos K.; DeVincenzi, Donald L. (Technical Monitor)
2001-01-01
In the absence of any 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 in which a small number of functional molecules are selected from a large, random population of candidates. The selected molecules are next vastly multiplied using the polymerase chain reaction.
Models of protocellular structures, functions and evolution
NASA Technical Reports Server (NTRS)
Pohorille, Andrew; New, Michael H.; DeVincenzi, Donald L. (Technical Monitor)
2000-01-01
The central step in the origin of life was the emergence of organized structures from organic molecules available on the early earth. These predecessors to modern cells, called 'proto-cells,' were simple, membrane bounded structures able to maintain themselves, grow, divide, and evolve. Since there is no fossil record of these earliest of life forms, it is a scientific challenge to discover plausible mechanisms for how these entities formed and functioned. To meet this challenge, it is essential to create laboratory models of protocells that capture the main attributes associated with living systems, while remaining consistent with known, or inferred, protobiological conditions. This report provides an overview of a project which has focused on protocellular metabolism and the coupling of metabolism to energy transduction. We have assumed that the emergence of systems endowed with genomes and capable of Darwinian evolution was preceded by a pre-genomic phase, in which protocells functioned and evolved using mostly proteins, without self-replicating nucleic acids such as RNA.
Swell-Dissipation Function for Wave Models
NASA Astrophysics Data System (ADS)
Babanin, A.
2012-04-01
In the paper, we will investigate swell attenuation due to production of turbulence by the wave orbital motion. Theoreticaly, potential waves cannot generate the vortex motion, but the scale considerations indicate that if the steepness of waves is not too small, the Reynolds number can exceed the critical values. This means that in presence of initial non-potential disturbances the orbital velocities can generate the vortex motion and turbulence. This problem was investigated by laboratory means, numerical simulations and field observations. As a sink of wave energy, such dissipation is small in presence of wave breaking, but is essential for swell. Swell prediction by spectral wave models is often poor, but is important for offshore and maritime industry, and across a broad range of oceanographic and air-sea interaction applications. Based on the research of wave-induced turbulence, new swell-dissipation function is proposed. It agrees well with satellite observations of long-distance swell propagation and has been employed and tested in spectral wave models.
Linear functional minimization for inverse modeling
Barajas-Solano, David A.; Wohlberg, Brendt Egon; Vesselinov, Velimir Valentinov; Tartakovsky, Daniel M.
2015-06-01
In this paper, we present a novel inverse modeling strategy to estimate spatially distributed parameters of nonlinear models. The maximum a posteriori (MAP) estimators of these parameters are based on a likelihood functional, which contains spatially discrete measurements of the system parameters and spatiotemporally discrete measurements of the transient system states. The piecewise continuity prior for the parameters is expressed via Total Variation (TV) regularization. The MAP estimator is computed by minimizing a nonquadratic objective equipped with the TV operator. We apply this inversion algorithm to estimate hydraulic conductivity of a synthetic confined aquifer from measurements of conductivity and hydraulicmore » head. The synthetic conductivity field is composed of a low-conductivity heterogeneous intrusion into a high-conductivity heterogeneous medium. Our algorithm accurately reconstructs the location, orientation, and extent of the intrusion from the steady-state data only. Finally, addition of transient measurements of hydraulic head improves the parameter estimation, accurately reconstructing the conductivity field in the vicinity of observation locations.« less
Model for ocular tear film function.
Mathers, W D; Lane, J A; Sutphin, J E; Zimmerman, M B
1996-03-01
Blepharitis patients have a number of disturbances in their tear film associated with meibomian gland dysfunction that affect evaporation and tear osmolarity. We tested a series of 156 consecutive patients, with a presumed diagnosis of blepharitis, dry eye, or allergic disease, and a series of 72 normals. We compared their tear film characteristics using tear osmolarity, tear volume, tear production (fluorophotometric and Schirmer test), tear turnover (decay constant), tear evaporation, and meibomian gland function evaluated by gland drop-out, expressed lipid viscosity, and volume. Of the 156 patients tested, we found 37 had dry eye, 10 had only allergic disease, 73 had meibomian gland dysfunction and dry eye, and 36 had only meibomian gland dysfunction. We created a model of the relative influence some of these factors had on each other using their correlation coefficients. The highest correlations for osmolarity were Schirmer test (-0.44), lipid volume low (-0.44), lipid viscosity high (0.39), gland drop-out (0.39), and tear evaporation (0.36). With regression analysis we accounted for 47% of the total variation in osmolarity, but only 17% of the variation in tear evaporation. We also present our classification system for blepharitis and dry eye patients based on our measurable physiologic parameters.
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.
Density functional calculations on model tyrosyl radicals.
Himo, F; Gräslund, A; Eriksson, L A
1997-01-01
A gradient-corrected density functional theory approach (PWP86) has been applied, together with large basis sets (IGLO-III), to investigate the structure and hyperfine properties of model tyrosyl free radicals. In nature, these radicals are observed in, e.g., the charge transfer pathways in photosystem II (PSII) and in ribonucleotide reductases (RNRs). By comparing spin density distributions and proton hyperfine couplings with experimental data, it is confirmed that the tyrosyl radicals present in the proteins are neutral. It is shown that hydrogen bonding to the phenoxyl oxygen atom, when present, causes a reduction in spin density on O and a corresponding increase on C4. Calculated proton hyperfine coupling constants for the beta-protons show that the alpha-carbon is rotated 75-80 degrees out of the plane of the ring in PSII and Salmonella typhimurium RNR, but only 20-30 degrees in, e.g., Escherichia coli, mouse, herpes simplex, and bacteriophage T4-induced RNRs. Furthermore, based on the present calculations, we have revised the empirical parameters used in the experimental determination of the oxygen spin density in the tyrosyl radical in E. coli RNR and of the ring carbon spin densities, from measured hyperfine coupling constants. Images FIGURE 1 FIGURE 5 PMID:9083661
Modeling Bamboo as a Functionally Graded Material
NASA Astrophysics Data System (ADS)
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.
Modeling Bamboo as a Functionally Graded Material
Silva, Emilio Carlos Nelli; Walters, Matthew C.; Paulino, Glaucio H.
2008-02-15
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.
Models of Protocellular Structure, Function and Evolution
NASA Technical Reports Server (NTRS)
New, Michael H.; Pohorille, Andrew; Szostak, Jack W.; Keefe, Tony; Lanyi, Janos K.
2001-01-01
In the absence of any 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 in which a small number of functional molecules are selected from a large, random population of candidates. The selected 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. Additional information is contained in the original extended abstract.
School Teams up for SSP Functional Models
NASA Astrophysics Data System (ADS)
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
Variance Function Partially Linear Single-Index Models1
LIAN, HENG; LIANG, HUA; CARROLL, RAYMOND J.
2014-01-01
We consider heteroscedastic regression models where the mean function is a partially linear single index model and the variance function depends upon a generalized partially linear single index model. We do not insist that the variance function depend only upon the mean function, as happens in the classical generalized partially linear single index model. We develop efficient and practical estimation methods for the variance function and for the mean function. Asymptotic theory for the parametric and nonparametric parts of the model is developed. Simulations illustrate the results. An empirical example involving ozone levels is used to further illustrate the results, and is shown to be a case where the variance function does not depend upon the mean function. PMID:25642139
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
Parametric models for samples of random functions
Grigoriu, M.
2015-09-15
A new class of parametric models, referred to as sample parametric models, is developed for random elements that match sample rather than the first two moments and/or other global properties of these elements. The models can be used to characterize, e.g., material properties at small scale in which case their samples represent microstructures of material specimens selected at random from a population. The samples of the proposed models are elements of finite-dimensional vector spaces spanned by samples, eigenfunctions of Karhunen–Loève (KL) representations, or modes of singular value decompositions (SVDs). The implementation of sample parametric models requires knowledge of the probability laws of target random elements. Numerical examples including stochastic processes and random fields are used to demonstrate the construction of sample parametric models, assess their accuracy, and illustrate how these models can be used to solve efficiently stochastic equations.
A Functional Test Platform for the Community Land Model
Xu, Yang; Thornton, Peter E; King, Anthony Wayne; Steed, Chad A; Gu, Lianhong; Schuchart, Joseph
2014-01-01
A functional test platform is presented to create direct linkages between site measurements and the process-based ecosystem model within the Community Earth System Models (CESM). The platform consists of three major parts: 1) interactive user interfaces, 2) functional test model and 3) observational datasets. It provides much needed integration interfaces for both field experimentalists and ecosystem modelers to improve the model s representation of ecosystem processes within the CESM framework without large software overhead.
Fourier functional analysis for unsteady aerodynamic modeling
NASA Technical Reports Server (NTRS)
Lan, C. Edward; Chin, Suei
1991-01-01
A method based on Fourier analysis is developed to analyze the force and moment data obtained in large amplitude forced oscillation tests at high angles of attack. The aerodynamic models for normal force, lift, drag, and pitching moment coefficients are built up from a set of aerodynamic responses to harmonic motions at different frequencies. Based on the aerodynamic models of harmonic data, the indicial responses are formed. The final expressions for the models involve time integrals of the indicial type advocated by Tobak and Schiff. Results from linear two- and three-dimensional unsteady aerodynamic theories as well as test data for a 70-degree delta wing are used to verify the models. It is shown that the present modeling method is accurate in producing the aerodynamic responses to harmonic motions and the ramp type motions. The model also produces correct trend for a 70-degree delta wing in harmonic motion with different mean angles-of-attack. However, the current model cannot be used to extrapolate data to higher angles-of-attack than that of the harmonic motions which form the aerodynamic model. For linear ramp motions, a special method is used to calculate the corresponding frequency and phase angle at a given time. The calculated results from modeling show a higher lift peak for linear ramp motion than for harmonic ramp motion. The current model also shows reasonably good results for the lift responses at different angles of attack.
On extended thermonuclear functions through pathway model
NASA Astrophysics Data System (ADS)
Kumar, Dilip
when α → 1. The beauty of the result is that these different families of three different functional forms are covered through the pathway parameter α. In a physical set up if f (x) in (3) is the stable or limiting form, the Maxwell-Boltzmann approach to thermonuclear functions, then f (x) in (1) and (2) will contain a large variety of unstable or chaotic situations which will all tend to (3) in the limit. Thus we get a clear idea of all the stable and unstable situations around the Maxwell-Boltzmann approach. Thus the current theory is given a mathematical extension and physical interpretations can be found to situations in (1) and (2). Incidently Tsallis statistics is a special case of (1) for γ = 0, a = 1, δ = 1, η = 1. The Beck-Cohen superstatistics, discussed in current statistical mechanics literature is a special case of (2) for a = 1, η = 1, α > 1. The main purpose of the present paper is to investigate in some more detail, mathematically, the extended thermonuclear functions for Maxwell-Boltzmann statistics and in the cut-off case. The extended thermonuclear functions will be evaluated in closed form for all convenient values of the parameter by means of residue calculus. A comparison of the standard thermonuclear functions with the extended thermonuclear functions is also done. The results and derivations in this paper are new and these will be of interest to physicists, mathematicians, probabilists, and statisticians.
Modelling protein functional domains in signal transduction using Maude
NASA Technical Reports Server (NTRS)
Sriram, M. G.
2003-01-01
Modelling of protein-protein interactions in signal transduction is receiving increased attention in computational biology. This paper describes recent research in the application of Maude, a symbolic language founded on rewriting logic, to the modelling of functional domains within signalling proteins. Protein functional domains (PFDs) are a critical focus of modern signal transduction research. In general, Maude models can simulate biological signalling networks and produce specific testable hypotheses at various levels of abstraction. Developing symbolic models of signalling proteins containing functional domains is important because of the potential to generate analyses of complex signalling networks based on structure-function relationships.
Latent Growth Modeling for Logistic Response Functions
ERIC Educational Resources Information Center
Choi, Jaehwa; Harring, Jeffrey R.; Hancock, Gregory R.
2009-01-01
Throughout much of the social and behavioral sciences, latent growth modeling (latent curve analysis) has become an important tool for understanding individuals' longitudinal change. Although nonlinear variations of latent growth models appear in the methodological and applied literature, a notable exclusion is the treatment of growth following…
Dispersion analysis with inverse dielectric function modelling.
Mayerhöfer, Thomas G; Ivanovski, Vladimir; Popp, Jürgen
2016-11-01
We investigate how dispersion analysis can profit from the use of a Lorentz-type description of the inverse dielectric function. In particular at higher angles of incidence, reflectance spectra using p-polarized light are dominated by bands from modes that have their transition moments perpendicular to the surface. Accordingly, the spectra increasingly resemble inverse dielectric functions. A corresponding description can therefore eliminate the complex dependencies of the dispersion parameters, allow their determination and facilitate a more accurate description of the optical properties of single crystals.
Dispersion analysis with inverse dielectric function modelling
NASA Astrophysics Data System (ADS)
Mayerhöfer, Thomas G.; Ivanovski, Vladimir; Popp, Jürgen
2016-11-01
We investigate how dispersion analysis can profit from the use of a Lorentz-type description of the inverse dielectric function. In particular at higher angles of incidence, reflectance spectra using p-polarized light are dominated by bands from modes that have their transition moments perpendicular to the surface. Accordingly, the spectra increasingly resemble inverse dielectric functions. A corresponding description can therefore eliminate the complex dependencies of the dispersion parameters, allow their determination and facilitate a more accurate description of the optical properties of single crystals.
Hydroacoustic forcing function modeling using DNS database
NASA Technical Reports Server (NTRS)
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.
The β-FUNCTION in Topological Sigma Models
NASA Astrophysics Data System (ADS)
Birmingham, Danny; Rakowski, Mark
The one-loop β-function is computed for topological sigma models. By gauge fixing the topological shift symmetry in the delta-function gauge, we find that the theory is finite with vanishing β-function. A similar result is shown to hold for supersymmetric quantum mechanics.
Correlation function of four spins in the percolation model
NASA Astrophysics Data System (ADS)
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.
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.
Multiscale Modeling of Form and Function
Engler, Adam J.; Humbert, Patrick O.; Wehrle-Haller, Bernhard; Weaver, Valerie M.
2015-01-01
Topobiology posits that morphogenesis is driven by differential adhesive interactions among heterogeneous cell populations. This paradigm has been revised to include force-dependent molecular switches, cell and tissue tension, and reciprocal interactions with the microenvironment. It is now appreciated that tissue development is executed through conserved decision-making modules that operate on multiple length scales from the molecular and subcellular level through to the cell and tissue level and that these regulatory mechanisms specify cell and tissue fate by modifying the context of cellular signaling and gene expression. Here, we discuss the origin of these decision-making modules and illustrate how emergent properties of adhesion-directed multicellular structures sculpt the tissue, promote its functionality, and maintain its homeostasis through spatial segregation and organization of anchored proteins and secreted factors and through emergent properties of tissues, including tension fields and energy optimization. PMID:19359578
Concerted reactions of polynuclear metalloenzymes and their functional chemical models
NASA Astrophysics Data System (ADS)
Dzhabiev, T. S.; Shilov, A. E.
2011-03-01
The mechanisms of the many-electron oxidation of water by a chemical model of the manganese oxidase cofactor in photosynthesis photosystem II (manganese(IV) clusters) and nitrogen reduction in chemical models of nitrogenase cofactor (vanadium(II) and molybdenum(III) clusters) were considered. The hypothesis was suggested according to which polynuclear enzyme cofactors and their functional chemical models performed two important functions, catalyzed noncomplementary processes and effected many-substrate concerted reactions with decreased activation energies.
Nanoscale device modeling: the Green's function method
NASA Astrophysics Data System (ADS)
Datta, Supriyo
2000-10-01
The non-equilibrium Green's function (NEGF) formalism provides a sound conceptual basis for the devlopment of atomic-level quantum mechanical simulators that will be needed for nanoscale devices of the future. However, this formalism is based on concepts that are unfamiliar to most device physicists and chemists and as such remains relatively obscure. In this paper we try to achieve two objectives: (1) explain the central concepts that define the 'language' of quantum transport, and (2) illustrate the NEGF formalism with simple examples that interested readers can easily duplicate on their PCs. These examples all involve a short n+ +- n+- n+ +resistor whose physics is easily understood. However, the basic formulation is quite general and can even be applied to something as different as a nanotube or a molecular wire, once a suitable Hamiltonian has been identified. These examples also underscore the importance of performing self-consistent calculations that include the Poisson equation. The I-V characteristics of nanoscale structures is determined by an interesting interplay between twentieth century physics (quantum transport) and nineteenth century physics (electrostatics) and there is a tendency to emphasize one or the other depending on one's background. However, it is important to do justice to both aspects in order to derive real insights.
Thermoplasmonics modeling: A Green's function approach
NASA Astrophysics Data System (ADS)
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.
Tactile Teaching: Exploring Protein Structure/Function Using Physical Models
ERIC Educational Resources Information Center
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…
Modeling Dynamic Functional Neuroimaging Data Using Structural Equation Modeling
ERIC Educational Resources Information Center
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…
ERIC Educational Resources Information Center
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…
Modelling thymic functions in a cellular automaton.
Morpurgo, D; Serenthà, R; Seiden, P E; Celada, F
1995-04-01
Along the lines developed by Celada and Seiden, for simulating an immune system by means of cellular automata, we have constructed a 'thymus' where T cells undergo positive and negative selection. The populations thus 'matured' have been analyzed and their performance has been tested in machina. The key feature of this thymus is to allow chance meeting and possible interaction between newly born T cells and antigen presenting cells. The latter represent both the epithelial and the dendritic cells of the biological organ and are equipped with MHC molecules that can accommodate selected self peptides. All possible specificities are represented among the virgin T cells entering the thymus, but this diversity is drastically reduced by the time they exit as mature elements. In the model organ the fate of T cells, i.e. whether they will undergo proliferation or apoptosis, is governed by their capacity to recognize MHCs and the affinity of this interaction. Crucial parameters turn out to be the concentration of presenting cells, the number of types of MHC per cell, the 'size of self' in terms of the number of different peptides and their prevalence. According to the results, events in the automaton can realize unforeseen cooperations and competitions among receptors, depending upon the interaction order and frequency, and ultimately determine the rescue or the killing of thymocytes. Thus the making of the mature T repertoire has a random component and cannot be completely predicted.
Four-point function in the IOP matrix model
NASA Astrophysics Data System (ADS)
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.
Gluon fragmentation functions in the Nambu-Jona-Lasinio model
NASA Astrophysics Data System (ADS)
Yang, Dong-Jing; Li, Hsiang-nan
2016-09-01
We derive gluon fragmentation functions in the Nambu-Jona-Lasinio (NJL) model by treating a gluon as a pair of color lines formed by a fictitious quark and antiquark (q q ¯). Gluon elementary fragmentation functions are obtained from the quark and antiquark elementary fragmentation functions for emitting specific mesons in the NJL model under the requirement that the q 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- annihilation. Our proposal provides a plausible construct for the gluon fragmentation functions, which are supposed to be null in the NJL model.
Learning local objective functions for robust face model fitting.
Wimmer, Matthias; Stulp, Freek; Pietzsch, Sylvia; Radig, Bernd
2008-08-01
Model-based techniques have proven to be successful in interpreting the large amount of information contained in images. Associated fitting algorithms search for the global optimum of an objective function, which should correspond to the best model fit in a given image. Although fitting algorithms have been the subject of intensive research and evaluation, the objective function is usually designed ad hoc, based on implicit and domain-dependent knowledge. In this article, we address the root of the problem by learning more robust objective functions. First, we formulate a set of desirable properties for objective functions and give a concrete example function that has these properties. Then, we propose a novel approach that learns an objective function from training data generated by manual image annotations and this ideal objective function. In this approach, critical decisions such as feature selection are automated, and the remaining manual steps hardly require domain-dependent knowledge. Furthermore, an extensive empirical evaluation demonstrates that the obtained objective functions yield more robustness. Learned objective functions enable fitting algorithms to determine the best model fit more accurately than with designed objective functions. PMID:18566491
Probability density function modeling for sub-powered interconnects
NASA Astrophysics Data System (ADS)
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.
The Interaction of Courseware Development and Implementation: Functions and Models
ERIC Educational Resources Information Center
Mahler, William A.
1976-01-01
A discussion of how the interaction of design and content of curricular materials determine their possible applications. A review of functions and models is presented for interactive curriculum development for computer based instructional systems. (HB)
Accuracy of functional surfaces on comparatively modeled protein structures
Zhao, Jieling; Dundas, Joe; Kachalo, Sema; Ouyang, Zheng; Liang, Jie
2012-01-01
Identification and characterization of protein functional surfaces are important for predicting protein function, understanding enzyme mechanism, and docking small compounds to proteins. As the rapid speed of accumulation of protein sequence information far exceeds that of structures, constructing accurate models of protein functional surfaces and identify their key elements become increasingly important. A promising approach is to build comparative models from sequences using known structural templates such as those obtained from structural genome projects. Here we assess how well this approach works in modeling binding surfaces. By systematically building three-dimensional comparative models of proteins using Modeller, we determine how well functional surfaces can be accurately reproduced. We use an alpha shape based pocket algorithm to compute all pockets on the modeled structures, and conduct a large-scale computation of similarity measurements (pocket RMSD and fraction of functional atoms captured) for 26,590 modeled enzyme protein structures. Overall, we find that when the sequence fragment of the binding surfaces has more than 45% identity to that of the tempalte protein, the modeled surfaces have on average an RMSD of 0.5 Å, and contain 48% or more of the binding surface atoms, with nearly all of the important atoms in the signatures of binding pockets captured. PMID:21541664
Enhancements to the SSME transfer function modeling code
NASA Technical Reports Server (NTRS)
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
Functional Linear Models for Association Analysis of Quantitative Traits
Fan, Ruzong; Wang, Yifan; Mills, James L.; Wilson, Alexander F.; Bailey-Wilson, Joan E.; Xiong, Momiao
2014-01-01
Functional linear models are developed in this paper for testing associations between quantitative traits and genetic variants, which can be rare variants or common variants or the combination of the two. By treating multiple genetic variants of an individual in a human population as a realization of a stochastic process, the genome of an individual in a chromosome region is a continuum of sequence data rather than discrete observations. The genome of an individual is viewed as a stochastic function that contains both linkage and linkage disequilibrium (LD) information of the genetic markers. By using techniques of functional data analysis, both fixed and mixed effect functional linear models are built to test the association between quantitative traits and genetic variants adjusting for covariates. After extensive simulation analysis, it is shown that the F-distributed tests of the proposed fixed effect functional linear models have higher power than that of sequence kernel association test (SKAT) and its optimal unified test (SKAT-O) for three scenarios in most cases: (1) the causal variants are all rare, (2) the causal variants are both rare and common, and (3) the causal variants are common. The superior performance of the fixed effect functional linear models is most likely due to its optimal utilization of both genetic linkage and LD information of multiple genetic variants in a genome and similarity among different individuals, while SKAT and SKAT-O only model the similarities and pairwise LD but do not model linkage and higher order LD information sufficiently. In addition, the proposed fixed effect models generate accurate type I error rates in simulation studies. We also show that the functional kernel score tests of the proposed mixed effect functional linear models are preferable in candidate gene analysis and small sample problems. The methods are applied to analyze three biochemical traits in data from the Trinity Students Study. PMID:24130119
Conventional modeling of the multilayer perceptron using polynomial basis functions.
Chen, M S; Manry, M 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.
Conventional modeling of the multilayer perceptron using polynomial basis functions
NASA Technical Reports Server (NTRS)
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.
Functional linear models for association analysis of quantitative traits.
Fan, Ruzong; Wang, Yifan; Mills, James L; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao
2013-11-01
Functional linear models are developed in this paper for testing associations between quantitative traits and genetic variants, which can be rare variants or common variants or the combination of the two. By treating multiple genetic variants of an individual in a human population as a realization of a stochastic process, the genome of an individual in a chromosome region is a continuum of sequence data rather than discrete observations. The genome of an individual is viewed as a stochastic function that contains both linkage and linkage disequilibrium (LD) information of the genetic markers. By using techniques of functional data analysis, both fixed and mixed effect functional linear models are built to test the association between quantitative traits and genetic variants adjusting for covariates. After extensive simulation analysis, it is shown that the F-distributed tests of the proposed fixed effect functional linear models have higher power than that of sequence kernel association test (SKAT) and its optimal unified test (SKAT-O) for three scenarios in most cases: (1) the causal variants are all rare, (2) the causal variants are both rare and common, and (3) the causal variants are common. The superior performance of the fixed effect functional linear models is most likely due to its optimal utilization of both genetic linkage and LD information of multiple genetic variants in a genome and similarity among different individuals, while SKAT and SKAT-O only model the similarities and pairwise LD but do not model linkage and higher order LD information sufficiently. In addition, the proposed fixed effect models generate accurate type I error rates in simulation studies. We also show that the functional kernel score tests of the proposed mixed effect functional linear models are preferable in candidate gene analysis and small sample problems. The methods are applied to analyze three biochemical traits in data from the Trinity Students Study.
A no extensive statistical model for the nucleon structure function
Trevisan, Luis A.; Mirez, Carlos
2013-03-25
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.
ILNCSIM: improved lncRNA functional similarity calculation model
You, Zhu-Hong; Huang, De-Shuang; Chan, Keith C.C.
2016-01-01
Increasing observations have indicated that lncRNAs play a significant role in various critical biological processes and the development and progression of various human diseases. Constructing lncRNA functional similarity networks could benefit the development of computational models for inferring lncRNA functions and identifying lncRNA-disease associations. However, little effort has been devoted to quantifying lncRNA functional similarity. In this study, we developed an Improved LNCRNA functional SIMilarity calculation model (ILNCSIM) based on the assumption that lncRNAs with similar biological functions tend to be involved in similar diseases. The main improvement comes from the combination of the concept of information content and the hierarchical structure of disease directed acyclic graphs for disease similarity calculation. ILNCSIM was combined with the previously proposed model of Laplacian Regularized Least Squares for lncRNA-Disease Association to further evaluate its performance. As a result, new model obtained reliable performance in the leave-one-out cross validation (AUCs of 0.9316 and 0.9074 based on MNDR and Lnc2cancer databases, respectively), and 5-fold cross validation (AUCs of 0.9221 and 0.9033 for MNDR and Lnc2cancer databases), which significantly improved the prediction performance of previous models. It is anticipated that ILNCSIM could serve as an effective lncRNA function prediction model for future biomedical researches. PMID:27028993
Ab initio derivation of model energy density functionals
NASA Astrophysics Data System (ADS)
Dobaczewski, Jacek
2016-08-01
I propose a simple and manageable method that allows for deriving coupling constants of model energy density functionals (EDFs) directly from ab initio calculations performed for finite fermion systems. A proof-of-principle application allows for linking properties of finite nuclei, determined by using the nuclear nonlocal Gogny functional, to the coupling constants of the quasilocal Skyrme functional. The method does not rely on properties of infinite fermion systems but on the ab initio calculations in finite systems. It also allows for quantifying merits of different model EDFs in describing the ab initio results.
The McMaster Model of Family Functioning.
ERIC Educational Resources Information Center
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)
Ensemble modeling with pedotransfer functions in the hydropedological context
Technology Transfer Automated Retrieval System (TEKTRAN)
Uncertainty of soil water content and/or soil water flux estimates with soil water models has recently become of a particular interest in various applications. This work provides examples of using pedotransfer functions (PTFs) to build ensembles of models to characterize the uncertainty of simulatio...
Feature Matching with Affine-Function Transformation Models.
Li, Hongsheng; Huang, Xiaolei; Huang, Junzhou; Zhang, Shaoting
2014-12-01
Feature matching is an important problem and has extensive uses in computer vision. However, existing feature matching methods support either a specific or a small set of transformation models. In this paper, we propose a unified feature matching framework which supports a large family of transformation models. We call the family of transformation models the affine-function family, in which all transformations can be expressed by affine functions with convex constraints. In this framework, the goal is to recover transformation parameters for every feature point in a template point set to calculate their optimal matching positions in an input image. Given pairwise feature dissimilarity values between all points in the template set and the input image, we create a convex dissimilarity function for each template point. Composition of such convex functions with any transformation model in the affine-function family is shown to have an equivalent convex optimization form that can be optimized efficiently. Four example transformation models in the affine-function family are introduced to show the flexibility of our proposed framework. Our framework achieves 0.0 percent matching errors for both CMU House and Hotel sequences following the experimental setup in [6]. PMID:26353148
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.
Additive functions in boolean models of gene regulatory network modules.
Darabos, Christian; Di Cunto, Ferdinando; Tomassini, Marco; Moore, Jason H; Provero, Paolo; Giacobini, Mario
2011-01-01
Gene-on-gene regulations are key components of every living organism. Dynamical abstract models of genetic regulatory networks help explain the genome's evolvability and robustness. These properties can be attributed to the structural topology of the graph formed by genes, as vertices, and regulatory interactions, as edges. Moreover, the actual gene interaction of each gene is believed to play a key role in the stability of the structure. With advances in biology, some effort was deployed to develop update functions in boolean models that include recent knowledge. We combine real-life gene interaction networks with novel update functions in a boolean model. We use two sub-networks of biological organisms, the yeast cell-cycle and the mouse embryonic stem cell, as topological support for our system. On these structures, we substitute the original random update functions by a novel threshold-based dynamic function in which the promoting and repressing effect of each interaction is considered. We use a third real-life regulatory network, along with its inferred boolean update functions to validate the proposed update function. Results of this validation hint to increased biological plausibility of the threshold-based function. To investigate the dynamical behavior of this new model, we visualized the phase transition between order and chaos into the critical regime using Derrida plots. We complement the qualitative nature of Derrida plots with an alternative measure, the criticality distance, that also allows to discriminate between regimes in a quantitative way. Simulation on both real-life genetic regulatory networks show that there exists a set of parameters that allows the systems to operate in the critical region. This new model includes experimentally derived biological information and recent discoveries, which makes it potentially useful to guide experimental research. The update function confers additional realism to the model, while reducing the complexity
Additive Functions in Boolean Models of Gene Regulatory Network Modules
Darabos, Christian; Di Cunto, Ferdinando; Tomassini, Marco; Moore, Jason H.; Provero, Paolo; Giacobini, Mario
2011-01-01
Gene-on-gene regulations are key components of every living organism. Dynamical abstract models of genetic regulatory networks help explain the genome's evolvability and robustness. These properties can be attributed to the structural topology of the graph formed by genes, as vertices, and regulatory interactions, as edges. Moreover, the actual gene interaction of each gene is believed to play a key role in the stability of the structure. With advances in biology, some effort was deployed to develop update functions in Boolean models that include recent knowledge. We combine real-life gene interaction networks with novel update functions in a Boolean model. We use two sub-networks of biological organisms, the yeast cell-cycle and the mouse embryonic stem cell, as topological support for our system. On these structures, we substitute the original random update functions by a novel threshold-based dynamic function in which the promoting and repressing effect of each interaction is considered. We use a third real-life regulatory network, along with its inferred Boolean update functions to validate the proposed update function. Results of this validation hint to increased biological plausibility of the threshold-based function. To investigate the dynamical behavior of this new model, we visualized the phase transition between order and chaos into the critical regime using Derrida plots. We complement the qualitative nature of Derrida plots with an alternative measure, the criticality distance, that also allows to discriminate between regimes in a quantitative way. Simulation on both real-life genetic regulatory networks show that there exists a set of parameters that allows the systems to operate in the critical region. This new model includes experimentally derived biological information and recent discoveries, which makes it potentially useful to guide experimental research. The update function confers additional realism to the model, while reducing the complexity
Phillips' Lambda function: Data summary and physical model
NASA Astrophysics Data System (ADS)
Irisov, V.; Plant, W.
2016-03-01
Measurements of Phillips' Lambda function describing the average length of breakers on the ocean per unit area at speed cb are summarized. An expression is developed that fits these data within reasonable bounds. A physical model for the Lambda function is derived based on the assumption that breaking occurs when the surface steepness exceeds a threshold value. The energy contained in the breaking region is related to the fifth power of the breaker speed, as Phillips showed, and from this the probability of finding a breaker with a speed cb may be determined from a simulation of the long-wave surface based on a linear superposition of Fourier components. This probability is directly related to the Lambda function so that a form for this function can be determined. The Lambda function so determined agrees in both shape and intensity with the fit to the measured Lambda functions.
Plethysms of Schur functions and the shell model
NASA Astrophysics Data System (ADS)
Carvalho, M. J.; D'Agostino, S.
2001-02-01
We present a method for evaluating plethysms of Schur functions that is conceptually simpler than existing methods. Moreover the algorithm can be easily implemented with an algebraic computer language. Plethysms of sums, differences and products of S-functions are dealt with in exactly the same manner as plethysms of simple S-functions. Sums and differences of S-functions are of importance for the description of multi-shell configurations in the shell model. The number of variables in which the S-functions are expressed can be specified in advance, significantly simplifying the calculations in typical applications to many-body problems. The method relies on an algorithm that we have developed for the product of monomial symmetric functions. We present a new way of calculating the Kostka numbers (using Gel'fand patterns) and give, as well, a new formula for the Littlewood-Richardson coefficients.
NASA Astrophysics Data System (ADS)
Slamet, Marlina; Sahni, Viraht
2006-03-01
In the QDFT mapping from a ground or excited state of the interacting system to one of noninteracting fermions in a particular excited state with equivalent density, there is an arbitrariness in the wave function of the model system. For example, in the case of a two-electron atom, the mapping to the excited singlet 2^1S state of the model system, there are three wave functions that lead to the same density: two single Slater determinants of the orbitals that are eigen functions of only Sz, and a linear combination of Slater determinants of these orbitals that is an eigen function of both Sz and S^2. Neither of the wave functions is more appropriate than the other, since all three wave functions deliver the same density. However, based on the choice of wave function, the structure of the corresponding Fermi and Coulomb holes, and therefore the values of the resulting Pauli and Coulomb correlation energies, will differ. Their sum, the Fermi-Coulomb holes, and the Pauli-Coulomb energy, remains unchanged. The wave function arbitrariness will be demonstrated via the Hooke's atom.1 Quantal Density Functional Theory, V. Sahni (Springer-Verlag, 2004).
Modeling uncertainty in reservoir loss functions using fuzzy sets
NASA Astrophysics Data System (ADS)
Teegavarapu, Ramesh S. V.; Simonovic, Slobodan P.
1999-09-01
Imprecision involved in the definition of reservoir loss functions is addressed using fuzzy set theory concepts. A reservoir operation problem is solved using the concepts of fuzzy mathematical programming. Membership functions from fuzzy set theory are used to represent the decision maker's preferences in the definition of shape of loss curves. These functions are assumed to be known and are used to model the uncertainties. Linear and nonlinear optimization models are developed under fuzzy environment. A new approach is presented that involves development of compromise reservoir operating policies based on the rules from the traditional optimization models and their fuzzy equivalents while considering the preferences of the decision maker. The imprecision associated with the definition of penalty and storage zones and uncertainty in the penalty coefficients are the main issues addressed through this study. The models developed are applied to the Green Reservoir, Kentucky. Simulations are performed to evaluate the operating rules generated by the models considering the uncertainties in the loss functions. Results indicate that the reservoir operating policies are sensitive to change in the shapes of loss functions.
Image-based modeling of lung structure and function
Tawhai, Merryn H.; Lin, Ching-Long
2010-01-01
Current state-of-the-art in image-based modeling allows derivation of patient-specific models of the lung, lobes, airways, and pulmonary vascular trees. The application of traditional engineering analyses of fluid and structural mechanics to image-based subject-specific models has the potential to provide new insight into structure-function relationships in the individual via functional interpretation that complements imaging and experimental studies. Three major issues that are encountered in studies of air flow through the bronchial airways are the representation of airway geometry, the imposition of physiological boundary conditions, and the treatment of turbulence. Here we review some efforts to resolve each of these issues, with particular focus on image-based models that have been developed to simulate air flow from the mouth to the terminal bronchiole, and subjected to physiologically meaningful boundary conditions via image registration and soft tissue mechanics models. PMID:21105146
Modeling scattering in turbid media using the Gegenbauer phase function
NASA Astrophysics Data System (ADS)
Calabro, Katherine W.; Cassarly, William
2015-03-01
The choice of scattering phase function is critically important in the modeling of photon propagation in turbid media, particularly when the scattering path within the material is on the order of several mean free path lengths. For tissue applications, the single parameter Henyey-Greenstein (HG) phase function is known to underestimate the contribution of backscattering, while phase functions based on Mie theory can be more complex than necessary due to the multitude of parameter inputs. In this work, the two term Gegenbauer phase function is highlighted as an effective compromise between HG and Mie, as demonstrated when fitting the various phase function to measured data from phantom materials. Further comparison against the Modified Henyey-Greenstein (MHG) phase function, another two term function, demonstrates that the Gegenbauer function provides better control of the higher order phase function moments, and hence allows for a wider range of values for the similarity parameter, γ. Wavelength dependence of the Gegenbauer parameters is also investigated using a range of theoretical particle distributions. Finally, extraction of the scattering properties of solid turbid samples from angularly resolved transmission measurements is performed using an iterative Monte Carlo optimization technique. Fitting results using Gegenbauer, HG, MHG, and Mie phase functions are compared.
Quark fragmentation functions in NJL-jet model
NASA Astrophysics Data System (ADS)
Bentz, Wolfgang; Matevosyan, Hrayr; Thomas, Anthony
2014-09-01
We report on our studies of quark fragmentation functions in the Nambu-Jona-Lasinio (NJL) - jet model. The results of Monte-Carlo simulations for the fragmentation functions to mesons and nucleons, as well as to pion and kaon pairs (dihadron fragmentation functions) are presented. The important role of intermediate vector meson resonances for those semi-inclusive deep inelastic production processes is emphasized. Our studies are very relevant for the extraction of transverse momentum dependent quark distribution functions from measured scattering cross sections. We report on our studies of quark fragmentation functions in the Nambu-Jona-Lasinio (NJL) - jet model. The results of Monte-Carlo simulations for the fragmentation functions to mesons and nucleons, as well as to pion and kaon pairs (dihadron fragmentation functions) are presented. The important role of intermediate vector meson resonances for those semi-inclusive deep inelastic production processes is emphasized. Our studies are very relevant for the extraction of transverse momentum dependent quark distribution functions from measured scattering cross sections. Supported by Grant in Aid for Scientific Research, Japanese Ministry of Education, Culture, Sports, Science and Technology, Project No. 20168769.
Using computational models to relate structural and functional brain connectivity
Hlinka, Jaroslav; Coombes, Stephen
2012-01-01
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. PMID:22805059
Connectotyping: model based fingerprinting of the functional connectome.
Miranda-Dominguez, Oscar; Mills, Brian D; Carpenter, Samuel D; Grant, Kathleen A; Kroenke, Christopher D; Nigg, Joel T; Fair, Damien A
2014-01-01
A better characterization of how an individual's brain is functionally organized will likely bring dramatic advances to many fields of study. Here we show a model-based approach toward characterizing resting state functional connectivity MRI (rs-fcMRI) that is capable of identifying a so-called "connectotype", or functional fingerprint in individual participants. The approach rests on a simple linear model that proposes the activity of a given brain region can be described by the weighted sum of its functional neighboring regions. The resulting coefficients correspond to a personalized model-based connectivity matrix that is capable of predicting the timeseries of each subject. Importantly, the model itself is subject specific and has the ability to predict an individual at a later date using a limited number of non-sequential frames. While we show that there is a significant amount of shared variance between models across subjects, the model's ability to discriminate an individual is driven by unique connections in higher order control regions in frontal and parietal cortices. Furthermore, we show that the connectotype is present in non-human primates as well, highlighting the translational potential of the approach.
Driver steering model for closed-loop steering function analysis
NASA Astrophysics Data System (ADS)
Bolia, Pratiksh; Weiskircher, Thomas; Müller, Steffen
2014-05-01
In this paper, a two level preview driver steering control model for the use in numerical vehicle dynamics simulation is introduced. The proposed model is composed of cascaded control loops: The outer loop is the path following layer based on potential field framework. The inner loop tries to capture the driver's physical behaviour. The proposed driver model allows easy implementation of different driving situations to simulate a wide range of different driver types, moods and vehicle types. The expediency of the proposed driver model is shown with the help of developed driver steering assist (DSA) function integrated with a conventional series production (Electric Power steering System with rack assist servo unit) system. With the help of the DSA assist function, the driver is prevented from over saturating the front tyre forces and loss of stability and controllability during cornering. The simulation results show different driver reactions caused by the change in the parameters or properties of the proposed driver model if the DSA assist function is activated. Thus, the proposed driver model is useful for the advanced driver steering and vehicle stability assist function evaluation in the early stage of vehicle dynamics handling and stability evaluation.
REVIEW: Zebrafish: A Renewed Model System For Functional Genomics
NASA Astrophysics Data System (ADS)
Wen, Xiao-Yan
2008-01-01
In the post genome era, a major goal in molecular biology is to determine the function of the many thousands of genes present in the vertebrate genome. The zebrafish (Danio rerio) provides an almost ideal genetic model to identify the biological roles of these novel genes, in part because their embryos are transparent and develop rapidly. The zebrafish has many advantages over mouse for genome-wide mutagenesis studies, allowing for easier, cheaper and faster functional characterization of novel genes in the vertebrate genome. Many molecular research tools such as chemical mutagenesis, transgenesis, gene trapping, gene knockdown, TILLING, gene targeting, RNAi and chemical genetic screen are now available in zebrafish. Combining all the forward, reverse, and chemical genetic tools, it is expected that zebrafish will make invaluable contribution to vertebrate functional genomics in functional annotation of the genes, modeling human diseases and drug discoveries.
Using Lambert W function and error function to model phase change on microfluidics
NASA Astrophysics Data System (ADS)
Bermudez Garcia, Anderson
2014-05-01
Solidification and melting modeling on microfluidics are solved using Lambert W's function and error's functions. Models are formulated using the heat's diffusion equation. The generic posed case is the melting of a slab with time dependent surface temperature, having a micro or nano-fluid liquid phase. At the beginning the solid slab is at melting temperature. A slab's face is put and maintained at temperature greater than the melting limit and varying in time. Lambert W function and error function are applied via Maple to obtain the analytic solution evolution of the front of microfluidic-solid interface, it is analytically computed and slab's corresponding melting time is determined. It is expected to have analytical results to be useful for food engineering, cooking engineering, pharmaceutical engineering, nano-engineering and bio-medical engineering.
Using special functions to model the propagation of airborne diseases
NASA Astrophysics Data System (ADS)
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.
Testing galaxy formation models with galaxy stellar mass functions
NASA Astrophysics Data System (ADS)
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.
Exact Solutions for Confined Model Systems Using Kummer Functions
NASA Astrophysics Data System (ADS)
Burrows, B. L.; Cohen, M.
We treat model systems where an electron is confined in a region of space. The particular models considered have solutions which may be expressed in terms of the Kummer functions. Both standard and non-standard Kummer functions are used in these models and a comprehensive summary of the usual and exceptional Kummer functions is given. The definition of confinement is widened to treat radial confinement in any spherical shell, including the asymptotic region and cases where the electron is confined to a lower dimension. Initially we consider the theory in K dimensional space and then give particular examples in 1, 2, and 3 dimensions. A commonly treated model is the radially confined hydrogen atom in 3 dimensions with an infinite barrier on a confining sphere so that the wavefunction is identically zero on this sphere. We have extended this model to treat a more general model of spherical confinement where the derivative of the charge density is zero on the confining sphere. It is shown that the analogous models for the radial harmonic oscillator and radial constant potentials may be treated using a generic technique.
The Thirring-Wess model revisited: a functional integral approach
Belvedere, L.V. . E-mail: armflavio@if.uff.br
2005-06-01
We consider the Wess-Zumino-Witten theory to obtain the functional integral bosonization of the Thirring-Wess model with an arbitrary regularization parameter. Proceeding a systematic of decomposing the Bose field algebra into gauge-invariant- and gauge-non-invariant field subalgebras, we obtain the local decoupled quantum action. The generalized operator solutions for the equations of motion are reconstructed from the functional integral formalism. The isomorphism between the QED {sub 2} (QCD {sub 2}) with broken gauge symmetry by a regularization prescription and the Abelian (non-Abelian) Thirring-Wess model with a fixed bare mass for the meson field is established.
An allosteric model for the functional plasticity of olfactory chemoreceptors
NASA Astrophysics Data System (ADS)
Colosimo, Alfredo
2000-12-01
A simple allosteric model may describe the relatively (a)specific behaviour of olfactory chemoreceptors (OCs) and their functional plasticity with a minimum number of parameters. Allosteric, heterotropic effectors are suggested as a possible cause of variable responses documented, in particular, in frog OCs. As an immediate spinoff of the continuously increasing amount of structural information available on natural OCs, development of appropriate allosteric models is foreseen to provide plausible molecular mechanisms for their complex functional performance. This may also have implications in the design of artificial olfaction systems.
Algorithmic chemistry: A model for functional self-organization
Fontana, W.
1990-01-01
We conjecture that adaptive systems are characterized by a self- referential loop in which combinatorial objects encode functions that act back on these objects. A model for this loop is presented. It uses a simple and powerful recursive language to map character strings into algorithms that symbolically manipulate strings. The interaction between algorithms, i.e. functions, can be defined in a natural way within the language. The behavior of a fixed size ensemble of functions acting on each other is studied under various conditions. The function gas,'' or Turing gas,'' evolves cooperative interaction patterns of considerable intricacy. Such patterns are observed to adapt under the influence of perturbations consisting in the addition of new random functions to the system. Completely different organizational architectures emerge depending on the availability of self-replicators.
Bessel functions in mass action modeling of memories and remembrances
NASA Astrophysics Data System (ADS)
Freeman, Walter J.; Capolupo, Antonio; Kozma, Robert; Olivares del Campo, Andrés; Vitiello, Giuseppe
2015-10-01
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.
Functional error modeling for uncertainty quantification in hydrogeology
NASA Astrophysics Data System (ADS)
Josset, L.; Ginsbourger, D.; Lunati, I.
2015-02-01
Approximate models (proxies) can be employed to reduce the computational costs of estimating uncertainty. The price to pay is that the approximations introduced by the proxy model can lead to a biased estimation. To avoid this problem and ensure a reliable uncertainty quantification, we propose to combine functional data analysis and machine learning to build error models that allow us to obtain an accurate prediction of the exact response without solving the exact model for all realizations. We build the relationship between proxy and exact model on a learning set of geostatistical realizations for which both exact and approximate solvers are run. Functional principal components analysis (FPCA) is used to investigate the variability in the two sets of curves and reduce the dimensionality of the problem while maximizing the retained information. Once obtained, the error model can be used to predict the exact response of any realization on the basis of the sole proxy response. This methodology is purpose-oriented as the error model is constructed directly for the quantity of interest, rather than for the state of the system. Also, the dimensionality reduction performed by FPCA allows a diagnostic of the quality of the error model to assess the informativeness of the learning set and the fidelity of the proxy to the exact model. The possibility of obtaining a prediction of the exact response for any newly generated realization suggests that the methodology can be effectively used beyond the context of uncertainty quantification, in particular for Bayesian inference and optimization.
"Sloppy" nuclear energy density functionals: Effective model reduction
NASA Astrophysics Data System (ADS)
Nikšić, Tamara; Vretenar, Dario
2016-08-01
Concepts from information geometry are used to analyze parameter sensitivity for a nuclear energy density functional, representative of a class of semiempirical 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," namely, characterized by an exponential range of sensitivity to parameter variations. Responsive to only a few stiff parameter combinations, sloppy functionals 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 range of parameter sensitivity. Using the manifold boundary approximation method, we illustrate how to systematically construct effective nuclear density functionals of successively lower dimension in parameter space until sloppiness is eventually eliminated and the resulting functional contains only stiff combinations of parameters.
Penalized spline estimation for functional coefficient regression models
Cao, Yanrong; Lin, Haiqun; Wu, Tracy Z.
2011-01-01
The functional coefficient regression models assume that the regression coefficients vary with some “threshold” variable, providing appreciable flexibility in capturing the underlying dynamics in data and avoiding the so-called “curse of dimensionality” in multivariate nonparametric estimation. We first investigate the estimation, inference, and forecasting for the functional coefficient regression models with dependent observations via penalized splines. The P-spline approach, as a direct ridge regression shrinkage type global smoothing method, is computationally efficient and stable. With established fixed-knot asymptotics, inference is readily available. Exact inference can be obtained for fixed smoothing parameter λ, which is most appealing for finite samples. Our penalized spline approach gives an explicit model expression, which also enables multi-step-ahead forecasting via simulations. Furthermore, we examine different methods of choosing the important smoothing parameter λ: modified multi-fold cross-validation (MCV), generalized cross-validation (GCV), and an extension of empirical bias bandwidth selection (EBBS) to P-splines. In addition, we implement smoothing parameter selection using mixed model framework through restricted maximum likelihood (REML) for P-spline functional coefficient regression models with independent observations. The P-spline approach also easily allows different smoothness for different functional coefficients, which is enabled by assigning different penalty λ accordingly. We demonstrate the proposed approach by both simulation examples and a real data application. PMID:21516260
Cohesive fracture model for functionally graded fiber reinforced concrete
Park, Kyoungsoo; Paulino, Glaucio H.; Roesler, Jeffery
2010-06-15
A simple, effective, and practical constitutive model for cohesive fracture of fiber reinforced concrete is proposed by differentiating the aggregate bridging zone and the fiber bridging zone. The aggregate bridging zone is related to the total fracture energy of plain concrete, while the fiber bridging zone is associated with the difference between the total fracture energy of fiber reinforced concrete and the total fracture energy of plain concrete. The cohesive fracture model is defined by experimental fracture parameters, which are obtained through three-point bending and split tensile tests. As expected, the model describes fracture behavior of plain concrete beams. In addition, it predicts the fracture behavior of either fiber reinforced concrete beams or a combination of plain and fiber reinforced concrete functionally layered in a single beam specimen. The validated model is also applied to investigate continuously, functionally graded fiber reinforced concrete composites.
A model for designing functionally gradient material joints
Messler, R.W. Jr.; Jou, M.; Orling, T.T.
1995-05-01
An analytical, thin-plate layer model was developed to assist research and development engineers in the design of functionally gradient material (FGM) joints consisting of discrete steps between end elements of dissimilar materials. Such joints have long been produced by diffusion bonding using intermediates or multiple interlayers; welding, brazing or soldering using multiple transition pieces; and glass-to-glass or glass-to-metal bonding using multiple layers to produce matched seals. More recently, FGM joints produced by self-propagating high-temperature synthesis (SHS) are attracting the attention of researchers. The model calculates temperature distributions and associated thermally induced stresses, assuming elastic behavior, for any number of layers of any thickness or composition, accounting for critically important thermophysical properties in each layer as functions of temperature. It is useful for assuring that cured-in fabrication stresses from thermal expansion mismatches will not prevent quality joint production. The model`s utility is demonstrated with general design cases.
Model Adequacy and the Macroevolution of Angiosperm Functional Traits.
Pennell, Matthew W; FitzJohn, Richard G; Cornwell, William K; Harmon, Luke J
2015-08-01
Making meaningful inferences from phylogenetic comparative data requires a meaningful model of trait evolution. It is thus important to determine whether the model is appropriate for the data and the question being addressed. One way to assess this is to ask whether the model provides a good statistical explanation for the variation in the data. To date, researchers have focused primarily on the explanatory power of a model relative to alternative models. Methods have been developed to assess the adequacy, or absolute explanatory power, of phylogenetic trait models, but these have been restricted to specific models or questions. Here we present a general statistical framework for assessing the adequacy of phylogenetic trait models. We use our approach to evaluate the statistical performance of commonly used trait models on 337 comparative data sets covering three key angiosperm functional traits. In general, the models we tested often provided poor statistical explanations for the evolution of these traits. This was true for many different groups and at many different scales. Whether such statistical inadequacy will qualitatively alter inferences drawn from comparative data sets will depend on the context. Regardless, assessing model adequacy can provide interesting biological insights-how and why a model fails to describe variation in a data set give us clues about what evolutionary processes may have driven trait evolution across time. PMID:26655160
Predicting plants -modeling traits as a function of environment
NASA Astrophysics Data System (ADS)
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
An integral representation of functions in gas-kinetic models
NASA Astrophysics Data System (ADS)
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.
Integrating behavioral and physiological models of hippocampal function.
Gluck, M A; Myers, C E
1996-01-01
In recent modeling of hippocampal function, we have attempted to integrate formal behavioral analyses of classical conditioning with psychobiological data on brain lesions (Gluck and Myers [1993] Hippocampus 3:491-516; Myers and Gluck [1994] Behav Neurosci 108(5):835-847). Based on comparative behavioral analyses, we have argued that animals with hippocampal region damage are unable to alter stimulus similarity based on experience. While hippocampal-damaged animals can still learn whether to respond to an individual stimulus, they are notably impaired at many tasks involving learning relationships between stimuli-especially in the absence of explicit reinforcement. These analyses lead to a computational theory which identifies two representational recoding processes-predictive differentiation and redundancy compression-which alter stimulus similarity relationships in intact animals but are dependent on intact hippocampal region processing. More recent, and ongoing, modeling aims to broaden this model of hippocampal region function in classical conditioning, with an emphasis on physiological and anatomical constraints, including the role of the fornix and subcortical modulation, preprocessing in sensory cortices, and localization of the proposed representational functions within more precisely identified hippocampal region substrates (Myers et al. [1995] Psychology 23(2):116-138; Myers and Gluck [1996] Behav Neurosci; Myers et al. [1996] Neurobiol Learning Memory). Working to bridge between behavioral and physiological levels of analysis, we ultimately hope to develop a more complete understanding of hippocampal region function in memory across a wider range of behavioral paradigms, elucidating how this functionality emerges from underlying physiological and anatomical substrates.
An Analytic Function of Lunar Surface Temperature for Exospheric Modeling
NASA Technical Reports Server (NTRS)
Hurley, Dana M.; Sarantos, Menelaos; Grava, Cesare; Williams, Jean-Pierre; Retherford, Kurt D.; Siegler, Matthew; Greenhagen, Benjamin; Paige, David
2014-01-01
We present an analytic expression to represent the lunar surface temperature as a function of Sun-state latitude and local time. The approximation represents neither topographical features nor compositional effects and therefore does not change as a function of selenographic latitude and longitude. The function reproduces the surface temperature measured by Diviner to within +/-10 K at 72% of grid points for dayside solar zenith angles of less than 80, and at 98% of grid points for nightside solar zenith angles greater than 100. The analytic function is least accurate at the terminator, where there is a strong gradient in the temperature, and the polar regions. Topographic features have a larger effect on the actual temperature near the terminator than at other solar zenith angles. For exospheric modeling the effects of topography on the thermal model can be approximated by using an effective longitude for determining the temperature. This effective longitude is randomly redistributed with 1 sigma of 4.5deg. The resulting ''roughened'' analytical model well represents the statistical dispersion in the Diviner data and is expected to be generally useful for future models of lunar surface temperature, especially those implemented within exospheric simulations that address questions of volatile transport.
A Multi-Level Model of Moral Functioning Revisited
ERIC Educational Resources Information Center
Reed, Don Collins
2009-01-01
The model of moral functioning scaffolded in the 2008 "JME" Special Issue is here revisited in response to three papers criticising that volume. As guest editor of that Special Issue I have formulated the main body of this response, concerning the dynamic systems approach to moral development, the problem of moral relativism and the role of…
An Adaptive Complex Network Model for Brain Functional Networks
Gomez Portillo, Ignacio J.; Gleiser, Pablo M.
2009-01-01
Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree distribution and the presence (or absence) of a hierarchical structure are not robust, and show different intriguing behaviors. In order to understand the basic ingredients necessary for the emergence of these complex network structures we present an adaptive complex network model for human brain functional networks. The microscopic units of the model are dynamical nodes that represent active regions of the brain, whose interaction gives rise to complex network structures. The links between the nodes are chosen following an adaptive algorithm that establishes connections between dynamical elements with similar internal states. We show that the model is able to describe topological characteristics of human brain networks obtained from functional magnetic resonance imaging studies. In particular, when the dynamical rules of the model allow for integrated processing over the entire network scale-free non-hierarchical networks with well defined communities emerge. On the other hand, when the dynamical rules restrict the information to a local neighborhood, communities cluster together into larger ones, giving rise to a hierarchical structure, with a truncated power law degree distribution. PMID:19738902
The fundamental structure function of oscillator noise models
NASA Technical Reports Server (NTRS)
Greenhall, C. A.
1983-01-01
Continuous-time models of oscillator phase noise x(t) usually have stationary nth differences, for some n. The covariance structure of such a model can be characterized in the time domain by the structure function: D sub n (t;gamma sub 1, gamma sub 2) = E delta (n) sub gamma sub 1 x(s+t) delta(n) sub gamma sub 2 x (s). Although formulas for the special case D sub 2 (0;gamma,gamma) (the Allan variance times 2 gamma(2)) exist for power-law spectral models, certain estimation problems require a more complete knowledge of (0). Exhibited is a much simpler function of one time variable, D(t), from which (0) can easily be obtained from the spectral density by uncomplicated integrations. Believing that D(t) is the simplest function of time that holds the same information as (0), D(t) is called the fundamental structure function. D(t) is computed for several power-law spectral models. Two examples are D(t) = K/t/(3) for random walk FM, D(t) = Kt(2) 1n/t/ for flicker FM. Then, to demonstrate its use, a BASIC program is given that computes means and variances of two Allan variance estimators, one of which incorporates a method of frequency drift estimation and removal.
Verbal Neuropsychological Functions in Aphasia: An Integrative Model
ERIC Educational Resources Information Center
Vigliecca, Nora Silvana; Báez, Sandra
2015-01-01
A theoretical framework which considers the verbal functions of the brain under a multivariate and comprehensive cognitive model was statistically analyzed. A confirmatory factor analysis was performed to verify whether some recognized aphasia constructs can be hierarchically integrated as latent factors from a homogenously verbal test. The Brief…
Assessing and Explaining Differential Item Functioning Using Logistic Mixed Models
ERIC Educational Resources Information Center
Van den Noortgate, Wim; De Boeck, Paul
2005-01-01
Although differential item functioning (DIF) theory traditionally focuses on the behavior of individual items in two (or a few) specific groups, in educational measurement contexts, it is often plausible to regard the set of items as a random sample from a broader category. This article presents logistic mixed models that can be used to model…
Subgrid spatial variability of soil hydraulic functions for hydrological modelling
NASA Astrophysics Data System (ADS)
Kreye, Phillip; Meon, Günter
2016-07-01
State-of-the-art hydrological applications require a process-based, spatially distributed hydrological model. Runoff characteristics are demanded to be well reproduced by the model. Despite that, the model should be able to describe the processes at a subcatchment scale in a physically credible way. The objective of this study is to present a robust procedure to generate various sets of parameterisations of soil hydraulic functions for the description of soil heterogeneity on a subgrid scale. Relations between Rosetta-generated values of saturated hydraulic conductivity (Ks) and van Genuchten's parameters of soil hydraulic functions were statistically analysed. An universal function that is valid for the complete bandwidth of Ks values could not be found. After concentrating on natural texture classes, strong correlations were identified for all parameters. The obtained regression results were used to parameterise sets of hydraulic functions for each soil class. The methodology presented in this study is applicable on a wide range of spatial scales and does not need input data from field studies. The developments were implemented into a hydrological modelling system.
AGSM Functional Fault Models for Fault Isolation Project
NASA Technical Reports Server (NTRS)
Harp, Janicce Leshay
2014-01-01
This project implements functional fault models to automate the isolation of failures during ground systems operations. FFMs will also be used to recommend sensor placement to improve fault isolation capabilities. The project enables the delivery of system health advisories to ground system operators.
Differential Expression and Network Inferences through Functional Data Modeling
Telesca, Donatello; Inoue, Lurdes Y.T.; Neira, Mauricio; Etzioni, Ruth; Gleave, Martin; Nelson, Colleen
2010-01-01
Time–course microarray data consist of mRNA expression from a common set of genes collected at different time points. Such data are thought to reflect underlying biological processes developing over time. In this article we propose a model that allows us to examine differential expression and gene network relationships using time course microarray data. We model each gene expression profile as a random functional transformation of the scale, amplitude and phase of a common curve. Inferences about the gene–specific amplitude parameters allow us to examine differential gene expression. Inferences about measures of functional similarity based on estimated time transformation functions allow us to examine gene networks while accounting for features of the gene expression profiles. We discuss applications to simulated data as well as to microarray data on prostate cancer progression. PMID:19053995
OFMTutor: An operator function model intelligent tutoring system
NASA Technical Reports Server (NTRS)
Jones, Patricia M.
1989-01-01
The design, implementation, and evaluation of an Operator Function Model intelligent tutoring system (OFMTutor) is presented. OFMTutor is intended to provide intelligent tutoring in the context of complex dynamic systems for which an operator function model (OFM) can be constructed. The human operator's role in such complex, dynamic, and highly automated systems is that of a supervisory controller whose primary responsibilities are routine monitoring and fine-tuning of system parameters and occasional compensation for system abnormalities. The automated systems must support the human operator. One potentially useful form of support is the use of intelligent tutoring systems to teach the operator about the system and how to function within that system. Previous research on intelligent tutoring systems (ITS) is considered. The proposed design for OFMTutor is presented, and an experimental evaluation is described.
Systemic Modeling of Biological Functions in Consideration of Physiome Project
NASA Astrophysics Data System (ADS)
Minamitani, Haruyuki
Emerging of the physiome project provides various influences on the medical, biological and pharmaceutical development. In this paper, as an example of physiome research, neural network model analysis providing the conduction mechanisms of pain and tactile sensations was presented, and the functional relations between neural activities of the network cells and stimulus intensity applied on the peripheral receptive fields were described. The modeling presented here is based on the various assumptions made by the results of physiological and anatomical studies reported in the literature. The functional activities of spinothalamic and thalamocortical cells show a good agreement with the physiological and psychophysical functions of somatosensory system that are very instructive for covering the gap between physiologically and psychophysically aspects of pain and tactile sensation.
Development on electromagnetic impedance function modeling and its estimation
Sutarno, D.
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
Development on electromagnetic impedance function modeling and its estimation
NASA Astrophysics Data System (ADS)
Sutarno, D.
2015-09-01
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
Optimal hemodynamic response model for functional near-infrared spectroscopy
Kamran, Muhammad A.; Jeong, Myung Yung; Mannan, Malik M. N.
2015-01-01
Functional near-infrared spectroscopy (fNIRS) is an emerging non-invasive brain imaging technique and measures brain activities by means of near-infrared light of 650–950 nm wavelengths. The cortical hemodynamic response (HR) differs in attributes at different brain regions and on repetition of trials, even if the experimental paradigm is kept exactly the same. Therefore, an HR model that can estimate such variations in the response is the objective of this research. The canonical hemodynamic response function (cHRF) is modeled by two Gamma functions with six unknown parameters (four of them to model the shape and other two to scale and baseline respectively). The HRF model is supposed to be a linear combination of HRF, baseline, and physiological noises (amplitudes and frequencies of physiological noises are supposed to be unknown). An objective function is developed as a square of the residuals with constraints on 12 free parameters. The formulated problem is solved by using an iterative optimization algorithm to estimate the unknown parameters in the model. Inter-subject variations in HRF and physiological noises have been estimated for better cortical functional maps. The accuracy of the algorithm has been verified using 10 real and 15 simulated data sets. Ten healthy subjects participated in the experiment and their HRF for finger-tapping tasks have been estimated and analyzed. The statistical significance of the estimated activity strength parameters has been verified by employing statistical analysis (i.e., t-value > tcritical and p-value < 0.05). PMID:26136668
Analytical Model for Thermal Elastoplastic Stresses of Functionally Graded Materials
Zhai, P. C.; Chen, G.; Liu, L. S.; Fang, C.; Zhang, Q. J.
2008-02-15
A modification analytical model is presented for the thermal elastoplastic stresses of functionally graded materials subjected to thermal loading. The presented model follows the analytical scheme presented by Y. L. Shen and S. Suresh [6]. In the present model, the functionally graded materials are considered as multilayered materials. Each layer consists of metal and ceramic with different volume fraction. The ceramic layer and the FGM interlayers are considered as elastic brittle materials. The metal layer is considered as elastic-perfectly plastic ductile materials. Closed-form solutions for different characteristic temperature for thermal loading are presented as a function of the structure geometries and the thermomechanical properties of the materials. A main advance of the present model is that the possibility of the initial and spread of plasticity from the two sides of the ductile layers taken into account. Comparing the analytical results with the results from the finite element analysis, the thermal stresses and deformation from the present model are in good agreement with the numerical ones.
Identifying Model-Based Reconfiguration Goals through Functional Deficiencies
NASA Technical Reports Server (NTRS)
Benazera, Emmanuel; Trave-Massuyes, Louise
2004-01-01
Model-based diagnosis is now advanced to the point autonomous systems face some uncertain and faulty situations with success. The next step toward more autonomy is to have the system recovering itself after faults occur, a process known as model-based reconfiguration. After faults occur, given a prediction of the nominal behavior of the system and the result of the diagnosis operation, this paper details how to automatically determine the functional deficiencies of the system. These deficiencies are characterized in the case of uncertain state estimates. A methodology is then presented to determine the reconfiguration goals based on the deficiencies. Finally, a recovery process interleaves planning and model predictive control to restore the functionalities in prioritized order.
A Method of EC Model Implementation Using Web Service Functions
NASA Astrophysics Data System (ADS)
Kurihara, Jun; Koizumi, Hisao; Ishikawa, Toshiyuki; Dasai, Takashi
In recent years, advances in computer and communication technology and the associated rapid increase in the number of Internet users are encouraging advances in Electronic Commerce (EC). Business models of EC are being actively developed by many different enterprises and engineers, and implemented in many kinds of fields. Meanwhile Web services that reuse remote components over the Internet are drawing attention. Web services are based on SOAP/WSDL/UDDI and are given an important position as the infrastructure of the EC systems. The article analyzes the functions and structures of various business models, establishing the patterns of their distinctive and common features, and proposes a method of determining the implementation specifications of business models utilizing these patterns and Web service functions. This method has been applied to a parts purchasing system, which is a typical pattern of the B to B (Business to Business) EC applications. The article also discusses the results of evaluating this prototype system.
Calculations of multiquark functions in effective models of strong interaction
Jafarov, R. G.; Rochev, V. E.
2013-09-15
In this paper we present our results of the investigation of multiquark equations in the Nambu-Jona-Lasinio model with chiral symmetry of SU(2) group in the mean-field expansion. To formulate the mean-field expansion we have used an iteration scheme of solution of the Schwinger-Dyson equations with the fermion bilocal source. We have considered the equations for Green functions of the Nambu-Jona-Lasinio model up to third step for this iteration scheme. To calculate the high-order corrections to the mean-field approximation, we propose the method of the Legendre transformation with respect to the bilocal source, which allows effectively to take into account the symmetry constraints related with the chiral Ward identity. We discuss also the problem of calculating the multiquark functions in the mean-field expansion for Nambu-Jona-Lasinio-type models with other types of the multifermion sources.
Future of Plant Functional Types in Terrestrial Biosphere Models
NASA Astrophysics Data System (ADS)
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
A Comparison of Functional Models for Use in the Function-Failure Design Method
NASA Technical Reports Server (NTRS)
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
Linking geophysics and soil function modelling - two examples
NASA Astrophysics Data System (ADS)
Krüger, J.; Franko, U.; Werban, U.; Dietrich, P.; Behrens, T.; Schmidt, K.; Fank, J.; Kroulik, M.
2011-12-01
iSOIL - "Interactions between soil related sciences - Linking geophysics, soil science and digital soil mapping" is a Collaborative Project (Grant Agreement number 211386) co-funded by the Research DG of the European Commission within the RTD activities of the FP7 Thematic Priority Environment. The iSOIL project aims at reliable mapping of soil properties and soil functions with various methods including geophysical, spectroscopic and monitoring techniques. The general procedure contains three steps (i) geophysical monitoring, (ii) generation of soil property maps and (iii) process modelling. The objective of this work is to demonstrate the methodological procedure on two different examples. Example A focuses on the turnover conditions for soil organic matter (SOM) since many soil functions in a direct or indirect way depend on SOM and SOM depletion is amongst the worst soil threats. Example B deals with the dynamics of soil water and the direct influence on crop biomass production. The applied CANDY model (Franko et al. 1995) was developed to describe dynamics of soil organic matter and mineral nitrogen as well as soil water and temperature. The new module PLUS extends CANDY to simulate crop biomass production based on environmental influences (Krüger et al. 2011). The methodological procedure of example A illustrates a model application for a field site in the Czech Republic using generated soil maps from combined geophysical data. Modelling requires a complete set of soil parameters. Combining measured soil properties and data of geophysical measurements (electrical conductivity and gamma spectrometry) is the basis for digital soil mapping which provided data about clay, silt and sand as well as SOC content. With these data pedotransfer functions produce detailed soil input data (e.g. bulk and particle density, field capacity, wilting point, saturated conductivity) for the rooted soil profile. CANDY calculated different indicators for SOM and gave hints about
Model updating using correlation analysis of strain frequency response function
NASA Astrophysics Data System (ADS)
Guo, Ning; Yang, Zhichun; Jia, You; Wang, Le
2016-03-01
A method is proposed to modify the structural parameters of a dynamic finite element (FE) model by using the correlation analysis for strain frequency response function (SFRF). Sensitivity analysis of correlation coefficients is used to establish the linear algebraic equations for model updating. In order to improve the accuracy of updated model, the regularization technique is used to solve the ill-posed problem in model updating procedure. Finally, a numerical study and a model updating experiment are performed to verify the feasibility and robustness of the proposed method. The results show that the updated SFRFs and experimental SFRFs agree well, especially in resonance regions. Meanwhile, the proposed method has good robustness to noise ability and remains good feasibility even the number of measurement locations reduced significantly.
Reducing equifinality of hydrological models by integrating Functional Streamflow Disaggregation
NASA Astrophysics Data System (ADS)
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
Structure, function, and behaviour of computational models in systems biology
2013-01-01
Background Systems Biology develops computational models in order to understand biological phenomena. The increasing number and complexity of such “bio-models” necessitate computer support for the overall modelling task. Computer-aided modelling has to be based on a formal semantic description of bio-models. But, even if computational bio-models themselves are represented precisely in terms of mathematical expressions their full meaning is not yet formally specified and only described in natural language. Results We present a conceptual framework – the meaning facets – which can be used to rigorously specify the semantics of bio-models. A bio-model has a dual interpretation: On the one hand it is a mathematical expression which can be used in computational simulations (intrinsic meaning). On the other hand the model is related to the biological reality (extrinsic meaning). We show that in both cases this interpretation should be performed from three perspectives: the meaning of the model’s components (structure), the meaning of the model’s intended use (function), and the meaning of the model’s dynamics (behaviour). In order to demonstrate the strengths of the meaning facets framework we apply it to two semantically related models of the cell cycle. Thereby, we make use of existing approaches for computer representation of bio-models as much as possible and sketch the missing pieces. Conclusions The meaning facets framework provides a systematic in-depth approach to the semantics of bio-models. It can serve two important purposes: First, it specifies and structures the information which biologists have to take into account if they build, use and exchange models. Secondly, because it can be formalised, the framework is a solid foundation for any sort of computer support in bio-modelling. The proposed conceptual framework establishes a new methodology for modelling in Systems Biology and constitutes a basis for computer-aided collaborative research
Damped sinusoidal function to model acute irradiation in radiotherapy patients.
Tukiendorf, Andrzej; Miszczyk, Leszek; Bojarski, Jacek
2013-09-01
In the paper, we suggest a damped sinusoidal function be used to model a regenerative response of mucosa in time after the radiotherapy treatment. The medical history of 389 RT patients irradiated within the years 1994-2000 at the Radiotherapy Department, Cancer Center, Maria Skłodowska-Curie Memorial Institute of Oncology, Gliwice, Poland, was taken into account. In the analyzed group of patients, the number of observations of a single patient ranged from 2 to 25 (mean = 8.3, median = 8) with severity determined by use of Dische's scores from 0 to 24 (mean = 7.4, median = 7). Statistical modeling of radiation-induced mucositis was performed for five groups of patients irradiated within the following radiotherapy schedules: CAIR, CB, Manchester, CHA-CHA, and Conventional. All of the regression parameters of the assumed model, i.e. amplitude, damping coefficient, angular frequency, phase of component, and offset, estimated in the analysis were statistically significant (p-value < 0.05) for the radiotherapy schedules. The model was validated using a non-oscillatory function. Following goodness-of-fit statistics, the damped sinusoidal function fits the data better than the non-oscillatory damped function. Model curves for harmonic characteristics with confidence intervals were plotted separately for each of the RT schedules and together in a combined design. The suggested model might be helpful in the numeric evaluation of the RT toxicity in the groups of patients under analysis as it allows for practical comparisons and treatment optimization. A statistical approach is also briefly described in the paper.
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 < 0.05). Substantial discrepancies between the CM and HoII models were possible depending on flock sizes used to model feeding 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.
System identification and model reduction using modulating function techniques
NASA Technical Reports Server (NTRS)
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.
ERIC Educational Resources Information Center
Campbell, Todd; Oh, Phil Seok; Maughn, Milo; Kiriazis, Nick; Zuwallack, Rebecca
2015-01-01
The current review examined modeling literature in top science education journals to better understand the pedagogical functions of modeling instruction reported over the last decade. Additionally, the review sought to understand the extent to which different modeling pedagogies were employed, the discursive acts that were identified as important,…
An autonomy supportive model of geriatric team function.
Powers, J S; White, S; Varnell, L; Turvy, C; Kidd, K; Harrell, D; Knight, B; Floyd, K; Zupko, K
2000-08-01
Interdisciplinary teams play a critical role in the delivery of geriatric health care. Health care professionals are commonly left to develop teamwork skills by chance. Medical team function differs from traditional group theory in that all members are caregivers. A non-competitive supportive atmosphere is appropriate for patient care. We propose a participatory (autonomy supportive) model fostering self-realization and positive reinforcement as an organizing philosophy. The primary group task is to maximize patient functional independence and personal goals. Leadership is task-dependent.
High temporal resolution functional MRI with partial separability model.
Ngo, Giang-Chau; Holtrop, Joseph L; Fu, Maojing; Lam, Fan; Sutton, Bradley P
2015-01-01
Even though the hemodynamic response is a slow phenomenon, high temporal resolution in functional fMRI can enable better differentiation between the signal of interest and physiological noise or increase the statistical power of functional studies. To increase the temporal resolution, several methods have been developed to decrease the repetition time, TR, such as simultaneous multi-slice imaging and MR encephalography approaches. In this work, a method using a fast acquisition and a partial separability model is presented to achieve a multi-slice fMRI protocol at a temporal resolution of 75 ms. The method is demonstrated on a visual block task. PMID:26738022
Molecular Modeling of Mechanosensory Ion Channel Structural and Functional Features
Gessmann, Renate; Kourtis, Nikos; Petratos, Kyriacos; Tavernarakis, Nektarios
2010-01-01
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. PMID:20877470
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.
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.
Functional modelling of planar cell polarity: an approach for identifying molecular function
2013-01-01
Background Cells in some tissues acquire a polarisation in the plane of the tissue in addition to apical-basal polarity. This polarisation is commonly known as planar cell polarity and has been found to be important in developmental processes, as planar polarity is required to define the in-plane tissue coordinate system at the cellular level. Results We have built an in-silico functional model of cellular polarisation that includes cellular asymmetry, cell-cell signalling and a response to a global cue. The model has been validated and parameterised against domineering non-autonomous wing hair phenotypes in Drosophila. Conclusions We have carried out a systematic comparison of in-silico polarity phenotypes with patterns observed in vivo under different genetic manipulations in the wing. This has allowed us to classify the specific functional roles of proteins involved in generating cell polarity, providing new hypotheses about their specific functions, in particular for Pk and Dsh. The predictions from the model allow direct assignment of functional roles of genes from genetic mosaic analysis of Drosophila wings. PMID:23672397
Generation of saturation functions for simulation models of carbonate reservoirs
NASA Astrophysics Data System (ADS)
Huang, Qingfeng
A rock type is the unit of rock deposited under similar conditions, which went through similar diagenetic processes, producing analogous rock fabric, with distinct set of pore types, and pore throat size distribution, having specific range of porosity and permeability. Rock typing can generally be used as a guide to assign petrophysical characteristics to different zones for detailed reservoir characterization, modeling and simulation, which provide valid frames for reservoir development. It is often assumed that conventional rock types are capable of assigning multiphase flow characteristics, such as capillary pressure and relative permeability to the cells of dynamic simulation models. However, these conventional rock types, or static reservoir rock types (SRRT) fail to capture the actual variability of capillary pressure and relative permeability, due to lack of representation of wettability difference at different elevation above the free water level (FWL) in carbonate reservoirs, especially in the highly heterogeneous reservoirs. This should be resolved through dynamic reservoir rock types (DRRT), in which wettability effect is imposed on the SRRTs to generate saturation functions for simulation models. This research studies Ghedan's comprehensive DRRT model7, and proposes a modified Ghedan's model. First, the defined static rock types are sub-divided into sub-static rock types based on porosity frequency. Second, three curve-fitting programs are coded to generate the related saturation-height functions. These are the modified Ghedan-Okuyiga equation, Cuddy function and Power Law function. Developed from Ghedan-Okuyiga function113, the recommended modified Ghedan-Okuyiga function has been proposed with saturation and implicit porosity as a function of height above FWL in the transition zone. Third, each sub-static rock type is divided into a number of DRRTs by determining the capillary pressure and relative permeability curves in the oil zone from gas
Photonic encryption : modeling and functional analysis of all optical logic.
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 and time delay
Coupled vibro-acoustic model updating using frequency response functions
NASA Astrophysics Data System (ADS)
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.
Adding ecosystem function to agent-based land use models
Yadav, V.; Del Grosso, S.J.; Parton, W.J.; Malanson, G.P.
2015-01-01
The objective of this paper is to examine issues in the inclusion of simulations of ecosystem functions in agent-based models of land use decision-making. The reasons for incorporating these simulations include local interests in land fertility and global interests in carbon sequestration. Biogeochemical models are needed in order to calculate such fluxes. The Century model is described with particular attention to the land use choices that it can encompass. When Century is applied to a land use problem the combinatorial choices lead to a potentially unmanageable number of simulation runs. Century is also parameter-intensive. Three ways of including Century output in agent-based models, ranging from separately calculated look-up tables to agents running Century within the simulation, are presented. The latter may be most efficient, but it moves the computing costs to where they are most problematic. Concern for computing costs should not be a roadblock. PMID:26191077
Implicit electrostatic solvent model with continuous dielectric permittivity function.
Basilevsky, Mikhail V; Grigoriev, Fedor V; Nikitina, Ekaterina A; Leszczynski, Jerzy
2010-02-25
The modification of the electrostatic continuum solvent model considered in the present work is based on the exact solution of the Poisson equation, which can be constructed provided that the dielectric permittivity epsilon of the total solute and solvent system is an isotropic and continuous spatial function. This assumption allows one to formulate a numerically efficient and universal computational scheme that covers the important case of a variable epsilon function inherent to the solvent region. The obtained type of solution is unavailable for conventional dielectric continuum models such as the Onsager and Kirkwood models for spherical cavities and the polarizable continuum model (PCM) for solute cavities of general shape, which imply that epsilon is discontinuous on the boundary confining the excluded volume cavity of the solute particle. Test computations based on the present algorithm are performed for water and several nonaqueous solvents. They illustrate specific features of this approach, called the "smooth boundary continuum model" (SBCM), as compared to the PCM procedure, and suggest primary tentative results of its parametrization for different solvents. The calculation for the case of a binary solvent mixture with variable epsilon in the solvent space region demonstrates the applicability of this approach to a novel application field covered by the SBCM.
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.
Quark-jet model for transverse momentum dependent fragmentation functions
NASA Astrophysics Data System (ADS)
Bentz, W.; Kotzinian, A.; Matevosyan, H. H.; Ninomiya, Y.; Thomas, A. W.; Yazaki, K.
2016-08-01
In order to describe the hadronization of polarized quarks, we discuss an extension of the quark-jet model to transverse momentum dependent fragmentation functions. The description is based on a product ansatz, where each factor in the product represents one of the transverse momentum dependent splitting functions, which can be calculated by using effective quark theories. The resulting integral equations and sum rules are discussed in detail for the case of inclusive pion production. In particular, we demonstrate that the three-dimensional momentum sum rules are satisfied naturally in this transverse momentum dependent quark-jet model. Our results are well suited for numerical calculations in effective quark theories and can be implemented in Monte Carlo simulations of polarized quark hadronization processes.
Electrostatics of a simple membrane model using Green's functions formalism.
von Kitzing, E; Soumpasis, D M
1996-01-01
The electrostatics of a simple membrane model picturing a lipid bilayer as a low dielectric constant slab immersed in a homogeneous medium of high dielectric constant (water) can be accurately computed using the exact Green's functions obtainable for this geometry. We present an extensive discussion of the analysis and numerical aspects of the problem and apply the formalism and algorithms developed to the computation of the energy profiles of a test charge (e.g., ion) across the bilayer and a molecular model of the acetylcholine receptor channel embedded in it. The Green's function approach is a very convenient tool for the computer simulation of ionic transport across membrane channels and other membrane problems where a good and computationally efficient first-order treatment of dielectric polarization effects is crucial. PMID:8842218
Caenorhabditis elegans as a model organism to study APP function
Ewald, Collin Y.; Li, Chris
2013-01-01
The brains of Alzheimer's disease patients show an increased number of senile plaques compared with normal patients. The major component of the plaques is the β-amyloid peptide, a cleavage product of the amyloid precursor protein (APP). Although the processing of APP has been well-described, the physiological functions of APP and its cleavage products remain unclear. This article reviews the multifunctional roles of an APP orthologue, the C. elegans APL-1. Understanding the function of APL-1 may provide insights into the functions and signaling pathways of human APP. In addition, the physiological effects of introducing human β-amyloid peptide into C. elegans are also reviewed. The C. elegans system provides a powerful genetic model to identify genes regulating the molecular mechanisms underlying intracellular β-amyloid peptide accumulation. PMID:22038715
Longitudinal functional magnetic resonance imaging in animal models.
Silva, Afonso C; Liu, Junjie V; Hirano, Yoshiyuki; Leoni, Renata F; Merkle, Hellmut; Mackel, Julie B; Zhang, Xian Feng; Nascimento, George C; Stefanovic, Bojana
2011-01-01
Functional magnetic resonance imaging (fMRI) has had an essential role in furthering our understanding of brain physiology and function. fMRI techniques are nowadays widely applied in neuroscience research, as well as in translational and clinical studies. The use of animal models in fMRI studies has been fundamental in helping elucidate the mechanisms of cerebral blood-flow regulation, and in the exploration of basic neuroscience questions, such as the mechanisms of perception, behavior, and cognition. Because animals are inherently non-compliant, most fMRI performed to date have required the use of anesthesia, which interferes with brain function and compromises interpretability and applicability of results to our understanding of human brain function. An alternative approach that eliminates the need for anesthesia involves training the animal to tolerate physical restraint during the data acquisition. In the present chapter, we review these two different approaches to obtaining fMRI data from animal models, with a specific focus on the acquisition of longitudinal data from the same subjects.
Calibration of two complex ecosystem models with different likelihood functions
NASA Astrophysics Data System (ADS)
Hidy, Dóra; Haszpra, László; Pintér, Krisztina; Nagy, Zoltán; Barcza, Zoltán
2014-05-01
The biosphere is a sensitive carbon reservoir. Terrestrial ecosystems were approximately carbon neutral during the past centuries, but they became net carbon sinks due to climate change induced environmental change and associated CO2 fertilization effect of the atmosphere. Model studies and measurements indicate that the biospheric carbon sink can saturate in the future due to ongoing climate change which can act as a positive feedback. Robustness of carbon cycle models is a key issue when trying to choose the appropriate model for decision support. The input parameters of the process-based models are decisive regarding the model output. At the same time there are several input parameters for which accurate values are hard to obtain directly from experiments or no local measurements are available. Due to the uncertainty associated with the unknown model parameters significant bias can be experienced if the model is used to simulate the carbon and nitrogen cycle components of different ecosystems. In order to improve model performance the unknown model parameters has to be estimated. We developed a multi-objective, two-step calibration method based on Bayesian approach in order to estimate the unknown parameters of PaSim and Biome-BGC models. Biome-BGC and PaSim are a widely used biogeochemical models that simulate the storage and flux of water, carbon, and nitrogen between the ecosystem and the atmosphere, and within the components of the terrestrial ecosystems (in this research the developed version of Biome-BGC is used which is referred as BBGC MuSo). Both models were calibrated regardless the simulated processes and type of model parameters. The calibration procedure is based on the comparison of measured data with simulated results via calculating a likelihood function (degree of goodness-of-fit between simulated and measured data). In our research different likelihood function formulations were used in order to examine the effect of the different model
Simple and complex models for studying muscle function in walking.
Pandy, Marcus G
2003-09-29
While simple models can be helpful in identifying basic features of muscle function, more complex models are needed to discern the functional roles of specific muscles in movement. In this paper, two very different models of walking, one simple and one complex, are used to study how muscle forces, gravitational forces and centrifugal forces (i.e. forces arising from motion of the joints) combine to produce the pattern of force exerted on the ground. Both the simple model and the complex one predict that muscles contribute significantly to the ground force pattern generated in walking; indeed, both models show that muscle action is responsible for the appearance of the two peaks in the vertical force. The simple model, an inverted double pendulum, suggests further that the first and second peaks are due to net extensor muscle moments exerted about the knee and ankle, respectively. Analyses based on a much more complex, muscle-actuated simulation of walking are in general agreement with these results; however, the more detailed model also reveals that both the hip extensor and hip abductor muscles contribute significantly to vertical motion of the centre of mass, and therefore to the appearance of the first peak in the vertical ground force, in early single-leg stance. This discrepancy in the model predictions is most probably explained by the difference in model complexity. First, movements of the upper body in the sagittal plane are not represented properly in the double-pendulum model, which may explain the anomalous result obtained for the contribution of a hip-extensor torque to the vertical ground force. Second, the double-pendulum model incorporates only three of the six major elements of walking, whereas the complex model is fully 3D and incorporates all six gait determinants. In particular, pelvic list occurs primarily in the frontal plane, so there is the potential for this mechanism to contribute significantly to the vertical ground force, especially
Simple and complex models for studying muscle function in walking.
Pandy, Marcus G
2003-01-01
While simple models can be helpful in identifying basic features of muscle function, more complex models are needed to discern the functional roles of specific muscles in movement. In this paper, two very different models of walking, one simple and one complex, are used to study how muscle forces, gravitational forces and centrifugal forces (i.e. forces arising from motion of the joints) combine to produce the pattern of force exerted on the ground. Both the simple model and the complex one predict that muscles contribute significantly to the ground force pattern generated in walking; indeed, both models show that muscle action is responsible for the appearance of the two peaks in the vertical force. The simple model, an inverted double pendulum, suggests further that the first and second peaks are due to net extensor muscle moments exerted about the knee and ankle, respectively. Analyses based on a much more complex, muscle-actuated simulation of walking are in general agreement with these results; however, the more detailed model also reveals that both the hip extensor and hip abductor muscles contribute significantly to vertical motion of the centre of mass, and therefore to the appearance of the first peak in the vertical ground force, in early single-leg stance. This discrepancy in the model predictions is most probably explained by the difference in model complexity. First, movements of the upper body in the sagittal plane are not represented properly in the double-pendulum model, which may explain the anomalous result obtained for the contribution of a hip-extensor torque to the vertical ground force. Second, the double-pendulum model incorporates only three of the six major elements of walking, whereas the complex model is fully 3D and incorporates all six gait determinants. In particular, pelvic list occurs primarily in the frontal plane, so there is the potential for this mechanism to contribute significantly to the vertical ground force, especially
A displaced-solvent functional analysis of model hydrophobic enclosures
Abel, Robert; Wang, Lingle; Friesner, Richard A.; Berne, B. J.
2010-01-01
Calculation of protein-ligand binding affinities continues to be a hotbed of research. Although many techniques for computing protein-ligand binding affinities have been introduced--ranging from computationally very expensive approaches, such as free energy perturbation (FEP) theory; to more approximate techniques, such as empirically derived scoring functions, which, although computationally efficient, lack a clear theoretical basis--there remains pressing need for more robust approaches. A recently introduced technique, the displaced-solvent functional (DSF) method, was developed to bridge the gap between the high accuracy of FEP and the computational efficiency of empirically derived scoring functions. In order to develop a set of reference data to test the DSF theory for calculating absolute protein-ligand binding affinities, we have pursued FEP theory calculations of the binding free energies of a methane ligand with 13 different model hydrophobic enclosures of varying hydrophobicity. The binding free energies of the methane ligand with the various hydrophobic enclosures were then recomputed by DSF theory and compared with the FEP reference data. We find that the DSF theory, which relies on no empirically tuned parameters, shows excellent quantitative agreement with the FEP. We also explored the ability of buried solvent accessible surface area and buried molecular surface area models to describe the relevant physics, and find the buried molecular surface area model to offer superior performance over this dataset. PMID:21135914
Di Maggio, Jimena; Fernández, Carolina; Parodi, Elisa R; Diaz, M Soledad; Estrada, Vanina
2016-01-01
In this paper we address the formulation of two mechanistic water quality models that differ in the way the phytoplankton community is described. We carry out parameter estimation subject to differential-algebraic constraints and validation for each model and comparison between models performance. The first approach aggregates phytoplankton species based on their phylogenetic characteristics (Taxonomic group model) and the second one, on their morpho-functional properties following Reynolds' classification (Functional group model). The latter approach takes into account tolerance and sensitivity to environmental conditions. The constrained parameter estimation problems are formulated within an equation oriented framework, with a maximum likelihood objective function. The study site is Paso de las Piedras Reservoir (Argentina), which supplies water for consumption for 450,000 population. Numerical results show that phytoplankton morpho-functional groups more closely represent each species growth requirements within the group. Each model performance is quantitatively assessed by three diagnostic measures. Parameter estimation results for seasonal dynamics of the phytoplankton community and main biogeochemical variables for a one-year time horizon are presented and compared for both models, showing the functional group model enhanced performance. Finally, we explore increasing nutrient loading scenarios and predict their effect on phytoplankton dynamics throughout a one-year time horizon.
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.
Linking geophysics and soil function modelling - biomass production
NASA Astrophysics Data System (ADS)
Krüger, J.; Franko, U.; Werban, U.; Fank, J.
2012-04-01
The iSOIL project aims at reliable mapping of soil properties and soil functions with various methods including geophysical, spectroscopic and monitoring techniques. The general procedure contains three steps (i) geophysical monitoring, (ii) generation of soil property maps and (iii) process modelling. The objective of this work is to demonstrate the mentioned procedure with a focus on process modelling. It deals with the dynamics of soil water and the direct influence on crop biomass production. The new module PLUS extends CANDY to simulate crop biomass production based on environmental influences. A soil function modelling with an adapted model parameterisation based on data of ground penetration radar (GPR) and conductivity (EM38) was realized. This study shows an approach to handle heterogeneity of soil properties with geophysical data used for biomass production modelling. The Austrian field site Wagna is characterised by highly heterogenic soil with fluvioglacial gravel sediments. The variation of thickness of topsoil above a sandy subsoil with gravels strongly influences the soil water balance. EM38, mounted on a mobile platform, enables to rapidly scan large areas whereas GPR requires a greater logistical effort. However, GPR can detect exact soil horizon depth between topsoil and subsoil, the combination of both results in a detailed large scale soil map. The combined plot-specific GPR and field site EM38 measurements extends the soil input data and improves the model performance of CANDY PLUS for plant biomass production (Krüger et al. 2011). The example demonstrates how geophysics provides a surplus of data for agroecosystem modelling which identifies and contributes alternative options for agricultural management decisions. iSOIL - "Interactions between soil related sciences - Linking geophysics, soil science and digital soil mapping" is a Collaborative Project (Grant Agreement number 211386) co-funded by the Research DG of the European Commission
Multiscale Modeling of Functionalized Nanocarriers in Targeted Drug Delivery
Liu, Jin; Bradley, Ryan; Eckmann, David M.; Ayyaswamy, Portonovo S.; Radhakrishnan, Ravi
2011-01-01
Targeted drug delivery using functionalized nanocarriers (NCs) is a strategy in therapeutic and diagnostic applications. In this paper we review the recent development of models at multiple length and time scales and their applications to targeting of antibody functionalized nanocarriers to antigens (receptors) on the endothelial cell (EC) surface. Our mesoscale (100 nm-1 μm) model is based on phenomenological interaction potentials for receptor-ligand interactions, receptor-flexure and resistance offered by glycocalyx. All free parameters are either directly determined from independent biophysical and cell biology experiments or estimated using molecular dynamics simulations. We employ a Metropolis Monte Carlo (MC) strategy in conjunction with the weighted histogram analysis method (WHAM) to compute the free energy landscape (potential of mean force or PMF) associated with the multivalent antigen-antibody interactions mediating the NC binding to EC. The binding affinities (association constants) are then derived from the PMF by computing absolute binding free energy of binding of NC to EC, taking into account the relevant translational and rotational entropy losses of NC and the receptors. We validate our model predictions by comparing the computed binding affinities and PMF to a wide range of experimental measurements, including in vitro cell culture, in vivo endothelial targeting, atomic force microscopy (AFM), and flow chamber experiments. The model predictions agree closely and quantitatively with all types experimental measurements. On this basis, we conclude that our computational protocol represents a quantitative and predictive approach for model driven design and optimization of functionalized NCs in targeted vascular drug delivery. PMID:22116782
Adaptive filters and internal models: multilevel description of cerebellar function.
Porrill, John; Dean, Paul; Anderson, Sean R
2013-11-01
Cerebellar function is increasingly discussed in terms of engineering schemes for motor control and signal processing that involve internal models. To address the relation between the cerebellum and internal models, we adopt the chip metaphor that has been used to represent the combination of a homogeneous cerebellar cortical microcircuit with individual microzones having unique external connections. This metaphor indicates that identifying the function of a particular cerebellar chip requires knowledge of both the general microcircuit algorithm and the chip's individual connections. Here we use a popular candidate algorithm as embodied in the adaptive filter, which learns to decorrelate its inputs from a reference ('teaching', 'error') signal. This algorithm is computationally powerful enough to be used in a very wide variety of engineering applications. However, the crucial issue is whether the external connectivity required by such applications can be implemented biologically. We argue that some applications appear to be in principle biologically implausible: these include the Smith predictor and Kalman filter (for state estimation), and the feedback-error-learning scheme for adaptive inverse control. However, even for plausible schemes, such as forward models for noise cancellation and novelty-detection, and the recurrent architecture for adaptive inverse control, there is unlikely to be a simple mapping between microzone function and internal model structure. This initial analysis suggests that cerebellar involvement in particular behaviours is therefore unlikely to have a neat classification into categories such as 'forward model'. It is more likely that cerebellar microzones learn a task-specific adaptive-filter operation which combines a number of signal-processing roles.
Plant Lessons: Exploring ABCB Functionality Through Structural Modeling
Bailly, Aurélien; Yang, Haibing; Martinoia, Enrico; Geisler, Markus; Murphy, Angus S.
2012-01-01
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. PMID:22639627
Electrophysiological Modeling of Cardiac Ventricular Function: From Cell to Organ
Winslow, R. L.; Scollan, D. F.; Holmes, A.; Yung, C. K.; Zhang, J.; Jafri, M. S.
2005-01-01
Three topics of importance to modeling the integrative function of the heart are reviewed. The first is modeling of the ventricular myocyte. Emphasis is placed on excitation-contraction coupling and intracellular Ca2+ handling, and the interpretation of experimental data regarding interval-force relationships. Second, data on use of diffusion tensor magnetic resonance (DTMR) imaging for measuring the anatomical structure of the cardiac ventricles are presented. A method for the semi-automated reconstruction of the ventricles using a combination of gradient recalled acquisition in the steady state (GRASS) and DTMR images is described. Third, we describe how these anatomically and biophysically based models of the cardiac ventricles can be implemented on parallel computers. PMID:11701509
A model of impairment and functional limitation in rheumatoid arthritis
Escalante, Agustín; Haas, Roy W; del Rincón, Inmaculada
2005-01-01
Background We have previously proposed a theoretical model for studying physical disability and other outcomes in rheumatoid arthritis (RA). The purpose of this paper is to test a model of impairment and functional limitation in (RA), using empirical data from a sample of RA patients. We based the model on the disablement process framework. Methods We posited two distinct types of impairment in RA: 1) Joint inflammation, measured by the tender, painful and swollen joint counts; and 2) Joint deformity, measured by the deformed joint count. We hypothesized direct paths from the two impairments to functional limitation, measured by the shirt-button speed, grip strength and walking velocity. We used structural equation modeling to test the hypothetical relationships, using empirical data from a sample of RA patients recruited from six rheumatology clinics. Results The RA sample was comprised of 779 RA patients. In the structural equation model, the joint inflammation impairment displayed a strong significant path toward the measured variables of joint pain, tenderness and swelling (standardized regression coefficients 0.758, 0.872 and 0.512, P ≤ 0.001 for each). The joint deformity impairment likewise displayed significant paths toward the measured upper limb, lower limb, and other deformed joint counts (standardized regression coefficients 0.849, 0.785, 0.308, P ≤ 0.001 for each). Both the joint inflammation and joint deformity impairments displayed strong direct paths toward functional limitation (standardized regression coefficients of -0.576 and -0.564, respectively, P ≤ 0.001 for each), and explained 65% of its variance. Model fit to data was fair to good, as evidenced by a comparative fit index of 0.975, and the root mean square error of approximation = 0.058. Conclusion This evidence supports the occurrence of two distinct impairments in RA, joint inflammation and joint deformity, that together, contribute strongly to functional limitations in this disease
ERS-1 modulation transfer function impact on shoreline change model
NASA Astrophysics Data System (ADS)
Marghany, Maged
2003-11-01
The impact of wave spectra modulation transfer function (MTF) in shoreline change model accuracy has been presented. The MTF consisted of real aperture radar (RAR) and velocity-bunching which is utilized to map the wave spectra observed from ERS-1 into the observed real ocean wave spectra. Based on this information, the shoreline change model have developed. Two hypotheses were concerned with the shoreline change model based on ERS-1 wave spectra. First, there is a significant difference between RAR and velocity-bunching modulations for ERS-1 wave spectra modeling. Second, this significant difference is induced a different spatial variation for shoreline change pattern. This study shows that there was the significant difference between velocity-bunching and quasi-linear models. The study shows that velocity-bunching model produces wave spectra pattern approximately close to the real ocean wave compared to the quasi-linear model. The error percentage occurred with velocity-bunching and quasi-linear models were 33.5 and 46.7%, respectively. The highest rate of erosion occurred to the shore south of Chendering with -5 m per year and the highest rate of sedimentation occurred to north of Chendering headland with 3 m per year. It can be concluded that ERS-1 data could be used to model shoreline change and identify the locations of erosion and sedimentation. The sedimentation was occurred due to the effect of lowest wave spectra energy captured along the range direction while the erosion was occurred due to highest spectra energy captured near azimuth direction.
Functional GI disorders: from animal models to drug development
Mayer, E A; Bradesi, S; Chang, L; Spiegel, B M R; Bueller, J A; Naliboff, B D
2014-01-01
Despite considerable efforts by academic researchers and by the pharmaceutical industry, the development of novel pharmacological treatments for irritable bowel syndrome (IBS) and other functional gastrointestinal (GI) disorders has been slow and disappointing. The traditional approach to identifying and evaluating novel drugs for these symptom-based syndromes has relied on a fairly standard algorithm using animal models, experimental medicine models and clinical trials. In the current article, the empirical basis for this process is reviewed, focusing on the utility of the assessment of visceral hypersensitivity and GI transit, in both animals and humans, as well as the predictive validity of preclinical and clinical models of IBS for identifying successful treatments for IBS symptoms and IBS-related quality of life impairment. A review of published evidence suggests that abdominal pain, defecation-related symptoms (urgency, straining) and psychological factors all contribute to overall symptom severity and to health-related quality of life. Correlations between readouts obtained in preclinical and clinical models and respective symptoms are small, and the ability to predict drug effectiveness for specific as well as for global IBS symptoms is limited. One possible drug development algorithm is proposed which focuses on pharmacological imaging approaches in both preclinical and clinical models, with decreased emphasis on evaluating compounds in symptom-related animal models, and more rapid screening of promising candidate compounds in man. PMID:17965064
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.
Holonomy spin foam models: asymptotic geometry of the partition function
NASA Astrophysics Data System (ADS)
Hellmann, Frank; Kaminski, Wojciech
2013-10-01
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 innovation that enables these results is the introduction of the notion of wave front sets, and the adaptation of tools for their study from micro local analysis to the case of spin foam partition functions.
A Model of School Counseling Supervision: The Goals, Functions, Roles, and Systems Model
ERIC Educational Resources Information Center
Wood, Chris; Rayle, Andrea Dixon
2006-01-01
The authors outline the Goals, Functions, Roles, and Systems Model (GFRS), a school counseling-specific model for supervising school counselors-in-training (SCITs). The GFRS was created as a guide for assisting in supervising and preparing SCITs for the multifaceted tasks they will undertake in their internships and careers. The components of this…
Resonating valence bond wave functions and classical interacting dimer models.
Damle, Kedar; Dhar, Deepak; Ramola, Kabir
2012-06-15
We relate properties of nearest-neighbor resonating valence-bond (NNRVB) wave functions for SU(g) spin systems on two-dimensional bipartite lattices to those of fully packed interacting classical dimer models on the same lattice. The interaction energy can be expressed as a sum of n-body potentials V(n), which are recursively determined from the NNRVB wave function on finite subgraphs of the original lattice. The magnitude of the n-body interaction V(n) (n>1) is of order O(g(-(n-1))) for small g(-1). The leading term is a two-body nearest-neighbor interaction V2(g) favoring two parallel dimers on elementary plaquettes. For SU(2) spins, using our calculated value of V2(g=2), we find that the long-distance behavior of the bond-energy correlation function is dominated by an oscillatory term that decays as 1/|r|α with α≈1.22. This result is in remarkable quantitative agreement with earlier direct numerical studies of the corresponding wave function, which give α≈1.20. PMID:23004328
AgBase: supporting functional modeling in agricultural organisms
McCarthy, Fiona M.; Gresham, Cathy R.; Buza, Teresia J.; Chouvarine, Philippe; Pillai, Lakshmi R.; Kumar, Ranjit; Ozkan, Seval; Wang, Hui; Manda, Prashanti; Arick, Tony; Bridges, Susan M.; Burgess, Shane C.
2011-01-01
AgBase (http://www.agbase.msstate.edu/) provides resources to facilitate modeling of functional genomics data and structural and functional annotation of agriculturally important animal, plant, microbe and parasite genomes. The website is redesigned to improve accessibility and ease of use, including improved search capabilities. Expanded capabilities include new dedicated pages for horse, cat, dog, cotton, rice and soybean. We currently provide 590 240 Gene Ontology (GO) annotations to 105 454 gene products in 64 different species, including GO annotations linked to transcripts represented on agricultural microarrays. For many of these arrays, this provides the only functional annotation available. GO annotations are available for download and we provide comprehensive, species-specific GO annotation files for 18 different organisms. The tools available at AgBase have been expanded and several existing tools improved based upon user feedback. One of seven new tools available at AgBase, GOModeler, supports hypothesis testing from functional genomics data. We host several associated databases and provide genome browsers for three agricultural pathogens. Moreover, we provide comprehensive training resources (including worked examples and tutorials) via links to Educational Resources at the AgBase website. PMID:21075795
Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.
Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao
2016-04-01
To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.
Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.
Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao
2016-04-01
To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes. PMID:27104857
Executive function in older adults: a structural equation modeling approach.
Hull, Rachel; Martin, Randi C; Beier, Margaret E; Lane, David; Hamilton, A Cris
2008-07-01
Confirmatory factor analysis (CFA) and structural equation modeling (SEM) were used to study the organization of executive functions in older adults. The four primary goals were to examine (a) whether executive functions were supported by one versus multiple underlying factors, (b) which underlying skill(s) predicted performance on complex executive function tasks, (c) whether performance on analogous verbal and nonverbal tasks was supported by separable underlying skills, and (d) how patterns of performance generally compared with those of young adults. A sample of 100 older adults completed 10 tasks, each designed to engage one of three control processes: mental set shifting (Shifting), information updating or monitoring (Updating), and inhibition of prepotent responses (Inhibition). CFA identified robust Shifting and Updating factors, but the Inhibition factor failed to emerge, and there was no evidence for verbal and nonverbal factors. SEM showed that Updating was the best predictor of performance on each of the complex tasks the authors assessed (the Tower of Hanoi and the Wisconsin Card Sort). Results are discussed in terms of insight for theories of cognitive aging and executive function. PMID:18590362
Gene3D: modelling protein structure, function and evolution.
Yeats, Corin; Maibaum, Michael; Marsden, Russell; Dibley, Mark; Lee, David; Addou, Sarah; Orengo, Christine A
2006-01-01
The Gene3D release 4 database and web portal (http://cathwww.biochem.ucl.ac.uk:8080/Gene3D) provide a combined structural, functional and evolutionary view of the protein world. It is focussed on providing structural annotation for protein sequences without structural representatives--including the complete proteome sets of over 240 different species. The protein sequences have also been clustered into whole-chain families so as to aid functional prediction. The structural annotation is generated using HMM models based on the CATH domain families; CATH is a repository for manually deduced protein domains. Amongst the changes from the last publication are: the addition of over 100 genomes and the UniProt sequence database, domain data from Pfam, metabolic pathway and functional data from COGs, KEGG and GO, and protein-protein interaction data from MINT and BIND. The website has been rebuilt to allow more sophisticated querying and the data returned is presented in a clearer format with greater functionality. Furthermore, all data can be downloaded in a simple XML format, allowing users to carry out complex investigations at their own computers.
Assessing Functional Performance in the Mdx Mouse Model
Aartsma-Rus, Annemieke; van Putten, Maaike
2014-01-01
Duchenne muscular dystrophy (DMD) is a severe and progressive muscle wasting disorder for which no cure is available. Nevertheless, several potential pharmaceutical compounds and gene therapy approaches have progressed into clinical trials. With improvement in muscle function being the most important end point in these trials, a lot of emphasis has been placed on setting up reliable, reproducible, and easy to perform functional tests to pre clinically assess muscle function, strength, condition, and coordination in the mdx mouse model for DMD. Both invasive and noninvasive tests are available. Tests that do not exacerbate the disease can be used to determine the natural history of the disease and the effects of therapeutic interventions (e.g. forelimb grip strength test, two different hanging tests using either a wire or a grid and rotarod running). Alternatively, forced treadmill running can be used to enhance disease progression and/or assess protective effects of therapeutic interventions on disease pathology. We here describe how to perform these most commonly used functional tests in a reliable and reproducible manner. Using these protocols based on standard operating procedures enables comparison of data between different laboratories. PMID:24747372
Dynamic causal modelling for functional near-infrared spectroscopy
Tak, S.; Kempny, A.M.; Friston, K.J.; Leff, A.P.; Penny, W.D.
2015-01-01
Functional near-infrared spectroscopy (fNIRS) is an emerging technique for measuring changes in cerebral hemoglobin concentration via optical absorption changes. Although there is great interest in using fNIRS to study brain connectivity, current methods are unable to infer the directionality of neuronal connections. In this paper, we apply Dynamic Causal Modelling (DCM) to fNIRS data. Specifically, we present a generative model of how observed fNIRS data are caused by interactions among hidden neuronal states. Inversion of this generative model, using an established Bayesian framework (variational Laplace), then enables inference about changes in directed connectivity at the neuronal level. Using experimental data acquired during motor imagery and motor execution tasks, we show that directed (i.e., effective) connectivity from the supplementary motor area to the primary motor cortex is negatively modulated by motor imagery, and this suppressive influence causes reduced activity in the primary motor cortex during motor imagery. These results are consistent with findings of previous functional magnetic resonance imaging (fMRI) studies, suggesting that the proposed method enables one to infer directed interactions in the brain mediated by neuronal dynamics from measurements of optical density changes. PMID:25724757
Genetic Models for the Study of Luteinizing Hormone Receptor Function
Narayan, Prema
2015-01-01
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. 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. PMID:26483755
Teleseismic receiver functions modeling of the eastern Indian craton
NASA Astrophysics Data System (ADS)
Mandal, Prantik; Biswas, Koushik
2016-09-01
We estimate receiver functions (RFs) through the time-domain deconvolution using three-component broadband data of 100 teleseismic events (30° ⩽ ∧ ⩽ 90°) from 15 seismographs in the eastern Indian craton. Estimated radial RFs show a positive phase at 4.6-5.8 s delay time corresponding to the crustal thicknesses of 37-46 km. Through the differential evolution (DE) waveform inversion modeling of radial receiver functions, we delineate the crustal structure at 15 broadband stations. On an average, the Archean Singhbhum Odisha Craton (SOC) is characterized by a thick crust of 43 ± 3 km in comparison to a relatively thin crust of 41 ± 1 km underlying the Proterozoic Chotanagpur Granite Gneissic terrain (CGGT). While, a thin crust of 38 ± 1 km characterizes the younger Eastern Ghats Mobile Belt (EGMB). The main results of our modeling reveal a 46 km thick Archean crust underlying the Singhbhum granite (SG) of 3.6 Ga, which is characterized by a 3 km crustal thickening probably resulted from the Archean subduction process. Our modeling also detects a 2-3 km crustal thinning with the thinnest crust of 37 km below the region near South Singhbhum Shear Zone, which could be attributed to the 1.6 Ga plume activity associated with Dalma volcanic. Our modeling also led to the delineation of a crustal thinning of 2-3 km underlying the region in EGMB, which was influenced by a much younger (∼117 Ma) Rajmahal magmatism associated with the Gondwana break-up episode. However, our study could not detect any age-dependent variation of crustal thicknesses in the eastern Indian craton. The main result of our modeling suggests a two-phase crustal evolution process for the SOC viz. older E-W crustal thickening due to E-W plate compression and later crustal thinning episodes associated with the Dalma volcanism in the north and the Rajmahal volcanism in the South.
Defining Predictive Probability Functions for Species Sampling Models
Lee, Jaeyong; Quintana, Fernando A.; Müller, Peter; Trippa, Lorenzo
2013-01-01
We review the class of species sampling models (SSM). In particular, we investigate the relation between the exchangeable partition probability function (EPPF) and the predictive probability function (PPF). It is straightforward to define a PPF from an EPPF, but the converse is not necessarily true. In this paper we introduce the notion of putative PPFs and show novel conditions for a putative PPF to define an EPPF. We show that all possible PPFs in a certain class have to define (unnormalized) probabilities for cluster membership that are linear in cluster size. We give a new necessary and sufficient condition for arbitrary putative PPFs to define an EPPF. Finally, we show posterior inference for a large class of SSMs with a PPF that is not linear in cluster size and discuss a numerical method to derive its PPF. PMID:24368874
β-deformed matrix model and Nekrasov partition function
NASA Astrophysics Data System (ADS)
Nishinaka, Takahiro; Rim, Chaiho
2012-02-01
We study Penner type matrix models in relation with the Nekrasov partition function of four dimensional mathcal{N} = {2} , SU(2) supersymmetric gauge theories with N F = 2 , 3 and 4. By evaluating the resolvent using the loop equation for general β, we explicitly construct the first half-genus correction to the free energy and demonstrate the result coincides with the corresponding Nekrasov partition function with general Ω-background, including higher instanton contributions after modifying the relation of the Coulomb branch parameter with the filling fraction. Our approach complements the proof using the Selberg integrals directly which is useful to find the contribution in the series of instanton numbers for a given deformation parameter.
a Global Model for Long-Range Interaction `DAMPING Functions'
NASA Astrophysics Data System (ADS)
Myatt, Philip Thomas; McCourt, Frederick R. W.; Le Roy, Robert J.
2016-06-01
In recent years, `damping functions', which characterize the weakening of inverse-power-sum long-range interatomic interaction energies with increasing electron overlap, have become an increasing important component of models for diatomic molecule interaction potentials. However, a key feature of models for damping functions, their portability, has received little scrutiny. The present work set out to examine all available ab initio induction and dispersion damping function data and to attempt to devise a `global' scheme for diatomic molecule damping functions. It appears that while neutral (H, He, Li, and Ne, homonuclear and mixed) and anion (H^- with H, He and Li) species obey (approximately) one common rule, proton plus neutral (H^+ with H, He and Li) and non-proton-cation plus neutral systems (He^+ and Li^+ with H, He and Li), must each be treated separately. However, for all three cases, a version of the Douketis-Scoles-Thakkar (ionization potential)power factor is a key scaling parameter. R.J. Le Roy, C. C. Haugen, J. Tao and Hui Li, Mol. Phys. 109,435 (2011). P.J. Knowles and W.J. Meath,J. Mol. Phys. 60, 1143 (1987); R.J. Wheatley and W.J. Meath,J. Mol. Phys. 80, 25 (1993); R.J. Wheatley and W.J. Meath J. Chem. Phys. 179, 341 (1994); R.J. Wheatley and W.J. Meath,J. Chem. Phys. 203, 209 (1996). C. Douketis,G. Scoles, S. Marchetti, M. Zen and A. J. Thakkar, J. Chem. Phys. 76, 3057 (1982).
Modeling the biomechanics of articular eminence function in anthropoid primates
Terhune, Claire E
2011-01-01
One of the most prominent features of the cranial component of the temporomandibular joint (TMJ) is the articular eminence (AE). This bar of bone is the primary surface upon which the condyle translates and rotates during movements of the mandible, and is therefore the primary point at which forces are transmitted from the mandible to the cranium during loading of the masticatory apparatus. The shape of the AE is highly variable across primates, and the raised eminence of humans has often been considered a defining feature of the human TMJ, yet few data exist to address whether this variation is functionally significant. This study used a broad interspecific sample of anthropoid primates to elaborate upon and test the predictions of a previously proposed model of AE function. This model suggests that AE inclination acts to resist non-normal forces at the TMJ, thereby maximizing bite forces (BFs). AE inclination was predicted to covary with two specific features of the masticatory apparatus: height of the TMJ above the occlusal plane; and inclination of the masticatory muscles. A correlate of this model is that taxa utilizing more resistant food objects should also exhibit relatively more inclined AEs. Results of the correlation analyses found that AE inclination is strongly correlated with height of the TMJ above the occlusal plane, but less so with inclination of the masticatory muscles. Furthermore, pairwise comparisons of closely related taxa with documented dietary differences found that the AE is consistently more inclined in taxa that utilize more resistant food items. These data preliminarily suggest that variation in AE morphology across anthropoid primates is functionally related to maximizing BFs, and add to the growing dataset of masticatory morphologies linked to feeding behavior. PMID:21923720
Effects of exercise on brain functions in diabetic animal models
Yi, Sun Shin
2015-01-01
Human life span has dramatically increased over several decades, and the quality of life has been considered to be equally important. However, diabetes mellitus (DM) characterized by problems related to insulin secretion and recognition has become a serious health problem in recent years that threatens human health by causing decline in brain functions and finally leading to neurodegenerative diseases. Exercise is recognized as an effective therapy for DM without medication administration. Exercise studies using experimental animals are a suitable option to overcome this drawback, and animal studies have improved continuously according to the needs of the experimenters. Since brain health is the most significant factor in human life, it is very important to assess brain functions according to the different exercise conditions using experimental animal models. Generally, there are two types of DM; insulin-dependent type 1 DM and an insulin-independent type 2 DM (T2DM); however, the author will mostly discuss brain functions in T2DM animal models in this review. Additionally, many physiopathologic alterations are caused in the brain by DM such as increased adiposity, inflammation, hormonal dysregulation, uncontrolled hyperphagia, insulin and leptin resistance, and dysregulation of neurotransmitters and declined neurogenesis in the hippocampus and we describe how exercise corrects these alterations in animal models. The results of changes in the brain environment differ according to voluntary, involuntary running exercises and resistance exercise, and gender in the animal studies. These factors have been mentioned in this review, and this review will be a good reference for studying how exercise can be used with therapy for treating DM. PMID:25987956
Modeling the biomechanics of articular eminence function in anthropoid primates.
Terhune, Claire E
2011-11-01
One of the most prominent features of the cranial component of the temporomandibular joint (TMJ) is the articular eminence (AE). This bar of bone is the primary surface upon which the condyle translates and rotates during movements of the mandible, and is therefore the primary point at which forces are transmitted from the mandible to the cranium during loading of the masticatory apparatus. The shape of the AE is highly variable across primates, and the raised eminence of humans has often been considered a defining feature of the human TMJ, yet few data exist to address whether this variation is functionally significant. This study used a broad interspecific sample of anthropoid primates to elaborate upon and test the predictions of a previously proposed model of AE function. This model suggests that AE inclination acts to resist non-normal forces at the TMJ, thereby maximizing bite forces (BFs). AE inclination was predicted to covary with two specific features of the masticatory apparatus: height of the TMJ above the occlusal plane; and inclination of the masticatory muscles. A correlate of this model is that taxa utilizing more resistant food objects should also exhibit relatively more inclined AEs. Results of the correlation analyses found that AE inclination is strongly correlated with height of the TMJ above the occlusal plane, but less so with inclination of the masticatory muscles. Furthermore, pairwise comparisons of closely related taxa with documented dietary differences found that the AE is consistently more inclined in taxa that utilize more resistant food items. These data preliminarily suggest that variation in AE morphology across anthropoid primates is functionally related to maximizing BFs, and add to the growing dataset of masticatory morphologies linked to feeding behavior.
Effects of exercise on brain functions in diabetic animal models.
Yi, Sun Shin
2015-05-15
Human life span has dramatically increased over several decades, and the quality of life has been considered to be equally important. However, diabetes mellitus (DM) characterized by problems related to insulin secretion and recognition has become a serious health problem in recent years that threatens human health by causing decline in brain functions and finally leading to neurodegenerative diseases. Exercise is recognized as an effective therapy for DM without medication administration. Exercise studies using experimental animals are a suitable option to overcome this drawback, and animal studies have improved continuously according to the needs of the experimenters. Since brain health is the most significant factor in human life, it is very important to assess brain functions according to the different exercise conditions using experimental animal models. Generally, there are two types of DM; insulin-dependent type 1 DM and an insulin-independent type 2 DM (T2DM); however, the author will mostly discuss brain functions in T2DM animal models in this review. Additionally, many physiopathologic alterations are caused in the brain by DM such as increased adiposity, inflammation, hormonal dysregulation, uncontrolled hyperphagia, insulin and leptin resistance, and dysregulation of neurotransmitters and declined neurogenesis in the hippocampus and we describe how exercise corrects these alterations in animal models. The results of changes in the brain environment differ according to voluntary, involuntary running exercises and resistance exercise, and gender in the animal studies. These factors have been mentioned in this review, and this review will be a good reference for studying how exercise can be used with therapy for treating DM.
Informing soil models using pedotransfer functions: challenges and perspectives
NASA Astrophysics Data System (ADS)
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
Predictions of Geospace Drivers By the Probability Distribution Function Model
NASA Astrophysics Data System (ADS)
Bussy-Virat, C.; Ridley, A. J.
2014-12-01
Geospace drivers like the solar wind speed, interplanetary magnetic field (IMF), and solar irradiance have a strong influence on the density of the thermosphere and the near-Earth space environment. This has important consequences on the drag on satellites that are in low orbit and therefore on their position. One of the basic problems with space weather prediction is that these drivers can only be measured about one hour before they affect the environment. In order to allow for adequate planning for some members of the commercial, military, or civilian communities, reliable long-term space weather forecasts are needed. The study presents a model for predicting geospace drivers up to five days in advance. This model uses the same general technique to predict the solar wind speed, the three components of the IMF, and the solar irradiance F10.7. For instance, it uses Probability distribution functions (PDFs) to relate the current solar wind speed and slope to the future solar wind speed, as well as the solar wind speed to the solar wind speed one solar rotation in the future. The PDF Model has been compared to other models for predictions of the speed. It has been found that it is better than using the current solar wind speed (i.e., persistence), and better than the Wang-Sheeley-Arge Model for prediction horizons of 24 hours. Once the drivers are predicted, and the uncertainty on the drivers are specified, the density in the thermosphere can be derived using various models of the thermosphere, such as the Global Ionosphere Thermosphere Model. In addition, uncertainties on the densities can be estimated, based on ensembles of simulations. From the density and uncertainty predictions, satellite positions, as well as the uncertainty in those positions can be estimated. These can assist operators in determining the probability of collisions between objects in low Earth orbit.
Exact maps in density functional theory for lattice models
NASA Astrophysics Data System (ADS)
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.
Exact maps in density functional theory for lattice models
NASA Astrophysics Data System (ADS)
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.
Models for predicting objective function weights in prostate cancer IMRT
Boutilier, Justin J. Lee, Taewoo; Craig, Tim; Sharpe, Michael B.; Chan, Timothy C. Y.
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.
Engelmann Spruce Site Index Models: A Comparison of Model Functions and Parameterizations
Nigh, Gordon
2015-01-01
Engelmann spruce (Picea engelmannii Parry ex Engelm.) is a high-elevation species found in western Canada and western USA. As this species becomes increasingly targeted for harvesting, better height growth information is required for good management of this species. This project was initiated to fill this need. The objective of the project was threefold: develop a site index model for Engelmann spruce; compare the fits and modelling and application issues between three model formulations and four parameterizations; and more closely examine the grounded-Generalized Algebraic Difference Approach (g-GADA) model parameterization. The model fitting data consisted of 84 stem analyzed Engelmann spruce site trees sampled across the Engelmann Spruce – Subalpine Fir biogeoclimatic zone. The fitted models were based on the Chapman-Richards function, a modified Hossfeld IV function, and the Schumacher function. The model parameterizations that were tested are indicator variables, mixed-effects, GADA, and g-GADA. Model evaluation was based on the finite-sample corrected version of Akaike’s Information Criteria and the estimated variance. Model parameterization had more of an influence on the fit than did model formulation, with the indicator variable method providing the best fit, followed by the mixed-effects modelling (9% increase in the variance for the Chapman-Richards and Schumacher formulations over the indicator variable parameterization), g-GADA (optimal approach) (335% increase in the variance), and the GADA/g-GADA (with the GADA parameterization) (346% increase in the variance). Factors related to the application of the model must be considered when selecting the model for use as the best fitting methods have the most barriers in their application in terms of data and software requirements. PMID:25853472
Constructing biological pathway models with hybrid functional Petri nets.
Doi, Atsushi; Fujita, Sachie; Matsuno, Hiroshi; Nagasaki, Masao; Miyano, Satoru
2004-01-01
In many research projects on modeling and analyzing biological pathways, the Petri net has been recognized as a promising method for representing biological pathways. From the pioneering works by Reddy et al., 1993, and Hofestädt, 1994, that model metabolic pathways by traditional Petri net, several enhanced Petri nets such as colored Petri net, stochastic Petri net, and hybrid Petri net have been used for modeling biological phenomena. Recently, Matsuno et al., 2003b, introduced the hybrid functional Petri net (HFPN) in order to give a more intuitive and natural modeling method for biological pathways than these existing Petri nets. Although the paper demonstrates the effectiveness of HFPN with two examples of gene regulation mechanism for circadian rhythms and apoptosis signaling pathway, there has been no detailed explanation about the method of HFPN construction for these examples. The purpose of this paper is to describe method to construct biological pathways with the HFPN step-by-step. The method is demonstrated by the well-known glycolytic pathway controlled by the lac operon gene regulatory mechanism. PMID:15724280
Modeling functional piezoelectricity in perovskite superlattices with competing instabilities
NASA Astrophysics Data System (ADS)
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
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.
The integrated Earth system model version 1: formulation and functionality
Collins, W. D.; Craig, A. P.; Truesdale, J. E.; Di Vittorio, A. V.; Jones, A. D.; Bond-Lamberty, B.; Calvin, K. V.; Edmonds, J. A.; Kim, S. H.; Thomson, A. M.; et al
2015-07-23
The integrated Earth system model (iESM) has been developed as a new tool for projecting 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 infrastructure. IAMs are the primary tool for describing the human–Earth system, including the sources of global greenhouse gases (GHGs) and short-lived species (SLS), land use and land cover change (LULCC), 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. Themore » iESM project integrates the economic and human-dimension modeling of an IAM and a fully coupled ESM within a single 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 understanding 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 describes the formulation, requirements, implementation, testing, and resulting functionality of the first version of the iESM released to the global climate community.« less
Informing soil models using pedotransfer functions: challenges and perspectives
NASA Astrophysics Data System (ADS)
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
Nonlinear Responses of a Nonlinear Cochlear Model with the Function of AN Outer Hair Cell Model
NASA Astrophysics Data System (ADS)
Murakami, Y.; Unoki, M.
2009-02-01
To investigate how outer hair cells (OHCs) produce compressive nonlinearity in both the cochlear I/O function and tuning curve for a single tone, we present a nonlinear cochlear model with a nonlinear OHC model. In modeling cochlea filtering, we modeled somatic motility as a function of OHCs and the interaction between the basilar membrane and somatic motility through the tectorial membrane as mechanoelectrical transducer networks. The parameter values of the model were set to the estimates for human data. Signal frequencies of 0.125, 0.25, 0.5, 1, 2, 3, 4, and 6 kHz were used in the simulations of cochlear filtering. The results revealed that this model can account for the compressive nonlinearity in both the I/O functions and tuning curves of a cochlea obtained from the experiments. They also suggest that the somatic motility depending on the transducer currents produces nonlinearities in the I/O functions and tuning curves of cochlea.
Modeling the Galaxy Three-Point Correlation Function
Marin, Felipe; Wechsler, Risa; Frieman, Joshua A.; Nichol, Robert; /Portsmouth U., ICG
2007-06-05
We present new theoretical predictions for the galaxy three-point correlation function (3PCF) using high-resolution dissipationless cosmological simulations of a flat Lambda CDM Universe which resolve galaxy-size halos and subhalos. We create realistic mock galaxy catalogs by assigning luminosities and colors to dark matter halos and subhalos, and we measure the reduced 3PCF as a function of luminosity and color in both real and redshift space. As galaxy luminosity and color are varied, we find small differences in the amplitude and shape dependence of the reduced 3PCF, at a level qualitatively consistent with recent measurements from the SDSS and 2dFGRS. We confirm that discrepancies between previous 3PCF measurements can be explained in part by differences in binning choices. We explore the degree to which a simple local bias model can fit the simulated 3PCF. The agreement between the model predictions and galaxy 3PCF measurements lends further credence to the straightforward association of galaxies with CDM halos and subhalos.
Measuring and Modeling the Interactions Between DNA-Functionalized Colloids
NASA Astrophysics Data System (ADS)
Rogers, William; Crocker, John
2011-03-01
DNA hybridization is an ideal tool to direct ``bottom-up'' assembly of complex materials and has been used to form crystalline assemblies of quantum dots, polymer microspheres and other materials made exclusively of DNA. In order to fully realize the potential of DNA-directed self-assembly, one must be able to quantitatively predict the binding energies and interaction potentials between the relevant ``building blocks.'' In this work, we use a scanning-line optical tweezers instrument to measure DNA-induced interactions between colloidal microspheres. We then use well-known concepts in statistical mechanics to model the pair-potentials, whose functional form and energetics of binding are intimately related to the equilibrium configurations of grafted polymers and polymer bridges. By measuring and modeling the pair interaction energies as a function of the essential system parameters (solution hybridization free energies, DNA concentrations, temperature, interparticle separation, etc.), we are able to develop simple, numerical tools that can be used to guide both experiment and simulation.
Longitudinal functional principal component modeling via Stochastic Approximation Monte Carlo
Martinez, Josue G.; Liang, Faming; Zhou, Lan; Carroll, Raymond J.
2010-01-01
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. PMID:20689648
Computer Modeling of the Earliest Cellular Structures and Functions
NASA Technical Reports Server (NTRS)
Pohorille, Andrew; Chipot, Christophe; Schweighofer, Karl
2000-01-01
In the absence of extinct or extant record of protocells (the earliest ancestors of contemporary cells). the most direct way to test our understanding of the origin of cellular life is to construct laboratory models of protocells. Such efforts are currently underway in the NASA Astrobiology Program. They are accompanied by computational studies aimed at explaining self-organization of simple molecules into ordered structures and developing designs for molecules that perform proto-cellular functions. Many of these functions, such as import of nutrients, capture and storage of energy. and response to changes in the environment are carried out by proteins bound to membrane< We will discuss a series of large-scale, molecular-level computer simulations which demonstrate (a) how small proteins (peptides) organize themselves into ordered structures at water-membrane interfaces and insert into membranes, (b) how these peptides aggregate to form membrane-spanning structures (eg. channels), and (c) by what mechanisms such aggregates perform essential proto-cellular functions, such as proton transport of protons across cell walls, a key step in cellular bioenergetics. The simulations were performed using the molecular dynamics method, in which Newton's equations of motion for each item in the system are solved iteratively. The problems of interest required simulations on multi-nanosecond time scales, which corresponded to 10(exp 6)-10(exp 8) time steps.
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.
Nelson, Celeste M.; Bissell, Mina J.
2010-01-01
In order to understand why cancer develops as well as predict the outcome of pharmacological treatments, we need to model the structure and function of organs in culture so that our experimental manipulations occur under physiological contexts. This review traces the history of the development of a prototypic example, the three-dimensional (3D) model of the mammary gland acinus. We briefly describe the considerable information available on both normal mammary gland function and breast cancer generated by the current model and present future challenges that will require an increase in its complexity. We propose the need for engineered tissues that faithfully recapitulate their native structures to allow a greater understanding of tissue function, dysfunction, and potential therapeutic intervention. PMID:15963732
Geometric and electrostatic modeling using molecular rigidity functions
Mu, Lin; Xia, Kelin; Wei, Guowei
2017-03-01
Geometric and electrostatic modeling is an essential component in computational biophysics and molecular biology. Commonly used geometric representations admit geometric singularities such as cusps, tips and self-intersecting facets that lead to computational instabilities in the molecular modeling. Our present work explores the use of flexibility and rigidity index (FRI), which has a proved superiority in protein B-factor prediction, for biomolecular geometric representation and associated electrostatic analysis. FRI rigidity surfaces are free of geometric singularities. We propose a rigidity based Poisson–Boltzmann equation for biomolecular electrostatic analysis. These approaches to surface and electrostatic modeling are validated by a set of 21 proteins.more » Our results are compared with those of established methods. Finally, being smooth and analytically differentiable, FRI rigidity functions offer excellent curvature analysis, which characterizes concave and convex regions on protein surfaces. Polarized curvatures constructed by using the product of minimum curvature and electrostatic potential is shown to predict potential protein–ligand binding sites.« less
Mouse ataxin-3 functional knock-out model.
Switonski, Pawel M; Fiszer, Agnieszka; Kazmierska, Katarzyna; Kurpisz, Maciej; Krzyzosiak, Wlodzimierz J; Figiel, Maciej
2011-03-01
Spinocerebellar ataxia 3 (SCA3) is a genetic disorder resulting from the expansion of the CAG repeats in the ATXN3 gene. The pathogenesis of SCA3 is based on the toxic function of the mutant ataxin-3 protein, but the exact mechanism of the disease remains elusive. Various types of transgenic mouse models explore different aspects of SCA3 pathogenesis, but a knock-in humanized mouse has not yet been created. The initial aim of this study was to generate an ataxin-3 humanized mouse model using a knock-in strategy. The human cDNA for ataxin-3 containing 69 CAG repeats was cloned from SCA3 patient and introduced into the mouse ataxin-3 locus at exon 2, deleting it along with exon 3 and intron 2. Although the human transgene was inserted correctly, the resulting mice acquired the knock-out properties and did not express ataxin-3 protein in any analyzed tissues, as confirmed by western blot and immunohistochemistry. Analyses of RNA expression revealed that the entire locus consisting of human and mouse exons was expressed and alternatively spliced. We detected mRNA isoforms composed of exon 1 spliced with mouse exon 4 or with human exon 7. After applying 37 PCR cycles, we also detected a very low level of the correct exon 1/exon 2 isoform. Additionally, we confirmed by bioinformatic analysis that the structure and power of the splicing site between mouse intron 1 and human exon 2 (the targeted locus) was not changed compared with the native mouse locus. We hypothesized that these splicing aberrations result from the deletion of further splicing sites and the presence of a strong splicing site in exon 4, which was confirmed by bioinformatic analysis. In summary, we created a functional ataxin-3 knock-out mouse model that is viable and fertile and does not present a reduced life span. Our work provides new insights into the splicing characteristics of the Atxn3 gene and provides useful information for future attempts to create knock-in SCA3 models.
Drosophila Cancer Models Identify Functional Differences between Ret Fusions.
Levinson, Sarah; Cagan, Ross L
2016-09-13
We generated and compared Drosophila models of RET fusions CCDC6-RET and NCOA4-RET. Both RET fusions directed cells to migrate, delaminate, and undergo EMT, and both resulted in lethality when broadly expressed. In all phenotypes examined, NCOA4-RET was more severe than CCDC6-RET, mirroring their effects on patients. A functional screen against the Drosophila kinome and a library of cancer drugs found that CCDC6-RET and NCOA4-RET acted through different signaling networks and displayed distinct drug sensitivities. Combining data from the kinome and drug screens identified the WEE1 inhibitor AZD1775 plus the multi-kinase inhibitor sorafenib as a synergistic drug combination that is specific for NCOA4-RET. Our work emphasizes the importance of identifying and tailoring a patient's treatment to their specific RET fusion isoform and identifies a multi-targeted therapy that may prove effective against tumors containing the NCOA4-RET fusion. PMID:27626672
PTEN recruitment controls synaptic and cognitive function in Alzheimer's models.
Knafo, Shira; Sánchez-Puelles, Cristina; Palomer, Ernest; Delgado, Igotz; Draffin, Jonathan E; Mingo, Janire; Wahle, Tina; Kaleka, Kanwardeep; Mou, Liping; Pereda-Perez, Inmaculada; Klosi, Edvin; Faber, Erik B; Chapman, Heidi M; Lozano-Montes, Laura; Ortega-Molina, Ana; Ordóñez-Gutiérrez, Lara; Wandosell, Francisco; Viña, Jose; Dotti, Carlos G; Hall, Randy A; Pulido, Rafael; Gerges, Nashaat Z; Chan, Andrew M; Spaller, Mark R; Serrano, Manuel; Venero, César; Esteban, José A
2016-03-01
Dyshomeostasis of amyloid-β peptide (Aβ) is responsible for synaptic malfunctions leading to cognitive deficits ranging from mild impairment to full-blown dementia in Alzheimer's disease. Aβ appears to skew synaptic plasticity events toward depression. We found that inhibition of PTEN, a lipid phosphatase that is essential to long-term depression, rescued normal synaptic function and cognition in cellular and animal models of Alzheimer's disease. Conversely, transgenic mice that overexpressed PTEN displayed synaptic depression that mimicked and occluded Aβ-induced depression. Mechanistically, Aβ triggers a PDZ-dependent recruitment of PTEN into the postsynaptic compartment. Using a PTEN knock-in mouse lacking the PDZ motif, and a cell-permeable interfering peptide, we found that this mechanism is crucial for Aβ-induced synaptic toxicity and cognitive dysfunction. Our results provide fundamental information on the molecular mechanisms of Aβ-induced synaptic malfunction and may offer new mechanism-based therapeutic targets to counteract downstream Aβ signaling.
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.
Tektin interactions and a model for molecular functions.
Setter, Peter W; Malvey-Dorn, Erika; Steffen, Walter; Stephens, Raymond E; Linck, Richard W
2006-09-10
Tektins from echinoderm flagella were analyzed for microheterogeneity, self-associations and association with tubulin, resulting in a general model of tektin filament structure and function applicable to most eukaryotic cilia and flagella. Using a new antibody to tektin consensus peptide RPNVELCRD, well-characterized chain-specific antibodies and quantitative gel densitometry, tektins A, B and C were found to be present in equimolar amounts in Sarkosyl-urea-stable filaments. In addition, two isoforms of tektin A are present in half-molar ratios to tektins B and C. Cross-linking of AB filaments indicates in situ nearest neighbor associations of tektin A1B and A2B heterodimers, -trimers, -tetramers and higher oligomers. Soluble purified tektin C is cross-linked as homodimers, trimers and tetramers, but not higher oligomers. Tektin filaments associate with both loosely bound and tightly bound tubulin, and with the latter in a 1:1 molar ratio, implying a specific, periodic association of tightly bound tubulin along the tektin axis. Similarly, in tektin-containing Sarkosyl-stable protofilament ribbons, two polypeptides ( approximately 67/73 kDa, homologues of rib72, efhc1 and efhc2) are present in equimolar ratios to each other and to individual tektins, co-fractionating with loosely bound tubulin. These results suggest a super-coiled arrangement of tektin filaments, the organization of which has important implications for the evolution, assembly and functions of cilia and flagella. PMID:16831421
Assessment of Differential Item Functioning under Cognitive Diagnosis Models: The DINA Model Example
ERIC Educational Resources Information Center
Li, Xiaomin; Wang, Wen-Chung
2015-01-01
The assessment of differential item functioning (DIF) is routinely conducted to ensure test fairness and validity. Although many DIF assessment methods have been developed in the context of classical test theory and item response theory, they are not applicable for cognitive diagnosis models (CDMs), as the underlying latent attributes of CDMs are…
Applying the luminosity function statistics in the fireshell model
NASA Astrophysics Data System (ADS)
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).
Neutrophil function in an experimental model of hemolytic uremic syndrome.
Vedanarayanan, V V; Kaplan, B S; Fong, J S
1987-03-01
To understand the role of neutrophil leukocytosis in hemolytic uremic syndrome, we studied the changes in neutrophil function in the modified generalized Shwartzman reaction in rabbits. This model resembles hemolytic uremic syndrome associated with endotoxemia. At the end of an endotoxin infusion, we observed leukopenia, thrombocytopenia, and a decrease in hematocrit associated with schistocytosis. Plasma B-glucuronidase levels increased and this was associated with a decrease in neutrophil content of the enzyme. The chemotactic index and neutrophil aggregation to zymosan-activated serum were impaired compared to controls. The neutrophil procoagulant content increased after endotoxin infusion. The serum creatinine concentration and proteinuria increased in the endotoxin-treated animals. The changes returned to normal by 48 h. Renal cortical malondialdehyde, a reflection of lipid peroxidation, was higher in the endotoxin-treated animals than in the controls. We have shown enzyme release by neutrophils, impairment of chemotaxis and aggregation, increased procoagulant content in neutrophils, and evidence of lipid peroxidation in renal cortical tissue in this model. These observations raise the possibility that leukocytes may have a role in the pathogenesis of the hemolytic uremic syndrome. PMID:3550673
Homology Modeling: Generating Structural Models to Understand Protein Function and Mechanism
NASA Astrophysics Data System (ADS)
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.
Uterine glands: development, function and experimental model systems
Cooke, Paul S.; Spencer, Thomas E.; Bartol, Frank F.; Hayashi, Kanako
2013-01-01
Development of uterine glands (adenogenesis) in mammals typically begins during the early post-natal period and involves budding of nascent glands from the luminal epithelium and extensive cell proliferation in these structures as they grow into the surrounding stroma, elongate and mature. Uterine glands are essential for pregnancy, as demonstrated by the infertility that results from inhibiting the development of these glands through gene mutation or epigenetic strategies. Several genes, including forkhead box A2, beta-catenin and members of the Wnt and Hox gene families, are implicated in uterine gland development. Progestins inhibit uterine epithelial proliferation, and this has been employed as a strategy to develop a model in which progestin treatment of ewes for 8 weeks from birth produces infertile adults lacking uterine glands. More recently, mouse models have been developed in which neonatal progestin treatment was used to permanently inhibit adenogenesis and adult fertility. These studies revealed a narrow and well-defined window in which progestin treatments induced permanent infertility by impairing neonatal gland development and establishing endometrial changes that result in implantation defects. These model systems are being utilized to better understand the molecular mechanisms underlying uterine adenogenesis and endometrial function. The ability of neonatal progestin treatment in sheep and mice to produce infertility suggests that an approach of this kind may provide a contraceptive strategy with application in other species. Recent studies have defined the temporal patterns of adenogenesis in uteri of neonatal and juvenile dogs and work is underway to determine whether neonatal progestin or other steroid hormone treatments might be a viable contraceptive approach in this species. PMID:23619340
Bethea, Cynthia L; Kim, Aaron; Cameron, Judy L
2012-01-01
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 x 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
ERIC Educational Resources Information Center
Slaughter, Susan; Bankes, Jane
2007-01-01
The Functional Transitions Model (FTM) integrates the theoretical notions of progressive functional decline associated with Alzheimer's disease (AD), excess disability, and transitions occurring intermittently along the trajectory of functional decline. Application of the Functional Transitions Model to clinical practice encompasses the paradox of…
Park, Eun-Young; Kim, Won-Ho
2013-05-01
Physical therapy intervention for children with cerebral palsy (CP) is focused on reducing neurological impairments, improving strength, and preventing the development of secondary impairments in order to improve functional outcomes. However, relationship between motor impairments and functional outcome has not been proved definitely. This study confirmed the construct of motor impairment and performed structural equation modeling (SEM) between motor impairment, gross motor function, and functional outcomes of regarding activities of daily living in children with CP. 98 children (59 boys, 39 girls) with CP participated in this cross-sectional study. Mean age was 11 y 5 mo (SD 1 y 9 mo). The Manual Muscle Test (MMT), the Modified Ashworth Scale (MAS), range of motion (ROM) measurement, and the selective motor control (SMC) scale were used to assess motor impairments. Gross motor function and functional outcomes were measured using the Gross Motor Function Measure (GMFM) and the Functional Skills domain of the Pediatric Evaluation of Disability Inventory (PEDI) respectively. Measurement of motor impairment was consisted of strength, spasticity, ROM, and SMC. The construct of motor impairment was confirmed though an examination of a measurement model. The proposed SEM model showed good fit indices. Motor impairment effected gross motor function (β=-.0869). Gross motor function and motor impairment affected functional outcomes directly (β=0.890) and indirectly (β=-0.773) respectively. We confirmed that the construct of motor impairment consist of strength, spasticity, ROM, and SMC and it was identified through measurement model analysis. Functional outcomes are best predicted by gross motor function and motor impairments have indirect effects on functional outcomes. PMID:23500167
A Latent Model for Prioritization of SNPs for Functional Studies
Fridley, Brooke L.; Iversen, Ed; Tsai, Ya-Yu; Jenkins, Gregory D.; Goode, Ellen L.; Sellers, Thomas A.
2011-01-01
One difficult question facing researchers is how to prioritize SNPs detected from genetic association studies for functional studies. Often a list of the top M SNPs is determined based on solely the p-value from an association analysis, where M is determined by financial/time constraints. For many studies of complex diseases, multiple analyses have been completed and integrating these multiple sets of results may be difficult. One may also wish to incorporate biological knowledge, such as whether the SNP is in the exon of a gene or a regulatory region, into the selection of markers to follow-up. In this manuscript, we propose a Bayesian latent variable model (BLVM) for incorporating “features” about a SNP to estimate a latent “quality score”, with SNPs prioritized based on the posterior probability distribution of the rankings of these quality scores. We illustrate the method using data from an ovarian cancer genome-wide association study (GWAS). In addition to the application of the BLVM to the ovarian GWAS, we applied the BLVM to simulated data which mimics the setting involving the prioritization of markers across multiple GWAS for related diseases/traits. The top ranked SNP by BLVM for the ovarian GWAS, ranked 2nd and 7th based on p-values from analyses of all invasive and invasive serous cases. The top SNP based on serous case analysis p-value (which ranked 197th for invasive case analysis), was ranked 8th based on the posterior probability of being in the top 5 markers (0.13). In summary, the application of the BLVM allows for the systematic integration of multiple SNP “features” for the prioritization of loci for fine-mapping or functional studies, taking into account the uncertainty in ranking. PMID:21687685
Wightman function and vacuum fluctuations in higher dimensional brane models
Saharian, Aram A.
2006-02-15
The Wightman function and the vacuum expectation value of the field square are evaluated for a massive scalar field with a general curvature coupling parameter subject to Robin boundary conditions on two codimension-one parallel branes located on a (D+1)-dimensional background spacetime AdS{sub D{sub 1}}{sub +1}x{sigma} with a warped internal space {sigma}. The general case of different Robin coefficients on separate branes is considered. The application of the generalized Abel-Plana formula for the series over zeros of combinations of cylinder functions allows us to manifestly extract the part due to the bulk without boundaries. Unlike the purely anti-de Sitter (AdS) bulk, the vacuum expectation value of the field square induced by a single brane, in addition to the distance from the brane, depends also on the position of the brane in the bulk. The brane induced part in this expectation value vanishes when the brane position tends to the AdS horizon or the AdS boundary. The asymptotic behavior of the vacuum densities near the branes and at large distances is investigated. The contribution of Kaluza-Klein modes along {sigma} is discussed in various limiting cases. In the limit when the curvature radius for the AdS spacetime tends to infinity, we derive the results for two parallel Robin plates on the background spacetime R{sup (D{sub 1},1)}x{sigma}. For strong gravitational fields corresponding to large values of the AdS energy scale, both the single brane and interference parts of the expectation values integrated over the internal space are exponentially suppressed. As an example the case {sigma}=S{sup 1} is considered, corresponding to the AdS{sub D+1} bulk with one compactified dimension. An application to the higher dimensional generalization of the Randall-Sundrum brane model with arbitrary mass terms on the branes is discussed.
GSK-3: Functional Insights from Cell Biology and Animal Models
Kaidanovich-Beilin, Oksana; Woodgett, James Robert
2011-01-01
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 knockout 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. PMID:22110425
Density functional theory modeling of multilayer "epitaxial" graphene oxide.
Zhou, Si; Bongiorno, Angelo
2014-11-18
CONSPECTUS: Graphene oxide (GO) is a complex material of both fundamental and applied interest. Elucidating the structure of GO is crucial to achieve control over its properties and technological applications. GO is a nonstoichiometric and hygroscopic material with a lamellar structure, and its physical chemical properties depend critically on synthesis procedures and postsynthesis treatments. Numerous efforts are in place to both understand and exploit this versatile layered carbon material. This Account reports on recent density functional theory (DFT) studies of "epitaxial" graphene oxide (hereafter EGO), a type of GO obtained by oxidation of graphene films grown epitaxially on silicon carbide. Here, we rely on selected X-ray photoelectron spectroscopy (XPS), infrared spectroscopy (IR), and X-ray diffraction (XRD) measurements of EGO, and we discuss in great detail how we utilized DFT-based techniques to project out from the experimental data basic atomistic information about the chemistry and structure of these films. This Account provides an example as to how DFT modeling can be used to elucidate complex materials such as GO from a limited set of experimental information. EGO exhibits a uniform layered structure, consisting of a stack of graphene planes hosting predominantly epoxide and hydroxyl groups, and water molecules intercalated between the oxidized carbon layers. Here, we first focus on XPS measurements of EGO, and we use DFT to generate realistic model structures, calculate core-level chemical shifts, and through the comparison with experiment, gain insight on the chemical composition and metastability characteristics of EGO. DFT calculations are then used to devise a simplistic but accurate simulation scheme to study thermodynamic and kinetic stability and to predict the intralayer structure of EGO films aged at room temperature. Our simulations show that aged EGO encompasses layers with nanosized oxidized domains presenting a high concentration of
Application of Gaussian Process Modeling to Analysis of Functional Unreliability
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
ERIC Educational Resources Information Center
Okawa, Yayoi; Nakamura, Shigemi; Kudo, Minako; Ueda, Satoshi
2009-01-01
The purpose of this study is to confirm the working hypothesis on two major models of functioning decline and two corresponding models of rehabilitation program in an older population through detailed interviews with the persons who have functioning declines and on-the-spot observations of key activities on home visits. A total of 542…
Stepwise building of plankton functional type (PFT) models: A feasible route to complex models?
NASA Astrophysics Data System (ADS)
Frede Thingstad, T.; Strand, Espen; Larsen, Aud
2010-01-01
We discuss the strategy of building models of the lower part of the planktonic food web in a stepwise manner: starting with few plankton functional types (PFTs) and adding resolution and complexity while carrying along the insight and results gained from simpler models. A central requirement for PFT models is that they allow sustained coexistence of the PFTs. Here we discuss how this identifies a need to consider predation, parasitism and defence mechanisms together with nutrient acquisition and competition. Although the stepwise addition of complexity is assumed to be useful and feasible, a rapid increase in complexity strongly calls for alternative approaches able to model emergent system-level features without a need for detailed representation of all the underlying biological detail.
Applying Quality Function Deployment Model in Burn Unit Service Improvement.
Keshtkaran, Ali; Hashemi, Neda; Kharazmi, Erfan; Abbasi, Mehdi
2016-01-01
Quality function deployment (QFD) is one of the most effective quality design tools. This study applies QFD technique to improve the quality of the burn unit services in Ghotbedin Hospital in Shiraz, Iran. First, the patients' expectations of burn unit services and their priorities were determined through Delphi method. Thereafter, burn unit service specifications were determined through Delphi method. Further, the relationships between the patients' expectations and service specifications and also the relationships between service specifications were determined through an expert group's opinion. Last, the final importance scores of service specifications were calculated through simple additive weighting method. The findings show that burn unit patients have 40 expectations in six different areas. These expectations are in 16 priority levels. Burn units also have 45 service specifications in six different areas. There are four-level relationships between the patients' expectations and service specifications and four-level relationships between service specifications. The most important burn unit service specifications have been identified in this study. The QFD model developed in the study can be a general guideline for QFD planners and executives.
Dicentric chromosomes: unique models to study centromere function and inactivation
Stimpson, Kaitlin M.; Matheny, Justyne E.
2013-01-01
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 division. The molecular basis for centromere inactivation is not well under-stood, 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. PMID:22801777
PTEN recruitment controls synaptic and cognitive function in Alzheimer's models.
Knafo, Shira; Sánchez-Puelles, Cristina; Palomer, Ernest; Delgado, Igotz; Draffin, Jonathan E; Mingo, Janire; Wahle, Tina; Kaleka, Kanwardeep; Mou, Liping; Pereda-Perez, Inmaculada; Klosi, Edvin; Faber, Erik B; Chapman, Heidi M; Lozano-Montes, Laura; Ortega-Molina, Ana; Ordóñez-Gutiérrez, Lara; Wandosell, Francisco; Viña, Jose; Dotti, Carlos G; Hall, Randy A; Pulido, Rafael; Gerges, Nashaat Z; Chan, Andrew M; Spaller, Mark R; Serrano, Manuel; Venero, César; Esteban, José A
2016-03-01
Dyshomeostasis of amyloid-β peptide (Aβ) is responsible for synaptic malfunctions leading to cognitive deficits ranging from mild impairment to full-blown dementia in Alzheimer's disease. Aβ appears to skew synaptic plasticity events toward depression. We found that inhibition of PTEN, a lipid phosphatase that is essential to long-term depression, rescued normal synaptic function and cognition in cellular and animal models of Alzheimer's disease. Conversely, transgenic mice that overexpressed PTEN displayed synaptic depression that mimicked and occluded Aβ-induced depression. Mechanistically, Aβ triggers a PDZ-dependent recruitment of PTEN into the postsynaptic compartment. Using a PTEN knock-in mouse lacking the PDZ motif, and a cell-permeable interfering peptide, we found that this mechanism is crucial for Aβ-induced synaptic toxicity and cognitive dysfunction. Our results provide fundamental information on the molecular mechanisms of Aβ-induced synaptic malfunction and may offer new mechanism-based therapeutic targets to counteract downstream Aβ signaling. PMID:26780512
A Model of Tight Junction Function In CNS Myelinated Axons
Gow, Alexander; Devaux, Jerome
2010-01-01
The insulative properties of myelin sheaths in the central and peripheral nervous systems (CNS and PNS) are widely thought to derive from the high resistance and low capacitance of the constituent membranes. Although this view adequately accounts for myelin function in large diameter PNS fibers, it poorly reflects the behavior of small fibers that are prominent in many regions of the CNS. Herein, we develop a computational model to more accurately represent conduction in small fibers. By incorporating structural features that, hitherto, have not been simulated, we demonstrate that myelin tight junctions improve saltatory conduction by reducing current flow through the myelin, limiting axonal membrane depolarization and restraining the activation of ion channels beneath the myelin sheath. Accordingly, our simulations provide a novel view of myelin by which tight junctions minimize charging of the membrane capacitance and lower the membrane time constant to improve the speed and accuracy of transmission in small diameter fibers. This study establishes possible mechanisms whereby TJs affect conduction in the absence of overt perturbations to myelin architecture and may in part explain the tremor and gait abnormalities observed in Claudin 11-null mice. PMID:20102674
Applying Quality Function Deployment Model in Burn Unit Service Improvement.
Keshtkaran, Ali; Hashemi, Neda; Kharazmi, Erfan; Abbasi, Mehdi
2016-01-01
Quality function deployment (QFD) is one of the most effective quality design tools. This study applies QFD technique to improve the quality of the burn unit services in Ghotbedin Hospital in Shiraz, Iran. First, the patients' expectations of burn unit services and their priorities were determined through Delphi method. Thereafter, burn unit service specifications were determined through Delphi method. Further, the relationships between the patients' expectations and service specifications and also the relationships between service specifications were determined through an expert group's opinion. Last, the final importance scores of service specifications were calculated through simple additive weighting method. The findings show that burn unit patients have 40 expectations in six different areas. These expectations are in 16 priority levels. Burn units also have 45 service specifications in six different areas. There are four-level relationships between the patients' expectations and service specifications and four-level relationships between service specifications. The most important burn unit service specifications have been identified in this study. The QFD model developed in the study can be a general guideline for QFD planners and executives. PMID:23884047
Modeling of Red Blood Cells and Related Spleen Function
NASA Astrophysics Data System (ADS)
Peng, Zhangli; Pivkin, Igor; Dao, Ming
2011-11-01
A key function of the spleen is to clear red blood cells (RBCs) with abnormal mechanical properties from the circulation. These abnormal mechanical properties may be due to RBC aging or RBC diseases, e.g., malaria and sickle cell anemia. Specifically, 10% of RBCs passing through the spleen are forced to squeeze into the narrow slits between the endothelial cells, and stiffer cells which get stuck are killed and digested by macrophages. To investigate this important physiological process, we employ three different approaches to study RBCs passage through these small slits, including analytical theory, Dissipative Particle Dynamics (DPD) simulation and Multiscale Finite Element Method (MS-FEM). By applying the analytical theory, we estimate the critical limiting geometries RBCs can pass. By using the DPD method, we study the full fluid-structure interaction problem, and compute RBC deformation under different pressure gradients. By employing the MS-FEM approach, we model the lipid bilayer and the cytoskeleton as two distinct layers, and focus on the cytoskeleton deformation and the bilayer-skeleton interaction force at the molecular level. Finally the results of these three approaches are compared to each other and correlated to the experimental observations.
ERIC Educational Resources Information Center
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…
ERIC Educational Resources Information Center
Gericke, Niklas Markus; Hagberg, Mariana
2007-01-01
Models are often used when teaching science. In this paper historical models and students' ideas about genetics are compared. The historical development of the scientific idea of the gene and its function is described and categorized into five historical models of gene function. Differences and similarities between these historical models are made…
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
2014-01-01
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.
NASA Technical Reports Server (NTRS)
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.
Mouse alpha-macroglobulin. Structure, function and a molecular model.
Hudson, N W; Kehoe, J M; Koo, P H
1987-01-01
Mouse alpha-macroglobulin (M-AMG) is believed to be a functional homologue of human alpha 2-macroglobulin (h-alpha 2M). The subunit composition, the tryptic cleavage pattern before and after methylamine incorporation and the two-dimensional tryptic-peptide mapping, however, indicate that these two proteins are structurally distinct. M-AMG is composed of two major types of polypeptides (Mr 163,000 and 35,000) together with a minor polypeptide (Mr 185,000), whereas h-alpha 2M has only one type of polypeptide (Mr 185,000). After incorporation of methylamine, there is no change in the normal tryptic-cleavage pattern of M-AMG; however, tryptic cleavage of h-alpha 2M is severely retarded [Hudson & Koo (1982) Biochim. Biophys. Acta 704, 290-303]. The N-terminal sequence of the 163,000-Mr polypeptide of M-AMG shows sequence homology with the N-terminal sequence of h-alpha 2M. The amino acid compositions of M-AMG and its two major polypeptide chains are compared. Thermal fragmentation studies show that the 163,000-Mr polypeptide is broken down into 125,000-Mr and 29,000-Mr fragments. Trypsin-binding studies show that M-AMG can bind two molecules of trypsin/molecule. Inactivations of the trypsin-binding property of M-AMG and h-alpha 2M with methylamine show similar kinetics of inhibition at 4 degrees C. A structural model of M-AMG is proposed, based on accumulated data. Images Fig. 3. PMID:2449173
Crustal structure beneath northeast India inferred from receiver function modeling
NASA Astrophysics Data System (ADS)
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.
Fabrication, Characterization and Modeling of Functionally Graded Materials
NASA Astrophysics Data System (ADS)
Lee, Po-Hua
In the past few decades, a number of theoretical and experimental studies for design, fabrication and performance analysis of solar panel systems (photovoltaic/thermal systems) have been documented. The existing literature shows that the use of solar energy provides a promising solution to alleviate the shortage of natural resources and the environmental pollution associated with electricity generation. A hybrid solar panel has been invented to integrate photovoltaic (PV) cells onto a substrate through a functionally graded material (FGM) with water tubes cast inside, through which water flow serves as both a heat sink and a solar heat collector. Due to the unique and graded material properties of FGMs, this novel design not only supplies efficient thermal harvest and electrical production, but also provides benefits such as structural integrity and material efficiency. In this work, a sedimentation method has been used to fabricate aluminum (Al) and high-density polyethylene (HDPE) FGMs. The size effect of aluminum powder on the material gradation along the depth direction is investigated. Aluminum powder or the mixture of Al and HDPE powder is thoroughly mixed and uniformly dispersed in ethanol and then subjected to sedimentation. During the sedimentation process, the concentration of Al and HDPE particles temporally and spatially changes in the depth direction due to the non-uniform motion of particles; this change further affects the effective viscosity of the suspension and thus changes the drag force of particles. A Stokes' law based model is developed to simulate the sedimentation process, demonstrate the effect of manufacturing parameters on sedimentation, and predict the graded microstructure of deposition in the depth direction. In order to improve the modeling for sedimentation behavior of particles, the Eshelby's equivalent inclusion method (EIM) is presented to determine the interaction between particles, which is not considered in a Stokes' law based
Lawrence Livermore National Security Cost Model Functional Management Assessment
Tevis, J; Hirahara, J; Thomas, B; Mendez, M
2008-06-12
The scope of the Functional Management Assessment of the cost model included a review of the plan and progress of the Cost Model Review Team. The review focused on processes in place to ensure simplicity, compliance with cost accounting standards and indirect cost allocation methodology, and the change management plan. This was intended to be a high-level initial review in order to provide recommendations for a subsequent more comprehensive review. The single document reviewed by the team during the assessment was the Indirect Cost Recovery Model Review, which describes how the indirect rate restructure and new organizational structure have resulted in streamlined charging practices to better understand and strategically manage costs. ISSUE 1: The cost model focuses heavily on rate structure but not on cost management. Significant progress has been made to simplify the rate structure. The number of indirect rates has been reduced from 67 different indirect rates used under the prior contract to 32 rates in the first year of the LLNS contract, with a goal of further reduction to 16 for FY09. The reductions are being recommended by a broad-based Working Group driven by Lab leadership desiring a simplified rate structure that would make it easier to analyze the true cost of overhead, be viewed as equitable, and ensure appropriate use of Service, i.e., operations, Centers. This has been a real challenge due to the significant change in approach from one that previously involved a very complex rate structure. Under this prior approach, the goal was to manage the rates, and rates were established at very detailed levels that would 'shine the light' on pools of overhead costs. As long as rates stayed constant or declined, not as much attention tended to be given to them, particularly with so many pools to review (184 indirect rate pools in FY05). However, as difficult and important as simplifying the rate structure has been, the fundamental reason for the simplification
Partition function of the elliptic solid-on-solid model as a single determinant
NASA Astrophysics Data System (ADS)
Galleas, W.
2016-07-01
In this Rapid Communication 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.
ERIC Educational Resources Information Center
Bowman, Anita H.
A pentagonal model, based on the star model of function understanding of C. Janvier (1987), is presented as a framework for the design and interpretation of research in the area of learning the concept of mathematical function. The five vertices of the pentagon correspond to five common representations of mathematical function: (1) graph; (2)…
Thienpont, Benedicte; Barata, Carlos; Raldúa, Demetrio
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
Modeling the fundamental characteristics and processes of the spacecraft functioning
NASA Technical Reports Server (NTRS)
Bazhenov, V. I.; Osin, M. I.; Zakharov, Y. V.
1986-01-01
The fundamental aspects of modeling of spacecraft characteristics by using computing means are considered. Particular attention is devoted to the design studies, the description of physical appearance of the spacecraft, and simulated modeling of spacecraft systems. The fundamental questions of organizing the on-the-ground spacecraft testing and the methods of mathematical modeling were presented.
MODELS-3/CMAQ APPLICATIONS WHICH ILLUSTRATE CAPABILITY AND FUNCTIONALITY
The Models-3/CMAQ developed by the U.S. Environmental Protections Agency (USEPA) is a third generation multiscale, multi-pollutant air quality modeling system within a high-level, object-oriented computer framework (Models-3). It has been available to the scientific community ...
Models of the Protocellular Structures, Functions and Evolution
NASA Technical Reports Server (NTRS)
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
Fatigue Crack Growth Analysis Models for Functionally Graded Materials
Dag, Serkan; Yildirim, Bora; Sabuncuoglu, Baris
2008-02-15
The objective of this study is to develop crack growth analysis methods for functionally graded materials (FGMs) subjected to mode I cyclic loading. The study presents finite elements based computational procedures for both two and three dimensional problems to examine fatigue crack growth in functionally graded materials. Developed methods allow the computation of crack length and generation of crack front profile for a graded medium subjected to fluctuating stresses. The results presented for an elliptical crack embedded in a functionally graded medium, illustrate the competing effects of ellipse aspect ratio and material property gradation on the fatigue crack growth behavior.
MODELING FUNCTIONALLY GRADED INTERPHASE REGIONS IN CARBON NANOTUBE REINFORCED COMPOSITES
NASA Technical Reports Server (NTRS)
Seidel, G. D.; Lagoudas, D. C.; Frankland, S. J. V.; Gates, T. S.
2006-01-01
A combination of micromechanics methods and molecular dynamics simulations are used to obtain the effective properties of the carbon nanotube reinforced composites with functionally graded interphase regions. The multilayer composite cylinders method accounts for the effects of non-perfect load transfer in carbon nanotube reinforced polymer matrix composites using a piecewise functionally graded interphase. The functional form of the properties in the interphase region, as well as the interphase thickness, is derived from molecular dynamics simulations of carbon nanotubes in a polymer matrix. Results indicate that the functional form of the interphase can have a significant effect on all the effective elastic constants except for the effective axial modulus for which no noticeable effects are evident.
NASA Astrophysics Data System (ADS)
Harnisch, Bernd; Weigel, Thomas
1994-09-01
The calculation of the BRDF (Bi-Directional-Reflection-Distribution-Function) from profile measurements was performed theoretically and verified by measurements on a BK7 sample. The assumptions on the surface topography and approximations done are highlighted.
Takemura, Kazuhisa; Murakami, Hajime
2016-01-01
A probability weighting function (w(p)) is considered to be a nonlinear function of probability (p) in behavioral decision theory. This study proposes a psychophysical model of probability weighting functions derived from a hyperbolic time discounting model and a geometric distribution. The aim of the study is to show probability weighting functions from the point of view of waiting time for a decision maker. Since the expected value of a geometrically distributed random variable X is 1/p, we formulized the probability weighting function of the expected value model for hyperbolic time discounting as w(p) = (1 − k log p)−1. Moreover, the probability weighting function is derived from Loewenstein and Prelec's (1992) generalized hyperbolic time discounting model. The latter model is proved to be equivalent to the hyperbolic-logarithmic weighting function considered by Prelec (1998) and Luce (2001). In this study, we derive a model from the generalized hyperbolic time discounting model assuming Fechner's (1860) psychophysical law of time and a geometric distribution of trials. In addition, we develop median models of hyperbolic time discounting and generalized hyperbolic time discounting. To illustrate the fitness of each model, a psychological experiment was conducted to assess the probability weighting and value functions at the level of the individual participant. The participants were 50 university students. The results of individual analysis indicated that the expected value model of generalized hyperbolic discounting fitted better than previous probability weighting decision-making models. The theoretical implications of this finding are discussed. PMID:27303338
Takemura, Kazuhisa; Murakami, Hajime
2016-01-01
A probability weighting function (w(p)) is considered to be a nonlinear function of probability (p) in behavioral decision theory. This study proposes a psychophysical model of probability weighting functions derived from a hyperbolic time discounting model and a geometric distribution. The aim of the study is to show probability weighting functions from the point of view of waiting time for a decision maker. Since the expected value of a geometrically distributed random variable X is 1/p, we formulized the probability weighting function of the expected value model for hyperbolic time discounting as w(p) = (1 - k log p)(-1). Moreover, the probability weighting function is derived from Loewenstein and Prelec's (1992) generalized hyperbolic time discounting model. The latter model is proved to be equivalent to the hyperbolic-logarithmic weighting function considered by Prelec (1998) and Luce (2001). In this study, we derive a model from the generalized hyperbolic time discounting model assuming Fechner's (1860) psychophysical law of time and a geometric distribution of trials. In addition, we develop median models of hyperbolic time discounting and generalized hyperbolic time discounting. To illustrate the fitness of each model, a psychological experiment was conducted to assess the probability weighting and value functions at the level of the individual participant. The participants were 50 university students. The results of individual analysis indicated that the expected value model of generalized hyperbolic discounting fitted better than previous probability weighting decision-making models. The theoretical implications of this finding are discussed. PMID:27303338
NASA Technical Reports Server (NTRS)
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.
A.V. Efremov, P. Schweitzer, O.V. Teryaev, P. Zavada
2011-03-01
We derive relations between transverse momentum dependent distribution functions (TMDs) and the usual parton distribution functions (PDFs) in the 3D covariant parton model, which follow from Lorentz invariance and the assumption of a rotationally symmetric distribution of parton momenta in the nucleon rest frame. Using the known PDFs f_1(x) and g_1(x) as input we predict the x- and pT-dependence of all twist-2 T-even TMDs.
A Multiscale Modeling Demonstration Based on the Pair Correlation Function
Gao, Carrie Y; Nicholson, Don M; Keffer, David; Edwards, Brian J
2008-01-01
For systems with interatomic interactions that are well described by pair-wise potentials, the pair correlation function provides a vehicle for passing information from the molecular level to the macroscopic level of description. In this work, we present a complete demonstration of the use of the pair correlation function to simulate a fluid at the molecular and macroscopic levels. At the molecular level, we describe a monatomic fluid using the Ornstein-Zernike integral equation theory closed with the Percus-Yevick approximation. We show that all of the required thermodynamic properties can be evaluated knowing the pair correlation function. At the macroscopic level, we perform a multiscale simulation with macroscopic evolution equations for the mass, momentum, temperature, and pair correlation function, using molecular-level simulation to provide the boundary conditions. We perform a self-consistency check by comparing the pair correlation function that evolved from the multiscale simulation with the one evaluated at the molecular-level; excellent agreement is achieved.
A Functional Model for the Treatment of Primary Enuresis.
ERIC Educational Resources Information Center
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
ERIC Educational Resources Information Center
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…
Basic Life Functions Instructional Program Model. Field Copy.
ERIC Educational Resources Information Center
Wisconsin State Dept. of Public Instruction, Madison. Div. for Handicapped Children.
Presented is a model, designed by the Wisconsin Department of Public Instruction, for development of an instructional program in basic living skills for trainable mentally retarded children (2- to 20-years-old). The model identifies the following instructional goals: to communicate ideas, to understand one's self and interact with others, to…
Discrete two-sex models of population dynamics: On modelling the mating function
NASA Astrophysics Data System (ADS)
Bessa-Gomes, Carmen; Legendre, Stéphane; Clobert, Jean
2010-09-01
Although sexual reproduction has long been a central subject of theoretical ecology, until recently its consequences for population dynamics were largely overlooked. This is now changing, and many studies have addressed this issue, showing that when the mating system is taken into account, the population dynamics depends on the relative abundance of males and females, and is non-linear. Moreover, sexual reproduction increases the extinction risk, namely due to the Allee effect. Nevertheless, different studies have identified diverse potential consequences, depending on the choice of mating function. In this study, we investigate the consequences of three alternative mating functions that are frequently used in discrete population models: the minimum; the harmonic mean; and the modified harmonic mean. We consider their consequences at three levels: on the probability that females will breed; on the presence and intensity of the Allee effect; and on the extinction risk. When we consider the harmonic mean, the number of times the individuals of the least abundant sex mate exceeds their mating potential, which implies that with variable sex-ratios the potential reproductive rate is no longer under the modeller's control. Consequently, the female breeding probability exceeds 1 whenever the sex-ratio is male-biased, which constitutes an obvious problem. The use of the harmonic mean is thus only justified if we think that this parameter should be re-defined in order to represent the females' breeding rate and the fact that females may reproduce more than once per breeding season. This phenomenon buffers the Allee effect, and reduces the extinction risk. However, when we consider birth-pulse populations, such a phenomenon is implausible because the number of times females can reproduce per birth season is limited. In general, the minimum or modified harmonic mean mating functions seem to be more suitable for assessing the impact of mating systems on population dynamics.
Putting the brakes on inhibitory models of frontal lobe function.
Hampshire, Adam
2015-06-01
There has been much recent debate regarding the neural basis of motor response inhibition. An influential hypothesis from the last decade proposes that a module within the right inferior frontal cortex (RIFC) of the human brain is dedicated to supporting response inhibition. However, there is growing evidence to support the alternative view that response inhibition is just one prominent example of the many cognitive control processes that are supported by the same set of 'domain general' functional networks. Here, I test directly between the modular and network accounts of motor response inhibition by applying a combination of data-driven, event-related and functional connectivity analyses to fMRI data from a variety of attention and inhibition tasks. The results demonstrate that there is no inhibitory module within the RIFC. Instead, response inhibition recruits a functionally heterogeneous ensemble of RIFC networks, which can be dissociated from each other in the context of other task demands.
Putting the brakes on inhibitory models of frontal lobe function
Hampshire, Adam
2015-01-01
There has been much recent debate regarding the neural basis of motor response inhibition. An influential hypothesis from the last decade proposes that a module within the right inferior frontal cortex (RIFC) of the human brain is dedicated to supporting response inhibition. However, there is growing evidence to support the alternative view that response inhibition is just one prominent example of the many cognitive control processes that are supported by the same set of ‘domain general’ functional networks. Here, I test directly between the modular and network accounts of motor response inhibition by applying a combination of data-driven, event-related and functional connectivity analyses to fMRI data from a variety of attention and inhibition tasks. The results demonstrate that there is no inhibitory module within the RIFC. Instead, response inhibition recruits a functionally heterogeneous ensemble of RIFC networks, which can be dissociated from each other in the context of other task demands. PMID:25818684
Modeling Functional Motions of Biological Systems by Customized Natural Moves.
Demharter, Samuel; Knapp, Bernhard; Deane, Charlotte M; Minary, Peter
2016-08-23
Simulating the functional motions of biomolecular systems requires large computational resources. We introduce a computationally inexpensive protocol for the systematic testing of hypotheses regarding the dynamic behavior of proteins and nucleic acids. The protocol is based on natural move Monte Carlo, a highly efficient conformational sampling method with built-in customization capabilities that allows researchers to design and perform a large number of simulations to investigate functional motions in biological systems. We demonstrate the use of this protocol on both a protein and a DNA case study. Firstly, we investigate the plasticity of a class II major histocompatibility complex in the absence of a bound peptide. Secondly, we study the effects of the epigenetic mark 5-hydroxymethyl on cytosine on the structure of the Dickerson-Drew dodecamer. We show how our customized natural moves protocol can be used to investigate causal relationships of functional motions in biological systems. PMID:27558715
Pump function curve shape for a model lymphatic vessel.
Bertram, C D; Macaskill, C; Moore, J E
2016-07-01
The transport capacity of a contractile segment of lymphatic vessel is defined by its pump function curve relating mean flow-rate and adverse pressure difference. Numerous system characteristics affect curve shape and the magnitude of the generated flow-rates and pressures. Some cannot be varied experimentally, but their separate and interacting effects can be systematically revealed numerically. This paper explores variations in the rate of change of active tension and the form of the relation between active tension and muscle length, factors not known from experiment to functional precision. Whether the pump function curve bends toward or away from the origin depends partly on the curvature of the passive pressure-diameter relation near zero transmural pressure, but rather more on the form of the relation between active tension and muscle length. A pump function curve bending away from the origin defines a well-performing pump by maximum steady output power. This behaviour is favoured by a length/active-tension relationship which sustains tension at smaller lengths. Such a relationship also favours high peak mechanical efficiency, defined as output power divided by the input power obtained from the lymphangion diameter changes and active-tension time-course. The results highlight the need to pin down experimentally the form of the length/active-tension relationship. PMID:27185045
Halliday's Communicative-Functional Model Revisited: A Case Study.
ERIC Educational Resources Information Center
Keshavarz, Mohammad Hossein
2001-01-01
Analysis of data collected from a Persian-English bilingual infant over 10 months beginning at age 9 months found that, in comparison to the monolingual child in a previous study by Halliday, both children developed pragmatic functions from a very early age. A categorization system is proposed to facilitate the analysis of child language…
Rational polynomial functions for modeling E. coli and bromide breakthrough
Technology Transfer Automated Retrieval System (TEKTRAN)
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
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.
León, Larry F; Cai, Tianxi
2012-04-01
In this paper we develop model checking techniques for assessing functional form specifications of covariates in censored linear regression models. These procedures are based on a censored data analog to taking cumulative sums of "robust" residuals over the space of the covariate under investigation. These cumulative sums are formed by integrating certain Kaplan-Meier estimators and may be viewed as "robust" censored data analogs to the processes considered by Lin, Wei & Ying (2002). The null distributions of these stochastic processes can be approximated by the distributions of certain zero-mean Gaussian processes whose realizations can be generated by computer simulation. Each observed process can then be graphically compared with a few realizations from the Gaussian process. We also develop formal test statistics for numerical comparison. Such comparisons enable one to assess objectively whether an apparent trend seen in a residual plot reects model misspecification or natural variation. We illustrate the methods with a well known dataset. In addition, we examine the finite sample performance of the proposed test statistics in simulation experiments. In our simulation experiments, the proposed test statistics have good power of detecting misspecification while at the same time controlling the size of the test.
ERIC Educational Resources Information Center
Meyers, Steven A.; And Others
Current psychological literature suggests that positive representations of self and others are associated with sensitivity of caregiving. This study was designed to examine the relationship among self-perceptions, perceptions of family functioning, and caregiving schemata in 618 undergraduates (437 females, 181 males) enrolled in Introductory…
ERIC Educational Resources Information Center
LaRue, Robert H.; Sloman, Kimberly N.; Weiss, Mary Jane; Delmolino, Lara; Hansford, Amy; Szalony, Jill; Madigan, Ryan; Lambright, Nathan M.
2011-01-01
Functional analysis procedures have been effectively used to determine the maintaining variables for challenging behavior and subsequently develop effective interventions. However, fear of evoking dangerous topographies of maladaptive behavior and concerns for reinforcing infrequent maladaptive behavior present challenges for people working in…
Isabelle, Boulangeat; Pauline, Philippe; Sylvain, Abdulhak; Roland, Douzet; Luc, Garraud; Sébastien, Lavergne; Sandra, Lavorel; Jérémie, Van Es; Pascal, Vittoz; Wilfried, Thuiller
2012-11-01
The pace of on-going climate change calls for reliable plant biodiversity scenarios. Traditional dynamic vegetation models use plant functional types that are summarized to such an extent that they become meaningless for biodiversity scenarios. Hybrid dynamic vegetation models of intermediate complexity (hybrid-DVMs) have recently been developed to address this issue. These models, at the crossroads between phenomenological and process-based models, are able to involve an intermediate number of well-chosen plant functional groups (PFGs). The challenge is to build meaningful PFGs that are representative of plant biodiversity, and consistent with the parameters and processes of hybrid-DVMs. Here, we propose and test a framework based on few selected traits to define a limited number of PFGs, which are both representative of the diversity (functional and taxonomic) of the flora in the Ecrins National Park, and adapted to hybrid-DVMs. This new classification scheme, together with recent advances in vegetation modeling, constitutes a step forward for mechanistic biodiversity modeling. PMID:24403847
Critical Function Models for Operation of the International Space Station
Nelson, William Roy; Bagian, T. M.
2000-11-01
Long duration and exploration class space missions will place new requirements on human performance when compared to current space shuttle missions. Specifically, assembly and operation of the International Space Station (ISS) will place significant new demands on the crew. For example, maintenance of systems that provide habitability will become an ongoing activity for the international flight crews. Tasks for maintaining space station habitability will need to be integrated with tasks associated with scientific research. In addition, tasks and resources will need to be prioritized and allocated dynamically in response to changing operational conditions and unplanned system breakdowns. This paper describes an ongoing program to develop a habitability index (HI) for space operations based on the critical function approach. This pilot project focuses on adaptation of the critical function approach to develop a habitability index specifically tailored for space operations. Further work will then be needed to expand and validate the habitability index for application in the ISS operational environment.
A Model-Based Approach to Constructing Music Similarity Functions
NASA Astrophysics Data System (ADS)
West, Kris; Lamere, Paul
2006-12-01
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.
NASA Astrophysics Data System (ADS)
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
Theta function solutions of the quantum Knizhnik-Zamolodchikov-Bernard equation for a face model
NASA Astrophysics Data System (ADS)
Finch, Peter E.; Weston, Robert; Zinn-Justin, Paul
2016-02-01
We consider the quantum Knizhnik-Zamolodchikov-Bernard equation for a face model with elliptic weights, the SOS model. We provide explicit solutions as theta functions. On the so-called combinatorial line, in which the model is equivalent to the three-colour model, these solutions are shown to be eigenvectors of the transfer matrix with periodic boundary conditions.
A functional circuit model of interaural time difference processing.
McColgan, Thomas; Shah, Sahil; Köppl, Christine; Carr, Catherine; Wagner, Hermann
2014-12-01
Inputs from the two sides of the brain interact to create maps of interaural time difference (ITD) in the nucleus laminaris of birds. How inputs from each side are matched with high temporal precision in ITD-sensitive circuits is unknown, given the differences in input path lengths from each side. To understand this problem in birds, we modeled the geometry of the input axons and their corresponding conduction velocities and latencies. Consistent with existing physiological data, we assumed a common latency up to the border of nucleus laminaris. We analyzed two biological implementations of the model, the single ITD map in chickens and the multiple maps of ITD in barn owls. For binaural inputs, since ipsi- and contralateral initial common latencies were very similar, we could restrict adaptive regulation of conduction velocity to within the nucleus. Other model applications include the simultaneous derivation of multiple conduction velocities from one set of measurements and the demonstration that contours with the same ITD cannot be parallel to the border of nucleus laminaris in the owl. Physiological tests of the predictions of the model demonstrate its validity and robustness. This model may have relevance not only for auditory processing but also for other computational tasks that require adaptive regulation of conduction velocity.
Modeling the Transfer Function for the Dark Energy Survey
Chang, C.
2015-03-04
We present a forward-modeling 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/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) and catalogs representative of the DES data. In this work we demonstrate the framework by simulating the 244 deg2 coadd images and catalogs in five bands for the DES Science Verification data. The simulation output is compared with themore » 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 illustrate how one can use the simulations to address systematics issues in data analysis. With clear understanding of the simplifications in our model, we show that one can use the simulations side-by-side with data products to interpret the measurements. This forward modeling approach is generally applicable for other upcoming and future surveys. It provides a powerful tool for systematics studies that is sufficiently realistic and highly controllable.« less
Modeling intracellular signaling underlying striatal function in health and disease.
Nair, Anu G; Gutierrez-Arenas, Omar; Eriksson, Olivia; Jauhiainen, Alexandra; Blackwell, Kim T; Kotaleski, Jeanette H
2014-01-01
Striatum, which is the input nucleus of the basal ganglia, integrates cortical and thalamic glutamatergic inputs with dopaminergic afferents from the substantia nigra pars compacta. The combination of dopamine and glutamate strongly modulates molecular and cellular properties of striatal neurons and the strength of corticostriatal synapses. These actions are performed via intracellular signaling networks, containing several intertwined feedback loops. Understanding the role of dopamine and other neuromodulators requires the development of quantitative dynamical models for describing the intracellular signaling, in order to provide precise unambiguous descriptions and quantitative predictions. Building such models requires integration of data from multiple data sources containing information regarding the molecular interactions, the strength of these interactions, and the subcellular localization of the molecules. Due to the uncertainty, variability, and sparseness of these data, parameter estimation techniques are critical for inferring or constraining the unknown parameters, and sensitivity analysis evaluates which parameters are most critical for a given observed macroscopic behavior. Here, we briefly review the modeling approaches and tools that have been used to investigate biochemical signaling in the striatum, along with some of the models built around striatum. We also suggest a future direction for the development of such models from the, now becoming abundant, high-throughput data.
A functional circuit model of interaural time difference processing.
McColgan, Thomas; Shah, Sahil; Köppl, Christine; Carr, Catherine; Wagner, Hermann
2014-12-01
Inputs from the two sides of the brain interact to create maps of interaural time difference (ITD) in the nucleus laminaris of birds. How inputs from each side are matched with high temporal precision in ITD-sensitive circuits is unknown, given the differences in input path lengths from each side. To understand this problem in birds, we modeled the geometry of the input axons and their corresponding conduction velocities and latencies. Consistent with existing physiological data, we assumed a common latency up to the border of nucleus laminaris. We analyzed two biological implementations of the model, the single ITD map in chickens and the multiple maps of ITD in barn owls. For binaural inputs, since ipsi- and contralateral initial common latencies were very similar, we could restrict adaptive regulation of conduction velocity to within the nucleus. Other model applications include the simultaneous derivation of multiple conduction velocities from one set of measurements and the demonstration that contours with the same ITD cannot be parallel to the border of nucleus laminaris in the owl. Physiological tests of the predictions of the model demonstrate its validity and robustness. This model may have relevance not only for auditory processing but also for other computational tasks that require adaptive regulation of conduction velocity. PMID:25185809
Modeling intracellular signaling underlying striatal function in health and disease.
Nair, Anu G; Gutierrez-Arenas, Omar; Eriksson, Olivia; Jauhiainen, Alexandra; Blackwell, Kim T; Kotaleski, Jeanette H
2014-01-01
Striatum, which is the input nucleus of the basal ganglia, integrates cortical and thalamic glutamatergic inputs with dopaminergic afferents from the substantia nigra pars compacta. The combination of dopamine and glutamate strongly modulates molecular and cellular properties of striatal neurons and the strength of corticostriatal synapses. These actions are performed via intracellular signaling networks, containing several intertwined feedback loops. Understanding the role of dopamine and other neuromodulators requires the development of quantitative dynamical models for describing the intracellular signaling, in order to provide precise unambiguous descriptions and quantitative predictions. Building such models requires integration of data from multiple data sources containing information regarding the molecular interactions, the strength of these interactions, and the subcellular localization of the molecules. Due to the uncertainty, variability, and sparseness of these data, parameter estimation techniques are critical for inferring or constraining the unknown parameters, and sensitivity analysis evaluates which parameters are most critical for a given observed macroscopic behavior. Here, we briefly review the modeling approaches and tools that have been used to investigate biochemical signaling in the striatum, along with some of the models built around striatum. We also suggest a future direction for the development of such models from the, now becoming abundant, high-throughput data. PMID:24560149
An anatomical and functional model of the human tracheobronchial tree.
Florens, M; Sapoval, B; Filoche, M
2011-03-01
The human tracheobronchial tree is a complex branched distribution system in charge of renewing the air inside the acini, which are the gas exchange units. We present here a systematic geometrical model of this system described as a self-similar assembly of rigid pipes. It includes the specific geometry of the upper bronchial tree and a self-similar intermediary tree with a systematic branching asymmetry. It ends by the terminal bronchioles whose generations range from 8 to 22. Unlike classical models, it does not rely on a simple scaling law. With a limited number of parameters, this model reproduces the morphometric data from various sources (Horsfield K, Dart G, Olson DE, Filley GF, Cumming G. J Appl Physiol 31: 207-217, 1971; Weibel ER. Morphometry of the Human Lung. New York: Academic Press, 1963) and the main characteristics of the ventilation. Studying various types of random variations of the airway sizes, we show that strong correlations are needed to reproduce the measured distributions. Moreover, the ventilation performances are observed to be robust against anatomical variability. The same methodology applied to the rat also permits building a geometrical model that reproduces the anatomical and ventilation characteristics of this animal. This simple model can be directly used as a common description of the entire tree in analytical or numerical studies such as the computation of air flow distribution or aerosol transport. PMID:21183626
Predicting and correcting ataxia using a model of cerebellar function
Bhanpuri, Nasir H.; Okamura, Allison M.
2014-01-01
Cerebellar damage results in uncoordinated, variable and dysmetric movements known as ataxia. Here we show that we can reliably model single-joint reaching trajectories of patients (n = 10), reproduce patient-like deficits in the behaviour of controls (n = 11), and apply patient-specific compensations that improve reaching accuracy (P < 0.02). Our approach was motivated by the theory that the cerebellum is essential for updating and/or storing an internal dynamic model that relates motor commands to changes in body state (e.g. arm position and velocity). We hypothesized that cerebellar damage causes a mismatch between the brain’s modelled dynamics and the actual body dynamics, resulting in ataxia. We used both behavioural and computational approaches to demonstrate that specific cerebellar patient deficits result from biased internal models. Our results strongly support the idea that an intact cerebellum is critical for maintaining accurate internal models of dynamics. Importantly, we demonstrate how subject-specific compensation can improve movement in cerebellar patients, who are notoriously unresponsive to treatment. PMID:24812203
Modeling the Transfer Function for the Dark Energy Survey
Chang, C.
2015-03-04
We present a forward-modeling 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/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) and catalogs representative of the DES data. In this work we demonstrate the framework by simulating the 244 deg^{2} coadd images and catalogs in five bands for the DES Science Verification 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 illustrate how one can use the simulations to address systematics issues in data analysis. With clear understanding of the simplifications in our model, we show that one can use the simulations side-by-side with data products to interpret the measurements. This forward modeling approach is generally applicable for other upcoming and future surveys. It provides a powerful tool for systematics studies that is sufficiently realistic and highly controllable.
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.
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. PMID:27066108
Computer Modeling of Protocellular Functions: Peptide Insertion in Membranes
NASA Technical Reports Server (NTRS)
Rodriquez-Gomez, D.; Darve, E.; Pohorille, A.
2006-01-01
Lipid vesicles became the precursors to protocells by acquiring the capabilities needed to survive and reproduce. These include transport of ions, nutrients and waste products across cell walls and capture of energy and its conversion into a chemically usable form. In modem organisms these functions are carried out by membrane-bound proteins (about 30% of the genome codes for this kind of proteins). A number of properties of alpha-helical peptides suggest that their associations are excellent candidates for protobiological precursors of proteins. In particular, some simple a-helical peptides can aggregate spontaneously and form functional channels. This process can be described conceptually by a three-step thermodynamic cycle: 1 - folding of helices at the water-membrane interface, 2 - helix insertion into the lipid bilayer and 3 - specific interactions of these helices that result in functional tertiary structures. Although a crucial step, helix insertion has not been adequately studied because of the insolubility and aggregation of hydrophobic peptides. In this work, we use computer simulation methods (Molecular Dynamics) to characterize the energetics of helix insertion and we discuss its importance in an evolutionary context. Specifically, helices could self-assemble only if their interactions were sufficiently strong to compensate the unfavorable Free Energy of insertion of individual helices into membranes, providing a selection mechanism for protobiological evolution.
Motifs emerge from function in model gene regulatory networks
Burda, Z.; Krzywicki, A.; Martin, O. C.; Zagorski, M.
2011-01-01
Gene regulatory networks allow the control of gene expression patterns in living cells. The study of network topology has revealed that certain subgraphs of interactions or “motifs” appear at anomalously high frequencies. We ask here whether this phenomenon may emerge because of the functions carried out by these networks. Given a framework for describing regulatory interactions and dynamics, we consider in the space of all regulatory networks those that have prescribed functional capabilities. Markov Chain Monte Carlo sampling is then used to determine how these functional networks lead to specific motif statistics in the interactions. In the case where the regulatory networks are constrained to exhibit multistability, we find a high frequency of gene pairs that are mutually inhibitory and self-activating. In contrast, networks constrained to have periodic gene expression patterns (mimicking for instance the cell cycle) have a high frequency of bifan-like motifs involving four genes with at least one activating and one inhibitory interaction. PMID:21960444
Thienpont, Benedicte; Barata, Carlos; Raldúa, Demetrio
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)-KClO4 (NIS-inhibitor) dosed at a fixed ratio of EC10 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. PMID:23562343
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.
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. PMID:27479466
A Caenorhabditis elegans model for ether lipid biosynthesis and function[S
Shi, Xun; Tarazona, Pablo; Brock, Trisha J.; Browse, John; Feussner, Ivo; Watts, Jennifer L.
2016-01-01
Ether lipids are widespread in nature, and they are structurally and functionally important components of membranes. The roundworm, Caenorhabditis elegans, synthesizes numerous lipid species containing alkyl and alkenyl ether bonds. We isolated C. elegans strains carrying loss-of-function mutations in three genes encoding the proteins required for the initial three steps in the ether lipid biosynthetic pathway, FARD-1/FAR1, ACL-7/GNPAT, and ADS-1/AGPS. Analysis of the mutant strains show that they lack ether lipids, but possess the ability to alter their lipid composition in response to lack of ether lipids. We found that increases in de novo fatty acid synthesis and reduction of stearoyl- and palmitoyl-CoA desaturase activity, processes that are at least partially regulated transcriptionally, mediate the altered lipid composition in ether lipid-deficient mutants. Phenotypic analysis demonstrated the importance of ether lipids for optimal fertility, lifespan, survival at cold temperatures, and resistance to oxidative stress.Caenorhabditis PMID:26685325
An exactly solvable model of an oscillator with nonlinear coupling and zeros of Bessel functions
NASA Technical Reports Server (NTRS)
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.
Defining a Model for Mitochondrial Function in mESC Differentiation
Defining a Model for Mitochondrial Function in mESC DifferentiationDefining a Model for Mitochondrial Function in mESC Differentiation Differentiating embryonic stem cells (ESCs) undergo mitochondrial maturation leading to a switch from a system dependent upon glycolysis to a re...
Psychometric Properties on Lecturers' Beliefs on Teaching Function: Rasch Model Analysis
ERIC Educational Resources Information Center
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…
A Classroom Note on: Modeling Functions with the TI-83/84 Calculator
ERIC Educational Resources Information Center
Lubowsky, Jack
2011-01-01
In Pre-Calculus courses, students are taught the composition and combination of functions to model physical applications. However, when combining two or more functions into a single more complicated one, students may lose sight of the physical picture which they are attempting to model. A block diagram, or flow chart, in which each block…
RAPID ASSESSMENT OF URBAN WETLANDS: FUNCTIONAL ASSESSMENT MODEL DEVELOPMENT AND EVALUATION
The objective of this study was to test the ability of existing hydrogeomorphic (HGM) functional assessment models and our own proposed models to predict rates of nitrate production and removal, functions critical to water quality protection, in forested riparian wetlands in nort...
ERIC Educational Resources Information Center
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…
Functional scale-free networks in the two-dimensional Abelian sandpile model
NASA Astrophysics Data System (ADS)
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.
A Simple Model System to Demonstrate Antibody Structure and Functions.
ERIC Educational Resources Information Center
O'Kennedy, Richard
1991-01-01
A model that can be used to show the arrangement of light and heavy chains, disulfide linkages, domains, and subclass variations in antibodies is given. It can be constructed and modified to illustrate Fab, F(ab')2, and Fc fragments, single domain and bifunctional antibodies, and labeling of antibodies. (Author)
A Functional Model of Sensemaking in a Neurocognitive Architecture
Lebiere, Christian; 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. PMID:24302930
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. PMID:24302930
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.
A model for designing functionally gradient material joints
Jou, M.; Messler, R.W.; Orling, T.T.
1994-12-31
Joining of dissimilar materials into hybrid structures to meet severe design and service requirements is becoming more necessary and common. Joints between heat-resisting or refractory metals and refractory or corrosion resistant ceramics and intermetallics are especially in demand. Before resorting to a more complicated but versatile finite element analysis (FEA) model, a simpler, more user-friendly analytical layer-model based on a thin plate assumption was developed and tested. The model has been successfully used to design simple FGM joints between Ni-base superalloys or Mo and SiC, Ni{sub 3}Al or Al{sub 2}O{sub 3} using self-propagating high-temperature or pressurized composition synthesis for joining. Cases are presented to demonstrate capability for: (1) varying processing temperature excursions or service gradients; (2) varying overall joint thickness for a fixed number of uniform composition steps; (3) varying the number of uniform steps for a particular overall joint thickness; (4) varying the thickness and/or composition of individual steps for a constant overall thickness; and (5) altering the constitutive law for mixed-material composition steps. The model provides a useful joint design tool for process R&D.
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.
NASA Astrophysics Data System (ADS)
Jolivet, L.; Cohen, M.; Ruas, A.
2015-08-01
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 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.
Knock-out models reveal new aquaporin functions.
Verkman, Alan S
2009-01-01
Knockout mice have been informative in the discovery of unexpected biological functions of aquaporins. Knockout mice have confirmed the predicted roles of aquaporins in transepithelial fluid transport, as in the urinary concentrating mechanism and glandular fluid secretion. A less obvious, though predictable role of aquaporins is in tissue swelling under stress, as in the brain in stroke, tumor and infection. Phenotype analysis of aquaporin knockout mice has revealed several unexpected cellular roles of aquaporins whose mechanisms are being elucidated. Aquaporins facilitate cell migration, as seen in aquaporin-dependent tumor angiogenesis and tumor metastasis, by a mechanism that may involve facilitated water transport in lamellipodia of migrating cells. The ' aquaglyceroporins', aquaporins that transport both glycerol and water, regulate glycerol content in epidermis, fat and other tissues, and lead to a multiplicity of interesting consequences of gene disruption including dry skin, resistance to skin carcinogenesis, impaired cell proliferation and altered fat metabolism. An even more surprising role of a mammalian aquaporin is in neural signal transduction in the central nervous system. The many roles of aquaporins might be exploited for clinical benefit by modulation of aquaporin expression/function - as diuretics, and in the treatment of brain swelling, glaucoma, epilepsy, obesity and cancer. PMID:19096787
Functional modelling of a novel mutation in BBS5
2014-01-01
Background Bardet-Biedl syndrome (BBS) is an autosomal recessive ciliopathy disorder with 18 known causative genes (BBS1-18). The primary clinical features are renal abnormalities, rod-cone dystrophy, post-axial polydactyly, learning difficulties, obesity and male hypogonadism. Results We describe the clinical phenotype in three Saudi siblings in whom we have identified a novel mutation in exon 12 of BBS5 (c.966dupT; p.Ala323CysfsX57). This single nucleotide duplication creates a frame shift results in a predicted elongated peptide. Translation blocking Morpholino oligonucleotides were used to create zebrafish bbs5 morphants. Morphants displayed retinal layering defects, abnormal cardiac looping and dilated, cystic pronephric ducts with reduced cilia expression. Morphants also displayed significantly reduced dextran clearance via the pronephros compared to wildtype embryos, suggesting reduced renal function in morphants. The eye, kidney and heart defects reported in morphant zebrafish resemble the human phenotype of BBS5 mutations. The pathogenicity of the novel BBS5 mutation was determined. Mutant mRNA was unable to rescue pleiotropic phenotypes of bbs5 morphant zebrafish and in cell culture we demonstrate a mislocalisation of mutant BBS5 protein which fails to localise discretely with the basal body. Conclusions We conclude that this novel BBS5 mutation has a deleterious function that accounts for the multisystem ciliopathy phenotype seen in affected human patients. PMID:24559376
NASA Astrophysics Data System (ADS)
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.
Modeling the two-point correlation of the vector stream function
NASA Technical Reports Server (NTRS)
Oberlack, M.; Rogers, M. M.; Reynolds, W. C.
1994-01-01
A new model for the two-point vector stream function correlation has been developed using tensor invariant arguments and evaluated by the comparison of model predictions with DNS data for incompressible homogeneous turbulent shear flow. This two-point vector stream function model correlation can then be used to calculate the two-point velocity correlation function and other quantities useful in turbulence modeling. The model assumes that the two-point vector stream function correlation can be written in terms of the separation vector and a new tensor function that depends only on the magnitude of the separation vector. The model has a single free model coefficient, which has been chosen by comparison with the DNS data. The relative error of the model predictions of the two-point vector stream function correlation is only a few percent for a broad range of the model coefficient. Predictions of the derivatives of this correlation, which are of interest in turbulence modeling, may not be this accurate.
The stochastic model of F1-ATPase molecular motor functioning
NASA Astrophysics Data System (ADS)
Pogrebnaya, Aleksandra F.; Romanovsky, Yury M.; Tikhonov, Aleksander N.
2004-05-01
This work is devoted to the study of the energy characteristics of the F1ATPase-substrate complex. The results of calculations of the electrostatic energy in the enzyme-substrate complex are presented in the first part. In calculations, we take into account the electrostatic interactions between the charged groups of the substrate (MgATP) and reaction products (MgADP and Pi) and charged amino acid residues of the α3β3γ complex that correspond to various conformations of the enzyme. The hydrolysis of ATP in the catalytic site leads to coordinated conformational changes in α, β subunits and to ordered rotation of γ subunit located in the center of F1ATPase complex. The calculations show that the energetically favorable process involving MgATP binding at the catalytic site in the "open" conformation initiates γ subunit rotation followed by the hydrolysis in the other (tight) catalytic site. In the second part, we propose the simplest stochastic model describing the ordered rotation of γ subunit (the rotor of F1-ATPase molecular motor). In the model we take into account the electrostatic interaction using the results of the previous calculations. We employ experimentally obtained dynamic parameters. The model takes into account the thermal fluctuations of the bath and the random processes of the substrate binding and the escape of the reaction products.
Approaches to Modelling the Dynamical Activity of Brain Function Based on the Electroencephalogram
NASA Astrophysics Data System (ADS)
Liley, David T. J.; Frascoli, Federico
The brain is arguably the quintessential complex system as indicated by the patterns of behaviour it produces. Despite many decades of concentrated research efforts, we remain largely ignorant regarding the essential processes that regulate and define its function. While advances in functional neuroimaging have provided welcome windows into the coarse organisation of the neuronal networks that underlie a range of cognitive functions, they have largely ignored the fact that behaviour, and by inference brain function, unfolds dynamically. Modelling the brain's dynamics is therefore a critical step towards understanding the underlying mechanisms of its functioning. To date, models have concentrated on describing the sequential organisation of either abstract mental states (functionalism, hard AI) or the objectively measurable manifestations of the brain's ongoing activity (rCBF, EEG, MEG). While the former types of modelling approach may seem to better characterise brain function, they do so at the expense of not making a definite connection with the actual physical brain. Of the latter, only models of the EEG (or MEG) offer a temporal resolution well matched to the anticipated temporal scales of brain (mental processes) function. This chapter will outline the most pertinent of these modelling approaches, and illustrate, using the electrocortical model of Liley et al, how the detailed application of the methods of nonlinear dynamics and bifurcation theory is central to exploring and characterising their various dynamical features. The rich repertoire of dynamics revealed by such dynamical systems approaches arguably represents a critical step towards an understanding of the complexity of brain function.
Modeling the Near-Infrared Luminosity Function of Young Stellar Clusters
NASA Astrophysics Data System (ADS)
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.
Assessment of models for pedestrian dynamics with functional principal component analysis
NASA Astrophysics Data System (ADS)
Chraibi, Mohcine; Ensslen, Tim; Gottschalk, Hanno; Saadi, Mohamed; Seyfried, Armin
2016-06-01
Many agent based simulation approaches have been proposed for pedestrian flow. As such models are applied e.g. in evacuation studies, the quality and reliability of such models is of vital interest. Pedestrian trajectories are functional data and thus functional principal component analysis is a natural tool to assess the quality of pedestrian flow models beyond average properties. In this article we conduct functional Principal Component Analysis (PCA) for the trajectories of pedestrians passing through a bottleneck. In this way it is possible to assess the quality of the models not only on basis of average values but also by considering its fluctuations. We benchmark two agent based models of pedestrian flow against the experimental data using PCA average and stochastic features. Functional PCA proves to be an efficient tool to detect deviation between simulation and experiment and to assess quality of pedestrian models.
Contextual modeling of functional MR images with conditional random fields.
Wang, Yang; Rajapakse, Jagath C
2006-06-01
This paper presents a conditional random field (CRF) approach to fuse contextual dependencies in functional magnetic resonance imaging (fMRI) data for the detection of brain activation. The interactions among both activation (activated/inactive) labels and observed data of brain voxels are unified in a probabilistic framework based on the CRF, where the interaction strength can be adaptively adjusted in terms of the data similarity of neighboring sites. Compared to earlier detection methods, including statistical parametric mapping and Markov random field, the proposed method avoids the suppression of high frequency information and relaxes the strong assumption of conditional independence of observed data. Experimental results show that the proposed approach effectively integrates contextual constraints within the detection process and robustly detects brain activities from fMRI data.
The function of the respiratory supercomplexes: the plasticity model.
Acin-Perez, Rebeca; Enriquez, Jose A
2014-04-01
Mitochondria are important organelles not only as efficient ATP generators but also in controlling and regulating many cellular processes. Mitochondria are dynamic compartments that rearrange under stress response and changes in food availability or oxygen concentrations. The mitochondrial electron transport chain parallels these rearrangements to achieve an optimum performance and therefore requires a plastic organization within the inner mitochondrial membrane. This consists in a balanced distribution between free respiratory complexes and supercomplexes. The mechanisms by which the distribution and organization of supercomplexes can be adjusted to the needs of the cells are still poorly understood. The aim of this review is to focus on the functional role of the respiratory supercomplexes and its relevance in physiology. This article is part of a Special Issue entitled: Dynamic and ultrastructure of bioenergetic membranes and their components.
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.
Scattering phase function for particulates-in-water: modeling and validation
NASA Astrophysics Data System (ADS)
Sahu, Sanjay Kumar; Shanmugam, Palanisamy
2016-05-01
Scattering phase function plays a crucial role in studies and calculations based on radiative transfer theory in water as well as atmosphere. A model based on Mie theory is developed for estimating the particulates-in-water scattering phase function for forward angles (0.1° - 90°). Particle size distribution (PSD) slope (ξ) and bulk refractive index (n) are chosen as key inputs for this proposed model. The PSD slope can be estimated from the attenuation spectrum measured directly in-situ and the bulk refractive index can be calculated by an inversion model using measured backscattering ratio (BP) and PSD slope. The attenuation spectrum and backscattering ratio can be easily measured in-situ using commercially available instruments in real time. The entire range of forward angles is divided into two ranges and phase function is modeled separately in the ranges 0.1° - 5° and 5° - 90°, from numerically calculated Volume Scattering Function (VSF) using Mie theory. The division boundary is decided owing to the fact that the scattering phase functions, for different oceanic conditions, exhibit a change in slope at approximately 5°. Performance of the present model is evaluated by comparing with existing empirical and analytical models as well as measured phase functions. The proposed phase function model shows a considerable improvement upon existing models, and will have important applications in remote sensing applications and underwater studies.
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. PMID:25263989
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.
Boer-Mulders function of the pion in the MIT bag model
NASA Astrophysics Data System (ADS)
Lu, Zhun; Ma, Bo-Qiang; Zhu, Jiacai
2012-11-01
We apply the MIT bag model to study the Boer-Mulders function of the pion, a T-odd function that describes the transverse polarization distribution of the quark inside the pion. We simulate the effect of the gauge link through the “one-gluon-exchange” approximation. We consider both the quark helicity nonflip and double-flip contributions. The result in the MIT bag model is compared with those in the spectator models.
Integrated Medical Model (IMM) 4.0 Enhanced Functionalities
NASA Technical Reports Server (NTRS)
Young, M.; Keenan, A. B.; Saile, L.; Boley, L. A.; Walton, M. E.; Shah, R. V.; Kerstman, E. L.; Myers, J. G.
2015-01-01
The Integrated Medical Model is a probabilistic simulation model that uses input data on 100 medical conditions to simulate expected medical events, the resources required to treat, and the resulting impact to the mission for specific crew and mission characteristics. The newest development version of IMM, IMM v4.0, adds capabilities that remove some of the conservative assumptions that underlie the current operational version, IMM v3. While IMM v3 provides the framework to simulate whether a medical event occurred, IMMv4 also simulates when the event occurred during a mission timeline. This allows for more accurate estimation of mission time lost and resource utilization. In addition to the mission timeline, IMMv4.0 features two enhancements that address IMM v3 assumptions regarding medical event treatment. Medical events in IMMv3 are assigned the untreated outcome if any resource required to treat the event was unavailable. IMMv4 allows for partially treated outcomes that are proportional to the amount of required resources available, thus removing the dichotomous treatment assumption. An additional capability IMMv4 is to use an alternative medical resource when the primary resource assigned to the condition is depleted, more accurately reflecting the real-world system. The additional capabilities defining IMM v4.0the mission timeline, partial treatment, and alternate drug result in more realistic predicted mission outcomes. The primary model outcomes of IMM v4.0 for the ISS6 mission, including mission time lost, probability of evacuation, and probability of loss of crew life, are be compared to those produced by the current operational version of IMM to showcase enhanced prediction capabilities.
Nano-Transistor Modeling: Two Dimensional Green's Function Method
NASA Technical Reports Server (NTRS)
Svizhenko, Alexei; Anantram, M. P.; Govindan, T. R.; Biegel, Bryan
2001-01-01
Two quantum mechanical effects that impact the operation of nanoscale transistors are inversion layer energy quantization and ballistic transport. While the qualitative effects of these features are reasonably understood, a comprehensive study of device physics in two dimensions is lacking. Our work addresses this shortcoming and provides: (a) a framework to quantitatively explore device physics issues such as the source-drain and gate leakage currents, DIBL (Drain Induced Barrier Lowering), and threshold voltage shift due to quantization, and b) a means of benchmarking quantum corrections to semiclassical models (such as density-gradient and quantum-corrected MEDICI).
Modelling of an oesophageal electrode for cardiac function tomography.
Tehrani, J Nasehi; Jin, C; McEwan, A L
2012-01-01
There is a need in critical care units for continuous cardiopulmonary monitoring techniques. ECG gated electrical impedance tomography is able to localize the impedance variations occurring during the cardiac cycle. This method is a safe, inexpensive and potentially fast technique for cardiac output imaging but the spatial resolution is presently low, particularly for central locations such as the heart. Many parameters including noise deteriorate the reconstruction result. One of the main obstacles in cardiac imaging at the heart location is the high impedance of lungs and muscles on the dorsal and posterior side of body. In this study we are investigating improvements of the measurement and initial conductivity estimation of the internal electrode by modelling an internal electrode inside the esophagus. We consider 16 electrodes connected around a cylindrical mesh. With the random noise level set near 0.05% of the signal we evaluated the Graz consensus reconstruction algorithm for electrical impedance tomography. The modelling and simulation results showed that the quality of the target in reconstructed images was improved by up to 5 times for amplitude response, position error, resolution, shape deformation and ringing effects with perturbations located in cardiac related positions when using an internal electrode.
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
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
Aircraft/Air Traffic Management Functional Analysis Model. Version 2.0; User's Guide
NASA Technical Reports Server (NTRS)
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.
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.
Molecular modelling of miraculin: Structural analyses and functional hypotheses.
Paladino, Antonella; Costantini, Susan; Colonna, Giovanni; Facchiano, Angelo M
2008-02-29
Miraculin is a plant protein that displays the peculiar property of modifying taste by swiching sour into a sweet taste. Its monomer is flavourless at all pH as well as at high concentration; the dimer form elicits its taste-modifying activity at acidic pH; a tetrameric form is also reported as active. Two histidine residues, located in exposed regions, are the main responsible of miraculin activity, as demonstrated by mutagenesis studies. Since structural data of miraculin are not available, we have predicted its three-dimensional structure and simulated both its dimer and tetramer forms by comparative modelling and molecular docking techniques. Finally, molecular dynamics simulations at different pH conditions have indicated that at acidic pH the dimer assumes a widely open conformation, in agreement with the hypotheses coming from other studies. PMID:18158914
Mapping baroreceptor function to genome: a mathematical modeling approach.
Kendziorski, C M; Cowley, A W; Greene, A S; Salgado, H C; Jacob, H J; Tonellato, P J
2002-01-01
To gain information about the genetic basis of a complex disease such as hypertension, blood pressure averages are often obtained and used as phenotypes in genetic mapping studies. In contrast, direct measurements of physiological regulatory mechanisms are not often obtained, due in large part to the time and expense required. As a result, little information about the genetic basis of physiological controlling mechanisms is available. Such information is important for disease diagnosis and treatment. In this article, we use a mathematical model of blood pressure to derive phenotypes related to the baroreceptor reflex, a short-term controller of blood pressure. The phenotypes are then used in a quantitative trait loci (QTL) mapping study to identify a potential genetic basis of this controller. PMID:11973321
A Note on the Item Information Function of the Four-Parameter Logistic Model
ERIC Educational Resources Information Center
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…
ERIC Educational Resources Information Center
Patarapichayatham, Chalie; Kamata, Akihito; Kanjanawasee, Sirichai
2012-01-01
Model specification issues on the cross-level two-way differential item functioning model were previously investigated by Patarapichayatham et al. (2009). Their study clarified that an incorrect model specification can easily lead to biased estimates of key parameters. The objective of this article is to provide further insights on the issue by…
Two Models for Exploring the Anti-predator Function of Eyespots.
ERIC Educational Resources Information Center
Cundy, J. M.; Allen, J. A.
1988-01-01
Describes two working models of moths that can be used to test the eyespot function as an aversive property. Uses simple mechanical and electrical models as the "moths" and wild birds as the predators. Includes diagrams, methods, models, validation statements, and a discussion. (RT)
RIM: A Random Item Mixture Model to Detect Differential Item Functioning
ERIC Educational Resources Information Center
Frederickx, Sofie; Tuerlinckx, Francis; De Boeck, Paul; Magis, David
2010-01-01
In this paper we present a new methodology for detecting differential item functioning (DIF). We introduce a DIF model, called the random item mixture (RIM), that is based on a Rasch model with random item difficulties (besides the common random person abilities). In addition, a mixture model is assumed for the item difficulties such that the…
ERIC Educational Resources Information Center
Rabe-Hesketh, Sophia; Toulopoulou, Timothea; Murray, Robin M.
2001-01-01
Describes multilevel modeling of cognitive function in 70 subjects with schizophrenia, 115 of their healthy first-degree relatives, and 66 controls. Describes four methodological issues arising during data analysis and how multilevel modeling can be used, and discusses some cautions in the use of multilevel models. (SLD)
NASA Astrophysics Data System (ADS)
Wirth, Erin A.; Long, Maureen D.; Moriarty, John C.
2016-10-01
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 to 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 tradeoffs - 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.
Prestat, Emmanuel; David, Maude M.; Hultman, Jenni; Ta , Neslihan; Lamendella, Regina; Dvornik, Jill; Mackelprang, Rachel; Myrold, David D.; Jumpponen, Ari; Tringe, Susannah G.; Holman, Elizabeth; Mavromatis, Konstantinos; Jansson, Janet K.
2014-09-26
A new functional gene database, FOAM (Functional Ontology Assignments for Metagenomes), was developed to screen environmental metagenomic sequence datasets. FOAM provides a new functional ontology dedicated to classify gene functions relevant to environmental microorganisms based on Hidden Markov Models (HMMs). Sets of aligned protein sequences (i.e. ‘profiles’) were tailored to a large group of target KEGG Orthologs (KOs) from which HMMs were trained. The alignments were checked and curated to make them specific to the targeted KO. Within this process, sequence profiles were enriched with the most abundant sequences available to maximize the yield of accurate classifier models. An associated functional ontology was built to describe the functional groups and hierarchy. FOAM allows the user to select the target search space before HMM-based comparison steps and to easily organize the results into different functional categories and subcategories. FOAM is publicly available at http://portal.nersc.gov/project/m1317/FOAM/.
Prestat, Emmanuel; David, Maude M; Hultman, Jenni; Taş, Neslihan; Lamendella, Regina; Dvornik, Jill; Mackelprang, Rachel; Myrold, David D; Jumpponen, Ari; Tringe, Susannah G; Holman, Elizabeth; Mavromatis, Konstantinos; Jansson, Janet K
2014-10-29
A new functional gene database, FOAM (Functional Ontology Assignments for Metagenomes), was developed to screen environmental metagenomic sequence datasets. FOAM provides a new functional ontology dedicated to classify gene functions relevant to environmental microorganisms based on Hidden Markov Models (HMMs). Sets of aligned protein sequences (i.e. 'profiles') were tailored to a large group of target KEGG Orthologs (KOs) from which HMMs were trained. The alignments were checked and curated to make them specific to the targeted KO. Within this process, sequence profiles were enriched with the most abundant sequences available to maximize the yield of accurate classifier models. An associated functional ontology was built to describe the functional groups and hierarchy. FOAM allows the user to select the target search space before HMM-based comparison steps and to easily organize the results into different functional categories and subcategories. FOAM is publicly available at http://portal.nersc.gov/project/m1317/FOAM/.
Effect of structure on function in model nerve nets.
Anninos, P A; Elul, R
1974-01-01
A theoretical analysis has been made on the effect of the pattern of interneuronal connectivity in model nerve nets on the activity of these nets. Two types of nets have been investigated: one in which the likelihood of a connection between a given neuron and any other element in the net is given by a Poisson probability distribution, and a second type in which the pattern of interconnection follows a Gaussian distribution. An analytical treatment is presented of the equations for noiseless nets in these two conditions. The principal result is that nets with Poisson connectivity law are activated by extraneous firing of a single neuron and continue in spontaneous activity indefinitely. On the other hand, similar nets in which the connections are, however, distributed according to a normal connectivity law, exhibit a definite threshold and produce spontaneous activity only subsequent to extraneous activation of a substantial fraction of the population. Moreover, spontaneous activity in Gaussian nets, but not in Poisson nets, becomes extinguished if the number of active neurons falls below the critical threshold. Some neuroanatomical implications are discussed which suggest that the pyramidal system of the cerebral cortex and other neuronal systems histologically characterized by large numbers of synapses per neuron may incorporate a Gaussian connectivity law, whereas a Poisson law may be characteristic of these cortical layers and nuclei primarily containing granule cells.
Network model of fear extinction and renewal functional pathways.
Bruchey, A K; Shumake, J; Gonzalez-Lima, F
2007-03-16
The objective of this study was to examine the opposite behavior responses of conditioned fear extinction and renewal and how they are represented by network interactions between brain regions. This work is a continuation of a series of brain mapping studies of various inhibitory phenomena, including conditioned inhibition, blocking and extinction. A tone-footshock fear conditioning paradigm in rats was used, followed by extinction and testing in two different contexts. Fluorodeoxyglucose autoradiography was used to compare mean regional brain activity and interregional correlations resulting from the presentation of the extinguished tone in or out of the extinction context. A confirmatory structural equation model, constructed from a neural network proposed to underlie fear extinction, showed a reversal from negative regional interactions during extinction recall to positive interactions during fear renewal. Additionally, the magnitude of direct effects was different between groups, reflecting a change in the strength of the influences conveyed through those pathways. The results suggest that the extinguished tone encountered outside of the extinction context recruits auditory and limbic areas, which in turn influence the interactions of the infralimbic cortex with the amygdala and ventrolateral periaqueductal gray. Interestingly, the results also suggest that two independent pathways influence conditioned freezing: one from the central amygdaloid nucleus and the other from the infralimbic cortex directly to the ventrolateral periaqueductal gray.
The polarized structure function of the nucleons with a non-extensive statistical quark model
Trevisan, Luis A.; Mirez, Carlos
2013-05-06
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 {Delta}u and {Delta}d of the polarized functions.
ERIC Educational Resources Information Center
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…
Customer short term load forecasting by using ARIMA transfer function model
Cho, M.Y.; Hwang, J.C.; Chen, C.S.
1995-12-31
Short-term load forecasting plays an important role in electric power system operation and planning. An accurate load forecasting not only reduces the generation cost in a power system, but also provides a good principle of effective operation. In this paper, the ARIMA model and transfer function model are applied to the short-term load forecasting by considering weather-load relationship. For four types of customer in Taiwan power (Taipower) system, residential load, commercial load, office load and industrial load customers, the summer ARIMA model transfer function model have been derived to proceed the short-term load forecasting during one week. To demonstrate the effectiveness of the proposed method, this paper compares the results of the transfer function model and the univariate ARIMA model with conventional regression. Besides, the transfer function model`s accuracy of the load forecast on weekday and weekend is thoroughly investigated. To improve the accuracy level of load forecast, the temperature effect is considered in the transfer function. According to the short-term load forecasting for these four customer classes, it is concluded that the proposed method can achieve better accuracy of load forecast than ARIMA model by considering the causality between power consumption and temperature.
A hypothetical universal model of cerebellar function: reconsideration of the current dogma.
Magal, Ari
2013-10-01
The cerebellum is commonly studied in the context of the classical eyeblink conditioning model, which attributes an adaptive motor function to cerebellar learning processes. This model of cerebellar function has quite a few shortcomings and may in fact be somewhat deficient in explaining the myriad functions attributed to the cerebellum, functions ranging from motor sequencing to emotion and cognition. The involvement of the cerebellum in these motor and non-motor functions has been demonstrated in both animals and humans in electrophysiological, behavioral, tracing, functional neuroimaging, and PET studies, as well as in clinical human case studies. A closer look at the cerebellum's evolutionary origin provides a clue to its underlying purpose as a tool which evolved to aid predation rather than as a tool for protection. Based upon this evidence, an alternative model of cerebellar function is proposed, one which might more comprehensively account both for the cerebellum's involvement in a myriad of motor, affective, and cognitive functions and for the relative simplicity and ubiquitous repetitiveness of its circuitry. This alternative model suggests that the cerebellum has the ability to detect coincidences of events, be they sensory, motor, affective, or cognitive in nature, and, after having learned to associate these, it can then trigger (or "mirror") these events after having temporally adjusted their onset based on positive/negative reinforcement. The model also provides for the cerebellum's direction of the proper and uninterrupted sequence of events resulting from this learning through the inhibition of efferent structures (as demonstrated in our lab).
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.
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.
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
Troitskaya, Yuliya; Abramov, Victor; Ermoshkin, Alexey; Zuikova, Emma; Kazakov, Vassily; Sergeev, Daniil; Kandaurov, Alexandr
2014-05-01
Satellite remote sensing is one of the main techniques of monitoring severe weather conditions over the ocean. The principal difficulty of the existing algorithms of retrieving wind based on dependence of microwave backscattering cross-section on wind speed (Geophysical Model Function, GMF) is due to its saturation at winds exceeding 25 - 30 m/s. Recently analysis of dual- and quad-polarization C-band radar return measured from satellite Radarsat-2 suggested that the cross-polarized radar return has much higher sensitivity to the wind speed than co-polarized back scattering [1] and conserved sensitivity to wind speed at hurricane conditions [2]. Since complete collocation of these data was not possible and time difference in flight legs and SAR images acquisition was up to 3 hours, these two sets of data were compared in [2] only statistically. The main purpose of this paper is investigation of the functional dependence of cross-polarized radar cross-section on the wind speed in laboratory experiment. Since cross-polarized radar return is formed due to scattering at small-scale structures of the air-sea interface (short-crested waves, foam, sprays, etc), which are well reproduced in laboratory conditions, then the approach based on laboratory experiment on radar scattering of microwaves at the water surface under hurricane wind looks feasible. The experiments were performed in the Wind-wave flume located on top of the Large Thermostratified Tank of the Institute of Applied Physics, where the airflow was produced in the flume with the straight working part of 10 m and operating cross section 0.40?0.40 sq. m, the axis velocity can be varied from 5 to 25 m/s. Microwave measurements were carried out by a coherent Doppler X-band (3.2 cm) scatterometer with the consequent receive of linear polarizations. Experiments confirmed higher sensitivity to the wind speed of the cross-polarized radar return. Simultaneously parameters of the air flow in the turbulent boundary layer
Orwin, Kate H; Ostle, Nick; Wilby, Andrew; Bardgett, Richard D
2014-03-01
Ecosystems provide multiple services upon which humans depend. Understanding the drivers of the ecosystem functions that support these services is therefore important. Much research has investigated how species richness influences functioning, but we lack knowledge of how other community attributes affect ecosystem functioning. Species evenness, species spatial arrangement, and the identity of dominant species are three attributes that could affect ecosystem functioning, by altering the relative abundance of functional traits and the probability of synergistic species interactions such as facilitation and complementary resource use. We tested the effect of these three community attributes and their interactions on ecosystem functions over a growing season, using model grassland communities consisting of three plant species from three functional groups: a grass (Anthoxanthum odoratum), a forb (Plantago lanceolata), and a N-fixing forb (Lotus corniculatus). We measured multiple ecosystem functions that support ecosystem services, including ecosystem gas exchange, water retention, C and N loss in leachates, and plant biomass production. Species evenness and dominant species identity strongly influenced the ecosystem functions measured, but spatial arrangement had few effects. By the end of the growing season, evenness consistently enhanced ecosystem functioning and this effect occurred regardless of dominant species identity. The identity of the dominant species under which the highest level of functioning was attained varied across the growing season. Spatial arrangement had the weakest effect on functioning, but interacted with dominant species identity to affect some functions. Our results highlight the importance of understanding the role of multiple community attributes in driving ecosystem functioning. PMID:24213721
Orwin, Kate H; Ostle, Nick; Wilby, Andrew; Bardgett, Richard D
2014-03-01
Ecosystems provide multiple services upon which humans depend. Understanding the drivers of the ecosystem functions that support these services is therefore important. Much research has investigated how species richness influences functioning, but we lack knowledge of how other community attributes affect ecosystem functioning. Species evenness, species spatial arrangement, and the identity of dominant species are three attributes that could affect ecosystem functioning, by altering the relative abundance of functional traits and the probability of synergistic species interactions such as facilitation and complementary resource use. We tested the effect of these three community attributes and their interactions on ecosystem functions over a growing season, using model grassland communities consisting of three plant species from three functional groups: a grass (Anthoxanthum odoratum), a forb (Plantago lanceolata), and a N-fixing forb (Lotus corniculatus). We measured multiple ecosystem functions that support ecosystem services, including ecosystem gas exchange, water retention, C and N loss in leachates, and plant biomass production. Species evenness and dominant species identity strongly influenced the ecosystem functions measured, but spatial arrangement had few effects. By the end of the growing season, evenness consistently enhanced ecosystem functioning and this effect occurred regardless of dominant species identity. The identity of the dominant species under which the highest level of functioning was attained varied across the growing season. Spatial arrangement had the weakest effect on functioning, but interacted with dominant species identity to affect some functions. Our results highlight the importance of understanding the role of multiple community attributes in driving ecosystem functioning.
Predicting predation through prey ontogeny using size-dependent functional response models.
McCoy, Michael W; Bolker, Benjamin M; Warkentin, Karen M; Vonesh, James R
2011-06-01
The functional response is a critical link between consumer and resource dynamics, describing how a consumer's feeding rate varies with prey density. Functional response models often assume homogenous prey size and size-independent feeding rates. However, variation in prey size due to ontogeny and competition is ubiquitous, and predation rates are often size dependent. Thus, functional responses that ignore prey size may not effectively predict predation rates through ontogeny or in heterogeneous populations. Here, we use short-term response-surface experiments and statistical modeling to develop and test prey size-dependent functional responses for water bugs and dragonfly larvae feeding on red-eyed treefrog tadpoles. We then extend these models through simulations to predict mortality through time for growing prey. Both conventional and size-dependent functional response models predicted average overall mortality in short-term mixed-cohort experiments, but only the size-dependent models accurately captured how mortality was spread across sizes. As a result, simulations that extrapolated these results through prey ontogeny showed that differences in size-specific mortality are compounded as prey grow, causing predictions from conventional and size-dependent functional response models to diverge dramatically through time. Our results highlight the importance of incorporating prey size when modeling consumer-prey dynamics in size-structured, growing prey populations. PMID:21597252
Li, Chunfeng; Wu, Aiping; Peng, Yousong; Wang, Jingfeng; Guo, Yang; Chen, Zhigao; Zhang, Hong; Wang, Yongqiang; Dong, Jiuhong; Wang, Lulan; Qin, F. Xiao-Feng; Cheng, Genhong; Deng, Tao; Jiang, Taijiao
2014-01-01
The influenza virus PB1 protein is the core subunit of the heterotrimeric polymerase complex (PA, PB1 and PB2) in which PB1 is responsible for catalyzing RNA polymerization and binding to the viral RNA promoter. Among the three subunits, PB1 is the least known subunit so far in terms of its structural information. In this work, by integrating template-based structural modeling approach with all known sequence and functional information about the PB1 protein, we constructed a modeled structure of PB1. Based on this model, we performed mutagenesis analysis for the key residues that constitute the RNA template binding and catalytic (TBC) channel in an RNP reconstitution system. The results correlated well with the model and further identified new residues of PB1 that are critical for RNA synthesis. Moreover, we derived 5 peptides from the sequence of PB1 that form the TBC channel and 4 of them can inhibit the viral RNA polymerase activity. Interestingly, we found that one of them named PB1(491–515) can inhibit influenza virus replication by disrupting viral RNA promoter binding activity of polymerase. Therefore, this study has not only deepened our understanding of structure-function relationship of PB1, but also promoted the development of novel therapeutics against influenza virus. PMID:25424584
NASA Astrophysics Data System (ADS)
Still, C. J.; Griffith, D.; Edwards, E.; Forrestel, E.; Lehmann, C.; Anderson, M.; Craine, J.; Pau, S.; Osborne, C.
2014-12-01
Variation in plant species traits, such as photosynthetic and hydraulic properties, can indicate vulnerability or resilience to climate change, and feed back to broad-scale spatial and temporal patterns in biogeochemistry, demographics, and biogeography. Yet, predicting how vegetation will respond to future environmental changes is severely limited by the inability of our models to represent species-level trait variation in processes and properties, as current generation process-based models are mostly based on the generalized and abstracted concept of plant functional types (PFTs) which were originally developed for hydrological modeling. For example, there are close to 11,000 grass species, but most vegetation models have only a single C4 grass and one or two C3 grass PFTs. However, while species trait databases are expanding rapidly, they have been produced mostly from unstructured research, with a focus on easily researched traits that are not necessarily the most important for determining plant function. Additionally, implementing realistic species-level trait variation in models is challenging. Combining related and ecologically similar species in these models might ameliorate this limitation. Here we argue for an intermediate, lineage-based approach to PFTs, which draws upon recent advances in gene sequencing and phylogenetic modeling, and where trait complex variations and anatomical features are constrained by a shared evolutionary history. We provide an example of this approach with grass lineages that vary in photosynthetic pathway (C3 or C4) and other functional and structural traits. We use machine learning approaches and geospatial databases to infer the most important environmental controls and climate niche variation for the distribution of grass lineages, and utilize a rapidly expanding grass trait database to demonstrate examples of lineage-based grass PFTs. For example, grasses in the Andropogoneae are typically tall species that dominate wet and
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. PMID:27668017
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.
An orbital-overlap model for minimal work functions of cesiated metal surfaces.
Chou, Sharon H; Voss, Johannes; Bargatin, Igor; Vojvodic, Aleksandra; Howe, Roger T; Abild-Pedersen, Frank
2012-11-01
We introduce a model for the effect of cesium adsorbates on the work function of transition metal surfaces. The model builds on the classical point-dipole equation by adding exponential terms that characterize the degree of orbital overlap between the 6s states of neighboring cesium adsorbates and its effect on the strength and orientation of electric dipoles along the adsorbate-substrate interface. The new model improves upon earlier models in terms of agreement with the work function-coverage curves obtained via first-principles calculations based on density functional theory. All the cesiated metal surfaces have optimal coverages between 0.6 and 0.8 monolayers, in accordance with experimental data. Of all the cesiated metal surfaces that we have considered, tungsten has the lowest minimum work function, also in accordance with experiments.
The Use of Haemoglobin as a Model for Teaching the Relationship Between Structure and Function
ERIC Educational Resources Information Center
Diggins, F. W. E.
1974-01-01
Presents information about an atomic model of haemoglobin and describes the oxygenation mechanism as a teaching principle to illustrate the relationship between structure and function at the molecular level. (Author/PEB)
ERIC Educational Resources Information Center
Herndon, Mary Anne
1978-01-01
In a model of the functioning of short term memory, the encoding of information for subsequent storage in long term memory is simulated. In the encoding process, semantically equivalent paragraphs are detected for recombination into a macro information unit. (HOD)
Bifurcation analysis of models with uncertain function specification: how should we proceed?
Adamson, M W; Morozov, A Yu
2014-05-01
When we investigate the bifurcation structure of models of natural phenomena, we usually assume that all model functions are mathematically specified and that the only existing uncertainty is with respect to the parameters of these functions. In this case, we can split the parameter space into domains corresponding to qualitatively similar dynamics, separated by bifurcation hypersurfaces. On the other hand, in the biological sciences, the exact shape of the model functions is often unknown, and only some qualitative properties of the functions can be specified: mathematically, we can consider that the unknown functions belong to a specific class of functions. However, the use of two different functions belonging to the same class can result in qualitatively different dynamical behaviour in the model and different types of bifurcation. In the literature, the conventional way to avoid such ambiguity is to narrow the class of unknown functions, which allows us to keep patterns of dynamical behaviour consistent for varying functions. The main shortcoming of this approach is that the restrictions on the model functions are often given by cumbersome expressions and are strictly model-dependent: biologically, they are meaningless. In this paper, we suggest a new framework (based on the ODE paradigm) which allows us to investigate deterministic biological models in which the mathematical formulation of some functions is unspecified except for some generic qualitative properties. We demonstrate that in such models, the conventional idea of revealing a concrete bifurcation structure becomes irrelevant: we can only describe bifurcations with a certain probability. We then propose a method to define the probability of a bifurcation taking place when there is uncertainty in the parameterisation in our model. As an illustrative example, we consider a generic predator-prey model where the use of different parameterisations of the logistic-type prey growth function can result in
NASA Astrophysics Data System (ADS)
Zolotarev, Vladimir A.
2009-04-01
Functional models are constructed for commutative systems \\{A_1,A_2\\} of bounded linear non-self-adjoint operators which do not contain dissipative operators (which means that \\xi_1A_1+\\xi_2A_2 is not a dissipative operator for any \\xi_1, \\xi_2\\in\\mathbb{R}). A significant role is played here by the de Branges transform and the function classes occurring in this context. Classes of commutative systems of operators \\{A_1,A_2\\} for which such a construction is possible are distinguished. Realizations of functional models in special spaces of meromorphic functions on Riemann surfaces are found, which lead to reasonable analogues of de Branges spaces on these Riemann surfaces. It turns out that the functions E(p) and \\widetilde E(p) determining the order of growth in de Branges spaces on Riemann surfaces coincide with the well-known Baker-Akhiezer functions. Bibliography: 11 titles.
Diamond, Solomon Gilbert; Perdue, Katherine L.; Boas, David A.
2009-01-01
Functional neuroimaging techniques such as functional magnetic resonance imaging (fMRI) and near-infrared spectroscopy (NIRS) can be used to isolate an evoked response to a stimulus from significant background physiological fluctuations. Data analysis approaches typically use averaging or linear regression to remove this physiological baseline with varying degrees of success. Biophysical model-based analysis of the functional hemodynamic response has also been advanced previously with the Balloon and Windkessel models. In the present work, a biophysical model of systemic and cerebral circulation and gas exchange is applied to resting state NIRS neuroimaging data from 10 human subjects. The model further includes dynamic cerebral autoregulation, which modulates the cerebral arteriole compliance to control cerebral blood flow. This biophysical model allows for prediction, from noninvasive blood pressure measurements, of the background hemodynamic fluctuations in the systemic and cerebral circulations. Significantly higher correlations with the NIRS data were found using the biophysical model predictions compared to blood pressure regression and compared to transfer function analysis (multifactor ANOVA, p<0.0001). This finding supports the further development and use of biophysical models for removing baseline activity in functional neuroimaging analysis. Future extensions of this work could model changes in cerebrovascular physiology that occur during development, aging and disease. PMID:19442671
Binder model system to be used for determination of prepolymer functionality
NASA Technical Reports Server (NTRS)
Martinelli, F. J.; Hodgkin, J. H.
1971-01-01
Development of a method for determining the functionality distribution of prepolymers used for rocket binders is discussed. Research has been concerned with accurately determining the gel point of a model polyester system containing a single trifunctional crosslinker, and the application of these methods to more complicated model systems containing a second trifunctional crosslinker, monofunctional ingredients, or a higher functionality crosslinker. Correlations of observed with theoretical gel points for these systems would allow the methods to be applied directly to prepolymers.
ERIC Educational Resources Information Center
Lee, Donghyung; Riccio, Cynthia A.; Hynd, George W.
2004-01-01
The role of executive functions in attention deficit hyperactivity disorder (ADHD) varies considerably depending on the models of ADHD. We examined the interrelationship of two major executive functions (i.e., inhibition and working memory) with behavioral, emotional, and school problems in a group of children who had a comprehensive…
Nonperturbative spectral-density function for the Anderson model at arbitrary temperatures
NASA Technical Reports Server (NTRS)
Neal, Henry L.
1991-01-01
Using a nonperturbative self-energy solution for the nondegenerate Anderson model, the temperature-dependent spectral-density function is calculated in the symmetric limit. The function is found to give reliable results for all values of the parameter u and inverse temperature beta.
Understanding Complex Natural Systems by Articulating Structure-Behavior-Function Models
ERIC Educational Resources Information Center
Vattam, Swaroop S.; Goel, Ashok K.; Rugaber, Spencer; Hmelo-Silver, Cindy E.; Jordan, Rebecca; Gray, Steven; Sinha, Suparna
2011-01-01
Artificial intelligence research on creative design has led to Structure-Behavior-Function (SBF) models that emphasize functions as abstractions for organizing understanding of physical systems. Empirical studies on understanding complex systems suggest that novice understanding is shallow, typically focusing on their visible structures and…
NASA Astrophysics Data System (ADS)
Liu, Jintao; Chen, Xi; Zhang, Xingnan; Hoagland, Kyle D.
2012-04-01
Recently developed hillslope storage dynamics theory can represent the essential physical behavior of a natural system by accounting explicitly for the plan shape of a hillslope in an elegant and simple way. As a result, this theory is promising for improving catchment-scale hydrologic modeling. In this study, grid digital elevation model (DEM) based algorithms for determination of hillslope geometric characteristics (e.g., hillslope units and width functions in hillslope storage dynamics models) are presented. This study further develops a method for hillslope partitioning, established by Fan and Bras (1998), by applying it on a grid network. On the basis of hillslope unit derivation, a flow distance transforms method (TD∞) is suggested in order to decrease the systematic error of grid DEM-based flow distance calculation caused by flow direction approximation to streamlines. Hillslope width transfer functions are then derived to convert the probability density functions of flow distance into hillslope width functions. These algorithms are applied and evaluated on five abstract hillslopes, and detailed tests and analyses are carried out by comparing the derivation results with theoretical width functions. The results demonstrate that the TD∞ improves estimations of the flow distance and thus hillslope width function. As the proposed procedures are further applied in a natural catchment, we find that the natural hillslope width function can be well fitted by the Gaussian function. This finding is very important for applying the newly developed hillslope storage dynamics models in a real catchment.
Uga, Minako; Dan, Ippeita; Sano, Toshifumi; Dan, Haruka; Watanabe, Eiju
2014-01-01
Abstract. An increasing number of functional near-infrared spectroscopy (fNIRS) studies utilize a general linear model (GLM) approach, which serves as a standard statistical method for functional magnetic resonance imaging (fMRI) data analysis. While fMRI solely measures the blood oxygen level dependent (BOLD) signal, fNIRS measures the changes of oxy-hemoglobin (oxy-Hb) and deoxy-hemoglobin (deoxy-Hb) signals at a temporal resolution severalfold higher. This suggests the necessity of adjusting the temporal parameters of a GLM for fNIRS signals. Thus, we devised a GLM-based method utilizing an adaptive hemodynamic response function (HRF). We sought the optimum temporal parameters to best explain the observed time series data during verbal fluency and naming tasks. The peak delay of the HRF was systematically changed to achieve the best-fit model for the observed oxy- and deoxy-Hb time series data. The optimized peak delay showed different values for each Hb signal and task. When the optimized peak delays were adopted, the deoxy-Hb data yielded comparable activations with similar statistical power and spatial patterns to oxy-Hb data. The adaptive HRF method could suitably explain the behaviors of both Hb parameters during tasks with the different cognitive loads during a time course, and thus would serve as an objective method to fully utilize the temporal structures of all fNIRS data. PMID:26157973
NASA Astrophysics Data System (ADS)
Stradi, Daniele; Martinez, Umberto; Blom, Anders; Brandbyge, Mads; Stokbro, Kurt
2016-04-01
Metal-semiconductor contacts are a pillar of modern semiconductor technology. Historically, their microscopic understanding has been hampered by the inability of traditional analytical and numerical methods to fully capture the complex physics governing their operating principles. Here we introduce an atomistic approach based on density functional theory and nonequilibrium Green's function, which includes all the relevant ingredients required to model realistic metal-semiconductor interfaces and allows for a direct comparison between theory and experiments via I -Vbias curve simulations. We apply this method to characterize an Ag/Si interface relevant for photovoltaic applications and study the rectifying-to-Ohmic transition as a function of the semiconductor doping. We also demonstrate that the standard "activation energy" method for the analysis of I -Vbias data might be inaccurate for nonideal interfaces as it neglects electron tunneling, and that finite-size atomistic models have problems in describing these interfaces in the presence of doping due to a poor representation of space-charge effects. Conversely, the present method deals effectively with both issues, thus representing a valid alternative to conventional procedures for the accurate characterization of metal-semiconductor interfaces.
A model for the probability density function of downwelling irradiance under ocean waves.
Shen, Meng; Xu, Zao; Yue, Dick K P
2011-08-29
We present a statistical model that analytically quantifies the probability density function (PDF) of the downwelling light irradiance under random ocean waves modeling the surface as independent and identically distributed flat facets. The model can incorporate the separate effects of surface short waves and volume light scattering. The theoretical model captures the characteristics of the PDF, from skewed to near-Gaussian shape as the depth increases from shallow to deep water. The model obtains a closed-form asymptotic for the probability that diminishes at a rate between exponential and Gaussian with increasing extreme values. The model is validated by comparisons with existing field measurements and Monte Carlo simulation.
Event-related functional magnetic resonance imaging: modelling, inference and optimization.
Josephs, O; Henson, R N
1999-01-01
Event-related functional magnetic resonance imaging is a recent and popular technique for detecting haemodynamic responses to brief stimuli or events. However, the design of event-related experiments requires careful consideration of numerous issues of measurement, modelling and inference. Here we review these issues, with particular emphasis on the use of basis functions within a general linear modelling framework to model and make inferences about the haemodynamic response. With these models in mind, we then consider how the properties of functional magnetic resonance imaging data determine the optimal experimental design for a specific hypothesis, in terms of stimulus ordering and interstimulus interval. Finally, we illustrate various event-related models with examples from recent studies. PMID:10466147
Evaluation of a functional model for simulating boron transport in soil
Corwin, D.L.; Goldberg, S.; David, A.
1999-10-01
There has been renewed interest in the application of functional models to the transport of nonpoint source pollutants at polypedon and watershed scales because of the ease of their coupling to a geographic information system and to the accepted organizational hierarchy of pedogenetic modeling approaches. However, very little work has been done to evaluate the performance of a functional transient-state model for the transport of a reactive solute over an extensive study period. Subsequently, the functional model TETrans (Trace Element Transport) was evaluated for model performance with boron (B) transport data collected from a meso-scale soil lysimeter column over a 1,000-day study period. Because the ability to simulate water flow has been evaluated previously for TETrans, the focus of this evaluation centered around the performance of various functional models of B adsorption used as subroutines within the TETrans model, including the (1) Freundlich, (2) kinetic Freundlich, (3) Langmuir, (4) temperature-dependent Langmuir, and (5) pH-dependent Keren adsorption isotherm equations. Model performance was evaluated with statistical functions, specifically the Average Absolute Prediction Error, the Root Mean Square Error, the Reduced Error Estimate and the Coefficient of Residual Mass, and graphic displays of observed and predicted B concentration profiles. Even though no single adsorption isotherm equation, when coupled to TETrans, could be considered poor in its performance, results indicated that the order of model performance was the pH-dependent Keren equation first, followed by the temperature-dependent Langmuir and kinetic Freundlich equations, the Freundlich equation, and, finally, the Langmuir equation. Overall, the TETrans model was able to simulate the transport of B with deviations because no functional adsorption equation incorporated all the influences of pH, ionic strength, temperature, and kinetic effects into a single equation. The inability to
NASA Astrophysics Data System (ADS)
Chen, Bingling; Guo, Zhouyi
2008-12-01
Conventional analyses of OCT signal measurements resolve the signal decay profile in terms of single discrete exponential function with distinct exponential model. In symmetrical medium, mono-exponential decay function can appear to provide a well fit to OCT signal decay data, but the assuption of symmetrical components is essentially arbitrary and is often erroneous. Actually, the real biological samples such as tissue contained more complex components and are more heterogeneous. To avoid the shortages of mono-exponential decay function fitting to OCT signal decay data from heterogeneous biological tissues, a novel model of flexible exponential function has been developed. The main idea of the flexible exponential function modle is based on the assuption that heterogeneous biological tissue can be considered as a multi-layered tissue. Each layer is symmetric and the OCT signal decay profile in each layer obeies to a distinct single exponential function. If we can find out all the distinct single exponential function for each layer, the total flexible exponential function is determined by summing up all the single exponential functions. As pilot studies on the practical application of flexibleexponential decay model for monitoring and quantifying the diffusion of different analytes in turbid biological tissues in vivo by using OCT system, we demonstrate an experiment of monitoring of glucose diffusion in agar gel. In addition, the flexible-exponential decay model can provide a direct measure of the heterogeneity of the sample, and the analysis of turbid tissues OCT map using the flexible-exponential decay model can reveal subtle tissue differences that other models fail to show.
ERIC Educational Resources Information Center
Engelhard, George, Jr.; Wang, Jue
2014-01-01
The authors of the Focus article pose important questions regarding whether or not performance-based tasks related to executive functioning are best viewed as reflective or formative indicators. Miyake and Friedman (2012) define executive functioning (EF) as "a set of general-purpose control mechanisms, often linked to the prefrontal cortex…
Tintelnot, M; Andrews, P
1989-03-01
An approach is described which makes use of X-ray structural data from enzyme-ligand complexes in order to obtain information for application in receptor modelling. The atomic surroundings of five different ligand functional groups were determined for all complex structures recorded in the Brookhaven Protein Data Bank. These atomic surroundings were then superimposed with respect to the atoms of the functional groups of the ligands in order to obtain clouds of neighbouring atoms. General principles were sought to describe the orientation or favoured position of groups or atoms around those functional groups when bound to a macromolecule. Some simple conclusions and leads for further modelling were thus derived.
Cook, Daniel L; Mejino, Jose L V; Rosse, Cornelius
2004-01-01
We describe the need for a Foundational Model of Physiology (FMP) as a reference ontology for "functional bioinformatics". The FMP is intended to support symbolic lookup, logical inference and mathematical analysis by integrating descriptive, qualitative and quantitative functional knowledge. The FMP will serve as a symbolic representation of biological functions initially pertaining to human physiology and ultimately extensible to other species. We describe the evolving architecture of the FMP, which is based on the ontological principles of the BioD biological description language and the Foundational Model of Anatomy (FMA). PMID:15360830
Integrative approaches for modeling regulation and function of the respiratory system
Ben-Tal, Alona
2013-01-01
Mathematical models have been central to understanding the interaction between neural control and breathing. Models of the entire respiratory system – which comprises the lungs and the neural circuitry that controls their ventilation - have been derived using simplifying assumptions to compartmentalise each component of the system and to define the interactions between components. These full system models often rely – through necessity - on empirically derived relationships or parameters, in addition to physiological values. In parallel with the development of whole respiratory system models are mathematical models that focus on furthering a detailed understanding of the neural control network, or of the several functions that contribute to gas exchange within the lung. These models are biophysically based, and rely on physiological parameters. They include single-unit models for a breathing lung or neural circuit, through to spatially-distributed models of ventilation and perfusion, or multi-circuit models for neural control. The challenge is to bring together these more recent advances in models of neural control with models of lung function, into a full simulation for the respiratory system that builds upon the more detailed models but remains computationally tractable. This requires first understanding the mathematical models that have been developed for the respiratory system at different levels, and which could be used to study how physiological levels of O2 and CO2 in the blood are maintained. PMID:24591490
Integrative approaches for modeling regulation and function of the respiratory system.
Ben-Tal, Alona; Tawhai, Merryn H
2013-01-01
Mathematical models have been central to understanding the interaction between neural control and breathing. Models of the entire respiratory system-which comprises the lungs and the neural circuitry that controls their ventilation-have been derived using simplifying assumptions to compartmentalize each component of the system and to define the interactions between components. These full system models often rely-through necessity-on empirically derived relationships or parameters, in addition to physiological values. In parallel with the development of whole respiratory system models are mathematical models that focus on furthering a detailed understanding of the neural control network, or of the several functions that contribute to gas exchange within the lung. These models are biophysically based, and rely on physiological parameters. They include single-unit models for a breathing lung or neural circuit, through to spatially distributed models of ventilation and perfusion, or multicircuit models for neural control. The challenge is to bring together these more recent advances in models of neural control with models of lung function, into a full simulation for the respiratory system that builds upon the more detailed models but remains computationally tractable. This requires first understanding the mathematical models that have been developed for the respiratory system at different levels, and which could be used to study how physiological levels of O2 and CO2 in the blood are maintained.
Functional Fault Modeling of a Cryogenic System for Real-Time Fault Detection and Isolation
NASA Technical Reports Server (NTRS)
Ferrell, Bob; Lewis, Mark; Oostdyk, Rebecca; Perotti, Jose
2009-01-01
When setting out to model and/or simulate a complex mechanical or electrical system, a modeler is faced with a vast array of tools, software, equations, algorithms and techniques that may individually or in concert aid in the development of the model. Mature requirements and a well understood purpose for the model may considerably shrink the field of possible tools and algorithms that will suit the modeling solution. Is the model intended to be used in an offline fashion or in real-time? On what platform does it need to execute? How long will the model be allowed to run before it outputs the desired parameters? What resolution is desired? Do the parameters need to be qualitative or quantitative? Is it more important to capture the physics or the function of the system in the model? Does the model need to produce simulated data? All these questions and more will drive the selection of the appropriate tools and algorithms, but the modeler must be diligent to bear in mind the final application throughout the modeling process to ensure the model meets its requirements without needless iterations of the design. The purpose of this paper is to describe the considerations and techniques used in the process of creating a functional fault model of a liquid hydrogen (LH2) system that will be used in a real-time environment to automatically detect and isolate failures.
NASA Astrophysics Data System (ADS)
Miwa, Tetsuji
2013-03-01
Studies on integrable models in statistical mechanics and quantum field theory originated in the works of Bethe on the one-dimensional quantum spin chain and the work of Onsager on the two-dimensional Ising model. I will talk on the discovery in 1977 of the link between quantum field theory in the scaling limit of the two-dimensional Ising model and the theory of monodromy preserving linear ordinary differential equations. This work was the staring point of our journey with Michio Jimbo in integrable models, the journey which finally led us to the exact results on the correlation functions of quantum spin chains in 1992.
ERIC Educational Resources Information Center
Davis, James; Leslie, Ray; Billington, Susan; Slater, Peter R.
2010-01-01
The use of "Origami" is presented as an accessible and transferable modeling system through which to convey the intricacies of molecular shape and highlight structure-function relationships. The implementation of origami has been found to be a versatile alternative to conventional ball-and-stick models, possessing the key advantages of being both…
A Functional Model of the Digital Extensor Mechanism: Demonstrating Biomechanics with Hair Bands
ERIC Educational Resources Information Center
Cloud, Beth A.; Youdas, James W.; Hellyer, Nathan J.; Krause, David A.
2010-01-01
The action of muscles about joints can be explained through analysis of their spatial relationship. A functional model of these relationships can be valuable in learning and understanding the muscular action about a joint. A model can be particularly helpful when examining complex actions across multiple joints such as in the digital extensor…
A Model of Marital Functioning Based on an Attraction Paradigm and Social-Penetration Dimensions.
ERIC Educational Resources Information Center
Honeycutt, James
1986-01-01
Tested structural equation model of marital functioning based on an attraction paradigm and social-penetration variables. The model posited that the attraction paradigm factors of being satisfied with marital issues and of perceived attitudinal similarity would have an impact upon marital happiness as well as perceived partner understanding, which…
Dynamical patterns of calcium signaling in a functional model of neuron–astrocyte networks
Koreshkov, R. N.; Brazhe, N. A.; Brazhe, A. R.; Sosnovtseva, O. V.
2009-01-01
We propose a functional mathematical model for neuron-astrocyte networks. The model incorporates elements of the tripartite synapse and the spatial branching structure of coupled astrocytes. We consider glutamate-induced calcium signaling as a specific mode of excitability and transmission in astrocytic–neuronal networks. We reproduce local and global dynamical patterns observed experimentally. PMID:19669421
Poor Vision, Functioning, and Depressive Symptoms: A Test of the Activity Restriction Model
ERIC Educational Resources Information Center
Bookwala, Jamila; Lawson, Brendan
2011-01-01
Purpose: This study tested the applicability of the activity restriction model of depressed affect to the context of poor vision in late life. This model hypothesizes that late-life stressors contribute to poorer mental health not only directly but also indirectly by restricting routine everyday functioning. Method: We used data from a national…
ERIC Educational Resources Information Center
Kamis-Gould, Edna; And Others
1991-01-01
A model for quality assurance (QA) in psychiatric hospitals is described. Its functions (general QA, utilization review, clinical records, evaluation, management information systems, risk management, and infection control), subfunctions, and corresponding staffing requirements are reviewed. This model was designed to foster standardization in QA…
ERIC Educational Resources Information Center
Ferrara, Steven; Walker-Bartnick, Leslie
A procedure was developed to detect differential item functioning (DIF) in a standardized essay test using the Partial Credit Model, the general polychotomous form of the Rasch model. Using a panel of experts in the writing process, hypothesized explanations for DIF at some score points were developed. Data for the study included averaged…
3D finite element model of the chinchilla ear for characterizing middle ear functions.
Wang, Xuelin; Gan, Rong Z
2016-10-01
Chinchilla is a commonly used animal model for research of sound transmission through the ear. Experimental measurements of the middle ear transfer function in chinchillas have shown that the middle ear cavity greatly affects the tympanic membrane (TM) and stapes footplate (FP) displacements. However, there is no finite element (FE) model of the chinchilla ear available in the literature to characterize the middle ear functions with the anatomical features of the chinchilla ear. This paper reports a recently completed 3D FE model of the chinchilla ear based on X-ray micro-computed tomography images of a chinchilla bulla. The model consisted of the ear canal, TM, middle ear ossicles and suspensory ligaments, and the middle ear cavity. Two boundary conditions of the middle ear cavity wall were simulated in the model as the rigid structure and the partially flexible surface, and the acoustic-mechanical coupled analysis was conducted with these two conditions to characterize the middle ear function. The model results were compared with experimental measurements reported in the literature including the TM and FP displacements and the middle ear input admittance in chinchilla ear. An application of this model was presented to identify the acoustic role of the middle ear septa-a unique feature of chinchilla middle ear cavity. This study provides the first 3D FE model of the chinchilla ear for characterizing the middle ear functions through the acoustic-mechanical coupled FE analysis.
3D finite element model of the chinchilla ear for characterizing middle ear functions.
Wang, Xuelin; Gan, Rong Z
2016-10-01
Chinchilla is a commonly used animal model for research of sound transmission through the ear. Experimental measurements of the middle ear transfer function in chinchillas have shown that the middle ear cavity greatly affects the tympanic membrane (TM) and stapes footplate (FP) displacements. However, there is no finite element (FE) model of the chinchilla ear available in the literature to characterize the middle ear functions with the anatomical features of the chinchilla ear. This paper reports a recently completed 3D FE model of the chinchilla ear based on X-ray micro-computed tomography images of a chinchilla bulla. The model consisted of the ear canal, TM, middle ear ossicles and suspensory ligaments, and the middle ear cavity. Two boundary conditions of the middle ear cavity wall were simulated in the model as the rigid structure and the partially flexible surface, and the acoustic-mechanical coupled analysis was conducted with these two conditions to characterize the middle ear function. The model results were compared with experimental measurements reported in the literature including the TM and FP displacements and the middle ear input admittance in chinchilla ear. An application of this model was presented to identify the acoustic role of the middle ear septa-a unique feature of chinchilla middle ear cavity. This study provides the first 3D FE model of the chinchilla ear for characterizing the middle ear functions through the acoustic-mechanical coupled FE analysis. PMID:26785845
An Examination of the Domain of Multivariable Functions Using the Pirie-Kieren Model
ERIC Educational Resources Information Center
Sengul, Sare; Yildiz, Sevda Goktepe
2016-01-01
The aim of this study is to employ the Pirie-Kieren model so as to examine the understandings relating to the domain of multivariable functions held by primary school mathematics preservice teachers. The data obtained was categorized according to Pirie-Kieren model and demonstrated visually in tables and bar charts. The study group consisted of…
Evaluation of a Digital Library by Means of Quality Function Deployment (QFD) and the Kano Model
ERIC Educational Resources Information Center
Garibay, Cecilia; Gutierrez, Humberto; Figueroa, Arturo
2010-01-01
This paper proposes utilizing a combination of the Quality Function Deployment (QFD)-Kano model as a useful tool to evaluate service quality. The digital library of the University of Guadalajara (Mexico) is presented as a case study. Data to feed the QFD-Kano model was gathered by an online questionnaire that was made available to users on the…
Testing for Nonuniform Differential Item Functioning with Multiple Indicator Multiple Cause Models
ERIC Educational Resources Information Center
Woods, Carol M.; Grimm, Kevin J.
2011-01-01
In extant literature, multiple indicator multiple cause (MIMIC) models have been presented for identifying items that display uniform differential item functioning (DIF) only, not nonuniform DIF. This article addresses, for apparently the first time, the use of MIMIC models for testing both uniform and nonuniform DIF with categorical indicators. A…
A Hierarchical Competing Systems Model of the Emergence and Early Development of Executive Function
ERIC Educational Resources Information Center
Marcovitch, Stuart; Zelazo, Philip David
2009-01-01
The hierarchical competing systems model (HCSM) provides a framework for understanding the emergence and early development of executive function--the cognitive processes underlying the conscious control of behavior--in the context of search for hidden objects. According to this model, behavior is determined by the joint influence of a…
Item Purification in Differential Item Functioning Using Generalized Linear Mixed Models
ERIC Educational Resources Information Center
Liu, Qian
2011-01-01
For this dissertation, four item purification procedures were implemented onto the generalized linear mixed model for differential item functioning (DIF) analysis, and the performance of these item purification procedures was investigated through a series of simulations. Among the four procedures, forward and generalized linear mixed model (GLMM)…
ERIC Educational Resources Information Center
Zbiek, Rose Mary
1998-01-01
Explores the strategies used by prospective secondary mathematics teachers (N=13) to develop and validate functions as mathematical models of real-world situations. Uses a grounded hypothesis on strategy selection. Concludes that strategy choice was influenced by task characteristics and interactions with other student modelers. Contains 38…
Model-based metrics of human-automation function allocation in complex work environments
NASA Astrophysics Data System (ADS)
Kim, So Young
Function allocation is the design decision which assigns work functions to all agents in a team, both human and automated. Efforts to guide function allocation systematically has been studied in many fields such as engineering, human factors, team and organization design, management science, and cognitive systems engineering. Each field focuses on certain aspects of function allocation, but not all; thus, an independent discussion of each does not address all necessary issues with function allocation. Four distinctive perspectives emerged from a review of these fields: technology-centered, human-centered, team-oriented, and work-oriented. Each perspective focuses on different aspects of function allocation: capabilities and characteristics of agents (automation or human), team structure and processes, and work structure and the work environment. Together, these perspectives identify the following eight issues with function allocation: 1) Workload, 2) Incoherency in function allocations, 3) Mismatches between responsibility and authority, 4) Interruptive automation, 5) Automation boundary conditions, 6) Function allocation preventing human adaptation to context, 7) Function allocation destabilizing the humans' work environment, and 8) Mission Performance. Addressing these issues systematically requires formal models and simulations that include all necessary aspects of human-automation function allocation: the work environment, the dynamics inherent to the work, agents, and relationships among them. Also, addressing these issues requires not only a (static) model, but also a (dynamic) simulation that captures temporal aspects of work such as the timing of actions and their impact on the agent's work. Therefore, with properly modeled work as described by the work environment, the dynamics inherent to the work, agents, and relationships among them, a modeling framework developed by this thesis, which includes static work models and dynamic simulation, can capture the
The Adults and Older Adults Functional Assessment Inventory: A Rasch Model Analysis.
Sousa, Liliana B; Prieto, Gerardo; Vilar, Manuela; Firmino, Horácio; Simões, Mário R
2015-11-01
Functional assessment methods are an important element in multidimensional neuropsychological evaluations, particularly in older adults. The Adults and Older Adults Functional Assessment Inventory is a new measure of basic and instrumental activities of daily living. Rasch model analyses were used to analyze the psychometric characteristics of the instrument in a sample of 803 participants. The original categories did not provide an optimal assessment of functional incapacity. The scale was dichotomized to achieve a better reliability score and item fit. The final 50 items revealed a moderately high variability in item difficulty, acceptable fits to items and persons, and a good Person Separation Reliability score. The scores were able to discriminate between normal controls and clinical patients. None of the items showed Differential Item Functioning associated with age, gender, or education. The instrument is able to achieve measures of functional incapacity with the useful properties of the Rasch model.
A numerical study of the string function using a primitive equation ocean model
NASA Astrophysics Data System (ADS)
Tyler, R. H.; Käse, R.
We use results from a primitive-equation ocean numerical model (SCRUM) to test a theoretical 'string function' formulation put forward by Tyler and Käse in another article in this issue. The string function acts as a stream function for the large-scale potential energy flow under the combined beta and topographic effects. The model results verify that large-scale anomalies propagate along the string function contours with a speed correctly given by the cross-string gradient. For anomalies having a scale similar to the Rossby radius, material rates of change in the layer mass following the string velocity are balanced by material rates of change in relative vorticity following the flow velocity. It is shown that large-amplitude anomalies can be generated when wind stress is resonant with the string function configuration.
The Adults and Older Adults Functional Assessment Inventory: A Rasch Model Analysis.
Sousa, Liliana B; Prieto, Gerardo; Vilar, Manuela; Firmino, Horácio; Simões, Mário R
2015-11-01
Functional assessment methods are an important element in multidimensional neuropsychological evaluations, particularly in older adults. The Adults and Older Adults Functional Assessment Inventory is a new measure of basic and instrumental activities of daily living. Rasch model analyses were used to analyze the psychometric characteristics of the instrument in a sample of 803 participants. The original categories did not provide an optimal assessment of functional incapacity. The scale was dichotomized to achieve a better reliability score and item fit. The final 50 items revealed a moderately high variability in item difficulty, acceptable fits to items and persons, and a good Person Separation Reliability score. The scores were able to discriminate between normal controls and clinical patients. None of the items showed Differential Item Functioning associated with age, gender, or education. The instrument is able to achieve measures of functional incapacity with the useful properties of the Rasch model. PMID:25651593
[Uniform model and experimental method of anaerobic inhibition dynamics using table function].
Yan, Zhong; Wang, Kai-Jun
2008-05-01
To figure out the problem, such as disunity of existent form in the model of traditional inhibition dynamic, and difficulty to obtain the parameters, we adopt the way of table function to formulate inhibition kinetics. Through indraught the way of table function to improve on the way of experiment in dynamic mensuration, DYNAMO software was used to process the data and simulate the inhibition phenomena of 2,4 dinitrophenol. The result shows that the table function is possible to simulate the inhibition phenomena. Compared with the traditional inhibition dynamic, the simulation curve of table function is much more close to the data of experiment, the modality is simple and unify, and simultaneously it solves the problem of parameter obtaining. When the complex inhibition phenomena is simulated, the table function shows obvious advantage, and may predigest the structure of model at a certain extent.
Hancock, D G; Guy, T V; Shklovskaya, E; Fazekas de St Groth, B
2013-02-01
The dendritic cell (DC) lineage is remarkably heterogeneous. It has been postulated that specialized DC subsets have evolved in order to select and support the multitude of possible T cell differentiation pathways. However, defining the function of individual DC subsets has proven remarkably difficult, and DC subset control of key T cell fates such as tolerance, T helper cell commitment and regulatory T cell induction is still not well understood. While the difficulty in assigning unique functions to particular DC subsets may be due to sharing of functions, it may also reflect a lack of appropriate physiological in-vivo models for studying DC function. In this paper we review the limitations associated with many of the current DC models and highlight some of the underlying difficulties involved in studying the function of murine DC subsets.
Twist-3 T-odd fragmentation functions G⊥ and G˜⊥ in a spectator model
NASA Astrophysics Data System (ADS)
Yang, Yongliang; Lu, Zhun; Schmidt, Ivan
2016-10-01
We present a calculation of the twist-3 T-odd chiral-even fragmentation functions G⊥ and G˜⊥ using a spectator model. We consider the effect gluon exchange to calculate all necessary one-loop diagrams for the quark-quark and quark-gluon-quark correlation functions. We find that the gluon loops corrections generate non-zero contribution to these two fragmentation function. We numerically calculate their half-kT moments by integrating over the transverse momentum and also verify the equation of motion relation among G⊥, G˜⊥ and the Collins function.
Charm structure functions and gluon shadowing effects with the AdS/CFT model
NASA Astrophysics Data System (ADS)
Wang, Hong-Min; Hou, Zhao-Yu; Liu, Jia-Fu; Sun, Xian-Jing
2012-08-01
By means of the UGD function extracted from an AdS/CFT inspired saturation model, the charm and bottom structure functions are studied in fixed-order perturbation theory. It is shown that the theoretical results are in good agreement with the recent HERA data. Then, this UGD function is also used to investigate net-kaon rapidity distribution in Au+Au collisions at RHIC energies and the theoretical results fit well to the BRAHMS data. In the end of this paper, we give the predicted results for nuclear charm structure function at very small x where the popular shadowing parameterizations are invalid.
NASA Astrophysics Data System (ADS)
Itagaki, N.; Matsuno, H.; Suhara, T.
2016-09-01
The antisymmetrized quasi-cluster model (AQCM) is a method to describe transitions from the α cluster wave functions to jj-coupling shell model wave functions. In this model, the cluster-shell transition is characterized by only two parameters: R representing the distance between α clusters and Λ describing the breaking of α clusters. The contribution of the spin-orbit interaction, very important in the jj-coupling shell model, can be taken into account starting with the α cluster model wave function. In this article we show the generality of AQCM by extending the application to heavier regions: various 4N nuclei from 4He to 100Sn. The characteristic magic numbers of the jj-coupling shell model, 28 and 50, are described starting with the α cluster model. The competition of two different configurations is discussed in 20Ne (16O + one quasi-cluster and 12C + two quasi-clusters) and 28Si (pentagon shape of five quasi-clusters and 12C + 16O). Also, we compare the energy curves for the α + 40Ca cluster configuration calculated with and without the α breaking effect in 44Ti.
Aircraft/Air Traffic Management Functional Analysis Model: Technical Description. 2.0
NASA Technical Reports Server (NTRS)
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) under a National Aeronautics and Space Administration (NASA) contract. This document provides a technical description of FAM 2.0 and its computer files to enable the modeler and programmer to make enhancements or modifications to the model. Those interested in a guide for using the model in analysis should consult the companion document, Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 Users Manual.
a Radiative Transfer Equation/phase Function Approach to Vegetation Canopy Reflectance Modeling
NASA Astrophysics Data System (ADS)
Randolph, Marion Herbert
Vegetation canopy reflectance models currently in use differ considerably in their treatment of the radiation scattering problem, and it is this fundamental difference which stimulated this investigation of the radiative transfer equation/phase function approach. The primary objective of this thesis is the development of vegetation canopy phase functions which describe the probability of radiation scattering within a canopy in terms of its biological and physical characteristics. In this thesis a technique based upon quadrature formulae is used to numerically generate a variety of vegetation canopy phase functions. Based upon leaf inclination distribution functions, phase functions are generated for plagiophile, extremophile, erectophile, spherical, planophile, blue grama (Bouteloua gracilis), and soybean canopies. The vegetation canopy phase functions generated are symmetric with respect to the incident and exitant angles, and hence satisfy the principle of reciprocity. The remaining terms in the radiative transfer equation are also derived in terms of canopy geometry and optical properties to complete the development of the radiative transfer equation/phase function description for vegetation canopy reflectance modeling. In order to test the radiative transfer equation/phase function approach the iterative discrete ordinates method for solving the radiative transfer equation is implemented. In comparison with field data, the approach tends to underestimate the visible reflectance and overestimate infrared reflectance. The approach does compare well, however, with other extant canopy reflectance models; for example, it agrees to within ten to fifteen percent of the Suits model (Suits, 1972). Sensitivity analysis indicates that canopy geometry may influence reflectance as much as 100 percent for a given wavelength. Optical thickness produces little change in reflectance after a depth of 2.5 (Leaf area index of 4.0) is reached, and reflectance generally increases
Kuceyeski, A.; Shah, S.; Dyke, J.P.; Bickel, S.; Abdelnour, F.; Schiff, N.D.; Voss, H.U.; Raj, A.
2016-01-01
Following severe injuries that result in disorders of consciousness, recovery can occur over many months or years post-injury. While post-injury synaptogenesis, axonal sprouting and functional reorganization are known to occur, the network-level processes underlying recovery are poorly understood. Here, we test a network-level functional rerouting hypothesis in recovery of patients with disorders of consciousness following severe brain injury. This hypothesis states that the brain recovers from injury by restoring normal functional connections via alternate structural pathways that circumvent impaired white matter connections. The so-called network diffusion model, which relates an individual's structural and functional connectomes by assuming that functional activation diffuses along structural pathways, is used here to capture this functional rerouting. We jointly examined functional and structural connectomes extracted from MRIs of 12 healthy and 16 brain-injured subjects. Connectome properties were quantified via graph theoretic measures and network diffusion model parameters. While a few graph metrics showed groupwise differences, they did not correlate with patients' level of consciousness as measured by the Coma Recovery Scale — Revised. There was, however, a strong and significant partial Pearson's correlation (accounting for age and years post-injury) between level of consciousness and network diffusion model propagation time (r = 0.76, p < 0.05, corrected), i.e. the time functional activation spends traversing the structural network. We concluded that functional rerouting via alternate (and less efficient) pathways leads to increases in network diffusion model propagation time. Simulations of injury and recovery in healthy connectomes confirmed these results. This work establishes the feasibility for using the network diffusion model to capture network-level mechanisms in recovery of consciousness after severe brain injury. PMID:27200264
Modeling the Pulse Signal by Wave-Shape Function and Analyzing by Synchrosqueezing Transform
Wang, Chun-Li; Yang, Yueh-Lung; Wu, Wen-Hsiang; Tsai, Tung-Hu; Chang, Hen-Hong
2016-01-01
We apply the recently developed adaptive non-harmonic model based on the wave-shape function, as well as the time-frequency analysis tool called synchrosqueezing transform (SST) to model and analyze oscillatory physiological signals. To demonstrate how the model and algorithm work, we apply them to study the pulse wave signal. By extracting features called the spectral pulse signature, and based on functional regression, we characterize the hemodynamics from the radial pulse wave signals recorded by the sphygmomanometer. Analysis results suggest the potential of the proposed signal processing approach to extract health-related hemodynamics features. PMID:27304979
A prototype symbolic model of canonical functional neuroanatomy of the motor system.
Talos, Ion-Florin; Rubin, Daniel L; Halle, Michael; Musen, Mark; Kikinis, Ron
2008-04-01
Recent advances in bioinformatics have opened entire new avenues for organizing, integrating and retrieving neuroscientific data, in a digital, machine-processable format, which can be at the same time understood by humans, using ontological, symbolic data representations. Declarative information stored in ontological format can be perused and maintained by domain experts, interpreted by machines, and serve as basis for a multitude of decision support, computerized simulation, data mining, and teaching applications. We have developed a prototype symbolic model of canonical neuroanatomy of the motor system. Our symbolic model is intended to support symbolic look up, logical inference and mathematical modeling by integrating descriptive, qualitative and quantitative functional neuroanatomical knowledge. Furthermore, we show how our approach can be extended to modeling impaired brain connectivity in disease states, such as common movement disorders. In developing our ontology, we adopted a disciplined modeling approach, relying on a set of declared principles, a high-level schema, Aristotelian definitions, and a frame-based authoring system. These features, along with the use of the Unified Medical Language System (UMLS) vocabulary, enable the alignment of our functional ontology with an existing comprehensive ontology of human anatomy, and thus allow for combining the structural and functional views of neuroanatomy for clinical decision support and neuroanatomy teaching applications. Although the scope of our current prototype ontology is limited to a particular functional system in the brain, it may be possible to adapt this approach for modeling other brain functional systems as well.
Region-Based Association Test for Familial Data under Functional Linear Models
Axenovich, Tatiana I.
2015-01-01
Region-based association analysis is a more powerful tool for gene mapping than testing of individual genetic variants, particularly for rare genetic variants. The most powerful methods for regional mapping are based on the functional data analysis approach, which assumes that the regional genome of an individual may be considered as a continuous stochastic function that contains information about both linkage and linkage disequilibrium. Here, we extend this powerful approach, earlier applied only to independent samples, to the samples of related individuals. To this end, we additionally include a random polygene effects in functional linear model used for testing association between quantitative traits and multiple genetic variants in the region. We compare the statistical power of different methods using Genetic Analysis Workshop 17 mini-exome family data and a wide range of simulation scenarios. Our method increases the power of regional association analysis of quantitative traits compared with burden-based and kernel-based methods for the majority of the scenarios. In addition, we estimate the statistical power of our method using regions with small number of genetic variants, and show that our method retains its advantage over burden-based and kernel-based methods in this case as well. The new method is implemented as the R-function ‘famFLM’ using two types of basis functions: the B-spline and Fourier bases. We compare the properties of the new method using models that differ from each other in the type of their function basis. The models based on the Fourier basis functions have an advantage in terms of speed and power over the models that use the B-spline basis functions and those that combine B-spline and Fourier basis functions. The ‘famFLM’ function is distributed under GPLv3 license and is freely available at http://mga.bionet.nsc.ru/soft/famFLM/. PMID:26111046
A phenotypic in vitro model for the main determinants of human whole heart function.
Stancescu, Maria; Molnar, Peter; McAleer, Christopher W; McLamb, William; Long, Christopher J; Oleaga, Carlota; Prot, Jean-Matthieu; Hickman, James J
2015-08-01
This article details the construction and testing of a phenotypic assay system that models in vivo cardiac function in a parallel in vitro environment with human stem cell derived cardiomyocytes. The major determinants of human whole-heart function were experimentally modeled by integrating separate 2D cellular systems with BioMicroelectromechanical Systems (BioMEMS) constructs. The model features a serum-free defined medium to enable both acute and chronic evaluation of drugs and toxins. The integration of data from both systems produced biologically relevant predictions of cardiac function in response to varying concentrations of selected drugs. Sotalol, norepinephrine and verapamil were shown to affect the measured parameters according to their specific mechanism of action, in agreement with clinical data. This system is applicable for cardiac side effect assessment, general toxicology, efficacy studies, and evaluation of in vitro cellular disease models in body-on-a-chip systems.
A phenotypic in vitro model for the main determinants of human whole heart function
Stancescu, Maria; Molnar, Peter; McAleer, Christopher W.; McLamb, William; Long, Christopher J.; Oleaga, Carlota; Prot, Jean-Matthieu; Hickman, James J.
2015-01-01
This article details the construction and testing of a phenotypic assay system that models in vivo cardiac function in a parallel in vitro environment with human stem cell derived cardiomyocytes. The major determinants of human whole-heart function were experimentally modeled by integrating separate 2D cellular systems with BioMicroelectromechanical Systems (BioMEMS) constructs. The model featured a serum-free defined medium to enable both acute and chronic evaluation of drugs and toxins. The integration of data from both systems produced biologically relevant predictions of cardiac function in response to varying concentrations of selected drugs. Sotalol, norepinephrine and verapamil were shown to affect the measured parameters according to their specific mechanism of action, in agreement with clinical data. This system is applicable for cardiac side effect assessment, general toxicology, efficacy studies, and evaluation of in vitro cellular disease models in body-on-a-chip systems. PMID:25978005
Zaĭtseva, N V; Trusov, P V; Kir'ianov, D A
2012-01-01
The mathematic concept model presented describes accumulation of functional disorders associated with environmental factors, plays predictive role and is designed for assessments of possible effects caused by heterogenous factors with variable exposures. Considering exposure changes with self-restoration process opens prospects of using the model to evaluate, analyse and manage occupational risks. To develop current theoretic approaches, the authors suggested a model considering age-related body peculiarities, systemic interactions of organs, including neuro-humoral regulation, accumulation of functional disorders due to external factors, rehabilitation of functions during treatment. General objective setting covers defining over a hundred unknow coefficients that characterize speed of various processes within the body. To solve this problem, the authors used iteration approach, successive identification, that starts from the certain primary approximation of the model parameters and processes subsequent updating on the basis of new theoretic and empirical knowledge.
Constitutive Modeling of Skeletal Muscle Tissue with an Explicit Strain-Energy Function
Odegard, G.M.; Donahue, T.L. Haut; Morrow, D.A.; Kaufman, K.R.
2010-01-01
While much work has previously been done in the modeling of skeletal muscle, no model has, to date, been developed that describes the mechanical behavior with an explicit strain-energy function associated with the active response of skeletal muscle tissue. A model is presented herein that has been developed to accommodate this design consideration using a robust dynamical approach. The model shows excellent agreement with a previously published model of both the active and passive length-tension properties of skeletal muscle. PMID:19045546
Vanheel, Hanne; Masaoka, Tatsuhiro; Salim Rasoel, Shadea; Tóth, Joran; Houben, Els; Verbeke, Kristin; De Hertogh, Gert; Berghe, Pieter Vanden; Tack, Jan; Farré, Ricard
2014-01-01
Background Impaired intestinal barrier function, low-grade inflammation and altered neuronal control are reported in functional gastrointestinal disorders. However, the sequence of and causal relation between these events is unclear, necessitating a spontaneous animal model. The aim of this study was to describe the natural history of intestinal permeability, mucosal and neuromuscular inflammation and nitrergic motor neuron function during the lifetime of the BioBreeding (BB) rat. Methods Normoglycemic BB-diabetes prone (DP) and control rats were sacrificed at different ages and jejunum was harvested to characterize intestinal permeability, inflammation and neuromuscular function. Results Both structural and functional evidence of increased intestinal permeability was found in young BB-DP rats from the age of 50 days. In older animals, starting in the mucosa from 70 days and in half of the animals also in the muscularis propria from 110 days, an inflammatory reaction, characterized by an influx of polymorphonuclear cells and higher myeloperoxidase activity, was observed. Finally, in animals older than 110 days, coinciding with a myenteric ganglionitis, a loss of nitrergic neurons and motor function was demonstrated. Conclusion In the BB-rat, mucosal inflammatory cell infiltration is preceded by intestinal barrier dysfunction and followed by myenteric ganglionitis and loss of nitrergic function. This sequence supports a primary role for impaired barrier function and provides an insightful model for the pathogenesis of functional gastrointestinal disorders. PMID:25354336
NASA Astrophysics Data System (ADS)
Zenzerovic, I.; Kropp, W.; Pieringer, A.
2016-08-01
Curve squeal is a strong tonal sound that may arise when a railway vehicle negotiates a tight curve. In contrast to frequency-domain models, time-domain models are able to capture the nonlinear and transient nature of curve squeal. However, these models are computationally expensive due to requirements for fine spatial and time discretization. In this paper, a computationally efficient engineering model for curve squeal in the time-domain is proposed. It is based on a steady-state point-contact model for the tangential wheel/rail contact and a Green's functions approach for wheel and rail dynamics. The squeal model also includes a simple model of sound radiation from the railway wheel from the literature. A validation of the tangential point-contact model against Kalker's transient variational contact model reveals that the point-contact model performs well within the squeal model up to at least 5 kHz. The proposed squeal model is applied to investigate the influence of lateral creepage, friction and wheel/rail contact position on squeal occurrence and amplitude. The study indicates a significant influence of the wheel/rail contact position on squeal frequencies and amplitudes. Friction and lateral creepage show an influence on squeal occurrence and amplitudes, but this is only secondary to the influence of the contact position.
A functional-dynamic reflection on participatory processes in modeling projects.
Seidl, Roman
2015-12-01
The participation of nonscientists in modeling projects/studies is increasingly employed to fulfill different functions. However, it is not well investigated if and how explicitly these functions and the dynamics of a participatory process are reflected by modeling projects in particular. In this review study, I explore participatory modeling projects from a functional-dynamic process perspective. The main differences among projects relate to the functions of participation-most often, more than one per project can be identified, along with the degree of explicit reflection (i.e., awareness and anticipation) on the dynamic process perspective. Moreover, two main approaches are revealed: participatory modeling covering diverse approaches and companion modeling. It becomes apparent that the degree of reflection on the participatory process itself is not always explicit and perfectly visible in the descriptions of the modeling projects. Thus, the use of common protocols or templates is discussed to facilitate project planning, as well as the publication of project results. A generic template may help, not in providing details of a project or model development, but in explicitly reflecting on the participatory process. It can serve to systematize the particular project's approach to stakeholder collaboration, and thus quality management.
Takagi-Sugeno fuzzy models in the framework of orthonormal basis functions.
Machado, Jeremias B; Campello, Ricardo J G B; Amaral, Wagner Caradori
2013-06-01
An approach to obtain Takagi-Sugeno (TS) fuzzy models of nonlinear dynamic systems using the framework of orthonormal basis functions (OBFs) is presented in this paper. This approach is based on an architecture in which local linear models with ladder-structured generalized OBFs (GOBFs) constitute the fuzzy rule consequents and the outputs of the corresponding GOBF filters are input variables for the rule antecedents. The resulting GOBF-TS model is characterized by having only real-valued parameters that do not depend on any user specification about particular types of functions to be used in the orthonormal basis. The fuzzy rules of the model are initially obtained by means of a well-known technique based on fuzzy clustering and least squares. Those rules are then simplified, and the model parameters (GOBF poles, GOBF expansion coefficients, and fuzzy membership functions) are subsequently adjusted by using a nonlinear optimization algorithm. The exact gradients of an error functional with respect to the parameters to be optimized are computed analytically. Those gradients provide exact search directions for the optimization process, which relies solely on input-output data measured from the system to be modeled. An example is presented to illustrate the performance of this approach in the modeling of a complex nonlinear dynamic system. PMID:23096073
Study of production functions for modeling forest biomass: An area for research
Nautiyal, J.C. ); Belli, K.L. )
1989-09-01
The usefulness of production functions, mathematical descriptions of production processes, has long been recognized by economists in manufacturing industries, and more recently by agricultural scientists in the field of biological production. As increasing emphasis in forestry is placed on short-rotation, intensive crop management it would seem that foresters would also require production functions for rational timber management planning. These functions could be useful in a number of areas such as: crop tree growth prediction, control of stand development, economic analysis for decision-making purposes, and for determining the so-called elasticities of inputs and outputs. A very general functional form that may be appropriate for the development of forestry models is the transcendental logarithmic, or translog, function. Unfortunately, at this time, sufficiently detailed data do not seem to be available for any tree species to estimate a production function that could make sophisticated intensive forest management possible.
Verifying the functional ability of microstructured surfaces by model-based testing
NASA Astrophysics Data System (ADS)
Hartmann, Wito; Weckenmann, Albert
2014-09-01
Micro- and nanotechnology enables the use of new product features such as improved light absorption, self-cleaning or protection, which are based, on the one hand, on the size of functional nanostructures and the other hand, on material-specific properties. With the need to reliably measure progressively smaller geometric features, coordinate and surface-measuring instruments have been refined and now allow high-resolution topography and structure measurements down to the sub-nanometre range. Nevertheless, in many cases it is not possible to make a clear statement about the functional ability of the workpiece or its topography because conventional concepts of dimensioning and tolerancing are solely geometry oriented and standardized surface parameters are not sufficient to consider interaction with non-geometric parameters, which are dominant for functions such as sliding, wetting, sealing and optical reflection. To verify the functional ability of microstructured surfaces, a method was developed based on a parameterized mathematical-physical model of the function. From this model, function-related properties can be identified and geometric parameters can be derived, which may be different for the manufacturing and verification processes. With this method it is possible to optimize the definition of the shape of the workpiece regarding the intended function by applying theoretical and experimental knowledge, as well as modelling and simulation. Advantages of this approach will be discussed and demonstrated by the example of a microstructured inking roll.
Basu, Anirban; Rathouz, Paul J
2005-01-01
We propose an extension to the estimating equations in generalized linear models to estimate parameters in the link function and variance structure simultaneously with regression coefficients. Rather than focusing on the regression coefficients, the purpose of these models is inference about the mean of the outcome as a function of a set of covariates, and various functionals of the mean function used to measure the effects of the covariates. A commonly used functional in econometrics, referred to as the marginal effect, is the partial derivative of the mean function with respect to any covariate, averaged over the empirical distribution of covariates in the model. We define an analogous parameter for discrete covariates. The proposed estimation method not only helps to identify an appropriate link function and to suggest an underlying distribution for a specific application but also serves as a robust estimator when no specific distribution for the outcome measure can be identified. Using Monte Carlo simulations, we show that the resulting parameter estimators are consistent. The method is illustrated with an analysis of inpatient expenditure data from a study of hospitalists.
Drosophila as a Model for MECP2 Gain of Function in Neurons
Vonhoff, Fernando; Williams, Alison; Ryglewski, Stefanie; Duch, Carsten
2012-01-01
Methyl-CpG-binding protein 2 (MECP2) is a multi-functional regulator of gene expression. In humans loss of MECP2 function causes classic Rett syndrome, but gain of MECP2 function also causes mental retardation. Although mouse models provide valuable insight into Mecp2 gain and loss of function, the identification of MECP2 genetic targets and interactors remains time intensive and complicated. This study takes a step toward utilizing Drosophila as a model to identify genetic targets and cellular consequences of MECP2 gain-of function mutations in neurons, the principle cell type affected in patients with Rett-related mental retardation. We show that heterologous expression of human MECP2 in Drosophila motoneurons causes distinct defects in dendritic structure and motor behavior, as reported with MECP2 gain of function in humans and mice. Multiple lines of evidence suggest that these defects arise from specific MECP2 function. First, neurons with MECP2-induced dendrite loss show normal membrane currents. Second, dendritic phenotypes require an intact methyl-CpG-binding domain. Third, dendritic defects are amended by reducing the dose of the chromatin remodeling protein, osa, indicating that MECP2 may act via chromatin remodeling in Drosophila. MECP2-induced motoneuron dendritic defects cause specific motor behavior defects that are easy to score in genetic screening. In sum, our data show that some aspects of MECP2 function can be studied in the Drosophila model, thus expanding the repertoire of genetic reagents that can be used to unravel specific neural functions of MECP2. However, additional genes and signaling pathways identified through such approaches in Drosophila will require careful validation in the mouse model. PMID:22363746
Harris, Michelle A.; Chang, Wesley S.; Dent, Erik W.; Nordheim, Erik V.; Franzen, Margaret A.
2016-01-01
Abstract Understanding how basic structural units influence function is identified as a foundational/core concept for undergraduate biological and biochemical literacy. It is essential for students to understand this concept at all size scales, but it is often more difficult for students to understand structure–function relationships at the molecular level, which they cannot as effectively visualize. Students need to develop accurate, 3‐dimensional mental models of biomolecules to understand how biomolecular structure affects cellular functions at the molecular level, yet most traditional curricular tools such as textbooks include only 2‐dimensional representations. We used a controlled, backward design approach to investigate how hand‐held physical molecular model use affected students' ability to logically predict structure–function relationships. Brief (one class period) physical model use increased quiz score for females, whereas there was no significant increase in score for males using physical models. Females also self‐reported higher learning gains in their understanding of context‐specific protein function. Gender differences in spatial visualization may explain the gender‐specific benefits of physical model use observed. © 2016 The Authors Biochemistry and Molecular Biology Education published by Wiley Periodicals, Inc. on behalf of International Union of Biochemistry and Molecular Biology, 44(4):326–335, 2016. PMID:26923186
Forbes-Lorman, Robin M; Harris, Michelle A; Chang, Wesley S; Dent, Erik W; Nordheim, Erik V; Franzen, Margaret A
2016-07-01
Understanding how basic structural units influence function is identified as a foundational/core concept for undergraduate biological and biochemical literacy. It is essential for students to understand this concept at all size scales, but it is often more difficult for students to understand structure-function relationships at the molecular level, which they cannot as effectively visualize. Students need to develop accurate, 3-dimensional mental models of biomolecules to understand how biomolecular structure affects cellular functions at the molecular level, yet most traditional curricular tools such as textbooks include only 2-dimensional representations. We used a controlled, backward design approach to investigate how hand-held physical molecular model use affected students' ability to logically predict structure-function relationships. Brief (one class period) physical model use increased quiz score for females, whereas there was no significant increase in score for males using physical models. Females also self-reported higher learning gains in their understanding of context-specific protein function. Gender differences in spatial visualization may explain the gender-specific benefits of physical model use observed. © 2016 The Authors Biochemistry and Molecular Biology Education published by Wiley Periodicals, Inc. on behalf of International Union of Biochemistry and Molecular Biology, 44(4):326-335, 2016. PMID:26923186
Harris, Michelle A.; Chang, Wesley S.; Dent, Erik W.; Nordheim, Erik V.; Franzen, Margaret A.
2016-01-01
Understanding how basic structural units influence function is identified as a foundational/core concept for undergraduate biological and biochemical literacy. It is essential for students to understand this concept at all size scales, but it is often more difficult for students to understand structure-function relationships at the molecular level, which they cannot as effectively visualize. Students need to develop accurate, 3-dimensional (3D) mental models of biomolecules to understand how biomolecular structure affects cellular functions at the molecular level, yet most traditional curricular tools such as textbooks include only 2-dimensional (2D) representations. We used a controlled, backwards design approach to investigate how hand-held physical molecular model use affected students’ ability to logically predict structure-function relationships. Brief (one class period) physical model use increased quiz score for females, whereas there was no significant increase in score for males using physical models. Females also self-reported higher learning gains in their understanding of context-specific protein function. Gender differences in spatial visualization may explain the gender-specific benefits of physical model use observed. PMID:26923186
Azzopardi, George; Petkov, Nicolai
2012-03-01
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 simple cells, and its effectiveness in contour detection tasks has never been compared with the effectiveness of alternative models. We propose a computational model that uses as afferent inputs the responses of model LGN cells with center-surround receptive fields (RFs) and we refer to it as a Combination of Receptive Fields (CORF) model. We use shifted gratings as test stimuli and simulated reverse correlation to explore the nature of the proposed model. We study its behavior regarding the effect of contrast on its response and orientation bandwidth as well as the effect of an orthogonal mask on the response to an optimally oriented stimulus. We also evaluate and compare the performances of the CORF and GF models regarding contour detection, using two public data sets of images of natural scenes with associated contour ground truths. The RF map of the proposed CORF model, determined with simulated reverse correlation, can be divided in elongated excitatory and inhibitory regions typical of simple cells. The modulated response to shifted gratings that this model shows is also characteristic of a simple cell. Furthermore, the CORF model exhibits cross orientation suppression, contrast invariant orientation tuning and response saturation. These properties are observed in real simple cells, but are not possessed by the GF model. The proposed CORF model outperforms the GF model in contour detection with high statistical confidence (RuG data set: p<10(-4), and Berkeley data set: p<10(-4)). The proposed CORF model is more realistic than the GF model and is more effective in contour detection, which is assumed to be the primary biological role of simple cells. PMID:22526357
White, Jim; Zardava, Kiriaki; Nayagum, Dharumarajen; Powrie, William
2015-04-01
Numerical models of landfill processes need to be able to estimate the capillary pressure and relative permeability of waste as a function of moisture content using analytical equations such as the van Genuchten equations. The paper identifies the range of van Genuchten parameter values for use in models and proposes a formulaic relationship between these parameter values and saturated moisture content. The concept of porous material, its behaviour under unsaturated conditions and Mualem's integral transform equation that estimates relative permeability from capillary pressure are reviewed. The application of the algebraic form of the capillary pressure function proposed by van Genuchten and its application using Mualem's transform to obtain the van Genuchten algebraic functions for relative permeability are discussed. Functional relationships are identified between saturated moisture content and the van Genuchten parameters using a database of results from other sources. These relationships may be used in numerical modelling of unsaturated flow in landfilled waste where the saturated moisture content varies significantly as the result of compression, settlement and degradation. A 2D numerical model simulation of leachate recirculation is used to investigate the sensitivity of the simulation to the introduction of these functional relationships. It is found that the transient liquid and gas flows across the model boundaries appear to be insensitive to whether or not the functions are incorporated into the model algorithm. However it is observed that using the relationships does have some impact on the distribution of the degree of saturation throughout the model and on the transient behaviour of the way in which the recirculation recharges the waste. However it is not thought that this impact would be sufficient to influence the design of a leachate recirculation system.
Hamilton, Joshua J.; Reed, Jennifer L.
2012-01-01
Genome-scale network reconstructions are useful tools for understanding cellular metabolism, and comparisons of such reconstructions can provide insight into metabolic differences between organisms. Recent efforts toward comparing genome-scale models have focused primarily on aligning metabolic networks at the reaction level and then looking at differences and similarities in reaction and gene content. However, these reaction comparison approaches are time-consuming and do not identify the effect network differences have on the functional states of the network. We have developed a bilevel mixed-integer programming approach, CONGA, to identify functional differences between metabolic networks by comparing network reconstructions aligned at the gene level. We first identify orthologous genes across two reconstructions and then use CONGA to identify conditions under which differences in gene content give rise to differences in metabolic capabilities. By seeking genes whose deletion in one or both models disproportionately changes flux through a selected reaction (e.g., growth or by-product secretion) in one model over another, we are able to identify structural metabolic network differences enabling unique metabolic capabilities. Using CONGA, we explore functional differences between two metabolic reconstructions of Escherichia coli and identify a set of reactions responsible for chemical production differences between the two models. We also use this approach to aid in the development of a genome-scale model of Synechococcus sp. PCC 7002. Finally, we propose potential antimicrobial targets in Mycobacterium tuberculosis and Staphylococcus aureus based on differences in their metabolic capabilities. Through these examples, we demonstrate that a gene-centric approach to comparing metabolic networks allows for a rapid comparison of metabolic models at a functional level. Using CONGA, we can identify differences in reaction and gene content which give rise to different
White, Jim; Zardava, Kiriaki; Nayagum, Dharumarajen; Powrie, William
2015-04-01
Numerical models of landfill processes need to be able to estimate the capillary pressure and relative permeability of waste as a function of moisture content using analytical equations such as the van Genuchten equations. The paper identifies the range of van Genuchten parameter values for use in models and proposes a formulaic relationship between these parameter values and saturated moisture content. The concept of porous material, its behaviour under unsaturated conditions and Mualem's integral transform equation that estimates relative permeability from capillary pressure are reviewed. The application of the algebraic form of the capillary pressure function proposed by van Genuchten and its application using Mualem's transform to obtain the van Genuchten algebraic functions for relative permeability are discussed. Functional relationships are identified between saturated moisture content and the van Genuchten parameters using a database of results from other sources. These relationships may be used in numerical modelling of unsaturated flow in landfilled waste where the saturated moisture content varies significantly as the result of compression, settlement and degradation. A 2D numerical model simulation of leachate recirculation is used to investigate the sensitivity of the simulation to the introduction of these functional relationships. It is found that the transient liquid and gas flows across the model boundaries appear to be insensitive to whether or not the functions are incorporated into the model algorithm. However it is observed that using the relationships does have some impact on the distribution of the degree of saturation throughout the model and on the transient behaviour of the way in which the recirculation recharges the waste. However it is not thought that this impact would be sufficient to influence the design of a leachate recirculation system. PMID:25573738
Asymptotic behaviour of two-point functions in multi-species models
NASA Astrophysics Data System (ADS)
Kozlowski, Karol K.; Ragoucy, Eric
2016-05-01
We extract the long-distance asymptotic behaviour of two-point correlation functions in massless quantum integrable models containing multi-species excitations. For such a purpose, we extend to these models the method of a large-distance regime re-summation of the form factor expansion of correlation functions. The key feature of our analysis is a technical hypothesis on the large-volume behaviour of the form factors of local operators in such models. We check the validity of this hypothesis on the example of the SU (3)-invariant XXX magnet by means of the determinant representations for the form factors of local operators in this model. Our approach confirms the structure of the critical exponents obtained previously for numerous models solvable by the nested Bethe Ansatz.
ERIC Educational Resources Information Center
DeMars, Christine E.; Jurich, Daniel P.
2015-01-01
In educational testing, differential item functioning (DIF) statistics must be accurately estimated to ensure the appropriate items are flagged for inspection or removal. This study showed how using the Rasch model to estimate DIF may introduce considerable bias in the results when there are large group differences in ability (impact) and the data…
Bordas, R.; Gillow, K.; Lou, Q.; Efimov, I. R.; Gavaghan, D.; Kohl, P.; Grau, V.; Rodriguez, B.
2011-01-01
The function of the ventricular specialized conduction system in the heart is to ensure the coordinated electrical activation of the ventricles. It is therefore critical to the overall function of the heart, and has also been implicated as an important player in various diseases, including lethal ventricular arrhythmias such as ventricular fibrillation and drug-induced torsades de pointes. However, current ventricular models of electrophysiology usually ignore, or include highly simplified representations of the specialized conduction system. Here, we describe the development of a image-based, species-consistent, anatomically-detailed model of rabbit ventricular electrophysiology that incorporates a detailed description of the free-running part of the specialized conduction system. Techniques used for the construction of the geometrical model of the specialized conduction system from a magnetic resonance dataset and integration of the system model into a ventricular anatomical model, developed from the same dataset, are described. Computer simulations of rabbit ventricular electrophysiology are conducted using the novel anatomical model and rabbit-specific membrane kinetics to investigate the importance of the components and properties of the conduction system in determining ventricular function under physiological conditions. Simulation results are compared to panoramic optical mapping experiments for model validation and results interpretation. Full access is provided to the anatomical models developed in this study. PMID:21672547
NASA Astrophysics Data System (ADS)
Moeys, J.; Larsbo, M.; Bergström, L.; Brown, C. D.; Coquet, Y.; Jarvis, N. J.
2012-02-01
Estimating pesticide leaching risks at the regional scale requires the ability to completely parameterise a pesticide fate model using only survey data, such as soil and land-use maps. Such parameterisation usually rely on a set of lookup tables and (pedo)transfer functions, relating elementary soil and site properties to model parameters. The aim of this paper is to describe and test a complete set of parameter estimation algorithms developed for the pesticide fate model MACRO, which accounts for preferential flow in soil macropores. We used tracer monitoring data from 16 lysimeter studies, carried out in three European countries, to evaluate the ability of MACRO and this "blind parameterisation" scheme to reproduce measured solute leaching at the base of each lysimeter. We focused on the prediction of early tracer breakthrough due to preferential flow, because this is critical for pesticide leaching. We then calibrated a selected number of parameters in order to assess to what extent the prediction of water and solute leaching could be improved. Our results show that water flow was generally reasonably well predicted (median model efficiency, ME, of 0.42). Although the general pattern of solute leaching was reproduced well by the model, the overall model efficiency was low (median ME = -0.26) due to errors in the timing and magnitude of some peaks. Preferential solute leaching at early pore volumes was also systematically underestimated. Nonetheless, the ranking of soils according to solute loads at early pore volumes was reasonably well estimated (concordance correlation coefficient, CCC, between 0.54 and 0.72). Moreover, we also found that ignoring macropore flow leads to a significant deterioration in the ability of the model to reproduce the observed leaching pattern, and especially the early breakthrough in some soils. Finally, the calibration procedure showed that improving the estimation of solute transport parameters is probably more important than the
NASA Astrophysics Data System (ADS)
Moeys, J.; Larsbo, M.; Bergström, L.; Brown, C. D.; Coquet, Y.; Jarvis, N. J.
2012-07-01
Estimating pesticide leaching risks at the regional scale requires the ability to completely parameterise a pesticide fate model using only survey data, such as soil and land-use maps. Such parameterisations usually rely on a set of lookup tables and (pedo)transfer functions, relating elementary soil and site properties to model parameters. The aim of this paper is to describe and test a complete set of parameter estimation algorithms developed for the pesticide fate model MACRO, which accounts for preferential flow in soil macropores. We used tracer monitoring data from 16 lysimeter studies, carried out in three European countries, to evaluate the ability of MACRO and this "blind parameterisation" scheme to reproduce measured solute leaching at the base of each lysimeter. We focused on the prediction of early tracer breakthrough due to preferential flow, because this is critical for pesticide leaching. We then calibrated a selected number of parameters in order to assess to what extent the prediction of water and solute leaching could be improved. Our results show that water flow was generally reasonably well predicted (median model efficiency, ME, of 0.42). Although the general pattern of solute leaching was reproduced well by the model, the overall model efficiency was low (median ME = -0.26) due to errors in the timing and magnitude of some peaks. Preferential solute leaching at early pore volumes was also systematically underestimated. Nonetheless, the ranking of soils according to solute loads at early pore volumes was reasonably well estimated (concordance correlation coefficient, CCC, between 0.54 and 0.72). Moreover, we also found that ignoring macropore flow leads to a significant deterioration in the ability of the model to reproduce the observed leaching pattern, and especially the early breakthrough in some soils. Finally, the calibration procedure showed that improving the estimation of solute transport parameters is probably more important than the
Modeling the Near-Infrared Luminosity Functions of Young Stellar Clusters
NASA Astrophysics Data System (ADS)
Muench, August A.; Lada, Elizabeth A.; Lada, Charles J.
2000-04-01
We present the results of numerical experiments designed to evaluate the usefulness of near-infrared (NIR) luminosity functions for constraining the initial mass function (IMF) of young stellar populations. We test the sensitivity of the NIR K-band luminosity function (KLF) of a young stellar cluster to variations in the underlying IMF, star-forming history, and pre-main-sequence mass-to-luminosity relations. Using Monte Carlo techniques, we create a suite of model luminosity functions systematically varying each of these basic underlying relations. 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. Variations in a cluster's star-forming history are also found to produce significant changes in the KLF. In particular, we find that the KLFs of young clusters evolve in a systematic manner with increasing mean age. Our experiments indicate that variations in the PMS mass-to-luminosity relation, resulting from differences in adopted PMS tracks, produce only small effects on the form of the model luminosity functions and that these effects are mostly likely not detectable observationally. To illustrate the potential effectiveness of using the KLF of a young cluster to constrain its IMF, we model the observed KLF of the nearby Trapezium cluster. With knowledge of the star-forming history of this cluster obtained from optical spectroscopic studies, we derive the simplest underlying IMF whose model luminosity function matches the observations. Our derived mass function for the Trapezium spans 2 orders of magnitude in stellar mass (5>Msolar>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. Comparison
NASA Astrophysics Data System (ADS)
Atencia Yepez, A.; Autrán Cerqueira, J.; Urueña, S.; Jurado, R.
2012-01-01
This paper, developed under contract with European Aviation Safety Agency (EASA), analyses in detail which may be the certification implications in the aeronautic industry associated to the application of model-level verification and validation techniques. Particularly, this paper focuses on the problematic of detecting unintended functions by applying Model Coverage Criteria at model level. This point is significantly important for the future extensive use of Model Based approaches in safety critical software, since the uncertainty in the system performance introduced by the unintended functions, which may also lead to unacceptable hazardous or catastrophic events, prevents the system to be compliance with certification requirements. The paper provides a definition and a categorization of unintended functions and gives some relevant examples to assess the efficiency of model- coverage techniques in the detection of UF. The paper explains how this analysis is supported by a methodology based on the study of sources for introducing unintended functions. Finally it is analysed the feasibility of using Model-level verification techniques to support the software certification process.
Memory for places: a navigational model in support of Marr's theory of hippocampal function.
Recce, M; Harris, K D
1996-01-01
In this report we describe a model that applies Marr's theory of hippocampal function to the problem of map-based navigation. Like many others we attribute a spatial memory function to the hippocampus, but we suggest that the additional functional components required for map-based navigation are located elsewhere in the brain. One of the key functional components in this model is an egocentric map of space, located in the neocortex, that is continuously updated using ideothetic (self-motion) information. The hippocampus stores snapshots of this egocentric map. The modeled activity pattern of head direction cells is used to set the best egocentric map rotation to match the snapshots stored in the hippocampus, resulting in place cells with a nondirectional firing pattern. We describe an evaluation of this model using a mobile robot and demonstrate that with this model the robot can recognize an environment and find a hidden goal. This model is discussed in the context of prior experiments that were designed to discover the map-based spatial processing of animals. We also predict the results of further experiments. PMID:9034859
Memory for places: a navigational model in support of Marr's theory of hippocampal function.
Recce, M; Harris, K D
1996-01-01
In this report we describe a model that applies Marr's theory of hippocampal function to the problem of map-based navigation. Like many others we attribute a spatial memory function to the hippocampus, but we suggest that the additional functional components required for map-based navigation are located elsewhere in the brain. One of the key functional components in this model is an egocentric map of space, located in the neocortex, that is continuously updated using ideothetic (self-motion) information. The hippocampus stores snapshots of this egocentric map. The modeled activity pattern of head direction cells is used to set the best egocentric map rotation to match the snapshots stored in the hippocampus, resulting in place cells with a nondirectional firing pattern. We describe an evaluation of this model using a mobile robot and demonstrate that with this model the robot can recognize an environment and find a hidden goal. This model is discussed in the context of prior experiments that were designed to discover the map-based spatial processing of animals. We also predict the results of further experiments.
Bignardi, A B; El Faro, L; Torres Júnior, R A A; Cardoso, V L; Machado, P F; Albuquerque, L G
2011-01-01
We analyzed 152,145 test-day records from 7317 first lactations of Holstein cows recorded from 1995 to 2003. Our objective was to model variations in test-day milk yield during the first lactation of Holstein cows by random regression model (RRM), using various functions in order to obtain adequate and parsimonious models for the estimation of genetic parameters. Test-day milk yields were grouped into weekly classes of days in milk, ranging from 1 to 44 weeks. The contemporary groups were defined as herd-test-day. The analyses were performed using a single-trait RRM, including the direct additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. The mean trend of milk yield was modeled with a fourth-order orthogonal Legendre polynomial. The additive genetic and permanent environmental covariance functions were estimated by random regression on two parametric functions, Ali and Schaeffer and Wilmink, and on B-spline functions of days in milk. The covariance components and the genetic parameters were estimated by the restricted maximum likelihood method. Results from RRM parametric and B-spline functions were compared to RRM on Legendre polynomials and with a multi-trait analysis, using the same data set. Heritability estimates presented similar trends during mid-lactation (13 to 31 weeks) and between week 37 and the end of lactation, for all RRM. Heritabilities obtained by multi-trait analysis were of a lower magnitude than those estimated by RRM. The RRMs with a higher number of parameters were more useful to describe the genetic variation of test-day milk yield throughout the lactation. RRM using B-spline and Legendre polynomials as base functions appears to be the most adequate to describe the covariance structure of the data.
Alternate forms of the associated Legendre functions for use in geomagnetic modeling.
Alldredge, L.R.; Benton, E.R.
1986-01-01
An inconvenience attending traditional use of associated Legendre functions in global modeling is that the functions are not separable with respect to the 2 indices (order and degree). In 1973 Merilees suggested a way to avoid the problem by showing that associated Legendre functions of order m and degree m+k can be expressed in terms of elementary functions. This note calls attention to some possible gains in time savings and accuracy in geomagnetic modeling based upon this form. For this purpose, expansions of associated Legendre polynomials in terms of sines and cosines of multiple angles are displayed up to degree and order 10. Examples are also given explaining how some surface spherical harmonics can be transformed into true Fourier series for selected polar great circle paths. -from Authors
The GRB luminosity function: prediction of the internal shock model and comparison to observations
Zitouni, H.; Daigne, F.; Mochkovitch, R.
2008-05-22
We compute the expected GRB luminosity function in the internal shock model. We find that if the population of GRB central engines produces all kind of relativistic outflows, from very smooth to highly variable, the luminosity function has to branchs: at low luminosity, the distribution is dominated by low efficiency GRBs and is close to a power law of slope -0.5, whereas at high luminosity, the luminosity function follows the distribution of injected kinetic power. Using Monte Carlo simulations and several observational constrains (BATSE logN-logP diagram, peak energy distribution of bright BATSE bursts, fraction of XRFs in the HETE2 sample), we show that it is currently impossible to distinguish between a single power law or a broken power law luminosity function. However, when the second case is considered, the low-luminosity slope is found to be -0.6{+-}0.2, which is compatible with the prediction of the internal shock model.
Determinants of functioning and well-being among individuals with schizophrenia: An integrated model
Yanos, P.T.; Moos, R.H.
2006-01-01
Outcomes for health conditions are typically the result of multiple factors; however, studies tend to focus on a narrow class of variables. Functioning and well-being outcomes for schizophrenia are diverse and have resisted simple explanation; however, prior research has not offered an integrated understanding of the relative contributions of enduring and episodic environmental factors, personal resources and psychiatric factors, and cognitive appraisal and coping, on functioning and well-being outcomes in schizophrenia. The present article sets out an integrated model of the determinants of functioning and well-being among individuals with schizophrenia. To examine evidence that bears on the model, literature on hypothesized relationships is reviewed to identify areas for which there is strong evidence and areas where more research is needed. The article suggests areas for further research, and directs researchers and practitioners toward areas of intervention that can enhance functioning and well-being for persons diagnosed with schizophrenia. PMID:16480804
Klika, Václav; Gaffney, Eamonn A; Chen, Ying-Chun; Brown, Cameron P
2016-09-01
There is a long history of mathematical and computational modelling with the objective of understanding the mechanisms governing cartilage׳s remarkable mechanical performance. Nonetheless, despite sophisticated modelling development, simulations of cartilage have consistently lagged behind structural knowledge and thus the relationship between structure and function in cartilage is not fully understood. However, in the most recent generation of studies, there is an emerging confluence between our structural knowledge and the structure represented in cartilage modelling. This raises the prospect of further refinement in our understanding of cartilage function and also the initiation of an engineering-level understanding for how structural degradation and ageing relates to cartilage dysfunction and pathology, as well as informing the potential design of prospective interventions. Aimed at researchers entering the field of cartilage modelling, we thus review the basic principles of cartilage models, discussing the underlying physics and assumptions in relatively simple settings, whilst presenting the derivation of relatively parsimonious multiphase cartilage models consistent with our discussions. We proceed to consider modern developments that start aligning the structure captured in the models with observed complexities. This emphasises the challenges associated with constitutive relations, boundary conditions, parameter estimation and validation in cartilage modelling programmes. Consequently, we further detail how both experimental interrogations and modelling developments can be utilised to investigate and reduce such difficulties before summarising how cartilage modelling initiatives may improve our understanding of cartilage ageing, pathology and intervention. PMID:27195911
STRONG GRAVITATIONAL LENS MODELING WITH SPATIALLY VARIANT POINT-SPREAD FUNCTIONS
Rogers, Adam; Fiege, Jason D.
2011-12-10
Astronomical instruments generally possess spatially variant point-spread functions, which determine the amount by which an image pixel is blurred as a function of position. Several techniques have been devised to handle this variability in the context of the standard image deconvolution problem. We have developed an iterative gravitational lens modeling code called Mirage that determines the parameters of pixelated source intensity distributions for a given lens model. We are able to include the effects of spatially variant point-spread functions using the iterative procedures in this lensing code. In this paper, we discuss the methods to include spatially variant blurring effects and test the results of the algorithm in the context of gravitational lens modeling problems.
Tse, Wai S; Rochelle, Tina L; Cheung, Jacky C K
2011-06-01
The relationship between personality, social functioning, and depression remains unclear. The present study employs structural equation modeling to examine the mediating role of social functioning between harm avoidance (HA), self-directedness (SD), and depression. A sample of 902 individuals completed a self-report questionnaire consisting of the following scales: HA and SD subscales of the Temperament and Character Inventory (TCI), Beck Depression Inventory (BDI), and Social Adaptation Self-Evaluation Scale (SASS). Structural equation modeling via analysis of moment structure was used to estimate the fit of nine related models. Results indicated that social functioning is a mediator between harm avoidance or self-directness and depression. Self-directedness was also shown to have direct effects on depression. The results support the social reinforcement theory of depression and provide a theoretical account of how the variables are related based on correlation methods. Suggestions are offered for future experimental and longitudinal research.
Micromechanics-based elastic model for functionally graded materials with particle interactions
Yin, H.M.; Sun, L.Z.; Paulino, G.H
2004-07-12
A micromechanics-based elastic model is developed for two-phase functionally graded materials with locally pair-wise interactions between particles. While the effective material properties change gradually along the gradation direction, there exist two microstructurally distinct zones: particle-matrix zone and transition zone. In the particle-matrix zone, pair-wise interactions between particles are employed using a modified Green's function method. By integrating the interactions from all other particles over the representative volume element, the homogenized elastic fields are obtained. The effective stiffness distribution over the gradation direction is further derived. In the transition zone, a transition function is constructed to make the homogenized elastic fields continuous and differentiable in the gradation direction. The model prediction is compared with other models and experimental data to demonstrate the capability of the proposed method.
Perveen, Nazia; Barot, Sébastien; Alvarez, Gaël; Klumpp, Katja; Martin, Raphael; Rapaport, Alain; Herfurth, Damien; Louault, Frédérique; Fontaine, Sébastien
2014-04-01
Integration of the priming effect (PE) in ecosystem models is crucial to better predict the consequences of global change on ecosystem carbon (C) dynamics and its feedbacks on climate. Over the last decade, many attempts have been made to model PE in soil. However, PE has not yet been incorporated into any ecosystem models. Here, we build plant/soil models to explore how PE and microbial diversity influence soil/plant interactions and ecosystem C and nitrogen (N) dynamics in response to global change (elevated CO2 and atmospheric N depositions). Our results show that plant persistence, soil organic matter (SOM) accumulation, and low N leaching in undisturbed ecosystems relies on a fine adjustment of microbial N mineralization to plant N uptake. This adjustment can be modeled in the SYMPHONY model by considering the destruction of SOM through PE, and the interactions between two microbial functional groups: SOM decomposers and SOM builders. After estimation of parameters, SYMPHONY provided realistic predictions on forage production, soil C storage and N leaching for a permanent grassland. Consistent with recent observations, SYMPHONY predicted a CO2 -induced modification of soil microbial communities leading to an intensification of SOM mineralization and a decrease in the soil C stock. SYMPHONY also indicated that atmospheric N deposition may promote SOM accumulation via changes in the structure and metabolic activities of microbial communities. Collectively, these results suggest that the PE and functional role of microbial diversity may be incorporated in ecosystem models with a few additional parameters, improving accuracy of predictions.
Perveen, Nazia; Barot, Sébastien; Alvarez, Gaël; Klumpp, Katja; Martin, Raphael; Rapaport, Alain; Herfurth, Damien; Louault, Frédérique; Fontaine, Sébastien
2014-04-01
Integration of the priming effect (PE) in ecosystem models is crucial to better predict the consequences of global change on ecosystem carbon (C) dynamics and its feedbacks on climate. Over the last decade, many attempts have been made to model PE in soil. However, PE has not yet been incorporated into any ecosystem models. Here, we build plant/soil models to explore how PE and microbial diversity influence soil/plant interactions and ecosystem C and nitrogen (N) dynamics in response to global change (elevated CO2 and atmospheric N depositions). Our results show that plant persistence, soil organic matter (SOM) accumulation, and low N leaching in undisturbed ecosystems relies on a fine adjustment of microbial N mineralization to plant N uptake. This adjustment can be modeled in the SYMPHONY model by considering the destruction of SOM through PE, and the interactions between two microbial functional groups: SOM decomposers and SOM builders. After estimation of parameters, SYMPHONY provided realistic predictions on forage production, soil C storage and N leaching for a permanent grassland. Consistent with recent observations, SYMPHONY predicted a CO2 -induced modification of soil microbial communities leading to an intensification of SOM mineralization and a decrease in the soil C stock. SYMPHONY also indicated that atmospheric N deposition may promote SOM accumulation via changes in the structure and metabolic activities of microbial communities. Collectively, these results suggest that the PE and functional role of microbial diversity may be incorporated in ecosystem models with a few additional parameters, improving accuracy of predictions. PMID:24339186
NASA Astrophysics Data System (ADS)
Greaves, Simon John; Muraoka, Hiroaki; Kanai, Yasushi
2015-05-01
Brillouin functions were used to model the temperature dependence of magnetisation in media for heat assisted magnetic recording. Although dHk/dT was higher when Brillouin functions with J = 0.5 or J = 1 were used, an earlier onset of the linear reversal mode led to a drop in dHc/dT near to Tc, resulting in wider written bits. Tracks written with a higher thermal gradient were also wider when J was small and had lower SNR.
Measurement and modeling of transfer functions for lightning coupling into the Sago mine.
Morris, Marvin E.; Higgins, Matthew B.
2007-04-01
This report documents measurements and analytical modeling of electromagnetic transfer functions to quantify the ability of cloud-to-ground lightning strokes (including horizontal arc-channel components) to couple electromagnetic energy into the Sago mine located near Buckhannon, WV. Two coupling mechanisms were measured: direct and indirect drive. These transfer functions are then used to predict electric fields within the mine and induced voltages on conductors that were left abandoned in the sealed area of the Sago mine.
Correlation functions of the antiferromagnetic Heisenberg model using a modified Lanczos method
NASA Astrophysics Data System (ADS)
Gagliano, Eduardo R.; Dagotto, Elbio; Moreo, Adriana; Alcaraz, Francisco C.
1986-08-01
Using a modified Lanczos algorithm, we study the correlation functions in the ground state of the one-dimensional antiferromagnetic Heisenberg model. We obtain numerical results for rings up to 24 sites. There are no indications of the anomalous behavior of these correlation functions recently observed in chains with 16 sites. We also present a pedagogical description of the hashing technique which is an efficient algorithm for searching and storage purposes.
The effects of videotape modeling on staff acquisition of functional analysis methodology.
Moore, James W; Fisher, Wayne W
2007-01-01
Lectures and two types of video modeling were compared to determine their relative effectiveness in training 3 staff members to conduct functional analysis sessions. Video modeling that contained a larger number of therapist exemplars resulted in mastery-level performance eight of the nine times it was introduced, whereas neither lectures nor partial video modeling produced significant improvements in performance. Results demonstrated that video modeling provided an effective training strategy but only when a wide range of exemplars of potential therapist behaviors were depicted in the videotape. PMID:17471805
Optimization of global model composed of radial basis functions using the term-ranking approach
Cai, Peng; Tao, Chao Liu, Xiao-Jun
2014-03-15
A term-ranking method is put forward to optimize the global model composed of radial basis functions to improve the predictability of the model. The effectiveness of the proposed method is examined by numerical simulation and experimental data. Numerical simulations indicate that this method can significantly lengthen the prediction time and decrease the Bayesian information criterion of the model. The application to real voice signal shows that the optimized global model can capture more predictable component in chaos-like voice data and simultaneously reduce the predictable component (periodic pitch) in the residual signal.
NASA Astrophysics Data System (ADS)
González, Diego Luis; Pimpinelli, Alberto; Einstein, T. L.
2011-07-01
We study the configurational structure of the point-island model for epitaxial growth in one dimension. In particular, we calculate the island gap and capture zone distributions. Our model is based on an approximate description of nucleation inside the gaps. Nucleation is described by the joint probability density pnXY(x,y), which represents the probability density to have nucleation at position x within a gap of size y. Our proposed functional form for pnXY(x,y) describes excellently the statistical behavior of the system. We compare our analytical model with extensive numerical simulations. Our model retains the most relevant physical properties of the system.
The effects of videotape modeling on staff acquisition of functional analysis methodology.
Moore, James W; Fisher, Wayne W
2007-01-01
Lectures and two types of video modeling were compared to determine their relative effectiveness in training 3 staff members to conduct functional analysis sessions. Video modeling that contained a larger number of therapist exemplars resulted in mastery-level performance eight of the nine times it was introduced, whereas neither lectures nor partial video modeling produced significant improvements in performance. Results demonstrated that video modeling provided an effective training strategy but only when a wide range of exemplars of potential therapist behaviors were depicted in the videotape.
A new anisotropic compact star model having Matese & Whitman mass function
NASA Astrophysics Data System (ADS)
Bhar, Piyali; Ratanpal, B. S.
2016-07-01
Present paper proposed a new singularity free model of anisotropic compact star. The Einstein field equations are solved in closed form by utilizing Matese & Whitman mass function. The model parameters ρ, pr and pt all are well behaved inside the stellar interior and our model satisfies all the required conditions to be physically acceptable. The model given in the present work is compatible with observational data of compact objects like SAX J 1808.4-3658 (SS1), SAX J 1808.4-3658 (SS2) and 4U 1820-30. A particular model of 4U 1820-30 is studied in detail and found that it satisfies all the condition needed for physically acceptable model. The present work is the generalization of Sharma and Ratanpal (Int. J. Mod. Phys. D 22:1350074, 2013) model for compact stars admitting quadratic equation of state.
Modeling the Hemodynamic Response Function in fMRI: Efficiency, Bias and Mis-modeling
Lindquist, Martin A.; Loh, Ji Meng; Atlas, Lauren Y.; Wager, Tor D.
2012-01-01
Most brain research to date has focused on studying the amplitude of evoked fMRI responses, though there has recently been an increased interest in measuring onset, peak latency and duration of the responses as well. A number of modeling procedures provide measures of the latency and duration of fMRI responses. In this work we compare several techniques that vary in their assumptions, model complexity, and interpretation. For each method, we introduce methods for estimating amplitude, peak latency, and duration and for performing inference in a multi-subject fMRI setting. We then assess the techniques’ relative sensitivity and their propensity for mis-attributing task effects on one parameter (e.g., duration) to another (e.g., amplitude). Finally, we introduce methods for quantifying model misspecification and assessing bias and power-loss related to the choice of model. Overall, the results show that it is surprisingly difficult to accurately recover true task-evoked changes in BOLD signal and that there are substantial differences among models in terms of power, bias and parameter confusability. Because virtually all fMRI studies in cognitive and affective neuroscience employ these models, the results bear on the interpretation of hemodynamic response estimates across a wide variety of psychological and neuroscientific studies. PMID:19084070
Roche, David; Gil, Debora; Giraldo, Jesús
2014-01-01
Empirical and mechanistic models differ in their approaches to the analysis of pharmacological effect. Whereas the parameters of the former are not physical constants those of the latter embody the nature, often complex, of biology. Empirical models are exclusively used for curve fitting, merely to characterize the shape of the E/[A] curves. Mechanistic models, on the contrary, enable the examination of mechanistic hypotheses by parameter simulation. Regretfully, the many parameters that mechanistic models may include can represent a great difficulty for curve fitting, representing, thus, a challenge for computational method development. In the present study some empirical and mechanistic models are shown and the connections, which may appear in a number of cases between them, are analyzed from the curves they yield. It may be concluded that systematic and careful curve shape analysis can be extremely useful for the understanding of receptor function, ligand classification and drug discovery, thus providing a common language for the communication between pharmacologists and medicinal chemists.
Integration of multiscale dendritic spine structure and function data into systems biology models
Mancuso, James J.; Cheng, Jie; Yin, Zheng; Gilliam, Jared C.; Xia, Xiaofeng; Li, Xuping; Wong, Stephen T. C.
2014-01-01
Comprising 1011 neurons with 1014 synaptic connections the human brain is the ultimate systems biology puzzle. An increasing body of evidence highlights the observation that changes in brain function, both normal and pathological, consistently correlate with dynamic changes in neuronal anatomy. Anatomical changes occur on a full range of scales from the trafficking of individual proteins, to alterations in synaptic morphology both individually and on a systems level, to reductions in long distance connectivity and brain volume. The major sites of contact for synapsing neurons are dendritic spines, which provide an excellent metric for the number and strength of signaling connections between elements of functional neuronal circuits. A comprehensive model of anatomical changes and their functional consequences would be a holy grail for the field of systems neuroscience but its realization appears far on the horizon. Various imaging technologies have advanced to allow for multi-scale visualization of brain plasticity and pathology, but computational analysis of the big data sets involved forms the bottleneck toward the creation of multiscale models of brain structure and function. While a full accounting of techniques and progress toward a comprehensive model of brain anatomy and function is beyond the scope of this or any other single paper, this review serves to highlight the opportunities for analysis of neuronal spine anatomy and function provided by new imaging technologies and the high-throughput application of older technologies while surveying the strengths and weaknesses of currently available computational analytical tools and room for future improvement. PMID:25429262
Larsen, Flemming H.; Engelsen, Søren B.
2015-01-01
Microbial polysaccharides represent an important class of microbial polymers with diverse functions such as biofilm formation, thickening, and gelling properties as well as health-promoting properties. The broad range of exopolysaccharide (EPS) functionalities has sparked a renewed interest in this class of molecules. Chemical, enzymatic as well as genetic modifications by metabolic engineering can be used to create large numbers of analogous EPS variants with respect to EPS functionality. While this top–down approach is effective in finding new candidates for desired functionality, there seems to be a lack of the corresponding bottom–up approach. The molecular mechanisms of the desired functionalities can be established from Nuclear Magnetic Resonance (NMR) and molecular models and it is proposed that these models can be fed back into the biotechnology by using a quantitative structure–property approach. In this way it will be possible to tailor specific functionality within a given design space. This perspective will include two well-known commercial microbial EPS examples namely gellan and diutan and show how even a limited use of multiphase NMR and molecular modeling can increase the insight into their different properties, which are based on only minor structural differences. PMID:26696983
A new guide for commissioning air handling systems: Using a model functional test
Haasl, Tudi; Sellers, David; Friedman, Hannah; Piette, Mary Ann; Bourassa, Norman; Gillespie, Ken
2002-05-01
Functional tests are a set of detailed instructions for building commissioning that demand extensive HVAC system knowledge to write and perform. Understanding the energy use implications and theory behind the test procedures, estimating the costs and benefits of doing a particular test, implementing the tests correctly, and resolving problems require years of field experience. As part of a large research project now underway, a practical guide is being developed that communicates this knowledge. This paper presents the components and intended use of the Functional Testing Guide and Model Functional Test for Air Handling Systems. A series of model functional tests, starting at the outdoor air intake section and proceeding through the air handling unit, distribution system, and terminal equipment and ending at the exhaust air discharge point, are provided for many commonly installed air handling system configurations. The model functional tests contain advice for tailoring the test procedures to specific system configurations, desirable and undesirable testing outcomes, a calculation appendix, references to other resources, and examples of completed test forms. The guide is an educational resource, with background information that clarifies the principles behind testing configurations and results. The functional tests have been selected from an extensive commissioning test protocol library compiled by Pacific Gas and Electric in 2001. The guide also includes a design guideline for the selection of control and monitoring points and a design intent documentation form.
Retrieving the Green's function of attenuating heterogeneous media by time-reversal modeling
NASA Astrophysics Data System (ADS)
Zhu, T.
2014-12-01
The Green's function between two locations within which seismograms that were not physically recorded, are retrieved by cross-correlation, convolution or deconvolution and summation of other recorded wavefields (also known as seismic interferometry). More recently seismic interferometry was applied in exploration seismology by Bakulin and Calvert (2006) and Schuster et al. (2004), in ultrasound by Weaver and Lobkis (2001), in crustal seismology by Campillo and Paul (2003), Sabra et al. (2005a, b), Roux et al. (2005) and Shapiro et al. (2005), and in helioseismology by Rickett and Claerbout (1999). Theory of the retrieval of Green's function can also be represented by time-reversal propagation because of time invariance of wave equations in the lossless media. In the presence of intrinsic attenuation in the media, however, the time invariance of wave equations is invalid. My previous work present methods of using novel viscoacoustic and viscoelastic wave equations to recover the time invariance property of such wave equations for viscoacoustic and viscoelastic time-reversal modeling. More importantly, attenuation effects are compensated for during time-reversal wave propagation. In this paper, I investigate the possibility of retrieving the Green's function through time-reversal modeling techniques in attenuating media. I consider two different models to illustrate the feasibility of Green's function retrieval in attenuating media. I consider the viscoacoustic as well as the viscoelastic situation. Numerical results show that the Green's function can be retrieved in the correct amplitude and phase by time-reversal modeling with compensating both amplitude loss and dispersion effects.
Analysis of functional importance of binding sites in the Drosophila gap gene network model
2015-01-01
Background The statistical thermodynamics based approach provides a promising framework for construction of the genotype-phenotype map in many biological systems. Among important aspects of a good model connecting the DNA sequence information with that of a molecular phenotype (gene expression) is the selection of regulatory interactions and relevant transcription factor bindings sites. As the model may predict different levels of the functional importance of specific binding sites in different genomic and regulatory contexts, it is essential to formulate and study such models under different modeling assumptions. Results We elaborate a two-layer model for the Drosophila gap gene network and include in the model a combined set of transcription factor binding sites and concentration dependent regulatory interaction between gap genes hunchback and Kruppel. We show that the new variants of the model are more consistent in terms of gene expression predictions for various genetic constructs in comparison to previous work. We quantify the functional importance of binding sites by calculating their impact on gene expression in the model and calculate how these impacts correlate across all sites under different modeling assumptions. Conclusions The assumption about the dual interaction between hb and Kr leads to the most consistent modeling results, but, on the other hand, may obscure existence of indirect interactions between binding sites in regulatory regions of distinct genes. The analysis confirms the previously formulated regulation concept of many weak binding sites working in concert. The model predicts a more or less uniform distribution of functionally important binding sites over the sets of experimentally characterized regulatory modules and other open chromatin domains. PMID:26694511
Quasiclassical approach to partition functions of ions in a chemical plasma model
Shpatakovskaya, G. V.
2008-03-15
The partition functions of ions that are used in a chemical plasma model are estimated by the Thomas-Fermi free ion model without reference to empirical data. Different form factors limiting the number of the excitation levels taken into account are considered, namely, those corresponding to the average atomic radius criterion, the temperature criterion, and the Planck-Brillouin-Larkin approximation. Expressions are presented for the average excitation energy and for the temperature and volume derivatives of the partition function. A comparison with the results of the empirical approach is made for the aluminum and iron plasmas.
Phytomonas: A non-pathogenic trypanosomatid model for functional expression of proteins.
Miranda, Mariana R; Sayé, Melisa; Reigada, Chantal; Carrillo, Carolina; Pereira, Claudio A
2015-10-01
Phytomonas are protozoan parasites from the Trypanosomatidae family which infect a wide variety of plants. Herein, Phytomonas Jma was tested as a model for functional expression of heterologous proteins. Green fluorescent protein expression was evaluated in Phytomonas and compared with Trypanosoma cruzi, the etiological agent of Chagas' disease. Phytomonas was able to express GFP at levels similar to T. cruzi although the transgenic selection time was higher. It was possible to establish an efficient transfection and selection protocol for protein expression. These results demonstrate that Phytomonas can be a good model for functional expression of proteins from other trypanosomatids, presenting the advantage of being completely safe for humans. PMID:26142019
Accurate FDTD modelling for dispersive media using rational function and particle swarm optimisation
NASA Astrophysics Data System (ADS)
Chung, Haejun; Ha, Sang-Gyu; Choi, Jaehoon; Jung, Kyung-Young
2015-07-01
This article presents an accurate finite-difference time domain (FDTD) dispersive modelling suitable for complex dispersive media. A quadratic complex rational function (QCRF) is used to characterise their dispersive relations. To obtain accurate coefficients of QCRF, in this work, we use an analytical approach and a particle swarm optimisation (PSO) simultaneously. In specific, an analytical approach is used to obtain the QCRF matrix-solving equation and PSO is applied to adjust a weighting function of this equation. Numerical examples are used to illustrate the validity of the proposed FDTD dispersion model.
Phytomonas: A non-pathogenic trypanosomatid model for functional expression of proteins.
Miranda, Mariana R; Sayé, Melisa; Reigada, Chantal; Carrillo, Carolina; Pereira, Claudio A
2015-10-01
Phytomonas are protozoan parasites from the Trypanosomatidae family which infect a wide variety of plants. Herein, Phytomonas Jma was tested as a model for functional expression of heterologous proteins. Green fluorescent protein expression was evaluated in Phytomonas and compared with Trypanosoma cruzi, the etiological agent of Chagas' disease. Phytomonas was able to express GFP at levels similar to T. cruzi although the transgenic selection time was higher. It was possible to establish an efficient transfection and selection protocol for protein expression. These results demonstrate that Phytomonas can be a good model for functional expression of proteins from other trypanosomatids, presenting the advantage of being completely safe for humans.
New parton structure functions and minijets in the two-component dual parton model
Bopp, F.W.; Pertermann, D. ); Engel, R. ); Ranft, J. )
1994-04-01
We use new fits to parton structure functions, including structure functions with Lipatov behavior at small [ital x] values and discuss the minijet component in the two-component dual parton model with a supercritical Pomeron as demanded by the fits to cross-section data. We find that a consistent model can only be formulated with a [ital p][sub [perpendicular]hr] cutoff for the minijets increasing with energy. The implications for particle production in hadronic collisions at TeV energies are discussed.
Object-oriented DFD models to present the functional and behavioral views
Maxted, A.
1993-06-01
An object-oriented methodology is presented that is based on two sets of Data Flow Diagrams (DFDs): one for the functional view, and one for the behavioral view. The functional view presents the information flow between shared objects. These objects map to the classes identified in the structural view (e.g., Information Model). The behavioral view presents the flow of information between control components and relates these components to their state models. Components appearing in multiple views provide a bridge between the views. The top-down hierarchical nature of the DFDs provide a needed overview or road map through the software system.
Chen, Xiaohong; Fan, Yanqin; Pouzo, Demian; Ying, Zhiliang
2010-07-01
We study estimation and model selection of semiparametric models of multivariate survival functions for censored data, which are characterized by possibly misspecified parametric copulas and nonparametric marginal survivals. We obtain the consistency and root-n asymptotic normality of a two-step copula estimator to the pseudo-true copula parameter value according to KLIC, and provide a simple consistent estimator of its asymptotic variance, allowing for a first-step nonparametric estimation of the marginal survivals. We establish the asymptotic distribution of the penalized pseudo-likelihood ratio statistic for comparing multiple semiparametric multivariate survival functions subject to copula misspecification and general censorship. An empirical application is provided.
Chen, Xiaohong; Fan, Yanqin; Pouzo, Demian; Ying, Zhiliang
2010-07-01
We study estimation and model selection of semiparametric models of multivariate survival functions for censored data, which are characterized by possibly misspecified parametric copulas and nonparametric marginal survivals. We obtain the consistency and root-n asymptotic normality of a two-step copula estimator to the pseudo-true copula parameter value according to KLIC, and provide a simple consistent estimator of its asymptotic variance, allowing for a first-step nonparametric estimation of the marginal survivals. We establish the asymptotic distribution of the penalized pseudo-likelihood ratio statistic for comparing multiple semiparametric multivariate survival functions subject to copula misspecification and general censorship. An empirical application is provided. PMID:24790286
A model function of the global bomb tritium distribution in precipitation, 1960-1986
NASA Astrophysics Data System (ADS)
Doney, Scott C.; Glover, David M.; Jenkins, William J.
1992-04-01
The paper presents a model function for predicting the annual mean concentration of the decay-corrected bomb tritium in precipitation over the time period 1960-1986. The model was developed using the World Meteorological Organization/International Atomic Energy Agency data for tritium precipitation. The resulting tritium function is global in scope and includes both marine and continental data. Estimates were obtained of the seasonal cycle of tritium in precipitation, which may be useful for studying atmospheric transport and oceanic processes, such as convection and subduction that occur on seasonal timescales.
Models for mixed irradiation with a 'reciprocal-time' pattern of the repair function.
Suzuki, Shozo; Miura, Yuri; Mizuno, Shoichi; Furusawa, Yoshiya
2002-09-01
Suzuki presented models for mixed irradiation with two and multiple types of radiation by extending the Zaider and Rossi model, which is based on the theory of dual radiation action. In these models, the repair function was simply assumed to be semi-logarithmically linear (i.e., monoexponential), or a first-order process, which has been experimentally contradicted. Fowler, however, suggested that the repair of radiation damage might be largely a second-order process rather than a first-order one, and presented data in support of this hypothesis. In addition, a second-order repair function is preferred to an n-exponential repair function for the reason that only one parameter is used in the former instead of 2n-1 parameters for the latter, although both repair functions show a good fit to the experimental data. However, according to a second-order repair function, the repair rate depends on the dose, which is incompatible with the experimental data. We, therefore, revised the models for mixed irradiation by Zaider and Rossi and by Suzuki, by substituting a 'reciprocal-time' pattern of the repair function, which is derived from the assumption that the repair rate is independent of the dose in a second-order repair function, for a first-order one in reduction and interaction factors of the models, although the underlying mechanism for this assumption cannot be well-explained. The reduction factor, which reduces the contribution of the square of a dose to cell killing in the linear-quadratic model and its derivatives, and the interaction factor, which also reduces the contribution of the interaction of two or more doses of different types of radiation, were formulated by using a 'reciprocal-time' pattern of the repair function. Cell survivals calculated from the older and the newly modified models were compared in terms of the dose-rate by assuming various types of single and mixed irradiation. The result implies that the newly modified models for mixed irradiation can
Functional linear models to test for differences in prairie wetland hydraulic gradients
Greenwood, Mark C.; Sojda, Richard S.; Preston, Todd M.; Swayne, David A.; Yang, Wanhong; Voinov, A.A.; Rizzoli, A.; Filatova, T.
2010-01-01
Functional data analysis provides a framework for analyzing multiple time series measured frequently in time, treating each series as a continuous function of time. Functional linear models are used to test for effects on hydraulic gradient functional responses collected from three types of land use in Northeastern Montana at fourteen locations. Penalized regression-splines are used to estimate the underlying continuous functions based on the discretely recorded (over time) gradient measurements. Permutation methods are used to assess the statistical significance of effects. A method for accommodating missing observations in each time series is described. Hydraulic gradients may be an initial and fundamental ecosystem process that responds to climate change. We suggest other potential uses of these methods for detecting evidence of climate change.