The Importance of Behavioral Thresholds and Objective Functions in Contaminant Transport Uncertainty Analysis

NASA Astrophysics Data System (ADS)

Sykes, J. F.; Kang, M.; Thomson, N. R.

2007-12-01

The TCE release from The Lockformer Company in Lisle Illinois resulted in a plume in a confined aquifer that is more than 4 km long and impacted more than 300 residential wells. Many of the wells are on the fringe of the plume and have concentrations that did not exceed 5 ppb. The settlement for the Chapter 11 bankruptcy protection of Lockformer involved the establishment of a trust fund that compensates individuals with cancers with payments being based on cancer type, estimated TCE concentration in the well and the duration of exposure to TCE. The estimation of early arrival times and hence low likelihood events is critical in the determination of the eligibility of an individual for compensation. Thus, an emphasis must be placed on the accuracy of the leading tail region in the likelihood distribution of possible arrival times at a well. The estimation of TCE arrival time, using a three-dimensional analytical solution, involved parameter estimation and uncertainty analysis. Parameters in the model included TCE source parameters, groundwater velocities, dispersivities and the TCE decay coefficient for both the confining layer and the bedrock aquifer. Numerous objective functions, which include the well-known L2-estimator, robust estimators (L1-estimators and M-estimators), penalty functions, and dead zones, were incorporated in the parameter estimation process to treat insufficiencies in both the model and observational data due to errors, biases, and limitations. The concept of equifinality was adopted and multiple maximum likelihood parameter sets were accepted if pre-defined physical criteria were met. The criteria ensured that a valid solution predicted TCE concentrations for all TCE impacted areas. Monte Carlo samples are found to be inadequate for uncertainty analysis of this case study due to its inability to find parameter sets that meet the predefined physical criteria. Successful results are achieved using a Dynamically-Dimensioned Search sampling methodology that inherently accounts for parameter correlations and does not require assumptions regarding parameter distributions. For uncertainty analysis, multiple parameter sets were obtained using a modified Cauchy's M-estimator. Penalty functions had to be incorporated into the objective function definitions to generate a sufficient number of acceptable parameter sets. The combined effect of optimization and the application of the physical criteria perform the function of behavioral thresholds by reducing anomalies and by removing parameter sets with high objective function values. The factors that are important to the creation of an uncertainty envelope for TCE arrival at wells are outlined in the work. In general, greater uncertainty appears to be present at the tails of the distribution. For a refinement of the uncertainty envelopes, the application of additional physical criteria or behavioral thresholds is recommended.

Abuse behavior of high-power, lithium-ion cells

NASA Astrophysics Data System (ADS)

Spotnitz, R.; Franklin, J.

Published accounts of abuse testing of lithium-ion cells and components are summarized, including modeling work. From this summary, a set of exothermic reactions is selected with corresponding estimates of heats of reaction. Using this set of reactions, along with estimated kinetic parameters and designs for high-rate batteries, models for the abuse behavior (oven, short-circuit, overcharge, nail, crush) are developed. Finally, the models are used to determine that fluorinated binder plays a relatively unimportant role in thermal runaway.

Fitting membrane resistance along with action potential shape in cardiac myocytes improves convergence: application of a multi-objective parallel genetic algorithm.

PubMed

Kaur, Jaspreet; Nygren, Anders; Vigmond, Edward J

2014-01-01

Fitting parameter sets of non-linear equations in cardiac single cell ionic models to reproduce experimental behavior is a time consuming process. The standard procedure is to adjust maximum channel conductances in ionic models to reproduce action potentials (APs) recorded in isolated cells. However, vastly different sets of parameters can produce similar APs. Furthermore, even with an excellent AP match in case of single cell, tissue behaviour may be very different. We hypothesize that this uncertainty can be reduced by additionally fitting membrane resistance (Rm). To investigate the importance of Rm, we developed a genetic algorithm approach which incorporated Rm data calculated at a few points in the cycle, in addition to AP morphology. Performance was compared to a genetic algorithm using only AP morphology data. The optimal parameter sets and goodness of fit as computed by the different methods were compared. First, we fit an ionic model to itself, starting from a random parameter set. Next, we fit the AP of one ionic model to that of another. Finally, we fit an ionic model to experimentally recorded rabbit action potentials. Adding the extra objective (Rm, at a few voltages) to the AP fit, lead to much better convergence. Typically, a smaller MSE (mean square error, defined as the average of the squared error between the target AP and AP that is to be fitted) was achieved in one fifth of the number of generations compared to using only AP data. Importantly, the variability in fit parameters was also greatly reduced, with many parameters showing an order of magnitude decrease in variability. Adding Rm to the objective function improves the robustness of fitting, better preserving tissue level behavior, and should be incorporated.

Uncertainty quantification for constitutive model calibration of brain tissue.

PubMed

Brewick, Patrick T; Teferra, Kirubel

2018-05-31

The results of a study comparing model calibration techniques for Ogden's constitutive model that describes the hyperelastic behavior of brain tissue are presented. One and two-term Ogden models are fit to two different sets of stress-strain experimental data for brain tissue using both least squares optimization and Bayesian estimation. For the Bayesian estimation, the joint posterior distribution of the constitutive parameters is calculated by employing Hamiltonian Monte Carlo (HMC) sampling, a type of Markov Chain Monte Carlo method. The HMC method is enriched in this work to intrinsically enforce the Drucker stability criterion by formulating a nonlinear parameter constraint function, which ensures the constitutive model produces physically meaningful results. Through application of the nested sampling technique, 95% confidence bounds on the constitutive model parameters are identified, and these bounds are then propagated through the constitutive model to produce the resultant bounds on the stress-strain response. The behavior of the model calibration procedures and the effect of the characteristics of the experimental data are extensively evaluated. It is demonstrated that increasing model complexity (i.e., adding an additional term in the Ogden model) improves the accuracy of the best-fit set of parameters while also increasing the uncertainty via the widening of the confidence bounds of the calibrated parameters. Despite some similarity between the two data sets, the resulting distributions are noticeably different, highlighting the sensitivity of the calibration procedures to the characteristics of the data. For example, the amount of uncertainty reported on the experimental data plays an essential role in how data points are weighted during the calibration, and this significantly affects how the parameters are calibrated when combining experimental data sets from disparate sources. Published by Elsevier Ltd.

Global-scale regionalization of hydrological model parameters using streamflow data from many small catchments

NASA Astrophysics Data System (ADS)

Beck, Hylke; de Roo, Ad; van Dijk, Albert; McVicar, Tim; Miralles, Diego; Schellekens, Jaap; Bruijnzeel, Sampurno; de Jeu, Richard

2015-04-01

Motivated by the lack of large-scale model parameter regionalization studies, a large set of 3328 small catchments (< 10000 km2) around the globe was used to set up and evaluate five model parameterization schemes at global scale. The HBV-light model was chosen because of its parsimony and flexibility to test the schemes. The catchments were calibrated against observed streamflow (Q) using an objective function incorporating both behavioral and goodness-of-fit measures, after which the catchment set was split into subsets of 1215 donor and 2113 evaluation catchments based on the calibration performance. The donor catchments were subsequently used to derive parameter sets that were transferred to similar grid cells based on a similarity measure incorporating climatic and physiographic characteristics, thereby producing parameter maps with global coverage. Overall, there was a lack of suitable donor catchments for mountainous and tropical environments. The schemes with spatially-uniform parameter sets (EXP2 and EXP3) achieved the worst Q estimation performance in the evaluation catchments, emphasizing the importance of parameter regionalization. The direct transfer of calibrated parameter sets from donor catchments to similar grid cells (scheme EXP1) performed best, although there was still a large performance gap between EXP1 and HBV-light calibrated against observed Q. The schemes with parameter sets obtained by simultaneously calibrating clusters of similar donor catchments (NC10 and NC58) performed worse than EXP1. The relatively poor Q estimation performance achieved by two (uncalibrated) macro-scale hydrological models suggests there is considerable merit in regionalizing the parameters of such models. The global HBV-light parameter maps and ancillary data are freely available via http://water.jrc.ec.europa.eu.

Quantifying Parameter Sensitivity, Interaction and Transferability in Hydrologically Enhanced Versions of Noah-LSM over Transition Zones

NASA Technical Reports Server (NTRS)

Rosero, Enrique; Yang, Zong-Liang; Wagener, Thorsten; Gulden, Lindsey E.; Yatheendradas, Soni; Niu, Guo-Yue

2009-01-01

We use sensitivity analysis to identify the parameters that are most responsible for shaping land surface model (LSM) simulations and to understand the complex interactions in three versions of the Noah LSM: the standard version (STD), a version enhanced with a simple groundwater module (GW), and version augmented by a dynamic phenology module (DV). We use warm season, high-frequency, near-surface states and turbulent fluxes collected over nine sites in the US Southern Great Plains. We quantify changes in the pattern of sensitive parameters, the amount and nature of the interaction between parameters, and the covariance structure of the distribution of behavioral parameter sets. Using Sobol s total and first-order sensitivity indexes, we show that very few parameters directly control the variance of the model output. Significant parameter interaction occurs so that not only the optimal parameter values differ between models, but the relationships between parameters change. GW decreases parameter interaction and appears to improve model realism, especially at wetter sites. DV increases parameter interaction and decreases identifiability, implying it is overparameterized and/or underconstrained. A case study at a wet site shows GW has two functional modes: one that mimics STD and a second in which GW improves model function by decoupling direct evaporation and baseflow. Unsupervised classification of the posterior distributions of behavioral parameter sets cannot group similar sites based solely on soil or vegetation type, helping to explain why transferability between sites and models is not straightforward. This evidence suggests a priori assignment of parameters should also consider climatic differences.

Multistability, local pattern formation, and global collective firing in a small-world network of nonleaky integrate-and-fire neurons.

PubMed

Rothkegel, Alexander; Lehnertz, Klaus

2009-03-01

We investigate numerically the collective dynamical behavior of pulse-coupled nonleaky integrate-and-fire neurons that are arranged on a two-dimensional small-world network. To ensure ongoing activity, we impose a probability for spontaneous firing for each neuron. We study network dynamics evolving from different sets of initial conditions in dependence on coupling strength and rewiring probability. Besides a homogeneous equilibrium state for low coupling strength, we observe different local patterns including cyclic waves, spiral waves, and turbulentlike patterns, which-depending on network parameters-interfere with the global collective firing of the neurons. We attribute the various network dynamics to distinct regimes in the parameter space. For the same network parameters different network dynamics can be observed depending on the set of initial conditions only. Such a multistable behavior and the interplay between local pattern formation and global collective firing may be attributable to the spatiotemporal dynamics of biological networks.

Set statistics in conductive bridge random access memory device with Cu/HfO{sub 2}/Pt structure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Meiyun; Long, Shibing, E-mail: longshibing@ime.ac.cn; Wang, Guoming

2014-11-10

The switching parameter variation of resistive switching memory is one of the most important challenges in its application. In this letter, we have studied the set statistics of conductive bridge random access memory with a Cu/HfO{sub 2}/Pt structure. The experimental distributions of the set parameters in several off resistance ranges are shown to nicely fit a Weibull model. The Weibull slopes of the set voltage and current increase and decrease logarithmically with off resistance, respectively. This experimental behavior is perfectly captured by a Monte Carlo simulator based on the cell-based set voltage statistics model and the Quantum Point Contact electronmore » transport model. Our work provides indications for the improvement of the switching uniformity.« less

Development of a tuned interfacial force field parameter set for the simulation of protein adsorption to silica glass.

PubMed

Snyder, James A; Abramyan, Tigran; Yancey, Jeremy A; Thyparambil, Aby A; Wei, Yang; Stuart, Steven J; Latour, Robert A

2012-12-01

Adsorption free energies for eight host-guest peptides (TGTG-X-GTGT, with X = N, D, G, K, F, T, W, and V) on two different silica surfaces [quartz (100) and silica glass] were calculated using umbrella sampling and replica exchange molecular dynamics and compared with experimental values determined by atomic force microscopy. Using the CHARMM force field, adsorption free energies were found to be overestimated (i.e., too strongly adsorbing) by about 5-9 kcal/mol compared to the experimental data for both types of silica surfaces. Peptide adsorption behavior for the silica glass surface was then adjusted using a modified version of the CHARMM program, which we call dual force-field CHARMM, which allows separate sets of nonbonded parameters (i.e., partial charge and Lennard-Jones parameters) to be used to represent intra-phase and inter-phase interactions within a given molecular system. Using this program, interfacial force field (IFF) parameters for the peptide-silica glass systems were corrected to obtain adsorption free energies within about 0.5 kcal/mol of their respective experimental values, while IFF tuning for the quartz (100) surface remains for future work. The tuned IFF parameter set for silica glass will subsequently be used for simulations of protein adsorption behavior on silica glass with greater confidence in the balance between relative adsorption affinities of amino acid residues and the aqueous solution for the silica glass surface.

Development of a Tuned Interfacial Force Field Parameter Set for the Simulation of Protein Adsorption to Silica Glass

PubMed Central

Snyder, James A.; Abramyan, Tigran; Yancey, Jeremy A.; Thyparambil, Aby A.; Wei, Yang; Stuart, Steven J.; Latour, Robert A.

2012-01-01

Adsorption free energies for eight host–guest peptides (TGTG-X-GTGT, with X = N, D, G, K, F, T, W, and V) on two different silica surfaces [quartz (100) and silica glass] were calculated using umbrella sampling and replica exchange molecular dynamics and compared with experimental values determined by atomic force microscopy. Using the CHARMM force field, adsorption free energies were found to be overestimated (i.e., too strongly adsorbing) by about 5–9 kcal/mol compared to the experimental data for both types of silica surfaces. Peptide adsorption behavior for the silica glass surface was then adjusted using a modified version of the CHARMM program, which we call dual force-field CHARMM, which allows separate sets of nonbonded parameters (i.e., partial charge and Lennard-Jones parameters) to be used to represent intra-phase and inter-phase interactions within a given molecular system. Using this program, interfacial force field (IFF) parameters for the peptide-silica glass systems were corrected to obtain adsorption free energies within about 0.5 kcal/mol of their respective experimental values, while IFF tuning for the quartz (100) surface remains for future work. The tuned IFF parameter set for silica glass will subsequently be used for simulations of protein adsorption behavior on silica glass with greater confidence in the balance between relative adsorption affinities of amino acid residues and the aqueous solution for the silica glass surface. PMID:22941539

Selection of physiological parameters for optoelectronic system supporting behavioral therapy of autistic children

NASA Astrophysics Data System (ADS)

Landowska, A.; Karpienko, K.; Wróbel, M.; Jedrzejewska-Szczerska, M.

2014-11-01

In this article the procedure of selection of physiological parameters for optoelectronic system supporting behavioral therapy of autistic children is proposed. Authors designed and conducted an experiment in which a group of 30 health volunteers (16 females and 14 males) were examined. Under controlled conditions people were exposed to a stressful situation caused by the picture or sound (1kHz constant sound, which was gradually silenced and finished with a shot sound). For each of volunteers, a set of physiological parameters were recorded, including: skin conductance, heart rate, peripheral temperature, respiration rate and electromyography. The selected characteristics were measured in different locations in order to choose the most suitable one for the designed therapy supporting system. The bio-statistical analysis allowed us to discern the proper physiological parameters that are most associated to changes due to emotional state of a patient, such as: skin conductance, temperatures and respiration rate. This allowed us to design optoelectronic sensors network for supporting behavioral therapy of children with autism.

Assimilation of Biophysical Neuronal Dynamics in Neuromorphic VLSI.

PubMed

Wang, Jun; Breen, Daniel; Akinin, Abraham; Broccard, Frederic; Abarbanel, Henry D I; Cauwenberghs, Gert

2017-12-01

Representing the biophysics of neuronal dynamics and behavior offers a principled analysis-by-synthesis approach toward understanding mechanisms of nervous system functions. We report on a set of procedures assimilating and emulating neurobiological data on a neuromorphic very large scale integrated (VLSI) circuit. The analog VLSI chip, NeuroDyn, features 384 digitally programmable parameters specifying for 4 generalized Hodgkin-Huxley neurons coupled through 12 conductance-based chemical synapses. The parameters also describe reversal potentials, maximal conductances, and spline regressed kinetic functions for ion channel gating variables. In one set of experiments, we assimilated membrane potential recorded from one of the neurons on the chip to the model structure upon which NeuroDyn was designed using the known current input sequence. We arrived at the programmed parameters except for model errors due to analog imperfections in the chip fabrication. In a related set of experiments, we replicated songbird individual neuron dynamics on NeuroDyn by estimating and configuring parameters extracted using data assimilation from intracellular neural recordings. Faithful emulation of detailed biophysical neural dynamics will enable the use of NeuroDyn as a tool to probe electrical and molecular properties of functional neural circuits. Neuroscience applications include studying the relationship between molecular properties of neurons and the emergence of different spike patterns or different brain behaviors. Clinical applications include studying and predicting effects of neuromodulators or neurodegenerative diseases on ion channel kinetics.

Modeling behavior dynamics using computational psychometrics within virtual worlds.

PubMed

Cipresso, Pietro

2015-01-01

In case of fire in a building, how will people behave in the crowd? The behavior of each individual affects the behavior of others and, conversely, each one behaves considering the crowd as a whole and the individual others. In this article, I propose a three-step method to explore a brand new way to study behavior dynamics. The first step relies on the creation of specific situations with standard techniques (such as mental imagery, text, video, and audio) and an advanced technique [Virtual Reality (VR)] to manipulate experimental settings. The second step concerns the measurement of behavior in one, two, or many individuals focusing on parameters extractions to provide information about the behavior dynamics. Finally, the third step, which uses the parameters collected and measured in the previous two steps in order to simulate possible scenarios to forecast through computational models, understand, and explain behavior dynamics at the social level. An experimental study was also included to demonstrate the three-step method and a possible scenario.

Health Behaviors, Nutritional Status, and Anthropometric Parameters of Roma and Non-Roma Mothers and Their Infants in the Czech Republic

ERIC Educational Resources Information Center

Rambouskova, Jolana; Dlouhy, Pavel; Krizova, Eva; Prochazka, Bohumir; Hrncirova, Dana; Andel, M

2009-01-01

Objective: To compare maternal health behaviors, maternal nutritional status, and infant size at birth of Romas and non-Romas in the Czech Republic. Design: Maternal interviews and food frequency questionnaire, maternal blood samples, physical measurements of mothers and infants. Setting: Hospital, maternal/child care center; 2-4 days postpartum.…

Flight Regime Recognition Analysis for the Army UH-60A IMDS Usage

DTIC Science & Technology

2006-12-01

61 Figure 34. The Behavior of The Parameter Weight.On.Wheels........................... 65 Figure 35. The ... Behavior of a Take-off Regime in Subsetting Process ................ 68 xi Figure 36. Subsetting the Big Data into Smaller Sets (WOW, Flags...of components can be extended to their true lifetime (Bechhoefer, n.d.) This is directly related to the accurate representation of regime

Modeling Answer Change Behavior: An Application of a Generalized Item Response Tree Model

ERIC Educational Resources Information Center

Jeon, Minjeong; De Boeck, Paul; van der Linden, Wim

2017-01-01

We present a novel application of a generalized item response tree model to investigate test takers' answer change behavior. The model allows us to simultaneously model the observed patterns of the initial and final responses after an answer change as a function of a set of latent traits and item parameters. The proposed application is illustrated…

Influence of parameter values on the oscillation sensitivities of two p53-Mdm2 models.

PubMed

Cuba, Christian E; Valle, Alexander R; Ayala-Charca, Giancarlo; Villota, Elizabeth R; Coronado, Alberto M

2015-09-01

Biomolecular networks that present oscillatory behavior are ubiquitous in nature. While some design principles for robust oscillations have been identified, it is not well understood how these oscillations are affected when the kinetic parameters are constantly changing or are not precisely known, as often occurs in cellular environments. Many models of diverse complexity level, for systems such as circadian rhythms, cell cycle or the p53 network, have been proposed. Here we assess the influence of hundreds of different parameter sets on the sensitivities of two configurations of a well-known oscillatory system, the p53 core network. We show that, for both models and all parameter sets, the parameter related to the p53 positive feedback, i.e. self-promotion, is the only one that presents sizeable sensitivities on extrema, periods and delay. Moreover, varying the parameter set values to change the dynamical characteristics of the response is more restricted in the simple model, whereas the complex model shows greater tunability. These results highlight the importance of the presence of specific network patterns, in addition to the role of parameter values, when we want to characterize oscillatory biochemical systems.

Universal dynamical properties preclude standard clustering in a large class of biochemical data.

PubMed

Gomez, Florian; Stoop, Ralph L; Stoop, Ruedi

2014-09-01

Clustering of chemical and biochemical data based on observed features is a central cognitive step in the analysis of chemical substances, in particular in combinatorial chemistry, or of complex biochemical reaction networks. Often, for reasons unknown to the researcher, this step produces disappointing results. Once the sources of the problem are known, improved clustering methods might revitalize the statistical approach of compound and reaction search and analysis. Here, we present a generic mechanism that may be at the origin of many clustering difficulties. The variety of dynamical behaviors that can be exhibited by complex biochemical reactions on variation of the system parameters are fundamental system fingerprints. In parameter space, shrimp-like or swallow-tail structures separate parameter sets that lead to stable periodic dynamical behavior from those leading to irregular behavior. We work out the genericity of this phenomenon and demonstrate novel examples for their occurrence in realistic models of biophysics. Although we elucidate the phenomenon by considering the emergence of periodicity in dependence on system parameters in a low-dimensional parameter space, the conclusions from our simple setting are shown to continue to be valid for features in a higher-dimensional feature space, as long as the feature-generating mechanism is not too extreme and the dimension of this space is not too high compared with the amount of available data. For online versions of super-paramagnetic clustering see http://stoop.ini.uzh.ch/research/clustering. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

An Open-Source Auto-Calibration Routine Supporting the Stormwater Management Model

NASA Astrophysics Data System (ADS)

Tiernan, E. D.; Hodges, B. R.

2017-12-01

The stormwater management model (SWMM) is a clustered model that relies on subcatchment-averaged parameter assignments to correctly capture catchment stormwater runoff behavior. Model calibration is considered a critical step for SWMM performance, an arduous task that most stormwater management designers undertake manually. This research presents an open-source, automated calibration routine that increases the efficiency and accuracy of the model calibration process. The routine makes use of a preliminary sensitivity analysis to reduce the dimensions of the parameter space, at which point a multi-objective function, genetic algorithm (modified Non-dominated Sorting Genetic Algorithm II) determines the Pareto front for the objective functions within the parameter space. The solutions on this Pareto front represent the optimized parameter value sets for the catchment behavior that could not have been reasonably obtained through manual calibration.

The structure and dynamics of tornado-like vortices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nolan, D.S.; Farrell, B.F.

The structure and dynamics of axisymmetric tornado-like vortices are explored with a numerical model of axisymmetric incompressible flow based on recently developed numerical methods. The model is first shown to compare favorably with previous results and is then used to study the effects of varying the major parameters controlling the vortex: the strength of the convective forcing, the strength of the rotational forcing, and the magnitude of the model eddy viscosity. Dimensional analysis of the model problem indicates that the results must depend on only two dimensionless parameters. The natural choices for these two parameters are a convective Reynolds numbermore » (based on the velocity scale associated with the convective forcing) and a parameter analogous to the swirl ratio in laboratory models. However, by examining sets of simulations with different model parameters it is found that a dimensionless parameter known as the vortex Reynolds number, which is the ratio of the far-field circulation to the eddy viscosity, is more effective than the convention swirl ratio for predicting the structure of the vortex. The parameter space defined by the choices for model parameters is further explored with large sets of numerical simulations. For much of this parameter space it is confirmed that the vortex structure and time-dependent behavior depend strongly on the vortex Reynolds number and only weakly on the convective Reynolds number. The authors also find that for higher convective Reynolds numbers, the maximum possible wind speed increases, and the rotational forcing necessary to achieve that wind speed decreases. Physical reasoning is used to explain this behavior, and implications for tornado dynamics are discussed.« less

Application of physical parameter identification to finite-element models

NASA Technical Reports Server (NTRS)

Bronowicki, Allen J.; Lukich, Michael S.; Kuritz, Steven P.

1987-01-01

The time domain parameter identification method described previously is applied to TRW's Large Space Structure Truss Experiment. Only control sensors and actuators are employed in the test procedure. The fit of the linear structural model to the test data is improved by more than an order of magnitude using a physically reasonable parameter set. The electro-magnetic control actuators are found to contribute significant damping due to a combination of eddy current and back electro-motive force (EMF) effects. Uncertainties in both estimated physical parameters and modal behavior variables are given.

A model for hormonal control of the menstrual cycle: structural consistency but sensitivity with regard to data.

PubMed

Selgrade, J F; Harris, L A; Pasteur, R D

2009-10-21

This study presents a 13-dimensional system of delayed differential equations which predicts serum concentrations of five hormones important for regulation of the menstrual cycle. Parameters for the system are fit to two different data sets for normally cycling women. For these best fit parameter sets, model simulations agree well with the two different data sets but one model also has an abnormal stable periodic solution, which may represent polycystic ovarian syndrome. This abnormal cycle occurs for the model in which the normal cycle has estradiol levels at the high end of the normal range. Differences in model behavior are explained by studying hysteresis curves in bifurcation diagrams with respect to sensitive model parameters. For instance, one sensitive parameter is indicative of the estradiol concentration that promotes pituitary synthesis of a large amount of luteinizing hormone, which is required for ovulation. Also, it is observed that models with greater early follicular growth rates may have a greater risk of cycling abnormally.

Behavioral Competence as a Positive Youth Development Construct: A Conceptual Review

PubMed Central

Ma, Hing Keung

2012-01-01

Behavioral competence is delineated in terms of four parameters: (a) Moral and Social Knowledge, (b) Social Skills, (c) Positive Characters and Positive Attributes, and (d) Behavioral Decision Process and Action Taking. Since Ma's other papers in this special issue have already discussed the moral and social knowledge as well as the social skills associated in detail, this paper focuses on the last two parameters. It is hypothesized that the following twelve positive characters are highly related to behavioral competence: humanity, intelligence, courage, conscience, autonomy, respect, responsibility, naturalness, loyalty, humility, assertiveness, and perseverance. Large-scale empirical future studies should be conducted to substantiate the predictive validity of the complete set of these positive characters. The whole judgment and behavioral decision process is constructed based on the information processing approach. The direction of future studies should focus more on the complex input, central control, and output subprocesses and the interactions among these sub-processes. The understanding of the formation of behavior is crucial to whole-person education and positive youth development. PMID:22645434

The fractal geometry of Hartree-Fock

NASA Astrophysics Data System (ADS)

Theel, Friethjof; Karamatskou, Antonia; Santra, Robin

2017-12-01

The Hartree-Fock method is an important approximation for the ground-state electronic wave function of atoms and molecules so that its usage is widespread in computational chemistry and physics. The Hartree-Fock method is an iterative procedure in which the electronic wave functions of the occupied orbitals are determined. The set of functions found in one step builds the basis for the next iteration step. In this work, we interpret the Hartree-Fock method as a dynamical system since dynamical systems are iterations where iteration steps represent the time development of the system, as encountered in the theory of fractals. The focus is put on the convergence behavior of the dynamical system as a function of a suitable control parameter. In our case, a complex parameter λ controls the strength of the electron-electron interaction. An investigation of the convergence behavior depending on the parameter λ is performed for helium, neon, and argon. We observe fractal structures in the complex λ-plane, which resemble the well-known Mandelbrot set, determine their fractal dimension, and find that with increasing nuclear charge, the fragmentation increases as well.

Parametric Sensitivity Analysis of Precipitation at Global and Local Scales in the Community Atmosphere Model CAM5

DOE PAGES

Qian, Yun; Yan, Huiping; Hou, Zhangshuan; ...

2015-04-10

We investigate the sensitivity of precipitation characteristics (mean, extreme and diurnal cycle) to a set of uncertain parameters that influence the qualitative and quantitative behavior of the cloud and aerosol processes in the Community Atmosphere Model (CAM5). We adopt both the Latin hypercube and quasi-Monte Carlo sampling approaches to effectively explore the high-dimensional parameter space and then conduct two large sets of simulations. One set consists of 1100 simulations (cloud ensemble) perturbing 22 parameters related to cloud physics and convection, and the other set consists of 256 simulations (aerosol ensemble) focusing on 16 parameters related to aerosols and cloud microphysics.more » Results show that for the 22 parameters perturbed in the cloud ensemble, the six having the greatest influences on the global mean precipitation are identified, three of which (related to the deep convection scheme) are the primary contributors to the total variance of the phase and amplitude of the precipitation diurnal cycle over land. The extreme precipitation characteristics are sensitive to a fewer number of parameters. The precipitation does not always respond monotonically to parameter change. The influence of individual parameters does not depend on the sampling approaches or concomitant parameters selected. Generally the GLM is able to explain more of the parametric sensitivity of global precipitation than local or regional features. The total explained variance for precipitation is primarily due to contributions from the individual parameters (75-90% in total). The total variance shows a significant seasonal variability in the mid-latitude continental regions, but very small in tropical continental regions.« less

Heavy Tail Behavior of Rainfall Extremes across Germany

NASA Astrophysics Data System (ADS)

Castellarin, A.; Kreibich, H.; Vorogushyn, S.; Merz, B.

2017-12-01

Distributions are termed heavy-tailed if extreme values are more likely than would be predicted by probability distributions that have exponential asymptotic behavior. Heavy-tail behavior often leads to surprise, because historical observations can be a poor guide for the future. Heavy-tail behavior seems to be widespread for hydro-meteorological extremes, such as extreme rainfall and flood events. To date there have been only vague hints to explain under which conditions these extremes show heavy-tail behavior. We use an observational data set consisting of 11 climate variables at 1440 stations across Germany. This homogenized, gap-free data set covers 110 years (1901-2010) at daily resolution. We estimate the upper tail behavior, including its uncertainty interval, of daily precipitation extremes for the 1,440 stations at the annual and seasonal time scales. Different tail indicators are tested, including the shape parameter of the Generalized Extreme Value distribution, the upper tail ratio and the obesity index. In a further step, we explore to which extent the tail behavior can be explained by geographical and climate factors. A large number of characteristics is derived, such as station elevation, degree of continentality, aridity, measures for quantifying the variability of humidity and wind velocity, or event-triggering large-scale atmospheric situation. The link between the upper tail behavior and these characteristics is investigated via data mining methods capable of detecting non-linear relationships in large data sets. This exceptionally rich observational data set, in terms of number of stations, length of time series and number of explaining variables, allows insights into the upper tail behavior which is rarely possible given the typical observational data sets available.

Modeling the viscoplastic behavior of Inconel 718 at 1200 F

NASA Technical Reports Server (NTRS)

Abdel-Kader, M. S.; Eftis, J.; Jones, D. L.

1988-01-01

A large number of tests, including tensile, creep, fatigue, and creep-fatigue were performed to characterize the mechanical properties of Inconel 718 (a nickel based superalloy) at 1200 F, the operating temperature for turbine blades. In addition, a few attempts were made to model the behavior of Inconel 718 at 1200 F using viscoplastic theories. The Chaboche theory of viscoplasticity can model a wide variety of mechanical behavior, including monotonic, sustained, and cyclic responses of homogeneous, initially-isotropic, strain hardening (or softening) materials. It is shown how the Chaboche theory can be used to model the viscoplastic behavior of Inconel 718 at 1200 F. First, an algorithm was developed to systematically determine the material parameters of the Chaboche theory from uniaxial tensile, creep, and cyclic data. The algorithm is general and can be used in conjunction with similar high temperature materials. A sensitivity study was then performed and an optimal set of Chaboche's parameters were obtained. This study has also indicated the role of each parameter in modeling the response to different loading conditions.

Definition and application of a five-parameter characterization of one-dimensional cellular automata rule space.

PubMed

Oliveira, G M; de Oliveira, P P; Omar, N

2001-01-01

Cellular automata (CA) are important as prototypical, spatially extended, discrete dynamical systems. Because the problem of forecasting dynamic behavior of CA is undecidable, various parameter-based approximations have been developed to address the problem. Out of the analysis of the most important parameters available to this end we proposed some guidelines that should be followed when defining a parameter of that kind. Based upon the guidelines, new parameters were proposed and a set of five parameters was selected; two of them were drawn from the literature and three are new ones, defined here. This article presents all of them and makes their qualities evident. Then, two results are described, related to the use of the parameter set in the Elementary Rule Space: a phase transition diagram, and some general heuristics for forecasting the dynamics of one-dimensional CA. Finally, as an example of the application of the selected parameters in high cardinality spaces, results are presented from experiments involving the evolution of radius-3 CA in the Density Classification Task, and radius-2 CA in the Synchronization Task.

Application of a quantum ensemble model to linguistic analysis

NASA Astrophysics Data System (ADS)

Rovenchak, Andrij; Buk, Solomija

2011-04-01

A new set of parameters to describe the behavior of word frequencies in texts is proposed. An analogy between the word frequency distribution and the Bose distribution is suggested, and the notion of “temperature” is introduced for this case. The calculations are made for English, Ukrainian, and the Guinean Maninka languages. A correlation between the language structure (the level of analyticity) and the defined parameters is shown to exist.

Bifurcations of the Self-Exciting Oscillations of a Wheeled Assembly About Straight-Line Motion

NASA Astrophysics Data System (ADS)

Vel'magina, N. A.

2013-11-01

The effect of characteristic parameters of a system describing a wheeled assembly on the oscillatory-instability domain is analyzed. The influence of the accuracy of approximation of the lateral force and the heeling moment on the behavior of self-exciting oscillations is examined. A bifurcation set that divides the plane of parameters into domains with different number of limit cycles is constructed

New Uses for Sensitivity Analysis: How Different Movement Tasks Effect Limb Model Parameter Sensitivity

NASA Technical Reports Server (NTRS)

Winters, J. M.; Stark, L.

1984-01-01

Original results for a newly developed eight-order nonlinear limb antagonistic muscle model of elbow flexion and extension are presented. A wider variety of sensitivity analysis techniques are used and a systematic protocol is established that shows how the different methods can be used efficiently to complement one another for maximum insight into model sensitivity. It is explicitly shown how the sensitivity of output behaviors to model parameters is a function of the controller input sequence, i.e., of the movement task. When the task is changed (for instance, from an input sequence that results in the usual fast movement task to a slower movement that may also involve external loading, etc.) the set of parameters with high sensitivity will in general also change. Such task-specific use of sensitivity analysis techniques identifies the set of parameters most important for a given task, and even suggests task-specific model reduction possibilities.

Modeling the Impact of Motivation, Personality, and Emotion on Social Behavior

NASA Astrophysics Data System (ADS)

Miller, Lynn C.; Read, Stephen J.; Zachary, Wayne; Rosoff, Andrew

Models seeking to predict human social behavior must contend with multiple sources of individual and group variability that underlie social behavior. One set of interrelated factors that strongly contribute to that variability - motivations, personality, and emotions - has been only minimally incorporated in previous computational models of social behavior. The Personality, Affect, Culture (PAC) framework is a theory-based computational model that addresses this gap. PAC is used to simulate social agents whose social behavior varies according to their personalities and emotions, which, in turn, vary according to their motivations and underlying motive control parameters. Examples involving disease spread and counter-insurgency operations show how PAC can be used to study behavioral variability in different social contexts.

Dynamics of cellular level function and regulation derived from murine expression array data.

PubMed

de Bivort, Benjamin; Huang, Sui; Bar-Yam, Yaneer

2004-12-21

A major open question of systems biology is how genetic and molecular components interact to create phenotypes at the cellular level. Although much recent effort has been dedicated to inferring effective regulatory influences within small networks of genes, the power of microarray bioinformatics has yet to be used to determine functional influences at the cellular level. In all cases of data-driven parameter estimation, the number of model parameters estimable from a set of data is strictly limited by the size of that set. Rather than infer parameters describing the detailed interactions of just a few genes, we chose a larger-scale investigation so that the cumulative effects of all gene interactions could be analyzed to identify the dynamics of cellular-level function. By aggregating genes into large groups with related behaviors (megamodules), we were able to determine the effective aggregate regulatory influences among 12 major gene groups in murine B lymphocytes over a variety of time steps. Intriguing observations about the behavior of cells at this high level of abstraction include: (i) a medium-term critical global transcriptional dependence on ATP-generating genes in the mitochondria, (ii) a longer-term dependence on glycolytic genes, (iii) the dual role of chromatin-reorganizing genes in transcriptional activation and repression, (iv) homeostasis-favoring influences, (v) the indication that, as a group, G protein-mediated signals are not concentration-dependent in their influence on target gene expression, and (vi) short-term-activating/long-term-repressing behavior of the cell-cycle system that reflects its oscillatory behavior.

Thermal - Hydraulic Behavior of Unsaturated Bentonite and Sand-Bentonite Material as Seal for Nuclear Waste Repository: Numerical Simulation of Column Experiments

NASA Astrophysics Data System (ADS)

Ballarini, E.; Graupner, B.; Bauer, S.

2015-12-01

For deep geological repositories of high-level radioactive waste (HLRW), bentonite and sand bentonite mixtures are investigated as buffer materials to form a a sealing layer. This sealing layer surrounds the canisters and experiences an initial drying due to the heat produced by HLRW and a successive re-saturation with fluid from the host rock. These complex thermal, hydraulic and mechanical processes interact and were investigated in laboratory column experiments using MX-80 clay pellets as well as a mixture of 35% sand and 65% bentonite. The aim of this study is to both understand the individual processes taking place in the buffer materials and to identify the key physical parameters that determine the material behavior under heating and hydrating conditions. For this end, detailed and process-oriented numerical modelling was applied to the experiments, simulating heat transport, multiphase flow and mechanical effects from swelling. For both columns, the same set of parameters was assigned to the experimental set-up (i.e. insulation, heater and hydration system), while the parameters of the buffer material were adapted during model calibration. A good fit between model results and data was achieved for temperature, relative humidity, water intake and swelling pressure, thus explaining the material behavior. The key variables identified by the model are the permeability and relative permeability, the water retention curve and the thermal conductivity of the buffer material. The different hydraulic and thermal behavior of the two buffer materials observed in the laboratory observations was well reproduced by the numerical model.

Optimizing Decision Support for Tailored Health Behavior Change Applications.

PubMed

Kukafka, Rita; Jeong, In cheol; Finkelstein, Joseph

2015-01-01

The Tailored Lifestyle Change Decision Aid (TLC DA) system was designed to provide support for a person to make an informed choice about which behavior change to work on when multiple unhealthy behaviors are present. TLC DA can be delivered via web, smartphones and tablets. The system collects a significant amount of information that is used to generate tailored messages to consumers to persuade them in certain healthy lifestyles. One limitation is the necessity to collect vast amounts of information from users who manually enter. By identifying an optimal set of self-reported parameters we will be able to minimize the data entry burden of the app users. The study was to identify primary determinants of health behavior choices made by patients after using the system. Using discriminant analysis an optimal set of predictors was identified. The resulting set included smoking status, smoking cessation success estimate, self-efficacy, body mass index and diet status. Predicting smoking cessation choice was the most accurate, followed by weight management. Physical activity and diet choices were better identified in a combined cluster.

Assessment and Reduction of Model Parametric Uncertainties: A Case Study with A Distributed Hydrological Model

NASA Astrophysics Data System (ADS)

Gan, Y.; Liang, X. Z.; Duan, Q.; Xu, J.; Zhao, P.; Hong, Y.

2017-12-01

The uncertainties associated with the parameters of a hydrological model need to be quantified and reduced for it to be useful for operational hydrological forecasting and decision support. An uncertainty quantification framework is presented to facilitate practical assessment and reduction of model parametric uncertainties. A case study, using the distributed hydrological model CREST for daily streamflow simulation during the period 2008-2010 over ten watershed, was used to demonstrate the performance of this new framework. Model behaviors across watersheds were analyzed by a two-stage stepwise sensitivity analysis procedure, using LH-OAT method for screening out insensitive parameters, followed by MARS-based Sobol' sensitivity indices for quantifying each parameter's contribution to the response variance due to its first-order and higher-order effects. Pareto optimal sets of the influential parameters were then found by the adaptive surrogate-based multi-objective optimization procedure, using MARS model for approximating the parameter-response relationship and SCE-UA algorithm for searching the optimal parameter sets of the adaptively updated surrogate model. The final optimal parameter sets were validated against the daily streamflow simulation of the same watersheds during the period 2011-2012. The stepwise sensitivity analysis procedure efficiently reduced the number of parameters that need to be calibrated from twelve to seven, which helps to limit the dimensionality of calibration problem and serves to enhance the efficiency of parameter calibration. The adaptive MARS-based multi-objective calibration exercise provided satisfactory solutions to the reproduction of the observed streamflow for all watersheds. The final optimal solutions showed significant improvement when compared to the default solutions, with about 65-90% reduction in 1-NSE and 60-95% reduction in |RB|. The validation exercise indicated a large improvement in model performance with about 40-85% reduction in 1-NSE, and 35-90% reduction in |RB|. Overall, this uncertainty quantification framework is robust, effective and efficient for parametric uncertainty analysis, the results of which provide useful information that helps to understand the model behaviors and improve the model simulations.

Aggregate-level analysis and prediction of midterm senatorial elections in the United States, 1974-1986.

PubMed

Lichtman, A J; Keilis-Borok, V I

1989-12-01

Pattern recognition study demonstrates that the outcomes of American midterm senatorial elections follow the dynamics of simple integral parameters that depict preelectoral situations aggregated to the state as a whole. A set of "commonsense" parameters is identified that is sufficient to predict such elections state-by-state and year-by-year. The analysis rejects many similar commonsense parameters. The existence and nature of integral collective behavior in U.S. elections at the level of the individual states is investigated. Implications for understanding the American electoral process are discussed.

On the identification of cohesive parameters for printed metal-polymer interfaces

NASA Astrophysics Data System (ADS)

Heinrich, Felix; Langner, Hauke H.; Lammering, Rolf

2017-05-01

The mechanical behavior of printed electronics on fiber reinforced composites is investigated. A methodology based on cohesive zone models is employed, considering interfacial strengths, stiffnesses and critical strain energy release rates. A double cantilever beam test and an end notched flexure test are carried out to experimentally determine critical strain energy release rates under fracture modes I and II. Numerical simulations are performed in Abaqus 6.13 to model both tests. Applying the simulations, an inverse parameter identification is run to determine the full set of cohesive parameters.

New approaches in agent-based modeling of complex financial systems

NASA Astrophysics Data System (ADS)

Chen, Ting-Ting; Zheng, Bo; Li, Yan; Jiang, Xiong-Fei

2017-12-01

Agent-based modeling is a powerful simulation technique to understand the collective behavior and microscopic interaction in complex financial systems. Recently, the concept for determining the key parameters of agent-based models from empirical data instead of setting them artificially was suggested. We first review several agent-based models and the new approaches to determine the key model parameters from historical market data. Based on the agents' behaviors with heterogeneous personal preferences and interactions, these models are successful in explaining the microscopic origination of the temporal and spatial correlations of financial markets. We then present a novel paradigm combining big-data analysis with agent-based modeling. Specifically, from internet query and stock market data, we extract the information driving forces and develop an agent-based model to simulate the dynamic behaviors of complex financial systems.

Spatial and temporal study of nitrate concentration in groundwater by means of coregionalization

USGS Publications Warehouse

D'Agostino, V.; Greene, E.A.; Passarella, G.; Vurro, M.

1998-01-01

Spatial and temporal behavior of hydrochemical parameters in groundwater can be studied using tools provided by geostatistics. The cross-variogram can be used to measure the spatial increments between observations at two given times as a function of distance (spatial structure). Taking into account the existence of such a spatial structure, two different data sets (sampled at two different times), representing concentrations of the same hydrochemical parameter, can be analyzed by cokriging in order to reduce the uncertainty of the estimation. In particular, if one of the two data sets is a subset of the other (that is, an undersampled set), cokriging allows us to study the spatial distribution of the hydrochemical parameter at that time, while also considering the statistical characteristics of the full data set established at a different time. This paper presents an application of cokriging by using temporal subsets to study the spatial distribution of nitrate concentration in the aquifer of the Lucca Plain, central Italy. Three data sets of nitrate concentration in groundwater were collected during three different periods in 1991. The first set was from 47 wells, but the second and the third are undersampled and represent 28 and 27 wells, respectively. Comparing the result of cokriging with ordinary kriging showed an improvement of the uncertainty in terms of reducing the estimation variance. The application of cokriging to the undersampled data sets reduced the uncertainty in estimating nitrate concentration and at the same time decreased the cost of the field sampling and laboratory analysis.Spatial and temporal behavior of hydrochemical parameters in groundwater can be studied using tools provided by geostatistics. The cross-variogram can be used to measure the spatial increments between observations at two given times as a function of distance (spatial structure). Taking into account the existence of such a spatial structure, two different data sets (sampled at two different times), representing concentrations of the same hydrochemical parameter, can be analyzed by cokriging in order to reduce the uncertainty of the estimation. In particular, if one of the two data sets is a subset of the other (that is, an undersampled set), cokriging allows us to study the spatial distribution of the hydrochemical parameter at that time, while also considering the statistical characteristics of the full data set established at a different time. This paper presents an application of cokriging by using temporal subsets to study the spatial distribution of nitrate concentration in the aquifer of the Lucca Plain, central Italy. Three data sets of nitrate concentration in groundwater were collected during three different periods in 1991. The first set was from 47 wells, but the second and the third are undersampled and represent 28 and 27 wells, respectively. Comparing the result of cokriging with ordinary kriging showed an improvement of the uncertainty in terms of reducing the estimation variance. The application of cokriging to the undersampled data sets reduced the uncertainty in estimating nitrate concentration and at the same time decreased the cost of the field sampling and laboratory analysis.

Parameterization of Shape and Compactness in Object-based Image Classification Using Quickbird-2 Imagery

NASA Astrophysics Data System (ADS)

Tonbul, H.; Kavzoglu, T.

2016-12-01

In recent years, object based image analysis (OBIA) has spread out and become a widely accepted technique for the analysis of remotely sensed data. OBIA deals with grouping pixels into homogenous objects based on spectral, spatial and textural features of contiguous pixels in an image. The first stage of OBIA, named as image segmentation, is the most prominent part of object recognition. In this study, multiresolution segmentation, which is a region-based approach, was employed to construct image objects. In the application of multi-resolution, three parameters, namely shape, compactness and scale must be set by the analyst. Segmentation quality remarkably influences the fidelity of the thematic maps and accordingly the classification accuracy. Therefore, it is of great importance to search and set optimal values for the segmentation parameters. In the literature, main focus has been on the definition of scale parameter, assuming that the effect of shape and compactness parameters is limited in terms of achieved classification accuracy. The aim of this study is to deeply analyze the influence of shape/compactness parameters by varying their values while using the optimal scale parameter determined by the use of Estimation of Scale Parameter (ESP-2) approach. A pansharpened Qickbird-2 image covering Trabzon, Turkey was employed to investigate the objectives of the study. For this purpose, six different combinations of shape/compactness were utilized to make deductions on the behavior of shape and compactness parameters and optimal setting for all parameters as a whole. Objects were assigned to classes using nearest neighbor classifier in all segmentation observations and equal number of pixels was randomly selected to calculate accuracy metrics. The highest overall accuracy (92.3%) was achieved by setting the shape/compactness criteria to 0.3/0.3. The results of this study indicate that shape/compactness parameters can have significant effect on classification accuracy with 4% change in overall accuracy. Also, statistical significance of differences in accuracy was tested using the McNemar's test and found that the difference between poor and optimal setting of shape/compactness parameters was statistically significant, suggesting a search for optimal parameterization instead of default setting.

An evaluation of behavior inferences from Bayesian state-space models: A case study with the Pacific walrus

USGS Publications Warehouse

Beatty, William; Jay, Chadwick V.; Fischbach, Anthony S.

2016-01-01

State-space models offer researchers an objective approach to modeling complex animal location data sets, and state-space model behavior classifications are often assumed to have a link to animal behavior. In this study, we evaluated the behavioral classification accuracy of a Bayesian state-space model in Pacific walruses using Argos satellite tags with sensors to detect animal behavior in real time. We fit a two-state discrete-time continuous-space Bayesian state-space model to data from 306 Pacific walruses tagged in the Chukchi Sea. We matched predicted locations and behaviors from the state-space model (resident, transient behavior) to true animal behavior (foraging, swimming, hauled out) and evaluated classification accuracy with kappa statistics (κ) and root mean square error (RMSE). In addition, we compared biased random bridge utilization distributions generated with resident behavior locations to true foraging behavior locations to evaluate differences in space use patterns. Results indicated that the two-state model fairly classified true animal behavior (0.06 ≤ κ ≤ 0.26, 0.49 ≤ RMSE ≤ 0.59). Kernel overlap metrics indicated utilization distributions generated with resident behavior locations were generally smaller than utilization distributions generated with true foraging behavior locations. Consequently, we encourage researchers to carefully examine parameters and priors associated with behaviors in state-space models, and reconcile these parameters with the study species and its expected behaviors.

Hierarchical representation and machine learning from faulty jet engine behavioral examples to detect real time abnormal conditions

NASA Technical Reports Server (NTRS)

Gupta, U. K.; Ali, M.

1988-01-01

The theoretical basis and operation of LEBEX, a machine-learning system for jet-engine performance monitoring, are described. The behavior of the engine is modeled in terms of four parameters (the rotational speeds of the high- and low-speed sections and the exhaust and combustion temperatures), and parameter variations indicating malfunction are transformed into structural representations involving instances and events. LEBEX extracts descriptors from a set of training data on normal and faulty engines, represents them hierarchically in a knowledge base, and uses them to diagnose and predict faults on a real-time basis. Diagrams of the system architecture and printouts of typical results are shown.

INDUCTIVE SYSTEM HEALTH MONITORING WITH STATISTICAL METRICS

NASA Technical Reports Server (NTRS)

Iverson, David L.

2005-01-01

Model-based reasoning is a powerful method for performing system monitoring and diagnosis. Building models for model-based reasoning is often a difficult and time consuming process. The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS processes nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. In particular, a clustering algorithm forms groups of nominal values for sets of related parameters. This establishes constraints on those parameter values that should hold during nominal operation. During monitoring, IMS provides a statistically weighted measure of the deviation of current system behavior from the established normal baseline. If the deviation increases beyond the expected level, an anomaly is suspected, prompting further investigation by an operator or automated system. IMS has shown potential to be an effective, low cost technique to produce system monitoring capability for a variety of applications. We describe the training and system health monitoring techniques of IMS. We also present the application of IMS to a data set from the Space Shuttle Columbia STS-107 flight. IMS was able to detect an anomaly in the launch telemetry shortly after a foam impact damaged Columbia's thermal protection system.

Hybrid phase transition into an absorbing state: Percolation and avalanches

NASA Astrophysics Data System (ADS)

Lee, Deokjae; Choi, S.; Stippinger, M.; Kertész, J.; Kahng, B.

2016-04-01

Interdependent networks are more fragile under random attacks than simplex networks, because interlayer dependencies lead to cascading failures and finally to a sudden collapse. This is a hybrid phase transition (HPT), meaning that at the transition point the order parameter has a jump but there are also critical phenomena related to it. Here we study these phenomena on the Erdős-Rényi and the two-dimensional interdependent networks and show that the hybrid percolation transition exhibits two kinds of critical behaviors: divergence of the fluctuations of the order parameter and power-law size distribution of finite avalanches at a transition point. At the transition point global or "infinite" avalanches occur, while the finite ones have a power law size distribution; thus the avalanche statistics also has the nature of a HPT. The exponent βm of the order parameter is 1 /2 under general conditions, while the value of the exponent γm characterizing the fluctuations of the order parameter depends on the system. The critical behavior of the finite avalanches can be described by another set of exponents, βa and γa. These two critical behaviors are coupled by a scaling law: 1 -βm=γa .

Azadirachtin, a neem-derived biopesticide, impairs behavioral and hematological parameters in carp (Cyprinus carpio).

PubMed

Murussi, Camila R; Menezes, Charlene C; Nunes, Mauro E M; Araújo, Maria do Carmo S; Quadros, Vanessa A; Rosemberg, Denis B; Loro, Vania L

2016-11-01

Azadirachtin (Aza) is a promisor biopesticide used in organic production and aquaculture. Although this compound is apparently safe, there is evidence that it may have deleterious effects on fish. Behavioral and hematological tests are grouped into a set of parameters that may predict potential toxicity of chemical compounds. Here, we investigate the effects of Aza, in the commercial formulation Neenmax ™ , on carp (Cyprinus carpio) by defining LC 50 (96 h), and testing behavioral and hematological parameters. In our study, LC 50 was estimated at 80 μL/L. We exposed carp to Aza at 20, 40, and 60 μL/L, values based on 25, 50, and 75% of LC 50 , respectively. At 60 μL/L, Aza promoted significant changes in several parameters, increasing the distance traveled and absolute turn angle. In addition, the same concentration decreased the time spent immobile and the number of immobile episodes. Hematological parameters, such as hematocrit, hemoglobin, hematimetrics index, and red cell distribution, were decreased at 60 μL/L Aza exposure. In conclusion, our study demonstrates that 60 μL/L Aza altered locomotor activity, motor pattern, and hematological parameters, suggesting potential toxicity to carp after acute exposure. In addition, this is the first report that evaluates the actions of a chemical contaminant using automated behavioral tracking of carp, which may be a useful tool for assessing the potential toxicity of biopesticides in conjunction with hematological tests. © 2015 Wiley Periodicals, Inc. Environ Toxicol 31: 1381-1388, 2016. © 2015 Wiley Periodicals, Inc.

Changes in optical properties of electroporated cells as revealed by digital holographic microscopy

PubMed Central

Calin, Violeta L.; Mihailescu, Mona; Mihale, Nicolae; Baluta, Alexandra V.; Kovacs, Eugenia; Savopol, Tudor; Moisescu, Mihaela G.

2017-01-01

Changes in optical and shape-related characteristics of B16F10 cells after electroporation were investigated using digital holographic microscopy (DHM). Bipolar rectangular pulses specific for electrochemotherapy were used. Electroporation was performed in an “off-axis” DHM set-up without using exogenous markers. Two types of cell parameters were monitored seconds and minutes after pulse train application: parameters addressing a specifically defined area of the cell (refractive index and cell height) and global cell parameters (projected area, optical phase shift profile and dry mass). The biphasic behavior of cellular parameters was explained by water and mannitol dynamics through the electropermeabilized cell membrane. PMID:28736667

Computer Simulations of Polytetrafluoroethylene in the Solid State

NASA Astrophysics Data System (ADS)

Holt, D. B.; Farmer, B. L.; Eby, R. K.; Macturk, K. S.

1996-03-01

Force field parameters (Set I) for fluoropolymers were previously derived from MOPAC AM1 semiempirical data on model molecules. A second set (Set II) was derived from the AM1 results augmented by ab initio calculations. Both sets yield reasonable helical and phase II packing structures for polytetrafluoroethylene (PTFE) chains. However, Set I and Set II differ in the strength of van der Waals interactions, with Set II having deeper potential wells (order of magnitude). To differentiate which parameter set provides a better description of PTFE behavior, molecular dynamics simulations have been performed with Biosym Discover on clusters of PTFE chains which begin in a phase II packing environment. Added to the model are artificial constraints which allow the simulation of thermal expansion without having to define periodic boundary conditions for each specific temperature of interest. The preliminary dynamics simulations indicate that the intra- and intermolecular interactions provided by Set I are too weak. The degree of helical disorder and chain motion are high even at temperatures well below the phase II-phase IV transition temperature (19 C). Set II appears to yield a better description of PTFE in the solid state.

Stability analysis in tachyonic potential chameleon cosmology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farajollahi, H.; Salehi, A.; Tayebi, F.

2011-05-01

We study general properties of attractors for tachyonic potential chameleon scalar-field model which possess cosmological scaling solutions. An analytic formulation is given to obtain fixed points with a discussion on their stability. The model predicts a dynamical equation of state parameter with phantom crossing behavior for an accelerating universe. We constrain the parameters of the model by best fitting with the recent data-sets from supernovae and simulated data points for redshift drift experiment generated by Monte Carlo simulations.

Phase transition in the countdown problem

NASA Astrophysics Data System (ADS)

Lacasa, Lucas; Luque, Bartolo

2012-07-01

We present a combinatorial decision problem, inspired by the celebrated quiz show called Countdown, that involves the computation of a given target number T from a set of k randomly chosen integers along with a set of arithmetic operations. We find that the probability of winning the game evidences a threshold phenomenon that can be understood in the terms of an algorithmic phase transition as a function of the set size k. Numerical simulations show that such probability sharply transitions from zero to one at some critical value of the control parameter, hence separating the algorithm's parameter space in different phases. We also find that the system is maximally efficient close to the critical point. We derive analytical expressions that match the numerical results for finite size and permit us to extrapolate the behavior in the thermodynamic limit.

Self-Organized Dynamic Flocking Behavior from a Simple Deterministic Map

NASA Astrophysics Data System (ADS)

Krueger, Wesley

2007-10-01

Coherent motion exhibiting large-scale order, such as flocking, swarming, and schooling behavior in animals, can arise from simple rules applied to an initial random array of self-driven particles. We present a completely deterministic dynamic map that exhibits emergent, collective, complex motion for a group of particles. Each individual particle is driven with a constant speed in two dimensions adopting the average direction of a fixed set of non-spatially related partners. In addition, the particle changes direction by π as it reaches a circular boundary. The dynamical patterns arising from these rules range from simple circular-type convective motion to highly sophisticated, complex, collective behavior which can be easily interpreted as flocking, schooling, or swarming depending on the chosen parameters. We present the results as a series of short movies and we also explore possible order parameters and correlation functions capable of quantifying the resulting coherence.

Calibrating the stress-time curve of a combined finite-discrete element method to a Split Hopkinson Pressure Bar experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Osthus, Dave; Godinez, Humberto C.; Rougier, Esteban

We presenmore » t a generic method for automatically calibrating a computer code to an experiment, with uncertainty, for a given “training” set of computer code runs. The calibration technique is general and probabilistic, meaning the calibration uncertainty is represented in the form of a probability distribution. We demonstrate the calibration method by calibrating a combined Finite-Discrete Element Method (FDEM) to a Split Hopkinson Pressure Bar (SHPB) experiment with a granite sample. The probabilistic calibration method combines runs of a FDEM computer simulation for a range of “training” settings and experimental uncertainty to develop a statistical emulator. The process allows for calibration of input parameters and produces output quantities with uncertainty estimates for settings where simulation results are desired. Input calibration and FDEM fitted results are presented. We find that the maximum shear strength σ t max and to a lesser extent maximum tensile strength σ n max govern the behavior of the stress-time curve before and around the peak, while the specific energy in Mode II (shear) E t largely governs the post-peak behavior of the stress-time curve. Good agreement is found between the calibrated FDEM and the SHPB experiment. Interestingly, we find the SHPB experiment to be rather uninformative for calibrating the softening-curve shape parameters (a, b, and c). This work stands as a successful demonstration of how a general probabilistic calibration framework can automatically calibrate FDEM parameters to an experiment.« less

Calibrating the stress-time curve of a combined finite-discrete element method to a Split Hopkinson Pressure Bar experiment

DOE PAGES

Osthus, Dave; Godinez, Humberto C.; Rougier, Esteban; ...

2018-05-01

We presenmore » t a generic method for automatically calibrating a computer code to an experiment, with uncertainty, for a given “training” set of computer code runs. The calibration technique is general and probabilistic, meaning the calibration uncertainty is represented in the form of a probability distribution. We demonstrate the calibration method by calibrating a combined Finite-Discrete Element Method (FDEM) to a Split Hopkinson Pressure Bar (SHPB) experiment with a granite sample. The probabilistic calibration method combines runs of a FDEM computer simulation for a range of “training” settings and experimental uncertainty to develop a statistical emulator. The process allows for calibration of input parameters and produces output quantities with uncertainty estimates for settings where simulation results are desired. Input calibration and FDEM fitted results are presented. We find that the maximum shear strength σ t max and to a lesser extent maximum tensile strength σ n max govern the behavior of the stress-time curve before and around the peak, while the specific energy in Mode II (shear) E t largely governs the post-peak behavior of the stress-time curve. Good agreement is found between the calibrated FDEM and the SHPB experiment. Interestingly, we find the SHPB experiment to be rather uninformative for calibrating the softening-curve shape parameters (a, b, and c). This work stands as a successful demonstration of how a general probabilistic calibration framework can automatically calibrate FDEM parameters to an experiment.« less

Maximum likelihood estimation of protein kinetic parameters under weak assumptions from unfolding force spectroscopy experiments

NASA Astrophysics Data System (ADS)

Aioanei, Daniel; Samorì, Bruno; Brucale, Marco

2009-12-01

Single molecule force spectroscopy (SMFS) is extensively used to characterize the mechanical unfolding behavior of individual protein domains under applied force by pulling chimeric polyproteins consisting of identical tandem repeats. Constant velocity unfolding SMFS data can be employed to reconstruct the protein unfolding energy landscape and kinetics. The methods applied so far require the specification of a single stretching force increase function, either theoretically derived or experimentally inferred, which must then be assumed to accurately describe the entirety of the experimental data. The very existence of a suitable optimal force model, even in the context of a single experimental data set, is still questioned. Herein, we propose a maximum likelihood (ML) framework for the estimation of protein kinetic parameters which can accommodate all the established theoretical force increase models. Our framework does not presuppose the existence of a single force characteristic function. Rather, it can be used with a heterogeneous set of functions, each describing the protein behavior in the stretching time range leading to one rupture event. We propose a simple way of constructing such a set of functions via piecewise linear approximation of the SMFS force vs time data and we prove the suitability of the approach both with synthetic data and experimentally. Additionally, when the spontaneous unfolding rate is the only unknown parameter, we find a correction factor that eliminates the bias of the ML estimator while also reducing its variance. Finally, we investigate which of several time-constrained experiment designs leads to better estimators.

Modeling the Effects of Interfacial Characteristics on Gas Permeation Behavior of Nanotube-Mixed Matrix Membranes.

PubMed

Chehrazi, Ehsan; Sharif, Alireza; Omidkhah, Mohammadreza; Karimi, Mohammad

2017-10-25

Theoretical approaches that accurately predict the gas permeation behavior of nanotube-containing mixed matrix membranes (nanotube-MMMs) are scarce. This is mainly due to ignoring the effects of nanotube/matrix interfacial characteristics in the existing theories. In this paper, based on the analogy of thermal conduction in polymer composites containing nanotubes, we develop a model to describe gas permeation through nanotube-MMMs. Two new parameters, "interfacial thickness" (a int ) and "interfacial permeation resistance" (R int ), are introduced to account for the role of nanotube/matrix interfacial interactions in the proposed model. The obtained values of a int , independent of the nature of the permeate gas, increased by increasing both the nanotubes aspect ratio and polymer-nanotube interfacial strength. An excellent correlation between the values of a int and polymer-nanotube interaction parameters, χ, helped to accurately reproduce the existing experimental data from the literature without the need to resort to any adjustable parameter. The data includes 10 sets of CO 2 /CH 4 permeation, 12 sets of CO 2 /N 2 permeation, 3 sets of CO 2 /O 2 permeation, and 2 sets of CO 2 /H 2 permeation through different nanotube-MMMs. Moreover, the average absolute relative errors between the experimental data and the predicted values of the proposed model are very small (less than 5%) in comparison with those of the existing models in the literature. To the best of our knowledge, this is the first study where such a systematic comparison between model predictions and such extensive experimental data is presented. Finally, the new way of assessing gas permeation data presented in the current work would be a simple alternative to complex approaches that are usually utilized to estimate interfacial thickness in polymer composites.

A novel phenomenological model for dynamic behavior of magnetorheological elastomers in tension-compression mode

NASA Astrophysics Data System (ADS)

Vatandoost, Hossein; Norouzi, Mahmood; Masoud Sajjadi Alehashem, Seyed; Smoukov, Stoyan K.

2017-06-01

Tension-compression operation in MR elastomers (MREs) offers both the most compact design and superior stiffness in many vertical load-bearing applications, such as MRE bearing isolators in bridges and buildings, suspension systems and engine mounts in cars, and vibration control equipment. It suffers, however, from lack of good computational models to predict device performance, and as a result shear-mode MREs are widely used in the industry, despite their low stiffness and load-bearing capacity. We start with a comprehensive review of modeling of MREs and their dynamic characteristics, showing previous studies have mostly focused on dynamic behavior of MREs in shear mode, though the MRE strength and MR effect are greatly decreased at high strain amplitudes, due to increasing distance between the magnetic particles. Moreover, the characteristic parameters of the current models assume either frequency, or strain, or magnetic field are constant; hence, new model parameters must be recalculated for new loading conditions. This is an experimentally time consuming and computationally expensive task, and no models capture the full dynamic behavior of the MREs at all loading conditions. In this study, we present an experimental setup to test MREs in a coupled tension-compression mode, as well as a novel phenomenological model which fully predicts the stress-strain material behavior as a function of magnetic flux density, loading frequency and strain. We use a training set of experiments to find the experimentally derived model parameters, from which can predict by interpolation the MRE behavior in a relatively large continuous range of frequency, strain and magnetic field. We also challenge the model to make extrapolating predictions and compare to additional experiments outside the training experimental data set with good agreement. Further development of this model would allow design and control of engineering structures equipped with tension-compression MREs and all the advantages they offer.

On The Behavior of Subgradient Projections Methods for Convex Feasibility Problems in Euclidean Spaces

PubMed Central

Butnariu, Dan; Censor, Yair; Gurfil, Pini; Hadar, Ethan

2010-01-01

We study some methods of subgradient projections for solving a convex feasibility problem with general (not necessarily hyperplanes or half-spaces) convex sets in the inconsistent case and propose a strategy that controls the relaxation parameters in a specific self-adapting manner. This strategy leaves enough user-flexibility but gives a mathematical guarantee for the algorithm’s behavior in the inconsistent case. We present numerical results of computational experiments that illustrate the computational advantage of the new method. PMID:20182556

On The Behavior of Subgradient Projections Methods for Convex Feasibility Problems in Euclidean Spaces.

PubMed

Butnariu, Dan; Censor, Yair; Gurfil, Pini; Hadar, Ethan

2008-07-03

We study some methods of subgradient projections for solving a convex feasibility problem with general (not necessarily hyperplanes or half-spaces) convex sets in the inconsistent case and propose a strategy that controls the relaxation parameters in a specific self-adapting manner. This strategy leaves enough user-flexibility but gives a mathematical guarantee for the algorithm's behavior in the inconsistent case. We present numerical results of computational experiments that illustrate the computational advantage of the new method.

Where to look? Automating attending behaviors of virtual human characters

NASA Technical Reports Server (NTRS)

Chopra Khullar, S.; Badler, N. I.

2001-01-01

This research proposes a computational framework for generating visual attending behavior in an embodied simulated human agent. Such behaviors directly control eye and head motions, and guide other actions such as locomotion and reach. The implementation of these concepts, referred to as the AVA, draws on empirical and qualitative observations known from psychology, human factors and computer vision. Deliberate behaviors, the analogs of scanpaths in visual psychology, compete with involuntary attention capture and lapses into idling or free viewing. Insights provided by implementing this framework are: a defined set of parameters that impact the observable effects of attention, a defined vocabulary of looking behaviors for certain motor and cognitive activity, a defined hierarchy of three levels of eye behavior (endogenous, exogenous and idling) and a proposed method of how these types interact.

The role of price and enforcement in water allocation: insights from Game Theory

NASA Astrophysics Data System (ADS)

Souza Filho, F.; Lall, U.; Porto, R.

2007-12-01

As many countries are moving towards water sector reforms, practical issues of how water management institutions can better effect allocation, regulation and enforcement of water rights have emerged. The uncertainty associated with water that is available at a particular diversion point becomes a parameter that is likely to influence the behavior of water users as to their application for water licenses, as well as their willingness to pay for licensed use. The ability of a water agency to reduce this uncertainty through effective water rights enforcement is related to the fiscal ability of the agency to sustain the enforcement effort. In this paper, this interplay across the users and the agency is explored, considering the hydraulic structure or sequence of water use, and parameters that define the users and the agency's economics. The potential for free rider behavior by the users, as well as their proposals for licensed use are derived conditional on this setting. The analyses presented are developed in the framework of the theory of "Law and Economics", with user interactions modeled as a game theoretic enterprise. The state of Ceara, Brazil is used loosely as an example setting, with parameter values for the experiments indexed to be approximately those relevant for current decisions. The potential for using the ideas in participatory decision making is discussed.

A statistical characterization of the finger tapping test: modeling, estimation, and applications.

PubMed

Austin, Daniel; McNames, James; Klein, Krystal; Jimison, Holly; Pavel, Misha

2015-03-01

Sensory-motor performance is indicative of both cognitive and physical function. The Halstead-Reitan finger tapping test is a measure of sensory-motor speed commonly used to assess function as part of a neuropsychological evaluation. Despite the widespread use of this test, the underlying motor and cognitive processes driving tapping behavior during the test are not well characterized or understood. This lack of understanding may make clinical inferences from test results about health or disease state less accurate because important aspects of the task such as variability or fatigue are unmeasured. To overcome these limitations, we enhanced the tapper with a sensor that enables us to more fully characterize all the aspects of tapping. This modification enabled us to decompose the tapping performance into six component phases and represent each phase with a set of parameters having clear functional interpretation. This results in a set of 29 total parameters for each trial, including change in tapping over time, and trial-to-trial and tap-to-tap variability. These parameters can be used to more precisely link different aspects of cognition or motor function to tapping behavior. We demonstrate the benefits of this new instrument with a simple hypothesis-driven trial comparing single and dual-task tapping.

A numerical framework for studying the biomechanical behavior of abdominal aortic aneurysm

NASA Astrophysics Data System (ADS)

Jalalahmadi, Golnaz; Linte, Cristian; Helguera, María.

2017-03-01

Abdominal aortic aneurysm (AAA) is known as a leading cause of death in the United States. AAA is an abnormal dilation of the aorta, which usually occurs below the renal arteries and causes an expansion at least 1.5 times its normal diameter. It has been shown that biomechanical parameters of the aortic tissue coupled with a set of specific geometric parameters characterizing the vessel expansion, affect the risk of aneurysm rupture. Here, we developed a numerical framework that incorporates both biomechanical and geometrical factors to study the behavior of abdominal aortic aneurysm. Our workflow enables the extraction of the aneurysm geometry from both clinical quality, as well as low-resolution MR images. We used a two-parameter, hyper-elastic, isotropic, incompressible material to model the vessel tissue. Our numerical model was tested using both synthetic and mouse data and we evaluated the effects of the geometrical and biomechanical properties on the developed peak wall stress. In addition, we performed several parameter sensitivity studies to investigate the effect of different factors affecting the AAA and its behavior and rupture. Lastly, relationships between different geometrical and biomechanical parameters and peak wall stress were determined. These studies help us better understand vessel tissue response to various loading, geometry and biomechanics conditions, and we plan to further correlate these findings with the pathophysiological conditions from a patient population diagnosed with abdominal aortic aneurysms.

COSP for Windows: Strategies for Rapid Analyses of Cyclic Oxidation Behavior

NASA Technical Reports Server (NTRS)

Smialek, James L.; Auping, Judith V.

2002-01-01

COSP is a publicly available computer program that models the cyclic oxidation weight gain and spallation process. Inputs to the model include the selection of an oxidation growth law and a spalling geometry, plus oxide phase, growth rate, spall constant, and cycle duration parameters. Output includes weight change, the amounts of retained and spalled oxide, the total oxygen and metal consumed, and the terminal rates of weight loss and metal consumption. The present version is Windows based and can accordingly be operated conveniently while other applications remain open for importing experimental weight change data, storing model output data, or plotting model curves. Point-and-click operating features include multiple drop-down menus for input parameters, data importing, and quick, on-screen plots showing one selection of the six output parameters for up to 10 models. A run summary text lists various characteristic parameters that are helpful in describing cyclic behavior, such as the maximum weight change, the number of cycles to reach the maximum weight gain or zero weight change, the ratio of these, and the final rate of weight loss. The program includes save and print options as well as a help file. Families of model curves readily show the sensitivity to various input parameters. The cyclic behaviors of nickel aluminide (NiAl) and a complex superalloy are shown to be properly fitted by model curves. However, caution is always advised regarding the uniqueness claimed for any specific set of input parameters,

Family composition and children's dental health behavior: evidence from Germany.

PubMed

Listl, Stefan

2011-01-01

To assess whether children's dental health behavior differs between family compositions of either natural parents or birth mothers together with stepfathers. We use data from the German Health Interview and Examination Survey Children and Adolescents (KiGGS) public use file. This is the first nationally r ep resentative sample on child health in Germany and particularly contains variables for dental attendance, tooth care, and eating behavior of 13,904 children below 14 years of age. A series of zero-inflated Poisson, ordinary least squares, binary, and ordered logistic regression models was set up in order to identify whether family composition is a significant explanatory variable for children's dental health behavior. Family composition turned out as a significant parameter for some aspects of children's dental health behavior. Specifically, children who grow up in families with a birth mother and a stepfather have only half the probability to access dental services but, once seeking treatment, the number of visits is significantly higher in comparison with children raised by their natural parents. Moreover, children growing up in such a patchwork family setting consume a higher amount of sugary foods and drinks. This appears mainly attributable to differential consumption habits for juices, cookies, and chocolate. Children who grow up in settings other than the nuclear family may develop different dental health behaviors than children who grow up with both natural parents, albeit more research is needed to identify the extent to which such behavioral changes lead to variations in caries occurrence.

Motion Estimation and Compensation Strategies in Dynamic Computerized Tomography

NASA Astrophysics Data System (ADS)

Hahn, Bernadette N.

2017-12-01

A main challenge in computerized tomography consists in imaging moving objects. Temporal changes during the measuring process lead to inconsistent data sets, and applying standard reconstruction techniques causes motion artefacts which can severely impose a reliable diagnostics. Therefore, novel reconstruction techniques are required which compensate for the dynamic behavior. This article builds on recent results from a microlocal analysis of the dynamic setting, which enable us to formulate efficient analytic motion compensation algorithms for contour extraction. Since these methods require information about the dynamic behavior, we further introduce a motion estimation approach which determines parameters of affine and certain non-affine deformations directly from measured motion-corrupted Radon-data. Our methods are illustrated with numerical examples for both types of motion.

Self-organized criticality in sandpiles - Nature of the critical phenomenon. [dynamic models in phase transition

NASA Technical Reports Server (NTRS)

Carlson, J. M.; Chayes, J. T.; Swindle, G. H.; Grannan, E. R.

1990-01-01

The scaling behavior of sandpile models is investigated analytically. First, it is shown that sandpile models contain a set of domain walls, referred to as troughs, which bound regions that can experience avalanches. It is further shown that the dynamics of the troughs is governed by a simple set of rules involving birth, death, and coalescence events. A simple trough model is then introduced, and it is proved that the model has a phase transition with the density of the troughs as an order parameter and that, in the thermodynamic limit, the trough density goes to zero at the transition point. Finally, it is shown that the observed scaling behavior is a consequence of finite-size effects.

Analysis of Flow Behavior of an Nb-Ti Microalloyed Steel During Hot Deformation

NASA Astrophysics Data System (ADS)

Mohebbi, Mohammad Sadegh; Parsa, Mohammad Habibi; Rezayat, Mohammad; Orovčík, L'ubomír

2018-03-01

The hot flow behavior of an Nb-Ti microalloyed steel is investigated through hot compression test at various strain rates and temperatures. By the combination of dynamic recovery (DRV) and dynamic recrystallization (DRX) models, a phenomenological constitutive model is developed to derive the flow stress. The predefined activation energy of Q = 270 kJ/mol and the exponent of n = 5 are successfully set to derive critical stress at the onset of DRX and saturation stress of DRV as functions of the Zener-Hollomon parameter by the classical hyperbolic sine equation. The remaining parameters of the constitutive model are determined by fitting them to the experiments. Through substitution of a normalized strain in the DRV model and considering the interconnections between dependent parameters, a new model is developed. It is shown that, despite its fewer parameters, this model is in good agreement with the experiments. Accurate analyses of flow data along with microstructural analyses indicate that the dissolution of NbC precipitates and its consequent solid solution strengthening and retardation of DRX are responsible for the distinguished behaviors in the two temperature ranges between T < 1100 °C and T ≥ 1100 °C. Nevertheless, it is shown that a single constitutive equation can still be employed for the present steel in the whole tested temperature ranges.

Dose-escalation designs in oncology: ADEPT and the CRM.

PubMed

Shu, Jianfen; O'Quigley, John

2008-11-20

The ADEPT software package is not a statistical method in its own right as implied by Gerke and Siedentop (Statist. Med. 2008; DOI: 10.1002/sim.3037). ADEPT implements two-parameter CRM models as described in O'Quigley et al. (Biometrics 1990; 46(1):33-48). All of the basic ideas (use of a two-parameter logistic model, use of a two-dimensional prior for the unknown slope and intercept parameters, sequential estimation and subsequent patient allocation based on minimization of some loss function, flexibility to use cohorts instead of one by one inclusion) are strictly identical. The only, and quite trivial, difference arises in the setting of the prior. O'Quigley et al. (Biometrics 1990; 46(1):33-48) used priors having an analytic expression whereas Whitehead and Brunier (Statist. Med. 1995; 14:33-48) use pseudo-data to play the role of the prior. The question of interest is whether two-parameter CRM works as well, or better, than the one-parameter CRM recommended in O'Quigley et al. (Biometrics 1990; 46(1):33-48). Gerke and Siedentop argue that it does. The published literature suggests otherwise. The conclusions of Gerke and Siedentop stem from three highly particular, and somewhat contrived, situations. Unlike one-parameter CRM (Biometrika 1996; 83:395-405; J. Statist. Plann. Inference 2006; 136:1765-1780; Biometrika 2005; 92:863-873), no statistical properties appear to have been studied for two-parameter CRM. In particular, for two-parameter CRM, the parameter estimates are inconsistent. This ought to be a source of major concern to those proposing its use. Worse still, for finite samples the behavior of estimates can be quite wild despite having incorporated the kind of dampening priors discussed by Gerke and Siedentop. An example in which we illustrate this behavior describes a single patient included at level 1 of 6 levels and experiencing a dose limiting toxicity. The subsequent recommendation is to experiment at level 6! Such problematic behavior is not common. Even so, we show that the allocation behavior of two-parameter CRM is very much less stable than that of one-parameter CRM.

Behavioral Feature Extraction to Determine Learning Styles in e-Learning Environments

ERIC Educational Resources Information Center

Fatahi, Somayeh; Moradi, Hadi; Farmad, Elaheh

2015-01-01

Learning Style (LS) is an important parameter in the learning process. Therefore, learning styles should be considered in the design, development, and implementation of e-learning environments. Consequently, an important capability of an e-learning system could be the automatic determination of a student's learning style. In this paper, a set of…

Application of the distributed activation energy model to the kinetic study of pyrolysis of the fresh water algae Chlorococcum humicola.

PubMed

Kirtania, Kawnish; Bhattacharya, Sankar

2012-03-01

Apart from capturing carbon dioxide, fresh water algae can be used to produce biofuel. To assess the energy potential of Chlorococcum humicola, the alga's pyrolytic behavior was studied at heating rates of 5-20K/min in a thermobalance. To model the weight loss characteristics, an algorithm was developed based on the distributed activation energy model and applied to experimental data to extract the kinetics of the decomposition process. When the kinetic parameters estimated by this method were applied to another set of experimental data which were not used to estimate the parameters, the model was capable of predicting the pyrolysis behavior, in the new set of data with a R(2) value of 0.999479. The slow weight loss, that took place at the end of the pyrolysis process, was also accounted for by the proposed algorithm which is capable of predicting the pyrolysis kinetics of C. humicola at different heating rates. Crown Copyright © 2011. Published by Elsevier Ltd. All rights reserved.

Analysis of temperature-dependent neutron transmission and self-indication measurements on tantalum at 2-keV neutron energy

NASA Technical Reports Server (NTRS)

Semler, T. T.

1973-01-01

The method of pseudo-resonance cross sections is used to analyze published temperature-dependent neutron transmission and self-indication measurements on tantalum in the unresolved region. In the energy region analyzed, 1825.0 to 2017.0 eV, a direct application of the pseudo-resonance approach using a customary average strength function will not provide effective cross sections which fit the measured cross section behavior. Rather a local value of the strength function is required, and a set of resonances which model the measured behavior of the effective cross sections is derived. This derived set of resonance parameters adequately represents the observed resonance hehavior in this local energy region. Similar analyses for the measurements in other unresolved energy regions are necessary to obtain local resonance parameters for improved reactor calculations. This study suggests that Doppler coefficients calculated by sampling from grand average statistical distributions over the entire unresolved resonance region can be in error, since significant local variations in the statistical distributions are not taken into consideration.

A Navigation Analysis Tool (NAT) to assess spatial behavior in open-field and structured mazes.

PubMed

Jarlier, Frédéric; Arleo, Angelo; Petit, Géraldine H; Lefort, Julie M; Fouquet, Céline; Burguière, Eric; Rondi-Reig, Laure

2013-05-15

Spatial navigation calls upon mnemonic capabilities (e.g. remembering the location of a rewarding site) as well as adaptive motor control (e.g. fine tuning of the trajectory according to the ongoing sensory context). To study this complex process by means of behavioral measurements it is necessary to quantify a large set of meaningful parameters on multiple time scales (from milliseconds to several minutes), and to compare them across different paradigms. Moreover, the issue of automating the behavioral analysis is critical to cope with the consequent computational load and the sophistication of the measurements. We developed a general purpose Navigation Analysis Tool (NAT) that provides an integrated architecture consisting of a data management system (implemented in MySQL), a core analysis toolbox (in MATLAB), and a graphical user interface (in JAVA). Its extensive characterization of trajectories over time, from exploratory behavior to goal-oriented navigation with decision points using a wide range of parameters, makes NAT a powerful analysis tool. In particular, NAT supplies a new set of specific measurements assessing performances in multiple intersection mazes and allowing navigation strategies to be discriminated (e.g. in the starmaze). Its user interface enables easy use while its modular organization provides many opportunities of extension and customization. Importantly, the portability of NAT to any type of maze and environment extends its exploitation far beyond the field of spatial navigation. Copyright © 2013 Elsevier B.V. All rights reserved.

Evaluation of a hydrological model based on Bidirectional Reach (BReach)

NASA Astrophysics Data System (ADS)

Van Eerdenbrugh, Katrien; Van Hoey, Stijn; Verhoest, Niko E. C.

2016-04-01

Evaluation and discrimination of model structures is crucial to ensure an appropriate use of hydrological models. When evaluating model results by aggregating their quality in (a subset of) individual observations, overall results of this analysis sometimes conceal important detailed information about model structural deficiencies. Analyzing model results within their local (time) context can uncover this detailed information. In this research, a methodology called Bidirectional Reach (BReach) is proposed to evaluate and analyze results of a hydrological model by assessing the maximum left and right reach in each observation point that is used for model evaluation. These maximum reaches express the capability of the model to describe a subset of the evaluation data both in the direction of the previous (left) and of the following data (right). This capability is evaluated on two levels. First, on the level of individual observations, the combination of a parameter set and an observation is classified as non-acceptable if the deviation between the accompanying model result and the measurement exceeds observational uncertainty. Second, the behavior in a sequence of observations is evaluated by means of a tolerance degree. This tolerance degree expresses the condition for satisfactory model behavior in a data series and is defined by the percentage of observations within this series that can have non-acceptable model results. Based on both criteria, the maximum left and right reaches of a model in an observation represent the data points in the direction of the previous respectively the following observations beyond which none of the sampled parameter sets both are satisfactory and result in an acceptable deviation. After assessing these reaches for a variety of tolerance degrees, results can be plotted in a combined BReach plot that show temporal changes in the behavior of model results. The methodology is applied on a Probability Distributed Model (PDM) of the river Grote Nete upstream of Geel-Zammel with 1 106 randomly sampled parameter sets for three separate years. Acceptable model results must fit in the 95 % uncertainty bounds of observed discharges and tolerance degrees of 0 %, 5 %, 10 %, 20 % and 40 % are applied. An evaluation of BReach results with regard to other variables, such as the magnitude and the rate of change of the observed discharges enables to detect recurring patterns in model errors. This results in an augmented understanding of the model's structural deficiencies, revealing the incapability of the PDM model to simulate both high and low flow simulations with a single parameter set for this catchment. As the methodology can be applied for different hydrological model structures, it is a useful tool to gain understanding of the difference in behavior of competing models.

Recommended Parameter Values for GENII Modeling of Radionuclides in Routine Air and Water Releases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Snyder, Sandra F.; Arimescu, Carmen; Napier, Bruce A.

The GENII v2 code is used to estimate dose to individuals or populations from the release of radioactive materials into air or water. Numerous parameter values are required for input into this code. User-defined parameters cover the spectrum from chemical data, meteorological data, agricultural data, and behavioral data. This document is a summary of parameter values that reflect conditions in the United States. Reasonable regional and age-dependent data is summarized. Data availability and quality varies. The set of parameters described address scenarios for chronic air emissions or chronic releases to public waterways. Considerations for the special tritium and carbon-14 modelsmore » are briefly addressed. GENIIv2.10.0 is the current software version that this document supports.« less

GVIPS Models and Software

NASA Technical Reports Server (NTRS)

Arnold, Steven M.; Gendy, Atef; Saleeb, Atef F.; Mark, John; Wilt, Thomas E.

2007-01-01

Two reports discuss, respectively, (1) the generalized viscoplasticity with potential structure (GVIPS) class of mathematical models and (2) the Constitutive Material Parameter Estimator (COMPARE) computer program. GVIPS models are constructed within a thermodynamics- and potential-based theoretical framework, wherein one uses internal state variables and derives constitutive equations for both the reversible (elastic) and the irreversible (viscoplastic) behaviors of materials. Because of the underlying potential structure, GVIPS models not only capture a variety of material behaviors but also are very computationally efficient. COMPARE comprises (1) an analysis core and (2) a C++-language subprogram that implements a Windows-based graphical user interface (GUI) for controlling the core. The GUI relieves the user of the sometimes tedious task of preparing data for the analysis core, freeing the user to concentrate on the task of fitting experimental data and ultimately obtaining a set of material parameters. The analysis core consists of three modules: one for GVIPS material models, an analysis module containing a specialized finite-element solution algorithm, and an optimization module. COMPARE solves the problem of finding GVIPS material parameters in the manner of a design-optimization problem in which the parameters are the design variables.

Maximum Likelihood Item Easiness Models for Test Theory without an Answer Key

ERIC Educational Resources Information Center

France, Stephen L.; Batchelder, William H.

2015-01-01

Cultural consensus theory (CCT) is a data aggregation technique with many applications in the social and behavioral sciences. We describe the intuition and theory behind a set of CCT models for continuous type data using maximum likelihood inference methodology. We describe how bias parameters can be incorporated into these models. We introduce…

Stepper motor

NASA Technical Reports Server (NTRS)

Dekramer, Cornelis

1994-01-01

The purpose of this document is to describe the more commonly used permanent magnet stepper motors for spaceflight. It will discuss the mechanical and electrical aspects of the devices, their torque behavior, those parameters which need to be controlled and measured, and test methods to be employed. It will also discuss torque margins, compare these to the existing margin requirements, and determine the applicability of these requirements. Finally it will attempt to generate a set of requirements which will be used in any stepper motor procurement and will fully characterize the stepper motor behavior in a consistent and repeatable fashion.

Inferring epidemiological parameters from phylogenetic information for the HIV-1 epidemic among MSM

NASA Astrophysics Data System (ADS)

Quax, Rick; van de Vijver, David A. M. C.; Frentz, Dineke; Sloot, Peter M. A.

2013-09-01

The HIV-1 epidemic in Europe is primarily sustained by a dynamic topology of sexual interactions among MSM who have individual immune systems and behavior. This epidemiological process shapes the phylogeny of the virus population. Both fields of epidemic modeling and phylogenetics have a long history, however it remains difficult to use phylogenetic data to infer epidemiological parameters such as the structure of the sexual network and the per-act infectiousness. This is because phylogenetic data is necessarily incomplete and ambiguous. Here we show that the cluster-size distribution indeed contains information about epidemiological parameters using detailed numberical experiments. We simulate the HIV epidemic among MSM many times using the Monte Carlo method with all parameter values and their ranges taken from literature. For each simulation and the corresponding set of parameter values we calculate the likelihood of reproducing an observed cluster-size distribution. The result is an estimated likelihood distribution of all parameters from the phylogenetic data, in particular the structure of the sexual network, the per-act infectiousness, and the risk behavior reduction upon diagnosis. These likelihood distributions encode the knowledge provided by the observed cluster-size distrbution, which we quantify using information theory. Our work suggests that the growing body of genetic data of patients can be exploited to understand the underlying epidemiological process.

System diagnostic builder

NASA Technical Reports Server (NTRS)

Nieten, Joseph L.; Burke, Roger

1992-01-01

The System Diagnostic Builder (SDB) is an automated software verification and validation tool using state-of-the-art Artificial Intelligence (AI) technologies. The SDB is used extensively by project BURKE at NASA-JSC as one component of a software re-engineering toolkit. The SDB is applicable to any government or commercial organization which performs verification and validation tasks. The SDB has an X-window interface, which allows the user to 'train' a set of rules for use in a rule-based evaluator. The interface has a window that allows the user to plot up to five data parameters (attributes) at a time. Using these plots and a mouse, the user can identify and classify a particular behavior of the subject software. Once the user has identified the general behavior patterns of the software, he can train a set of rules to represent his knowledge of that behavior. The training process builds rules and fuzzy sets to use in the evaluator. The fuzzy sets classify those data points not clearly identified as a particular classification. Once an initial set of rules is trained, each additional data set given to the SDB will be used by a machine learning mechanism to refine the rules and fuzzy sets. This is a passive process and, therefore, it does not require any additional operator time. The evaluation component of the SDB can be used to validate a single software system using some number of different data sets, such as a simulator. Moreover, it can be used to validate software systems which have been re-engineered from one language and design methodology to a totally new implementation.

Analysis of Fiber Clustering in Composite Materials Using High-Fidelity Multiscale Micromechanics

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Aboudi, Jacob; Arnold, Steven M.

2015-01-01

A new multiscale micromechanical approach is developed for the prediction of the behavior of fiber reinforced composites in presence of fiber clustering. The developed method is based on a coupled two-scale implementation of the High-Fidelity Generalized Method of Cells theory, wherein both the local and global scales are represented using this micromechanical method. Concentration tensors and effective constitutive equations are established on both scales and linked to establish the required coupling, thus providing the local fields throughout the composite as well as the global properties and effective nonlinear response. Two nondimensional parameters, in conjunction with actual composite micrographs, are used to characterize the clustering of fibers in the composite. Based on the predicted local fields, initial yield and damage envelopes are generated for various clustering parameters for a polymer matrix composite with both carbon and glass fibers. Nonlinear epoxy matrix behavior is also considered, with results in the form of effective nonlinear response curves, with varying fiber clustering and for two sets of nonlinear matrix parameters.

Phase transition in the parametric natural visibility graph.

PubMed

Snarskii, A A; Bezsudnov, I V

2016-10-01

We investigate time series by mapping them to the complex networks using a parametric natural visibility graph (PNVG) algorithm that generates graphs depending on arbitrary continuous parameter-the angle of view. We study the behavior of the relative number of clusters in PNVG near the critical value of the angle of view. Artificial and experimental time series of different nature are used for numerical PNVG investigations to find critical exponents above and below the critical point as well as the exponent in the finite size scaling regime. Altogether, they allow us to find the critical exponent of the correlation length for PNVG. The set of calculated critical exponents satisfies the basic Widom relation. The PNVG is found to demonstrate scaling behavior. Our results reveal the similarity between the behavior of the relative number of clusters in PNVG and the order parameter in the second-order phase transitions theory. We show that the PNVG is another example of a system (in addition to magnetic, percolation, superconductivity, etc.) with observed second-order phase transition.

An integrated inverse model-experimental approach to determine soft tissue three-dimensional constitutive parameters: application to post-infarcted myocardium.

PubMed

Avazmohammadi, Reza; Li, David S; Leahy, Thomas; Shih, Elizabeth; Soares, João S; Gorman, Joseph H; Gorman, Robert C; Sacks, Michael S

2018-02-01

Knowledge of the complete three-dimensional (3D) mechanical behavior of soft tissues is essential in understanding their pathophysiology and in developing novel therapies. Despite significant progress made in experimentation and modeling, a complete approach for the full characterization of soft tissue 3D behavior remains elusive. A major challenge is the complex architecture of soft tissues, such as myocardium, which endows them with strongly anisotropic and heterogeneous mechanical properties. Available experimental approaches for quantifying the 3D mechanical behavior of myocardium are limited to preselected planar biaxial and 3D cuboidal shear tests. These approaches fall short in pursuing a model-driven approach that operates over the full kinematic space. To address these limitations, we took the following approach. First, based on a kinematical analysis and using a given strain energy density function (SEDF), we obtained an optimal set of displacement paths based on the full 3D deformation gradient tensor. We then applied this optimal set to obtain novel experimental data from a 1-cm cube of post-infarcted left ventricular myocardium. Next, we developed an inverse finite element (FE) simulation of the experimental configuration embedded in a parameter optimization scheme for estimation of the SEDF parameters. Notable features of this approach include: (i) enhanced determinability and predictive capability of the estimated parameters following an optimal design of experiments, (ii) accurate simulation of the experimental setup and transmural variation of local fiber directions in the FE environment, and (iii) application of all displacement paths to a single specimen to minimize testing time so that tissue viability could be maintained. Our results indicated that, in contrast to the common approach of conducting preselected tests and choosing an SEDF a posteriori, the optimal design of experiments, integrated with a chosen SEDF and full 3D kinematics, leads to a more robust characterization of the mechanical behavior of myocardium and higher predictive capabilities of the SEDF. The methodology proposed and demonstrated herein will ultimately provide a means to reliably predict tissue-level behaviors, thus facilitating organ-level simulations for efficient diagnosis and evaluation of potential treatments. While applied to myocardium, such developments are also applicable to characterization of other types of soft tissues.

Examining driver behavior at the onset of yellow in a traffic simulator environment: Comparisons between random parameters and latent class logit models.

PubMed

Savolainen, Peter T

2016-11-01

This study involves an examination of driver behavior at the onset of a yellow signal indication. Behavioral data were obtained from a driving simulator study that was conducted through the National Advanced Driving Simulator (NADS) laboratory at the University of Iowa. These data were drawn from a series of events during which study participants drove through a series of intersections where the traffic signals changed from the green to yellow phase. The resulting dataset provides potential insights into how driver behavior is affected by distracted driving through an experimental design that alternated handheld, headset, and hands-free cell phone use with "normal" baseline driving events. The results of the study show that male drivers ages 18-45 were more likely to stop. Participants were also more likely to stop as they became more familiar with the simulator environment. Cell phone use was found to some influence on driver behavior in this setting, though the effects varied significantly across individuals. The study also demonstrates two methodological approaches for dealing with unobserved heterogeneity across drivers. These include random parameters and latent class logit models, each of which analyze the data as a panel. The results show each method to provide significantly better fit than a pooled, fixed parameter model. Differences in terms of the context of these two approaches are discussed, providing important insights as to the differences between these modeling frameworks. Copyright © 2016 Elsevier Ltd. All rights reserved.

Numerical Model for the Study of the Strength and Failure Modes of Rock Containing Non-Persistent Joints

NASA Astrophysics Data System (ADS)

Vergara, Maximiliano R.; Van Sint Jan, Michel; Lorig, Loren

2016-04-01

The mechanical behavior of rock containing parallel non-persistent joint sets was studied using a numerical model. The numerical analysis was performed using the discrete element software UDEC. The use of fictitious joints allowed the inclusion of non-persistent joints in the model domain and simulating the progressive failure due to propagation of existing fractures. The material and joint mechanical parameters used in the model were obtained from experimental results. The results of the numerical model showed good agreement with the strength and failure modes observed in the laboratory. The results showed the large anisotropy in the strength resulting from variation of the joint orientation. Lower strength of the specimens was caused by the coalescence of fractures belonging to parallel joint sets. A correlation was found between geometrical parameters of the joint sets and the contribution of the joint sets strength in the global strength of the specimen. The results suggest that for the same dip angle with respect to the principal stresses; the uniaxial strength depends primarily on the joint spacing and the angle between joints tips and less on the length of the rock bridges (persistency). A relation between joint geometrical parameters was found from which the resulting failure mode can be predicted.

Beyond synergies. Comment on "Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands" by Marco Santello et al.

NASA Astrophysics Data System (ADS)

Schwartz, Andrew B.

2016-07-01

The target paper by Santello et al. [1] uses the observation that hand shape during grasping can be described by a small set of basic postures, or ;synergies,; to describe the possible neural basis of motor control during this complex behavior. In the literature, the term ;synergy; has been used with a number of different meanings and is still loosely defined, making it difficult to derive concrete analogs of corresponding neural structure. Here, I will define ;synergy; broadly, as a set of parameters bound together by a pattern of correlation. With this definition, it can be argued that behavioral synergies are just one facet of the correlational structuring used by the brain to generate behavior. As pointed out in the target article, the structure found in synergies is driven by the physical constraints of our bodies and our surroundings, combined with the behavioral control imparted by our nervous system. This control itself is based on correlational structure which is likely to be a fundamental property of brain function.

Theoretical Tools and Software for Modeling, Simulation and Control Design of Rocket Test Facilities

NASA Technical Reports Server (NTRS)

Richter, Hanz

2004-01-01

A rocket test stand and associated subsystems are complex devices whose operation requires that certain preparatory calculations be carried out before a test. In addition, real-time control calculations must be performed during the test, and further calculations are carried out after a test is completed. The latter may be required in order to evaluate if a particular test conformed to specifications. These calculations are used to set valve positions, pressure setpoints, control gains and other operating parameters so that a desired system behavior is obtained and the test can be successfully carried out. Currently, calculations are made in an ad-hoc fashion and involve trial-and-error procedures that may involve activating the system with the sole purpose of finding the correct parameter settings. The goals of this project are to develop mathematical models, control methodologies and associated simulation environments to provide a systematic and comprehensive prediction and real-time control capability. The models and controller designs are expected to be useful in two respects: 1) As a design tool, a model is the only way to determine the effects of design choices without building a prototype, which is, in the context of rocket test stands, impracticable; 2) As a prediction and tuning tool, a good model allows to set system parameters off-line, so that the expected system response conforms to specifications. This includes the setting of physical parameters, such as valve positions, and the configuration and tuning of any feedback controllers in the loop.

Laban Movement Analysis towards Behavior Patterns

NASA Astrophysics Data System (ADS)

Santos, Luís; Dias, Jorge

This work presents a study about the use of Laban Movement Analysis (LMA) as a robust tool to describe human basic behavior patterns, to be applied in human-machine interaction. LMA is a language used to describe and annotate dancing movements and is divided in components [1]: Body, Space, Shape and Effort. Despite its general framework is widely used in physical and mental therapy [2], it has found little application in the engineering domain. Rett J. [3] proposed to implement LMA using Bayesian Networks. However LMA component models have not yet been fully implemented. A study on how to approach behavior using LMA is presented. Behavior is a complex feature and movement chain, but we believe that most basic behavior primitives can be discretized in simple features. Correctly identifying Laban parameters and the movements the authors feel that good patterns can be found within a specific set of basic behavior semantics.

Ambulatory instrumentation suitable for long-term monitoring of cattle health.

PubMed

Schoenig, S A; Hildreth, T S; Nagl, L; Erickson, H; Spire, M; Andresen, D; Warren, S

2004-01-01

The benefits of real-time health diagnoses of cattle are potentially tremendous. Early detection of transmissible disease, whether from natural or terrorist events, could help to avoid huge financial losses in the agriculture industry while also improving meat quality. This work discusses physiological and behavioral parameters relevant to cattle state-of-health assessment. These parameters, along with a potentially harsh monitoring environment, drive a set of design considerations that must be addressed when building systems to acquire long-term, real-time measurements in the field. A prototype system is presented that supports the measurement of suitable physiologic parameters and begins to address the design constraints for continuous state-of-health determination in free-roaming cattle.

An improved hybrid of particle swarm optimization and the gravitational search algorithm to produce a kinetic parameter estimation of aspartate biochemical pathways.

PubMed

Ismail, Ahmad Muhaimin; Mohamad, Mohd Saberi; Abdul Majid, Hairudin; Abas, Khairul Hamimah; Deris, Safaai; Zaki, Nazar; Mohd Hashim, Siti Zaiton; Ibrahim, Zuwairie; Remli, Muhammad Akmal

2017-12-01

Mathematical modelling is fundamental to understand the dynamic behavior and regulation of the biochemical metabolisms and pathways that are found in biological systems. Pathways are used to describe complex processes that involve many parameters. It is important to have an accurate and complete set of parameters that describe the characteristics of a given model. However, measuring these parameters is typically difficult and even impossible in some cases. Furthermore, the experimental data are often incomplete and also suffer from experimental noise. These shortcomings make it challenging to identify the best-fit parameters that can represent the actual biological processes involved in biological systems. Computational approaches are required to estimate these parameters. The estimation is converted into multimodal optimization problems that require a global optimization algorithm that can avoid local solutions. These local solutions can lead to a bad fit when calibrating with a model. Although the model itself can potentially match a set of experimental data, a high-performance estimation algorithm is required to improve the quality of the solutions. This paper describes an improved hybrid of particle swarm optimization and the gravitational search algorithm (IPSOGSA) to improve the efficiency of a global optimum (the best set of kinetic parameter values) search. The findings suggest that the proposed algorithm is capable of narrowing down the search space by exploiting the feasible solution areas. Hence, the proposed algorithm is able to achieve a near-optimal set of parameters at a fast convergence speed. The proposed algorithm was tested and evaluated based on two aspartate pathways that were obtained from the BioModels Database. The results show that the proposed algorithm outperformed other standard optimization algorithms in terms of accuracy and near-optimal kinetic parameter estimation. Nevertheless, the proposed algorithm is only expected to work well in small scale systems. In addition, the results of this study can be used to estimate kinetic parameter values in the stage of model selection for different experimental conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

Advanced active quenching circuit for ultra-fast quantum cryptography.

PubMed

Stipčević, Mario; Christensen, Bradley G; Kwiat, Paul G; Gauthier, Daniel J

2017-09-04

Commercial photon-counting modules based on actively quenched solid-state avalanche photodiode sensors are used in a wide variety of applications. Manufacturers characterize their detectors by specifying a small set of parameters, such as detection efficiency, dead time, dark counts rate, afterpulsing probability and single-photon arrival-time resolution (jitter). However, they usually do not specify the range of conditions over which these parameters are constant or present a sufficient description of the characterization process. In this work, we perform a few novel tests on two commercial detectors and identify an additional set of imperfections that must be specified to sufficiently characterize their behavior. These include rate-dependence of the dead time and jitter, detection delay shift, and "twilighting". We find that these additional non-ideal behaviors can lead to unexpected effects or strong deterioration of the performance of a system using these devices. We explain their origin by an in-depth analysis of the active quenching process. To mitigate the effects of these imperfections, a custom-built detection system is designed using a novel active quenching circuit. Its performance is compared against two commercial detectors in a fast quantum key distribution system with hyper-entangled photons and a random number generator.

Anelastic characterization of soft poroelastic materials by anelastography

NASA Astrophysics Data System (ADS)

Flores B, Carolina; Ammann, Jean Jacques; Rivera, Ricardo

2008-11-01

This paper presents the ID characterization of the local anelastic strain determined in soft poroelastic materials through acoustic scattering in a creep test configuration. Backscattering signals are obtained at successive times in a specimen submitted to a constant stress, applied coaxially to the acoustic beam of a 5 MHz ultrasonic transducer operated in pulse-echo mode. The local displacement is measured by determining the local shift between the RF traces by performing a running cross-correlation operation between equivalent segments extracted from two pairs of RF traces. The local strain the in the specimen is obtained as the displacement gradient. The method has been implemented on biphasic porous materials that present poroelastic behaviors such as synthetic latex sponges impregnated with viscous liquids. The strain/time curves have been interpreted through a continuous bimodal anelastic model (CBA), composed of an infinite set of Kelvin-Voigt cells connected in series with an elastic spring. The fit of an experimental strain/time curve selected at a specific depth through the CBA model allow characterizing the local anelastic behavior through a set of 7 characteristics parameters for the specimen at this location: three short-term and three long-term anelastic parameters and one elastic constant.

A computational framework for testing arrhythmia marker sensitivities to model parameters in functionally calibrated populations of atrial cells

NASA Astrophysics Data System (ADS)

Vagos, Márcia R.; Arevalo, Hermenegild; de Oliveira, Bernardo Lino; Sundnes, Joakim; Maleckar, Mary M.

2017-09-01

Models of cardiac cell electrophysiology are complex non-linear systems which can be used to gain insight into mechanisms of cardiac dynamics in both healthy and pathological conditions. However, the complexity of cardiac models can make mechanistic insight difficult. Moreover, these are typically fitted to averaged experimental data which do not incorporate the variability in observations. Recently, building populations of models to incorporate inter- and intra-subject variability in simulations has been combined with sensitivity analysis (SA) to uncover novel ionic mechanisms and potentially clarify arrhythmogenic behaviors. We used the Koivumäki human atrial cell model to create two populations, representing normal Sinus Rhythm (nSR) and chronic Atrial Fibrillation (cAF), by varying 22 key model parameters. In each population, 14 biomarkers related to the action potential and dynamic restitution were extracted. Populations were calibrated based on distributions of biomarkers to obtain reasonable physiological behavior, and subjected to SA to quantify correlations between model parameters and pro-arrhythmia markers. The two populations showed distinct behaviors under steady state and dynamic pacing. The nSR population revealed greater variability, and more unstable dynamic restitution, as compared to the cAF population, suggesting that simulated cAF remodeling rendered cells more stable to parameter variation and rate adaptation. SA revealed that the biomarkers depended mainly on five ionic currents, with noted differences in sensitivities to these between nSR and cAF. Also, parameters could be selected to produce a model variant with no alternans and unaltered action potential morphology, highlighting that unstable dynamical behavior may be driven by specific cell parameter settings. These results ultimately suggest that arrhythmia maintenance in cAF may not be due to instability in cell membrane excitability, but rather due to tissue-level effects which promote initiation and maintenance of reentrant arrhythmia.

Optimizing Design Parameters for Sets of Concentric Tube Robots using Sampling-based Motion Planning

PubMed Central

Baykal, Cenk; Torres, Luis G.; Alterovitz, Ron

2015-01-01

Concentric tube robots are tentacle-like medical robots that can bend around anatomical obstacles to access hard-to-reach clinical targets. The component tubes of these robots can be swapped prior to performing a task in order to customize the robot’s behavior and reachable workspace. Optimizing a robot’s design by appropriately selecting tube parameters can improve the robot’s effectiveness on a procedure-and patient-specific basis. In this paper, we present an algorithm that generates sets of concentric tube robot designs that can collectively maximize the reachable percentage of a given goal region in the human body. Our algorithm combines a search in the design space of a concentric tube robot using a global optimization method with a sampling-based motion planner in the robot’s configuration space in order to find sets of designs that enable motions to goal regions while avoiding contact with anatomical obstacles. We demonstrate the effectiveness of our algorithm in a simulated scenario based on lung anatomy. PMID:26951790

Optimizing Design Parameters for Sets of Concentric Tube Robots using Sampling-based Motion Planning.

PubMed

Baykal, Cenk; Torres, Luis G; Alterovitz, Ron

2015-09-28

Concentric tube robots are tentacle-like medical robots that can bend around anatomical obstacles to access hard-to-reach clinical targets. The component tubes of these robots can be swapped prior to performing a task in order to customize the robot's behavior and reachable workspace. Optimizing a robot's design by appropriately selecting tube parameters can improve the robot's effectiveness on a procedure-and patient-specific basis. In this paper, we present an algorithm that generates sets of concentric tube robot designs that can collectively maximize the reachable percentage of a given goal region in the human body. Our algorithm combines a search in the design space of a concentric tube robot using a global optimization method with a sampling-based motion planner in the robot's configuration space in order to find sets of designs that enable motions to goal regions while avoiding contact with anatomical obstacles. We demonstrate the effectiveness of our algorithm in a simulated scenario based on lung anatomy.

Passive autonomous infrared sensor technology

NASA Astrophysics Data System (ADS)

Sadjadi, Firooz

1987-10-01

This study was conducted in response to the DoD's need for establishing understanding of algorithm's modules for passive infrared sensors and seekers and establishing a standardized systematic procedure for applying this understanding to DoD applications. We quantified the performances of Honeywell's Background Adaptive Convexity Operator Region Extractor (BACORE) detection and segmentation modules, as functions of a set of image metrics for both single-frame and multiframe processing. We established an understanding of the behavior of the BACORE's internal parameters. We characterized several sets of stationary and sequential imagery and extracted TIR squared, TBIR squared, ESR, and range for each target. We generated a set of performance models for multi-frame processing BACORE that could be used to predict the behavior of BACORE in image metric space. A similar study was conducted for another of Honeywell's segmentors, namely Texture Boundary Locator (TBL), and its performances were quantified. Finally, a comparison of TBL and BACORE on the same data base and same number of frames was made.

Linking aquifer spatial properties and non-Fickian transport in mobile-immobile like alluvial settings

USGS Publications Warehouse

Zhang, Yong; Green, Christopher T.; Baeumer, Boris

2014-01-01

Time-nonlocal transport models can describe non-Fickian diffusion observed in geological media, but the physical meaning of parameters can be ambiguous, and most applications are limited to curve-fitting. This study explores methods for predicting the parameters of a temporally tempered Lévy motion (TTLM) model for transient sub-diffusion in mobile–immobile like alluvial settings represented by high-resolution hydrofacies models. The TTLM model is a concise multi-rate mass transfer (MRMT) model that describes a linear mass transfer process where the transfer kinetics and late-time transport behavior are controlled by properties of the host medium, especially the immobile domain. The intrinsic connection between the MRMT and TTLM models helps to estimate the main time-nonlocal parameters in the TTLM model (which are the time scale index, the capacity coefficient, and the truncation parameter) either semi-analytically or empirically from the measurable aquifer properties. Further applications show that the TTLM model captures the observed solute snapshots, the breakthrough curves, and the spatial moments of plumes up to the fourth order. Most importantly, the a priori estimation of the time-nonlocal parameters outside of any breakthrough fitting procedure provides a reliable “blind” prediction of the late-time dynamics of subdiffusion observed in a spectrum of alluvial settings. Predictability of the time-nonlocal parameters may be due to the fact that the late-time subdiffusion is not affected by the exact location of each immobile zone, but rather is controlled by the time spent in immobile blocks surrounding the pathway of solute particles. Results also show that the effective dispersion coefficient has to be fitted due to the scale effect of transport, and the mean velocity can differ from local measurements or volume averages. The link between medium heterogeneity and time-nonlocal parameters will help to improve model predictability for non-Fickian transport in alluvial settings.

Sensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection

PubMed Central

Alam, Maksudul; Deng, Xinwei; Philipson, Casandra; Bassaganya-Riera, Josep; Bisset, Keith; Carbo, Adria; Eubank, Stephen; Hontecillas, Raquel; Hoops, Stefan; Mei, Yongguo; Abedi, Vida; Marathe, Madhav

2015-01-01

Agent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system. The interaction of components and the behavior of individual objects is described procedurally as a function of the internal states and the local interactions, which are often stochastic in nature. Such models typically have complex structures and consist of a large number of modeling parameters. Determining the key modeling parameters which govern the outcomes of the system is very challenging. Sensitivity analysis plays a vital role in quantifying the impact of modeling parameters in massively interacting systems, including large complex ABM. The high computational cost of executing simulations impedes running experiments with exhaustive parameter settings. Existing techniques of analyzing such a complex system typically focus on local sensitivity analysis, i.e. one parameter at a time, or a close “neighborhood” of particular parameter settings. However, such methods are not adequate to measure the uncertainty and sensitivity of parameters accurately because they overlook the global impacts of parameters on the system. In this article, we develop novel experimental design and analysis techniques to perform both global and local sensitivity analysis of large-scale ABMs. The proposed method can efficiently identify the most significant parameters and quantify their contributions to outcomes of the system. We demonstrate the proposed methodology for ENteric Immune SImulator (ENISI), a large-scale ABM environment, using a computational model of immune responses to Helicobacter pylori colonization of the gastric mucosa. PMID:26327290

Sensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection.

PubMed

Alam, Maksudul; Deng, Xinwei; Philipson, Casandra; Bassaganya-Riera, Josep; Bisset, Keith; Carbo, Adria; Eubank, Stephen; Hontecillas, Raquel; Hoops, Stefan; Mei, Yongguo; Abedi, Vida; Marathe, Madhav

2015-01-01

Agent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system. The interaction of components and the behavior of individual objects is described procedurally as a function of the internal states and the local interactions, which are often stochastic in nature. Such models typically have complex structures and consist of a large number of modeling parameters. Determining the key modeling parameters which govern the outcomes of the system is very challenging. Sensitivity analysis plays a vital role in quantifying the impact of modeling parameters in massively interacting systems, including large complex ABM. The high computational cost of executing simulations impedes running experiments with exhaustive parameter settings. Existing techniques of analyzing such a complex system typically focus on local sensitivity analysis, i.e. one parameter at a time, or a close "neighborhood" of particular parameter settings. However, such methods are not adequate to measure the uncertainty and sensitivity of parameters accurately because they overlook the global impacts of parameters on the system. In this article, we develop novel experimental design and analysis techniques to perform both global and local sensitivity analysis of large-scale ABMs. The proposed method can efficiently identify the most significant parameters and quantify their contributions to outcomes of the system. We demonstrate the proposed methodology for ENteric Immune SImulator (ENISI), a large-scale ABM environment, using a computational model of immune responses to Helicobacter pylori colonization of the gastric mucosa.

Parameters Selection for Bivariate Multiscale Entropy Analysis of Postural Fluctuations in Fallers and Non-Fallers Older Adults.

PubMed

Ramdani, Sofiane; Bonnet, Vincent; Tallon, Guillaume; Lagarde, Julien; Bernard, Pierre Louis; Blain, Hubert

2016-08-01

Entropy measures are often used to quantify the regularity of postural sway time series. Recent methodological developments provided both multivariate and multiscale approaches allowing the extraction of complexity features from physiological signals; see "Dynamical complexity of human responses: A multivariate data-adaptive framework," in Bulletin of Polish Academy of Science and Technology, vol. 60, p. 433, 2012. The resulting entropy measures are good candidates for the analysis of bivariate postural sway signals exhibiting nonstationarity and multiscale properties. These methods are dependant on several input parameters such as embedding parameters. Using two data sets collected from institutionalized frail older adults, we numerically investigate the behavior of a recent multivariate and multiscale entropy estimator; see "Multivariate multiscale entropy: A tool for complexity analysis of multichannel data," Physics Review E, vol. 84, p. 061918, 2011. We propose criteria for the selection of the input parameters. Using these optimal parameters, we statistically compare the multivariate and multiscale entropy values of postural sway data of non-faller subjects to those of fallers. These two groups are discriminated by the resulting measures over multiple time scales. We also demonstrate that the typical parameter settings proposed in the literature lead to entropy measures that do not distinguish the two groups. This last result confirms the importance of the selection of appropriate input parameters.

A tutorial on the use of Excel 2010 and Excel for Mac 2011 for conducting delay-discounting analyses.

PubMed

Reed, Derek D; Kaplan, Brent A; Brewer, Adam T

2012-01-01

In recent years, researchers and practitioners in the behavioral sciences have profited from a growing literature on delay discounting. The purpose of this article is to provide readers with a brief tutorial on how to use Microsoft Office Excel 2010 and Excel for Mac 2011 to analyze discounting data to yield parameters for both the hyperbolic discounting model and area under the curve. This tutorial is intended to encourage the quantitative analysis of behavior in both research and applied settings by readers with relatively little formal training in nonlinear regression.

A TUTORIAL ON THE USE OF EXCEL 2010 AND EXCEL FOR MAC 2011 FOR CONDUCTING DELAY-DISCOUNTING ANALYSES

PubMed Central

Reed, Derek D; Kaplan, Brent A; Brewer, Adam T

2012-01-01

In recent years, researchers and practitioners in the behavioral sciences have profited from a growing literature on delay discounting. The purpose of this article is to provide readers with a brief tutorial on how to use Microsoft Office Excel 2010 and Excel for Mac 2011 to analyze discounting data to yield parameters for both the hyperbolic discounting model and area under the curve. This tutorial is intended to encourage the quantitative analysis of behavior in both research and applied settings by readers with relatively little formal training in nonlinear regression. PMID:22844143

Electronic properties of long DNA nanowires in dry and wet conditions

NASA Astrophysics Data System (ADS)

Mousavi, Hamze; Khodadadi, Jabbar; Grabowski, Marek

2015-11-01

The electronic behavior of the long disordered DNA nanowires in both dry and wet conditions is investigated through the band structure and density of states of a tight-binding Hamiltonian model for π-electrons of the backbone, using Green's functions approach. For a chosen set of parameters in the dry case, semiconducting behavior is reproduced. It is also shown that for sufficiently long strands, the order of the base pairs has no noticeable effect on the energy band-gap. Moreover, this semiconducting duplex shows metallic tendencies when interacting with the environment of polar molecules.

An accelerated test design for use with synchronous orbit. [on Ni-Cd cell degradation behavior

NASA Technical Reports Server (NTRS)

Mcdermott, P. P.; Vasanth, K. L.

1980-01-01

The Naval Weapons Support Center at Crane, Indiana has conducted a large scale accelerated test of 6.0 Ah Ni-Cd cells. Data from the Crane test have been used to develop an equation for the description of Ni-Cd cell behavior in geosynchronous orbit. This equation relates the anticipated time to failure for a cell in synchronous orbit to temperature and overcharge rate sustained by the cell during the light period. A test design is suggested which uses this equation for setting test parameters for future accelerated testing.

Multiple concurrent recursive least squares identification with application to on-line spacecraft mass-property identification

NASA Technical Reports Server (NTRS)

Wilson, Edward (Inventor)

2006-01-01

The present invention is a method for identifying unknown parameters in a system having a set of governing equations describing its behavior that cannot be put into regression form with the unknown parameters linearly represented. In this method, the vector of unknown parameters is segmented into a plurality of groups where each individual group of unknown parameters may be isolated linearly by manipulation of said equations. Multiple concurrent and independent recursive least squares identification of each said group run, treating other unknown parameters appearing in their regression equation as if they were known perfectly, with said values provided by recursive least squares estimation from the other groups, thereby enabling the use of fast, compact, efficient linear algorithms to solve problems that would otherwise require nonlinear solution approaches. This invention is presented with application to identification of mass and thruster properties for a thruster-controlled spacecraft.

A comparison of Stokes parameters for sky and a soybean canopy

NASA Technical Reports Server (NTRS)

Schutt, John B.; Holben, Brent N.; Mcmurtrey, James E., III

1991-01-01

An evaluation of the polarization signatures obtained from the four Stokes parameters is reported for the atmosphere and a soybean canopy. The polarimeter design and operation are set forth, and the Stokes parameters' relationships are discussed. The canopy polarization was different from the sky at azimuths of 90 and 270 degrees, demonstrating a response that reflecting the sky polarization signatures across a plane parallel to the polarization axis and passing through a phase angle of about 90 degrees would produce. Classical behavior in terms of electromagnetic theory was found in the fourth Stokes parameter of the canopy which was obtained in the principal plane. Only the third Stokes parameter is demonstrated to be unambiguously affected in a comparison of sky polarization signatures and aerosol optical densities. The similarity between the sky at azimuth 180 degrees and the soybean canopy data at the principal plane is interesting considering the disparity of the subjects.

Behavioral Health and Performance Laboratory Standard Measures (BHP-SM)

NASA Technical Reports Server (NTRS)

Williams, Thomas J.; Cromwell, Ronita

2017-01-01

The Spaceflight Standard Measures is a NASA Johnson Space Center Human Research Project (HRP) project that proposes to collect a set of core measurements, representative of many of the human spaceflight risks, from astronauts before, during and after long-duration International Space Station (ISS) missions. The term "standard measures" is defined as a set of core measurements, including physiological, biochemical, psychosocial, cognitive, and functional, that are reliable, valid, and accepted in terrestrial science, are associated with a specific and measurable outcome known to occur as a consequence of spaceflight, that will be collected in a standardized fashion from all (or most) crewmembers. While such measures might be used to define standards of health and performance or readiness for flight, the prime intent in their collection is to allow longitudinal analysis of multiple parameters in order to answer a variety of operational, occupational, and research-based questions. These questions are generally at a high level, and the approach for this project is to populate the standard measures database with the smallest set of data necessary to indicate further detailed research is required. Also included as standard measures are parameters that are not outcome-based in and of-themselves, but provide ancillary information that supports interpretation of the outcome measures, e.g., nutritional assessment, vehicle environmental parameters, crew debriefs, etc. The project's main aim is to ensure that an optimized minimal set of measures is consistently captured from all ISS crewmembers until the end of Station in order to characterize the human in space. -This allows the HRP to identify, establish, and evaluate a common set of measures for use in spaceflight and analog research to: develop baselines, systematically characterize risk likelihood and consequences, and assess effectiveness of countermeasures that work for behavioral health and performance risk factors. -By standardizing the battery of measures on all crewmembers, it will allow the HRP to evaluate countermeasures that work for one physiological system and ensure another system is not negatively affected. -These measures, named "Standard Measures," will serve as a data repository and be available to other studies under data sharing agreements.

A quasi-crisis

NASA Astrophysics Data System (ADS)

Wang, Ying-Mei; Wang, Wen-Xiu; Chen, He-Sheng; Zhang, Kai; Jiang, Yu-Mei; Wang, Xu-Ming; He, Da-Ren

2002-03-01

A system concatenated by two area-preserving maps may be addressed as "quasi- dissipative," since such a system can display dissipative behaviors^1. This is due to noninvertibility induced by discontinuity in the system function. In such a system, the image set of the discontinuous border forms a chaotic quasi-attractor. At a critical control parameter value the quasi-attractor suddenly vanishes. The chaotic iterations escape, via a leaking hole, to an emergent period-8 elliptic island. The hole is the intersection of the chaotic quasi-attractor and the period-8 island. The chaotic quasi-attractor thus changes to chaotic quasi-transients. The scaling behavior that drives the quasi-crisis has been investigated numerically. It reads: ∝ (p-p_c)^-ν , where is defined as the averaged length of quasi-transients. The scaling exponent ν=1.66 ± 0.04. The critical parameter value equals p_c=-1.0069799. ^1 J. Wang et al., Phys.Rev.E, 64(2001)026202.

Variational prediction of the mechanical behavior of shape memory alloys based on thermal experiments

NASA Astrophysics Data System (ADS)

Junker, Philipp; Jaeger, Stefanie; Kastner, Oliver; Eggeler, Gunther; Hackl, Klaus

2015-07-01

In this work, we present simulations of shape memory alloys which serve as first examples demonstrating the predicting character of energy-based material models. We begin with a theoretical approach for the derivation of the caloric parts of the Helmholtz free energy. Afterwards, experimental results for DSC measurements are presented. Then, we recall a micromechanical model based on the principle of the minimum of the dissipation potential for the simulation of polycrystalline shape memory alloys. The previously determined caloric parts of the Helmholtz free energy close the set of model parameters without the need of parameter fitting. All quantities are derived directly from experiments. Finally, we compare finite element results for tension tests to experimental data and show that the model identified by thermal measurements can predict mechanically induced phase transformations and thus rationalize global material behavior without any further assumptions.

Impulsive Choice and Workplace Safety: A New Area of Inquiry for Research in Occupational Settings

ERIC Educational Resources Information Center

Reynolds, Brady; Schiffbauer, Ryan M.

2004-01-01

A conceptual argument is presented for the relevance of behavior-analytic research on impulsive choice to issues of occupational safety and health. Impulsive choice is defined in terms of discounting, which is the tendency for the value of a commodity to decrease as a function of various parameters (e.g., having to wait or expend energy to receive…

Design Change Model for Effective Scheduling Change Propagation Paths

NASA Astrophysics Data System (ADS)

Zhang, Hai-Zhu; Ding, Guo-Fu; Li, Rong; Qin, Sheng-Feng; Yan, Kai-Yin

2017-09-01

Changes in requirements may result in the increasing of product development project cost and lead time, therefore, it is important to understand how requirement changes propagate in the design of complex product systems and be able to select best options to guide design. Currently, a most approach for design change is lack of take the multi-disciplinary coupling relationships and the number of parameters into account integrally. A new design change model is presented to systematically analyze and search change propagation paths. Firstly, a PDS-Behavior-Structure-based design change model is established to describe requirement changes causing the design change propagation in behavior and structure domains. Secondly, a multi-disciplinary oriented behavior matrix is utilized to support change propagation analysis of complex product systems, and the interaction relationships of the matrix elements are used to obtain an initial set of change paths. Finally, a rough set-based propagation space reducing tool is developed to assist in narrowing change propagation paths by computing the importance of the design change parameters. The proposed new design change model and its associated tools have been demonstrated by the scheduling change propagation paths of high speed train's bogie to show its feasibility and effectiveness. This model is not only supportive to response quickly to diversified market requirements, but also helpful to satisfy customer requirements and reduce product development lead time. The proposed new design change model can be applied in a wide range of engineering systems design with improved efficiency.

Signal Processing in Periodically Forced Gradient Frequency Neural Networks

PubMed Central

Kim, Ji Chul; Large, Edward W.

2015-01-01

Oscillatory instability at the Hopf bifurcation is a dynamical phenomenon that has been suggested to characterize active non-linear processes observed in the auditory system. Networks of oscillators poised near Hopf bifurcation points and tuned to tonotopically distributed frequencies have been used as models of auditory processing at various levels, but systematic investigation of the dynamical properties of such oscillatory networks is still lacking. Here we provide a dynamical systems analysis of a canonical model for gradient frequency neural networks driven by a periodic signal. We use linear stability analysis to identify various driven behaviors of canonical oscillators for all possible ranges of model and forcing parameters. The analysis shows that canonical oscillators exhibit qualitatively different sets of driven states and transitions for different regimes of model parameters. We classify the parameter regimes into four main categories based on their distinct signal processing capabilities. This analysis will lead to deeper understanding of the diverse behaviors of neural systems under periodic forcing and can inform the design of oscillatory network models of auditory signal processing. PMID:26733858

Development and Validation of the Behavioral Tendencies Questionnaire

PubMed Central

Van Dam, Nicholas T.; Brown, Anna; Mole, Tom B.; Davis, Jake H.; Britton, Willoughby B.; Brewer, Judson A.

2015-01-01

At a fundamental level, taxonomy of behavior and behavioral tendencies can be described in terms of approach, avoid, or equivocate (i.e., neither approach nor avoid). While there are numerous theories of personality, temperament, and character, few seem to take advantage of parsimonious taxonomy. The present study sought to implement this taxonomy by creating a questionnaire based on a categorization of behavioral temperaments/tendencies first identified in Buddhist accounts over fifteen hundred years ago. Items were developed using historical and contemporary texts of the behavioral temperaments, described as “Greedy/Faithful”, “Aversive/Discerning”, and “Deluded/Speculative”. To both maintain this categorical typology and benefit from the advantageous properties of forced-choice response format (e.g., reduction of response biases), binary pairwise preferences for items were modeled using Latent Class Analysis (LCA). One sample (n1 = 394) was used to estimate the item parameters, and the second sample (n2 = 504) was used to classify the participants using the established parameters and cross-validate the classification against multiple other measures. The cross-validated measure exhibited good nomothetic span (construct-consistent relationships with related measures) that seemed to corroborate the ideas present in the original Buddhist source documents. The final 13-block questionnaire created from the best performing items (the Behavioral Tendencies Questionnaire or BTQ) is a psychometrically valid questionnaire that is historically consistent, based in behavioral tendencies, and promises practical and clinical utility particularly in settings that teach and study meditation practices such as Mindfulness Based Stress Reduction (MBSR). PMID:26535904

Development and Validation of the Behavioral Tendencies Questionnaire.

PubMed

Van Dam, Nicholas T; Brown, Anna; Mole, Tom B; Davis, Jake H; Britton, Willoughby B; Brewer, Judson A

2015-01-01

At a fundamental level, taxonomy of behavior and behavioral tendencies can be described in terms of approach, avoid, or equivocate (i.e., neither approach nor avoid). While there are numerous theories of personality, temperament, and character, few seem to take advantage of parsimonious taxonomy. The present study sought to implement this taxonomy by creating a questionnaire based on a categorization of behavioral temperaments/tendencies first identified in Buddhist accounts over fifteen hundred years ago. Items were developed using historical and contemporary texts of the behavioral temperaments, described as "Greedy/Faithful", "Aversive/Discerning", and "Deluded/Speculative". To both maintain this categorical typology and benefit from the advantageous properties of forced-choice response format (e.g., reduction of response biases), binary pairwise preferences for items were modeled using Latent Class Analysis (LCA). One sample (n1 = 394) was used to estimate the item parameters, and the second sample (n2 = 504) was used to classify the participants using the established parameters and cross-validate the classification against multiple other measures. The cross-validated measure exhibited good nomothetic span (construct-consistent relationships with related measures) that seemed to corroborate the ideas present in the original Buddhist source documents. The final 13-block questionnaire created from the best performing items (the Behavioral Tendencies Questionnaire or BTQ) is a psychometrically valid questionnaire that is historically consistent, based in behavioral tendencies, and promises practical and clinical utility particularly in settings that teach and study meditation practices such as Mindfulness Based Stress Reduction (MBSR).

Changes in the transmission properties of multi-tooth plasmonic nano-filters (multi-TPNFs) caused by geometrical imperfection

NASA Astrophysics Data System (ADS)

Khaksar, A.; Fatemi, H.

2012-08-01

To model the filtering behavior of a multi-tooth plasmonic nano-filter (multi-TPNF), an equivalent circuitry composed of a set of serried impedances is considered. The changes caused in its filtering behavior are proposed as a measuring tool to investigate the effect of the geometrical imperfections occurring during the manufacture of the device. Consequently, the effects of changes in the nominal size of each of the geometrical parameters of a multi-TPNF sample, such as its tooth height, d, its tooth width, w, and the separation between two successive teeth, Δ, on its transmittance are investigated. It is observed that each single tooth of the multi-TPNF and also the waveguide between any of its two successive teeth exhibit a very Fabry-Perot interferometer like behavior. The variation of the transmission spectra of a multi-TPNF whose geometrical parameters are imperfect is compared with the desired filter, and also the effect of the number of geometrically imperfect teeth of the multi-TPNF on the filtering spectra is examined.

Differential effects of intranasal oxytocin on sexual experiences and partner interactions in couples.

PubMed

Behnia, Behnoush; Heinrichs, Markus; Bergmann, Wiebke; Jung, Stefanie; Germann, Janine; Schedlowski, Manfred; Hartmann, Uwe; Kruger, Tillmann H C

2014-03-01

Knowledge about the effects of the neuropeptide oxytocin (OXT) on human sexual behaviors and partner interactions remains limited. Based on our previous studies, we hypothesize that OXT should be able to positively influence parameters of sexual function and couple interactions. Employing a naturalistic setting involving 29 healthy heterosexual couples (n=58 participants), we analyzed the acute effects of intranasally administered OXT (24IU) on sexual drive, arousal, orgasm and refractory aspects of sexual behavior together with partner interactions. Data were assessed by psychometric instruments (Acute Sexual Experiences Scale, Arizona Sexual Experience Scale) as well as biomarkers, such as cortisol, α-amylase and heart rate. Intranasal OXT administration did not alter "classical" parameters of sexual function, such as sexual drive, arousal or penile erection and lubrication. However, analysis of variance and a hierarchical linear model (HLM) revealed specific effects related to the orgasmic/post-orgasmic interval as well as parameters of partner interactions. According to HLM analysis, OXT increased the intensity of orgasm, contentment after sexual intercourse and the effect of study participation. According to ANOVA analysis, these effects were more pronounced in men. Men additionally indicated higher levels of sexual satiety after sexual intercourse with OXT administration. Women felt more relaxed and subgroups indicated better abilities to share sexual desires or to empathize with their partners. The effect sizes were small to moderate. Biomarkers indicated moderate psychophysiological activation but were not affected by OXT, gender or method of contraception. Using a naturalistic setting, intranasal OXT administration in couples exerted differential effects on parameters of sexual function and partner interactions. These results warrant further investigations, including subjects with sexual and relationship problems. Copyright © 2014 Elsevier Inc. All rights reserved.

Validation of a mathematical model of the bovine estrous cycle for cows with different estrous cycle characteristics.

PubMed

Boer, H M T; Butler, S T; Stötzel, C; Te Pas, M F W; Veerkamp, R F; Woelders, H

2017-11-01

A recently developed mechanistic mathematical model of the bovine estrous cycle was parameterized to fit empirical data sets collected during one estrous cycle of 31 individual cows, with the main objective to further validate the model. The a priori criteria for validation were (1) the resulting model can simulate the measured data correctly (i.e. goodness of fit), and (2) this is achieved without needing extreme, probably non-physiological parameter values. We used a least squares optimization procedure to identify parameter configurations for the mathematical model to fit the empirical in vivo measurements of follicle and corpus luteum sizes, and the plasma concentrations of progesterone, estradiol, FSH and LH for each cow. The model was capable of accommodating normal variation in estrous cycle characteristics of individual cows. With the parameter sets estimated for the individual cows, the model behavior changed for 21 cows, with improved fit of the simulated output curves for 18 of these 21 cows. Moreover, the number of follicular waves was predicted correctly for 18 of the 25 two-wave and three-wave cows, without extreme parameter value changes. Estimation of specific parameters confirmed results of previous model simulations indicating that parameters involved in luteolytic signaling are very important for regulation of general estrous cycle characteristics, and are likely responsible for differences in estrous cycle characteristics between cows.

Basic research on design analysis methods for rotorcraft vibrations

NASA Technical Reports Server (NTRS)

Hanagud, S.

1991-01-01

The objective of the present work was to develop a method for identifying physically plausible finite element system models of airframe structures from test data. The assumed models were based on linear elastic behavior with general (nonproportional) damping. Physical plausibility of the identified system matrices was insured by restricting the identification process to designated physical parameters only and not simply to the elements of the system matrices themselves. For example, in a large finite element model the identified parameters might be restricted to the moduli for each of the different materials used in the structure. In the case of damping, a restricted set of damping values might be assigned to finite elements based on the material type and on the fabrication processes used. In this case, different damping values might be associated with riveted, bolted and bonded elements. The method itself is developed first, and several approaches are outlined for computing the identified parameter values. The method is applied first to a simple structure for which the 'measured' response is actually synthesized from an assumed model. Both stiffness and damping parameter values are accurately identified. The true test, however, is the application to a full-scale airframe structure. In this case, a NASTRAN model and actual measured modal parameters formed the basis for the identification of a restricted set of physically plausible stiffness and damping parameters.

Molecular dynamics simulation of premelting and melting phase transitions in stoichiometric uranium dioxide

NASA Astrophysics Data System (ADS)

Yakub, Eugene; Ronchi, Claudio; Staicu, Dragos

2007-09-01

Results of molecular dynamics (MD) simulation of UO2 in a wide temperature range are presented and discussed. A new approach to the calibration of a partly ionic Busing-Ida-type model is proposed. A potential parameter set is obtained reproducing the experimental density of solid UO2 in a wide range of temperatures. A conventional simulation of the high-temperature stoichiometric UO2 on large MD cells, based on a novel fast method of computation of Coulomb forces, reveals characteristic features of a premelting λ transition at a temperature near to that experimentally observed (Tλ=2670K ). A strong deviation from the Arrhenius behavior of the oxygen self-diffusion coefficient was found in the vicinity of the transition point. Predictions for liquid UO2, based on the same potential parameter set, are in good agreement with existing experimental data and theoretical calculations.

An optimization based sampling approach for multiple metrics uncertainty analysis using generalized likelihood uncertainty estimation

NASA Astrophysics Data System (ADS)

Zhou, Rurui; Li, Yu; Lu, Di; Liu, Haixing; Zhou, Huicheng

2016-09-01

This paper investigates the use of an epsilon-dominance non-dominated sorted genetic algorithm II (ɛ-NSGAII) as a sampling approach with an aim to improving sampling efficiency for multiple metrics uncertainty analysis using Generalized Likelihood Uncertainty Estimation (GLUE). The effectiveness of ɛ-NSGAII based sampling is demonstrated compared with Latin hypercube sampling (LHS) through analyzing sampling efficiency, multiple metrics performance, parameter uncertainty and flood forecasting uncertainty with a case study of flood forecasting uncertainty evaluation based on Xinanjiang model (XAJ) for Qing River reservoir, China. Results obtained demonstrate the following advantages of the ɛ-NSGAII based sampling approach in comparison to LHS: (1) The former performs more effective and efficient than LHS, for example the simulation time required to generate 1000 behavioral parameter sets is shorter by 9 times; (2) The Pareto tradeoffs between metrics are demonstrated clearly with the solutions from ɛ-NSGAII based sampling, also their Pareto optimal values are better than those of LHS, which means better forecasting accuracy of ɛ-NSGAII parameter sets; (3) The parameter posterior distributions from ɛ-NSGAII based sampling are concentrated in the appropriate ranges rather than uniform, which accords with their physical significance, also parameter uncertainties are reduced significantly; (4) The forecasted floods are close to the observations as evaluated by three measures: the normalized total flow outside the uncertainty intervals (FOUI), average relative band-width (RB) and average deviation amplitude (D). The flood forecasting uncertainty is also reduced a lot with ɛ-NSGAII based sampling. This study provides a new sampling approach to improve multiple metrics uncertainty analysis under the framework of GLUE, and could be used to reveal the underlying mechanisms of parameter sets under multiple conflicting metrics in the uncertainty analysis process.

Friction spinning - Twist phenomena and the capability of influencing them

NASA Astrophysics Data System (ADS)

Lossen, Benjamin; Homberg, Werner

2016-10-01

The friction spinning process can be allocated to the incremental forming techniques. The process consists of process elements from both metal spinning and friction welding. The selective combination of process elements from these two processes results in the integration of friction sub-processes in a spinning process. This implies self-induced heat generation with the possibility of manufacturing functionally graded parts from tube and sheets. Compared with conventional spinning processes, this in-process heat treatment permits the extension of existing forming limits and also the production of more complex geometries. Furthermore, the defined adjustment of part properties like strength, grain size/orientation and surface conditions can be achieved through the appropriate process parameter settings and consequently by setting a specific temperature profile in combination with the degree of deformation. The results presented from tube forming start with an investigation into the resulting twist phenomena in flange processing. In this way, the influence of the main parameters, such as rotation speed, feed rate, forming paths and tool friction surface, and their effects on temperature, forces and finally the twist behavior are analyzed. Following this, the significant correlations with the parameters and a new process strategy are set out in order to visualize the possibility of achieving a defined grain texture orientation.

Estimating kinetic mechanisms with prior knowledge I: Linear parameter constraints.

PubMed

Salari, Autoosa; Navarro, Marco A; Milescu, Mirela; Milescu, Lorin S

2018-02-05

To understand how ion channels and other proteins function at the molecular and cellular levels, one must decrypt their kinetic mechanisms. Sophisticated algorithms have been developed that can be used to extract kinetic parameters from a variety of experimental data types. However, formulating models that not only explain new data, but are also consistent with existing knowledge, remains a challenge. Here, we present a two-part study describing a mathematical and computational formalism that can be used to enforce prior knowledge into the model using constraints. In this first part, we focus on constraints that enforce explicit linear relationships involving rate constants or other model parameters. We develop a simple, linear algebra-based transformation that can be applied to enforce many types of model properties and assumptions, such as microscopic reversibility, allosteric gating, and equality and inequality parameter relationships. This transformation converts the set of linearly interdependent model parameters into a reduced set of independent parameters, which can be passed to an automated search engine for model optimization. In the companion article, we introduce a complementary method that can be used to enforce arbitrary parameter relationships and any constraints that quantify the behavior of the model under certain conditions. The procedures described in this study can, in principle, be coupled to any of the existing methods for solving molecular kinetics for ion channels or other proteins. These concepts can be used not only to enforce existing knowledge but also to formulate and test new hypotheses. © 2018 Salari et al.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bernal, José Luis; Cuesta, Antonio J.; Verde, Licia, E-mail: joseluis.bernal@icc.ub.edu, E-mail: liciaverde@icc.ub.edu, E-mail: ajcuesta@icc.ub.edu

We perform an empirical consistency test of General Relativity/dark energy by disentangling expansion history and growth of structure constraints. We replace each late-universe parameter that describes the behavior of dark energy with two meta-parameters: one describing geometrical information in cosmological probes, and the other controlling the growth of structure. If the underlying model (a standard wCDM cosmology with General Relativity) is correct, that is under the null hypothesis, the two meta-parameters coincide. If they do not, it could indicate a failure of the model or systematics in the data. We present a global analysis using state-of-the-art cosmological data sets whichmore » points in the direction that cosmic structures prefer a weaker growth than that inferred by background probes. This result could signify inconsistencies of the model, the necessity of extensions to it or the presence of systematic errors in the data. We examine all these possibilities. The fact that the result is mostly driven by a specific sub-set of galaxy clusters abundance data, points to the need of a better understanding of this probe.« less

Optimal HRF and smoothing parameters for fMRI time series within an autoregressive modeling framework.

PubMed

Galka, Andreas; Siniatchkin, Michael; Stephani, Ulrich; Groening, Kristina; Wolff, Stephan; Bosch-Bayard, Jorge; Ozaki, Tohru

2010-12-01

The analysis of time series obtained by functional magnetic resonance imaging (fMRI) may be approached by fitting predictive parametric models, such as nearest-neighbor autoregressive models with exogeneous input (NNARX). As a part of the modeling procedure, it is possible to apply instantaneous linear transformations to the data. Spatial smoothing, a common preprocessing step, may be interpreted as such a transformation. The autoregressive parameters may be constrained, such that they provide a response behavior that corresponds to the canonical haemodynamic response function (HRF). We present an algorithm for estimating the parameters of the linear transformations and of the HRF within a rigorous maximum-likelihood framework. Using this approach, an optimal amount of both the spatial smoothing and the HRF can be estimated simultaneously for a given fMRI data set. An example from a motor-task experiment is discussed. It is found that, for this data set, weak, but non-zero, spatial smoothing is optimal. Furthermore, it is demonstrated that activated regions can be estimated within the maximum-likelihood framework.

Understanding proenvironmental intentions and behaviors: The importance of considering both the behavior setting and the type of behavior.

PubMed

Maki, Alexander; Rothman, Alexander J

2017-01-01

To better understand the consistency of people's proenvironmental intentions and behaviors, we set out to examine two sets of research questions. First, do people perform (1) different types of proenvironmental behaviors consistently, and (2) the same proenvironmental behavior consistently across settings? Second, are there consistent predictors of proenvironmental behavioral intentions across behavior and setting type? Participants reported four recycling and conservation behaviors across three settings, revealing significant variability in rates of behaviors across settings. Prior behavior, attitudes toward the behavior, and importance of the behaviour consistently predicted proenvironmental intentions. However, perceived behavioral control tended to predict intentions to perform proenvironmental behavior outside the home. Future research aimed at understanding and influencing different proenvironmental behaviors should carefully consider how settings affect intentions and behavior.

Non-line-of-sight ultraviolet link loss in noncoplanar geometry.

PubMed

Wang, Leijie; Xu, Zhengyuan; Sadler, Brian M

2010-04-15

Various path loss models have been developed for solar blind non-line-of-sight UV communication links under an assumption of coplanar source beam axis and receiver pointing direction. This work further extends an existing single-scattering coplanar analytical model to noncoplanar geometry. The model is derived as a function of geometric parameters and atmospheric characteristics. Its behavior is numerically studied in different noncoplanar geometric settings.

Simulating Scenario Floods for Hazard Assessment on the Lower Bicol Floodplain, the Philippines

NASA Astrophysics Data System (ADS)

Usamah, Muhibuddin Bin; Alkema, Dinand

This paper describes the first results from a study to the behavior of floods in the lower Bicol area, the Philippines. A 1D2D dynamic hydraulic model was applied to simulate a set of scenario floods through the complex topography of the city Naga and surrounding area. The simulation results are integrated into a multi-parameter hazard zonation for the five scenario floods.

Efficient calculation of general Voigt profiles

NASA Astrophysics Data System (ADS)

Cope, D.; Khoury, R.; Lovett, R. J.

1988-02-01

An accurate and efficient program is presented for the computation of OIL profiles, generalizations of the Voigt profile resulting from the one-interacting-level model of Ward et al. (1974). These profiles have speed dependent shift and width functions and have asymmetric shapes. The program contains an adjustable error control parameter and includes the Voigt profile as a special case, although the general nature of this program renders it slower than a specialized Voigt profile method. Results on accuracy and computation time are presented for a broad set of test parameters, and a comparison is made with previous work on the asymptotic behavior of general Voigt profiles.

Simulation of financial market via nonlinear Ising model

NASA Astrophysics Data System (ADS)

Ko, Bonggyun; Song, Jae Wook; Chang, Woojin

2016-09-01

In this research, we propose a practical method for simulating the financial return series whose distribution has a specific heaviness. We employ the Ising model for generating financial return series to be analogous to those of the real series. The similarity between real financial return series and simulated one is statistically verified based on their stylized facts including the power law behavior of tail distribution. We also suggest the scheme for setting the parameters in order to simulate the financial return series with specific tail behavior. The simulation method introduced in this paper is expected to be applied to the other financial products whose price return distribution is fat-tailed.

Attractor learning in synchronized chaotic systems in the presence of unresolved scales

NASA Astrophysics Data System (ADS)

Wiegerinck, W.; Selten, F. M.

2017-12-01

Recently, supermodels consisting of an ensemble of interacting models, synchronizing on a common solution, have been proposed as an alternative to the common non-interactive multi-model ensembles in order to improve climate predictions. The connection terms in the interacting ensemble are to be optimized based on the data. The supermodel approach has been successfully demonstrated in a number of simulation experiments with an assumed ground truth and a set of good, but imperfect models. The supermodels were optimized with respect to their short-term prediction error. Nevertheless, they produced long-term climatological behavior that was close to the long-term behavior of the assumed ground truth, even in cases where the long-term behavior of the imperfect models was very different. In these supermodel experiments, however, a perfect model class scenario was assumed, in which the ground truth and imperfect models belong to the same model class and only differ in parameter setting. In this paper, we consider the imperfect model class scenario, in which the ground truth model class is more complex than the model class of imperfect models due to unresolved scales. We perform two supermodel experiments in two toy problems. The first one consists of a chaotically driven Lorenz 63 oscillator ground truth and two Lorenz 63 oscillators with constant forcings as imperfect models. The second one is more realistic and consists of a global atmosphere model as ground truth and imperfect models that have perturbed parameters and reduced spatial resolution. In both problems, we find that supermodel optimization with respect to short-term prediction error can lead to a long-term climatological behavior that is worse than that of the imperfect models. However, we also show that attractor learning can remedy this problem, leading to supermodels with long-term behavior superior to the imperfect models.

Effects of digital altimetry on pilot workload

NASA Technical Reports Server (NTRS)

Harris, R. L., Sr.; Glover, B. J.

1985-01-01

A series of VOR-DME instrument landing approaches was flown in the DC-9 full-workload simulator to compare pilot performance, scan behavior, and workload when using a computer-drum-pointer altimeter (CDPA) and a digital altimeter (DA). Six pilots executed two sets of instrument landing approaches, with a CDPA on one set and a DA on the other set. Pilot scanning parameters, flight performance, and subjective opinion data were evaluated. It is found that the processes of gathering information from the CDPA and the DA are different. The DA requires a higher mental workload than the CDPA for a VOR-DME type landing approach. Mental processing of altitude information after transitioning back to the attitude indicator is more evident with the DA than with the CDPA.

Selection of experimental modal data sets for damage detection via model update

NASA Technical Reports Server (NTRS)

Doebling, S. W.; Hemez, F. M.; Barlow, M. S.; Peterson, L. D.; Farhat, C.

1993-01-01

When using a finite element model update algorithm for detecting damage in structures, it is important that the experimental modal data sets used in the update be selected in a coherent manner. In the case of a structure with extremely localized modal behavior, it is necessary to use both low and high frequency modes, but many of the modes in between may be excluded. In this paper, we examine two different mode selection strategies based on modal strain energy, and compare their success to the choice of an equal number of modes based merely on lowest frequency. Additionally, some parameters are introduced to enable a quantitative assessment of the success of our damage detection algorithm when using the various set selection criteria.

A Comparison of different learning models used in Data Mining for Medical Data

NASA Astrophysics Data System (ADS)

Srimani, P. K.; Koti, Manjula Sanjay

2011-12-01

The present study aims at investigating the different Data mining learning models for different medical data sets and to give practical guidelines to select the most appropriate algorithm for a specific medical data set. In practical situations, it is absolutely necessary to take decisions with regard to the appropriate models and parameters for diagnosis and prediction problems. Learning models and algorithms are widely implemented for rule extraction and the prediction of system behavior. In this paper, some of the well-known Machine Learning(ML) systems are investigated for different methods and are tested on five medical data sets. The practical criteria for evaluating different learning models are presented and the potential benefits of the proposed methodology for diagnosis and learning are suggested.

Fracture mechanics validity limits

NASA Technical Reports Server (NTRS)

Lambert, Dennis M.; Ernst, Hugo A.

1994-01-01

Fracture behavior is characteristics of a dramatic loss of strength compared to elastic deformation behavior. Fracture parameters have been developed and exhibit a range within which each is valid for predicting growth. Each is limited by the assumptions made in its development: all are defined within a specific context. For example, the stress intensity parameters, K, and the crack driving force, G, are derived using an assumption of linear elasticity. To use K or G, the zone of plasticity must be small as compared to the physical dimensions of the object being loaded. This insures an elastic response, and in this context, K and G will work well. Rice's J-integral has been used beyond the limits imposed on K and G. J requires an assumption of nonlinear elasticity, which is not characteristic of real material behavior, but is thought to be a reasonable approximation if unloading is kept to a minimum. As well, the constraint cannot change dramatically (typically, the crack extension is limited to ten-percent of the initial remaining ligament length). Rice, et al investigated the properties required of J-type parameters, J(sub x), and showed that the time rate, dJ(sub x)/dt, must not be a function of the crack extension rate, da/dt. Ernst devised the modified-J parameter, J(sub M), that meets this criterion. J(sub M) correlates fracture data to much higher crack growth than does J. Ultimately, a limit of the validity of J(sub M) is anticipated, and this has been estimated to be at a crack extension of about 40-percent of the initial remaining ligament length. None of the various parameters can be expected to describe fracture in an environment of gross plasticity, in which case the process is better described by deformation parameters, e.g., stress and strain. In the current study, various schemes to identify the onset of the plasticity-dominated behavior, i.e., the end of fracture mechanics validity, are presented. Each validity limit parameter is developed in detail, and then data is presented and the various schemes for establishing a limit of the validity are compared. The selected limiting parameter is applied to a set of fracture data showing the improvement of correlation gained.

BWR station blackout: A RISMC analysis using RAVEN and RELAP5-3D

DOE PAGES

Mandelli, D.; Smith, C.; Riley, T.; ...

2016-01-01

The existing fleet of nuclear power plants is in the process of extending its lifetime and increasing the power generated from these plants via power uprates and improved operations. In order to evaluate the impact of these factors on the safety of the plant, the Risk-Informed Safety Margin Characterization (RISMC) project aims to provide insights to decision makers through a series of simulations of the plant dynamics for different initial conditions and accident scenarios. This paper presents a case study in order to show the capabilities of the RISMC methodology to assess impact of power uprate of a Boiling Watermore » Reactor system during a Station Black-Out accident scenario. We employ a system simulator code, RELAP5-3D, coupled with RAVEN which perform the stochastic analysis. Furthermore, our analysis is performed by: 1) sampling values from a set of parameters from the uncertainty space of interest, 2) simulating the system behavior for that specific set of parameter values and 3) analyzing the outcomes from the set of simulation runs.« less

A Generalized 2D-Dynamical Mean-Field Ising Model with a Rich Set of Bifurcations (Inspired and Applied to Financial Crises)

NASA Astrophysics Data System (ADS)

Smug, Damian; Sornette, Didier; Ashwin, Peter

We analyze an extended version of the dynamical mean-field Ising model. Instead of classical physical representation of spins and external magnetic field, the model describes traders' opinion dynamics. The external field is endogenized to represent a smoothed moving average of the past state variable. This model captures in a simple set-up the interplay between instantaneous social imitation and past trends in social coordinations. We show the existence of a rich set of bifurcations as a function of the two parameters quantifying the relative importance of instantaneous versus past social opinions on the formation of the next value of the state variable. Moreover, we present a thorough analysis of chaotic behavior, which is exhibited in certain parameter regimes. Finally, we examine several transitions through bifurcation curves and study how they could be understood as specific market scenarios. We find that the amplitude of the corrections needed to recover from a crisis and to push the system back to “normal” is often significantly larger than the strength of the causes that led to the crisis itself.

Estimation and Control for Autonomous Coring from a Rover Manipulator

NASA Technical Reports Server (NTRS)

Hudson, Nicolas; Backes, Paul; DiCicco, Matt; Bajracharya, Max

2010-01-01

A system consisting of a set of estimators and autonomous behaviors has been developed which allows robust coring from a low-mass rover platform, while accommodating for moderate rover slip. A redundant set of sensors, including a force-torque sensor, visual odometry, and accelerometers are used to monitor discrete critical and operational modes, as well as to estimate continuous drill parameters during the coring process. A set of critical failure modes pertinent to shallow coring from a mobile platform is defined, and autonomous behaviors associated with each critical mode are used to maintain nominal coring conditions. Autonomous shallow coring is demonstrated from a low-mass rover using a rotary-percussive coring tool mounted on a 5 degree-of-freedom (DOF) arm. A new architecture of using an arm-stabilized, rotary percussive tool with the robotic arm used to provide the drill z-axis linear feed is validated. Particular attention to hole start using this architecture is addressed. An end-to-end coring sequence is demonstrated, where the rover autonomously detects and then recovers from a series of slip events that exceeded 9 cm total displacement.

Adaptive density trajectory cluster based on time and space distance

NASA Astrophysics Data System (ADS)

Liu, Fagui; Zhang, Zhijie

2017-10-01

There are some hotspot problems remaining in trajectory cluster for discovering mobile behavior regularity, such as the computation of distance between sub trajectories, the setting of parameter values in cluster algorithm and the uncertainty/boundary problem of data set. As a result, based on the time and space, this paper tries to define the calculation method of distance between sub trajectories. The significance of distance calculation for sub trajectories is to clearly reveal the differences in moving trajectories and to promote the accuracy of cluster algorithm. Besides, a novel adaptive density trajectory cluster algorithm is proposed, in which cluster radius is computed through using the density of data distribution. In addition, cluster centers and number are selected by a certain strategy automatically, and uncertainty/boundary problem of data set is solved by designed weighted rough c-means. Experimental results demonstrate that the proposed algorithm can perform the fuzzy trajectory cluster effectively on the basis of the time and space distance, and obtain the optimal cluster centers and rich cluster results information adaptably for excavating the features of mobile behavior in mobile and sociology network.

Practice parameters and financial factors impacting developmental-behavioral pediatrics.

PubMed

Adair, Robin; Perrin, Ellen; Hubbard, Carol; Savageau, Judith A

2010-01-01

Little has been published about the professional activities of developmental-behavioral (DB) pediatricians. To better understand the settings in which DB pediatricians work, allocation of their professional time, and how financial considerations impact their practice, the Society for Developmental and Behavioral Pediatrics surveyed its membership. An extensive on-line three-part survey was conducted in 2006-2007 assessing sociodemographic characteristics, practice descriptors, coding and billing practices, productivity goals and perceived pressures among Society for Developmental and Behavioral Pediatric's 438 physician members. Of the pediatricians responding, representing all regions of the United States, 93% were DB pediatrics subspecialty board certified or eligible. The majority was practicing DB pediatrics full-time (73%); and 67% were exclusively in academic settings. All reported seeing patients, 84% reported teaching, 76% reported having administrative responsibilities, and 46% reported conducting research. Despite having non-clinical responsibilities, full-time equivalent positions included an average of 25 hours per week in direct patient care and 14.5 hours per week (37% of clinical time) in indirect patient care. Only 42% reported working with multidisciplinary teams. Salaries varied widely within and across regions. Deficits in billing/coding practices, awareness of personal clinical productivity, and familiarity with national productivity benchmarks were identified. DB pediatricians work in diverse settings nationwide. They provide considerable time in indirect patient care, which is poorly reimbursed in general and relative to direct patient care. The results of this survey offer opportunities for provider, institutional and payer education.

A minimum data set of water quality parameters to assess and compare treatment efficiency of stormwater facilities.

PubMed

Ingvertsen, Simon Toft; Jensen, Marina Bergen; Magid, Jakob

2011-01-01

Urban stormwater runoff is often of poor quality, impacting aquatic ecosystems and limiting the use of stormwater runoff for recreational purposes. Several stormwater treatment facilities (STFs) are in operation or at the pilot testing stage, but their efficiencies are neither well documented nor easily compared due to the complex contaminant profile of stormwater and the highly variable runoff hydrograph. On the basis of a review of available data sets on urban stormwater quality and environmental contaminant behavior, we suggest a few carefully selected contaminant parameters (the minimum data set) to be obligatory when assessing and comparing the efficiency of STFs. Consistent use of the minimum data set in all future monitoring schemes for STFs will ensure broad-spectrum testing at low costs and strengthen comparability among facilities. The proposed minimum data set includes: (i) fine fraction of suspended solids (<63 μm), (ii) total concentrations of zinc and copper, (iii) total concentrations of phenanthrene, fluoranthene, and benzo(b,k)fluoranthene, and (iv) total concentrations of phosphorus and nitrogen. Indicator pathogens and other specific contaminants (i.e., chromium, pesticides, phenols) may be added if recreational or certain catchment-scale objectives are to be met. Issues that need further investigation have been identified during the iterative process of developing the minimum data set. by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Accurate diode behavioral model with reverse recovery

NASA Astrophysics Data System (ADS)

Banáš, Stanislav; Divín, Jan; Dobeš, Josef; Paňko, Václav

2018-01-01

This paper deals with the comprehensive behavioral model of p-n junction diode containing reverse recovery effect, applicable to all standard SPICE simulators supporting Verilog-A language. The model has been successfully used in several production designs, which require its full complexity, robustness and set of tuning parameters comparable with standard compact SPICE diode model. The model is like standard compact model scalable with area and temperature and can be used as a stand-alone diode or as a part of more complex device macro-model, e.g. LDMOS, JFET, bipolar transistor. The paper briefly presents the state of the art followed by the chapter describing the model development and achieved solutions. During precise model verification some of them were found non-robust or poorly converging and replaced by more robust solutions, demonstrated in the paper. The measurement results of different technologies and different devices compared with a simulation using the new behavioral model are presented as the model validation. The comparison of model validation in time and frequency domains demonstrates that the implemented reverse recovery effect with correctly extracted parameters improves the model simulation results not only in switching from ON to OFF state, which is often published, but also its impedance/admittance frequency dependency in GHz range. Finally the model parameter extraction and the comparison with SPICE compact models containing reverse recovery effect is presented.

Development and characterization of camphor sulphonic acid doped polyaniline film with broadband negative dielectric constant for microwave applications

NASA Astrophysics Data System (ADS)

Sreekala, P. S.; Honey, John; Aanandan, C. K.

2018-05-01

In this communication, the broadband artificial dielectric plasma behavior of Camphor Sulphonic acid doped Polyaniline (PANI-CSA) film at microwave frequencies is experimentally verified. The fabricated PANI-CSA films have been experimentally characterized by rectangular wave guide measurements for a broad range of frequencies within the X band and the effective material parameters, skin depth and conductivity have been extracted from the scattering parameters. Since most of the artificial materials available today are set up by consolidating two structured materials which independently demonstrates negative permittivity and negative permeability, this open another strategy for creation of compact single negative materials for microwave applications. The proposed doping can shift the double positive material parameter of the sample to single negative in nature.

On the applicability of low-dimensional models for convective flow reversals at extreme Prandtl numbers

NASA Astrophysics Data System (ADS)

Mannattil, Manu; Pandey, Ambrish; Verma, Mahendra K.; Chakraborty, Sagar

2017-12-01

Constructing simpler models, either stochastic or deterministic, for exploring the phenomenon of flow reversals in fluid systems is in vogue across disciplines. Using direct numerical simulations and nonlinear time series analysis, we illustrate that the basic nature of flow reversals in convecting fluids can depend on the dimensionless parameters describing the system. Specifically, we find evidence of low-dimensional behavior in flow reversals occurring at zero Prandtl number, whereas we fail to find such signatures for reversals at infinite Prandtl number. Thus, even in a single system, as one varies the system parameters, one can encounter reversals that are fundamentally different in nature. Consequently, we conclude that a single general low-dimensional deterministic model cannot faithfully characterize flow reversals for every set of parameter values.

Application of an automatic approach to calibrate the NEMURO nutrient-phytoplankton-zooplankton food web model in the Oyashio region

NASA Astrophysics Data System (ADS)

Ito, Shin-ichi; Yoshie, Naoki; Okunishi, Takeshi; Ono, Tsuneo; Okazaki, Yuji; Kuwata, Akira; Hashioka, Taketo; Rose, Kenneth A.; Megrey, Bernard A.; Kishi, Michio J.; Nakamachi, Miwa; Shimizu, Yugo; Kakehi, Shigeho; Saito, Hiroaki; Takahashi, Kazutaka; Tadokoro, Kazuaki; Kusaka, Akira; Kasai, Hiromi

2010-10-01

The Oyashio region in the western North Pacific supports high biological productivity and has been well monitored. We applied the NEMURO (North Pacific Ecosystem Model for Understanding Regional Oceanography) model to simulate the nutrients, phytoplankton, and zooplankton dynamics. Determination of parameters values is very important, yet ad hoc calibration methods are often used. We used the automatic calibration software PEST (model-independent Parameter ESTimation), which has been used previously with NEMURO but in a system without ontogenetic vertical migration of the large zooplankton functional group. Determining the performance of PEST with vertical migration, and obtaining a set of realistic parameter values for the Oyashio, will likely be useful in future applications of NEMURO. Five identical twin simulation experiments were performed with the one-box version of NEMURO. The experiments differed in whether monthly snapshot or averaged state variables were used, in whether state variables were model functional groups or were aggregated (total phytoplankton, small plus large zooplankton), and in whether vertical migration of large zooplankton was included or not. We then applied NEMURO to monthly climatological field data covering 1 year for the Oyashio, and compared model fits and parameter values between PEST-determined estimates and values used in previous applications to the Oyashio region that relied on ad hoc calibration. We substituted the PEST and ad hoc calibrated parameter values into a 3-D version of NEMURO for the western North Pacific, and compared the two sets of spatial maps of chlorophyll- a with satellite-derived data. The identical twin experiments demonstrated that PEST could recover the known model parameter values when vertical migration was included, and that over-fitting can occur as a result of slight differences in the values of the state variables. PEST recovered known parameter values when using monthly snapshots of aggregated state variables, but estimated a different set of parameters with monthly averaged values. Both sets of parameters resulted in good fits of the model to the simulated data. Disaggregating the variables provided to PEST into functional groups did not solve the over-fitting problem, and including vertical migration seemed to amplify the problem. When we used the climatological field data, simulated values with PEST-estimated parameters were closer to these field data than with the previously determined ad hoc set of parameter values. When these same PEST and ad hoc sets of parameter values were substituted into 3-D-NEMURO (without vertical migration), the PEST-estimated parameter values generated spatial maps that were similar to the satellite data for the Kuroshio Extension during January and March and for the subarctic ocean from May to November. With non-linear problems, such as vertical migration, PEST should be used with caution because parameter estimates can be sensitive to how the data are prepared and to the values used for the searching parameters of PEST. We recommend the usage of PEST, or other parameter optimization methods, to generate first-order parameter estimates for simulating specific systems and for insertion into 2-D and 3-D models. The parameter estimates that are generated are useful, and the inconsistencies between simulated values and the available field data provide valuable information on model behavior and the dynamics of the ecosystem.

Vortex equations: Singularities, numerical solution, and axisymmetric vortex breakdown

NASA Technical Reports Server (NTRS)

Bossel, H. H.

1972-01-01

A method of weighted residuals for the computation of rotationally symmetric quasi-cylindrical viscous incompressible vortex flow is presented and used to compute a wide variety of vortex flows. The method approximates the axial velocity and circulation profiles by series of exponentials having (N + 1) and N free parameters, respectively. Formal integration results in a set of (2N + 1) ordinary differential equations for the free parameters. The governing equations are shown to have an infinite number of discrete singularities corresponding to critical values of the swirl parameters. The computations point to the controlling influence of the inner core flow on vortex behavior. They also confirm the existence of two particular critical swirl parameter values: one separates vortex flow which decays smoothly from vortex flow which eventually breaks down, and the second is the first singularity of the quasi-cylindrical system, at which point physical vortex breakdown is thought to occur.

Observational constraints on variable equation of state parameters of dark matter and dark energy after Planck

NASA Astrophysics Data System (ADS)

Kumar, Suresh; Xu, Lixin

2014-10-01

In this paper, we study a cosmological model in general relativity within the framework of spatially flat Friedmann-Robertson-Walker space-time filled with ordinary matter (baryonic), radiation, dark matter and dark energy, where the latter two components are described by Chevallier-Polarski-Linder equation of state parameters. We utilize the observational data sets from SNLS3, BAO and Planck + WMAP9 + WiggleZ measurements of matter power spectrum to constrain the model parameters. We find that the current observational data offer tight constraints on the equation of state parameter of dark matter. We consider the perturbations and study the behavior of dark matter by observing its effects on CMB and matter power spectra. We find that the current observational data favor the cold dark matter scenario with the cosmological constant type dark energy at the present epoch.

Block voter model: Phase diagram and critical behavior

NASA Astrophysics Data System (ADS)

Sampaio-Filho, C. I. N.; Moreira, F. G. B.

2011-11-01

We introduce and study the block voter model with noise on two-dimensional square lattices using Monte Carlo simulations and finite-size scaling techniques. The model is defined by an outflow dynamics where a central set of NPCS spins, here denoted by persuasive cluster spins (PCS), tries to influence the opinion of their neighboring counterparts. We consider the collective behavior of the entire system with varying PCS size. When NPCS>2, the system exhibits an order-disorder phase transition at a critical noise parameter qc which is a monotonically increasing function of the size of the persuasive cluster. We conclude that a larger PCS has more power of persuasion, when compared to a smaller one. It also seems that the resulting critical behavior is Ising-like independent of the range of interaction.

Synthetic Training Data Generation for Activity Monitoring and Behavior Analysis

NASA Astrophysics Data System (ADS)

Monekosso, Dorothy; Remagnino, Paolo

This paper describes a data generator that produces synthetic data to simulate observations from an array of environment monitoring sensors. The overall goal of our work is to monitor the well-being of one occupant in a home. Sensors are embedded in a smart home to unobtrusively record environmental parameters. Based on the sensor observations, behavior analysis and modeling are performed. However behavior analysis and modeling require large data sets to be collected over long periods of time to achieve the level of accuracy expected. A data generator - was developed based on initial data i.e. data collected over periods lasting weeks to facilitate concurrent data collection and development of algorithms. The data generator is based on statistical inference techniques. Variation is introduced into the data using perturbation models.

Constitutive Models for the Viscoelastic Behavior of Polyimide Membranes at Room and Deep Cryogenic Temperatures

DOE PAGES

Bhandarkar, Suhas; Betcher, Jacob; Smith, Ryan; ...

2016-06-30

Targets for ICF shots on NIF typically use ~500nm thin polyimide films with a coating of 25nm of aluminum as windows that seal the laser entrance hole or LEH. Their role is to contain the hohlraum gas and minimize the extraneous infra-red radiation getting in. This is necessary to precisely control the hohlraum thermal environment for layering inside the capsule with solid deuterium-tritium at 18K. Here, we use our empirical data on the bulging behavior of these foils under various different conditions to develop models to capture the complex viscoelastic behavior of these films at both ambient and cryogenic temperatures.more » The constitutive equations derived from these models give us the ability to quantitatively specify the film’s behavior during the fielding of these targets and set the best parameters for new target designs.« less

Self-organized sorting limits behavioral variability in swarms

PubMed Central

Copenhagen, Katherine; Quint, David A.; Gopinathan, Ajay

2016-01-01

Swarming is a phenomenon where collective motion arises from simple local interactions between typically identical individuals. Here, we investigate the effects of variability in behavior among the agents in finite swarms with both alignment and cohesive interactions. We show that swarming is abolished above a critical fraction of non-aligners who do not participate in alignment. In certain regimes, however, swarms above the critical threshold can dynamically reorganize and sort out excess non-aligners to maintain the average fraction close to the critical value. This persists even in swarms with a distribution of alignment interactions, suggesting a simple, robust and efficient mechanism that allows heterogeneously mixed populations to naturally regulate their composition and remain in a collective swarming state or even differentiate among behavioral phenotypes. We show that, for evolving swarms, this self-organized sorting behavior can couple to the evolutionary dynamics leading to new evolutionarily stable equilibrium populations set by the physical swarm parameters. PMID:27550316

3D Holographic Observatory for Long-term Monitoring of Complex Behaviors in Drosophila

NASA Astrophysics Data System (ADS)

Kumar, S. Santosh; Sun, Yaning; Zou, Sige; Hong, Jiarong

2016-09-01

Drosophila is an excellent model organism towards understanding the cognitive function, aging and neurodegeneration in humans. The effects of aging and other long-term dynamics on the behavior serve as important biomarkers in identifying such changes to the brain. In this regard, we are presenting a new imaging technique for lifetime monitoring of Drosophila in 3D at spatial and temporal resolutions capable of resolving the motion of limbs and wings using holographic principles. The developed system is capable of monitoring and extracting various behavioral parameters, such as ethograms and spatial distributions, from a group of flies simultaneously. This technique can image complicated leg and wing motions of flies at a resolution, which allows capturing specific landing responses from the same data set. Overall, this system provides a unique opportunity for high throughput screenings of behavioral changes in 3D over a long term in Drosophila.

Behavior-Based Cleaning for Unreliable RFID Data Sets

PubMed Central

Fan, Hua; Wu, Quanyuan; Lin, Yisong

2012-01-01

Radio Frequency IDentification (RFID) technology promises to revolutionize the way we track items and assets, but in RFID systems, missreading is a common phenomenon and it poses an enormous challenge to RFID data management, so accurate data cleaning becomes an essential task for the successful deployment of systems. In this paper, we present the design and development of a RFID data cleaning system, the first declarative, behavior-based unreliable RFID data smoothing system. We take advantage of kinematic characteristics of tags to assist in RFID data cleaning. In order to establish the conversion relationship between RFID data and kinematic parameters of the tags, we propose a movement behavior detection model. Moreover, a Reverse Order Filling Mechanism is proposed to ensure a more complete access to get the movement behavior characteristics of tag. Finally, we validate our solution with a common RFID application and demonstrate the advantages of our approach through extensive simulations. PMID:23112595

Behavior-based cleaning for unreliable RFID data sets.

PubMed

Fan, Hua; Wu, Quanyuan; Lin, Yisong

2012-01-01

Radio Frequency IDentification (RFID) technology promises to revolutionize the way we track items and assets, but in RFID systems, missreading is a common phenomenon and it poses an enormous challenge to RFID data management, so accurate data cleaning becomes an essential task for the successful deployment of systems. In this paper, we present the design and development of a RFID data cleaning system, the first declarative, behavior-based unreliable RFID data smoothing system. We take advantage of kinematic characteristics of tags to assist in RFID data cleaning. In order to establish the conversion relationship between RFID data and kinematic parameters of the tags, we propose a movement behavior detection model. Moreover, a Reverse Order Filling Mechanism is proposed to ensure a more complete access to get the movement behavior characteristics of tag. Finally, we validate our solution with a common RFID application and demonstrate the advantages of our approach through extensive simulations.

Self-organized sorting limits behavioral variability in swarms

NASA Astrophysics Data System (ADS)

Copenhagen, Katherine; Quint, David A.; Gopinathan, Ajay

2016-08-01

Swarming is a phenomenon where collective motion arises from simple local interactions between typically identical individuals. Here, we investigate the effects of variability in behavior among the agents in finite swarms with both alignment and cohesive interactions. We show that swarming is abolished above a critical fraction of non-aligners who do not participate in alignment. In certain regimes, however, swarms above the critical threshold can dynamically reorganize and sort out excess non-aligners to maintain the average fraction close to the critical value. This persists even in swarms with a distribution of alignment interactions, suggesting a simple, robust and efficient mechanism that allows heterogeneously mixed populations to naturally regulate their composition and remain in a collective swarming state or even differentiate among behavioral phenotypes. We show that, for evolving swarms, this self-organized sorting behavior can couple to the evolutionary dynamics leading to new evolutionarily stable equilibrium populations set by the physical swarm parameters.

Impact Of The Material Variability On The Stamping Process: Numerical And Analytical Analysis

NASA Astrophysics Data System (ADS)

Ledoux, Yann; Sergent, Alain; Arrieux, Robert

2007-05-01

The finite element simulation is a very useful tool in the deep drawing industry. It is used more particularly for the development and the validation of new stamping tools. It allows to decrease cost and time for the tooling design and set up. But one of the most important difficulties to have a good agreement between the simulation and the real process comes from the definition of the numerical conditions (mesh, punch travel speed, limit conditions,…) and the parameters which model the material behavior. Indeed, in press shop, when the sheet set changes, often a variation of the formed part geometry is observed according to the variability of the material properties between these different sets. This last parameter represents probably one of the main source of process deviation when the process is set up. That's why it is important to study the influence of material data variation on the geometry of a classical stamped part. The chosen geometry is an omega shaped part because of its simplicity and it is representative one in the automotive industry (car body reinforcement). Moreover, it shows important springback deviations. An isotropic behaviour law is assumed. The impact of the statistical deviation of the three law coefficients characterizing the material and the friction coefficient around their nominal values is tested. A Gaussian distribution is supposed and their impact on the geometry variation is studied by FE simulation. An other approach is envisaged consisting in modeling the process variability by a mathematical model and then, in function of the input parameters variability, it is proposed to define an analytical model which leads to find the part geometry variability around the nominal shape. These two approaches allow to predict the process capability as a function of the material parameter variability.

Effect of tillage system and cumulative rainfall on multifractal parameters of soil surface microrelief

NASA Astrophysics Data System (ADS)

Vidal Vázquez, E.; Miranda, J. G. V.; Mirás-Avalos, J. M.; Díaz, M. C.; Paz-Ferreiro, J.

2009-04-01

Mathematical description of the spatial characteristics of soil surface microrelief still remains a challenge. Soil surface roughness parameters are required for modelling overland flow and erosion. The objective of this work was to evaluate the potential of multifractal for analyzing the decay of initial surface roughness induced by natural rainfall under different soil tillage systems. Field experiments were performed on an Oxisol at Campinas, São Paulo State (Brazil). Six tillage treatments, namely, disc harrow, disc plow, chisel plow, disc harrow + disc level, disc plow + disc level and chisel plow + disc level were tested. In each plot soil surface microrelief was measured for times, with increasing amounts of natural rainfall using a pinmeter. The sampling scheme was a square grid with 25 x 25 mm point spacing and the plot size was 1350 x 1350 mm, so that each data set consisted of 3025 individual elevation points. Duplicated measurements were taken per treatment and date, yielding a total of 48 experimental data sets. All the investigated microrelief data sets exhibited, in general, scale properties, and the degree of multifractality showed wide differences between them. Multifractal analysis distinguishes two different patterns of soil surface microrelief, the first one has features close to monofractal spectra and the second clearly indicates multifractal behavior. Both, singularity spectra and generalized dimension spectra allow differentiating between soil tillage systems. In general, changes in values of multifractal parameters under simulated rainfall showed no or little correspondence with the evolution of the vertical microrelief component described by indices such as the standard deviation of the point height measurements. Multifractal parameters provided valuable information for chararacterizing the spatial features of soil surface microrelief as they were able to discriminate data sets with similar values for the vertical component of roughness.

Understanding heart rate alarm adjustment in the intensive care units through an analytical approach.

PubMed

Fidler, Richard L; Pelter, Michele M; Drew, Barbara J; Palacios, Jorge Arroyo; Bai, Yong; Stannard, Daphne; Aldrich, J Matt; Hu, Xiao

2017-01-01

Heart rate (HR) alarms are prevalent in ICU, and these parameters are configurable. Not much is known about nursing behavior associated with tailoring HR alarm parameters to individual patients to reduce clinical alarm fatigue. To understand the relationship between heart rate (HR) alarms and adjustments to reduce unnecessary heart rate alarms. Retrospective, quantitative analysis of an adjudicated database using analytical approaches to understand behaviors surrounding parameter HR alarm adjustments. Patients were sampled from five adult ICUs (77 beds) over one month at a quaternary care university medical center. A total of 337 of 461 ICU patients had HR alarms with 53.7% male, mean age 60.3 years, and 39% non-Caucasian. Default HR alarm parameters were 50 and 130 beats per minute (bpm). The occurrence of each alarm, vital signs, and physiologic waveforms was stored in a relational database (SQL server). There were 23,624 HR alarms for analysis, with 65.4% exceeding the upper heart rate limit. Only 51% of patients with HR alarms had parameters adjusted, with a median upper limit change of +5 bpm and -1 bpm lower limit. The median time to first HR parameter adjustment was 17.9 hours, without reduction in alarms occurrence (p = 0.57). HR alarms are prevalent in ICU, and half of HR alarm settings remain at default. There is a long delay between HR alarms and parameters changes, with insufficient changes to decrease HR alarms. Increasing frequency of HR alarms shortens the time to first adjustment. Best practice guidelines for HR alarm limits are needed to reduce alarm fatigue and improve monitoring precision.

Application of advanced sampling and analysis methods to predict the structure of adsorbed protein on a material surface

PubMed Central

Abramyan, Tigran M.; Hyde-Volpe, David L.; Stuart, Steven J.; Latour, Robert A.

2017-01-01

The use of standard molecular dynamics simulation methods to predict the interactions of a protein with a material surface have the inherent limitations of lacking the ability to determine the most likely conformations and orientations of the adsorbed protein on the surface and to determine the level of convergence attained by the simulation. In addition, standard mixing rules are typically applied to combine the nonbonded force field parameters of the solution and solid phases the system to represent interfacial behavior without validation. As a means to circumvent these problems, the authors demonstrate the application of an efficient advanced sampling method (TIGER2A) for the simulation of the adsorption of hen egg-white lysozyme on a crystalline (110) high-density polyethylene surface plane. Simulations are conducted to generate a Boltzmann-weighted ensemble of sampled states using force field parameters that were validated to represent interfacial behavior for this system. The resulting ensembles of sampled states were then analyzed using an in-house-developed cluster analysis method to predict the most probable orientations and conformations of the protein on the surface based on the amount of sampling performed, from which free energy differences between the adsorbed states were able to be calculated. In addition, by conducting two independent sets of TIGER2A simulations combined with cluster analyses, the authors demonstrate a method to estimate the degree of convergence achieved for a given amount of sampling. The results from these simulations demonstrate that these methods enable the most probable orientations and conformations of an adsorbed protein to be predicted and that the use of our validated interfacial force field parameter set provides closer agreement to available experimental results compared to using standard CHARMM force field parameterization to represent molecular behavior at the interface. PMID:28514864

Quantifying Uncertainty in Inverse Models of Geologic Data from Shear Zones

NASA Astrophysics Data System (ADS)

Davis, J. R.; Titus, S.

2016-12-01

We use Bayesian Markov chain Monte Carlo simulation to quantify uncertainty in inverse models of geologic data. Although this approach can be applied to many tectonic settings, field areas, and mathematical models, we focus on transpressional shear zones. The underlying forward model, either kinematic or dynamic, produces a velocity field, which predicts the dikes, foliation-lineations, crystallographic preferred orientation (CPO), shape preferred orientation (SPO), and other geologic data that should arise in the shear zone. These predictions are compared to data using modern methods of geometric statistics, including the Watson (for lines such as dike poles), isotropic matrix Fisher (for orientations such as foliation-lineations and CPO), and multivariate normal (for log-ellipsoids such as SPO) distributions. The result of the comparison is a likelihood, which is a key ingredient in the Bayesian approach. The other key ingredient is a prior distribution, which reflects the geologist's knowledge of the parameters before seeing the data. For some parameters, such as shear zone strike and dip, we identify realistic informative priors. For other parameters, where the geologist has no prior knowledge, we identify useful uninformative priors.We investigate the performance of this approach through numerical experiments on synthetic data sets. A fundamental issue is that many models of deformation exhibit asymptotic behavior (e.g., flow apophyses, fabric attractors) or periodic behavior (e.g., SPO when the clasts are rigid), which causes the likelihood to be too uniform. Based on our experiments, we offer rules of thumb for how many data, of which types, are needed to constrain deformation.

Coexisting multiple attractors and riddled basins of a memristive system.

PubMed

Wang, Guangyi; Yuan, Fang; Chen, Guanrong; Zhang, Yu

2018-01-01

In this paper, a new memristor-based chaotic system is designed, analyzed, and implemented. Multistability, multiple attractors, and complex riddled basins are observed from the system, which are investigated along with other dynamical behaviors such as equilibrium points and their stabilities, symmetrical bifurcation diagrams, and sustained chaotic states. With different sets of system parameters, the system can also generate various multi-scroll attractors. Finally, the system is realized by experimental circuits.

Experimental Research on Selective Laser Melting AlSi10Mg Alloys: Process, Densification and Performance

NASA Astrophysics Data System (ADS)

Chen, Zhen; Wei, Zhengying; Wei, Pei; Chen, Shenggui; Lu, Bingheng; Du, Jun; Li, Junfeng; Zhang, Shuzhe

2017-12-01

In this work, a set of experiments was designed to investigate the effect of process parameters on the relative density of the AlSi10Mg parts manufactured by SLM. The influence of laser scan speed v, laser power P and hatch space H, which were considered as the dominant parameters, on the powder melting and densification behavior was also studied experimentally. In addition, the laser energy density was introduced to evaluate the combined effect of the above dominant parameters, so as to control the SLM process integrally. As a result, a high relative density (> 97%) was obtained by SLM at an optimized laser energy density of 3.5-5.5 J/mm2. Moreover, a parameter-densification map was established to visually select the optimum process parameters for the SLM-processed AlSi10Mg parts with elevated density and required mechanical properties. The results provide an important experimental guidance for obtaining AlSi10Mg components with full density and gradient functional porosity by SLM.

A new parametric method to smooth time-series data of metabolites in metabolic networks.

PubMed

Miyawaki, Atsuko; Sriyudthsak, Kansuporn; Hirai, Masami Yokota; Shiraishi, Fumihide

2016-12-01

Mathematical modeling of large-scale metabolic networks usually requires smoothing of metabolite time-series data to account for measurement or biological errors. Accordingly, the accuracy of smoothing curves strongly affects the subsequent estimation of model parameters. Here, an efficient parametric method is proposed for smoothing metabolite time-series data, and its performance is evaluated. To simplify parameter estimation, the method uses S-system-type equations with simple power law-type efflux terms. Iterative calculation using this method was found to readily converge, because parameters are estimated stepwise. Importantly, smoothing curves are determined so that metabolite concentrations satisfy mass balances. Furthermore, the slopes of smoothing curves are useful in estimating parameters, because they are probably close to their true behaviors regardless of errors that may be present in the actual data. Finally, calculations for each differential equation were found to converge in much less than one second if initial parameters are set at appropriate (guessed) values. Copyright © 2016 Elsevier Inc. All rights reserved.

Parameter space of experimental chaotic circuits with high-precision control parameters.

PubMed

de Sousa, Francisco F G; Rubinger, Rero M; Sartorelli, José C; Albuquerque, Holokx A; Baptista, Murilo S

2016-08-01

We report high-resolution measurements that experimentally confirm a spiral cascade structure and a scaling relationship of shrimps in the Chua's circuit. Circuits constructed using this component allow for a comprehensive characterization of the circuit behaviors through high resolution parameter spaces. To illustrate the power of our technological development for the creation and the study of chaotic circuits, we constructed a Chua circuit and study its high resolution parameter space. The reliability and stability of the designed component allowed us to obtain data for long periods of time (∼21 weeks), a data set from which an accurate estimation of Lyapunov exponents for the circuit characterization was possible. Moreover, this data, rigorously characterized by the Lyapunov exponents, allows us to reassure experimentally that the shrimps, stable islands embedded in a domain of chaos in the parameter spaces, can be observed in the laboratory. Finally, we confirm that their sizes decay exponentially with the period of the attractor, a result expected to be found in maps of the quadratic family.

Parameter extraction with neural networks

NASA Astrophysics Data System (ADS)

Cazzanti, Luca; Khan, Mumit; Cerrina, Franco

1998-06-01

In semiconductor processing, the modeling of the process is becoming more and more important. While the ultimate goal is that of developing a set of tools for designing a complete process (Technology CAD), it is also necessary to have modules to simulate the various technologies and, in particular, to optimize specific steps. This need is particularly acute in lithography, where the continuous decrease in CD forces the technologies to operate near their limits. In the development of a 'model' for a physical process, we face several levels of challenges. First, it is necessary to develop a 'physical model,' i.e. a rational description of the process itself on the basis of know physical laws. Second, we need an 'algorithmic model' to represent in a virtual environment the behavior of the 'physical model.' After a 'complete' model has been developed and verified, it becomes possible to do performance analysis. In many cases the input parameters are poorly known or not accessible directly to experiment. It would be extremely useful to obtain the values of these 'hidden' parameters from experimental results by comparing model to data. This is particularly severe, because the complexity and costs associated with semiconductor processing make a simple 'trial-and-error' approach infeasible and cost- inefficient. Even when computer models of the process already exists, obtaining data through simulations may be time consuming. Neural networks (NN) are powerful computational tools to predict the behavior of a system from an existing data set. They are able to adaptively 'learn' input/output mappings and to act as universal function approximators. In this paper we use artificial neural networks to build a mapping from the input parameters of the process to output parameters which are indicative of the performance of the process. Once the NN has been 'trained,' it is also possible to observe the process 'in reverse,' and to extract the values of the inputs which yield outputs with desired characteristics. Using this method, we can extract optimum values for the parameters and determine the process latitude very quickly.

Rheological Behaviors of Thickened Infant Formula Prepared with Xanthan Gum-Based Food Thickeners for Dysphagic Infants.

PubMed

Yoon, Sung-No; Yoo, Byoungseung

2017-06-01

Thickened infant formula (TIF) prepared with commercial xanthan gum (XG)-based food thickeners are commonly used to care for infants with swallowing difficulties or regurgitation. In this study, the rheological properties of TIF prepared with four commercial food thickeners (coded A-D) were determined as a function of thickener concentration, thickener type, and setting time because the selection of an appropriate food thickener for TIF preparation is necessary for managing dysphagia in infants. The flow and dynamic rheological properties of TIF were investigated at three different concentrations (1.0, 2.0, and 3.0% w/w) of XG-based thickener. The flow properties of TIF were described by the power law and Casson models. All TIF samples demonstrated high shear-thinning (n = 0.12-0.33) behavior at all concentrations (1.0-3.0%). Their apparent viscosity (η a,50 ), consistency index (K), yield stress (σ oc ), storage modulus (G'), and loss modulus (G″) increased with an increase in thickener concentration. In general, TIF with thickener A had much higher values for all flow parameters at each thickener concentration when compared to TIF with other thickeners (B, C, and D). However, the n values of TIF samples with thickener A were much lower, indicating that they are less slimy and have better mouthfeel than those of TIF samples with other thickeners. All TIF samples with different thickeners produced different thickening patterns over a setting time. The flow and dynamic rheological parameters demonstrated differences in the rheological behaviors between XG-based thickeners, indicating that their rheological properties are related to the concentration and type of thickener as well as the setting time. These results suggest the importance of considering not only the concentration and type of thickeners but also the time being administered after its addition to effectively treat dysphagic infants. In addition, selecting an appropriate commercial food thickener appears to be of great importance for the safe and easy swallowing of dysphagic infants.

Criticality as a Set-Point for Adaptive Behavior in Neuromorphic Hardware

PubMed Central

Srinivasa, Narayan; Stepp, Nigel D.; Cruz-Albrecht, Jose

2015-01-01

Neuromorphic hardware are designed by drawing inspiration from biology to overcome limitations of current computer architectures while forging the development of a new class of autonomous systems that can exhibit adaptive behaviors. Several designs in the recent past are capable of emulating large scale networks but avoid complexity in network dynamics by minimizing the number of dynamic variables that are supported and tunable in hardware. We believe that this is due to the lack of a clear understanding of how to design self-tuning complex systems. It has been widely demonstrated that criticality appears to be the default state of the brain and manifests in the form of spontaneous scale-invariant cascades of neural activity. Experiment, theory and recent models have shown that neuronal networks at criticality demonstrate optimal information transfer, learning and information processing capabilities that affect behavior. In this perspective article, we argue that understanding how large scale neuromorphic electronics can be designed to enable emergent adaptive behavior will require an understanding of how networks emulated by such hardware can self-tune local parameters to maintain criticality as a set-point. We believe that such capability will enable the design of truly scalable intelligent systems using neuromorphic hardware that embrace complexity in network dynamics rather than avoiding it. PMID:26648839

Crystal viscoplasticity model for the creep-fatigue interactions in single-crystal Ni-base superalloy CMSX-8

DOE Office of Scientific and Technical Information (OSTI.GOV)

Estrada Rodas, Ernesto A.; Neu, Richard W.

A crystal viscoplasticity (CVP) model for the creep-fatigue interactions of nickel-base superalloy CMSX-8 is proposed. At the microstructure scale of relevance, the superalloys are a composite material comprised of a γ phase and a γ' strengthening phase with unique deformation mechanisms that are highly dependent on temperature. Considering the differences in the deformation of the individual material phases is paramount to predicting the deformation behavior of superalloys at a wide range of temperatures. In this work, we account for the relevant deformation mechanisms that take place in both material phases by utilizing two additive strain rates to model the deformationmore » on each material phase. The model is capable of representing the creep-fatigue interactions in single-crystal superalloys for realistic 3-dimensional components in an Abaqus User Material Subroutine (UMAT). Using a set of material parameters calibrated to superalloy CMSX-8, the model predicts creep-fatigue, fatigue and thermomechanical fatigue behavior of this single-crystal superalloy. In conclusion, a sensitivity study of the material parameters is done to explore the effect on the deformation due to changes in the material parameters relevant to the microstructure.« less

Landsat-5 bumper-mode geometric correction

USGS Publications Warehouse

Storey, James C.; Choate, Michael J.

2004-01-01

The Landsat-5 Thematic Mapper (TM) scan mirror was switched from its primary operating mode to a backup mode in early 2002 in order to overcome internal synchronization problems arising from long-term wear of the scan mirror mechanism. The backup bumper mode of operation removes the constraints on scan start and stop angles enforced in the primary scan angle monitor operating mode, requiring additional geometric calibration effort to monitor the active scan angles. It also eliminates scan timing telemetry used to correct the TM scan geometry. These differences require changes to the geometric correction algorithms used to process TM data. A mathematical model of the scan mirror's behavior when operating in bumper mode was developed. This model includes a set of key timing parameters that characterize the time-varying behavior of the scan mirror bumpers. To simplify the implementation of the bumper-mode model, the bumper timing parameters were recast in terms of the calibration and telemetry data items used to process normal TM imagery. The resulting geometric performance, evaluated over 18 months of bumper-mode operations, though slightly reduced from that achievable in the primary operating mode, is still within the Landsat specifications when the data are processed with the most up-to-date calibration parameters.

Upscaling Cement Paste Microstructure to Obtain the Fracture, Shear, and Elastic Concrete Mechanical LDPM Parameters.

PubMed

Sherzer, Gili; Gao, Peng; Schlangen, Erik; Ye, Guang; Gal, Erez

2017-02-28

Modeling the complex behavior of concrete for a specific mixture is a challenging task, as it requires bridging the cement scale and the concrete scale. We describe a multiscale analysis procedure for the modeling of concrete structures, in which material properties at the macro scale are evaluated based on lower scales. Concrete may be viewed over a range of scale sizes, from the atomic scale (10 -10 m), which is characterized by the behavior of crystalline particles of hydrated Portland cement, to the macroscopic scale (10 m). The proposed multiscale framework is based on several models, including chemical analysis at the cement paste scale, a mechanical lattice model at the cement and mortar scales, geometrical aggregate distribution models at the mortar scale, and the Lattice Discrete Particle Model (LDPM) at the concrete scale. The analysis procedure starts from a known chemical and mechanical set of parameters of the cement paste, which are then used to evaluate the mechanical properties of the LDPM concrete parameters for the fracture, shear, and elastic responses of the concrete. Although a macroscopic validation study of this procedure is presented, future research should include a comparison to additional experiments in each scale.

Crystal viscoplasticity model for the creep-fatigue interactions in single-crystal Ni-base superalloy CMSX-8

DOE PAGES

Estrada Rodas, Ernesto A.; Neu, Richard W.

2017-09-11

A crystal viscoplasticity (CVP) model for the creep-fatigue interactions of nickel-base superalloy CMSX-8 is proposed. At the microstructure scale of relevance, the superalloys are a composite material comprised of a γ phase and a γ' strengthening phase with unique deformation mechanisms that are highly dependent on temperature. Considering the differences in the deformation of the individual material phases is paramount to predicting the deformation behavior of superalloys at a wide range of temperatures. In this work, we account for the relevant deformation mechanisms that take place in both material phases by utilizing two additive strain rates to model the deformationmore » on each material phase. The model is capable of representing the creep-fatigue interactions in single-crystal superalloys for realistic 3-dimensional components in an Abaqus User Material Subroutine (UMAT). Using a set of material parameters calibrated to superalloy CMSX-8, the model predicts creep-fatigue, fatigue and thermomechanical fatigue behavior of this single-crystal superalloy. In conclusion, a sensitivity study of the material parameters is done to explore the effect on the deformation due to changes in the material parameters relevant to the microstructure.« less

Dynamics of a modified Hindmarsh-Rose neural model with random perturbations: Moment analysis and firing activities

NASA Astrophysics Data System (ADS)

Mondal, Argha; Upadhyay, Ranjit Kumar

2017-11-01

In this paper, an attempt has been made to understand the activity of mean membrane voltage and subsidiary system variables with moment equations (i.e., mean, variance and covariance's) under noisy environment. We consider a biophysically plausible modified Hindmarsh-Rose (H-R) neural system injected by an applied current exhibiting spiking-bursting phenomenon. The effects of predominant parameters on the dynamical behavior of a modified H-R system are investigated. Numerically, it exhibits period-doubling, period halving bifurcation and chaos phenomena. Further, a nonlinear system has been analyzed for the first and second order moments with additive stochastic perturbations. It has been solved using fourth order Runge-Kutta method and noisy systems by Euler's scheme. It has been demonstrated that the firing properties of neurons to evoke an action potential in a certain parameter space of the large exact systems can be estimated using an approximated model. Strong stimulation can cause a change in increase or decrease of the firing patterns. Corresponding to a fixed set of parameter values, the firing behavior and dynamical differences of the collective variables of a large, exact and approximated systems are investigated.

Material and shape optimization for multi-layered vocal fold models using transient loadings.

PubMed

Schmidt, Bastian; Leugering, Günter; Stingl, Michael; Hüttner, Björn; Agaimy, Abbas; Döllinger, Michael

2013-08-01

Commonly applied models to study vocal fold vibrations in combination with air flow distributions are self-sustained physical models of the larynx consisting of artificial silicone vocal folds. Choosing appropriate mechanical parameters and layer geometries for these vocal fold models while considering simplifications due to manufacturing restrictions is difficult but crucial for achieving realistic behavior. In earlier work by Schmidt et al. [J. Acoust. Soc. Am. 129, 2168-2180 (2011)], the authors presented an approach in which material parameters of a static numerical vocal fold model were optimized to achieve an agreement of the displacement field with data retrieved from hemilarynx experiments. This method is now generalized to a fully transient setting. Moreover in addition to the material parameters, the extended approach is capable of finding optimized layer geometries. Depending on chosen material restriction, significant modifications of the reference geometry are predicted. The additional flexibility in the design space leads to a significantly more realistic deformation behavior. At the same time, the predicted biomechanical and geometrical results are still feasible for manufacturing physical vocal fold models consisting of several silicone layers. As a consequence, the proposed combined experimental and numerical method is suited to guide the construction of physical vocal fold models.

Upscaling Cement Paste Microstructure to Obtain the Fracture, Shear, and Elastic Concrete Mechanical LDPM Parameters

PubMed Central

Sherzer, Gili; Gao, Peng; Schlangen, Erik; Ye, Guang; Gal, Erez

2017-01-01

Modeling the complex behavior of concrete for a specific mixture is a challenging task, as it requires bridging the cement scale and the concrete scale. We describe a multiscale analysis procedure for the modeling of concrete structures, in which material properties at the macro scale are evaluated based on lower scales. Concrete may be viewed over a range of scale sizes, from the atomic scale (10−10 m), which is characterized by the behavior of crystalline particles of hydrated Portland cement, to the macroscopic scale (10 m). The proposed multiscale framework is based on several models, including chemical analysis at the cement paste scale, a mechanical lattice model at the cement and mortar scales, geometrical aggregate distribution models at the mortar scale, and the Lattice Discrete Particle Model (LDPM) at the concrete scale. The analysis procedure starts from a known chemical and mechanical set of parameters of the cement paste, which are then used to evaluate the mechanical properties of the LDPM concrete parameters for the fracture, shear, and elastic responses of the concrete. Although a macroscopic validation study of this procedure is presented, future research should include a comparison to additional experiments in each scale. PMID:28772605

Numerical explorations of R. M. Goodwin's business cycle model.

PubMed

Jakimowicz, Aleksander

2010-01-01

Goodwin's model, which was formulated in , still attracts economists' attention. The model possesses numerous interesting properties that have been discovered only recently due to the development of the chaos theory and the complexity theory. The first numerical explorations of the model were conducted in the early s by Strotz, McAnulty and Naines (1953). They discovered the coexistence of attractors that are well-known today, two properties of chaotic systems: the sensitive dependence on the initial conditions and the sensitive dependence on parameters. The occurrence of periodic and chaotic attractors is dependent on the value of parameters in a system. In case of certain parametric values fractal basin boundaries exist which results in enormous system sensitivity to external noise. If periodic attractors are placed in the neighborhood of the fractal basin boundaries, then even a low external noise can move the trajectory into the region in which the basin's structure is tangled. This leads to a kind of movement that resembles a chaotic movement on a strange attractor. In Goodwin's model, apart from typical chaotic behavior, there exists yet another kind of complex movements - transient chaotic behavior that is caused by the occurrence of invariant chaotic sets that are not attracting. Such sets are represented by chaotic saddles. Some of the latest observation methods of trajectories lying on invariant chaotic sets that are not attracting are straddle methods. This article provides examples of the basin boundary straddle trajectory and the saddle straddle trajectory. These cases were studied by Lorenz and Nusse (2002). I supplement the results they acquired with calculations of capacity dimension and correlation dimension.

Understanding Attitudes towards Proenvironmental Travel: An Empirical Study from Tangshan City in China

PubMed Central

Chen, Weiya

2014-01-01

Understanding people's attitudes towards proenvironmental travel will help to encourage people to adopt proenvironmental travel behavior. Revealed preference theory assumes that the consumption preference of consumers can be revealed by their consumption behavior. In order to investigate the influences on citizens' travel decision and analyze the difficulties of promoting proenvironmental travel behavior in medium-sized cities in China, based on revealed preference theory, this paper uses the RP survey method and disaggregate model to analyze how individual characteristics, situational factors, and trip features influence the travel mode choice. The field investigation was conducted in Tangshan City to obtain the RP data. An MNL model was built to deal with the travel mode choice. SPSS software was used to calibrate the model parameters. The goodness-of-fit tests and the predicted outcome demonstrate the validation of the parameter setting. The results show that gender, occupation, trip purpose, and distance have an obvious influence on the travel mode choice. In particular, the male gender, high income, and business travel show a high correlation with carbon-intensive travel, while the female gender and a medium income scored higher in terms of proenvironmental travel modes, such as walking, cycling, and public transport. PMID:25435872

Understanding attitudes towards proenvironmental travel: an empirical study from Tangshan City in China.

PubMed

Fang, Xiaoping; Xu, Yajing; Chen, Weiya

2014-01-01

Understanding people's attitudes towards proenvironmental travel will help to encourage people to adopt proenvironmental travel behavior. Revealed preference theory assumes that the consumption preference of consumers can be revealed by their consumption behavior. In order to investigate the influences on citizens' travel decision and analyze the difficulties of promoting proenvironmental travel behavior in medium-sized cities in China, based on revealed preference theory, this paper uses the RP survey method and disaggregate model to analyze how individual characteristics, situational factors, and trip features influence the travel mode choice. The field investigation was conducted in Tangshan City to obtain the RP data. An MNL model was built to deal with the travel mode choice. SPSS software was used to calibrate the model parameters. The goodness-of-fit tests and the predicted outcome demonstrate the validation of the parameter setting. The results show that gender, occupation, trip purpose, and distance have an obvious influence on the travel mode choice. In particular, the male gender, high income, and business travel show a high correlation with carbon-intensive travel, while the female gender and a medium income scored higher in terms of proenvironmental travel modes, such as walking, cycling, and public transport.

Hybrid pairwise likelihood analysis of animal behavior experiments.

PubMed

Cattelan, Manuela; Varin, Cristiano

2013-12-01

The study of the determinants of fights between animals is an important issue in understanding animal behavior. For this purpose, tournament experiments among a set of animals are often used by zoologists. The results of these tournament experiments are naturally analyzed by paired comparison models. Proper statistical analysis of these models is complicated by the presence of dependence between the outcomes of fights because the same animal is involved in different contests. This paper discusses two different model specifications to account for between-fights dependence. Models are fitted through the hybrid pairwise likelihood method that iterates between optimal estimating equations for the regression parameters and pairwise likelihood inference for the association parameters. This approach requires the specification of means and covariances only. For this reason, the method can be applied also when the computation of the joint distribution is difficult or inconvenient. The proposed methodology is investigated by simulation studies and applied to real data about adult male Cape Dwarf Chameleons. © 2013, The International Biometric Society.

A theory of post-stall transients in multistage axial compression systems

NASA Technical Reports Server (NTRS)

Moore, F. K.; Greitzer, E. M.

1985-01-01

A theory is presented for post stall transients in multistage axial compressors. The theory leads to a set of coupled first-order ordinary differential equations capable of describing the growth and possible decay of a rotating-stall cell during a compressor mass-flow transient. These changing flow features are shown to have a significant effect on the instantaneous compressor pumping characteristic during unsteady operation, and henace on the overall system behavior. It is also found from the theory that the ultimate mode of system response, stable rotating stall or surge, depends not only on the B parameter but also on other parameters, such as the compressor length-to-diameter ratio. Small values of this latter quantity tend to favor the occurrence of surge, as do large values of B. A limited parametric study is carried out to show the impact of the different system features on transient behavior. Based on analytical and numerical results, several specific topics are suggested for future research on post-stall transients.

Creep-rupture reliability analysis

NASA Technical Reports Server (NTRS)

Peralta-Duran, A.; Wirsching, P. H.

1984-01-01

A probabilistic approach to the correlation and extrapolation of creep-rupture data is presented. Time temperature parameters (TTP) are used to correlate the data, and an analytical expression for the master curve is developed. The expression provides a simple model for the statistical distribution of strength and fits neatly into a probabilistic design format. The analysis focuses on the Larson-Miller and on the Manson-Haferd parameters, but it can be applied to any of the TTP's. A method is developed for evaluating material dependent constants for TTP's. It is shown that optimized constants can provide a significant improvement in the correlation of the data, thereby reducing modelling error. Attempts were made to quantify the performance of the proposed method in predicting long term behavior. Uncertainty in predicting long term behavior from short term tests was derived for several sets of data. Examples are presented which illustrate the theory and demonstrate the application of state of the art reliability methods to the design of components under creep.

Two-diode behavior in metal-ferroelectric-semiconductor structures with bismuth titanate interfacial layer

NASA Astrophysics Data System (ADS)

Durmuş, Perihan; Altindal, Şemsettin

2017-10-01

In this study, electrical parameters of the Al/Bi4Ti3O12/p-Si metal-ferroelectric-semiconductor (MFS) structure and their temperature dependence were investigated using current-voltage (I-V) data measured between 120 K and 300 K. Semi-logarithmic I-V plots of the structure revealed that fabricated structure presents two-diode behavior that leads to two sets of ideality factor, reverse saturation current and zero-bias barrier height (BH) values. Obtained results of these parameters suggest that current conduction mechanism (CCM) deviates strongly from thermionic emission theory particularly at low temperatures. High values of interface states and nkT/q-kT/q plot supported the idea of deviation from thermionic emission. In addition, ln(I)-ln(V) plots suggested that CCM varies from one bias region to another and depends on temperature as well. Series resistance values were calculated using Ohm’s law and Cheungs’ functions, and they decreased drastically with increasing temperature.

Estimating parametric phenotypes that determine anthesis date in Zea mays: Challenges in combining ecophysiological models with genetics

PubMed Central

Welch, Stephen M.; White, Jeffrey W.; Thorp, Kelly R.; Bello, Nora M.

2018-01-01

Ecophysiological crop models encode intra-species behaviors using parameters that are presumed to summarize genotypic properties of individual lines or cultivars. These genotype-specific parameters (GSP’s) can be interpreted as quantitative traits that can be mapped or otherwise analyzed, as are more conventional traits. The goal of this study was to investigate the estimation of parameters controlling maize anthesis date with the CERES-Maize model, based on 5,266 maize lines from 11 plantings at locations across the eastern United States. High performance computing was used to develop a database of 356 million simulated anthesis dates in response to four CERES-Maize model parameters. Although the resulting estimates showed high predictive value (R2 = 0.94), three issues presented serious challenges for use of GSP’s as traits. First (expressivity), the model was unable to express the observed data for 168 to 3,339 lines (depending on the combination of site-years), many of which ended up sharing the same parameter value irrespective of genetics. Second, for 2,254 lines, the model reproduced the data, but multiple parameter sets were equally effective (equifinality). Third, parameter values were highly dependent (p<10−6919) on the sets of environments used to estimate them (instability), calling in to question the assumption that they represent fundamental genetic traits. The issues of expressivity, equifinality and instability must be addressed before the genetic mapping of GSP’s becomes a robust means to help solve the genotype-to-phenotype problem in crops. PMID:29672629

Generalized gas-solid adsorption modeling: Single-component equilibria

DOE PAGES

Ladshaw, Austin; Yiacoumi, Sotira; Tsouris, Costas; ...

2015-01-07

Over the last several decades, modeling of gas–solid adsorption at equilibrium has generally been accomplished through the use of isotherms such as the Freundlich, Langmuir, Tóth, and other similar models. While these models are relatively easy to adapt for describing experimental data, their simplicity limits their generality to be used with many different sets of data. This limitation forces engineers and scientists to test each different model in order to evaluate which one can best describe their data. Additionally, the parameters of these models all have a different physical interpretation, which may have an effect on how they can bemore » further extended into kinetic, thermodynamic, and/or mass transfer models for engineering applications. Therefore, it is paramount to adopt not only a more general isotherm model, but also a concise methodology to reliably optimize for and obtain the parameters of that model. A model of particular interest is the Generalized Statistical Thermodynamic Adsorption (GSTA) isotherm. The GSTA isotherm has enormous flexibility, which could potentially be used to describe a variety of different adsorption systems, but utilizing this model can be fairly difficult due to that flexibility. To circumvent this complication, a comprehensive methodology and computer code has been developed that can perform a full equilibrium analysis of adsorption data for any gas-solid system using the GSTA model. The code has been developed in C/C++ and utilizes a Levenberg–Marquardt’s algorithm to handle the non-linear optimization of the model parameters. Since the GSTA model has an adjustable number of parameters, the code iteratively goes through all number of plausible parameters for each data set and then returns the best solution based on a set of scrutiny criteria. Data sets at different temperatures are analyzed serially and then linear correlations with temperature are made for the parameters of the model. The end result is a full set of optimal GSTA parameters, both dimensional and non-dimensional, as well as the corresponding thermodynamic parameters necessary to predict the behavior of the system at temperatures for which data were not available. It will be shown that this code, utilizing the GSTA model, was able to describe a wide variety of gas-solid adsorption systems at equilibrium.In addition, a physical interpretation of these results will be provided, as well as an alternate derivation of the GSTA model, which intends to reaffirm the physical meaning.« less

Prognostics of lithium-ion batteries based on Dempster-Shafer theory and the Bayesian Monte Carlo method

NASA Astrophysics Data System (ADS)

He, Wei; Williard, Nicholas; Osterman, Michael; Pecht, Michael

A new method for state of health (SOH) and remaining useful life (RUL) estimations for lithium-ion batteries using Dempster-Shafer theory (DST) and the Bayesian Monte Carlo (BMC) method is proposed. In this work, an empirical model based on the physical degradation behavior of lithium-ion batteries is developed. Model parameters are initialized by combining sets of training data based on DST. BMC is then used to update the model parameters and predict the RUL based on available data through battery capacity monitoring. As more data become available, the accuracy of the model in predicting RUL improves. Two case studies demonstrating this approach are presented.

Quantifying and predicting Drosophila larvae crawling phenotypes

NASA Astrophysics Data System (ADS)

Günther, Maximilian N.; Nettesheim, Guilherme; Shubeita, George T.

2016-06-01

The fruit fly Drosophila melanogaster is a widely used model for cell biology, development, disease, and neuroscience. The fly’s power as a genetic model for disease and neuroscience can be augmented by a quantitative description of its behavior. Here we show that we can accurately account for the complex and unique crawling patterns exhibited by individual Drosophila larvae using a small set of four parameters obtained from the trajectories of a few crawling larvae. The values of these parameters change for larvae from different genetic mutants, as we demonstrate for fly models of Alzheimer’s disease and the Fragile X syndrome, allowing applications such as genetic or drug screens. Using the quantitative model of larval crawling developed here we use the mutant-specific parameters to robustly simulate larval crawling, which allows estimating the feasibility of laborious experimental assays and aids in their design.

LAGEOS geodetic analysis-SL7.1

NASA Technical Reports Server (NTRS)

Smith, D. E.; Kolenkiewicz, R.; Dunn, P. J.; Klosko, S. M.; Robbins, J. W.; Torrence, M. H.; Williamson, R. G.; Pavlis, E. C.; Douglas, N. B.; Fricke, S. K.

1991-01-01

Laser ranging measurements to the LAGEOS satellite from 1976 through 1989 are related via geodetic and orbital theories to a variety of geodetic and geodynamic parameters. The SL7.1 analyses are explained of this data set including the estimation process for geodetic parameters such as Earth's gravitational constant (GM), those describing the Earth's elasticity properties (Love numbers), and the temporally varying geodetic parameters such as Earth's orientation (polar motion and Delta UT1) and tracking site horizontal tectonic motions. Descriptions of the reference systems, tectonic models, and adopted geodetic constants are provided; these are the framework within which the SL7.1 solution takes place. Estimates of temporal variations in non-conservative force parameters are included in these SL7.1 analyses as well as parameters describing the orbital states at monthly epochs. This information is useful in further refining models used to describe close-Earth satellite behavior. Estimates of intersite motions and individual tracking site motions computed through the network adjustment scheme are given. Tabulations of tracking site eccentricities, data summaries, estimated monthly orbital and force model parameters, polar motion, Earth rotation, and tracking station coordinate results are also provided.

Manipulations of the features of standard video lottery terminal (VLT) games: effects in pathological and non-pathological gamblers.

PubMed

Loba, P; Stewart, S H; Klein, R M; Blackburn, J R

2001-01-01

The present study was conducted to identify game parameters that would reduce the risk of abuse of video lottery terminals (VLTs) by pathological gamblers, while exerting minimal effects on the behavior of non-pathological gamblers. Three manipulations of standard VLT game features were explored. Participants were exposed to: a counter which displayed a running total of money spent; a VLT spinning reels game where participants could no longer "stop" the reels by touching the screen; and sensory feature manipulations. In control conditions, participants were exposed to standard settings for either a spinning reels or a video poker game. Dependent variables were self-ratings of reactions to each set of parameters. A set of 2(3) x 2 x 2 (game manipulation [experimental condition(s) vs. control condition] x game [spinning reels vs. video poker] x gambler status [pathological vs. non-pathological]) repeated measures ANOVAs were conducted on all dependent variables. The findings suggest that the sensory manipulations (i.e., fast speed/sound or slow speed/no sound manipulations) produced the most robust reaction differences. Before advocating harm reduction policies such as lowering sensory features of VLT games to reduce potential harm to pathological gamblers, it is important to replicate findings in a more naturalistic setting, such as a real bar.

Time-spatial model on the dynamics of the proliferation of Aedes aegypti

NASA Astrophysics Data System (ADS)

Gouvêa, Maury Meirelles, Jr.

2017-03-01

Some complex physical systems, such as cellular regulation, ecosystems, and societies, can be represented by local interactions between agents. Then, complex behaviors may emerge. A cellular automaton is a discrete dynamic system with these features. Among the several complex systems, epidemic diseases are given special attention by researchers with respect to their dynamics. Understanding the behavior of an epidemic may well benefit a society. For instance, different proliferation scenarios may be produced and a prevention policy set. This paper presents a new simulation method of the time-spatial spread of the Dengue mosquito with a cellular automaton. Thus, it will be possible to create different dissemination scenarios and preventive policies for these in several regions. Simulations were performed with different initial conditions and parameters as a result of which the behavior of the proposed method was characterized.

Control of collective network chaos.

PubMed

Wagemakers, Alexandre; Barreto, Ernest; Sanjuán, Miguel A F; So, Paul

2014-06-01

Under certain conditions, the collective behavior of a large globally-coupled heterogeneous network of coupled oscillators, as quantified by the macroscopic mean field or order parameter, can exhibit low-dimensional chaotic behavior. Recent advances describe how a small set of "reduced" ordinary differential equations can be derived that captures this mean field behavior. Here, we show that chaos control algorithms designed using the reduced equations can be successfully applied to imperfect realizations of the full network. To systematically study the effectiveness of this technique, we measure the quality of control as we relax conditions that are required for the strict accuracy of the reduced equations, and hence, the controller. Although the effects are network-dependent, we show that the method is effective for surprisingly small networks, for modest departures from global coupling, and even with mild inaccuracy in the estimate of network heterogeneity.

Graphic analysis and multifractal on percolation-based return interval series

NASA Astrophysics Data System (ADS)

Pei, A. Q.; Wang, J.

2015-05-01

A financial time series model is developed and investigated by the oriented percolation system (one of the statistical physics systems). The nonlinear and statistical behaviors of the return interval time series are studied for the proposed model and the real stock market by applying visibility graph (VG) and multifractal detrended fluctuation analysis (MF-DFA). We investigate the fluctuation behaviors of return intervals of the model for different parameter settings, and also comparatively study these fluctuation patterns with those of the real financial data for different threshold values. The empirical research of this work exhibits the multifractal features for the corresponding financial time series. Further, the VGs deviated from both of the simulated data and the real data show the behaviors of small-world, hierarchy, high clustering and power-law tail for the degree distributions.

The Evolution of Psychology as a Basic Bio-behavioral Science in Healthcare Education.

PubMed

Carr, John E

2017-12-01

For over a century, researchers and educators have called for the integration of psychological science into medical school curricula, but such efforts have been impeded by barriers within medicine and psychology. In addressing these barriers, Psychology has re-examined its relationship to Medicine, incorporated psychological practices into health care, and redefined its parameters as a science. In response to interdisciplinary research into the mechanisms of bio-behavioral interaction, Psychology evolved from an ancillary social science to a bio-behavioral science that is fundamental to medicine and health care. However, in recent medical school curriculum innovations, psychological science is being reduced to a set of "clinical skills," and once again viewed as an ancillary social science. These developments warrant concern and consideration of new approaches to integrating psychological science in medical education.

Mechanical behavior and shape optimization of lining structure for subsea tunnel excavated in weathered slot

NASA Astrophysics Data System (ADS)

Li, Peng-fei; Zhou, Xiao-jun

2015-12-01

Subsea tunnel lining structures should be designed to sustain the loads transmitted from surrounding ground and groundwater during excavation. Extremely high pore-water pressure reduces the effective strength of the country rock that surrounds a tunnel, thereby lowering the arching effect and stratum stability of the structure. In this paper, the mechanical behavior and shape optimization of the lining structure for the Xiang'an tunnel excavated in weathered slots are examined. Eight cross sections with different geometric parameters are adopted to study the mechanical behavior and shape optimization of the lining structure. The hyperstatic reaction method is used through finite element analysis software ANSYS. The mechanical behavior of the lining structure is evidently affected by the geometric parameters of crosssectional shape. The minimum safety factor of the lining structure elements is set to be the objective function. The efficient tunnel shape to maximize the minimum safety factor is identified. The minimum safety factor increases significantly after optimization. The optimized cross section significantly improves the mechanical characteristics of the lining structure and effectively reduces its deformation. Force analyses of optimization process and program are conducted parametrically so that the method can be applied to the optimization design of other similar structures. The results obtained from this study enhance our understanding of the mechanical behavior of the lining structure for subsea tunnels. These results are also beneficial to the optimal design of lining structures in general.

Near Identifiability of Dynamical Systems

NASA Technical Reports Server (NTRS)

Hadaegh, F. Y.; Bekey, G. A.

1987-01-01

Concepts regarding approximate mathematical models treated rigorously. Paper presents new results in analysis of structural identifiability, equivalence, and near equivalence between mathematical models and physical processes they represent. Helps establish rigorous mathematical basis for concepts related to structural identifiability and equivalence revealing fundamental requirements, tacit assumptions, and sources of error. "Structural identifiability," as used by workers in this field, loosely translates as meaning ability to specify unique mathematical model and set of model parameters that accurately predict behavior of corresponding physical system.

Celestial mechanics solutions that escape

NASA Astrophysics Data System (ADS)

Gingold, Harry; Solomon, Daniel

2017-08-01

We establish the existence of an open set of initial conditions through which pass solutions without singularities to Newton's gravitational equations in R3 on a semi-infinite interval in forward time, for which every pair of particles separates like At , A > 0, as t → ∞. The solutions are constructable as series with rapid uniform convergence and their asymptotic behavior to any order is prescribed. We show that this family of solutions depends on 6N parameters subject to certain constraints.

Benchmarking Ada tasking on tightly coupled multiprocessor architectures

NASA Technical Reports Server (NTRS)

Collard, Philippe; Goforth, Andre; Marquardt, Matthew

1989-01-01

The development of benchmarks and performance measures for parallel Ada tasking is reported with emphasis on the macroscopic behavior of the benchmark across a set of load parameters. The application chosen for the study was the NASREM model for telerobot control, relevant to many NASA missions. The results of the study demonstrate the potential of parallel Ada in accomplishing the task of developing a control system for a system such as the Flight Telerobotic Servicer using the NASREM framework.

Vision System for Coarsely Estimating Motion Parameters for Unknown Fast Moving Objects in Space

PubMed Central

Chen, Min; Hashimoto, Koichi

2017-01-01

Motivated by biological interests in analyzing navigation behaviors of flying animals, we attempt to build a system measuring their motion states. To do this, in this paper, we build a vision system to detect unknown fast moving objects within a given space, calculating their motion parameters represented by positions and poses. We proposed a novel method to detect reliable interest points from images of moving objects, which can be hardly detected by general purpose interest point detectors. 3D points reconstructed using these interest points are then grouped and maintained for detected objects, according to a careful schedule, considering appearance and perspective changes. In the estimation step, a method is introduced to adapt the robust estimation procedure used for dense point set to the case for sparse set, reducing the potential risk of greatly biased estimation. Experiments are conducted against real scenes, showing the capability of the system of detecting multiple unknown moving objects and estimating their positions and poses. PMID:29206189

Multifaceted Schwinger effect in de Sitter space

NASA Astrophysics Data System (ADS)

Sharma, Ramkishor; Singh, Suprit

2017-07-01

We investigate particle production à la the Schwinger mechanism in an expanding, flat de Sitter patch as is relevant for the inflationary epoch of our Universe. Defining states and particle content in curved spacetime is certainly not a unique process. There being different prescriptions on how that can be done, we have used the Schrödinger formalism to define instantaneous particle content of the state, etc. This allows us to go past the adiabatic regime to which the effect has been restricted in the previous studies and bring out its multifaceted nature in different settings. Each of these settings gives rise to contrasting features and behavior as per the effect of the electric field and expansion rate on the instantaneous mean particle number. We also quantify the degree of classicality of the process during its evolution using a "classicality parameter" constructed out of parameters of the Wigner function to obtain information about the quantum to classical transition in this case.

Reactive flow model development for PBXW-126 using modern nonlinear optimization methods

NASA Astrophysics Data System (ADS)

Murphy, M. J.; Simpson, R. L.; Urtiew, P. A.; Souers, P. C.; Garcia, F.; Garza, R. G.

1996-05-01

The initiation and detonation behavior of PBXW-126 has been characterized and is described. PBXW-126 is a composite explosive consisting of approximately equal amounts of RDX, AP, AL, and NTO with a polyurethane binder. The three term ignition and growth of reaction model parameters (ignition+two growth terms) have been found using nonlinear optimization methods to determine the "best" set of model parameters. The ignition term treats the initiation of up to 0.5% of the RDX. The first growth term in the model treats the RDX growth of reaction up to 20% reacted. The second growth term treats the subsequent growth of reaction of the remaining AP/AL/NTO. The unreacted equation of state (EOS) was determined from the wave profiles of embedded gauge tests while the JWL product EOS was determined from cylinder expansion test results. The nonlinear optimization code, NLQPEB/GLO, was used to determine the "best" set of coefficients for the three term Lee-Tarver ignition and growth of reaction model.

A simple depth-averaged model for dry granular flow

NASA Astrophysics Data System (ADS)

Hung, Chi-Yao; Stark, Colin P.; Capart, Herve

Granular flow over an erodible bed is an important phenomenon in both industrial and geophysical settings. Here we develop a depth-averaged theory for dry erosive flows using balance equations for mass, momentum and (crucially) kinetic energy. We assume a linearized GDR-Midi rheology for granular deformation and Coulomb friction along the sidewalls. The theory predicts the kinematic behavior of channelized flows under a variety of conditions, which we test in two sets of experiments: (1) a linear chute, where abrupt changes in tilt drive unsteady uniform flows; (2) a rotating drum, to explore steady non-uniform flow. The theoretical predictions match the experimental results well in all cases, without the need to tune parameters or invoke an ad hoc equation for entrainment at the base of the flow. Here we focus on the drum problem. A dimensionless rotation rate (related to Froude number) characterizes flow geometry and accounts not just for spin rate, drum radius and gravity, but also for grain size, wall friction and channel width. By incorporating Coriolis force the theory can treat behavior under centrifuge-induced enhanced gravity. We identify asymptotic flow regimes at low and high dimensionless rotation rates that exhibit distinct power-law scaling behaviors.

Lipophilicity indices derived from the liquid chromatographic behavior observed under bimodal retention conditions (reversed phase/hydrophilic interaction): application to a representative set of pyridinium oximes.

PubMed

Voicu, Victor; Sârbu, Costel; Tache, Florentin; Micăle, Florina; Rădulescu, Ştefan Flavian; Sakurada, Koichi; Ohta, Hikoto; Medvedovici, Andrei

2014-05-01

The liquid chromatographic behavior observed under bimodal retention conditions (reversed phase and hydrophilic interaction) offers a new basis for the determination of some derived lipophilicity indices. The experiments were carried out on a representative group (30 compounds) of pyridinium oximes, therapeutically tested in acetylcholinesterase reactivation, covering a large range of lipophilic character. The chromatographic behavior was observed on a mixed mode acting stationary phase, resulting from covalent functionalization of high purity spherical silica with long chain alkyl groups terminated by a polar environment created through the vicinal diol substitution at the lasting carbon atoms (Acclaim Mixed Mode HILIC 1 column). Elution was achieved by combining different proportions of 5 mM ammonium formiate solutions in water and acetonitrile. The derived lipophilicity indices were compared with logP values resulting from different computational algorithms. The correlations between experimental and computed data sets are significant. To obtain a better insight on the transition from reversed phase to hydrophilic interaction retention mechanisms, the variation of the thermodynamic parameters determined through the van׳t Hoff approach was also discussed. Copyright © 2014 Elsevier B.V. All rights reserved.

Control of Superelastic Behavior of NiTi Wires Aided by Thermomechanical Treatment with Reference to Three-Point Bending

NASA Astrophysics Data System (ADS)

Shahmir, Hamed; Nili-Ahmadabadi, Mahmoud; Naghdi, Fariba; Habibi-Parsa, Mohammad; Haririan, Ismaeil

2014-04-01

The aim of this study is to investigate the effect of thermomechanical treatment on the superelastic behavior of a Ti-50.5 at.%Ni wire in terms of loading/unloading plateau, mechanical hysteresis, and permanent set to optimize these parameters for orthodontic applications. A new three-point bending fixture, oral cavity configuration three-point bending (OCTPB) test, was utilized to determine the superelastic property in clinical condition, and therefore, the tests were carried out at 37 °C. The results indicate that the thermomechanical treatment is crucial for thermal transformation and mechanically induced transformation characteristics of the wire. Annealing of thermomechanically treated specimens at 300 and 400 °C for 1/2 and 1 h leads to good superelasticity for orthodontic applications. However, the best superelasticity at body temperature is obtained after annealing at 300 °C for 1/2 h with regard to low and constant unloading force and minimum permanent set.

Message survival and decision dynamics in a class of reactive complex systems subject to external fields

NASA Astrophysics Data System (ADS)

Rodriguez Lucatero, C.; Schaum, A.; Alarcon Ramos, L.; Bernal-Jaquez, R.

2014-07-01

In this study, the dynamics of decisions in complex networks subject to external fields are studied within a Markov process framework using nonlinear dynamical systems theory. A mathematical discrete-time model is derived using a set of basic assumptions regarding the convincement mechanisms associated with two competing opinions. The model is analyzed with respect to the multiplicity of critical points and the stability of extinction states. Sufficient conditions for extinction are derived in terms of the convincement probabilities and the maximum eigenvalues of the associated connectivity matrices. The influences of exogenous (e.g., mass media-based) effects on decision behavior are analyzed qualitatively. The current analysis predicts: (i) the presence of fixed-point multiplicity (with a maximum number of four different fixed points), multi-stability, and sensitivity with respect to the process parameters; and (ii) the bounded but significant impact of exogenous perturbations on the decision behavior. These predictions were verified using a set of numerical simulations based on a scale-free network topology.

Understanding heart rate alarm adjustment in the intensive care units through an analytical approach

PubMed Central

Pelter, Michele M.; Drew, Barbara J.; Palacios, Jorge Arroyo; Bai, Yong; Stannard, Daphne; Aldrich, J. Matt; Hu, Xiao

2017-01-01

Background Heart rate (HR) alarms are prevalent in ICU, and these parameters are configurable. Not much is known about nursing behavior associated with tailoring HR alarm parameters to individual patients to reduce clinical alarm fatigue. Objectives To understand the relationship between heart rate (HR) alarms and adjustments to reduce unnecessary heart rate alarms. Methods Retrospective, quantitative analysis of an adjudicated database using analytical approaches to understand behaviors surrounding parameter HR alarm adjustments. Patients were sampled from five adult ICUs (77 beds) over one month at a quaternary care university medical center. A total of 337 of 461 ICU patients had HR alarms with 53.7% male, mean age 60.3 years, and 39% non-Caucasian. Default HR alarm parameters were 50 and 130 beats per minute (bpm). The occurrence of each alarm, vital signs, and physiologic waveforms was stored in a relational database (SQL server). Results There were 23,624 HR alarms for analysis, with 65.4% exceeding the upper heart rate limit. Only 51% of patients with HR alarms had parameters adjusted, with a median upper limit change of +5 bpm and -1 bpm lower limit. The median time to first HR parameter adjustment was 17.9 hours, without reduction in alarms occurrence (p = 0.57). Conclusions HR alarms are prevalent in ICU, and half of HR alarm settings remain at default. There is a long delay between HR alarms and parameters changes, with insufficient changes to decrease HR alarms. Increasing frequency of HR alarms shortens the time to first adjustment. Best practice guidelines for HR alarm limits are needed to reduce alarm fatigue and improve monitoring precision. PMID:29176776

Short pulse gastric electrical stimulation for cisplatin-induced emesis in dogs.

PubMed

Song, J; Zhong, D-X; Qian, W; Hou, X-H; Chen, J D Z

2011-05-01

In a previous study, we investigated the ameliorating effect of gastric electrical stimulation (GES) with a single set of parameters on emesis and behaviors suggestive of nausea induced by cisplatin in dogs. The aim of this study was to investigate the effects of GES with different parameters on cisplatin-induced emesis in dogs. Seven dogs implanted with gastric serosal electrodes were studied in six randomized sessions: one control session with cisplatin (2 mg kg(-1)) and five sessions with cisplatin plus GES of different parameters: GES-A: 14 Hz, 5 mA, 0.3 ms, 0.1 s on and 5 s off; GES-B: increased frequency and on-time; GES-C: increased frequency; GES-D: increased frequency and pulse width; and GES-E: increased frequency and amplitude. Gastric slow waves and emetic responses were recorded in each session. (i) Cisplatin induced emetic responses and gastric dysrhythmia. The peak time of the emetic response was during the fourth hour after cisplatin. (ii) GES with appropriate parameters reduced cisplatin-induced emesis. The number of vomiting times during the 6 h after cisplatin was 7.0 ± 1.4 in the control, 4.7 ± 1.2 with GES-A (P = 0.179), 4.2 ± 1.2 with GES-B (P = 0.109), 7.0 ± 0.8 with GES-C (P = 0.928), 2.1 ± 0.3 with GES-D (P = 0.005) and 4.7 ± 1.5 with GES-E (P = 0.129). However, none of the GES parameters could improve gastric dysrhythmia. Gastric electrical stimulation with appropriate parameters reduces cisplatin-induced emetic responses and behaviors suggestive of nausea in dogs. Among the tested parameters, GES with increased pulse width seems to produce better relief of cisplatin-induced emesis. © 2011 Blackwell Publishing Ltd.

Linking disease symptoms and subtypes with personalized systems-based phenotypes: A proof of concept study

PubMed Central

Aschbacher, Kirstin; Adam, Emma K.; Crofford, Leslie J.; Kemeny, Margaret E.; Demitrack, Mark A.; Ben-Zvi, Amos

2012-01-01

A dynamic systems model was used to generate parameters describing a phenotype of Hypothalamic–Pituitary–Adrenal (HPA) behavior in a sample of 36 patients with chronic fatigue syndrome (CFS) and/ or fibromyalgia (FM) and 36 case-matched healthy controls. Altered neuroendocrine function, particularly in relation to somatic symptoms and poor sleep quality, may contribute to the pathophysiology of these disorders. Blood plasma was assayed for cortisol and ACTH every 10 min for 24 h. The dynamic model was specified with an ordinary differential equation using three parameters: (1) ACTH-adrenal signaling, (2) inhibitory feedback, and (3) non-ACTH influences. The model was ‘‘personalized’’ by estimating an individualized set of parameters from each participant’s data. Day and nighttime parameters were assessed separately. Two nocturnal parameters (ACTH-adrenal signaling and inhibitory feedback) significantly differentiated the two patient subgroups (“fatigue-predominant” patients with CFS only versus ‘‘pain-predominant’’ patients with FM and comorbid chronic fatigue) from controls (allp’s < .05), whereas daytime parameters and diurnal/nocturnal slopes did not. The same nocturnal parameters were significantly associated with somatic symptoms among patients (p’s < .05). There was a significantly different pattern of association between nocturnal non-ACTH influences and sleep quality among patients versus controls (p < .05). Although speculative, the finding that patient somatic symptoms decreased when more cortisol was produced per unit ACTH, is consistent with cortisol’s anti-inflammatory and sleep-modulatory effects. Patients’ HPA systems may compensate by promoting more rapid or sustained cortisol production. Mapping “behavioral phenotypes” of stress–arousal systems onto symptom clusters may help disentangle the pathophysiology of complex disorders with frequent comorbidity. PMID:22687333

Modeling the [NTf2] pyridinium ionic liquids family and their mixtures with the soft statistical associating fluid theory equation of state.

PubMed

Oliveira, M B; Llovell, F; Coutinho, J A P; Vega, L F

2012-08-02

In this work, the soft statistical associating fluid theory (soft-SAFT) equation of state (EoS) has been used to provide an accurate thermodynamic characterization of the pyridinium-based family of ionic liquids (ILs) with the bis(trifluoromethylsulfonyl)imide anion [NTf(2)](-). On the basis of recent molecular simulation studies for this family, a simple molecular model was proposed within the soft-SAFT EoS framework. The chain length value was transferred from the equivalent imidazolium-based ILs family, while the dispersive energy and the molecular parameters describing the cation-anion interactions were set to constant values for all of the compounds. With these assumptions, an appropriate set of molecular parameters was found for each compound fitting to experimental temperature-density data at atmospheric pressure. Correlations for the nonconstant parameters (describing the volume of the IL) with the molecular weight were established, allowing the prediction of the parameters for other pyridiniums not included in the fitting. Then, the suitability of the proposed model and its optimized parameters were tested by predicting high-pressure densities and second-order thermodynamic derivative properties such as isothermal compressibilities of selected [NTf(2)] pyridinium ILs, in a large range of thermodynamic conditions. The surface tension was also provided using the density gradient theory coupled to the soft-SAFT equation. Finally, the soft-SAFT EoS was applied to describe the phase behavior of several binary mixtures of [NTf(2)] pyridinium ILs with carbon dioxide, sulfur dioxide, and water. In all cases, a temperature-independent binary parameter was enough to reach quantitative agreement with the experimental data. The description of the solubility of CO(2) in these ILs also allowed identification of a relation between the binary parameter and the molecular weight of the ionic liquid, allowing the prediction of the CO(2) + C(12)py[NTf(2)] mixture. The good agreement with the experimental data shows the excellent ability of the soft-SAFT EoS to describe the thermophysical properties of ILs as well as their phase behavior. Results prove that this equation of state can be a valuable tool to assist the design of ILs (in what concerns cation and anion selection) in order to obtain ILs with the desired properties and, consequently, enhancing their potential industrial applications.

Multivariate models for prediction of rheological characteristics of filamentous fermentation broth from the size distribution.

PubMed

Petersen, Nanna; Stocks, Stuart; Gernaey, Krist V

2008-05-01

The main purpose of this article is to demonstrate that principal component analysis (PCA) and partial least squares regression (PLSR) can be used to extract information from particle size distribution data and predict rheological properties. Samples from commercially relevant Aspergillus oryzae fermentations conducted in 550 L pilot scale tanks were characterized with respect to particle size distribution, biomass concentration, and rheological properties. The rheological properties were described using the Herschel-Bulkley model. Estimation of all three parameters in the Herschel-Bulkley model (yield stress (tau(y)), consistency index (K), and flow behavior index (n)) resulted in a large standard deviation of the parameter estimates. The flow behavior index was not found to be correlated with any of the other measured variables and previous studies have suggested a constant value of the flow behavior index in filamentous fermentations. It was therefore chosen to fix this parameter to the average value thereby decreasing the standard deviation of the estimates of the remaining rheological parameters significantly. Using a PLSR model, a reasonable prediction of apparent viscosity (micro(app)), yield stress (tau(y)), and consistency index (K), could be made from the size distributions, biomass concentration, and process information. This provides a predictive method with a high predictive power for the rheology of fermentation broth, and with the advantages over previous models that tau(y) and K can be predicted as well as micro(app). Validation on an independent test set yielded a root mean square error of 1.21 Pa for tau(y), 0.209 Pa s(n) for K, and 0.0288 Pa s for micro(app), corresponding to R(2) = 0.95, R(2) = 0.94, and R(2) = 0.95 respectively. Copyright 2007 Wiley Periodicals, Inc.

Dynamic interaction of monowheel inclined vehicle-vibration platform coupled system with quadratic and cubic nonlinearities

NASA Astrophysics Data System (ADS)

Zhou, Shihua; Song, Guiqiu; Sun, Maojun; Ren, Zhaohui; Wen, Bangchun

2018-01-01

In order to analyze the nonlinear dynamics and stability of a novel design for the monowheel inclined vehicle-vibration platform coupled system (MIV-VPCS) with intermediate nonlinearity support subjected to a harmonic excitation, a multi-degree of freedom lumped parameter dynamic model taking into account the dynamic interaction of the MIV-VPCS with quadratic and cubic nonlinearities is presented. The dynamical equations of the coupled system are derived by applying the displacement relationship, interaction force relationship at the contact position and Lagrange's equation, which are further discretized into a set of nonlinear ordinary differential equations with coupled terms by Galerkin's truncation. Based on the mathematical model, the coupled multi-body nonlinear dynamics of the vibration system is investigated by numerical method, and the parameters influences of excitation amplitude, mass ratio and inclined angle on the dynamic characteristics are precisely analyzed and discussed by bifurcation diagram, Largest Lyapunov exponent and 3-D frequency spectrum. Depending on different ranges of system parameters, the results show that the different motions and jump discontinuity appear, and the coupled system enters into chaotic behavior through different routes (period-doubling bifurcation, inverse period-doubling bifurcation, saddle-node bifurcation and Hopf bifurcation), which are strongly attributed to the dynamic interaction of the MIV-VPCS. The decreasing excitation amplitude and inclined angle could reduce the higher order bifurcations, and effectively control the complicated nonlinear dynamic behaviors under the perturbation of low rotational speed. The first bifurcation and chaotic motion occur at lower value of inclined angle, and the chaotic behavior lasts for larger intervals with higher rotational speed. The investigation results could provide a better understanding of the nonlinear dynamic behaviors for the dynamic interaction of the MIV-VPCS.

Model-based functional neuroimaging using dynamic neural fields: An integrative cognitive neuroscience approach

PubMed Central

Wijeakumar, Sobanawartiny; Ambrose, Joseph P.; Spencer, John P.; Curtu, Rodica

2017-01-01

A fundamental challenge in cognitive neuroscience is to develop theoretical frameworks that effectively span the gap between brain and behavior, between neuroscience and psychology. Here, we attempt to bridge this divide by formalizing an integrative cognitive neuroscience approach using dynamic field theory (DFT). We begin by providing an overview of how DFT seeks to understand the neural population dynamics that underlie cognitive processes through previous applications and comparisons to other modeling approaches. We then use previously published behavioral and neural data from a response selection Go/Nogo task as a case study for model simulations. Results from this study served as the ‘standard’ for comparisons with a model-based fMRI approach using dynamic neural fields (DNF). The tutorial explains the rationale and hypotheses involved in the process of creating the DNF architecture and fitting model parameters. Two DNF models, with similar structure and parameter sets, are then compared. Both models effectively simulated reaction times from the task as we varied the number of stimulus-response mappings and the proportion of Go trials. Next, we directly simulated hemodynamic predictions from the neural activation patterns from each model. These predictions were tested using general linear models (GLMs). Results showed that the DNF model that was created by tuning parameters to capture simultaneously trends in neural activation and behavioral data quantitatively outperformed a Standard GLM analysis of the same dataset. Further, by using the GLM results to assign functional roles to particular clusters in the brain, we illustrate how DNF models shed new light on the neural populations’ dynamics within particular brain regions. Thus, the present study illustrates how an interactive cognitive neuroscience model can be used in practice to bridge the gap between brain and behavior. PMID:29118459

System and method for statistically monitoring and analyzing sensed conditions

DOEpatents

Pebay, Philippe P [Livermore, CA; Brandt, James M [Dublin, CA; Gentile, Ann C [Dublin, CA; Marzouk, Youssef M [Oakland, CA; Hale, Darrian J [San Jose, CA; Thompson, David C [Livermore, CA

2011-01-04

A system and method of monitoring and analyzing a plurality of attributes for an alarm condition is disclosed. The attributes are processed and/or unprocessed values of sensed conditions of a collection of a statistically significant number of statistically similar components subjected to varying environmental conditions. The attribute values are used to compute the normal behaviors of some of the attributes and also used to infer parameters of a set of models. Relative probabilities of some attribute values are then computed and used along with the set of models to determine whether an alarm condition is met. The alarm conditions are used to prevent or reduce the impact of impending failure.

System and method for statistically monitoring and analyzing sensed conditions

DOEpatents

Pebay, Philippe P [Livermore, CA; Brandt, James M [Dublin, CA; Gentile, Ann C [Dublin, CA; Marzouk, Youssef M [Oakland, CA; Hale, Darrian J [San Jose, CA; Thompson, David C [Livermore, CA

2011-01-25

A system and method of monitoring and analyzing a plurality of attributes for an alarm condition is disclosed. The attributes are processed and/or unprocessed values of sensed conditions of a collection of a statistically significant number of statistically similar components subjected to varying environmental conditions. The attribute values are used to compute the normal behaviors of some of the attributes and also used to infer parameters of a set of models. Relative probabilities of some attribute values are then computed and used along with the set of models to determine whether an alarm condition is met. The alarm conditions are used to prevent or reduce the impact of impending failure.

System and method for statistically monitoring and analyzing sensed conditions

DOEpatents

Pebay, Philippe P [Livermore, CA; Brandt, James M. , Gentile; Ann C. , Marzouk; Youssef M. , Hale; Darrian J. , Thompson; David, C [Livermore, CA

2010-07-13

A system and method of monitoring and analyzing a plurality of attributes for an alarm condition is disclosed. The attributes are processed and/or unprocessed values of sensed conditions of a collection of a statistically significant number of statistically similar components subjected to varying environmental conditions. The attribute values are used to compute the normal behaviors of some of the attributes and also used to infer parameters of a set of models. Relative probabilities of some attribute values are then computed and used along with the set of models to determine whether an alarm condition is met. The alarm conditions are used to prevent or reduce the impact of impending failure.

Chaotic evolution of arms races

NASA Astrophysics Data System (ADS)

Tomochi, Masaki; Kono, Mitsuo

1998-12-01

A new set of model equations is proposed to describe the evolution of the arms race, by extending Richardson's model with special emphases that (1) power dependent defensive reaction or historical enmity could be a motive force to promote armaments, (2) a deterrent would suppress the growth of armaments, and (3) the defense reaction of one nation against the other nation depends nonlinearly on the difference in armaments between two. The set of equations is numerically solved to exhibit stationary, periodic, and chaotic behavior depending on the combinations of parameters involved. The chaotic evolution is realized when the economic situation of each country involved in the arms race is quite different, which is often observed in the real world.

Developing custom fire behavior fuel models from ecologically complex fuel structures for upper Atlantic Coastal Plain forests.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parresol, Bernard, R.; Scott, Joe, H.; Andreu, Anne

2012-01-01

Currently geospatial fire behavior analyses are performed with an array of fire behavior modeling systems such as FARSITE, FlamMap, and the Large Fire Simulation System. These systems currently require standard or customized surface fire behavior fuel models as inputs that are often assigned through remote sensing information. The ability to handle hundreds or thousands of measured surface fuelbeds representing the fine scale variation in fire behavior on the landscape is constrained in terms of creating compatible custom fire behavior fuel models. In this study, we demonstrate an objective method for taking ecologically complex fuelbeds from inventory observations and converting thosemore » into a set of custom fuel models that can be mapped to the original landscape. We use an original set of 629 fuel inventory plots measured on an 80,000 ha contiguous landscape in the upper Atlantic Coastal Plain of the southeastern United States. From models linking stand conditions to component fuel loads, we impute fuelbeds for over 6000 stands. These imputed fuelbeds were then converted to fire behavior parameters under extreme fuel moisture and wind conditions (97th percentile) using the fuel characteristic classification system (FCCS) to estimate surface fire rate of spread, surface fire flame length, shrub layer reaction intensity (heat load), non-woody layer reaction intensity, woody layer reaction intensity, and litter-lichen-moss layer reaction intensity. We performed hierarchical cluster analysis of the stands based on the values of the fire behavior parameters. The resulting 7 clusters were the basis for the development of 7 custom fire behavior fuel models from the cluster centroids that were calibrated against the FCCS point data for wind and fuel moisture. The latter process resulted in calibration against flame length as it was difficult to obtain a simultaneous calibration against both rate of spread and flame length. The clusters based on FCCS fire behavior parameters represent reasonably identifiable stand conditions, being: (1) pine dominated stands with more litter and down woody debriscomponents than other stands, (2) hardwood and pine stands with no shrubs, (3) hardwood dominated stands with low shrub and high non-woody biomass and high down woody debris, (4) stands with high grass and forb (i.e., non-woody) biomass as well as substantial shrub biomass, (5) stands with both high shrub and litter biomass, (6) pine-mixed hardwood stands with moderate litter biomass and low shrub biomass, and (7) baldcypress-tupelo stands. Models representing these stand clusters generated flame lengths from 0.6 to 2.3 musing a 30 km h{sub 1} wind speed and fireline intensities of 100-1500 kW m{sub 1} that are typical within the range of experience on this landscape. The fuel models ranked 1 < 2 < 7 < 5 < 4 < 3 < 6 in terms of both flame length and fireline intensity. The method allows for ecologically complex data to be utilized in order to create a landscape representative of measured fuel conditions and to create models that interface with geospatial fire models.« less

A Comparison of Three Approaches to Model Human Behavior

NASA Astrophysics Data System (ADS)

Palmius, Joel; Persson-Slumpi, Thomas

2010-11-01

One way of studying social processes is through the use of simulations. The use of simulations for this purpose has been established as its own field, social simulations, and has been used for studying a variety of phenomena. A simulation of a social setting can serve as an aid for thinking about that social setting, and for experimenting with different parameters and studying the outcomes caused by them. When using the simulation as an aid for thinking and experimenting, the chosen simulation approach will implicitly steer the simulationist towards thinking in a certain fashion in order to fit the model. To study the implications of model choice on the understanding of a setting where human anticipation comes into play, a simulation scenario of a coffee room was constructed using three different simulation approaches: Cellular Automata, Systems Dynamics and Agent-based modeling. The practical implementations of the models were done in three different simulation packages: Stella for Systems Dynamic, CaFun for Cellular automata and SesAM for Agent-based modeling. The models were evaluated both using Randers' criteria for model evaluation, and through introspection where the authors reflected upon how their understanding of the scenario was steered through the model choice. Further the software used for implementing the simulation models was evaluated, and practical considerations for the choice of software package are listed. It is concluded that the models have very different strengths. The Agent-based modeling approach offers the most intuitive support for thinking about and modeling a social setting where the behavior of the individual is in focus. The Systems Dynamics model would be preferable in situations where populations and large groups would be studied as wholes, but where individual behavior is of less concern. The Cellular Automata models would be preferable where processes need to be studied from the basis of a small set of very simple rules. It is further concluded that in most social simulation settings the Agent-based modeling approach would be the probable choice. This since the other models does not offer much in the way of supporting the modeling of the anticipatory behavior of humans acting in an organization.

Aphrodisiac and spermatogenic potential of alkaloidal fraction of Hygrophila spinosa T. Ander in rats.

PubMed

Vyas, Niraj Y; Raval, Manan A

2016-12-24

Seeds of Hygrophila spinosa T. Ander (Acanthaceae) are traditionally used as aphrodisiac and spermatogenic in Indian System of medicine. Preliminary phytochemical screening of plant revealed the presence of alkaloids in seeds. As, alkaloidal fractions of several plants showed aphrodisiac and spermatogenic potential, set of experiments were designed to assess alkaloid enriched fraction of seeds of the plant for spermatogenic and aphrodisiac activity using in vitro and in vivo methods. Alkaloid enriched fraction was prepared and assessed for spermatogenic activity using isolated rat Leydig cells in vitro. The fraction was further evaluated in vivo for spermatogenic and aphrodisiac potential using rat as an experimental animal. Increase in weight of reproductive organs, biochemical evaluation of selected parameters, histological studies of testes and sexual behavioral studies were selected as evaluation parameters for in vivo studies. Isolated rat Leydig cells treated with the fraction showed increased amount of testosterone present in culture media (14.7µg/ml) as compared to that of control (0.8µg/ml). Results of in vivo studies showed increase in serum testosterone level in treated animals (50mg/kg) by (115%), increase in weight of testes (8.0%) as compared to control. Marked improvement in testis histo-architecture of rats evident preliminarily by observing overcrowding of spermatozoa in enlarged lumen of seminiferous tubules in animals treated with testosterone and test fraction. Sertoli cells in treated animals were enlarged with highly granulated cytoplasm. Leydig cells also showed enlarged nucleus and darkly stained cytoplasm as compared to control. Mounting behavior of test animals improved, while latency period was decreased, as observed in behavioral studies. The set studies confirmed the ability of the fraction to stimulate Leydig cells and increased serum testosterone level. Increased testosterone level might be responsible for higher number of spermatozoa in testicular lumen as seen in testicular histology as well as increased libido as observed in behavioral studies. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A model-based analysis of impulsivity using a slot-machine gambling paradigm

PubMed Central

Paliwal, Saee; Petzschner, Frederike H.; Schmitz, Anna Katharina; Tittgemeyer, Marc; Stephan, Klaas E.

2014-01-01

Impulsivity plays a key role in decision-making under uncertainty. It is a significant contributor to problem and pathological gambling (PG). Standard assessments of impulsivity by questionnaires, however, have various limitations, partly because impulsivity is a broad, multi-faceted concept. What remains unclear is which of these facets contribute to shaping gambling behavior. In the present study, we investigated impulsivity as expressed in a gambling setting by applying computational modeling to data from 47 healthy male volunteers who played a realistic, virtual slot-machine gambling task. Behaviorally, we found that impulsivity, as measured independently by the 11th revision of the Barratt Impulsiveness Scale (BIS-11), correlated significantly with an aggregate read-out of the following gambling responses: bet increases (BIs), machines switches (MS), casino switches (CS), and double-ups (DUs). Using model comparison, we compared a set of hierarchical Bayesian belief-updating models, i.e., the Hierarchical Gaussian Filter (HGF) and Rescorla–Wagner reinforcement learning (RL) models, with regard to how well they explained different aspects of the behavioral data. We then examined the construct validity of our winning models with multiple regression, relating subject-specific model parameter estimates to the individual BIS-11 total scores. In the most predictive model (a three-level HGF), the two free parameters encoded uncertainty-dependent mechanisms of belief updates and significantly explained BIS-11 variance across subjects. Furthermore, in this model, decision noise was a function of trial-wise uncertainty about winning probability. Collectively, our results provide a proof of concept that hierarchical Bayesian models can characterize the decision-making mechanisms linked to the impulsive traits of an individual. These novel indices of gambling mechanisms unmasked during actual play may be useful for online prevention measures for at-risk players and future assessments of PG. PMID:25071497

Computational intelligence models to predict porosity of tablets using minimum features

PubMed Central

Khalid, Mohammad Hassan; Kazemi, Pezhman; Perez-Gandarillas, Lucia; Michrafy, Abderrahim; Szlęk, Jakub; Jachowicz, Renata; Mendyk, Aleksander

2017-01-01

The effects of different formulations and manufacturing process conditions on the physical properties of a solid dosage form are of importance to the pharmaceutical industry. It is vital to have in-depth understanding of the material properties and governing parameters of its processes in response to different formulations. Understanding the mentioned aspects will allow tighter control of the process, leading to implementation of quality-by-design (QbD) practices. Computational intelligence (CI) offers an opportunity to create empirical models that can be used to describe the system and predict future outcomes in silico. CI models can help explore the behavior of input parameters, unlocking deeper understanding of the system. This research endeavor presents CI models to predict the porosity of tablets created by roll-compacted binary mixtures, which were milled and compacted under systematically varying conditions. CI models were created using tree-based methods, artificial neural networks (ANNs), and symbolic regression trained on an experimental data set and screened using root-mean-square error (RMSE) scores. The experimental data were composed of proportion of microcrystalline cellulose (MCC) (in percentage), granule size fraction (in micrometers), and die compaction force (in kilonewtons) as inputs and porosity as an output. The resulting models show impressive generalization ability, with ANNs (normalized root-mean-square error [NRMSE] =1%) and symbolic regression (NRMSE =4%) as the best-performing methods, also exhibiting reliable predictive behavior when presented with a challenging external validation data set (best achieved symbolic regression: NRMSE =3%). Symbolic regression demonstrates the transition from the black box modeling paradigm to more transparent predictive models. Predictive performance and feature selection behavior of CI models hints at the most important variables within this factor space. PMID:28138223

Computational intelligence models to predict porosity of tablets using minimum features.

PubMed

Khalid, Mohammad Hassan; Kazemi, Pezhman; Perez-Gandarillas, Lucia; Michrafy, Abderrahim; Szlęk, Jakub; Jachowicz, Renata; Mendyk, Aleksander

2017-01-01

The effects of different formulations and manufacturing process conditions on the physical properties of a solid dosage form are of importance to the pharmaceutical industry. It is vital to have in-depth understanding of the material properties and governing parameters of its processes in response to different formulations. Understanding the mentioned aspects will allow tighter control of the process, leading to implementation of quality-by-design (QbD) practices. Computational intelligence (CI) offers an opportunity to create empirical models that can be used to describe the system and predict future outcomes in silico. CI models can help explore the behavior of input parameters, unlocking deeper understanding of the system. This research endeavor presents CI models to predict the porosity of tablets created by roll-compacted binary mixtures, which were milled and compacted under systematically varying conditions. CI models were created using tree-based methods, artificial neural networks (ANNs), and symbolic regression trained on an experimental data set and screened using root-mean-square error (RMSE) scores. The experimental data were composed of proportion of microcrystalline cellulose (MCC) (in percentage), granule size fraction (in micrometers), and die compaction force (in kilonewtons) as inputs and porosity as an output. The resulting models show impressive generalization ability, with ANNs (normalized root-mean-square error [NRMSE] =1%) and symbolic regression (NRMSE =4%) as the best-performing methods, also exhibiting reliable predictive behavior when presented with a challenging external validation data set (best achieved symbolic regression: NRMSE =3%). Symbolic regression demonstrates the transition from the black box modeling paradigm to more transparent predictive models. Predictive performance and feature selection behavior of CI models hints at the most important variables within this factor space.

Temporal variability and social heterogeneity in disease transmission: the case of SARS in Hong Kong.

PubMed

Cori, Anne; Boëlle, Pierre-Yves; Thomas, Guy; Leung, Gabriel M; Valleron, Alain-Jacques

2009-08-01

The extent to which self-adopted or intervention-related changes in behaviors affect the course of epidemics remains a key issue for outbreak control. This study attempted to quantify the effect of such changes on the risk of infection in different settings, i.e., the community and hospitals. The 2002-2003 severe acute respiratory syndrome (SARS) outbreak in Hong Kong, where 27% of cases were healthcare workers, was used as an example. A stochastic compartmental SEIR (susceptible-exposed-infectious-removed) model was used: the population was split into healthcare workers, hospitalized people and general population. Super spreading events (SSEs) were taken into account in the model. The temporal evolutions of the daily effective contact rates in the community and hospitals were modeled with smooth functions. Data augmentation techniques and Markov chain Monte Carlo (MCMC) methods were applied to estimate SARS epidemiological parameters. In particular, estimates of daily reproduction numbers were provided for each subpopulation. The average duration of the SARS infectious period was estimated to be 9.3 days (+/-0.3 days). The model was able to disentangle the impact of the two SSEs from background transmission rates. The effective contact rates, which were estimated on a daily basis, decreased with time, reaching zero inside hospitals. This observation suggests that public health measures and possible changes in individual behaviors effectively reduced transmission, especially in hospitals. The temporal patterns of reproduction numbers were similar for healthcare workers and the general population, indicating that on average, an infectious healthcare worker did not infect more people than any other infectious person. We provide a general method to estimate time dependence of parameters in structured epidemic models, which enables investigation of the impact of control measures and behavioral changes in different settings.

Age-related changes in visual exploratory behavior in a natural scene setting

PubMed Central

Hamel, Johanna; De Beukelaer, Sophie; Kraft, Antje; Ohl, Sven; Audebert, Heinrich J.; Brandt, Stephan A.

2013-01-01

Diverse cognitive functions decline with increasing age, including the ability to process central and peripheral visual information in a laboratory testing situation (useful visual field of view). To investigate whether and how this influences activities of daily life, we studied age-related changes in visual exploratory behavior in a natural scene setting: a driving simulator paradigm of variable complexity was tested in subjects of varying ages with simultaneous eye- and head-movement recordings via a head-mounted camera. Detection and reaction times were also measured by visual fixation and manual reaction. We considered video computer game experience as a possible influence on performance. Data of 73 participants of varying ages were analyzed, driving two different courses. We analyzed the influence of route difficulty level, age, and eccentricity of test stimuli on oculomotor and driving behavior parameters. No significant age effects were found regarding saccadic parameters. In the older subjects head-movements increasingly contributed to gaze amplitude. More demanding courses and more peripheral stimuli locations induced longer reaction times in all age groups. Deterioration of the functionally useful visual field of view with increasing age was not suggested in our study group. However, video game-experienced subjects revealed larger saccade amplitudes and a broader distribution of fixations on the screen. They reacted faster to peripheral objects suggesting the notion of a general detection task rather than perceiving driving as a central task. As the video game-experienced population consisted of younger subjects, our study indicates that effects due to video game experience can easily be misinterpreted as age effects if not accounted for. We therefore view it as essential to consider video game experience in all testing methods using virtual media. PMID:23801970

How does a specific learning and memory system in the mammalian brain gain control of behavior?

PubMed

McDonald, Robert J; Hong, Nancy S

2013-11-01

This review addresses a fundamental, yet poorly understood set of issues in systems neuroscience. The issues revolve around conceptualizations of the organization of learning and memory in the mammalian brain. One intriguing, and somewhat popular, conceptualization is the idea that there are multiple learning and memory systems in the mammalian brain and they interact in different ways to influence and/or control behavior. This approach has generated interesting empirical and theoretical work supporting this view. One issue that needs to be addressed is how these systems influence or gain control of voluntary behavior. To address this issue, we clearly specify what we mean by a learning and memory system. We then review two types of processes that might influence which memory system gains control of behavior. One set of processes are external factors that can affect which system controls behavior in a given situation including task parameters like the kind of information available to the subject, types of training experience, and amount of training. The second set of processes are brain mechanisms that might influence what memory system controls behavior in a given situation including executive functions mediated by the prefrontal cortex; switching mechanisms mediated by ascending neurotransmitter systems, the unique role of the hippocampus during learning. The issue of trait differences in control of different learning and memory systems will also be considered in which trait differences in learning and memory function are thought to potentially emerge from differences in level of prefrontal influence, differences in plasticity processes, differences in ascending neurotransmitter control, differential access to effector systems like motivational and motor systems. Finally, we present scenarios in which different mechanisms might interact. This review was conceived to become a jumping off point for new work directed at understanding these issues. The outcome of this work, in combination with other approaches, might improve understanding of the mechanisms of volition in human and non-human animals. Copyright © 2013 Wiley Periodicals, Inc.

Extrusion and rheology of fine particulate ceramic pastes

NASA Astrophysics Data System (ADS)

Mazzeo, Fred Anthony

A rheological study was conducted on an extruded blend of two alumina powders, Alcoa A-3500-SG and Reynolds ERC. These extruded blends were mixed in four compositions, varying in distribution modulus. This work focuses on the interaction of the composition components, mainly particle size distribution and amount of water at a constant binder amount. The rheological parameters of extruded pastes, Sigma, Tau, alpha and beta, were determined by using capillary rheometry modeling by the methodology set forth by Benbow and Bridgwater. This methodology makes use of capillary rheometer to determine extrusion parameters, which describe the flow behavior of a paste. The parameter values are indirectly determined by extrapolating high shear rate information obtained by the extrusion process. A goal of this research was to determine fundamental rheological properties directly from fundamental rheological equations of state. This was accomplished by assessing the material properties by using a dynamic stress rheometer. The rheological parameters used in this study to characterize the paste are elastic modulus, viscosity, tan delta, and relaxation time. This technique approaches a step closer in understanding the microstructural influence on flow behavior of a paste. This method directly determines rheological properties by using linear viscoelastic theory, giving a quantitative analysis of material properties. A strong correlation between the elastic modulus and sigma, and viscosity and alpha is shown to exist, indicating a relationship between these two techniques. Predictive process control methodology, based on particle packing modeling, quantitatively determined structural parameters useful in evaluating a composition. The determined parameters are: distribution modulus, interparticle separation distance, porosity, and particle crowding index, which are important to understand the extrudates packed state. A connection between the physical structure of the extrudate and its rheological behavior, can lead to a better understanding of what conditions and parameters are necessary to characterize the extrusion process. This study shows how particle packing and particle size influences the rheological behavior of the paste. Results showed that an optimally packed system was found to occur at a distribution modulus of 0.51. This system was determined both experimentally and quantitatively to exhibit the lowest porosity at any water content. The 0.51 system required a lower amount of water to extrude and the parameters of both rheological techniques agreed well, in which all parameters are influenced by the packing state of the paste, and a consistent trend was generally found. The capillary rheometry results can be explained by the strong interaction of particles that occurs at high shear rates. The dynamic stress rheometer results can be explained by the particle packing characteristics, interparticle separation distance and particle-crowding index, and the capillary forces between particles. The excess amount of liquid that is present in the structure decreases the role of the capillary attraction between particles and an increase in the particle size role on the rheological behavior of the pastes occurs.

Development of type transfer functions for regional-scale nonpoint source groundwater vulnerability assessments

NASA Astrophysics Data System (ADS)

Stewart, Iris T.; Loague, Keith

2003-12-01

Groundwater vulnerability assessments of nonpoint source agrochemical contamination at regional scales are either qualitative in nature or require prohibitively costly computational efforts. By contrast, the type transfer function (TTF) modeling approach for vadose zone pesticide leaching presented here estimates solute concentrations at a depth of interest, only uses available soil survey, climatic, and irrigation information, and requires minimal computational cost for application. TTFs are soil texture based travel time probability density functions that describe a characteristic leaching behavior for soil profiles with similar soil hydraulic properties. Seven sets of TTFs, representing different levels of upscaling, were developed for six loam soil textural classes with the aid of simulated breakthrough curves from synthetic data sets. For each TTF set, TTFs were determined from a group or subgroup of breakthrough curves for each soil texture by identifying the effective parameters of the function that described the average leaching behavior of the group. The grouping of the breakthrough curves was based on the TTF index, a measure of the magnitude of the peak concentration, the peak arrival time, and the concentration spread. Comparison to process-based simulations show that the TTFs perform well with respect to mass balance, concentration magnitude, and the timing of concentration peaks. Sets of TTFs based on individual soil textures perform better for all the evaluation criteria than sets that span all textures. As prediction accuracy and computational cost increase with the number of TTFs in a set, the selection of a TTF set is determined by a given application.

The Behavioral Space of Zebrafish Locomotion and Its Neural Network Analog.

PubMed

Girdhar, Kiran; Gruebele, Martin; Chemla, Yann R

2015-01-01

How simple is the underlying control mechanism for the complex locomotion of vertebrates? We explore this question for the swimming behavior of zebrafish larvae. A parameter-independent method, similar to that used in studies of worms and flies, is applied to analyze swimming movies of fish. The motion itself yields a natural set of fish "eigenshapes" as coordinates, rather than the experimenter imposing a choice of coordinates. Three eigenshape coordinates are sufficient to construct a quantitative "postural space" that captures >96% of the observed zebrafish locomotion. Viewed in postural space, swim bouts are manifested as trajectories consisting of cycles of shapes repeated in succession. To classify behavioral patterns quantitatively and to understand behavioral variations among an ensemble of fish, we construct a "behavioral space" using multi-dimensional scaling (MDS). This method turns each cycle of a trajectory into a single point in behavioral space, and clusters points based on behavioral similarity. Clustering analysis reveals three known behavioral patterns-scoots, turns, rests-but shows that these do not represent discrete states, but rather extremes of a continuum. The behavioral space not only classifies fish by their behavior but also distinguishes fish by age. With the insight into fish behavior from postural space and behavioral space, we construct a two-channel neural network model for fish locomotion, which produces strikingly similar postural space and behavioral space dynamics compared to real zebrafish.

The Behavioral Space of Zebrafish Locomotion and Its Neural Network Analog

PubMed Central

Girdhar, Kiran; Gruebele, Martin; Chemla, Yann R.

2015-01-01

How simple is the underlying control mechanism for the complex locomotion of vertebrates? We explore this question for the swimming behavior of zebrafish larvae. A parameter-independent method, similar to that used in studies of worms and flies, is applied to analyze swimming movies of fish. The motion itself yields a natural set of fish "eigenshapes" as coordinates, rather than the experimenter imposing a choice of coordinates. Three eigenshape coordinates are sufficient to construct a quantitative "postural space" that captures >96% of the observed zebrafish locomotion. Viewed in postural space, swim bouts are manifested as trajectories consisting of cycles of shapes repeated in succession. To classify behavioral patterns quantitatively and to understand behavioral variations among an ensemble of fish, we construct a "behavioral space" using multi-dimensional scaling (MDS). This method turns each cycle of a trajectory into a single point in behavioral space, and clusters points based on behavioral similarity. Clustering analysis reveals three known behavioral patterns—scoots, turns, rests—but shows that these do not represent discrete states, but rather extremes of a continuum. The behavioral space not only classifies fish by their behavior but also distinguishes fish by age. With the insight into fish behavior from postural space and behavioral space, we construct a two-channel neural network model for fish locomotion, which produces strikingly similar postural space and behavioral space dynamics compared to real zebrafish. PMID:26132396

LS-DYNA Simulation of Hemispherical-punch Stamping Process Using an Efficient Algorithm for Continuum Damage Based Elastoplastic Constitutive Equation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Salajegheh, Nima; Abedrabbo, Nader; Pourboghrat, Farhang

An efficient integration algorithm for continuum damage based elastoplastic constitutive equations is implemented in LS-DYNA. The isotropic damage parameter is defined as the ratio of the damaged surface area over the total cross section area of the representative volume element. This parameter is incorporated into the integration algorithm as an internal variable. The developed damage model is then implemented in the FEM code LS-DYNA as user material subroutine (UMAT). Pure stretch experiments of a hemispherical punch are carried out for copper sheets and the results are compared against the predictions of the implemented damage model. Evaluation of damage parameters ismore » carried out and the optimized values that correctly predicted the failure in the sheet are reported. Prediction of failure in the numerical analysis is performed through element deletion using the critical damage value. The set of failure parameters which accurately predict the failure behavior in copper sheets compared to experimental data is reported as well.« less

Advance Preparation in Task-Switching: Converging Evidence from Behavioral, Brain Activation, and Model-Based Approaches

PubMed Central

Karayanidis, Frini; Jamadar, Sharna; Ruge, Hannes; Phillips, Natalie; Heathcote, Andrew; Forstmann, Birte U.

2010-01-01

Recent research has taken advantage of the temporal and spatial resolution of event-related brain potentials (ERPs) and functional magnetic resonance imaging (fMRI) to identify the time course and neural circuitry of preparatory processes required to switch between different tasks. Here we overview some key findings contributing to understanding strategic processes in advance preparation. Findings from these methodologies are compatible with advance preparation conceptualized as a set of processes activated for both switch and repeat trials, but with substantial variability as a function of individual differences and task requirements. We then highlight new approaches that attempt to capitalize on this variability to link behavior and brain activation patterns. One approach examines correlations among behavioral, ERP and fMRI measures. A second “model-based” approach accounts for differences in preparatory processes by estimating quantitative model parameters that reflect latent psychological processes. We argue that integration of behavioral and neuroscientific methodologies is key to understanding the complex nature of advance preparation in task-switching. PMID:21833196

A Sensitivity Analysis Method to Study the Behavior of Complex Process-based Models

NASA Astrophysics Data System (ADS)

Brugnach, M.; Neilson, R.; Bolte, J.

2001-12-01

The use of process-based models as a tool for scientific inquiry is becoming increasingly relevant in ecosystem studies. Process-based models are artificial constructs that simulate the system by mechanistically mimicking the functioning of its component processes. Structurally, a process-based model can be characterized, in terms of its processes and the relationships established among them. Each process comprises a set of functional relationships among several model components (e.g., state variables, parameters and input data). While not encoded explicitly, the dynamics of the model emerge from this set of components and interactions organized in terms of processes. It is the task of the modeler to guarantee that the dynamics generated are appropriate and semantically equivalent to the phenomena being modeled. Despite the availability of techniques to characterize and understand model behavior, they do not suffice to completely and easily understand how a complex process-based model operates. For example, sensitivity analysis studies model behavior by determining the rate of change in model output as parameters or input data are varied. One of the problems with this approach is that it considers the model as a "black box", and it focuses on explaining model behavior by analyzing the relationship input-output. Since, these models have a high degree of non-linearity, understanding how the input affects an output can be an extremely difficult task. Operationally, the application of this technique may constitute a challenging task because complex process-based models are generally characterized by a large parameter space. In order to overcome some of these difficulties, we propose a method of sensitivity analysis to be applicable to complex process-based models. This method focuses sensitivity analysis at the process level, and it aims to determine how sensitive the model output is to variations in the processes. Once the processes that exert the major influence in the output are identified, the causes of its variability can be found. Some of the advantages of this approach are that it reduces the dimensionality of the search space, it facilitates the interpretation of the results and it provides information that allows exploration of uncertainty at the process level, and how it might affect model output. We present an example using the vegetation model BIOME-BGC.

Nonlinear mechanical behavior of thermoplastic matrix materials for advanced composites

NASA Technical Reports Server (NTRS)

Arenz, R. J.; Landel, R. F.

1989-01-01

Two recent theories of nonlinear mechanical response are quantitatively compared and related to experimental data. Computer techniques are formulated to handle the numerical integration and iterative procedures needed to solve the associated sets of coupled nonlinear differential equations. Problems encountered during these formulations are discussed and some open questions described. Bearing in mind these cautions, the consequences of changing parameters that appear in the formulations on the resulting engineering properties are discussed. Hence, engineering approaches to the analysis of thermoplastic matrix material can be suggested.

Analytical redundancy management mechanization and flight data analysis for the F-8 digital fly-by-wire aircraft flight control sensors

NASA Technical Reports Server (NTRS)

Deckert, J. C.

1983-01-01

The details are presented of an onboard digital computer algorithm designed to reliably detect and isolate the first failure in a duplex set of flight control sensors aboard the NASA F-8 digital fly-by-wire aircraft. The algorithm's successful flight test program is summarized, and specific examples are presented of algorithm behavior in response to software-induced signal faults, both with and without aircraft parameter modeling errors.

Prediction and Computation of Corrosion Rates of A36 Mild Steel in Oilfield Seawater

NASA Astrophysics Data System (ADS)

Paul, Subir; Mondal, Rajdeep

2018-04-01

The parameters which primarily control the corrosion rate and life of steel structures are several and they vary across the different ocean and seawater as well as along the depth. While the effect of single parameter on corrosion behavior is known, the conjoint effects of multiple parameters and the interrelationship among the variables are complex. Millions sets of experiments are required to understand the mechanism of corrosion failure. Statistical modeling such as ANN is one solution that can reduce the number of experimentation. ANN model was developed using 170 sets of experimental data of A35 mild steel in simulated seawater, varying the corrosion influencing parameters SO4 2-, Cl-, HCO3 -,CO3 2-, CO2, O2, pH and temperature as input and the corrosion current as output. About 60% of experimental data were used to train the model, 20% for testing and 20% for validation. The model was developed by programming in Matlab. 80% of the validated data could predict the corrosion rate correctly. Corrosion rates predicted by the ANN model are displayed in 3D graphics which show many interesting phenomenon of the conjoint effects of multiple variables that might throw new ideas of mitigation of corrosion by simply modifying the chemistry of the constituents. The model could predict the corrosion rates of some real systems.

Solar Radiation Pressure Binning for the Geosynchronous Orbit

NASA Technical Reports Server (NTRS)

Hejduk, M. D.; Ghrist, R. W.

2011-01-01

Orbital maintenance parameters for individual satellites or groups of satellites have traditionally been set by examining orbital parameters alone, such as through apogee and perigee height binning; this approach ignored the other factors that governed an individual satellite's susceptibility to non-conservative forces. In the atmospheric drag regime, this problem has been addressed by the introduction of the "energy dissipation rate," a quantity that represents the amount of energy being removed from the orbit; such an approach is able to consider both atmospheric density and satellite frontal area characteristics and thus serve as a mechanism for binning satellites of similar behavior. The geo-synchronous orbit (of broader definition than the geostationary orbit -- here taken to be from 1300 to 1800 minutes in orbital period) is not affected by drag; rather, its principal non-conservative force is that of solar radiation pressure -- the momentum imparted to the satellite by solar radiometric energy. While this perturbation is solved for as part of the orbit determination update, no binning or division scheme, analogous to the drag regime, has been developed for the geo-synchronous orbit. The present analysis has begun such an effort by examining the behavior of geosynchronous rocket bodies and non-stabilized payloads as a function of solar radiation pressure susceptibility. A preliminary examination of binning techniques used in the drag regime gives initial guidance regarding the criteria for useful bin divisions. Applying these criteria to the object type, solar radiation pressure, and resultant state vector accuracy for the analyzed dataset, a single division of "large" satellites into two bins for the purposes of setting related sensor tasking and orbit determination (OD) controls is suggested. When an accompanying analysis of high area-to-mass objects is complete, a full set of binning recommendations for the geosynchronous orbit will be available.

Cell shape characterization and classification with discrete Fourier transforms and self-organizing maps.

PubMed

Kriegel, Fabian L; Köhler, Ralf; Bayat-Sarmadi, Jannike; Bayerl, Simon; Hauser, Anja E; Niesner, Raluca; Luch, Andreas; Cseresnyes, Zoltan

2018-03-01

Cells in their natural environment often exhibit complex kinetic behavior and radical adjustments of their shapes. This enables them to accommodate to short- and long-term changes in their surroundings under physiological and pathological conditions. Intravital multi-photon microscopy is a powerful tool to record this complex behavior. Traditionally, cell behavior is characterized by tracking the cells' movements, which yields numerous parameters describing the spatiotemporal characteristics of cells. Cells can be classified according to their tracking behavior using all or a subset of these kinetic parameters. This categorization can be supported by the a priori knowledge of experts. While such an approach provides an excellent starting point for analyzing complex intravital imaging data, faster methods are required for automated and unbiased characterization. In addition to their kinetic behavior, the 3D shape of these cells also provide essential clues about the cells' status and functionality. New approaches that include the study of cell shapes as well may also allow the discovery of correlations amongst the track- and shape-describing parameters. In the current study, we examine the applicability of a set of Fourier components produced by Discrete Fourier Transform (DFT) as a tool for more efficient and less biased classification of complex cell shapes. By carrying out a number of 3D-to-2D projections of surface-rendered cells, the applied method reduces the more complex 3D shape characterization to a series of 2D DFTs. The resulting shape factors are used to train a Self-Organizing Map (SOM), which provides an unbiased estimate for the best clustering of the data, thereby characterizing groups of cells according to their shape. We propose and demonstrate that such shape characterization is a powerful addition to, or a replacement for kinetic analysis. This would make it especially useful in situations where live kinetic imaging is less practical or not possible at all. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

Modeling Temporal Behavior in Large Networks: A Dynamic Mixed-Membership Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rossi, R; Gallagher, B; Neville, J

Given a large time-evolving network, how can we model and characterize the temporal behaviors of individual nodes (and network states)? How can we model the behavioral transition patterns of nodes? We propose a temporal behavior model that captures the 'roles' of nodes in the graph and how they evolve over time. The proposed dynamic behavioral mixed-membership model (DBMM) is scalable, fully automatic (no user-defined parameters), non-parametric/data-driven (no specific functional form or parameterization), interpretable (identifies explainable patterns), and flexible (applicable to dynamic and streaming networks). Moreover, the interpretable behavioral roles are generalizable, computationally efficient, and natively supports attributes. We applied ourmore » model for (a) identifying patterns and trends of nodes and network states based on the temporal behavior, (b) predicting future structural changes, and (c) detecting unusual temporal behavior transitions. We use eight large real-world datasets from different time-evolving settings (dynamic and streaming). In particular, we model the evolving mixed-memberships and the corresponding behavioral transitions of Twitter, Facebook, IP-Traces, Email (University), Internet AS, Enron, Reality, and IMDB. The experiments demonstrate the scalability, flexibility, and effectiveness of our model for identifying interesting patterns, detecting unusual structural transitions, and predicting the future structural changes of the network and individual nodes.« less

Homogeneous quantum electrodynamic turbulence

NASA Technical Reports Server (NTRS)

Shebalin, John V.

1992-01-01

The electromagnetic field equations and Dirac equations for oppositely charged wave functions are numerically time-integrated using a spatial Fourier method. The numerical approach used, a spectral transform technique, is based on a continuum representation of physical space. The coupled classical field equations contain a dimensionless parameter which sets the strength of the nonlinear interaction (as the parameter increases, interaction volume decreases). For a parameter value of unity, highly nonlinear behavior in the time-evolution of an individual wave function, analogous to ideal fluid turbulence, is observed. In the truncated Fourier representation which is numerically implemented here, the quantum turbulence is homogeneous but anisotropic and manifests itself in the nonlinear evolution of equilibrium modal spatial spectra for the probability density of each particle and also for the electromagnetic energy density. The results show that nonlinearly interacting fermionic wave functions quickly approach a multi-mode, dynamic equilibrium state, and that this state can be determined by numerical means.

The Problem of Spectral Mimicry of Supergiants

NASA Astrophysics Data System (ADS)

Klochkova, V. G.; Chentsov, E. L.

2018-01-01

The phenomenon of spectral mimicry refers to the fact that hypergiants and post-AGB supergiants—stars of different masses in fundamentally different stages of their evolution—have similar optical spectra, and also share certain other characteristics (unstable extended atmospheres, expanding dust-gas envelopes, high IR excesses). As a consequence, it is not always possible to distinguish post-AGB stars from hypergiants based on individual spectral observations in the optical. Examples of spectral mimicry are analyzed using uniform, high-quality spectral material obtained on the 6-m telescope of the Special Astrophysical Observatory in the course of long-term monitoring of high-luminosity stars. It is shown that unambiguously resolving the mimicry problem for individual stars requires the determination of a whole set of parameters: luminosity, wind parameters, spectral energy distribution, spectral features, velocity field in the atmosphere and circumstellar medium, behavior of the parameters with time, and the chemical composition of the atmosphere.

Herding, minority game, market clearing and efficient markets in a simple spin model framework

NASA Astrophysics Data System (ADS)

Kristoufek, Ladislav; Vosvrda, Miloslav

2018-01-01

We present a novel approach towards the financial Ising model. Most studies utilize the model to find settings which generate returns closely mimicking the financial stylized facts such as fat tails, volatility clustering and persistence, and others. We tackle the model utility from the other side and look for the combination of parameters which yields return dynamics of the efficient market in the view of the efficient market hypothesis. Working with the Ising model, we are able to present nicely interpretable results as the model is based on only two parameters. Apart from showing the results of our simulation study, we offer a new interpretation of the Ising model parameters via inverse temperature and entropy. We show that in fact market frictions (to a certain level) and herding behavior of the market participants do not go against market efficiency but what is more, they are needed for the markets to be efficient.

JuPOETs: a constrained multiobjective optimization approach to estimate biochemical model ensembles in the Julia programming language.

PubMed

Bassen, David M; Vilkhovoy, Michael; Minot, Mason; Butcher, Jonathan T; Varner, Jeffrey D

2017-01-25

Ensemble modeling is a promising approach for obtaining robust predictions and coarse grained population behavior in deterministic mathematical models. Ensemble approaches address model uncertainty by using parameter or model families instead of single best-fit parameters or fixed model structures. Parameter ensembles can be selected based upon simulation error, along with other criteria such as diversity or steady-state performance. Simulations using parameter ensembles can estimate confidence intervals on model variables, and robustly constrain model predictions, despite having many poorly constrained parameters. In this software note, we present a multiobjective based technique to estimate parameter or models ensembles, the Pareto Optimal Ensemble Technique in the Julia programming language (JuPOETs). JuPOETs integrates simulated annealing with Pareto optimality to estimate ensembles on or near the optimal tradeoff surface between competing training objectives. We demonstrate JuPOETs on a suite of multiobjective problems, including test functions with parameter bounds and system constraints as well as for the identification of a proof-of-concept biochemical model with four conflicting training objectives. JuPOETs identified optimal or near optimal solutions approximately six-fold faster than a corresponding implementation in Octave for the suite of test functions. For the proof-of-concept biochemical model, JuPOETs produced an ensemble of parameters that gave both the mean of the training data for conflicting data sets, while simultaneously estimating parameter sets that performed well on each of the individual objective functions. JuPOETs is a promising approach for the estimation of parameter and model ensembles using multiobjective optimization. JuPOETs can be adapted to solve many problem types, including mixed binary and continuous variable types, bilevel optimization problems and constrained problems without altering the base algorithm. JuPOETs is open source, available under an MIT license, and can be installed using the Julia package manager from the JuPOETs GitHub repository.

The Franco-American macaque experiment. [bone demineralization of monkeys on Space Shuttle

NASA Technical Reports Server (NTRS)

Cipriano, Leonard F.; Ballard, Rodney W.

1988-01-01

The details of studies to be carried out jointly by French and American teams on two rhesus monkeys prepared for future experiments aboard the Space Shuttle are discussed together with the equipment involved. Seven science discipline teams were formed, which will study the effects of flight and/or weightlessness on the bone and calcium metabolism, the behavior, the cardiovascular system, the fluid balance and electrolytes, the muscle system, the neurovestibular interactions, and the sleep/biorhythm cycles. New behavioral training techniques were developed, in which the animals were trained to respond to behavioral tasks in order to measure the parameters involving eye/hand coordination, the response time to target tracking, visual discrimination, and muscle forces used by the animals. A large data set will be obtained from different animals on the two to three Space Shuttle flights; the hardware technologies developed for these experiments will be applied for primate experiments on the Space Station.

Reduction behavior and kinetics of vanadium-titanium sinters under high potential oxygen enriched pulverized coal injection

NASA Astrophysics Data System (ADS)

Ma, Jin-fang; Wang, Guang-wei; Zhang, Jian-liang; Li, Xin-yu; Liu, Zheng-jian; Jiao, Ke-xin; Guo, Jian

2017-05-01

In this work, the reduction behavior of vanadium-titanium sinters was studied under five different sets of conditions of pulverized coal injection with oxygen enrichment. The modified random pore model was established to analyze the reduction kinetics. The results show that the reduction rate of sinters was accelerated by an increase of CO and H2 contents. Meanwhile, with the increase in CO and H2 contents, the increasing range of the medium reduction index (MRE) of sinters decreased. The increasing oxygen enrichment ratio played a diminishing role in improving the reduction behavior of the sinters. The reducing process kinetic parameters were solved using the modified random role model. The results indicated that, with increasing oxygen enrichment, the contents of CO and H2 in the reducing gas increased. The reduction activation energy of the sinters decreased to between 20.4 and 23.2 kJ/mol.

Confinement control mechanism for two-electron Hulthen quantum dots in plasmas

NASA Astrophysics Data System (ADS)

Bahar, M. K.; Soylu, A.

2018-05-01

In this study, for the first time, the energies of two-electron Hulthen quantum dots (TEHQdots) embedded in Debye and quantum plasmas modeled by the more general exponential cosine screened Coulomb (MGECSC) potential under the combined influence of electric and magnetic fields are investigated by numerically solving the Schrödinger equation using the asymptotic iteration method. To do this, the four different forms of the MGECSC potential, which set through the different cases of the potential parameters, are taken into consideration. We propose that plasma environments form considerable quantum mechanical effects for quantum dots and other atomic systems and that plasmas are important experimental arguments. In this study, by considering the quantum dot parameters, the external field parameters, and the plasma screening parameters, a control mechanism of the confinement on energies of TEHQdots and the frequency of the radiation emitted by TEHQdots as a result of any excitation is discussed. In this mechanism, the behaviors, similarities, the functionalities of the control parameters, and the influences of plasmas on these quantities are explored.

Structural Equation Model Trees

PubMed Central

Brandmaier, Andreas M.; von Oertzen, Timo; McArdle, John J.; Lindenberger, Ulman

2015-01-01

In the behavioral and social sciences, structural equation models (SEMs) have become widely accepted as a modeling tool for the relation between latent and observed variables. SEMs can be seen as a unification of several multivariate analysis techniques. SEM Trees combine the strengths of SEMs and the decision tree paradigm by building tree structures that separate a data set recursively into subsets with significantly different parameter estimates in a SEM. SEM Trees provide means for finding covariates and covariate interactions that predict differences in structural parameters in observed as well as in latent space and facilitate theory-guided exploration of empirical data. We describe the methodology, discuss theoretical and practical implications, and demonstrate applications to a factor model and a linear growth curve model. PMID:22984789

Fungible weights in logistic regression.

PubMed

Jones, Jeff A; Waller, Niels G

2016-06-01

In this article we develop methods for assessing parameter sensitivity in logistic regression models. To set the stage for this work, we first review Waller's (2008) equations for computing fungible weights in linear regression. Next, we describe 2 methods for computing fungible weights in logistic regression. To demonstrate the utility of these methods, we compute fungible logistic regression weights using data from the Centers for Disease Control and Prevention's (2010) Youth Risk Behavior Surveillance Survey, and we illustrate how these alternate weights can be used to evaluate parameter sensitivity. To make our work accessible to the research community, we provide R code (R Core Team, 2015) that will generate both kinds of fungible logistic regression weights. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

LIBOR troubles: Anomalous movements detection based on maximum entropy

NASA Astrophysics Data System (ADS)

Bariviera, Aurelio F.; Martín, María T.; Plastino, Angelo; Vampa, Victoria

2016-05-01

According to the definition of the London Interbank Offered Rate (LIBOR), contributing banks should give fair estimates of their own borrowing costs in the interbank market. Between 2007 and 2009, several banks made inappropriate submissions of LIBOR, sometimes motivated by profit-seeking from their trading positions. In 2012, several newspapers' articles began to cast doubt on LIBOR integrity, leading surveillance authorities to conduct investigations on banks' behavior. Such procedures resulted in severe fines imposed to involved banks, who recognized their financial inappropriate conduct. In this paper, we uncover such unfair behavior by using a forecasting method based on the Maximum Entropy principle. Our results are robust against changes in parameter settings and could be of great help for market surveillance.

The behavior of a macroscopic granular material in vortex flow

NASA Astrophysics Data System (ADS)

Nishikawa, Asami

A granular material is defined as a collection of discrete particles such as powder and grain. Granular materials display a large number of complex behaviors. In this project, the behavior of macroscopic granular materials under tornado-like vortex airflow, with varying airflow velocity, was observed and studied. The experimental system was composed of a 9.20-cm inner diameter acrylic pipe with a metal mesh bottom holding the particles, a PVC duct, and an airflow source controlled by a variable auto-transformer, and a power-meter. A fixed fan blade was attached to the duct's inner wall to create a tornado-like vortex airflow from straight flow. As the airflow velocity was increased gradually, the behavior of a set of same-diameter granular materials was observed. The observed behaviors were classified into six phases based on the macroscopic mechanical dynamics. Through this project, we gained insights on the significant parameters for a computer simulation of a similar system by Heath Rice [5]. Comparing computationally and experimentally observed phase diagrams, we can see similar structure. The experimental observations showed the effect of initial arrangement of particles on the phase transitions.

The trade-off between morphology and control in the co-optimized design of robots.

PubMed

Rosendo, Andre; von Atzigen, Marco; Iida, Fumiya

2017-01-01

Conventionally, robot morphologies are developed through simulations and calculations, and different control methods are applied afterwards. Assuming that simulations and predictions are simplified representations of our reality, how sure can roboticists be that the chosen morphology is the most adequate for the possible control choices in the real-world? Here we study the influence of the design parameters in the creation of a robot with a Bayesian morphology-control (MC) co-optimization process. A robot autonomously creates child robots from a set of possible design parameters and uses Bayesian Optimization (BO) to infer the best locomotion behavior from real world experiments. Then, we systematically change from an MC co-optimization to a control-only (C) optimization, which better represents the traditional way that robots are developed, to explore the trade-off between these two methods. We show that although C processes can greatly improve the behavior of poor morphologies, such agents are still outperformed by MC co-optimization results with as few as 25 iterations. Our findings, on one hand, suggest that BO should be used in the design process of robots for both morphological and control parameters to reach optimal performance, and on the other hand, point to the downfall of current design methods in face of new search techniques.

Fractional viscoelasticity of soft elastomers and auxetic foams

NASA Astrophysics Data System (ADS)

Solheim, Hannah; Stanisauskis, Eugenia; Miles, Paul; Oates, William

2018-03-01

Dielectric elastomers are commonly implemented in adaptive structures due to their unique capabilities for real time control of a structure's shape, stiffness, and damping. These active polymers are often used in applications where actuator control or dynamic tunability are important, making an accurate understanding of the viscoelastic behavior critical. This challenge is complicated as these elastomers often operate over a broad range of deformation rates. Whereas research has demonstrated success in applying a nonlinear viscoelastic constitutive model to characterize the behavior of Very High Bond (VHB) 4910, robust predictions of the viscoelastic response over the entire range of time scales is still a significant challenge. An alternative formulation for viscoelastic modeling using fractional order calculus has shown significant improvement in predictive capabilities. While fractional calculus has been explored theoretically in the field of linear viscoelasticity, limited experimental validation and statistical evaluation of the underlying phenomena have been considered. In the present study, predictions across several orders of magnitude in deformation rates are validated against data using a single set of model parameters. Moreover, we illustrate the fractional order is material dependent by running complementary experiments and parameter estimation on the elastomer VHB 4949 as well as an auxetic foam. All results are statistically validated using Bayesian uncertainty methods to obtain posterior densities for the fractional order as well as the hyperelastic parameters.

The trade-off between morphology and control in the co-optimized design of robots

PubMed Central

Iida, Fumiya

2017-01-01

Conventionally, robot morphologies are developed through simulations and calculations, and different control methods are applied afterwards. Assuming that simulations and predictions are simplified representations of our reality, how sure can roboticists be that the chosen morphology is the most adequate for the possible control choices in the real-world? Here we study the influence of the design parameters in the creation of a robot with a Bayesian morphology-control (MC) co-optimization process. A robot autonomously creates child robots from a set of possible design parameters and uses Bayesian Optimization (BO) to infer the best locomotion behavior from real world experiments. Then, we systematically change from an MC co-optimization to a control-only (C) optimization, which better represents the traditional way that robots are developed, to explore the trade-off between these two methods. We show that although C processes can greatly improve the behavior of poor morphologies, such agents are still outperformed by MC co-optimization results with as few as 25 iterations. Our findings, on one hand, suggest that BO should be used in the design process of robots for both morphological and control parameters to reach optimal performance, and on the other hand, point to the downfall of current design methods in face of new search techniques. PMID:29023482

Dynamic Task Performance, Cohesion, and Communications in Human Groups.

PubMed

Giraldo, Luis Felipe; Passino, Kevin M

2016-10-01

In the study of the behavior of human groups, it has been observed that there is a strong interaction between the cohesiveness of the group, its performance when the group has to solve a task, and the patterns of communication between the members of the group. Developing mathematical and computational tools for the analysis and design of task-solving groups that are not only cohesive but also perform well is of importance in social sciences, organizational management, and engineering. In this paper, we model a human group as a dynamical system whose behavior is driven by a task optimization process and the interaction between subsystems that represent the members of the group interconnected according to a given communication network. These interactions are described as attractions and repulsions among members. We show that the dynamics characterized by the proposed mathematical model are qualitatively consistent with those observed in real-human groups, where the key aspect is that the attraction patterns in the group and the commitment to solve the task are not static but change over time. Through a theoretical analysis of the system we provide conditions on the parameters that allow the group to have cohesive behaviors, and Monte Carlo simulations are used to study group dynamics for different sets of parameters, communication topologies, and tasks to solve.

A Method for Generating Natural and User-Defined Sniffing Patterns in Anesthetized or Reduced Preparations

PubMed Central

Carey, Ryan M.; Wachowiak, Matt

2009-01-01

Sniffing has long been thought to play a critical role in shaping neural responses to odorants at multiple levels of the nervous system. However, it has been difficult to systematically examine how particular parameters of sniffing behavior shape odorant-evoked activity, in large part because of the complexity of sniffing behavior and the difficulty in reproducing this behavior in an anesthetized or reduced preparation. Here we present a method for generating naturalistic sniffing patterns in such preparations. The method involves a nasal ventilator whose movement is controlled by an analog command voltage. The command signal may consist of intranasal pressure transients recorded from awake rats and mice or user-defined waveforms. This “sniff playback” device generates intranasal pressure and airflow transients in anesthetized animals that approximate those recorded from the awake animal and are reproducible across trials and across preparations. The device accurately reproduces command waveforms over an amplitude range of approximately 1 log unit and up to frequencies of approximately 12 Hz. Further, odorant-evoked neural activity imaged during sniff playback appears similar to that seen in awake animals. This method should prove useful in investigating how the parameters of odorant sampling shape neural responses in a variety of experimental settings. PMID:18791186

Model-independent reconstruction of f( T) teleparallel cosmology

NASA Astrophysics Data System (ADS)

Capozziello, Salvatore; D'Agostino, Rocco; Luongo, Orlando

2017-11-01

We propose a model-independent formalism to numerically solve the modified Friedmann equations in the framework of f( T) teleparallel cosmology. Our strategy is to expand the Hubble parameter around the redshift z=0 up to a given order and to adopt cosmographic bounds as initial settings to determine the corresponding f(z)≡ f(T(H(z))) function. In this perspective, we distinguish two cases: the first expansion is up to the jerk parameter, the second expansion is up to the snap parameter. We show that inside the observed redshift domain z≤ 1, only the net strength of f( z) is modified passing from jerk to snap, whereas its functional behavior and shape turn out to be identical. As first step, we set the cosmographic parameters by means of the most recent observations. Afterwards, we calibrate our numerical solutions with the concordance Λ CDM model. In both cases, there is a good agreement with the cosmological standard model around z≤ 1, with severe discrepancies outer of this limit. We demonstrate that the effective dark energy term evolves following the test-function: f(z)=A+B{z}^2e^{Cz}. Bounds over the set A, B, C are also fixed by statistical considerations, comparing discrepancies between f( z) with data. The approach opens the possibility to get a wide class of test-functions able to frame the dynamics of f( T) without postulating any model a priori. We thus re-obtain the f( T) function through a back-scattering procedure once f( z) is known. We figure out the properties of our f( T) function at the level of background cosmology, to check the goodness of our numerical results. Finally, a comparison with previous cosmographic approaches is carried out giving results compatible with theoretical expectations.

Steel Rack Connections: Identification of Most Influential Factors and a Comparison of Stiffness Design Methods.

PubMed

Shah, S N R; Sulong, N H Ramli; Shariati, Mahdi; Jumaat, M Z

2015-01-01

Steel pallet rack (SPR) beam-to-column connections (BCCs) are largely responsible to avoid the sway failure of frames in the down-aisle direction. The overall geometry of beam end connectors commercially used in SPR BCCs is different and does not allow a generalized analytic approach for all types of beam end connectors; however, identifying the effects of the configuration, profile and sizes of the connection components could be the suitable approach for the practical design engineers in order to predict the generalized behavior of any SPR BCC. This paper describes the experimental behavior of SPR BCCs tested using a double cantilever test set-up. Eight sets of specimens were identified based on the variation in column thickness, beam depth and number of tabs in the beam end connector in order to investigate the most influential factors affecting the connection performance. Four tests were repeatedly performed for each set to bring uniformity to the results taking the total number of tests to thirty-two. The moment-rotation (M-θ) behavior, load-strain relationship, major failure modes and the influence of selected parameters on connection performance were investigated. A comparative study to calculate the connection stiffness was carried out using the initial stiffness method, the slope to half-ultimate moment method and the equal area method. In order to find out the more appropriate method, the mean stiffness of all the tested connections and the variance in values of mean stiffness according to all three methods were calculated. The calculation of connection stiffness by means of the initial stiffness method is considered to overestimate the values when compared to the other two methods. The equal area method provided more consistent values of stiffness and lowest variance in the data set as compared to the other two methods.

Intelligent Entity Behavior Within Synthetic Environments. Chapter 3

NASA Technical Reports Server (NTRS)

Kruk, R. V.; Howells, P. B.; Siksik, D. N.

2007-01-01

This paper describes some elements in the development of realistic performance and behavior in the synthetic entities (players) which support Modeling and Simulation (M&S) applications, particularly military training. Modern human-in-the-loop (virtual) training systems incorporate sophisticated synthetic environments, which provide: 1. The operational environment, including, for example, terrain databases; 2. Physical entity parameters which define performance in engineered systems, such as aircraft aerodynamics; 3. Platform/system characteristics such as acoustic, IR and radar signatures; 4. Behavioral entity parameters which define interactive performance, including knowledge/reasoning about terrain, tactics; and, 5. Doctrine, which combines knowledge and tactics into behavior rule sets. The resolution and fidelity of these model/database elements can vary substantially, but as synthetic environments are designed to be compose able, attributes may easily be added (e.g., adding a new radar to an aircraft) or enhanced (e.g. Amending or replacing missile seeker head/ Electronic Counter Measures (ECM) models to improve the realism of their interaction). To a human in the loop with synthetic entities, their observed veridicality is assessed via engagement responses (e.g. effect of countermeasures upon a closing missile), as seen on systems displays, and visual (image) behavior. The realism of visual models in a simulation (level of detail as well as motion fidelity) remains a challenge in realistic articulation of elements such as vehicle antennae and turrets, or, with human figures; posture, joint articulation, response to uneven ground. Currently the adequacy of visual representation is more dependant upon the quality and resolution of the physical models driving those entities than graphics processing power per Se. Synthetic entities in M&S applications traditionally have represented engineered systems (e.g. aircraft) with human-in-the-loop performance characteristics (e.g. visual acuity) included in the system behavioral specification. As well, performance affecting human parameters such as experience level, fatigue and stress are coming into wider use (via AI approaches) to incorporate more uncertainty as to response type as well as performance (e.g. Where an opposing entity might go and what it might do, as well as how well it might perform).

Characterization technique for inhomogeneous 4H-SiC Schottky contacts: A practical model for high temperature behavior

NASA Astrophysics Data System (ADS)

Brezeanu, G.; Pristavu, G.; Draghici, F.; Badila, M.; Pascu, R.

2017-08-01

In this paper, a characterization technique for 4H-SiC Schottky diodes with varying levels of metal-semiconductor contact inhomogeneity is proposed. A macro-model, suitable for high-temperature evaluation of SiC Schottky contacts, with discrete barrier height non-uniformity, is introduced in order to determine the temperature interval and bias domain where electrical behavior of the devices can be described by the thermionic emission theory (has a quasi-ideal performance). A minimal set of parameters, the effective barrier height and peff, the non-uniformity factor, is associated. Model-extracted parameters are discussed in comparison with literature-reported results based on existing inhomogeneity approaches, in terms of complexity and physical relevance. Special consideration was given to models based on a Gaussian distribution of barrier heights on the contact surface. The proposed methodology is validated by electrical characterization of nickel silicide Schottky contacts on silicon carbide (4H-SiC), where a discrete barrier distribution can be considered. The same method is applied to inhomogeneous Pt/4H-SiC contacts. The forward characteristics measured at different temperatures are accurately reproduced using this inhomogeneous barrier model. A quasi-ideal behavior is identified for intervals spanning 200 °C for all measured Schottky samples, with Ni and Pt contact metals. A predictable exponential current-voltage variation over at least 2 orders of magnitude is also proven, with a stable barrier height and effective area for temperatures up to 400 °C. This application-oriented characterization technique is confirmed by using model parameters to fit a SiC-Schottky high temperature sensor's response.

Spatio-Temporal Regression Based Clustering of Precipitation Extremes in a Presence of Systematically Missing Covariates

NASA Astrophysics Data System (ADS)

Kaiser, Olga; Martius, Olivia; Horenko, Illia

2017-04-01

Regression based Generalized Pareto Distribution (GPD) models are often used to describe the dynamics of hydrological threshold excesses relying on the explicit availability of all of the relevant covariates. But, in real application the complete set of relevant covariates might be not available. In this context, it was shown that under weak assumptions the influence coming from systematically missing covariates can be reflected by a nonstationary and nonhomogenous dynamics. We present a data-driven, semiparametric and an adaptive approach for spatio-temporal regression based clustering of threshold excesses in a presence of systematically missing covariates. The nonstationary and nonhomogenous behavior of threshold excesses is describes by a set of local stationary GPD models, where the parameters are expressed as regression models, and a non-parametric spatio-temporal hidden switching process. Exploiting nonparametric Finite Element time-series analysis Methodology (FEM) with Bounded Variation of the model parameters (BV) for resolving the spatio-temporal switching process, the approach goes beyond strong a priori assumptions made is standard latent class models like Mixture Models and Hidden Markov Models. Additionally, the presented FEM-BV-GPD provides a pragmatic description of the corresponding spatial dependence structure by grouping together all locations that exhibit similar behavior of the switching process. The performance of the framework is demonstrated on daily accumulated precipitation series over 17 different locations in Switzerland from 1981 till 2013 - showing that the introduced approach allows for a better description of the historical data.

Using CV-GLUE procedure in analysis of wetland model predictive uncertainty.

PubMed

Huang, Chun-Wei; Lin, Yu-Pin; Chiang, Li-Chi; Wang, Yung-Chieh

2014-07-01

This study develops a procedure that is related to Generalized Likelihood Uncertainty Estimation (GLUE), called the CV-GLUE procedure, for assessing the predictive uncertainty that is associated with different model structures with varying degrees of complexity. The proposed procedure comprises model calibration, validation, and predictive uncertainty estimation in terms of a characteristic coefficient of variation (characteristic CV). The procedure first performed two-stage Monte-Carlo simulations to ensure predictive accuracy by obtaining behavior parameter sets, and then the estimation of CV-values of the model outcomes, which represent the predictive uncertainties for a model structure of interest with its associated behavior parameter sets. Three commonly used wetland models (the first-order K-C model, the plug flow with dispersion model, and the Wetland Water Quality Model; WWQM) were compared based on data that were collected from a free water surface constructed wetland with paddy cultivation in Taipei, Taiwan. The results show that the first-order K-C model, which is simpler than the other two models, has greater predictive uncertainty. This finding shows that predictive uncertainty does not necessarily increase with the complexity of the model structure because in this case, the more simplistic representation (first-order K-C model) of reality results in a higher uncertainty in the prediction made by the model. The CV-GLUE procedure is suggested to be a useful tool not only for designing constructed wetlands but also for other aspects of environmental management. Copyright © 2014 Elsevier Ltd. All rights reserved.

First Principles Investigation of Fluorine Based Strontium Series of Perovskites

NASA Astrophysics Data System (ADS)

Erum, Nazia; Azhar Iqbal, Muhammad

2016-11-01

Density functional theory is used to explore structural, elastic, and mechanical properties of SrLiF3, SrNaF3, SrKF3 and SrRbF3 fluoroperovskite compounds by means of an ab-initio Full Potential-Linearized Augmented Plane Wave (FP-LAPW) method. Several lattice parameters are employed to obtain accurate equilibrium volume (Vo). The resultant quantities include ground state energy, elastic constants, shear modulus, bulk modulus, young's modulus, cauchy's pressure, poisson's ratio, shear constant, ratio of elastic anisotropy factor, kleinman's parameter, melting temperature, and lame's coefficient. The calculated structural parameters via DFT as well as analytical methods are found to be consistent with experimental findings. Chemical bonding is used to investigate corresponding chemical trends which authenticate combination of covalent-ionic behavior. Furthermore electron density plots as well as elastic and mechanical properties are reported for the first time which reveals that fluorine based strontium series of perovskites are mechanically stable and posses weak resistance towards shear deformation as compared to resistance towards unidirectional compression while brittleness and ionic behavior is dominated in them which decreases from SrLiF3 to SrRbF3. Calculated cauchy's pressure, poisson's ratio and B/G ratio also proves ionic nature in these compounds. The present methodology represents an effective and influential approach to calculate the whole set of elastic and mechanical parameters which would support to understand various physical phenomena and empower device engineers for implementing these materials in numerous applications.

Unique effects of setting goals on behavior change: Systematic review and meta-analysis.

PubMed

Epton, Tracy; Currie, Sinead; Armitage, Christopher J

2017-12-01

Goal setting is a common feature of behavior change interventions, but it is unclear when goal setting is optimally effective. The aims of this systematic review and meta-analysis were to evaluate: (a) the unique effects of goal setting on behavior change, and (b) under what circumstances and for whom goal setting works best. Four databases were searched for articles that assessed the unique effects of goal setting on behavior change using randomized controlled trials. One-hundred and 41 papers were identified from which 384 effect sizes (N = 16,523) were extracted and analyzed. A moderator analysis of sample characteristics, intervention characteristics, inclusion of other behavior change techniques, study design and delivery, quality of study, outcome measures, and behavior targeted was conducted. A random effects model indicated a small positive unique effect of goal setting across a range of behaviors, d = .34 (CI [.28, .41]). Moderator analyses indicated that goal setting was particularly effective if the goal was: (a) difficult, (b) set publicly, and (c) was a group goal. There was weaker evidence that goal setting was more effective when paired with external monitoring of the behavior/outcome by others without feedback and delivered face-to-face. Goal setting is an effective behavior change technique that has the potential to be considered a fundamental component of successful interventions. The present review adds novel insights into the means by which goal setting might be augmented to maximize behavior change and sets the agenda for future programs of research. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Pore-level determination of spectral reflection behaviors of high-porosity metal foam sheets

NASA Astrophysics Data System (ADS)

Li, Yang; Xia, Xin-Lin; Ai, Qing; Sun, Chuang; Tan, He-Ping

2018-03-01

Open cell metal foams are currently attracting attention and their radiative behaviors are of primary importance in high temperature applications. The spectral reflection behaviors of high-porosity metal foam sheets, bidirectional reflectance distribution function (BRDF) and directional-hemispherical reflectivity were numerically investigated. A set of realistic nickel foams with porosity from 0.87 to 0.97 and pore density from 10 to 40 pores per inch were tomographied to obtain their 3-D digital cell network. A Monte Carlo ray-tracing method was employed in order to compute the pore-level radiative transfer inside the network within the limit of geometrical optics. The apparent reflection behaviors and their dependency on the textural parameters and strut optical properties were comprehensively computed and analysed. The results show a backward scattering of the reflected energy at the foam sheet surface. Except in the cases of large incident angles, an energy peak is located almost along the incident direction and increases with increasing incident angles. Through an analytical relation established, the directional-hemispherical reflectivity can be related directly to the porosity of the foam sheet and to the complex refractive index of the solid phase as well as the specularity parameter which characterizes the local reflection model. The computations show that a linear decrease in normal-hemispherical reflectivity occurs with increasing porosity. The rate of this decrease is directly proportional to the strut normal reflectivity. In addition, the hemispherical reflectivity increases as a power function of the incident angle cosine.

Analyzing simulation-based PRA data through traditional and topological clustering: A BWR station blackout case study

DOE PAGES

Maljovec, D.; Liu, S.; Wang, B.; ...

2015-07-14

Here, dynamic probabilistic risk assessment (DPRA) methodologies couple system simulator codes (e.g., RELAP and MELCOR) with simulation controller codes (e.g., RAVEN and ADAPT). Whereas system simulator codes model system dynamics deterministically, simulation controller codes introduce both deterministic (e.g., system control logic and operating procedures) and stochastic (e.g., component failures and parameter uncertainties) elements into the simulation. Typically, a DPRA is performed by sampling values of a set of parameters and simulating the system behavior for that specific set of parameter values. For complex systems, a major challenge in using DPRA methodologies is to analyze the large number of scenarios generated,more » where clustering techniques are typically employed to better organize and interpret the data. In this paper, we focus on the analysis of two nuclear simulation datasets that are part of the risk-informed safety margin characterization (RISMC) boiling water reactor (BWR) station blackout (SBO) case study. We provide the domain experts a software tool that encodes traditional and topological clustering techniques within an interactive analysis and visualization environment, for understanding the structures of such high-dimensional nuclear simulation datasets. We demonstrate through our case study that both types of clustering techniques complement each other for enhanced structural understanding of the data.« less

Effect of Watermarking on Diagnostic Preservation of Atherosclerotic Ultrasound Video in Stroke Telemedicine.

PubMed

Dey, Nilanjan; Bose, Soumyo; Das, Achintya; Chaudhuri, Sheli Sinha; Saba, Luca; Shafique, Shoaib; Nicolaides, Andrew; Suri, Jasjit S

2016-04-01

Embedding of diagnostic and health care information requires secure encryption and watermarking. This research paper presents a comprehensive study for the behavior of some well established watermarking algorithms in frequency domain for the preservation of stroke-based diagnostic parameters. Two different sets of watermarking algorithms namely: two correlation-based (binary logo hiding) and two singular value decomposition (SVD)-based (gray logo hiding) watermarking algorithms are used for embedding ownership logo. The diagnostic parameters in atherosclerotic plaque ultrasound video are namely: (a) bulb identification and recognition which consists of identifying the bulb edge points in far and near carotid walls; (b) carotid bulb diameter; and (c) carotid lumen thickness all along the carotid artery. The tested data set consists of carotid atherosclerotic movies taken under IRB protocol from University of Indiana Hospital, USA-AtheroPoint™ (Roseville, CA, USA) joint pilot study. ROC (receiver operating characteristic) analysis was performed on the bulb detection process that showed an accuracy and sensitivity of 100 % each, respectively. The diagnostic preservation (DPsystem) for SVD-based approach was above 99 % with PSNR (Peak signal-to-noise ratio) above 41, ensuring the retention of diagnostic parameter devalorization as an effect of watermarking. Thus, the fully automated proposed system proved to be an efficient method for watermarking the atherosclerotic ultrasound video for stroke application.

PILOT RESULTS ON FORWARD COLLISION WARNING SYSTEM EFFECTIVENESS IN OLDER DRIVERS

PubMed Central

Lester, Benjamin D.; Sager, Lauren N.; Dawson, Jeffrey; Hacker, Sarah D.; Aksan, Nazan; Rizzo, Matthew; Kitazaki, Satoshi

2016-01-01

Summary Advanced Driver Assistance Systems (ADAS) have largely been developed with a “one-size-fits-all” approach. This approach neglects the large inter-individual variability in perceptual and cognitive abilities that affect aging ADAS users. We investigated the effectiveness of a forward collision warning (FCW) with fixed response parameters in young and older drivers with differing levels of cognitive functioning. Drivers responded to a pedestrian stepping into the driver’s path on a simulated urban road. Behavioral metrics included response times (RT) for pedal controls and two indices of risk penetration (e.g., maximum deceleration and minimum time-to-collision (TTC)). Older drivers showed significantly slower responses at several time points compared to younger drivers. The FCW facilitated response times (RTs) for older and younger drivers. However, older drivers still showed smaller safety gains compared to younger drivers at accelerator pedal release and initial brake application when the FCW was active. No significant differences in risk metrics were observed within the condition studied. The results demonstrate older drivers likely differ from younger drivers using a FCW with a fixed parameter set. Finally, we briefly discuss how future research should examine predictive relationships between domains of cognitive functioning and ADAS responses to develop parameter sets to fit the individual. PMID:27135061

Analysis of the Negative-SET Behaviors in Cu/ZrO2/Pt Devices

NASA Astrophysics Data System (ADS)

Liu, Sen; Zhao, Xiaolong; Li, Qingjiang; Li, Nan; Wang, Wei; Liu, Qi; Xu, Hui

2016-12-01

Metal oxide-based electrochemical metallization memory (ECM) shows promising performance for next generation non-volatile memory. The negative-SET behavior has been observed in various oxide-based ECM devices. But the underlying mechanism of this behavior remains unaddressed and the role of the metal cation and oxygen vacancy in this behavior is unclear. In this work, we have observed two kinds of negative-SET (labeled as N-SET1 and N-SET2) behaviors in our Cu/ZrO2/Pt devices. Both the two behaviors can result in hard breakdown due to the high compliance current in reset process. The I-V characteristic shows that the two negative-SET behaviors have an obvious difference in operation voltage. Using four-probe resistance measurement method, the resistance-temperature characteristics of the ON-state after various negative-SET behaviors have been studied. The temperature dependence results demonstrate that the N-SET1 behavior is dominated by Cu conductive filament (CF) reformation caused by the Cu CF overgrowth phenomenon while the N-SET2 is related to the formation of oxygen vacancy CF. This work may provide a comprehensive understanding of the switching mechanism in oxide-based ECM devices.

Speaker verification system using acoustic data and non-acoustic data

DOEpatents

Gable, Todd J [Walnut Creek, CA; Ng, Lawrence C [Danville, CA; Holzrichter, John F [Berkeley, CA; Burnett, Greg C [Livermore, CA

2006-03-21

A method and system for speech characterization. One embodiment includes a method for speaker verification which includes collecting data from a speaker, wherein the data comprises acoustic data and non-acoustic data. The data is used to generate a template that includes a first set of "template" parameters. The method further includes receiving a real-time identity claim from a claimant, and using acoustic data and non-acoustic data from the identity claim to generate a second set of parameters. The method further includes comparing the first set of parameters to the set of parameters to determine whether the claimant is the speaker. The first set of parameters and the second set of parameters include at least one purely non-acoustic parameter, including a non-acoustic glottal shape parameter derived from averaging multiple glottal cycle waveforms.

Data series embedding and scale invariant statistics.

PubMed

Michieli, I; Medved, B; Ristov, S

2010-06-01

Data sequences acquired from bio-systems such as human gait data, heart rate interbeat data, or DNA sequences exhibit complex dynamics that is frequently described by a long-memory or power-law decay of autocorrelation function. One way of characterizing that dynamics is through scale invariant statistics or "fractal-like" behavior. For quantifying scale invariant parameters of physiological signals several methods have been proposed. Among them the most common are detrended fluctuation analysis, sample mean variance analyses, power spectral density analysis, R/S analysis, and recently in the realm of the multifractal approach, wavelet analysis. In this paper it is demonstrated that embedding the time series data in the high-dimensional pseudo-phase space reveals scale invariant statistics in the simple fashion. The procedure is applied on different stride interval data sets from human gait measurements time series (Physio-Bank data library). Results show that introduced mapping adequately separates long-memory from random behavior. Smaller gait data sets were analyzed and scale-free trends for limited scale intervals were successfully detected. The method was verified on artificially produced time series with known scaling behavior and with the varying content of noise. The possibility for the method to falsely detect long-range dependence in the artificially generated short range dependence series was investigated. (c) 2009 Elsevier B.V. All rights reserved.

Cortical Specializations Underlying Fast Computations

PubMed Central

Volgushev, Maxim

2016-01-01

The time course of behaviorally relevant environmental events sets temporal constraints on neuronal processing. How does the mammalian brain make use of the increasingly complex networks of the neocortex, while making decisions and executing behavioral reactions within a reasonable time? The key parameter determining the speed of computations in neuronal networks is a time interval that neuronal ensembles need to process changes at their input and communicate results of this processing to downstream neurons. Theoretical analysis identified basic requirements for fast processing: use of neuronal populations for encoding, background activity, and fast onset dynamics of action potentials in neurons. Experimental evidence shows that populations of neocortical neurons fulfil these requirements. Indeed, they can change firing rate in response to input perturbations very quickly, within 1 to 3 ms, and encode high-frequency components of the input by phase-locking their spiking to frequencies up to 300 to 1000 Hz. This implies that time unit of computations by cortical ensembles is only few, 1 to 3 ms, which is considerably faster than the membrane time constant of individual neurons. The ability of cortical neuronal ensembles to communicate on a millisecond time scale allows for complex, multiple-step processing and precise coordination of neuronal activity in parallel processing streams, while keeping the speed of behavioral reactions within environmentally set temporal constraints. PMID:25689988

Evaluating Uncertainty of Runoff Simulation using SWAT model of the Feilaixia Watershed in China Based on the GLUE Method

NASA Astrophysics Data System (ADS)

Chen, X.; Huang, G.

2017-12-01

In recent years, distributed hydrological models have been widely used in storm water management, water resources protection and so on. Therefore, how to evaluate the uncertainty of the model reasonably and efficiently becomes a hot topic today. In this paper, the soil and water assessment tool (SWAT) model is constructed for the study area of China's Feilaixia watershed, and the uncertainty of the runoff simulation is analyzed by GLUE method deeply. Taking the initial parameter range of GLUE method as the research core, the influence of different initial parameter ranges on model uncertainty is studied. In this paper, two sets of parameter ranges are chosen as the object of study, the first one (range 1) is recommended by SWAT-CUP and the second one (range 2) is calibrated by SUFI-2. The results showed that under the same number of simulations (10,000 times), the overall uncertainty obtained by the range 2 is less than the range 1. Specifically, the "behavioral" parameter sets for the range 2 is 10000 and for the range 1 is 4448. In the calibration and the validation, the ratio of P-factor to R-factor for range 1 is 1.387 and 1.391, and for range 2 is 1.405 and 1.462 respectively. In addition, the simulation result of range 2 is better with the NS and R2 slightly higher than range 1. Therefore, it can be concluded that using the parameter range calibrated by SUFI-2 as the initial parameter range for the GLUE is a way to effectively capture and evaluate the simulation uncertainty.

Behavior control in the sensorimotor loop with short-term synaptic dynamics induced by self-regulating neurons.

PubMed

Toutounji, Hazem; Pasemann, Frank

2014-01-01

The behavior and skills of living systems depend on the distributed control provided by specialized and highly recurrent neural networks. Learning and memory in these systems is mediated by a set of adaptation mechanisms, known collectively as neuronal plasticity. Translating principles of recurrent neural control and plasticity to artificial agents has seen major strides, but is usually hampered by the complex interactions between the agent's body and its environment. One of the important standing issues is for the agent to support multiple stable states of behavior, so that its behavioral repertoire matches the requirements imposed by these interactions. The agent also must have the capacity to switch between these states in time scales that are comparable to those by which sensory stimulation varies. Achieving this requires a mechanism of short-term memory that allows the neurocontroller to keep track of the recent history of its input, which finds its biological counterpart in short-term synaptic plasticity. This issue is approached here by deriving synaptic dynamics in recurrent neural networks. Neurons are introduced as self-regulating units with a rich repertoire of dynamics. They exhibit homeostatic properties for certain parameter domains, which result in a set of stable states and the required short-term memory. They can also operate as oscillators, which allow them to surpass the level of activity imposed by their homeostatic operation conditions. Neural systems endowed with the derived synaptic dynamics can be utilized for the neural behavior control of autonomous mobile agents. The resulting behavior depends also on the underlying network structure, which is either engineered or developed by evolutionary techniques. The effectiveness of these self-regulating units is demonstrated by controlling locomotion of a hexapod with 18 degrees of freedom, and obstacle-avoidance of a wheel-driven robot.

Behavior control in the sensorimotor loop with short-term synaptic dynamics induced by self-regulating neurons

PubMed Central

Toutounji, Hazem; Pasemann, Frank

2014-01-01

The behavior and skills of living systems depend on the distributed control provided by specialized and highly recurrent neural networks. Learning and memory in these systems is mediated by a set of adaptation mechanisms, known collectively as neuronal plasticity. Translating principles of recurrent neural control and plasticity to artificial agents has seen major strides, but is usually hampered by the complex interactions between the agent's body and its environment. One of the important standing issues is for the agent to support multiple stable states of behavior, so that its behavioral repertoire matches the requirements imposed by these interactions. The agent also must have the capacity to switch between these states in time scales that are comparable to those by which sensory stimulation varies. Achieving this requires a mechanism of short-term memory that allows the neurocontroller to keep track of the recent history of its input, which finds its biological counterpart in short-term synaptic plasticity. This issue is approached here by deriving synaptic dynamics in recurrent neural networks. Neurons are introduced as self-regulating units with a rich repertoire of dynamics. They exhibit homeostatic properties for certain parameter domains, which result in a set of stable states and the required short-term memory. They can also operate as oscillators, which allow them to surpass the level of activity imposed by their homeostatic operation conditions. Neural systems endowed with the derived synaptic dynamics can be utilized for the neural behavior control of autonomous mobile agents. The resulting behavior depends also on the underlying network structure, which is either engineered or developed by evolutionary techniques. The effectiveness of these self-regulating units is demonstrated by controlling locomotion of a hexapod with 18 degrees of freedom, and obstacle-avoidance of a wheel-driven robot. PMID:24904403

Imitative and best response behaviors in a nonlinear Cournotian setting

NASA Astrophysics Data System (ADS)

Cerboni Baiardi, Lorenzo; Naimzada, Ahmad K.

2018-05-01

We consider the competition among quantity setting players in a deterministic nonlinear oligopoly framework characterized by an isoelastic demand curve. Players are characterized by having heterogeneous decisional mechanisms to set their outputs: some players are imitators, while the remaining others adopt a rational-like rule according to which their past decisions are adjusted towards their static expectation best response. The Cournot-Nash production level is a stationary state of our model together with a further production level that can be interpreted as the competitive outcome in case only imitators are present. We found that both the number of players and the relative fraction of imitators influence stability of the Cournot-Nash equilibrium with an ambiguous role, and double instability thresholds may be observed. Global analysis shows that a wide variety of complex dynamic scenarios emerge. Chaotic trajectories as well as multi-stabilities, where different attractors coexist, are robust phenomena that can be observed for a wide spectrum of parameter sets.

Model Adaptation in Parametric Space for POD-Galerkin Models

NASA Astrophysics Data System (ADS)

Gao, Haotian; Wei, Mingjun

2017-11-01

The development of low-order POD-Galerkin models is largely motivated by the expectation to use the model developed with a set of parameters at their native values to predict the dynamic behaviors of the same system under different parametric values, in other words, a successful model adaptation in parametric space. However, most of time, even small deviation of parameters from their original value may lead to large deviation or unstable results. It has been shown that adding more information (e.g. a steady state, mean value of a different unsteady state, or an entire different set of POD modes) may improve the prediction of flow with other parametric states. For a simple case of the flow passing a fixed cylinder, an orthogonal mean mode at a different Reynolds number may stabilize the POD-Galerkin model when Reynolds number is changed. For a more complicated case of the flow passing an oscillatory cylinder, a global POD-Galerkin model is first applied to handle the moving boundaries, then more information (e.g. more POD modes) is required to predicate the flow under different oscillatory frequencies. Supported by ARL.

3-Iodobenzaldehyde: XRD, FT-IR, Raman and DFT studies.

PubMed

Kumar, Chandraju Sadolalu Chidan; Parlak, Cemal; Tursun, Mahir; Fun, Hoong-Kun; Rhyman, Lydia; Ramasami, Ponnadurai; Alswaidan, Ibrahim A; Keşan, Gürkan; Chandraju, Siddegowda; Quah, Ching Kheng

2015-06-15

The structure of 3-iodobenzaldehyde (3IB) was characterized by FT-IR, Raman and single-crystal X-ray diffraction techniques. The conformational isomers, optimized geometric parameters, normal mode frequencies and corresponding vibrational assignments of 3IB were examined using density functional theory (DFT) method, with the Becke-3-Lee-Yang-Parr (B3LYP) functional and the 6-311+G(3df,p) basis set for all atoms except for iodine. The LANL2DZ effective core basis set was used for iodine. Potential energy distribution (PED) analysis of normal modes was performed to identify characteristic frequencies. 3IB crystallizes in monoclinic space group P21/c with the O-trans form. There is a good agreement between the theoretically predicted structural parameters, and vibrational frequencies and those obtained experimentally. In order to understand halogen effect, 3-halogenobenzaldehyde [XC6H4CHO; X=F, Cl and Br] was also studied theoretically. The free energy difference between the isomers is small but the rotational barrier is about 8kcal/mol. An atypical behavior of fluorine affecting conformational preference is observed. Copyright © 2015 Elsevier B.V. All rights reserved.

Reactive flow model development for PBXW-126 using modern nonlinear optimization methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murphy, M.J.; Simpson, R.L.; Urtiew, P.A.

1995-08-01

The initiation and detonation behavior of PBXW-126 has been characterized and is described. PBXW-126 is a composite explosive consisting of approximately equal amounts of RDX, AP, AL, and NTO with a polyurethane binder. The three term ignition and growth of reaction model parameters (ignition + two growth terms) have been found using nonlinear optimization methods to determine the {open_quotes}best{close_quotes} set of model parameters. The ignition term treats the initiation of up to 0.5% of the RDX The first growth term in the model treats the RDX growth of reaction up to 20% reacted. The second growth term treats the subsequentmore » growth of reaction of the remaining AP/AL/NTO. The unreacted equation of state (EOS) was determined from the wave profiles of embedded gauge tests while the JWL product EOS was determined from cylinder expansion test results. The nonlinear optimization code, NLQPEB/GLO, was used to determine the {open_quotes}best{close_quotes} set of coefficients for the three term Lee-Tarver ignition and growth of reaction model.« less

Modeling the impact behavior of high strength ceramics. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rajendran, A.M.

1993-12-01

An advanced constitutive model is used to describe the shock and high strain rate behaviors of silicon carbide (SC), boron carbide B4C, and titanium diboride (TiB2) under impact loading conditions. The model's governing equations utilize a set of microphysically-based constitutive relationships to model the deformation and damage processes in a ceramic. The total strain is decomposed into elastic, plastic, and microcracking components. The plastic strain component was calculated using conventional viscoplastic equations. The strain components due to microcracking utilized relationships derived for a penny-shaped crack containing elastic solids. The main features of the model include degradation of strength and stiffnessmore » under both compressive and tensile loading conditions. When loaded above the Hugoniot elastic limit (HEL), the strength is limited by the strain rate dependent strength equation. However, below the HEL, the strength variation with respect to strain rate and pressure is modeled through microcracking relationships assuming no plastic flow. The ceramic model parameters were determined using a set of VISAR data from the plate impact experiments.« less

Full-scale computation for all the thermoelectric property parameters of half-Heusler compounds

DOE PAGES

Hong, A. J.; Li, L.; He, R.; ...

2016-03-07

The thermoelectric performance of materials relies substantially on the band structures that determine the electronic and phononic transports, while the transport behaviors compete and counter-act for the power factor PF and figure-of-merit ZT. These issues make a full-scale computation of the whole set of thermoelectric parameters particularly attractive, while a calculation scheme of the electronic and phononic contributions to thermal conductivity remains yet challenging. In this work, we present a full-scale computation scheme based on the first-principles calculations by choosing a set of doped half- Heusler compounds as examples for illustration. The electronic structure is computed using the WIEN2k codemore » and the carrier relaxation times for electrons and holes are calculated using the Bardeen and Shockley’s deformation potential (DP) theory. The finite-temperature electronic transport is evaluated within the framework of Boltzmann transport theory. In sequence, the density functional perturbation combined with the quasi-harmonic approximation and the Klemens’ equation is implemented for calculating the lattice thermal conductivity of carrier-doped thermoelectric materials such as Tidoped NbFeSb compounds without losing a generality. The calculated results show good agreement with experimental data. Lastly, the present methodology represents an effective and powerful approach to calculate the whole set of thermoelectric properties for thermoelectric materials.« less

Full-scale computation for all the thermoelectric property parameters of half-Heusler compounds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hong, A. J.; Li, L.; He, R.

The thermoelectric performance of materials relies substantially on the band structures that determine the electronic and phononic transports, while the transport behaviors compete and counter-act for the power factor PF and figure-of-merit ZT. These issues make a full-scale computation of the whole set of thermoelectric parameters particularly attractive, while a calculation scheme of the electronic and phononic contributions to thermal conductivity remains yet challenging. In this work, we present a full-scale computation scheme based on the first-principles calculations by choosing a set of doped half- Heusler compounds as examples for illustration. The electronic structure is computed using the WIEN2k codemore » and the carrier relaxation times for electrons and holes are calculated using the Bardeen and Shockley’s deformation potential (DP) theory. The finite-temperature electronic transport is evaluated within the framework of Boltzmann transport theory. In sequence, the density functional perturbation combined with the quasi-harmonic approximation and the Klemens’ equation is implemented for calculating the lattice thermal conductivity of carrier-doped thermoelectric materials such as Tidoped NbFeSb compounds without losing a generality. The calculated results show good agreement with experimental data. Lastly, the present methodology represents an effective and powerful approach to calculate the whole set of thermoelectric properties for thermoelectric materials.« less

Surveillance metrics sensitivity study.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamada, Michael S.; Bierbaum, Rene Lynn; Robertson, Alix A.

2011-09-01

In September of 2009, a Tri-Lab team was formed to develop a set of metrics relating to the NNSA nuclear weapon surveillance program. The purpose of the metrics was to develop a more quantitative and/or qualitative metric(s) describing the results of realized or non-realized surveillance activities on our confidence in reporting reliability and assessing the stockpile. As a part of this effort, a statistical sub-team investigated various techniques and developed a complementary set of statistical metrics that could serve as a foundation for characterizing aspects of meeting the surveillance program objectives. The metrics are a combination of tolerance limit calculationsmore » and power calculations, intending to answer level-of-confidence type questions with respect to the ability to detect certain undesirable behaviors (catastrophic defects, margin insufficiency defects, and deviations from a model). Note that the metrics are not intended to gauge product performance but instead the adequacy of surveillance. This report gives a short description of four metrics types that were explored and the results of a sensitivity study conducted to investigate their behavior for various inputs. The results of the sensitivity study can be used to set the risk parameters that specify the level of stockpile problem that the surveillance program should be addressing.« less

Surveillance Metrics Sensitivity Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bierbaum, R; Hamada, M; Robertson, A

2011-11-01

In September of 2009, a Tri-Lab team was formed to develop a set of metrics relating to the NNSA nuclear weapon surveillance program. The purpose of the metrics was to develop a more quantitative and/or qualitative metric(s) describing the results of realized or non-realized surveillance activities on our confidence in reporting reliability and assessing the stockpile. As a part of this effort, a statistical sub-team investigated various techniques and developed a complementary set of statistical metrics that could serve as a foundation for characterizing aspects of meeting the surveillance program objectives. The metrics are a combination of tolerance limit calculationsmore » and power calculations, intending to answer level-of-confidence type questions with respect to the ability to detect certain undesirable behaviors (catastrophic defects, margin insufficiency defects, and deviations from a model). Note that the metrics are not intended to gauge product performance but instead the adequacy of surveillance. This report gives a short description of four metrics types that were explored and the results of a sensitivity study conducted to investigate their behavior for various inputs. The results of the sensitivity study can be used to set the risk parameters that specify the level of stockpile problem that the surveillance program should be addressing.« less

Incorporation of prior information on parameters into nonlinear regression groundwater flow models: 2. Applications

USGS Publications Warehouse

Cooley, Richard L.

1983-01-01

This paper investigates factors influencing the degree of improvement in estimates of parameters of a nonlinear regression groundwater flow model by incorporating prior information of unknown reliability. Consideration of expected behavior of the regression solutions and results of a hypothetical modeling problem lead to several general conclusions. First, if the parameters are properly scaled, linearized expressions for the mean square error (MSE) in parameter estimates of a nonlinear model will often behave very nearly as if the model were linear. Second, by using prior information, the MSE in properly scaled parameters can be reduced greatly over the MSE of ordinary least squares estimates of parameters. Third, plots of estimated MSE and the estimated standard deviation of MSE versus an auxiliary parameter (the ridge parameter) specifying the degree of influence of the prior information on regression results can help determine the potential for improvement of parameter estimates. Fourth, proposed criteria can be used to make appropriate choices for the ridge parameter and another parameter expressing degree of overall bias in the prior information. Results of a case study of Truckee Meadows, Reno-Sparks area, Washoe County, Nevada, conform closely to the results of the hypothetical problem. In the Truckee Meadows case, incorporation of prior information did not greatly change the parameter estimates from those obtained by ordinary least squares. However, the analysis showed that both sets of estimates are more reliable than suggested by the standard errors from ordinary least squares.

System health monitoring using multiple-model adaptive estimation techniques

NASA Astrophysics Data System (ADS)

Sifford, Stanley Ryan

Monitoring system health for fault detection and diagnosis by tracking system parameters concurrently with state estimates is approached using a new multiple-model adaptive estimation (MMAE) method. This novel method is called GRid-based Adaptive Parameter Estimation (GRAPE). GRAPE expands existing MMAE methods by using new techniques to sample the parameter space. GRAPE expands on MMAE with the hypothesis that sample models can be applied and resampled without relying on a predefined set of models. GRAPE is initially implemented in a linear framework using Kalman filter models. A more generalized GRAPE formulation is presented using extended Kalman filter (EKF) models to represent nonlinear systems. GRAPE can handle both time invariant and time varying systems as it is designed to track parameter changes. Two techniques are presented to generate parameter samples for the parallel filter models. The first approach is called selected grid-based stratification (SGBS). SGBS divides the parameter space into equally spaced strata. The second approach uses Latin Hypercube Sampling (LHS) to determine the parameter locations and minimize the total number of required models. LHS is particularly useful when the parameter dimensions grow. Adding more parameters does not require the model count to increase for LHS. Each resample is independent of the prior sample set other than the location of the parameter estimate. SGBS and LHS can be used for both the initial sample and subsequent resamples. Furthermore, resamples are not required to use the same technique. Both techniques are demonstrated for both linear and nonlinear frameworks. The GRAPE framework further formalizes the parameter tracking process through a general approach for nonlinear systems. These additional methods allow GRAPE to either narrow the focus to converged values within a parameter range or expand the range in the appropriate direction to track the parameters outside the current parameter range boundary. Customizable rules define the specific resample behavior when the GRAPE parameter estimates converge. Convergence itself is determined from the derivatives of the parameter estimates using a simple moving average window to filter out noise. The system can be tuned to match the desired performance goals by making adjustments to parameters such as the sample size, convergence criteria, resample criteria, initial sampling method, resampling method, confidence in prior sample covariances, sample delay, and others.

Heat and Mass Transfer in an L Shaped Porous Medium

NASA Astrophysics Data System (ADS)

Salman Ahmed, N. J.; Azeem; Yunus Khan, T. M.

2017-08-01

This article is an extension to the heat transfer in L-shaped porous medium by including the mass diffusion. The heat and mass transfer in the porous domain is represented by three coupled partial differential equations representing the fluid movement, energy transport and mass transport. The equations are converted into algebraic form of equations by the application of finite element method that can be conveniently solved by matrix method. An iterative approach is adopted to solve the coupled equations by setting suitable convergence criterion. The results are discussed in terms of heat transfer characteristics influenced by physical parameters such as buoyancy ratio, Lewis number, Rayleigh number etc. It is found that these physical parameters have significant effect on heat and mass transfer behavior of L-shaped porous medium.

Bonded orthotropic strips with cracks

NASA Technical Reports Server (NTRS)

Delale, F.; Erdogan, F.

1978-01-01

The elastostatic problem for a nonhomogeneous plane which consists of two sets of periodically arranged dissimilar orthotropic strips is considered. First, the problem of cracks fully imbedded into the homogeneous strips is considered. Then, the singular behavior of the stresses for two special crack geometries is studied in some detail. The first is the case of a broken laminate in which the crack tips touch the interfaces. The second is the case of cracks crossing the interfaces. A number of numerical examples are worked out in order to separate the primary material parameters influencing the stress intensity factors and the powers of stress singularity, and to determine the trends regarding the influence of the secondary parameters. Finally, some numerical results are given for the stress intensity factors in certain basic crack geometries and for typical material combinations.

Lods, wrods, and mods: the interpretation of lod scores calculated under different models.

PubMed

Hodge, S E; Elston, R C

1994-01-01

In this paper we examine the relationships among classical lod scores, "wrod" scores (lod scores calculated under the wrong genetic model), and "mod" scores (lod scores maximized over genetic model parameters). We compare the behavior of these scores when the state of nature is linkage to their behavior when the state of nature is no linkage. We describe sufficient conditions for mod scores to be valid and discuss their use to determine the correct genetic model. We show that lod scores represent a likelihood-ratio test for independence. We explain the "ascertainment-assumption-free" aspect of using mod scores to determine mode of inheritance and we set this aspect into a well-established statistical framework. Finally, we summarize practical guidelines for the use of mod scores.

Land Ice Verification and Validation Kit

DOE Office of Scientific and Technical Information (OSTI.GOV)

2015-07-15

To address a pressing need to better understand the behavior and complex interaction of ice sheets within the global Earth system, significant development of continental-scale, dynamical ice-sheet models is underway. The associated verification and validation process of these models is being coordinated through a new, robust, python-based extensible software package, the Land Ice Verification and Validation toolkit (LIVV). This release provides robust and automated verification and a performance evaluation on LCF platforms. The performance V&V involves a comprehensive comparison of model performance relative to expected behavior on a given computing platform. LIVV operates on a set of benchmark and testmore » data, and provides comparisons for a suite of community prioritized tests, including configuration and parameter variations, bit-4-bit evaluation, and plots of tests where differences occur.« less

Magnetism of internal surfaces in a fractal structure

NASA Astrophysics Data System (ADS)

Branco, N. S.; Chame, Anna

1993-09-01

We study the inhomogeneous magnetization behavior of an Ising ferromagnet in Sierpiński pastry shells, using a real-space renormalization group approach. Two qualitatively different regions on the fractal are distinguished: the bulk and the set of internal surfaces which border the eliminated portions. We obtain the spontaneous mean magnetizations for these regions as a function of the temperature for different values of α = JS/ JB (J S and J B are the internal surface and bulk coupling constants respectively) and different geometrical parameters b and l. The critical β exponents are obtained for the several transitions. We obtain different universality classes for the bulk transitions, depending on what occurs at the surfaces, and a step-like behavior of the magnetization as a function of the temperature of some values of b and l.

Can the identity of a behavior setting be perceived through patterns of joint action? An investigation of place perception.

PubMed

Heft, Harry; Hoch, Justine; Edmunds, Trent; Weeks, Jillian

2014-10-13

"Behavior settings" are generated by joint actions of individuals in conjunction with the milieu features (or affordances) that are available. The reported research explores the hypothesis that the identity or meaning of a behavior setting can be perceived by means of the patterns of action collectively generated by the setting's participants. A set of computer animations was created based on detailed observation of activities in everyday settings. Three experiments were conducted to assess whether perceivers could extract "structure from motion" (in this case, collective actions) that was specific to the particular behavior setting displayed by way of the animations. Two experiments assessed whether individuals could accurately perceive the identity of the behavior settings with such displays, and a third experiment indirectly examined this possibility by evaluating whether setting possibilities and constraints were recognized. The results offered some support for the hypothesis, and suggested several refinements in how to conceptualize a typology of behavior settings. An ecological approach to place perception is also discussed.

Group contribution methodology based on the statistical associating fluid theory for heteronuclear molecules formed from Mie segments.

PubMed

Papaioannou, Vasileios; Lafitte, Thomas; Avendaño, Carlos; Adjiman, Claire S; Jackson, George; Müller, Erich A; Galindo, Amparo

2014-02-07

A generalization of the recent version of the statistical associating fluid theory for variable range Mie potentials [Lafitte et al., J. Chem. Phys. 139, 154504 (2013)] is formulated within the framework of a group contribution approach (SAFT-γ Mie). Molecules are represented as comprising distinct functional (chemical) groups based on a fused heteronuclear molecular model, where the interactions between segments are described with the Mie (generalized Lennard-Jonesium) potential of variable attractive and repulsive range. A key feature of the new theory is the accurate description of the monomeric group-group interactions by application of a high-temperature perturbation expansion up to third order. The capabilities of the SAFT-γ Mie approach are exemplified by studying the thermodynamic properties of two chemical families, the n-alkanes and the n-alkyl esters, by developing parameters for the methyl, methylene, and carboxylate functional groups (CH3, CH2, and COO). The approach is shown to describe accurately the fluid-phase behavior of the compounds considered with absolute average deviations of 1.20% and 0.42% for the vapor pressure and saturated liquid density, respectively, which represents a clear improvement over other existing SAFT-based group contribution approaches. The use of Mie potentials to describe the group-group interaction is shown to allow accurate simultaneous descriptions of the fluid-phase behavior and second-order thermodynamic derivative properties of the pure fluids based on a single set of group parameters. Furthermore, the application of the perturbation expansion to third order for the description of the reference monomeric fluid improves the predictions of the theory for the fluid-phase behavior of pure components in the near-critical region. The predictive capabilities of the approach stem from its formulation within a group-contribution formalism: predictions of the fluid-phase behavior and thermodynamic derivative properties of compounds not included in the development of group parameters are demonstrated. The performance of the theory is also critically assessed with predictions of the fluid-phase behavior (vapor-liquid and liquid-liquid equilibria) and excess thermodynamic properties of a variety of binary mixtures, including polymer solutions, where very good agreement with the experimental data is seen, without the need for adjustable mixture parameters.

A simple approach for the modeling of an ODS steel mechanical behavior in pilgering conditions

NASA Astrophysics Data System (ADS)

Vanegas-Márquez, E.; Mocellin, K.; Toualbi, L.; de Carlan, Y.; Logé, R. E.

2012-01-01

The optimization of the forming of ODS tubes is linked to the choice of an appropriated constitutive model for modeling the metal forming process. In the framework of a unified plastic constitutive theory, the strain-controlled cyclic characteristics of a ferritic ODS steel were analyzed and modeled with two different tests. The first test is a classical tension-compression test, and leads to cyclic softening at low to intermediate strain amplitudes. The second test consists in alternated uniaxial compressions along two perpendicular axes, and is selected based on the similarities with the loading path induced by the Fe-14Cr-1W-Ti ODS cladding tube pilgering process. This second test exhibits cyclic hardening at all tested strain amplitudes. Since variable strain amplitudes prevail in pilgering conditions, the parameters of the considered constitutive law were identified based on a loading sequence including strain amplitude changes. A proposed semi automated inverse analysis methodology is shown to efficiently provide optimal sets of parameters for the considered loading sequences. When compared to classical approaches, the model involves a reduced number of parameters, while keeping a good ability to capture stress changes induced by strain amplitude changes. Furthermore, the methodology only requires one test, which is an advantage when the amount of available material is limited. As two distinct sets of parameters were identified for the two considered tests, it is recommended to consider the loading path when modeling cold forming of the ODS steel.

Performance comparison of extracellular spike sorting algorithms for single-channel recordings.

PubMed

Wild, Jiri; Prekopcsak, Zoltan; Sieger, Tomas; Novak, Daniel; Jech, Robert

2012-01-30

Proper classification of action potentials from extracellular recordings is essential for making an accurate study of neuronal behavior. Many spike sorting algorithms have been presented in the technical literature. However, no comparative analysis has hitherto been performed. In our study, three widely-used publicly-available spike sorting algorithms (WaveClus, KlustaKwik, OSort) were compared with regard to their parameter settings. The algorithms were evaluated using 112 artificial signals (publicly available online) with 2-9 different neurons and varying noise levels between 0.00 and 0.60. An optimization technique based on Adjusted Mutual Information was employed to find near-optimal parameter settings for a given artificial signal and algorithm. All three algorithms performed significantly better (p<0.01) with optimized parameters than with the default ones. WaveClus was the most accurate spike sorting algorithm, receiving the best evaluation score for 60% of all signals. OSort operated at almost five times the speed of the other algorithms. In terms of accuracy, OSort performed significantly less well (p<0.01) than WaveClus for signals with a noise level in the range 0.15-0.30. KlustaKwik achieved similar scores to WaveClus for signals with low noise level 0.00-0.15 and was worse otherwise. In conclusion, none of the three compared algorithms was optimal in general. The accuracy of the algorithms depended on proper choice of the algorithm parameters and also on specific properties of the examined signal. Copyright © 2011 Elsevier B.V. All rights reserved.

An opinion-driven behavioral dynamics model for addictive behaviors

NASA Astrophysics Data System (ADS)

Moore, Thomas W.; Finley, Patrick D.; Apelberg, Benjamin J.; Ambrose, Bridget K.; Brodsky, Nancy S.; Brown, Theresa J.; Husten, Corinne; Glass, Robert J.

2015-04-01

We present a model of behavioral dynamics that combines a social network-based opinion dynamics model with behavioral mapping. The behavioral component is discrete and history-dependent to represent situations in which an individual's behavior is initially driven by opinion and later constrained by physiological or psychological conditions that serve to maintain the behavior. Individuals are modeled as nodes in a social network connected by directed edges. Parameter sweeps illustrate model behavior and the effects of individual parameters and parameter interactions on model results. Mapping a continuous opinion variable into a discrete behavioral space induces clustering on directed networks. Clusters provide targets of opportunity for influencing the network state; however, the smaller the network the greater the stochasticity and potential variability in outcomes. This has implications both for behaviors that are influenced by close relationships verses those influenced by societal norms and for the effectiveness of strategies for influencing those behaviors.

Bifurcation and Stability Analysis of the Equilibrium States in Thermodynamic Systems in a Small Vicinity of the Equilibrium Values of Parameters

NASA Astrophysics Data System (ADS)

Barsuk, Alexandr A.; Paladi, Florentin

2018-04-01

The dynamic behavior of thermodynamic system, described by one order parameter and one control parameter, in a small neighborhood of ordinary and bifurcation equilibrium values of the system parameters is studied. Using the general methods of investigating the branching (bifurcations) of solutions for nonlinear equations, we performed an exhaustive analysis of the order parameter dependences on the control parameter in a small vicinity of the equilibrium values of parameters, including the stability analysis of the equilibrium states, and the asymptotic behavior of the order parameter dependences on the control parameter (bifurcation diagrams). The peculiarities of the transition to an unstable state of the system are discussed, and the estimates of the transition time to the unstable state in the neighborhood of ordinary and bifurcation equilibrium values of parameters are given. The influence of an external field on the dynamic behavior of thermodynamic system is analyzed, and the peculiarities of the system dynamic behavior are discussed near the ordinary and bifurcation equilibrium values of parameters in the presence of external field. The dynamic process of magnetization of a ferromagnet is discussed by using the general methods of bifurcation and stability analysis presented in the paper.

Anisotropic cosmological solutions in R + R^2 gravity

NASA Astrophysics Data System (ADS)

Müller, Daniel; Ricciardone, Angelo; Starobinsky, Alexei A.; Toporensky, Aleksey

2018-04-01

In this paper we investigate the past evolution of an anisotropic Bianchi I universe in R+R^2 gravity. Using the dynamical system approach we show that there exists a new two-parameter set of solutions that includes both an isotropic "false radiation" solution and an anisotropic generalized Kasner solution, which is stable. We derive the analytic behavior of the shear from a specific property of f( R) gravity and the analytic asymptotic form of the Ricci scalar when approaching the initial singularity. Finally, we numerically check our results.

Behavioral and physiological reactions in dogs to a veterinary examination: Owner-dog interactions improve canine well-being.

PubMed

Csoltova, Erika; Martineau, Michaël; Boissy, Alain; Gilbert, Caroline

2017-08-01

In order to improve well-being of dogs during veterinary visits, we aimed to investigate the effect of human social interactions on behavior and physiology during routine examination. Firstly, we assessed the impact of a standardized veterinary examination on behavioral and physiological indicators of stress in dogs. Secondly, we examined whether the owner's tactile and verbal interactions with the dog influenced behavioral and physiological stress-associated parameters. A randomized within-subjects crossover design was used to examine behavior (n=33), rectal temperature (n=33), heart rate (HR) (n=18), maximal ocular surface temperature (max OST) (n=13) and salivary cortisol concentrations (n=10) in healthy privately owned pet dogs. The study consisted of two experimental conditions: a) "contact" - owner petting and talking to the dog during the examination; b) "non-contact" - owner present during the examination but not allowed to interact with the dog. Our findings showed that the veterinary examinations produced acute stress responses in dogs during both "contact" and "non-contact" conditions, with significant increases in lip licking, HR, and max OST. A significant decrease in attempts to jump off the examination table (p=0.002) was observed during the examination in the "contact" compared to the "non-contact" condition. In addition, interactions of owners showed an attenuating effect on HR (p=0.018) and max OST (p=0.011) in their dogs. The testing order (first vs. second visit) had no impact on behavioral and physiological parameters, suggesting that dogs did not habituate or sensitize to the examination procedure. Moreover, the duration of the owner-dog interactions had no significant impact on the behavioral and physiological responses of their dogs. This study demonstrates that owner-dog interactions improve the well-being of dogs during a veterinary examination. Future research may assist in further understanding the mechanisms associated with reducing stress in dogs in similar settings. Copyright © 2017 Elsevier Inc. All rights reserved.

Modeling metabolic networks in C. glutamicum: a comparison of rate laws in combination with various parameter optimization strategies

PubMed Central

Dräger, Andreas; Kronfeld, Marcel; Ziller, Michael J; Supper, Jochen; Planatscher, Hannes; Magnus, Jørgen B; Oldiges, Marco; Kohlbacher, Oliver; Zell, Andreas

2009-01-01

Background To understand the dynamic behavior of cellular systems, mathematical modeling is often necessary and comprises three steps: (1) experimental measurement of participating molecules, (2) assignment of rate laws to each reaction, and (3) parameter calibration with respect to the measurements. In each of these steps the modeler is confronted with a plethora of alternative approaches, e. g., the selection of approximative rate laws in step two as specific equations are often unknown, or the choice of an estimation procedure with its specific settings in step three. This overall process with its numerous choices and the mutual influence between them makes it hard to single out the best modeling approach for a given problem. Results We investigate the modeling process using multiple kinetic equations together with various parameter optimization methods for a well-characterized example network, the biosynthesis of valine and leucine in C. glutamicum. For this purpose, we derive seven dynamic models based on generalized mass action, Michaelis-Menten and convenience kinetics as well as the stochastic Langevin equation. In addition, we introduce two modeling approaches for feedback inhibition to the mass action kinetics. The parameters of each model are estimated using eight optimization strategies. To determine the most promising modeling approaches together with the best optimization algorithms, we carry out a two-step benchmark: (1) coarse-grained comparison of the algorithms on all models and (2) fine-grained tuning of the best optimization algorithms and models. To analyze the space of the best parameters found for each model, we apply clustering, variance, and correlation analysis. Conclusion A mixed model based on the convenience rate law and the Michaelis-Menten equation, in which all reactions are assumed to be reversible, is the most suitable deterministic modeling approach followed by a reversible generalized mass action kinetics model. A Langevin model is advisable to take stochastic effects into account. To estimate the model parameters, three algorithms are particularly useful: For first attempts the settings-free Tribes algorithm yields valuable results. Particle swarm optimization and differential evolution provide significantly better results with appropriate settings. PMID:19144170

Deformation partitioning provides insight into elastic, plastic, and viscous contributions to bone material behavior.

PubMed

Ferguson, V L

2009-08-01

The relative contributions of elastic, plastic, and viscous material behavior are poorly described by the separate extraction and analysis of the plane strain modulus, E('), the contact hardness, H(c) (a hybrid parameter encompassing both elastic and plastic behavior), and various viscoelastic material constants. A multiple element mechanical model enables the partitioning of a single indentation response into its fundamental elastic, plastic, and viscous deformation components. The objective of this study was to apply deformation partitioning to explore the role of hydration, tissue type, and degree of mineralization in bone and calcified cartilage. Wet, ethanol-dehydrated, and PMMA-embedded equine cortical bone samples and PMMA-embedded human femoral head tissues were analyzed for contributions of elastic, plastic and viscous deformation to the overall nanoindentation response at each site. While the alteration of hydration state had little effect on any measure of deformation, unembedded tissues demonstrated significantly greater measures of resistance to plastic deformation than PMMA-embedded tissues. The PMMA appeared to mechanically stabilize the tissues and prevent extensive permanent deformation within the bone material. Increasing mineral volume fraction correlated with positive changes in E('), H(c), and resistance to plastic deformation, H; however, the partitioned deformation components were generally unaffected by mineralization. The contribution of viscous deformation was minimal and may only play a significant role in poorly mineralized tissues. Deformation partitioning enables a detailed interpretation of the elastic, plastic, and viscous contributions to the nanomechanical behavior of mineralized tissues that is not possible when examining modulus and contact hardness alone. Varying experimental or biological factors, such as hydration or mineralization level, enables the understanding of potential mechanisms for specific mechanical behavior patterns that would otherwise be hidden within a more complex set of material property parameters.

Report on in-situ studies of flash sintering of uranium dioxide

DOE Office of Scientific and Technical Information (OSTI.GOV)

Raftery, Alicia Marie

Flash sintering is a novel type of field assisted sintering that uses an electric field and current to provide densification of materials on very short time scales. The potential for field assisted sintering techniques to be used in producing nuclear fuel is gaining recognition due to the potential economic benefits and improvements in material properties. The flash sintering behavior has so far been linked to applied and material parameters, but the underlying mechanisms active during flash sintering have yet to be identified. This report summarizes the efforts to investigate flash sintering of uranium dioxide using dilatometer studies at Los Alamosmore » National Laboratory and two separate sets of in-situ studies at Brookhaven National Laboratory’s NSLS-II XPD-1 beamline. The purpose of the dilatometer studies was to understand individual parameter (applied and material) effects on the flash behavior and the purpose of the in-situ studies was to better understand the mechanisms active during flash sintering. As far as applied parameters, it was found that stoichiometry, or oxygen-to-metal ratio, has a significant effect on the flash behavior (time to flash and speed of flash). Composite systems were found to have degraded sintering behavior relative to pure UO 2. The critical field studies are complete for UO 2.00 and will be analyzed against an existing model for comparison. The in-situ studies showed that the strength of the field and current are directly related to the sample temperature, with temperature-driven phase changes occurring at high values. The existence of an ‘incubation time’ has been questioned, due to a continuous change in lattice parameter values from the moment that the field is applied. Some results from the in-situ experiments, which should provide evidence regarding ion migration, are still being analyzed. Some preliminary conclusions can be made from these results with regard to using field assisted sintering to fabricate nuclear fuel. First, the pure UO 2-based system shows promising behavior with flash sintering, but composite systems are likely to show better sintering behavior with spark plasma sintering. Efforts to develop these methods should therefore be tailored towards the likelihood of success. Additionally, modeling is a rapidly developing aspect of current flash sintering research and should be used in parallel with experiments. Ultimately, ongoing flash sintering studies on various materials, like those summarized in this report, are rapidly contributing to the feasibility of controlling this method for use in the future.« less

Simulating the behavior of volatiles belonging to the C-O-H-S system in silicate melts under magmatic conditions with the software D-Compress

NASA Astrophysics Data System (ADS)

Burgisser, Alain; Alletti, Marina; Scaillet, Bruno

2015-06-01

Modeling magmatic degassing, or how the volatile distribution between gas and melt changes at pressure varies, is a complex task that involves a large number of thermodynamical relationships and that requires dedicated software. This article presents the software D-Compress, which computes the gas and melt volatile composition of five element sets in magmatic systems (O-H, S-O-H, C-S-O-H, C-S-O-H-Fe, and C-O-H). It has been calibrated so as to simulate the volatiles coexisting with three common types of silicate melts (basalt, phonolite, and rhyolite). Operational temperatures depend on melt composition and range from 790 to 1400 °C. A specificity of D-Compress is the calculation of volatile composition as pressure varies along a (de)compression path between atmospheric and 3000 bars. This software was prepared so as to maximize versatility by proposing different sets of input parameters. In particular, whenever new solubility laws on specific melt compositions are available, the model parameters can be easily tuned to run the code on that composition. Parameter gaps were minimized by including sets of chemical species for which calibration data were available over a wide range of pressure, temperature, and melt composition. A brief description of the model rationale is followed by the presentation of the software capabilities. Examples of use are then presented with outputs comparisons between D-Compress and other currently available thermodynamical models. The compiled software and the source code are available as electronic supplementary materials.

Modeling of the flow behavior of SAE 8620H combing microstructure evolution in hot forming

NASA Astrophysics Data System (ADS)

Fu, Xiaobin; Wang, Baoyu; Tang, Xuefeng

2017-10-01

With the development of net-shape forming technology, hot forming process is widely applied to manufacturing gear parts, during which, materials suffer severe plastic distortion and microstructure changes continually. In this paper, to understand and model the flow behavior and microstructure evolution, SAE 8620H, a widely used gear steel, is selected as the object and the flow behavior and microstructure evolution are observed by an isothermal hot compression tests at 1273-1373 K with a strain rate of 0.1-10 s-1. Depending on the results of the compression test, a set of internal-state-variable based unified constitutive equations is put forward to describe the flow behavior and microstructure evaluation of SAE 8620H. Moreover, the evaluation of the dislocation density and the fraction of dynamic recrystallization based on the theory of thermal activation is modeled and reincorporated into the constitutive law. The material parameters in the constitutive model are calculated based on the measured flow stress and dynamic recrystallization fraction. The predicted flow stress under different deformation conditions has a good agreement with the measured results.

Model calculation of Cr dissolution behavior of ODS ferritic steel in high-temperature flowing sodium environment

NASA Astrophysics Data System (ADS)

Ohtsuka, Satoshi; Tanno, Takashi; Oka, Hiroshi; Yano, Yasuhide; Kato, Shoichi; Furukawa, Tomohiro; Kaito, Takeji

2018-07-01

A calculation model was constructed to systematically study the effects of environmental conditions (i.e. Cr concentration in sodium, test temperature, axial temperature gradient of fuel pin, and sodium flow velocity) on Cr dissolution behavior. Chromium dissolution was largely influenced by small changes in Cr concentration (i.e. chemical potential of Cr) in liquid sodium in the model calculation. Chromium concentration in sodium coolant, therefore, should be recognized as a critical parameter for the prediction and management of Cr dissolution behavior in the sodium-cooled fast reactor (SFR) core. Because the fuel column length showed no impact on dissolution behavior in the model calculation, no significant downstream effects possibly take place in the SFR fuel cladding tube due to the much shorter length compared with sodium loops in the SFR plant and the large axial temperature gradient. The calculated profile of Cr concentration along the wall-thickness direction was consistent with that measured in BOR-60 irradiation test where Cr concentration in inlet sodium bulk flow was set at 0.07 wt ppm in the calculation.

A Regionalization Approach to select the final watershed parameter set among the Pareto solutions

NASA Astrophysics Data System (ADS)

Park, G. H.; Micheletty, P. D.; Carney, S.; Quebbeman, J.; Day, G. N.

2017-12-01

The calibration of hydrological models often results in model parameters that are inconsistent with those from neighboring basins. Considering that physical similarity exists within neighboring basins some of the physically related parameters should be consistent among them. Traditional manual calibration techniques require an iterative process to make the parameters consistent, which takes additional effort in model calibration. We developed a multi-objective optimization procedure to calibrate the National Weather Service (NWS) Research Distributed Hydrological Model (RDHM), using the Nondominant Sorting Genetic Algorithm (NSGA-II) with expert knowledge of the model parameter interrelationships one objective function. The multi-objective algorithm enables us to obtain diverse parameter sets that are equally acceptable with respect to the objective functions and to choose one from the pool of the parameter sets during a subsequent regionalization step. Although all Pareto solutions are non-inferior, we exclude some of the parameter sets that show extremely values for any of the objective functions to expedite the selection process. We use an apriori model parameter set derived from the physical properties of the watershed (Koren et al., 2000) to assess the similarity for a given parameter across basins. Each parameter is assigned a weight based on its assumed similarity, such that parameters that are similar across basins are given higher weights. The parameter weights are useful to compute a closeness measure between Pareto sets of nearby basins. The regionalization approach chooses the Pareto parameter sets that minimize the closeness measure of the basin being regionalized. The presentation will describe the results of applying the regionalization approach to a set of pilot basins in the Upper Colorado basin as part of a NASA-funded project.

Crystallization tendency of active pharmaceutical ingredients following rapid solvent evaporation--classification and comparison with crystallization tendency from undercooled melts.

PubMed

Van Eerdenbrugh, Bernard; Baird, Jared A; Taylor, Lynne S

2010-09-01

In this study, the crystallization behavior of a variety of compounds was studied following rapid solvent evaporation using spin coating. Initial screening to determine model compound suitability was performed using a structurally diverse set of 51 compounds in three different solvent systems [dichloromethane (DCM), a 1:1 (w/w) dichloromethane/ethanol mixture (MIX), and ethanol (EtOH)]. Of this starting set of 153 drug-solvent combinations, 93 (40 compounds) were selected for further evaluation based on solubility, chemical solution stability, and processability criteria. These systems were spin coated and their crystallization was monitored using polarized light microscopy (7 days, dry conditions). The crystallization behavior of the samples could be classified as rapid (Class I: 39 cases), intermediate (Class II: 23 cases), or slow (Class III: 31 cases). The solvent system employed influenced the classification outcome for only four of the compounds. The various compounds showed very diverse crystallization behavior. Upon comparison of classification results with those of a previous study, where cooling from the melt was used as a preparation technique, a good similarity was found whereby 68% of the cases were identically classified. Multivariate analysis was performed using a set of relevant physicochemical compound characteristics. It was found that a number of these parameters tended to differ between the different classes. These could be further interpreted in terms of the nature of the crystallization process. Additional multivariate analysis on the separate classes of compounds indicated some potential in predicting the crystallization tendency of a given compound.

Tuning of Kalman filter parameters via genetic algorithm for state-of-charge estimation in battery management system.

PubMed

Ting, T O; Man, Ka Lok; Lim, Eng Gee; Leach, Mark

2014-01-01

In this work, a state-space battery model is derived mathematically to estimate the state-of-charge (SoC) of a battery system. Subsequently, Kalman filter (KF) is applied to predict the dynamical behavior of the battery model. Results show an accurate prediction as the accumulated error, in terms of root-mean-square (RMS), is a very small value. From this work, it is found that different sets of Q and R values (KF's parameters) can be applied for better performance and hence lower RMS error. This is the motivation for the application of a metaheuristic algorithm. Hence, the result is further improved by applying a genetic algorithm (GA) to tune Q and R parameters of the KF. In an online application, a GA can be applied to obtain the optimal parameters of the KF before its application to a real plant (system). This simply means that the instantaneous response of the KF is not affected by the time consuming GA as this approach is applied only once to obtain the optimal parameters. The relevant workable MATLAB source codes are given in the appendix to ease future work and analysis in this area.

Tuning of Kalman Filter Parameters via Genetic Algorithm for State-of-Charge Estimation in Battery Management System

PubMed Central

Ting, T. O.; Lim, Eng Gee

2014-01-01

In this work, a state-space battery model is derived mathematically to estimate the state-of-charge (SoC) of a battery system. Subsequently, Kalman filter (KF) is applied to predict the dynamical behavior of the battery model. Results show an accurate prediction as the accumulated error, in terms of root-mean-square (RMS), is a very small value. From this work, it is found that different sets of Q and R values (KF's parameters) can be applied for better performance and hence lower RMS error. This is the motivation for the application of a metaheuristic algorithm. Hence, the result is further improved by applying a genetic algorithm (GA) to tune Q and R parameters of the KF. In an online application, a GA can be applied to obtain the optimal parameters of the KF before its application to a real plant (system). This simply means that the instantaneous response of the KF is not affected by the time consuming GA as this approach is applied only once to obtain the optimal parameters. The relevant workable MATLAB source codes are given in the appendix to ease future work and analysis in this area. PMID:25162041

Dual learning processes underlying human decision-making in reversal learning tasks: functional significance and evidence from the model fit to human behavior

PubMed Central

Bai, Yu; Katahira, Kentaro; Ohira, Hideki

2014-01-01

Humans are capable of correcting their actions based on actions performed in the past, and this ability enables them to adapt to a changing environment. The computational field of reinforcement learning (RL) has provided a powerful explanation for understanding such processes. Recently, the dual learning system, modeled as a hybrid model that incorporates value update based on reward-prediction error and learning rate modulation based on the surprise signal, has gained attention as a model for explaining various neural signals. However, the functional significance of the hybrid model has not been established. In the present study, we used computer simulation in a reversal learning task to address functional significance in a probabilistic reversal learning task. The hybrid model was found to perform better than the standard RL model in a large parameter setting. These results suggest that the hybrid model is more robust against the mistuning of parameters compared with the standard RL model when decision-makers continue to learn stimulus-reward contingencies, which can create abrupt changes. The parameter fitting results also indicated that the hybrid model fit better than the standard RL model for more than 50% of the participants, which suggests that the hybrid model has more explanatory power for the behavioral data than the standard RL model. PMID:25161635

Evaluation of bacterial run and tumble motility parameters through trajectory analysis

NASA Astrophysics Data System (ADS)

Liang, Xiaomeng; Lu, Nanxi; Chang, Lin-Ching; Nguyen, Thanh H.; Massoudieh, Arash

2018-04-01

In this paper, a method for extraction of the behavior parameters of bacterial migration based on the run and tumble conceptual model is described. The methodology is applied to the microscopic images representing the motile movement of flagellated Azotobacter vinelandii. The bacterial cells are considered to change direction during both runs and tumbles as is evident from the movement trajectories. An unsupervised cluster analysis was performed to fractionate each bacterial trajectory into run and tumble segments, and then the distribution of parameters for each mode were extracted by fitting mathematical distributions best representing the data. A Gaussian copula was used to model the autocorrelation in swimming velocity. For both run and tumble modes, Gamma distribution was found to fit the marginal velocity best, and Logistic distribution was found to represent better the deviation angle than other distributions considered. For the transition rate distribution, log-logistic distribution and log-normal distribution, respectively, was found to do a better job than the traditionally agreed exponential distribution. A model was then developed to mimic the motility behavior of bacteria at the presence of flow. The model was applied to evaluate its ability to describe observed patterns of bacterial deposition on surfaces in a micro-model experiment with an approach velocity of 200 μm/s. It was found that the model can qualitatively reproduce the attachment results of the micro-model setting.

PubMed Central

SARTINI, M.; PANATTO, D.; PERDELLI, F.; CRISTINA, M.L.

2013-01-01

Summary An experimental study was conducted in a hospital in Liguria (northern Italy) on two groups of patients with the same disease severity who were undergoing the same type of surgery (primary hemiarthroplasty). Our aim was to assessing the results of a quality- improvement scheme implemented in the operating room. The quality-improvement protocol involved analyzing a set of parameters concerning the operating team's behavior and environmental conditions that could be attributed to the operating team itself. A program of training and sanitary education was carried to rectify any improper behavior of the operating staff. Two hundred and six hip-joint replacement operations (primary hip hemiarthroplasty - ICD9-CM 81.51) all conducted in the same operating room were studied: 103 patients, i.e. operations performed before the quality-improvement scheme and 103 patients, i.e. operations performed after the quality improvement scheme; all were comparable in terms of type of surgery and severity. The scheme resulted in an improvement in both behavioral and environmental parameters and an 80% reduction in the level of microbial air contamination (p < 0.001). Patient outcomes improved in terms of average postoperative hospitalization time, the occurrence and duration of fever (>37.5°C) and microbiological contamination of surgical wounds. From an economic point of view, facility efficiency increased by 28.57%, average hospitalization time decreased (p<0.001) and a theoretical increase of € 1,441,373.58 a year in revenues was achieved. PMID:24396985

Acidic deposition, plant pests, and the fate of forest ecosystems.

PubMed

Gragnani, A; Gatto, M; Rinaldi, S

1998-12-01

We present and analyze a nonlinear dynamical system modelling forest-pests interactions and the way they are affected by acidic deposition. The model includes mechanisms of carbon and nitrogen exchange between soil and vegetation, biomass decomposition and microbial mineralization, and defoliation by pest grazers, which are partially controlled by avian or mammalian predators. Acidic deposition is assumed to directly damage vegetation, to decrease soil pH, which in turn damages roots and inhibits microbial activity, and to predispose trees to increased pest attack. All the model parameters are set to realistic values except the inflow of protons to soil and the predation mortality inflicted to the pest which are allowed to vary inside reasonable ranges. A numerical bifurcation analysis with respect to these two parameters is carried out. Five functioning modes are uncovered: (i) pest-free equilibrium; (ii) pest persisting at endemic equilibrium; (iii) forest-pest permanent oscillations; (iv) bistable behavior with the system converging either to pest-free equilibrium or endemic pest presence in accordance with initial conditions; (v) bistable behavior with convergence to endemic pest presence or permanent oscillations depending on initial conditions. Catastrophic bifurcations between the different behavior modes are possible, provided the abundance of predators is not too small. Numerical simulation shows that increasing acidic load can lead the forest to collapse in a short time period without important warning signals. Copyright 1998 Academic Press.

Weak Interactions Govern the Viscosity of Concentrated Antibody Solutions: High-Throughput Analysis Using the Diffusion Interaction Parameter

PubMed Central

Connolly, Brian D.; Petry, Chris; Yadav, Sandeep; Demeule, Barthélemy; Ciaccio, Natalie; Moore, Jamie M.R.; Shire, Steven J.; Gokarn, Yatin R.

2012-01-01

Weak protein-protein interactions are thought to modulate the viscoelastic properties of concentrated antibody solutions. Predicting the viscoelastic behavior of concentrated antibodies from their dilute solution behavior is of significant interest and remains a challenge. Here, we show that the diffusion interaction parameter (kD), a component of the osmotic second virial coefficient (B2) that is amenable to high-throughput measurement in dilute solutions, correlates well with the viscosity of concentrated monoclonal antibody (mAb) solutions. We measured the kD of 29 different mAbs (IgG1 and IgG4) in four different solvent conditions (low and high ion normality) and found a linear dependence between kD and the exponential coefficient that describes the viscosity concentration profiles (|R| ≥ 0.9). Through experimentally measured effective charge measurements, under low ion normality where the electroviscous effect can dominate, we show that the mAb solution viscosity is poorly correlated with the mAb net charge (|R| ≤ 0.6). With this large data set, our results provide compelling evidence in support of weak intermolecular interactions, in contrast to the notion that the electroviscous effect is important in governing the viscoelastic behavior of concentrated mAb solutions. Our approach is particularly applicable as a screening tool for selecting mAbs with desirable viscosity properties early during lead candidate selection. PMID:22828333

Collision-avoidance behaviors of minimally restrained flying locusts to looming stimuli

PubMed Central

Chan, R. WM.; Gabbiani, F.

2013-01-01

SUMMARY Visually guided collision avoidance is of paramount importance in flight, for instance to allow escape from potential predators. Yet, little is known about the types of collision-avoidance behaviors that may be generated by flying animals in response to an impending visual threat. We studied the behavior of minimally restrained locusts flying in a wind tunnel as they were subjected to looming stimuli presented to the side of the animal, simulating the approach of an object on a collision course. Using high-speed movie recordings, we observed a wide variety of collision-avoidance behaviors including climbs and dives away from – but also towards – the stimulus. In a more restrained setting, we were able to relate kinematic parameters of the flapping wings with yaw changes in the trajectory of the animal. Asymmetric wing flapping was most strongly correlated with changes in yaw, but we also observed a substantial effect of wing deformations. Additionally, the effect of wing deformations on yaw was relatively independent of that of wing asymmetries. Thus, flying locusts exhibit a rich range of collision-avoidance behaviors that depend on several distinct aerodynamic characteristics of wing flapping flight. PMID:23364572

How Settings Change People: Applying Behavior Setting Theory to Consumer-Run Organizations

ERIC Educational Resources Information Center

Brown, Louis D.; Shepherd, Matthew D.; Wituk, Scott A.; Meissen, Greg

2007-01-01

Self-help initiatives stand as a classic context for organizational studies in community psychology. Behavior setting theory stands as a classic conception of organizations and the environment. This study explores both, applying behavior setting theory to consumer-run organizations (CROs). Analysis of multiple data sets from all CROs in Kansas…

State Variability and Psychopathological Attractors: the Behavioural Complexity as Discriminating Factor Between the Pathology and Normality Profiles

NASA Astrophysics Data System (ADS)

Marconi, Pier Luigi

369 patients, selected within a set of 1215 outpatients, were studied. The data were clustered into two set: the baseline set and the endpoint set. The clinical parameters had a higher variability at the baseline than at the endpoint. 4 to 5 factors were extracted in total group and 3 subgroups (190 "affective", 34 type-B personality, 166 without any of both disorders). In all subgroups there was a background pattern of 6 components: 3 components confirming the trifactorial temperamental model of Cloninger; 1 component related to the quality of social relationships; 2 components (that are the main components of factorial model about in all groups) relating to quality of life and adjustment self perceived by patients, and to pattern of dysfunctional behavior, inner feelings, and thought processes externally evaluated. These background components seem to aggregate differently in the subgroups in accordance to the clinical diagnosis. These patterns may be interpreted as expression of an increased "coherence" among parameters due to a lack of flexibility caused by the illness. The different class of illness can be further distinguished by intensity of maladjustment, that is related to the intensity of clinical signs just only at the baseline. These data suggest that the main interfering factors are clinical psychopathology at baseline and stable personality traits at endpoint. This persistent chronic maladjustment personality-driven is evidenced after the clinical disorder was cured by treatment. An interpretative model is presented by the author.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chremos, Alexandros, E-mail: achremos@imperial.ac.uk; Nikoubashman, Arash, E-mail: arashn@princeton.edu; Panagiotopoulos, Athanassios Z.

In this contribution, we develop a coarse-graining methodology for mapping specific block copolymer systems to bead-spring particle-based models. We map the constituent Kuhn segments to Lennard-Jones particles, and establish a semi-empirical correlation between the experimentally determined Flory-Huggins parameter χ and the interaction of the model potential. For these purposes, we have performed an extensive set of isobaric–isothermal Monte Carlo simulations of binary mixtures of Lennard-Jones particles with the same size but with asymmetric energetic parameters. The phase behavior of these monomeric mixtures is then extended to chains with finite sizes through theoretical considerations. Such a top-down coarse-graining approach is importantmore » from a computational point of view, since many characteristic features of block copolymer systems are on time and length scales which are still inaccessible through fully atomistic simulations. We demonstrate the applicability of our method for generating parameters by reproducing the morphology diagram of a specific diblock copolymer, namely, poly(styrene-b-methyl methacrylate), which has been extensively studied in experiments.« less

On magnetohydrodynamic flow of second grade nanofluid over a nonlinear stretching sheet

NASA Astrophysics Data System (ADS)

Hayat, Tasawar; Aziz, Arsalan; Muhammad, Taseer; Ahmad, Bashir

2016-06-01

This research article addresses the magnetohydrodynamic (MHD) flow of second grade nanofluid over a nonlinear stretching sheet. Heat and mass transfer aspects are investigated through the thermophoresis and Brownian motion effects. Second grade fluid is assumed electrically conducting through a non-uniform applied magnetic field. Mathematical formulation is developed subject to small magnetic Reynolds number and boundary layer assumptions. Newly constructed condition having zero mass flux of nanoparticles at the boundary is incorporated. Transformations have been invoked for the reduction of partial differential systems into the set of nonlinear ordinary differential systems. The governing nonlinear systems have been solved for local behavior. Graphical results of different influential parameters are studied and discussed in detail. Computations for skin friction coefficient and local Nusselt number have been carried out. It is observed that the effects of thermophoresis parameter on the temperature and nanoparticles concentration distributions are qualitatively similar. The temperature and nanoparticles concentration distributions are enhanced for the larger magnetic parameter.

The net fractional depth dose: a basis for a unified analytical description of FDD, TAR, TMR, and TPR.

PubMed

van de Geijn, J; Fraass, B A

1984-01-01

The net fractional depth dose (NFD) is defined as the fractional depth dose (FDD) corrected for inverse square law. Analysis of its behavior as a function of depth, field size, and source-surface distance has led to an analytical description with only seven model parameters related to straightforward physical properties. The determination of the characteristic parameter values requires only seven experimentally determined FDDs. The validity of the description has been tested for beam qualities ranging from 60Co gamma rays to 18-MV x rays, using published data from several different sources as well as locally measured data sets. The small number of model parameters is attractive for computer or hand-held calculator applications. The small amount of required measured data is important in view of practical data acquisition for implementation of a computer-based dose calculation system. The generating function allows easy and accurate generation of FDD, tissue-air ratio, tissue-maximum ratio, and tissue-phantom ratio tables.

Net fractional depth dose: a basis for a unified analytical description of FDD, TAR, TMR, and TPR

DOE Office of Scientific and Technical Information (OSTI.GOV)

van de Geijn, J.; Fraass, B.A.

The net fractional depth dose (NFD) is defined as the fractional depth dose (FDD) corrected for inverse square law. Analysis of its behavior as a function of depth, field size, and source-surface distance has led to an analytical description with only seven model parameters related to straightforward physical properties. The determination of the characteristic parameter values requires only seven experimentally determined FDDs. The validity of the description has been tested for beam qualities ranging from /sup 60/Co gamma rays to 18-MV x rays, using published data from several different sources as well as locally measured data sets. The small numbermore » of model parameters is attractive for computer or hand-held calculator applications. The small amount of required measured data is important in view of practical data acquisition for implementation of a computer-based dose calculation system. The generating function allows easy and accurate generation of FDD, tissue-air ratio, tissue-maximum ratio, and tissue-phantom ratio tables.« less

Generating Models of Infinite-State Communication Protocols Using Regular Inference with Abstraction

NASA Astrophysics Data System (ADS)

Aarts, Fides; Jonsson, Bengt; Uijen, Johan

In order to facilitate model-based verification and validation, effort is underway to develop techniques for generating models of communication system components from observations of their external behavior. Most previous such work has employed regular inference techniques which generate modest-size finite-state models. They typically suppress parameters of messages, although these have a significant impact on control flow in many communication protocols. We present a framework, which adapts regular inference to include data parameters in messages and states for generating components with large or infinite message alphabets. A main idea is to adapt the framework of predicate abstraction, successfully used in formal verification. Since we are in a black-box setting, the abstraction must be supplied externally, using information about how the component manages data parameters. We have implemented our techniques by connecting the LearnLib tool for regular inference with the protocol simulator ns-2, and generated a model of the SIP component as implemented in ns-2.

A fractional factorial probabilistic collocation method for uncertainty propagation of hydrologic model parameters in a reduced dimensional space

NASA Astrophysics Data System (ADS)

Wang, S.; Huang, G. H.; Huang, W.; Fan, Y. R.; Li, Z.

2015-10-01

In this study, a fractional factorial probabilistic collocation method is proposed to reveal statistical significance of hydrologic model parameters and their multi-level interactions affecting model outputs, facilitating uncertainty propagation in a reduced dimensional space. The proposed methodology is applied to the Xiangxi River watershed in China to demonstrate its validity and applicability, as well as its capability of revealing complex and dynamic parameter interactions. A set of reduced polynomial chaos expansions (PCEs) only with statistically significant terms can be obtained based on the results of factorial analysis of variance (ANOVA), achieving a reduction of uncertainty in hydrologic predictions. The predictive performance of reduced PCEs is verified by comparing against standard PCEs and the Monte Carlo with Latin hypercube sampling (MC-LHS) method in terms of reliability, sharpness, and Nash-Sutcliffe efficiency (NSE). Results reveal that the reduced PCEs are able to capture hydrologic behaviors of the Xiangxi River watershed, and they are efficient functional representations for propagating uncertainties in hydrologic predictions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sousa, Francisco F. G. de; Rubinger, Rero M.; Sartorelli, José C., E-mail: sartorelli@if.usp.br

We report high-resolution measurements that experimentally confirm a spiral cascade structure and a scaling relationship of shrimps in the Chua's circuit. Circuits constructed using this component allow for a comprehensive characterization of the circuit behaviors through high resolution parameter spaces. To illustrate the power of our technological development for the creation and the study of chaotic circuits, we constructed a Chua circuit and study its high resolution parameter space. The reliability and stability of the designed component allowed us to obtain data for long periods of time (∼21 weeks), a data set from which an accurate estimation of Lyapunov exponentsmore » for the circuit characterization was possible. Moreover, this data, rigorously characterized by the Lyapunov exponents, allows us to reassure experimentally that the shrimps, stable islands embedded in a domain of chaos in the parameter spaces, can be observed in the laboratory. Finally, we confirm that their sizes decay exponentially with the period of the attractor, a result expected to be found in maps of the quadratic family.« less

Using goal setting as a strategy for dietary behavior change.

PubMed

Cullen, K W; Baranowski, T; Smith, S P

2001-05-01

Recent reviews have noted that behavioral theory-based nutrition education programs are more successful at achieving food behavior change than knowledge-based programs and that a clear understanding of the mechanisms of behavior change procedures enable dietetics professionals to more effectively promote change. Successful dietary behavior change programs target 1 or more of the personal, behavioral, or environmental factors that influence the behavior of interest and apply theory-based strategies to influence or change those factors. Goal setting is a strategy that is frequently used to help people change. A 4-step goal-setting process has been identified: recognizing a need for change; establishing a goal; adopting a goal-directed activity and self-monitoring it; and self-rewarding goal attainment. The applications of goal setting in dietary interventions for adults and children are reviewed here. Because interventions using goal setting appear to promote dietary change, dietitians should consider incorporating the goal-setting strategies to enhance the behavior change process in nutrition education programs.

Child Behaviors of Young Children With Autism Spectrum Disorder Across Play Settings.

PubMed

MacDonald, Megan; Hatfield, Bridget; Twardzik, Erica

2017-01-01

The hallmark characteristics of a diagnosis of autism spectrum disorder (ASD) are deficits in social communicative skills and the use of repetitive and/or stereotyped behaviors. In addition, children with ASD experience known motor-skill delays. The purpose of this study was to examine salient child behaviors of young children with and without ASD in 2 distinctly different play settings: a traditional social-play-based setting and a motor-behavior-based play setting. Child behavior (engagement toward parent, negativity, and attention) and dyad characteristics (connectedness) were examined in 2 distinctly different play settings. Results indicated that children with ASD performed more like their peers without ASD in a social-play-based setting and less like their peers in a motor-behavior-based play setting. Aspects of our results shed light on the critical need to develop creative methods of early intervention that combine efforts in all aspects of child development, including motor-skill development.

The use of simple inflow- and storage-based heuristics equations to represent reservoir behavior in California for investigating human impacts on the water cycle

NASA Astrophysics Data System (ADS)

Solander, K.; David, C. H.; Reager, J. T.; Famiglietti, J. S.

2013-12-01

The ability to reasonably replicate reservoir behavior in terms of storage and outflow is important for studying the potential human impacts on the terrestrial water cycle. Developing a simple method for this purpose could facilitate subsequent integration in a land surface or global climate model. This study attempts to simulate monthly reservoir outflow and storage using a simple, temporally-varying set of heuristics equations with input consisting of in situ records of reservoir inflow and storage. Equations of increasing complexity relative to the number of parameters involved were tested. Only two parameters were employed in the final equations used to predict outflow and storage in an attempt to best mimic seasonal reservoir behavior while still preserving model parsimony. California reservoirs were selected for model development due to the high level of data availability and intensity of water resource management in this region relative to other areas. Calibration was achieved using observations from eight major reservoirs representing approximately 41% of the 107 largest reservoirs in the state. Parameter optimization was accomplished using the minimum RMSE between observed and modeled storage and outflow as the main objective function. Initial results obtained for a multi-reservoir average of the correlation coefficient between observed and modeled storage (resp. outflow) is of 0.78 (resp. 0.75). These results combined with the simplicity of the equations being used show promise for integration into a land surface or a global climate model. This would be invaluable for evaluations of reservoir management impacts on the flow regime and associated ecosystems as well as on the climate at both regional and global scales.

A reduced Iwan model that includes pinning for bolted joint mechanics

DOE PAGES

Brake, M. R. W.

2016-10-28

Bolted joints are prevalent in most assembled structures; however, predictive models for their behavior do not exist. Calibrated models, such as the Iwan model, are able to predict the response of a jointed structure over a range of excitations once calibrated at a nominal load. The Iwan model, though, is not widely adopted due to the high computational expense of implementation. To address this, an analytical solution of the Iwan model is derived under the hypothesis that for an arbitrary load reversal, there is a new distribution of dry friction elements, which are now stuck, that approximately resemble a scaledmore » version of the original distribution of dry friction elements. The dry friction elements internal to the Iwan model do not have a uniform set of parameters and are described by a distribution of parameters, i.e., which internal dry friction elements are stuck or slipping at a given load, that ultimately governs the behavior of the joint as it transitions from microslip to macroslip. This hypothesis allows the model to require no information from previous loading cycles. Additionally, the model is extended to include the pinning behavior inherent in a bolted joint. Modifications of the resulting framework are discussed to highlight how the constitutive model for friction can be changed (in the case of an Iwan–Stribeck formulation) or how the distribution of dry friction elements can be changed (as is the case for the Iwan plasticity model). Finally, the reduced Iwan plus pinning model is then applied to the Brake–Reuß beam in order to discuss methods to deduce model parameters from experimental data.« less

Surface energy effect on nonlinear buckling and postbuckling behavior of functionally graded piezoelectric cylindrical nanoshells under lateral pressure

NASA Astrophysics Data System (ADS)

Fang, Xue-Qian; Zhu, Chang-Song; Liu, Jin-Xi; Zhao, Jing

2018-04-01

In this paper, the surface energy effect on the nonlinear buckling and postbuckling behavior of functionally graded piezoelectric (FGP) cylindrical nanoshells subjected to lateral pressure is studied based on the electro-elastic surface/interface theory together with von-Kármán-Donnell-type kinematics of nonlinearity. The total strain energy of the FGP nanoshell, including surface energy, is derived by considering the constitutive formulations of surface phase. The principle of minimum potential energy is utilized to establish the nonlinear governing differential equations, and the singular perturbation technique is employed to obtain the asymptotic solutions. Then, two sets of comparison are conducted to validate the present work, and some numerical examples are given to study the effects of surface parameters, power law index and aspect ratio on the buckling and postbuckling behavior of FGP nanoshells. The results show that the critical buckling load and postbuckling path of FGP nanoshell are significantly size-dependent.

Entrainment and Control of Bacterial Populations: An in Silico Study over a Spatially Extended Agent Based Model.

PubMed

Mina, Petros; Tsaneva-Atanasova, Krasimira; Bernardo, Mario di

2016-07-15

We extend a spatially explicit agent based model (ABM) developed previously to investigate entrainment and control of the emergent behavior of a population of synchronized oscillating cells in a microfluidic chamber. Unlike most of the work in models of control of cellular systems which focus on temporal changes, we model individual cells with spatial dependencies which may contribute to certain behavioral responses. We use the model to investigate the response of both open loop and closed loop strategies, such as proportional control (P-control), proportional-integral control (PI-control) and proportional-integral-derivative control (PID-control), to heterogeinities and growth in the cell population, variations of the control parameters and spatial effects such as diffusion in the spatially explicit setting of a microfluidic chamber setup. We show that, as expected from the theory of phase locking in dynamical systems, open loop control can only entrain the cell population in a subset of forcing periods, with a wide variety of dynamical behaviors obtained outside these regions of entrainment. Closed-loop control is shown instead to guarantee entrainment in a much wider region of control parameter space although presenting limitations when the population size increases over a certain threshold. In silico tracking experiments are also performed to validate the ability of classical control approaches to achieve other reference behaviors such as a desired constant output or a linearly varying one. All simulations are carried out in BSim, an advanced agent-based simulator of microbial population which is here extended ad hoc to include the effects of control strategies acting onto the population.

Functional approach to exploring climatic and landscape controls of runoff generation: 1. Behavioral constraints on runoff volume

NASA Astrophysics Data System (ADS)

Li, Hong-Yi; Sivapalan, Murugesu; Tian, Fuqiang; Harman, Ciaran

2014-12-01

Inspired by the Dunne diagram, the climatic and landscape controls on the partitioning of annual runoff into its various components (Hortonian and Dunne overland flow and subsurface stormflow) are assessed quantitatively, from a purely theoretical perspective. A simple distributed hydrologic model has been built sufficient to simulate the effects of different combinations of climate, soil, and topography on the runoff generation processes. The model is driven by a sequence of simple hypothetical precipitation events, for a large combination of climate and landscape properties, and hydrologic responses at the catchment scale are obtained through aggregation of grid-scale responses. It is found, first, that the water balance responses, including relative contributions of different runoff generation mechanisms, could be related to a small set of dimensionless similarity parameters. These capture the competition between the wetting, drying, storage, and drainage functions underlying the catchment responses, and in this way, provide a quantitative approximation of the conceptual Dunne diagram. Second, only a subset of all hypothetical catchment/climate combinations is found to be "behavioral," in terms of falling sufficiently close to the Budyko curve, describing mean annual runoff as a function of climate aridity. Furthermore, these behavioral combinations are mostly consistent with the qualitative picture presented in the Dunne diagram, indicating clearly the commonality between the Budyko curve and the Dunne diagram. These analyses also suggest clear interrelationships amongst the "behavioral" climate, soil, and topography parameter combinations, implying these catchment properties may be constrained to be codependent in order to satisfy the Budyko curve.

Individual differences in orexin 1 receptor modulation of motivation for the opioid remifentanil

PubMed Central

Porter-Stransky, Kirsten A.; Bentzley, Brandon S.; Aston-Jones, Gary

2015-01-01

Orexin-1 receptors (Ox1Rs) have been implicated in the motivation for drugs of abuse. Here, we utilized a within-session behavioral-economic threshold procedure to screen for individual differences in economic demand for the ultra-short acting opioid remifentanil and to test whether antagonism of Ox1Rs reduces remifentanil demand. The behavioral-economic procedure revealed robust individual differences in free consumption of remifentanil (Q0 parameter; hedonic set point). Rats with low baseline Q0 (low takers) displayed high demand elasticity (α parameter; reduced responding as drug price increased indicating low motivation for drug), whereas subjects with a higher Q0 (high takers) exhibit low demand elasticity (low α) by continuing to self-administer remifentanil despite increased cost (reflecting higher motivation for drug). In a punished responding paradigm utilizing footshock, subjects that were classified as high takers at baseline withstood twice as much shock as low takers to continue self-administering remifentanil. Interestingly, Ox1R antagonism with SB-334867 reduced Q0 and increased α in low takers but not in high takers. Similarly, the Ox1R antagonist attenuated cue-, but not drug-, induced reinstatement of remifentanil seeking in low takers, but had no significant effect on reinstatement of drug seeking in high takers. Together, these data reveal a novel role of orexins in demand for remifentanil: Ox1Rs modulate demand in low takers but not in individuals that exhibit addictive-like behaviors (high takers). Finally, the behavioral assays in this study can serve as a novel laboratory model for studying individual differences in opioid use disorders. PMID:26598295

Translating Dental Flossing Intentions into Behavior: a Longitudinal Investigation of the Mediating Effect of Planning and Self-Efficacy on Young Adults.

PubMed

Hamilton, Kyra; Bonham, Mikaela; Bishara, Jason; Kroon, Jeroen; Schwarzer, Ralf

2017-06-01

Although poor oral hygiene practices can have serious health consequences, a large number of adults brush or floss their teeth less than the recommended time or not at all. This study examined the mediating effect of two key self-regulatory processes, self-efficacy and planning, as the mechanisms that translate dental flossing intentions into behavior. Participants (N = 629) comprised young adults attending a major university in Queensland, Australia. A longitudinal design guided by sound theory was adopted to investigate the sequential mediation chain for the effect of dental flossing intentions (time 1) on behavior (time 3) via self-efficacy and planning (time 2). A latent variable structural equation model with standardized parameter estimates revealed the model was a good fit to the data. Controlling for baseline flossing, the effect of intentions on behavior was mediated via self-efficacy and planning, with 64 % of the flossing variance accounted for by this set of predictors. Controlling for age and sex did not change the results. The results extend previous research to further elucidate the mechanisms that help to translate oral hygiene intentions into behavior and make a significant contribution to the cumulative empirical evidence about self-regulatory components in health behavior change.

Bayesian Parameter Estimation for Heavy-Duty Vehicles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, Eric; Konan, Arnaud; Duran, Adam

2017-03-28

Accurate vehicle parameters are valuable for design, modeling, and reporting. Estimating vehicle parameters can be a very time-consuming process requiring tightly-controlled experimentation. This work describes a method to estimate vehicle parameters such as mass, coefficient of drag/frontal area, and rolling resistance using data logged during standard vehicle operation. The method uses Monte Carlo to generate parameter sets which is fed to a variant of the road load equation. Modeled road load is then compared to measured load to evaluate the probability of the parameter set. Acceptance of a proposed parameter set is determined using the probability ratio to the currentmore » state, so that the chain history will give a distribution of parameter sets. Compared to a single value, a distribution of possible values provides information on the quality of estimates and the range of possible parameter values. The method is demonstrated by estimating dynamometer parameters. Results confirm the method's ability to estimate reasonable parameter sets, and indicates an opportunity to increase the certainty of estimates through careful selection or generation of the test drive cycle.« less

Parametric models to relate spike train and LFP dynamics with neural information processing.

PubMed

Banerjee, Arpan; Dean, Heather L; Pesaran, Bijan

2012-01-01

Spike trains and local field potentials (LFPs) resulting from extracellular current flows provide a substrate for neural information processing. Understanding the neural code from simultaneous spike-field recordings and subsequent decoding of information processing events will have widespread applications. One way to demonstrate an understanding of the neural code, with particular advantages for the development of applications, is to formulate a parametric statistical model of neural activity and its covariates. Here, we propose a set of parametric spike-field models (unified models) that can be used with existing decoding algorithms to reveal the timing of task or stimulus specific processing. Our proposed unified modeling framework captures the effects of two important features of information processing: time-varying stimulus-driven inputs and ongoing background activity that occurs even in the absence of environmental inputs. We have applied this framework for decoding neural latencies in simulated and experimentally recorded spike-field sessions obtained from the lateral intraparietal area (LIP) of awake, behaving monkeys performing cued look-and-reach movements to spatial targets. Using both simulated and experimental data, we find that estimates of trial-by-trial parameters are not significantly affected by the presence of ongoing background activity. However, including background activity in the unified model improves goodness of fit for predicting individual spiking events. Uncovering the relationship between the model parameters and the timing of movements offers new ways to test hypotheses about the relationship between neural activity and behavior. We obtained significant spike-field onset time correlations from single trials using a previously published data set where significantly strong correlation was only obtained through trial averaging. We also found that unified models extracted a stronger relationship between neural response latency and trial-by-trial behavioral performance than existing models of neural information processing. Our results highlight the utility of the unified modeling framework for characterizing spike-LFP recordings obtained during behavioral performance.

An opinion-driven behavioral dynamics model for addictive behaviors

DOE PAGES

Moore, Thomas W.; Finley, Patrick D.; Apelberg, Benjamin J.; ...

2015-04-08

We present a model of behavioral dynamics that combines a social network-based opinion dynamics model with behavioral mapping. The behavioral component is discrete and history-dependent to represent situations in which an individual’s behavior is initially driven by opinion and later constrained by physiological or psychological conditions that serve to maintain the behavior. Additionally, individuals are modeled as nodes in a social network connected by directed edges. Parameter sweeps illustrate model behavior and the effects of individual parameters and parameter interactions on model results. Mapping a continuous opinion variable into a discrete behavioral space induces clustering on directed networks. Clusters providemore » targets of opportunity for influencing the network state; however, the smaller the network the greater the stochasticity and potential variability in outcomes. Furthermore, this has implications both for behaviors that are influenced by close relationships verses those influenced by societal norms and for the effectiveness of strategies for influencing those behaviors.« less

Combining in silico evolution and nonlinear dimensionality reduction to redesign responses of signaling networks

NASA Astrophysics Data System (ADS)

Prescott, Aaron M.; Abel, Steven M.

2016-12-01

The rational design of network behavior is a central goal of synthetic biology. Here, we combine in silico evolution with nonlinear dimensionality reduction to redesign the responses of fixed-topology signaling networks and to characterize sets of kinetic parameters that underlie various input-output relations. We first consider the earliest part of the T cell receptor (TCR) signaling network and demonstrate that it can produce a variety of input-output relations (quantified as the level of TCR phosphorylation as a function of the characteristic TCR binding time). We utilize an evolutionary algorithm (EA) to identify sets of kinetic parameters that give rise to: (i) sigmoidal responses with the activation threshold varied over 6 orders of magnitude, (ii) a graded response, and (iii) an inverted response in which short TCR binding times lead to activation. We also consider a network with both positive and negative feedback and use the EA to evolve oscillatory responses with different periods in response to a change in input. For each targeted input-output relation, we conduct many independent runs of the EA and use nonlinear dimensionality reduction to embed the resulting data for each network in two dimensions. We then partition the results into groups and characterize constraints placed on the parameters by the different targeted response curves. Our approach provides a way (i) to guide the design of kinetic parameters of fixed-topology networks to generate novel input-output relations and (ii) to constrain ranges of biological parameters using experimental data. In the cases considered, the network topologies exhibit significant flexibility in generating alternative responses, with distinct patterns of kinetic rates emerging for different targeted responses.

Personality and performance are affected by age and early life parameters in a small primate.

PubMed

Zablocki-Thomas, Pauline B; Herrel, Anthony; Hardy, Isabelle; Rabardel, Lucile; Perret, Martine; Aujard, Fabienne; Pouydebat, Emmanuelle

2018-05-01

A whole suite of parameters is likely to influence the behavior and performance of individuals as adults, including correlations between phenotypic traits or an individual's developmental context. Here, we ask the question whether behavior and physical performance traits are correlated and how early life parameters such as birth weight, litter size, and growth can influence these traits as measured during adulthood. We studied 486 captive gray mouse lemurs ( Microcebus murinus ) and measured two behavioral traits and two performance traits potentially involved in two functions: exploration behavior with pull strength and agitation score with bite force. We checked for the existence of behavioral consistency in behaviors and explored correlations between behavior, performance, morphology. We analyzed the effect of birth weight, growth, and litter size, while controlling for age, sex, and body weight. Behavior and performance were not correlated with one another, but were both influenced by age. Growth rate had a positive effect on adult morphology, and birth weight significantly affected emergence latency and bite force. Grip strength was not directly affected by early life traits, but bite performance and exploration behavior were impacted by birth weight. This study shows how early life parameters impact personality and performance.

Piezoelectric Behaviour of Sputtered Aluminium Nitride Thin Film for High Frequency Ultrasonic Sensors

NASA Astrophysics Data System (ADS)

Herzog, T.; Walter, S.; Bartzsch, H.; Gittner, M.; Gloess, D.; Heuer, H.

2011-06-01

Many new materials and processes require non destructive evaluation in higher resolutions by phased array ultrasonic techniques in a frequency range up to 250 MHz. This paper presents aluminium nitride, a promising material for the use as a piezoelectric sensor material in the considered frequency range, which contains the potential for high frequency phased array application in the future. This work represents the fundamental development of piezoelectric aluminium nitride films with a thickness of up to 10 μm. We have investigated and optimized the deposition process of the aluminium nitride thin film layers regarding their piezoelectric behavior. Therefore a specific test setup and a measuring station were created to determine the piezoelectric charge constant (d33) and the electro acoustic behavior of the sensor. Single element transducers were deposited on silicon substrates with aluminium electrodes for top and bottom, using different parameters for the magnetron sputter process, like pressure and bias voltage. Afterwards acoustical measurements up to 500 MHz in pulse echo mode have been carried out and the electrical and electromechanical properties were qualified. In two different parameter sets for the sputtering process excellent piezoelectric charge constant of about 8.0 pC/N maximum were obtained.

Performance assessment of solid state actuators through a common procedure and comparison criteria

NASA Astrophysics Data System (ADS)

Reithler, Livier; Guedra-Degeorges, Didier

1998-07-01

The design of systems based on smart structure technologies for active shape and vibration control and high precision positioning requires a good knowledge of the behavior of the active materials (electrostrictive and piezoelectric ceramics and polymers, magnetostrictive and shape memory alloys...) and of commercially available actuators. Extensive theoretical studies have been made on the behavior of active materials during the past decades but there are only a few developments on experimental comparisons between different kinds of commercially available actuators. The purpose of this study is to find out the pertinent parameters for the design of such systems, to set up a common static test procedure for all types of actuators and to define comparison criteria in terms of output force and displacement, mechanical and electrical energy, mass and dimensions. After having define the pertinent parameters of the characterization and having described the resulting testing procedure, test results are presented for different types of actuators based on piezoceramics and magnetostrictive alloys. The performances of each actuator are compared through both the test results and the announced characteristics: to perform this comparison absolute and relative criteria are chosen considering aeronautical and space applications.

Applying "domino" model to study dipolar geomagnetic field reversals and secular variation

NASA Astrophysics Data System (ADS)

Peqini, Klaudio; Duka, Bejo

2014-05-01

Aiming to understand the physical processes underneath the reversals events of geomagnetic field, different numerical models have been conceived. We considered the so named "domino" model, an Ising-Heisenberg model of interacting magnetic spins aligned along a ring [Mazaud and Laj, EPSL, 1989; Mori et al., arXiv:1110.5062v2, 2012]. We will present here some results which are slightly different from the already published results, and will give our interpretation on the differences. Following the empirical studies of the long series of the axial magnetic moment (dipolar moment or "magnetization") generated by the model varying all model parameters, we defined the set of parameters that supply the longest mean time between reversals. Using this set of parameters, a short time series (about 10,000 years) of axial magnetic moment was generated. After de-noising the fluctuation of this time series, we compared it with the series of dipolar magnetic moment values supplied by CALS10K.1b model for the last 10000 years. We found similar behavior of the both series, even if the "domino" model could not supply a full explanation of the geomagnetic field SV. In a similar way we will compare a 14000 years long series with the dipolar magnetic moment obtained by the model SHA.DIF.14k [Pavón-Carrasco et al., EPSL, 2014].

Computational modeling of muscular thin films for cardiac repair

NASA Astrophysics Data System (ADS)

Böl, Markus; Reese, Stefanie; Parker, Kevin Kit; Kuhl, Ellen

2009-03-01

Motivated by recent success in growing biohybrid material from engineered tissues on synthetic polymer films, we derive a computational simulation tool for muscular thin films in cardiac repair. In this model, the polydimethylsiloxane base layer is simulated in terms of microscopically motivated tetrahedral elements. Their behavior is characterized through a volumetric contribution and a chain contribution that explicitly accounts for the polymeric microstructure of networks of long chain molecules. Neonatal rat ventricular cardiomyocytes cultured on these polymeric films are modeled with actively contracting truss elements located on top of the sheet. The force stretch response of these trusses is motivated by the cardiomyocyte force generated during active contraction as suggested by the filament sliding theory. In contrast to existing phenomenological models, all material parameters of this novel model have a clear biophyisical interpretation. The predictive features of the model will be demonstrated through the simulation of muscular thin films. First, the set of parameters will be fitted for one particular experiment documented in the literature. This parameter set is then used to validate the model for various different experiments. Last, we give an outlook of how the proposed simulation tool could be used to virtually predict the response of multi-layered muscular thin films. These three-dimensional constructs show a tremendous regenerative potential in repair of damaged cardiac tissue. The ability to understand, tune and optimize their structural response is thus of great interest in cardiovascular tissue engineering.

Two Key Parameters Controlling Particle Clumping Caused by Streaming Instability in the Dead-zone Dust Layer of a Protoplanetary Disk

NASA Astrophysics Data System (ADS)

Sekiya, Minoru; Onishi, Isamu K.

2018-06-01

The streaming instability and Kelvin–Helmholtz instability are considered the two major sources causing clumping of dust particles and turbulence in the dust layer of a protoplanetary disk as long as we consider the dead zone where the magnetorotational instability does not grow. Extensive numerical simulations have been carried out in order to elucidate the condition for the development of particle clumping caused by the streaming instability. In this paper, a set of two parameters suitable for classifying the numerical results is proposed. One is the Stokes number that has been employed in previous works and the other is the dust particle column density that is nondimensionalized using the gas density in the midplane, Keplerian angular velocity, and difference between the Keplerian and gaseous orbital velocities. The magnitude of dust clumping is a measure of the behavior of the dust layer. Using three-dimensional numerical simulations of dust particles and gas based on Athena code v. 4.2, it is confirmed that the magnitude of dust clumping for two disk models are similar if the corresponding sets of values of the two parameters are identical to each other, even if the values of the metallicity (i.e., the ratio of the columns density of the dust particles to that of the gas) are different.

Stress intensity factors for bonded orthotropic strips with cracks

NASA Technical Reports Server (NTRS)

Delale, F.; Erdogan, F.

1978-01-01

The elastostatic problem for a nonhomogeneous plane which consists of two sets of periodically arranged dissimilar orthotropic strips is considered. It is assumed that the plane contains a series of collinear cracks perpendicular to the interfaces and is loaded in tension away from and perpendicular to the cracks. Cracks fully imbedded into the homogenous strips were analyzed as well as the singular behavior of the stresses for two special crack geometries. The analysis of cracks crossing interfaces indicates that, for certain orthotropic material combinations, the stress state at the point of intersection of a crack and an interface may be bounded. A number of numerical examples are worked out in order to separate the primary material parameters influencing the stress intensity factors and the powers of stress singularity, and to determine the trends regarding the influence of the secondary parameters.

Cognitive Models of Risky Choice: Parameter Stability and Predictive Accuracy of Prospect Theory

ERIC Educational Resources Information Center

Glockner, Andreas; Pachur, Thorsten

2012-01-01

In the behavioral sciences, a popular approach to describe and predict behavior is cognitive modeling with adjustable parameters (i.e., which can be fitted to data). Modeling with adjustable parameters allows, among other things, measuring differences between people. At the same time, parameter estimation also bears the risk of overfitting. Are…

Numerical and experimental analyses of out-of-plane deformation of triaxial woven fabric

NASA Astrophysics Data System (ADS)

Zhou, Hongtao; Xiao, Xueliang; Qian, Kun; Zhang, Kun; Zhang, Diantang

2018-05-01

With three sets of yarns interwoven in plane for angle-interlock structure, triaxial woven fabric (TWF) is a unique and perfect construction material for products subjected to multi-directional loads, as compared to classic fabrics of orthogonal structure. Finite-element analysis (FEA) and experimental methods are applied to study the out-of-plane deformation (OPD) behaviors of TWF and plain woven fabric (PWF). Among this, the yarn cross section, path and woven structure are obtained using optical microscopy, the related parameters are input to finite element model (FEM) for simulating the OPD behavior. This paper presents a detailed analysis on out-of-plane deformation behavior of TWF and PWF by the finite element method and experiment. In consideration of the comparability, TWF and PWF are designed and prepared with the same yarns and areal density (g/m2). The deformation profile, maximum stress and maximum deflection of TWF and PWF are obtained by FEA and experiment. It has been found that the maximum deflection and maximum stress of TWF is smaller than that of PWF under the same uniform negative pressure, both FEA and experiment. Furthermore, the stress distribution of TWF is more evenly than that of PWF, indicating that TWF exhibited superior isotropy in comparison with PWF for one more directional set of yarns in undertaking the OPD.

Model-free information-theoretic approach to infer leadership in pairs of zebrafish.

PubMed

Butail, Sachit; Mwaffo, Violet; Porfiri, Maurizio

2016-04-01

Collective behavior affords several advantages to fish in avoiding predators, foraging, mating, and swimming. Although fish schools have been traditionally considered egalitarian superorganisms, a number of empirical observations suggest the emergence of leadership in gregarious groups. Detecting and classifying leader-follower relationships is central to elucidate the behavioral and physiological causes of leadership and understand its consequences. Here, we demonstrate an information-theoretic approach to infer leadership from positional data of fish swimming. In this framework, we measure social interactions between fish pairs through the mathematical construct of transfer entropy, which quantifies the predictive power of a time series to anticipate another, possibly coupled, time series. We focus on the zebrafish model organism, which is rapidly emerging as a species of choice in preclinical research for its genetic similarity to humans and reduced neurobiological complexity with respect to mammals. To overcome experimental confounds and generate test data sets on which we can thoroughly assess our approach, we adapt and calibrate a data-driven stochastic model of zebrafish motion for the simulation of a coupled dynamical system of zebrafish pairs. In this synthetic data set, the extent and direction of the coupling between the fish are systematically varied across a wide parameter range to demonstrate the accuracy and reliability of transfer entropy in inferring leadership. Our approach is expected to aid in the analysis of collective behavior, providing a data-driven perspective to understand social interactions.

Model-free information-theoretic approach to infer leadership in pairs of zebrafish

NASA Astrophysics Data System (ADS)

Butail, Sachit; Mwaffo, Violet; Porfiri, Maurizio

2016-04-01

Collective behavior affords several advantages to fish in avoiding predators, foraging, mating, and swimming. Although fish schools have been traditionally considered egalitarian superorganisms, a number of empirical observations suggest the emergence of leadership in gregarious groups. Detecting and classifying leader-follower relationships is central to elucidate the behavioral and physiological causes of leadership and understand its consequences. Here, we demonstrate an information-theoretic approach to infer leadership from positional data of fish swimming. In this framework, we measure social interactions between fish pairs through the mathematical construct of transfer entropy, which quantifies the predictive power of a time series to anticipate another, possibly coupled, time series. We focus on the zebrafish model organism, which is rapidly emerging as a species of choice in preclinical research for its genetic similarity to humans and reduced neurobiological complexity with respect to mammals. To overcome experimental confounds and generate test data sets on which we can thoroughly assess our approach, we adapt and calibrate a data-driven stochastic model of zebrafish motion for the simulation of a coupled dynamical system of zebrafish pairs. In this synthetic data set, the extent and direction of the coupling between the fish are systematically varied across a wide parameter range to demonstrate the accuracy and reliability of transfer entropy in inferring leadership. Our approach is expected to aid in the analysis of collective behavior, providing a data-driven perspective to understand social interactions.

Gaussian closure technique applied to the hysteretic Bouc model with non-zero mean white noise excitation

NASA Astrophysics Data System (ADS)

Waubke, Holger; Kasess, Christian H.

2016-11-01

Devices that emit structure-borne sound are commonly decoupled by elastic components to shield the environment from acoustical noise and vibrations. The elastic elements often have a hysteretic behavior that is typically neglected. In order to take hysteretic behavior into account, Bouc developed a differential equation for such materials, especially joints made of rubber or equipped with dampers. In this work, the Bouc model is solved by means of the Gaussian closure technique based on the Kolmogorov equation. Kolmogorov developed a method to derive probability density functions for arbitrary explicit first-order vector differential equations under white noise excitation using a partial differential equation of a multivariate conditional probability distribution. Up to now no analytical solution of the Kolmogorov equation in conjunction with the Bouc model exists. Therefore a wide range of approximate solutions, especially the statistical linearization, were developed. Using the Gaussian closure technique that is an approximation to the Kolmogorov equation assuming a multivariate Gaussian distribution an analytic solution is derived in this paper for the Bouc model. For the stationary case the two methods yield equivalent results, however, in contrast to statistical linearization the presented solution allows to calculate the transient behavior explicitly. Further, stationary case leads to an implicit set of equations that can be solved iteratively with a small number of iterations and without instabilities for specific parameter sets.

Combined Estimation of Hydrogeologic Conceptual Model and Parameter Uncertainty

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meyer, Philip D.; Ye, Ming; Neuman, Shlomo P.

2004-03-01

The objective of the research described in this report is the development and application of a methodology for comprehensively assessing the hydrogeologic uncertainties involved in dose assessment, including uncertainties associated with conceptual models, parameters, and scenarios. This report describes and applies a statistical method to quantitatively estimate the combined uncertainty in model predictions arising from conceptual model and parameter uncertainties. The method relies on model averaging to combine the predictions of a set of alternative models. Implementation is driven by the available data. When there is minimal site-specific data the method can be carried out with prior parameter estimates basedmore » on generic data and subjective prior model probabilities. For sites with observations of system behavior (and optionally data characterizing model parameters), the method uses model calibration to update the prior parameter estimates and model probabilities based on the correspondence between model predictions and site observations. The set of model alternatives can contain both simplified and complex models, with the requirement that all models be based on the same set of data. The method was applied to the geostatistical modeling of air permeability at a fractured rock site. Seven alternative variogram models of log air permeability were considered to represent data from single-hole pneumatic injection tests in six boreholes at the site. Unbiased maximum likelihood estimates of variogram and drift parameters were obtained for each model. Standard information criteria provided an ambiguous ranking of the models, which would not justify selecting one of them and discarding all others as is commonly done in practice. Instead, some of the models were eliminated based on their negligibly small updated probabilities and the rest were used to project the measured log permeabilities by kriging onto a rock volume containing the six boreholes. These four projections, and associated kriging variances, were averaged using the posterior model probabilities as weights. Finally, cross-validation was conducted by eliminating from consideration all data from one borehole at a time, repeating the above process, and comparing the predictive capability of the model-averaged result with that of each individual model. Using two quantitative measures of comparison, the model-averaged result was superior to any individual geostatistical model of log permeability considered.« less

A novel rotometer based on a RISC microcontroller.

PubMed

Heredia-López, F J; Bata-García, J L; Alvarez-Cervera, F J; Góngora-Alfaro, J L

2002-08-01

A new, low-cost rotometer, based on a reduced instruction set computer (RISC) microcontroller, is presented. Like earlier devices, it counts the number and direction of full turns for predetermined time periods during the evaluation of turning behavior induced by drug administration in rats. The present stand-alone system includes a nonvolatile memory for long-term data storage and a serial port for data transmission. It also contains a display for monitoring the experiments and has battery backup to avoid interruptions owing to power failures. A high correlation was found (r > .988, p < 2 x 10(-14)) between the counts of the rotometer and those of two trained observers. The system reflects quantitative differences in turning behavior owing to pharmacological manipulations. It provides the most common counting parameters and is inexpensive, flexible, highly reliable, and completely portable (weight including batteries, 159 g).

Interface crack in a nonhomogeneous elastic medium

NASA Technical Reports Server (NTRS)

Delale, F.; Erdogan, F.

1988-01-01

The linear elasticity problem for an interface crack between two bonded half planes is reconsidered. It is assumed that one of the half planes is homogeneous and the second is nonhomogeneous in such a way that the elastic properties are continuous throughout the plane and have discontinuous derivatives along the interface. The problem is formulated in terms of a system of integral equations and the asymptotic behavior of the stress state near the crack tip is determined. The results lead to the conclusion that the singular behavior of stresses in the nonhomogeneous medium is identical to that in a homogeneous material provided the spacial distribution of material properties is continuous near and at the crack tip. The problem is solved for various values of the nonhomogeneity parameter and for four different sets of crack surface tractions, and the corresponding stress intensity factors are tabulated.

Experimental research on the behavior of the pneumatic transport of fine-grained iron

NASA Astrophysics Data System (ADS)

Andrei, V.; Hritac, M.; Constantin, N.; Dobrescu, C.

2017-01-01

Mixed injection of fine-grained iron ore and pulverized coal in the furnace, involves determining the behavior of these materials during pneumatic transport in a dense state through the pipe and setting possibilities for adjusting the flow rate of material transported with the corresponding values of the process. Parameters of the pneumatic transport were determined for the main types of iron ore and chalk used in Arcelor Mittal Galati. Outside the intended purpose of injecting iron ore and flux, it was considered also the experimental check of the possibility for injecting ilmenite in the furnace for crucible protection purpose. The possibility of injecting cinder mill into the furnace was also considered. Injecting cinder could be taken into account for the recycling of ferrous waste in the furnace, also as additive for intensifying the combustion process around the tuyeres.

Model-Driven Analysis of Eyeblink Classical Conditioning Reveals the Underlying Structure of Cerebellar Plasticity and Neuronal Activity.

PubMed

Antonietti, Alberto; Casellato, Claudia; D'Angelo, Egidio; Pedrocchi, Alessandra

The cerebellum plays a critical role in sensorimotor control. However, how the specific circuits and plastic mechanisms of the cerebellum are engaged in closed-loop processing is still unclear. We developed an artificial sensorimotor control system embedding a detailed spiking cerebellar microcircuit with three bidirectional plasticity sites. This proved able to reproduce a cerebellar-driven associative paradigm, the eyeblink classical conditioning (EBCC), in which a precise time relationship between an unconditioned stimulus (US) and a conditioned stimulus (CS) is established. We challenged the spiking model to fit an experimental data set from human subjects. Two subsequent sessions of EBCC acquisition and extinction were recorded and transcranial magnetic stimulation (TMS) was applied on the cerebellum to alter circuit function and plasticity. Evolutionary algorithms were used to find the near-optimal model parameters to reproduce the behaviors of subjects in the different sessions of the protocol. The main finding is that the optimized cerebellar model was able to learn to anticipate (predict) conditioned responses with accurate timing and success rate, demonstrating fast acquisition, memory stabilization, rapid extinction, and faster reacquisition as in EBCC in humans. The firing of Purkinje cells (PCs) and deep cerebellar nuclei (DCN) changed during learning under the control of synaptic plasticity, which evolved at different rates, with a faster acquisition in the cerebellar cortex than in DCN synapses. Eventually, a reduced PC activity released DCN discharge just after the CS, precisely anticipating the US and causing the eyeblink. Moreover, a specific alteration in cortical plasticity explained the EBCC changes induced by cerebellar TMS in humans. In this paper, for the first time, it is shown how closed-loop simulations, using detailed cerebellar microcircuit models, can be successfully used to fit real experimental data sets. Thus, the changes of the model parameters in the different sessions of the protocol unveil how implicit microcircuit mechanisms can generate normal and altered associative behaviors.The cerebellum plays a critical role in sensorimotor control. However, how the specific circuits and plastic mechanisms of the cerebellum are engaged in closed-loop processing is still unclear. We developed an artificial sensorimotor control system embedding a detailed spiking cerebellar microcircuit with three bidirectional plasticity sites. This proved able to reproduce a cerebellar-driven associative paradigm, the eyeblink classical conditioning (EBCC), in which a precise time relationship between an unconditioned stimulus (US) and a conditioned stimulus (CS) is established. We challenged the spiking model to fit an experimental data set from human subjects. Two subsequent sessions of EBCC acquisition and extinction were recorded and transcranial magnetic stimulation (TMS) was applied on the cerebellum to alter circuit function and plasticity. Evolutionary algorithms were used to find the near-optimal model parameters to reproduce the behaviors of subjects in the different sessions of the protocol. The main finding is that the optimized cerebellar model was able to learn to anticipate (predict) conditioned responses with accurate timing and success rate, demonstrating fast acquisition, memory stabilization, rapid extinction, and faster reacquisition as in EBCC in humans. The firing of Purkinje cells (PCs) and deep cerebellar nuclei (DCN) changed during learning under the control of synaptic plasticity, which evolved at different rates, with a faster acquisition in the cerebellar cortex than in DCN synapses. Eventually, a reduced PC activity released DCN discharge just after the CS, precisely anticipating the US and causing the eyeblink. Moreover, a specific alteration in cortical plasticity explained the EBCC changes induced by cerebellar TMS in humans. In this paper, for the first time, it is shown how closed-loop simulations, using detailed cerebellar microcircuit models, can be successfully used to fit real experimental data sets. Thus, the changes of the model parameters in the different sessions of the protocol unveil how implicit microcircuit mechanisms can generate normal and altered associative behaviors.

Hydrologic Model Development and Calibration: Contrasting a Single- and Multi-Objective Approach for Comparing Model Performance

NASA Astrophysics Data System (ADS)

Asadzadeh, M.; Maclean, A.; Tolson, B. A.; Burn, D. H.

2009-05-01

Hydrologic model calibration aims to find a set of parameters that adequately simulates observations of watershed behavior, such as streamflow, or a state variable, such as snow water equivalent (SWE). There are different metrics for evaluating calibration effectiveness that involve quantifying prediction errors, such as the Nash-Sutcliffe (NS) coefficient and bias evaluated for the entire calibration period, on a seasonal basis, for low flows, or for high flows. Many of these metrics are conflicting such that the set of parameters that maximizes the high flow NS differs from the set of parameters that maximizes the low flow NS. Conflicting objectives are very likely when different calibration objectives are based on different fluxes and/or state variables (e.g., NS based on streamflow versus SWE). One of the most popular ways to balance different metrics is to aggregate them based on their importance and find the set of parameters that optimizes a weighted sum of the efficiency metrics. Comparing alternative hydrologic models (e.g., assessing model improvement when a process or more detail is added to the model) based on the aggregated objective might be misleading since it represents one point on the tradeoff of desired error metrics. To derive a more comprehensive model comparison, we solved a bi-objective calibration problem to estimate the tradeoff between two error metrics for each model. Although this approach is computationally more expensive than the aggregation approach, it results in a better understanding of the effectiveness of selected models at each level of every error metric and therefore provides a better rationale for judging relative model quality. The two alternative models used in this study are two MESH hydrologic models (version 1.2) of the Wolf Creek Research basin that differ in their watershed spatial discretization (a single Grouped Response Unit, GRU, versus multiple GRUs). The MESH model, currently under development by Environment Canada, is a coupled land-surface and hydrologic model. Results will demonstrate the conclusions a modeller might make regarding the value of additional watershed spatial discretization under both an aggregated (single-objective) and multi-objective model comparison framework.

PM10 and gaseous pollutants trends from air quality monitoring networks in Bari province: principal component analysis and absolute principal component scores on a two years and half data set

PubMed Central

2014-01-01

Background The chemical composition of aerosols and particle size distributions are the most significant factors affecting air quality. In particular, the exposure to finer particles can cause short and long-term effects on human health. In the present paper PM10 (particulate matter with aerodynamic diameter lower than 10 μm), CO, NOx (NO and NO2), Benzene and Toluene trends monitored in six monitoring stations of Bari province are shown. The data set used was composed by bi-hourly means for all parameters (12 bi-hourly means per day for each parameter) and it’s referred to the period of time from January 2005 and May 2007. The main aim of the paper is to provide a clear illustration of how large data sets from monitoring stations can give information about the number and nature of the pollutant sources, and mainly to assess the contribution of the traffic source to PM10 concentration level by using multivariate statistical techniques such as Principal Component Analysis (PCA) and Absolute Principal Component Scores (APCS). Results Comparing the night and day mean concentrations (per day) for each parameter it has been pointed out that there is a different night and day behavior for some parameters such as CO, Benzene and Toluene than PM10. This suggests that CO, Benzene and Toluene concentrations are mainly connected with transport systems, whereas PM10 is mostly influenced by different factors. The statistical techniques identified three recurrent sources, associated with vehicular traffic and particulate transport, covering over 90% of variance. The contemporaneous analysis of gas and PM10 has allowed underlining the differences between the sources of these pollutants. Conclusions The analysis of the pollutant trends from large data set and the application of multivariate statistical techniques such as PCA and APCS can give useful information about air quality and pollutant’s sources. These knowledge can provide useful advices to environmental policies in order to reach the WHO recommended levels. PMID:24555534

Modeling and Parameter Estimation of Spacecraft Fuel Slosh with Diaphragms Using Pendulum Analogs

NASA Technical Reports Server (NTRS)

Chatman, Yadira; Gangadharan, Sathya; Schlee, Keith; Ristow, James; Suderman, James; Walker, Charles; Hubert, Carl

2007-01-01

Prediction and control of liquid slosh in moving containers is an important consideration in the design of spacecraft and launch vehicle control systems. Even with modern computing systems, CFD type simulations are not fast enough to allow for large scale Monte Carlo analyses of spacecraft and launch vehicle dynamic behavior with slosh included. It is still desirable to use some type of simplified mechanical analog for the slosh to shorten computation time. Analytic determination of the slosh analog parameters has met with mixed success and is made even more difficult by the introduction of propellant management devices such as elastomeric diaphragms. By subjecting full-sized fuel tanks with actual flight fuel loads to motion similar to that experienced in flight and measuring the forces experienced by the tanks, these parameters can be determined experimentally. Currently, the identification of the model parameters is a laborious trial-and-error process in which the hand-derived equations of motion for the mechanical analog are evaluated and their results compared with the experimental results. This paper will describe efforts by the university component of a team comprised of NASA's Launch Services Program, Embry Riddle Aeronautical University, Southwest Research Institute and Hubert Astronautics to improve the accuracy and efficiency of modeling techniques used to predict these types of motions. Of particular interest is the effect of diaphragms and bladders on the slosh dynamics and how best to model these devices. The previous research was an effort to automate the process of slosh model parameter identification using a MATLAB/SimMechanics-based computer simulation. These results are the first step in applying the same computer estimation to a full-size tank and vehicle propulsion system. The introduction of diaphragms to this experimental set-up will aid in a better and more complete prediction of fuel slosh characteristics and behavior. Automating the parameter identification process will save time and thus allow earlier identification of potential vehicle performance problems.

Implementation of Positive Behavior Support with a Sibling Set in a Home Environment

ERIC Educational Resources Information Center

Duda, Michelle A.; Clarke, Shelley; Fox, Lise; Dunlap, Glen

2008-01-01

This study provides a demonstration of the process of positive behavior support (PBS) within a home setting to address the challenging behavior of a sibling set within family routines. Although a growing data base is demonstrating the feasibility and effectiveness of conducting functional behavioral assessment and implementing assessment-based…

A comprehensive numerical analysis of the hydraulic behavior of a permeable pavement

NASA Astrophysics Data System (ADS)

Brunetti, Giuseppe; Šimůnek, Jiří; Piro, Patrizia

2016-09-01

The increasing frequency of flooding events in urban catchments related to an increase in impervious surfaces highlights the inadequacy of traditional urban drainage systems. Low Impact Development (LID) techniques have proven to be a viable and effective alternative by reducing stormwater runoff and increasing the infiltration and evapotranspiration capacity of urban areas. However, the lack of adequate modeling tools represents a barrier in designing and constructing such systems. This paper investigates the suitability of a mechanistic model, HYDRUS-1D, to correctly describe the hydraulic behavior of permeable pavement installed at the University of Calabria. Two different scenarios of describing the hydraulic behavior of the permeable pavement system were analyzed: the first one uses a single-porosity model for all layers of the permeable pavement; the second one uses a dual-porosity model for the base and sub-base layers. Measured and modeled month-long hydrographs were compared using the Nash-Sutcliffe efficiency (NSE) index. A Global Sensitivity Analysis (GSA) followed by a Monte Carlo filtering highlighted the influence of the wear layer on the hydraulic behavior of the pavement and identified the ranges of parameters generating behavioral solutions. Reduced ranges were then used in the calibration procedure conducted with the metaheuristic Particle swarm optimization (PSO) algorithm for the estimation of hydraulic parameters. The best fit value for the first scenario was NSE = 0.43; for the second scenario, it was NSE = 0.81, indicating that the dual-porosity approach is more appropriate for describing the variably-saturated flow in the base and sub-base layers. Estimated parameters were validated using an independent, month-long set of measurements, resulting in NSE values of 0.43 and 0.86 for the first and second scenarios, respectively. The improvement in correspondence between measured and modeled hydrographs confirmed the reliability of the combination of GSA and PSO in dealing with highly dimensional optimization problems. Obtained results have demonstrated that PSO, due to its easiness of implementation and effectiveness, can represent a new and viable alternative to traditional optimization algorithms for the inverse estimation of unsaturated hydraulic properties. Finally, the results confirmed the suitability and the accuracy of HYDRUS-1D in correctly describing the hydraulic behavior of permeable pavements.

Thermodynamic behavior of a phase transition in a model for sympatric speciation

NASA Astrophysics Data System (ADS)

Luz-Burgoa, K.; Moss de Oliveira, S.; Schwämmle, Veit; Sá Martins, J. S.

2006-08-01

We investigate the macroscopic effects of the ingredients that drive the origin of species through sympatric speciation. In our model, sympatric speciation is obtained as we tune up the strength of competition between individuals with different phenotypes. As a function of this control parameter, we can characterize, through the behavior of a macroscopic order parameter, a phase transition from a nonspeciation to a speciation state of the system. The behavior of the first derivative of the order parameter with respect to the control parameter is consistent with a phase transition and exhibits a sharp peak at the transition point. For different resources distribution, the transition point is shifted, an effect similar to pressure in a PVT system. The inverse of the parameter related to a sexual selection strength behaves like an external field in the system and, as thus, is also a control parameter. The macroscopic effects of the biological parameters used in our model are a reminiscent of the behavior of thermodynamic quantities in a phase transition of an equilibrium physical system.

A Sensitivity Analysis of an Inverted Pendulum Balance Control Model.

PubMed

Pasma, Jantsje H; Boonstra, Tjitske A; van Kordelaar, Joost; Spyropoulou, Vasiliki V; Schouten, Alfred C

2017-01-01

Balance control models are used to describe balance behavior in health and disease. We identified the unique contribution and relative importance of each parameter of a commonly used balance control model, the Independent Channel (IC) model, to identify which parameters are crucial to describe balance behavior. The balance behavior was expressed by transfer functions (TFs), representing the relationship between sensory perturbations and body sway as a function of frequency, in terms of amplitude (i.e., magnitude) and timing (i.e., phase). The model included an inverted pendulum controlled by a neuromuscular system, described by several parameters. Local sensitivity of each parameter was determined for both the magnitude and phase using partial derivatives. Both the intrinsic stiffness and proportional gain shape the magnitude at low frequencies (0.1-1 Hz). The derivative gain shapes the peak and slope of the magnitude between 0.5 and 0.9 Hz. The sensory weight influences the overall magnitude, and does not have any effect on the phase. The effect of the time delay becomes apparent in the phase above 0.6 Hz. The force feedback parameters and intrinsic stiffness have a small effect compared with the other parameters. All parameters shape the TF magnitude and phase and therefore play a role in the balance behavior. The sensory weight, time delay, derivative gain, and the proportional gain have a unique effect on the TFs, while the force feedback parameters and intrinsic stiffness contribute less. More insight in the unique contribution and relative importance of all parameters shows which parameters are crucial and critical to identify underlying differences in balance behavior between different patient groups.

Econometrics of inventory holding and shortage costs: the case of refined gasoline

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krane, S.D.

1985-01-01

This thesis estimates a model of a firm's optimal inventory and production behavior in order to investigate the link between the role of inventories in the business cycle and the microeconomic incentives for holding stocks of finished goods. The goal is to estimate a set of structural cost function parameters that can be used to infer the optimal cyclical response of inventories and production to shocks in demand. To avoid problems associated with the use of value based aggregate inventory data, an industry level physical unit data set for refined motor gasoline is examined. The Euler equations for a refiner'smore » multiperiod decision problem are estimated using restrictions imposed by the rational expectations hypothesis. The model also embodies the fact that, in most periods, the level of shortages will be zero, and even when positive, the shortages are not directly observable in the data set. These two concerns lead us to use a generalized method of moments estimation technique on a functional form that resembles the formulation of a Tobit problem. The estimation results are disappointing; the model and data yield coefficient estimates incongruous with the cost function interpretations of the structural parameters. These is only some superficial evidence that production smoothing is significant and that marginal inventory shortage costs increase at a faster rate than do marginal holding costs.« less

Performance factors in associative learning: assessment of the sometimes competing retrieval model.

PubMed

Witnauer, James E; Wojick, Brittany M; Polack, Cody W; Miller, Ralph R

2012-09-01

Previous simulations revealed that the sometimes competing retrieval model (SOCR; Stout & Miller, Psychological Review, 114, 759-783, 2007), which assumes local error reduction, can explain many cue interaction phenomena that elude traditional associative theories based on total error reduction. Here, we applied SOCR to a new set of Pavlovian phenomena. Simulations used a single set of fixed parameters to simulate each basic effect (e.g., blocking) and, for specific experiments using different procedures, used fitted parameters discovered through hill climbing. In simulation 1, SOCR was successfully applied to basic acquisition, including the overtraining effect, which is context dependent. In simulation 2, we applied SOCR to basic extinction and renewal. SOCR anticipated these effects with both fixed parameters and best-fitting parameters, although the renewal effects were weaker than those observed in some experiments. In simulation 3a, feature-negative training was simulated, including the often observed transition from second-order conditioning to conditioned inhibition. In simulation 3b, SOCR predicted the observation that conditioned inhibition after feature-negative and differential conditioning depends on intertrial interval. In simulation 3c, SOCR successfully predicted failure of conditioned inhibition to extinguish with presentations of the inhibitor alone under most circumstances. In simulation 4, cue competition, including blocking (4a), recovery from relative validity (4b), and unblocking (4c), was simulated. In simulation 5, SOCR correctly predicted that inhibitors gain more behavioral control than do excitors when they are trained in compound. Simulation 6 demonstrated that SOCR explains the slower acquisition observed following CS-weak shock pairings.

The role of land use/land cover dependent preferential flow paths in hydrologic response of steep and seasonal tropical catchments

NASA Astrophysics Data System (ADS)

Cheng, Y.; Ogden, F. L.; Zhu, J.

2017-12-01

The hydrologic behavior of steep catchments with saprolitic soils in the humid seasonal tropics varies with land use and cover, even when they have identical topographic index and slope distributions, underlying geology and soils textures. Forested catchments can produce more baseflow during the dry season compared to catchments containing substantial amount of pasture, the so-called "sponge effect". During rainfall events, forested catchments can also exhibit lower peak runoff rates and runoff efficiencies compared to pasture catchments. We hypothesize that hydrologic effects of land use arise from differences in preferential flow paths (PFPs) formed by biotic and abiotic factors in the upper one to two meters of soil and that land use effects on hydrological response are described by the relative amounts of forest and pasture within a catchment. Furthermore, we hypothesize that infiltration measurements at different scales allow estimation of PFP-related parameters. These hypotheses are tested by a model that explicitly simulates PFPs using distinct input parameter sets for forest and pasture. Runoff observations from three catchments with pasture, forest, and a mosaic of subsistence agricultural land covers allow model evaluation. Multiple objective criteria indicate that field measurements of infiltration enable PFP-relevant parameter identification and that pasture and forest end member parameter sets describe much of the observed difference. Analysis of water balance components and comparison between average transient water table depth and vertical PFP flow capacity demonstrate that the interplay of lateral and vertical PFPs contribute to the sponge-effect and can explain differences in peak runoff and runoff efficiency.

The development of novel simulation methodologies and intermolecular potential models for real fluids

NASA Astrophysics Data System (ADS)

Errington, Jeffrey Richard

This work focuses on the development of intermolecular potential models for real fluids. United-atom models have been developed for both non-polar and polar fluids. The models have been optimized to the vapor-liquid coexistence properties. Histogram reweighting techniques were used to calculate phase behavior. The Hamiltonian scaling grand canonical Monte Carlo method was developed to enable the determination of thermodynamic properties of several related Hamiltonians from a single simulation. With this method, the phase behavior of variations of the Buckingham exponential-6 potential was determined. Reservoir grand canonical Monte Carlo simulations were developed to simulate molecules with complex architectures and/or stiff intramolecular constraints. The scheme is based on the creation of a reservoir of ideal chains from which structures are selected for insertion during a simulation. New intermolecular potential models have been developed for water, the n-alkane homologous series, benzene, cyclohexane, carbon dioxide, ammonia and methanol. The models utilize the Buckingham exponential-6 potential to model non-polar interactions and point charges to describe polar interactions. With the exception of water, the new models reproduce experimental saturated densities, vapor pressures and critical parameters to within a few percent. In the case of water, we found a set of parameters that describes the phase behavior better than other available point charge models while giving a reasonable description of the liquid structure. The mixture behavior of water-hydrocarbon mixtures has also been examined. The Henry's law constants of methane, ethane, benzene and cyclohexane in water were determined using Widom insertion and expanded ensemble techniques. In addition the high-pressure phase behavior of water-methane and water-ethane systems was studied using the Gibbs ensemble method. The results from this study indicate that it is possible to obtain a good description of the phase behavior of pure components using united-atom models. The mixture behavior of non-polar systems, including highly asymmetric components, was in good agreement with experiment. The calculations for the highly non-ideal water-hydrocarbon mixtures reproduced experimental behavior with varying degrees of success. The results indicate that multibody effects, such as polarizability, must be taken into account when modeling mixtures of polar and non-polar components.

Evolution properties of the community members for dynamic networks

NASA Astrophysics Data System (ADS)

Yang, Kai; Guo, Qiang; Li, Sheng-Nan; Han, Jing-Ti; Liu, Jian-Guo

2017-03-01

The collective behaviors of community members for dynamic social networks are significant for understanding evolution features of communities. In this Letter, we empirically investigate the evolution properties of the new community members for dynamic networks. Firstly, we separate data sets into different slices, and analyze the statistical properties of new members as well as communities they joined in for these data sets. Then we introduce a parameter φ to describe community evolution between different slices and investigate the dynamic community properties of the new community members. The empirical analyses for the Facebook, APS, Enron and Wiki data sets indicate that both the number of new members and joint communities increase, the ratio declines rapidly and then becomes stable over time, and most of the new members will join in the small size communities that is s ≤ 10. Furthermore, the proportion of new members in existed communities decreases firstly and then becomes stable and relatively small for these data sets. Our work may be helpful for deeply understanding the evolution properties of community members for social networks.

Software for rapid time dependent ChIP-sequencing analysis (TDCA).

PubMed

Myschyshyn, Mike; Farren-Dai, Marco; Chuang, Tien-Jui; Vocadlo, David

2017-11-25

Chromatin immunoprecipitation followed by DNA sequencing (ChIP-seq) and associated methods are widely used to define the genome wide distribution of chromatin associated proteins, post-translational epigenetic marks, and modifications found on DNA bases. An area of emerging interest is to study time dependent changes in the distribution of such proteins and marks by using serial ChIP-seq experiments performed in a time resolved manner. Despite such time resolved studies becoming increasingly common, software to facilitate analysis of such data in a robust automated manner is limited. We have designed software called Time-Dependent ChIP-Sequencing Analyser (TDCA), which is the first program to automate analysis of time-dependent ChIP-seq data by fitting to sigmoidal curves. We provide users with guidance for experimental design of TDCA for modeling of time course (TC) ChIP-seq data using two simulated data sets. Furthermore, we demonstrate that this fitting strategy is widely applicable by showing that automated analysis of three previously published TC data sets accurately recapitulates key findings reported in these studies. Using each of these data sets, we highlight how biologically relevant findings can be readily obtained by exploiting TDCA to yield intuitive parameters that describe behavior at either a single locus or sets of loci. TDCA enables customizable analysis of user input aligned DNA sequencing data, coupled with graphical outputs in the form of publication-ready figures that describe behavior at either individual loci or sets of loci sharing common traits defined by the user. TDCA accepts sequencing data as standard binary alignment map (BAM) files and loci of interest in browser extensible data (BED) file format. TDCA accurately models the number of sequencing reads, or coverage, at loci from TC ChIP-seq studies or conceptually related TC sequencing experiments. TC experiments are reduced to intuitive parametric values that facilitate biologically relevant data analysis, and the uncovering of variations in the time-dependent behavior of chromatin. TDCA automates the analysis of TC ChIP-seq experiments, permitting researchers to easily obtain raw and modeled data for specific loci or groups of loci with similar behavior while also enhancing consistency of data analysis of TC data within the genomics field.

Overcoming Barriers in Unhealthy Settings

PubMed Central

Lemke, Michael K.; Meissen, Gregory J.; Apostolopoulos, Yorghos

2016-01-01

We investigated the phenomenon of sustained health-supportive behaviors among long-haul commercial truck drivers, who belong to an occupational segment with extreme health disparities. With a focus on setting-level factors, this study sought to discover ways in which individuals exhibit resiliency while immersed in endemically obesogenic environments, as well as understand setting-level barriers to engaging in health-supportive behaviors. Using a transcendental phenomenological research design, 12 long-haul truck drivers who met screening criteria were selected using purposeful maximum sampling. Seven broad themes were identified: access to health resources, barriers to health behaviors, recommended alternative settings, constituents of health behavior, motivation for health behaviors, attitude toward health behaviors, and trucking culture. We suggest applying ecological theories of health behavior and settings approaches to improve driver health. We also propose the Integrative and Dynamic Healthy Commercial Driving (IDHCD) paradigm, grounded in complexity science, as a new theoretical framework for improving driver health outcomes. PMID:28462332

The iron-nickel-phosphorus system: Effects on the distribution of trace elements during the evolution of iron meteorites

NASA Astrophysics Data System (ADS)

Corrigan, Catherine M.; Chabot, Nancy L.; McCoy, Timothy J.; McDonough, William F.; Watson, Heather C.; Saslow, Sarah A.; Ash, Richard D.

2009-05-01

To better understand the partitioning behavior of elements during the formation and evolution of iron meteorites, two sets of experiments were conducted at 1 atm in the Fe-Ni-P system. The first set examined the effect of P on solid metal/liquid metal partitioning behavior of 22 elements, while the other set explored the effect of the crystal structures of body-centered cubic (α)- and face-centered cubic (γ)-solid Fe alloys on partitioning behavior. Overall, the effect of P on the partition coefficients for the majority of the elements was minimal. As, Au, Ga, Ge, Ir, Os, Pt, Re, and Sb showed slightly increasing partition coefficients with increasing P-content of the metallic liquid. Co, Cu, Pd, and Sn showed constant partition coefficients. Rh, Ru, W, and Mo showed phosphorophile (P-loving) tendencies. Parameterization models were applied to solid metal/liquid metal results for 12 elements. As, Au, Pt, and Re failed to match previous parameterization models, requiring the determination of separate parameters for the Fe-Ni-S and Fe-Ni-P systems. Experiments with coexisting α and γ Fe alloy solids produced partitioning ratios close to unity, indicating that an α versus γ Fe alloy crystal structure has only a minor influence on the partitioning behaviors of the trace element studied. A simple relationship between an element's natural crystal structure and its α/γ partitioning ratio was not observed. If an iron meteorite crystallizes from a single metallic liquid that contains both S and P, the effect of P on the distribution of elements between the crystallizing solids and the residual liquid will be minor in comparison to the effect of S. This indicates that to a first order, fractional crystallization models of the Fe-Ni-S-P system that do not take into account P are appropriate for interpreting the evolution of iron meteorites if the effects of S are appropriately included in the effort.

Models of Pilot Behavior and Their Use to Evaluate the State of Pilot Training

NASA Astrophysics Data System (ADS)

Jirgl, Miroslav; Jalovecky, Rudolf; Bradac, Zdenek

2016-07-01

This article discusses the possibilities of obtaining new information related to human behavior, namely the changes or progressive development of pilots' abilities during training. The main assumption is that a pilot's ability can be evaluated based on a corresponding behavioral model whose parameters are estimated using mathematical identification procedures. The mean values of the identified parameters are obtained via statistical methods. These parameters are then monitored and their changes evaluated. In this context, the paper introduces and examines relevant mathematical models of human (pilot) behavior, the pilot-aircraft interaction, and an example of the mathematical analysis.

Loads and Deformations of Buckled Rectangular Plates. Degree awarded by Virginia Polytechnic Inst., Jun. 1958

NASA Technical Reports Server (NTRS)

Stein, Manuel

1959-01-01

The nonlinear large-deflection equations of von Karman for plates are converted into a set of linear equations by expanding the displacements Into a power series in terms of an arbitrary parameter. The postbuckling behavior of simply supported rectangular plates subjected to longitudinal compression and subject to a uniform temperature rise is investigated in detail by solving the first few of the equations. Experimental data are presented for the compression problem. Comparisons are made for total shortening and local strains and deflections which indicate good agreement between experimental and theoretical results.

Systems and methods for optimal power flow on a radial network

DOEpatents

Low, Steven H.; Peng, Qiuyu

2018-04-24

Node controllers and power distribution networks in accordance with embodiments of the invention enable distributed power control. One embodiment includes a node controller including a distributed power control application; a plurality of node operating parameters describing the operating parameter of a node and a set of at least one node selected from the group consisting of an ancestor node and at least one child node; wherein send node operating parameters to nodes in the set of at least one node; receive operating parameters from the nodes in the set of at least one node; calculate a plurality of updated node operating parameters using an iterative process to determine the updated node operating parameters using the node operating parameters that describe the operating parameters of the node and the set of at least one node, where the iterative process involves evaluation of a closed form solution; and adjust node operating parameters.

On the use of published radiobiological parameters and the evaluation of NTCP models regarding lung pneumonitis in clinical breast radiotherapy.

PubMed

Svolos, Patricia; Tsougos, Ioannis; Kyrgias, Georgios; Kappas, Constantine; Theodorou, Kiki

2011-04-01

In this study we sought to evaluate and accent the importance of radiobiological parameter selection and implementation to the normal tissue complication probability (NTCP) models. The relative seriality (RS) and the Lyman-Kutcher-Burman (LKB) models were studied. For each model, a minimum and maximum set of radiobiological parameter sets was selected from the overall published sets applied in literature and a theoretical mean parameter set was computed. In order to investigate the potential model weaknesses in NTCP estimation and to point out the correct use of model parameters, these sets were used as input to the RS and the LKB model, estimating radiation induced complications for a group of 36 breast cancer patients treated with radiotherapy. The clinical endpoint examined was Radiation Pneumonitis. Each model was represented by a certain dose-response range when the selected parameter sets were applied. Comparing the models with their ranges, a large area of coincidence was revealed. If the parameter uncertainties (standard deviation) are included in the models, their area of coincidence might be enlarged, constraining even greater their predictive ability. The selection of the proper radiobiological parameter set for a given clinical endpoint is crucial. Published parameter values are not definite but should be accompanied by uncertainties, and one should be very careful when applying them to the NTCP models. Correct selection and proper implementation of published parameters provides a quite accurate fit of the NTCP models to the considered endpoint.

Models of Lift and Drag Coefficients of Stalled and Unstalled Airfoils in Wind Turbines and Wind Tunnels

NASA Technical Reports Server (NTRS)

Spera, David A.

2008-01-01

Equations are developed with which to calculate lift and drag coefficients along the spans of torsionally-stiff rotating airfoils of the type used in wind turbine rotors and wind tunnel fans, at angles of attack in both the unstalled and stalled aerodynamic regimes. Explicit adjustments are made for the effects of aspect ratio (length to chord width) and airfoil thickness ratio. Calculated lift and drag parameters are compared to measured parameters for 55 airfoil data sets including 585 test points. Mean deviation was found to be -0.4 percent and standard deviation was 4.8 percent. When the proposed equations were applied to the calculation of power from a stall-controlled wind turbine tested in a NASA wind tunnel, mean deviation from 54 data points was -1.3 percent and standard deviation was 4.0 percent. Pressure-rise calculations for a large wind tunnel fan deviated by 2.7 percent (mean) and 4.4 percent (standard). The assumption that a single set of lift and drag coefficient equations can represent the stalled aerodynamic behavior of a wide variety of airfoils was found to be satisfactory.

Estimating the biophysical properties of neurons with intracellular calcium dynamics.

PubMed

Ye, Jingxin; Rozdeba, Paul J; Morone, Uriel I; Daou, Arij; Abarbanel, Henry D I

2014-06-01

We investigate the dynamics of a conductance-based neuron model coupled to a model of intracellular calcium uptake and release by the endoplasmic reticulum. The intracellular calcium dynamics occur on a time scale that is orders of magnitude slower than voltage spiking behavior. Coupling these mechanisms sets the stage for the appearance of chaotic dynamics, which we observe within certain ranges of model parameter values. We then explore the question of whether one can, using observed voltage data alone, estimate the states and parameters of the voltage plus calcium (V+Ca) dynamics model. We find the answer is negative. Indeed, we show that voltage plus another observed quantity must be known to allow the estimation to be accurate. We show that observing both the voltage time course V(t) and the intracellular Ca time course will permit accurate estimation, and from the estimated model state, accurate prediction after observations are completed. This sets the stage for how one will be able to use a more detailed model of V+Ca dynamics in neuron activity in the analysis of experimental data on individual neurons as well as functional networks in which the nodes (neurons) have these biophysical properties.

Communication: Density functional theory embedding with the orthogonality constrained basis set expansion procedure

NASA Astrophysics Data System (ADS)

Culpitt, Tanner; Brorsen, Kurt R.; Hammes-Schiffer, Sharon

2017-06-01

Density functional theory (DFT) embedding approaches have generated considerable interest in the field of computational chemistry because they enable calculations on larger systems by treating subsystems at different levels of theory. To circumvent the calculation of the non-additive kinetic potential, various projector methods have been developed to ensure the orthogonality of molecular orbitals between subsystems. Herein the orthogonality constrained basis set expansion (OCBSE) procedure is implemented to enforce this subsystem orbital orthogonality without requiring a level shifting parameter. This scheme is a simple alternative to existing parameter-free projector-based schemes, such as the Huzinaga equation. The main advantage of the OCBSE procedure is that excellent convergence behavior is attained for DFT-in-DFT embedding without freezing any of the subsystem densities. For the three chemical systems studied, the level of accuracy is comparable to or higher than that obtained with the Huzinaga scheme with frozen subsystem densities. Allowing both the high-level and low-level DFT densities to respond to each other during DFT-in-DFT embedding calculations provides more flexibility and renders this approach more generally applicable to chemical systems. It could also be useful for future extensions to embedding approaches combining wavefunction theories and DFT.

Estimating the biophysical properties of neurons with intracellular calcium dynamics

NASA Astrophysics Data System (ADS)

Ye, Jingxin; Rozdeba, Paul J.; Morone, Uriel I.; Daou, Arij; Abarbanel, Henry D. I.

2014-06-01

We investigate the dynamics of a conductance-based neuron model coupled to a model of intracellular calcium uptake and release by the endoplasmic reticulum. The intracellular calcium dynamics occur on a time scale that is orders of magnitude slower than voltage spiking behavior. Coupling these mechanisms sets the stage for the appearance of chaotic dynamics, which we observe within certain ranges of model parameter values. We then explore the question of whether one can, using observed voltage data alone, estimate the states and parameters of the voltage plus calcium (V+Ca) dynamics model. We find the answer is negative. Indeed, we show that voltage plus another observed quantity must be known to allow the estimation to be accurate. We show that observing both the voltage time course V (t) and the intracellular Ca time course will permit accurate estimation, and from the estimated model state, accurate prediction after observations are completed. This sets the stage for how one will be able to use a more detailed model of V+Ca dynamics in neuron activity in the analysis of experimental data on individual neurons as well as functional networks in which the nodes (neurons) have these biophysical properties.

Reactive flow model development for PBXW-126 using modern nonlinear optimization methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murphy, M.J.; Simpson, R.L.; Urtiew, P.A.

1996-05-01

The initiation and detonation behavior of PBXW-126 has been characterized and is described. PBXW-126 is a composite explosive consisting of approximately equal amounts of RDX, AP, AL, and NTO with a polyurethane binder. The three term ignition and growth of reaction model parameters (ignition+two growth terms) have been found using nonlinear optimization methods to determine the {open_quotes}best{close_quotes} set of model parameters. The ignition term treats the initiation of up to 0.5{percent} of the RDX. The first growth term in the model treats the RDX growth of reaction up to 20{percent} reacted. The second growth term treats the subsequent growth ofmore » reaction of the remaining AP/AL/NTO. The unreacted equation of state (EOS) was determined from the wave profiles of embedded gauge tests while the JWL product EOS was determined from cylinder expansion test results. The nonlinear optimization code, NLQPEB/GLO, was used to determine the {open_quotes}best{close_quotes} set of coefficients for the three term Lee-Tarver ignition and growth of reaction model. {copyright} {ital 1996 American Institute of Physics.}« less

Fatigue Behavior of Porous Ti-6Al-4V Made by Laser-Engineered Net Shaping.

PubMed

Razavi, Seyed Mohammad Javad; Bordonaro, Giancarlo G; Ferro, Paolo; Torgersen, Jan; Berto, Filippo

2018-02-12

The fatigue behavior and fracture mechanisms of additively manufactured Ti-6Al-4V specimens are investigated in this study. Three sets of testing samples were fabricated for the assessment of fatigue life. The first batch of samples was built by using Laser-Engineered Net Shaping (LENS) technology, a Direct Energy Deposition (DED) method. Internal voids and defects were induced in a second batch of samples by changing LENS machine processing parameters. Fatigue performance of these samples is compared to the wrought Ti-6Al-4V samples. The effects of machine-induced porosity are assessed on mechanical properties and results are presented in the form of SN curves for the three sets of samples. Fracture mechanisms are examined by using Scanning Electron Microscopy (SEM) to characterize the morphological characteristics of the failure surface. Different fracture surface morphologies are observed for porous and non-porous specimens due to the combination of head write speed and laser power. Formation of defects such as pores, unmelted regions, and gas entrapments affect the failure mechanisms in porous specimens. Non-porous specimens exhibit fatigue properties comparable with that of the wrought specimens, but porous specimens are found to show a tremendous reduced fatigue strength.

A Multi-Area Stochastic Model for a Covert Visual Search Task.

PubMed

Schwemmer, Michael A; Feng, Samuel F; Holmes, Philip J; Gottlieb, Jacqueline; Cohen, Jonathan D

2015-01-01

Decisions typically comprise several elements. For example, attention must be directed towards specific objects, their identities recognized, and a choice made among alternatives. Pairs of competing accumulators and drift-diffusion processes provide good models of evidence integration in two-alternative perceptual choices, but more complex tasks requiring the coordination of attention and decision making involve multistage processing and multiple brain areas. Here we consider a task in which a target is located among distractors and its identity reported by lever release. The data comprise reaction times, accuracies, and single unit recordings from two monkeys' lateral interparietal area (LIP) neurons. LIP firing rates distinguish between targets and distractors, exhibit stimulus set size effects, and show response-hemifield congruence effects. These data motivate our model, which uses coupled sets of leaky competing accumulators to represent processes hypothesized to occur in feature-selective areas and limb motor and pre-motor areas, together with the visual selection process occurring in LIP. Model simulations capture the electrophysiological and behavioral data, and fitted parameters suggest that different connection weights between LIP and the other cortical areas may account for the observed behavioral differences between the animals.

CORC: An Online Data Quality Tool For CUORE

NASA Astrophysics Data System (ADS)

Welliver, Bradford

2017-09-01

The Cryogenic Underground Observatory for Rare Events (CUORE) is a large neutrinoless double beta decay search experiment. Currently CUORE is actively taking data at the Laboratori Nazionali del Gran Sasso (LNGS). These searches can address fundamental questions about the nature of the neutrino and may provide insight into the observed matter-antimatter asymmetry in the universe leading to beyond standard model physics via lepton number violation. CUORE is the largest array of crystal bolometers in the world, containing a total of 988 TeO2 crystals with a mass of 742kg and is expected to achieve a sensitivity on the 130Te 0 νββ half-life of T1 / 2 = 9 × 1025 years (90% C.L.) after 5 years of operation. The large number of individual crystals in CUORE presents challenges for monitoring data quality and determination of time periods of detector behavior suitable for analysis. We will discuss the current state of the online run diagnostic system that allows for easy monitoring of all crystals, provides an overview of performance over time, and gives an ability to set flags for periods of bad detector behavior as well as set phone and email alarms on various cryostat parameters.

Guided goal setting: effectiveness in a dietary and physical activity intervention with low-income adolescents.

PubMed

Shilts, Mical Kay; Horowitz, Marcel; Townsend, Marilyn S

2009-01-01

Determining the effectiveness of the guided goal setting strategy on changing adolescents' dietary and physical activity self-efficacy and behaviors. Adolescents were individually assigned to treatment (intervention with guided goal setting) or control conditions (intervention without guided goal setting) with data collected before and after the education intervention. Urban middle school in a low-income community in Central California. Ethnically diverse middle school students (n = 94, 55% male) who were participants of a USDA nutrition education program. Driven by the Social Cognitive Theory, the intervention targeted dietary and physical activity behaviors of adolescents. Dietary self-efficacy and behavior; physical activity self-efficacy and behavior; goal effort and spontaneous goal setting. ANCOVA and path analysis were performed using the full sample and a sub-sample informed by Locke's recommendations (accounting for goal effort and spontaneous goal setting). No significant differences were found between groups using the full sample. Using the sub-sample, greater gains in dietary behavior (p < .05), physical activity behavior (p < .05), and physical activity self-efficacy (p < .05) were made by treatment participants compared to control participants. Change in physical activity behaviors was mediated by self-efficacy. Accounting for goal effort and spontaneous goal setting, this study provides some evidence that the use of guided goal setting with adolescents may be a viable strategy to promote dietary and physical activity behavior change.

Role of codeposited impurities during growth. II. Dependence of morphology on binding and barrier energies

NASA Astrophysics Data System (ADS)

Sathiyanarayanan, Rajesh; Hamouda, Ajmi Bh.; Pimpinelli, A.; Einstein, T. L.

2011-01-01

In an accompanying article we showed that surface morphologies obtained through codeposition of a small quantity (2%) of impurities with Cu during growth (step-flow mode, θ = 40 ML) significantly depends on the lateral nearest-neighbor binding energy (ENN) to Cu adatom and the diffusion barrier (Ed) of the impurity atom on Cu(0 0 1). Based on these two energy parameters, ENN and Ed, we classify impurity atoms into four sets. We study island nucleation and growth in the presence of codeposited impurities from different sets in the submonolayer (θ⩽ 0.7 ML) regime. Similar to growth in the step-flow mode, we find different nucleation and growth behavior for impurities from different sets. We characterize these differences through variations of the number of islands (Ni) and the average island size with coverage (θ). Further, we compute the critical nucleus size (i) for all of these cases from the distribution of capture-zone areas using the generalized Wigner distribution.

Comparison of least squares and exponential sine sweep methods for Parallel Hammerstein Models estimation

NASA Astrophysics Data System (ADS)

Rebillat, Marc; Schoukens, Maarten

2018-05-01

Linearity is a common assumption for many real-life systems, but in many cases the nonlinear behavior of systems cannot be ignored and must be modeled and estimated. Among the various existing classes of nonlinear models, Parallel Hammerstein Models (PHM) are interesting as they are at the same time easy to interpret as well as to estimate. One way to estimate PHM relies on the fact that the estimation problem is linear in the parameters and thus that classical least squares (LS) estimation algorithms can be used. In that area, this article introduces a regularized LS estimation algorithm inspired on some of the recently developed regularized impulse response estimation techniques. Another mean to estimate PHM consists in using parametric or non-parametric exponential sine sweeps (ESS) based methods. These methods (LS and ESS) are founded on radically different mathematical backgrounds but are expected to tackle the same issue. A methodology is proposed here to compare them with respect to (i) their accuracy, (ii) their computational cost, and (iii) their robustness to noise. Tests are performed on simulated systems for several values of methods respective parameters and of signal to noise ratio. Results show that, for a given set of data points, the ESS method is less demanding in computational resources than the LS method but that it is also less accurate. Furthermore, the LS method needs parameters to be set in advance whereas the ESS method is not subject to conditioning issues and can be fully non-parametric. In summary, for a given set of data points, ESS method can provide a first, automatic, and quick overview of a nonlinear system than can guide more computationally demanding and precise methods, such as the regularized LS one proposed here.

Flexible Method for Inter-object Communication in C++

NASA Technical Reports Server (NTRS)

Curlett, Brian P.; Gould, Jack J.

1994-01-01

A method has been developed for organizing and sharing large amounts of information between objects in C++ code. This method uses a set of object classes to define variables and group them into tables. The variable tables presented here provide a convenient way of defining and cataloging data, as well as a user-friendly input/output system, a standardized set of access functions, mechanisms for ensuring data integrity, methods for interprocessor data transfer, and an interpretive language for programming relationships between parameters. The object-oriented nature of these variable tables enables the use of multiple data types, each with unique attributes and behavior. Because each variable provides its own access methods, redundant table lookup functions can be bypassed, thus decreasing access times while maintaining data integrity. In addition, a method for automatic reference counting was developed to manage memory safely.

Improved inhalation technology for setting safe exposure levels for workplace chemicals

NASA Technical Reports Server (NTRS)

Stuart, Bruce O.

1993-01-01

Threshold Limit Values recommended as allowable air concentrations of a chemical in the workplace are often based upon a no-observable-effect-level (NOEL) determined by experimental inhalation studies using rodents. A 'safe level' for human exposure must then be estimated by the use of generalized safety factors in attempts to extrapolate from experimental rodents to man. The recent development of chemical-specific physiologically-based toxicokinetics makes use of measured physiological, biochemical, and metabolic parameters to construct a validated model that is able to 'scale-up' rodent response data to predict the behavior of the chemical in man. This procedure is made possible by recent advances in personal computer software and the emergence of appropriate biological data, and provides an analytical tool for much more reliable risk evaluation and airborne chemical exposure level setting for humans.

A set of constitutive relationships accounting for residual NAPL in the unsaturated zone.

PubMed

Wipfler, E L; van der Zee, S E

2001-07-01

Although laboratory experiments show that non-aqueous phase liquid (NAPL) is retained in the unsaturated zone, no existing multiphase flow model has been developed to account for residual NAPL after NAPL drainage in the unsaturated zone. We developed a static constitutive set of saturation-capillary pressure relationships for water, NAPL and air that accounts for both this residual NAPL and entrapped NAPL. The set of constitutive relationships is formulated similarly to the set of scaled relationships that is frequently applied in continuum models. The new set consists of three fluid-phase systems: a three-phase system and a two-phase system, that both comply with the original constitutive model, and a newly introduced residual NAPL system. The new system can be added relatively easily to the original two- and three-phase systems. Entrapment is included in the model. The constitutive relationships of the non-drainable residual NAPL system are based on qualitative fluid behavior derived from a pore scale model. The pore scale model reveals that the amount of residual NAPL depends on the spreading coefficient and the water saturation. Furthermore, residual NAPL is history-dependent. At the continuum scale, a critical NAPL pressure head defines the transition from free, mobile NAPL to residual NAPL. Although the Pc-S relationships for water and total liquid are not independent in case of residual NAPL, two two-phase Pc-S relations can represent a three-phase residual system of Pc-S relations. A newly introduced parameter, referred to as the residual oil pressure head, reflects the mutual dependency of water and oil. Example calculations show consistent behavior of the constitutive model. Entrapment and retention in the unsaturated zone cooperate to retain NAPL. Moreover, the results of our constitutive model are in agreement with experimental observations.

Standard fire behavior fuel models: a comprehensive set for use with Rothermel's surface fire spread model

Treesearch

Joe H. Scott; Robert E. Burgan

2005-01-01

This report describes a new set of standard fire behavior fuel models for use with Rothermel's surface fire spread model and the relationship of the new set to the original set of 13 fire behavior fuel models. To assist with transition to using the new fuel models, a fuel model selection guide, fuel model crosswalk, and set of fuel model photos are provided.

Solution Focused Empathy Training Groups for Students with Fire-Setting Behaviors

ERIC Educational Resources Information Center

Froeschle, Janet G.

2006-01-01

Fire-setting students are those who intentionally or unintentionally set one or more fires due to curiosity, stress, a need for attention, or due to criminal delinquency. This article describes the nature of fire-setting behaviors, discusses the profile and risk factors associated with the behavior, and outlines a group program using empathy…

Goal setting: an integral component of effective diabetes care.

PubMed

Miller, Carla K; Bauman, Jennifer

2014-08-01

Goal setting is a widely used behavior change tool in diabetes education and training. Prior research found specific relatively difficult but attainable goals set within a specific timeframe improved performance in sports and at the workplace. However, the impact of goal setting in diabetes self-care has not received extensive attention. This review examined the mechanisms underlying behavioral change according to goal setting theory and evaluated the impact of goal setting in diabetes intervention studies. Eight studies were identified, which incorporated goal setting as the primary strategy to promote behavioral change in individual, group-based, and primary care settings among patients with type 2 diabetes. Improvements in diabetes-related self-efficacy, dietary intake, physical activity, and A1c were observed in some but not all studies. More systematic research is needed to determine the conditions and behaviors for which goal setting is most effective. Initial recommendations for using goal setting in diabetes patient encounters are offered.

Steel Rack Connections: Identification of Most Influential Factors and a Comparison of Stiffness Design Methods

PubMed Central

Shah, S. N. R.; Sulong, N. H. Ramli; Shariati, Mahdi; Jumaat, M. Z.

2015-01-01

Steel pallet rack (SPR) beam-to-column connections (BCCs) are largely responsible to avoid the sway failure of frames in the down-aisle direction. The overall geometry of beam end connectors commercially used in SPR BCCs is different and does not allow a generalized analytic approach for all types of beam end connectors; however, identifying the effects of the configuration, profile and sizes of the connection components could be the suitable approach for the practical design engineers in order to predict the generalized behavior of any SPR BCC. This paper describes the experimental behavior of SPR BCCs tested using a double cantilever test set-up. Eight sets of specimens were identified based on the variation in column thickness, beam depth and number of tabs in the beam end connector in order to investigate the most influential factors affecting the connection performance. Four tests were repeatedly performed for each set to bring uniformity to the results taking the total number of tests to thirty-two. The moment-rotation (M-θ) behavior, load-strain relationship, major failure modes and the influence of selected parameters on connection performance were investigated. A comparative study to calculate the connection stiffness was carried out using the initial stiffness method, the slope to half-ultimate moment method and the equal area method. In order to find out the more appropriate method, the mean stiffness of all the tested connections and the variance in values of mean stiffness according to all three methods were calculated. The calculation of connection stiffness by means of the initial stiffness method is considered to overestimate the values when compared to the other two methods. The equal area method provided more consistent values of stiffness and lowest variance in the data set as compared to the other two methods. PMID:26452047

Interactive model evaluation tool based on IPython notebook

NASA Astrophysics Data System (ADS)

Balemans, Sophie; Van Hoey, Stijn; Nopens, Ingmar; Seuntjes, Piet

2015-04-01

In hydrological modelling, some kind of parameter optimization is mostly performed. This can be the selection of a single best parameter set, a split in behavioural and non-behavioural parameter sets based on a selected threshold or a posterior parameter distribution derived with a formal Bayesian approach. The selection of the criterion to measure the goodness of fit (likelihood or any objective function) is an essential step in all of these methodologies and will affect the final selected parameter subset. Moreover, the discriminative power of the objective function is also dependent from the time period used. In practice, the optimization process is an iterative procedure. As such, in the course of the modelling process, an increasing amount of simulations is performed. However, the information carried by these simulation outputs is not always fully exploited. In this respect, we developed and present an interactive environment that enables the user to intuitively evaluate the model performance. The aim is to explore the parameter space graphically and to visualize the impact of the selected objective function on model behaviour. First, a set of model simulation results is loaded along with the corresponding parameter sets and a data set of the same variable as the model outcome (mostly discharge). The ranges of the loaded parameter sets define the parameter space. A selection of the two parameters visualised can be made by the user. Furthermore, an objective function and a time period of interest need to be selected. Based on this information, a two-dimensional parameter response surface is created, which actually just shows a scatter plot of the parameter combinations and assigns a color scale corresponding with the goodness of fit of each parameter combination. Finally, a slider is available to change the color mapping of the points. Actually, the slider provides a threshold to exclude non behaviour parameter sets and the color scale is only attributed to the remaining parameter sets. As such, by interactively changing the settings and interpreting the graph, the user gains insight in the model structural behaviour. Moreover, a more deliberate choice of objective function and periods of high information content can be identified. The environment is written in an IPython notebook and uses the available interactive functions provided by the IPython community. As such, the power of the IPython notebook as a development environment for scientific computing is illustrated (Shen, 2014).

History of childhood trauma and disruptive behaviors in the medical setting.

PubMed

Sansone, Randy A; Farukhi, Shahzad; Wiederman, Michael W

2012-03-01

In this study, we examined relationships between five types of childhood trauma and 17 disruptive behaviors in the medical setting. Using a cross-sectional consecutive sample of 394 internal medicine outpatients, we surveyed participants about five types of childhood trauma (i.e. witnessing of violence, physical neglect, emotional abuse, physical abuse, and sexual abuse) and 17 disruptive behaviors in the medical setting (e.g., yelling, cursing, threatening medical personnel). Initial correlations indicated relationships between four of the five forms of childhood trauma and the number of different disruptive behaviors endorsed. However, using multiple regression analysis, only witnessing violence and physical abuse remained independent predictors of disruptive behaviors in the medical setting. Individuals with childhood histories of witnessing violence and/or physical abuse are at-risk for perpetrating various disruptive behaviors in the medical setting.

Lattice model for water-solute mixtures.

PubMed

Furlan, A P; Almarza, N G; Barbosa, M C

2016-10-14

A lattice model for the study of mixtures of associating liquids is proposed. Solvent and solute are modeled by adapting the associating lattice gas (ALG) model. The nature of interaction of solute/solvent is controlled by tuning the energy interactions between the patches of ALG model. We have studied three set of parameters, resulting in, hydrophilic, inert, and hydrophobic interactions. Extensive Monte Carlo simulations were carried out, and the behavior of pure components and the excess properties of the mixtures have been studied. The pure components, water (solvent) and solute, have quite similar phase diagrams, presenting gas, low density liquid, and high density liquid phases. In the case of solute, the regions of coexistence are substantially reduced when compared with both the water and the standard ALG models. A numerical procedure has been developed in order to attain series of results at constant pressure from simulations of the lattice gas model in the grand canonical ensemble. The excess properties of the mixtures, volume and enthalpy as the function of the solute fraction, have been studied for different interaction parameters of the model. Our model is able to reproduce qualitatively well the excess volume and enthalpy for different aqueous solutions. For the hydrophilic case, we show that the model is able to reproduce the excess volume and enthalpy of mixtures of small alcohols and amines. The inert case reproduces the behavior of large alcohols such as propanol, butanol, and pentanol. For the last case (hydrophobic), the excess properties reproduce the behavior of ionic liquids in aqueous solution.

A sensitive biomarker for the detection of aquatic contamination based on behavioral assays using zebrafish larvae.

PubMed

Nüßer, Leonie K; Skulovich, Olya; Hartmann, Sarah; Seiler, Thomas-Benjamin; Cofalla, Catrina; Schuettrumpf, Holger; Hollert, Henner; Salomons, Elad; Ostfeld, Avi

2016-11-01

An effective biological early warning system for the detection of water contamination should employ undemanding species that rapidly react to the presence of contaminants in their environment. The demonstrated reaction should be comprehensible and unambiguously evidential of the contamination event. This study utilized 96h post fertilization zebrafish larvae and tested their behavioral response to acute exposure to low concentrations of cadmium chloride (CdCl2) (5.0, 2.5, 1.25, 0.625mg/L) and permethrin (0.05, 0.029, 0.017, 0.01μg/L). We hypothesize that the number of larvae that show advanced trajectories in a group corresponds with water contamination, as the latter triggers avoidance behavior in the organisms. The proportion of advanced trajectories in the control and treated groups during the first minute of darkness was designated as a segregation parameter. It was parametrized and a threshold value was set using one CdCl2 trial and then applied to the remaining CdCl2 and permethrin replicates. For all cases, the method allowed distinguishing between the control and treated groups within two cycles of light: dark. The calculated parameter was statistically significantly different between the treated and control groups, except for the lowest CdCl2 concentration (0.625mg/L) in one replicate. This proof-of-concept study shows the potential of the proposed methodology for utilization as part of a multispecies biomonitoring system. Copyright © 2016 Elsevier Inc. All rights reserved.

Microstructure and Mechanical Properties in Hot-Rolled Extra High-Yield-Strength Steel Plates for Offshore Structure and Shipbuilding

NASA Astrophysics Data System (ADS)

Liu, Dongsheng; Li, Qingliang; Emi, Toshihiko

2011-05-01

Key parameters for a thermomechanically controlled processing and accelerated cooling process (TMCP-AcC) were determined for integrated mass production to produce extra high-yield-strength microalloyed low carbon SiMnCrNiCu steel plates for offshore structure and bulk shipbuilding. Confocal scanning microscopy was used to make in-situ observations on the austenite grain growth during reheating. A Gleeble 3800 thermomechanical simulator was employed to investigate the flow stress behavior, static recrystallization (SRX) of austenite, and decomposition behavior of the TMCP conditioned austenite during continuous cooling. The Kocks-Mecking model was employed to describe the constitutive behavior, while the Johnson-Mehl-Avrami-Kolmogorov (JMAK) approach was used to predict the SRX kinetics. The effects of hot rolling schedule and AcC on microstructure and properties were investigated by test-scale rolling trials. The bridging between the laboratory observations and the process parameter determination to optimize the mass production was made by integrated industrial production trials on a set of a 5-m heavy plate mill equipped with an accelerated cooling system. Successful production of 60- and 50-mm-thick plates with yield strength in excess of 460 MPa and excellent toughness at low temperature (213 K (-60 °C)) in the parent metal and the simulated coarse-grained heat affected zone (CGHAZ) provides a useful integrated database for developing advanced high-strength steel plates via TMCP-AcC.

Relaxation dynamics of multilayer triangular Husimi cacti

NASA Astrophysics Data System (ADS)

Galiceanu, Mircea; Jurjiu, Aurel

2016-09-01

We focus on the relaxation dynamics of multilayer polymer structures having, as underlying topology, the Husimi cactus. The relaxation dynamics of the multilayer structures is investigated in the framework of generalized Gaussian structures model using both Rouse and Zimm approaches. In the Rouse type-approach, we determine analytically the complete eigenvalues spectrum and based on it we calculate the mechanical relaxation moduli (storage and loss modulus) and the average monomer displacement. First, we monitor these physical quantities for structures with a fixed generation number and we increase the number of layers, such that the linear topology will smoothly come into play. Second, we keep constant the size of the structures, varying simultaneously two parameters: the generation number of the main layer, G, and the number of layers, c. This fact allows us to study in detail the crossover from a pure Husimi cactus behavior to a predominately linear chain behavior. The most interesting situation is found when the two limiting topologies cancel each other. For this case, we encounter in the intermediate frequency/time domain regions of constant slope for different values of the parameter set (G, c) and we show that the number of layers follows an exponential-law of G. In the Zimm-type approach, which includes the hydrodynamic interactions, the quantities that describe the mechanical relaxation dynamics do not show scaling behavior as in the Rouse model, except the limiting case, namely, a very high number of layers and low generation number.

Generalized Likelihood Uncertainty Estimation (GLUE) Using Multi-Optimization Algorithm as Sampling Method

NASA Astrophysics Data System (ADS)

Wang, Z.

2015-12-01

For decades, distributed and lumped hydrological models have furthered our understanding of hydrological system. The development of hydrological simulation in large scale and high precision elaborated the spatial descriptions and hydrological behaviors. Meanwhile, the new trend is also followed by the increment of model complexity and number of parameters, which brings new challenges of uncertainty quantification. Generalized Likelihood Uncertainty Estimation (GLUE) has been widely used in uncertainty analysis for hydrological models referring to Monte Carlo method coupled with Bayesian estimation. However, the stochastic sampling method of prior parameters adopted by GLUE appears inefficient, especially in high dimensional parameter space. The heuristic optimization algorithms utilizing iterative evolution show better convergence speed and optimality-searching performance. In light of the features of heuristic optimization algorithms, this study adopted genetic algorithm, differential evolution, shuffled complex evolving algorithm to search the parameter space and obtain the parameter sets of large likelihoods. Based on the multi-algorithm sampling, hydrological model uncertainty analysis is conducted by the typical GLUE framework. To demonstrate the superiority of the new method, two hydrological models of different complexity are examined. The results shows the adaptive method tends to be efficient in sampling and effective in uncertainty analysis, providing an alternative path for uncertainty quantilization.

Bayesian population analysis of a washin-washout physiologically based pharmacokinetic model for acetone

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moerk, Anna-Karin, E-mail: anna-karin.mork@ki.s; Jonsson, Fredrik; Pharsight, a Certara company, St. Louis, MO

2009-11-01

The aim of this study was to derive improved estimates of population variability and uncertainty of physiologically based pharmacokinetic (PBPK) model parameters, especially of those related to the washin-washout behavior of polar volatile substances. This was done by optimizing a previously published washin-washout PBPK model for acetone in a Bayesian framework using Markov chain Monte Carlo simulation. The sensitivity of the model parameters was investigated by creating four different prior sets, where the uncertainty surrounding the population variability of the physiological model parameters was given values corresponding to coefficients of variation of 1%, 25%, 50%, and 100%, respectively. The PBPKmore » model was calibrated to toxicokinetic data from 2 previous studies where 18 volunteers were exposed to 250-550 ppm of acetone at various levels of workload. The updated PBPK model provided a good description of the concentrations in arterial, venous, and exhaled air. The precision of most of the model parameter estimates was improved. New information was particularly gained on the population distribution of the parameters governing the washin-washout effect. The results presented herein provide a good starting point to estimate the target dose of acetone in the working and general populations for risk assessment purposes.« less

Behavioral Dynamics in Swimming: The Appropriate Use of Inertial Measurement Units.

PubMed

Guignard, Brice; Rouard, Annie; Chollet, Didier; Seifert, Ludovic

2017-01-01

Motor control in swimming can be analyzed using low- and high-order parameters of behavior. Low-order parameters generally refer to the superficial aspects of movement (i.e., position, velocity, acceleration), whereas high-order parameters capture the dynamics of movement coordination. To assess human aquatic behavior, both types have usually been investigated with multi-camera systems, as they offer high three-dimensional spatial accuracy. Research in ecological dynamics has shown that movement system variability can be viewed as a functional property of skilled performers, helping them adapt their movements to the surrounding constraints. Yet to determine the variability of swimming behavior, a large number of stroke cycles (i.e., inter-cyclic variability) has to be analyzed, which is impossible with camera-based systems as they simply record behaviors over restricted volumes of water. Inertial measurement units (IMUs) were designed to explore the parameters and variability of coordination dynamics. These light, transportable and easy-to-use devices offer new perspectives for swimming research because they can record low- to high-order behavioral parameters over long periods. We first review how the low-order behavioral parameters (i.e., speed, stroke length, stroke rate) of human aquatic locomotion and their variability can be assessed using IMUs. We then review the way high-order parameters are assessed and the adaptive role of movement and coordination variability in swimming. We give special focus to the circumstances in which determining the variability between stroke cycles provides insight into how behavior oscillates between stable and flexible states to functionally respond to environmental and task constraints. The last section of the review is dedicated to practical recommendations for coaches on using IMUs to monitor swimming performance. We therefore highlight the need for rigor in dealing with these sensors appropriately in water. We explain the fundamental and mandatory steps to follow for accurate results with IMUs, from data acquisition (e.g., waterproofing procedures) to interpretation (e.g., drift correction).

Behavioral Dynamics in Swimming: The Appropriate Use of Inertial Measurement Units

PubMed Central

Guignard, Brice; Rouard, Annie; Chollet, Didier; Seifert, Ludovic

2017-01-01

Motor control in swimming can be analyzed using low- and high-order parameters of behavior. Low-order parameters generally refer to the superficial aspects of movement (i.e., position, velocity, acceleration), whereas high-order parameters capture the dynamics of movement coordination. To assess human aquatic behavior, both types have usually been investigated with multi-camera systems, as they offer high three-dimensional spatial accuracy. Research in ecological dynamics has shown that movement system variability can be viewed as a functional property of skilled performers, helping them adapt their movements to the surrounding constraints. Yet to determine the variability of swimming behavior, a large number of stroke cycles (i.e., inter-cyclic variability) has to be analyzed, which is impossible with camera-based systems as they simply record behaviors over restricted volumes of water. Inertial measurement units (IMUs) were designed to explore the parameters and variability of coordination dynamics. These light, transportable and easy-to-use devices offer new perspectives for swimming research because they can record low- to high-order behavioral parameters over long periods. We first review how the low-order behavioral parameters (i.e., speed, stroke length, stroke rate) of human aquatic locomotion and their variability can be assessed using IMUs. We then review the way high-order parameters are assessed and the adaptive role of movement and coordination variability in swimming. We give special focus to the circumstances in which determining the variability between stroke cycles provides insight into how behavior oscillates between stable and flexible states to functionally respond to environmental and task constraints. The last section of the review is dedicated to practical recommendations for coaches on using IMUs to monitor swimming performance. We therefore highlight the need for rigor in dealing with these sensors appropriately in water. We explain the fundamental and mandatory steps to follow for accurate results with IMUs, from data acquisition (e.g., waterproofing procedures) to interpretation (e.g., drift correction). PMID:28352243

Goal setting as a strategy for dietary and physical activity behavior change: a review of the literature.

PubMed

Shilts, Mical Kay; Horowitz, Marcel; Townsend, Marilyn S

2004-01-01

Estimate effectiveness of goal setting for nutrition and physical activity behavior change, review the effect of goal-setting characteristics on behavior change, and investigate effectiveness of interventions containing goal setting. For this review, a literature search was conducted for the period January 1977 through December 2003 that included a Current Contents, Biosis Previews, Medline, PubMed, PsycINFO, and ERIC search of databases and a reference list search. Key words were goal, goal setting, nutrition, diet, dietary, physical activity, exercise, behavior change, interventions, and fitness. The search identified 144 studies, of which 28 met inclusion criteria for being published in a peer reviewed journal and using goal setting in an intervention to modify dietary or physical activity behaviors. Excluded from this review were those studies that (1) evaluated goal setting cross-sectionally without an intervention; (2) used goal setting for behavioral disorders, to improve academic achievement, or in sports performance; (3) were reviews. The articles were categorized by target audience and secondarily by research focus. Data extracted included outcome measure, research rating, purpose, sample, sample description, assignment, findings, and goal-setting support. Thirteen of the 23 adult studies used a goal-setting effectiveness study design and eight produced positive results supporting goal setting. No adolescent or child studies used this design. The results were inconclusive for the studies investigating goal-setting characteristics (n = 7). Four adult and four child intervention evaluation studies showed positive outcomes. No studies reported power calculations, and only 32% of the studies were rated as fully supporting goal setting. Goal setting has shown some promise in promoting dietary and physical activity behavior change among adults, but methodological issues still need to be resolved. The literature with adolescents and children is limited, and the authors are not aware of any published studies with this audience investigating the independent effect of goal setting on dietary or physical activity behavior. Although, goal setting is widely used with children and adolescents in nutrition interventions, its effectiveness has yet to be reported.

The light spot test: Measuring anxiety in mice in an automated home-cage environment.

PubMed

Aarts, Emmeke; Maroteaux, Gregoire; Loos, Maarten; Koopmans, Bastijn; Kovačević, Jovana; Smit, August B; Verhage, Matthijs; Sluis, Sophie van der

2015-11-01

Behavioral tests of animals in a controlled experimental setting provide a valuable tool to advance understanding of genotype-phenotype relations, and to study the effects of genetic and environmental manipulations. To optimally benefit from the increasing numbers of genetically engineered mice, reliable high-throughput methods for comprehensive behavioral phenotyping of mice lines have become a necessity. Here, we describe the development and validation of an anxiety test, the light spot test, that allows for unsupervised, automated, high-throughput testing of mice in a home-cage system. This automated behavioral test circumvents bias introduced by pretest handling, and enables recording both baseline behavior and the behavioral test response over a prolonged period of time. We demonstrate that the light spot test induces a behavioral response in C57BL/6J mice. This behavior reverts to baseline when the aversive stimulus is switched off, and is blunted by treatment with the anxiolytic drug Diazepam, demonstrating predictive validity of the assay, and indicating that the observed behavioral response has a significant anxiety component. Also, we investigated the effectiveness of the light spot test as part of sequential testing for different behavioral aspects in the home-cage. Two learning tests, administered prior to the light spot test, affected the light spot test parameters. The light spot test is a novel, automated assay for anxiety-related high-throughput testing of mice in an automated home-cage environment, allowing for both comprehensive behavioral phenotyping of mice, and rapid screening of pharmacological compounds. Copyright © 2015 Elsevier B.V. All rights reserved.

Atomistic modeling of metallic thin films by modified embedded atom method

NASA Astrophysics Data System (ADS)

Hao, Huali; Lau, Denvid

2017-11-01

Molecular dynamics simulation is applied to investigate the deposition process of metallic thin films. Eight metals, titanium, vanadium, iron, cobalt, nickel, copper, tungsten, and gold, are chosen to be deposited on the aluminum substrate. The second nearest-neighbor modified embedded atom method potential is adopted to predict their thermal and mechanical properties. When quantifying the screening parameters of the potential, the error for Young's modulus and coefficient of thermal expansion between the simulated results and the experimental measurements is less than 15%, demonstrating the reliability of the potential to predict metallic behaviors related to thermal and mechanical properties. A set of potential parameters which governs the interactions between aluminum and other metals in a binary system is also generated from ab initio calculation. The details of interfacial structures between the chosen films and substrate are successfully simulated with the help of these parameters. Our results indicate that the preferred orientation of film growth depends on the film crystal structure, and the inter-diffusion at the interface is correlated the cohesive energy parameter of potential for the binary system. Such finding provides an important basis to further understand the interfacial science, which contributes to the improvement of the mechanical properties, reliability and durability of films.

Patterns of Home and School Behavior Problems in Rural and Urban Settings

PubMed Central

Hope, Timothy L; Bierman, Karen L

2009-01-01

This study examined the cross-situational patterns of behavior problems shown by children in rural and urban communities at school entry. Behavior problems exhibited in home settings were not expected to vary significantly across urban and rural settings. In contrast, it was anticipated that child behavior at school would be heavily influenced by the increased exposure to aggressive models and deviant peer support experienced by children in urban as compared to rural schools, leading to higher rates of school conduct problems for children in urban settings. Statistical comparisons of the patterns of behavior problems shown by representative samples of 89 rural and 221 urban children provided support for these hypotheses, as significant rural-urban differences emerged in school and not in home settings. Cross-situational patterns of behavior problems also varied across setting, with home-only patterns of problems characterizing more children at the rural site and school-only, patterns of behavior problems characterizing more children at the urban sites. In addition, whereas externalizing behavior was the primary school problem exhibited by urban children, rural children displayed significantly higher rates of internalizing problems at school. The implications of these results are discussed for developmental models of behavior problems and for preventive interventions. PMID:19834584

Influence of parameter changes to stability behavior of rotors

NASA Technical Reports Server (NTRS)

Fritzen, C. P.; Nordmann, R.

1982-01-01

The occurrence of unstable vibrations in rotating machinery requires corrective measures for improvement of the stability behavior. A simple approximate method is represented to find out the influence of parameter changes to the stability behavior. The method is based on an expansion of the eigenvalues in terms of system parameters. Influence coefficients show the effect of structural modifications. The method first of all was applied to simple nonconservative rotor models. It was approved for an unsymmetric rotor of a test rig.

Simulation of inverse Compton scattering and its implications on the scattered linewidth

NASA Astrophysics Data System (ADS)

Ranjan, N.; Terzić, B.; Krafft, G. A.; Petrillo, V.; Drebot, I.; Serafini, L.

2018-03-01

Rising interest in inverse Compton sources has increased the need for efficient models that properly quantify the behavior of scattered radiation given a set of interaction parameters. The current state-of-the-art simulations rely on Monte Carlo-based methods, which, while properly expressing scattering behavior in high-probability regions of the produced spectra, may not correctly simulate such behavior in low-probability regions (e.g. tails of spectra). Moreover, sampling may take an inordinate amount of time for the desired accuracy to be achieved. In this paper, we present an analytic derivation of the expression describing the scattered radiation linewidth and propose a model to describe the effects of horizontal and vertical emittance on the properties of the scattered radiation. We also present an improved version of the code initially reported in Krafft et al. [Phys. Rev. Accel. Beams 19, 121302 (2016), 10.1103/PhysRevAccelBeams.19.121302], that can perform the same simulations as those present in cain and give accurate results in low-probability regions by integrating over the emissions of the electrons. Finally, we use these codes to carry out simulations that closely verify the behavior predicted by the analytically derived scaling law.

Simulation of inverse Compton scattering and its implications on the scattered linewidth

DOE PAGES

Ranjan, N.; Terzić, B.; Krafft, G. A.; ...

2018-03-06

Rising interest in inverse Compton sources has increased the need for efficient models that properly quantify the behavior of scattered radiation given a set of interaction parameters. The current state-of-the-art simulations rely on Monte Carlo-based methods, which, while properly expressing scattering behavior in high-probability regions of the produced spectra, may not correctly simulate such behavior in low-probability regions (e.g. tails of spectra). Moreover, sampling may take an inordinate amount of time for the desired accuracy to be achieved. Here in this article, we present an analytic derivation of the expression describing the scattered radiation linewidth and propose a model tomore » describe the effects of horizontal and vertical emittance on the properties of the scattered radiation. We also present an improved version of the code initially reported in Krafft et al. [Phys. Rev. Accel. Beams 19, 121302 (2016)], that can perform the same simulations as those present in cain and give accurate results in low-probability regions by integrating over the emissions of the electrons. Finally, we use these codes to carry out simulations that closely verify the behavior predicted by the analytically derived scaling law.« less

A Literature Review of Research Quality and Effective Practices in Alternative Education Settings

ERIC Educational Resources Information Center

Flower, Andrea; McDaniel, Sara C.; Jolivette, Kristine

2011-01-01

Effective behavioral practices for students with emotional/behavioral disorders (E/BD) are critical. Students with E/BD are often served in alternative education (AE) settings due to behavior that cannot be supported in a typical school setting or due to court adjudication based on delinquent activity. Like other settings for students with E/BD,…

Alternative Setting-Wide Positive Behavior Support

ERIC Educational Resources Information Center

Simonsen, Brandi; Jeffrey-Pearsall, Jennifer; Sugai, George; McCurdy, Barry

2011-01-01

School-wide positive behavior support (SWPBS) has an established evidence base in general education settings, and emerging evidence suggests that SWPBS may be effective in alternative settings (e.g., alternative, residential, or hospital schools; psychiatric hospitals). Given the intense educational and behavioral needs of students typically…

Addressing the Social, Academic, and Behavioral Needs of Students with Challenging Behavior in Inclusive and Alternative Settings. Highlights from the Forum on Comprehensive Programming for a Diverse Population of Children and Youth with Challenging Behavior: Addressing Social, Academic, and Behavioral Needs within Inclusive and Alternative Settings (Las Vegas, Nevada, February 9-10, 2001).

ERIC Educational Resources Information Center

Bullock, Lyndal M., Ed.; Gable, Robert A., Ed.

This document presents the texts of 11 major presentations and conference highlights from a February 2001 conference on the social, academic, and behavioral needs of students with challenging behavior in inclusive and alternative settings as required under the 1997 amendments to the Individuals with Disabilities Education Act. The presentations…

Simplifying the complexity of a coupled carbon turnover and pesticide degradation model

NASA Astrophysics Data System (ADS)

Marschmann, Gianna; Erhardt, André H.; Pagel, Holger; Kügler, Philipp; Streck, Thilo

2016-04-01

The mechanistic one-dimensional model PECCAD (PEsticide degradation Coupled to CArbon turnover in the Detritusphere; Pagel et al. 2014, Biogeochemistry 117, 185-204) has been developed as a tool to elucidate regulation mechanisms of pesticide degradation in soil. A feature of this model is that it integrates functional traits of microorganisms, identifiable by molecular tools, and physicochemical processes such as transport and sorption that control substrate availability. Predicting the behavior of microbially active interfaces demands a fundamental understanding of factors controlling their dynamics. Concepts from dynamical systems theory allow us to study general properties of the model such as its qualitative behavior, intrinsic timescales and dynamic stability: Using a Latin hypercube method we sampled the parameter space for physically realistic steady states of the PECCAD ODE system and set up a numerical continuation and bifurcation problem with the open-source toolbox MatCont in order to obtain a complete classification of the dynamical system's behaviour. Bifurcation analysis reveals an equilibrium state of the system entirely controlled by fungal kinetic parameters. The equilibrium is generally unstable in response to small perturbations except for a small band in parameter space where the pesticide pool is stable. Time scale separation is a phenomenon that occurs in almost every complex open physical system. Motivated by the notion of "initial-stage" and "late-stage" decomposers and the concept of r-, K- or L-selected microbial life strategies, we test the applicability of geometric singular perturbation theory to identify fast and slow time scales of PECCAD. Revealing a generic fast-slow structure would greatly simplify the analysis of complex models of organic matter turnover by reducing the number of unknowns and parameters and providing a systematic mathematical framework for studying their properties.

Advances in tribological testing of artificial joint biomaterials using multidirectional pin-on-disk testers

PubMed Central

Baykal, D.; Siskey, R.S.; Haider, H.; Saikko, V.; Ahlroos, T.; Kurtz, S.M.

2013-01-01

The introduction of numerous formulations of Ultra-high molecular weight polyethylene (UHMWPE), which is widely used as a bearing material in orthopedic implants, necessitated screening of bearing couples to identify promising iterations for expensive joint simulations. Pin-on-disk (POD) testers capable of multidirectional sliding can correctly rank formulations of UHMWPE with respect to their predictive in vivo wear behavior. However, there are still uncertainties regarding POD test parameters for facilitating clinically relevant wear mechanisms of UHMWPE. Studies on the development of POD testing were briefly summarized. We systematically reviewed wear rate data of UHMWPE generated by POD testers. To determine if POD testing was capable of correctly ranking bearings and if test parameters outlined in ASTM F732 enabled differentiation between wear behavior of various formulations, mean wear rates of non-irradiated, conventional (25–50 kGy) and highly crosslinked (≥90 kGy) UHMWPE were grouped and compared. The mean wear rates of non-irradiated, conventional and highly crosslinked UHMWPEs were 7.03, 5.39 and 0.67 mm3/MC. Based on studies that complied with the guidelines of ASTM F732, the mean wear rates of non-irradiated, conventional and highly crosslinked UHMWPEs were 0.32, 0.21 and 0.04 mm3/km, respectively. In both sets of results, the mean wear rate of highly crosslinked UHMPWE was smaller than both conventional and non-irradiated UHMWPEs (p<0.05). Thus, POD testers can compare highly crosslinked and conventional UHMWPEs despite different test parameters. Narrowing the allowable range for standardized test parameters could improve sensitivity of multi-axial testers in correctly ranking materials. PMID:23831149

A mixed-effects regression model for longitudinal multivariate ordinal data.

PubMed

Liu, Li C; Hedeker, Donald

2006-03-01

A mixed-effects item response theory model that allows for three-level multivariate ordinal outcomes and accommodates multiple random subject effects is proposed for analysis of multivariate ordinal outcomes in longitudinal studies. This model allows for the estimation of different item factor loadings (item discrimination parameters) for the multiple outcomes. The covariates in the model do not have to follow the proportional odds assumption and can be at any level. Assuming either a probit or logistic response function, maximum marginal likelihood estimation is proposed utilizing multidimensional Gauss-Hermite quadrature for integration of the random effects. An iterative Fisher scoring solution, which provides standard errors for all model parameters, is used. An analysis of a longitudinal substance use data set, where four items of substance use behavior (cigarette use, alcohol use, marijuana use, and getting drunk or high) are repeatedly measured over time, is used to illustrate application of the proposed model.

Energy transfer and motion synchronization between mechanical oscillators through microhydrodynamic coupling

NASA Astrophysics Data System (ADS)

Wan, Yu; Jin, Kai; Ahmad, Talha J.; Black, Michael J.; Xu, Zhiping

2017-03-01

Fluidic environment is encountered for mechanical components in many circumstances, which not only damps the oscillation but also modulates their dynamical behaviors through hydrodynamic interactions. In this study, we examine energy transfer and motion synchronization between two mechanical micro-oscillators by performing thermal lattice-Boltzmann simulations. The coefficient of inter-oscillator energy transfer is measured to quantify the strength of microhydrodynamic coupling, which depends on their distance and fluid properties such as density and viscosity. Synchronized motion of the oscillators is observed in the simulations for typical parameter sets in relevant applications, with the formation and loss of stable anti-phase synchronization controlled by the oscillating frequency, amplitude, and hydrodynamic coupling strength. The critical ranges of key parameters to assure efficient energy transfer or highly synchronized motion are predicted. These findings could be used to advise mechanical design of passive and active devices that operate in fluid.

Estimation of αL, velocity, Kd and confidence limits from tracer injection test data

USGS Publications Warehouse

Broermann, James; Bassett, R.L.; Weeks, Edwin P.; Borgstrom, Mark

1997-01-01

Bromide and boron were used as tracers during an injection experiment conducted at an artificial recharge facility near Stanton, Texas. The Ogallala aquifer at the Stanton site represents a heterogeneous alluvial environment and provides the opportunity to report scale dependent dispersivities at observation distances of 2 to 15 m in this setting. Values of longitudinal dispersivities are compared with other published values. Water samples were collected at selected depths both from piezometers and from fully screened observation wells at radii of 2, 5, 10 and 15 m. An exact analytical solution is used to simulate the concentration breakthrough curves and estimate longitudinal dispersivities and velocity parameters. Greater confidence can be placed on these data because the estimated parameters are error bounded using the bootstrap method. The non-conservative behavior of boron transport in clay rich sections of the aquifer were quantified with distribution coefficients by using bromide as a conservative reference tracer.

Estimation of αL, velocity, Kd, and confidence limits from tracer injection data

USGS Publications Warehouse

Broermann, James; Bassett, R.L.; Weeks, Edwin P.; Borgstrom, Mark

1997-01-01

Bromide and boron were used as tracers during an injection experiment conducted at an artificial recharge facility near Stanton, Texas. The Ogallala aquifer at the Stanton site represents a heterogeneous alluvial environment and provides the opportunity to report scale dependent dispersivities at observation distances of 2 to 15 m in this setting. Values of longitudinal dispersivities are compared with other published values. Water samples were collected at selected depths both from piezometers and from fully screened observation wells at radii of 2, 5, 10 and 15 m. An exact analytical solution is used to simulate the concentration breakthrough curves and estimate longitudinal dispersivities and velocity parameters. Greater confidence can be placed on these data because the estimated parameters are error bounded using the bootstrap method. The non-conservative behavior of boron transport in clay rich sections of the aquifer were quantified with distribution coefficients by using bromide as a conservative reference tracer.

Cattaneo-Christov double-diffusion theory for three-dimensional flow of viscoelastic nanofluid with the effect of heat generation/absorption

NASA Astrophysics Data System (ADS)

Hayat, Tasawar; Qayyum, Sajid; Shehzad, Sabir Ali; Alsaedi, Ahmed

2018-03-01

The present research article focuses on three-dimensional flow of viscoelastic(second grade) nanofluid in the presence of Cattaneo-Christov double-diffusion theory. Flow caused is due to stretching sheet. Characteristics of heat transfer are interpreted by considering the heat generation/absorption. Nanofluid theory comprises of Brownian motion and thermophoresis. Cattaneo-Christov double-diffusion theory is introduced in the energy and concentration expressions. Such diffusions are developed as a part of formulating the thermal and solutal relaxation times framework. Suitable variables are implemented for the conversion of partial differential systems into a sets of ordinary differential equations. The transformed expressions have been explored through homotopic algorithm. Behavior of sundry variables on the velocities, temperature and concentration are scrutinized graphically. Numerical values of skin friction coefficients are also calculated and examined. Here thermal field enhances for heat generation parameter while reverse situation is noticed for heat absorption parameter.

Development and application of a particle-particle particle-mesh Ewald method for dispersion interactions.

PubMed

Isele-Holder, Rolf E; Mitchell, Wayne; Ismail, Ahmed E

2012-11-07

For inhomogeneous systems with interfaces, the inclusion of long-range dispersion interactions is necessary to achieve consistency between molecular simulation calculations and experimental results. For accurate and efficient incorporation of these contributions, we have implemented a particle-particle particle-mesh Ewald solver for dispersion (r(-6)) interactions into the LAMMPS molecular dynamics package. We demonstrate that the solver's O(N log N) scaling behavior allows its application to large-scale simulations. We carefully determine a set of parameters for the solver that provides accurate results and efficient computation. We perform a series of simulations with Lennard-Jones particles, SPC/E water, and hexane to show that with our choice of parameters the dependence of physical results on the chosen cutoff radius is removed. Physical results and computation time of these simulations are compared to results obtained using either a plain cutoff or a traditional Ewald sum for dispersion.

Foraging for brain stimulation: toward a neurobiology of computation.

PubMed

Gallistel, C R

1994-01-01

The self-stimulating rat performs foraging tasks mediated by simple computations that use interreward intervals and subjective reward magnitudes to determine stay durations. This is a simplified preparation in which to study the neurobiology of the elementary computational operations that make cognition possible, because the neural signal specifying the value of a computationally relevant variable is produced by direct electrical stimulation of a neural pathway. Newly developed measurement methods yield functions relating the subjective reward magnitude to the parameters of the neural signal. These measurements also show that the decision process that governs foraging behavior divides the subjective reward magnitude by the most recent interreward interval to determine the preferability of an option (a foraging patch). The decision process sets the parameters that determine stay durations (durations of visits to foraging patches) so that the ratios of the stay durations match the ratios of the preferabilities.

Qualitative and temporal reasoning in engine behavior analysis

NASA Technical Reports Server (NTRS)

Dietz, W. E.; Stamps, M. E.; Ali, M.

1987-01-01

Numerical simulation models, engine experts, and experimental data are used to generate qualitative and temporal representations of abnormal engine behavior. Engine parameters monitored during operation are used to generate qualitative and temporal representations of actual engine behavior. Similarities between the representations of failure scenarios and the actual engine behavior are used to diagnose fault conditions which have already occurred, or are about to occur; to increase the surveillance by the monitoring system of relevant engine parameters; and to predict likely future engine behavior.

Regional propagation characteristics and source parameters of earthquakes in northeastern North America

USGS Publications Warehouse

Boatwright, John

1994-01-01

The vertical components of the S wave trains recorded on the Eastern Canadian Telemetered Network (ECTN) from 1980 through 1990 have been spectrally analyzed for source, site, and propagation characteristics. The data set comprises some 1033 recordings of 97 earthquakes whose magnitudes range from M ≈ 3 to 6. The epicentral distances range from 15 to 1000 km, with most of the data set recorded at distances from 200 to 800 km. The recorded S wave trains contain the phases S, SmS, Sn, and Lg and are sampled using windows that increase with distance; the acceleration spectra were analyzed from 1.0 to 10 Hz. To separate the source, site, and propagation characteristics, an inversion for the earthquake corner frequencies, low-frequency levels, and average attenuation parameters is alternated with a regression of residuals onto the set of stations and a grid of 14 distances ranging from 25 to 1000 km. The iteration between these two parts of the inversion converges in about 60 steps. The average attenuation parameters obtained from the inversion were Q = 1997 ± 10 and γ = 0.998 ± 0.003. The most pronounced variation from this average attenuation is a marked deamplification of more than a factor of 2 at 63 km and 2 Hz, which shallows with increasing frequency and increasing distance out to 200 km. The site-response spectra obtained for the ECTN stations are generally flat. The source spectral shape assumed in this inversion provides an adequate spectral model for the smaller events (Mo < 3 × 1021 dyne-cm) in the data set, whose Brune stress drops range from 5 to 150 bars. For the five events in the data set with Mo ≧ 1023 dyne-cm, however, the source spectra obtained by regressing the residuals suggest that an ω2 spectrum is an inadequate model for the spectral shape. In particular, the corner frequencies for most of these large events appear to be split, so that the spectra exhibit an intermediate behavior (where |ü(ω)| is roughly proportional to ω).

Representing Micro-Macro Linkages by Actor-Based Dynamic Network Models

PubMed Central

Snijders, Tom A.B.; Steglich, Christian E.G.

2014-01-01

Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of generalized linear statistical models they aim to be realistic detailed representations of network dynamics in empirical data sets. Statistical parallels to micro-macro considerations can be found in the estimation of parameters determining local actor behavior from empirical data, and the assessment of goodness of fit from the correspondence with network-level descriptives. This article studies several network-level consequences of dynamic actor-based models applied to represent cross-sectional network data. Two examples illustrate how network-level characteristics can be obtained as emergent features implied by micro-specifications of actor-based models. PMID:25960578

Statistical distribution of mechanical properties for three graphite-epoxy material systems

NASA Technical Reports Server (NTRS)

Reese, C.; Sorem, J., Jr.

1981-01-01

Graphite-epoxy composites are playing an increasing role as viable alternative materials in structural applications necessitating thorough investigation into the predictability and reproducibility of their material strength properties. This investigation was concerned with tension, compression, and short beam shear coupon testing of large samples from three different material suppliers to determine their statistical strength behavior. Statistical results indicate that a two Parameter Weibull distribution model provides better overall characterization of material behavior for the graphite-epoxy systems tested than does the standard Normal distribution model that is employed for most design work. While either a Weibull or Normal distribution model provides adequate predictions for average strength values, the Weibull model provides better characterization in the lower tail region where the predictions are of maximum design interest. The two sets of the same material were found to have essentially the same material properties, and indicate that repeatability can be achieved.

Spatiotemporal property and predictability of large-scale human mobility

NASA Astrophysics Data System (ADS)

Zhang, Hai-Tao; Zhu, Tao; Fu, Dongfei; Xu, Bowen; Han, Xiao-Pu; Chen, Duxin

2018-04-01

Spatiotemporal characteristics of human mobility emerging from complexity on individual scale have been extensively studied due to the application potential on human behavior prediction and recommendation, and control of epidemic spreading. We collect and investigate a comprehensive data set of human activities on large geographical scales, including both websites browse and mobile towers visit. Numerical results show that the degree of activity decays as a power law, indicating that human behaviors are reminiscent of scale-free random walks known as Lévy flight. More significantly, this study suggests that human activities on large geographical scales have specific non-Markovian characteristics, such as a two-segment power-law distribution of dwelling time and a high possibility for prediction. Furthermore, a scale-free featured mobility model with two essential ingredients, i.e., preferential return and exploration, and a Gaussian distribution assumption on the exploration tendency parameter is proposed, which outperforms existing human mobility models under scenarios of large geographical scales.

A hybrid model for opinion formation

NASA Astrophysics Data System (ADS)

Borra, Domenica; Lorenzi, Tommaso

2013-06-01

This paper presents a hybrid model for opinion formation in a large group of agents exposed to the persuasive action of a small number of strong opinion leaders. The model is defined by coupling a finite difference equation for the dynamics of leaders opinion with a continuous integro-differential equation for the dynamics of the others. Such a definition stems from the idea that the leaders are few and tend to retain original opinions, so that their dynamics occur on a longer time scale with respect to the one of the other agents. A general well-posedness result is established for the initial value problem linked to the model. The asymptotic behavior in time of the related solution is characterized for some general parameter settings, which mimic distinct social scenarios, where different emerging behaviors can be observed. Analytical results are illustrated and extended through numerical simulations.

Correspondence behavior of classical and quantum dissipative directed transport via thermal noise.

PubMed

Carlo, Gabriel G; Ermann, Leonardo; Rivas, Alejandro M F; Spina, María E

2016-04-01

We systematically study several classical-quantum correspondence properties of the dissipative modified kicked rotator, a paradigmatic ratchet model. We explore the behavior of the asymptotic currents for finite ℏ_{eff} values in a wide range of the parameter space. We find that the correspondence between the classical currents with thermal noise providing fluctuations of size ℏ_{eff} and the quantum ones without it is very good in general with the exception of specific regions. We systematically consider the spectra of the corresponding classical Perron-Frobenius operators and quantum superoperators. By means of an average distance between the classical and quantum sets of eigenvalues we find that the correspondence is unexpectedly quite uniform. This apparent contradiction is solved with the help of the Weyl-Wigner distributions of the equilibrium eigenvectors, which reveal the key role of quantum effects by showing surviving coherences in the asymptotic states.

Modeling turbulent energy behavior and sudden viscous dissipation in compressing plasma turbulence

DOE PAGES

Davidovits, Seth; Fisch, Nathaniel J.

2017-12-21

Here, we present a simple model for the turbulent kinetic energy behavior of subsonic plasma turbulence undergoing isotropic three-dimensional compression, which may exist in various inertial confinement fusion experiments or astrophysical settings. The plasma viscosity depends on both the temperature and the ionization state, for which many possible scalings with compression are possible. For example, in an adiabatic compression the temperature scales as 1/L 2, with L the linear compression ratio, but if thermal energy loss mechanisms are accounted for, the temperature scaling may be weaker. As such, the viscosity has a wide range of net dependencies on the compression.more » The model presented here, with no parameter changes, agrees well with numerical simulations for a range of these dependencies. This model permits the prediction of the partition of injected energy between thermal and turbulent energy in a compressing plasma.« less

Modeling turbulent energy behavior and sudden viscous dissipation in compressing plasma turbulence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Davidovits, Seth; Fisch, Nathaniel J.

Here, we present a simple model for the turbulent kinetic energy behavior of subsonic plasma turbulence undergoing isotropic three-dimensional compression, which may exist in various inertial confinement fusion experiments or astrophysical settings. The plasma viscosity depends on both the temperature and the ionization state, for which many possible scalings with compression are possible. For example, in an adiabatic compression the temperature scales as 1/L 2, with L the linear compression ratio, but if thermal energy loss mechanisms are accounted for, the temperature scaling may be weaker. As such, the viscosity has a wide range of net dependencies on the compression.more » The model presented here, with no parameter changes, agrees well with numerical simulations for a range of these dependencies. This model permits the prediction of the partition of injected energy between thermal and turbulent energy in a compressing plasma.« less

Goal setting in diabetes self-management: taking the baby steps to success.

PubMed

DeWalt, Darren A; Davis, Terry C; Wallace, Andrea S; Seligman, Hilary K; Bryant-Shilliday, Betsy; Arnold, Connie L; Freburger, Janet; Schillinger, Dean

2009-11-01

To evaluate the usefulness of a diabetes self-management guide and a brief counseling intervention in helping patients set and achieve their behavioral goals. We conducted a quasi-experimental study using a one group pretest posttest design to assess the effectiveness of a goal setting intervention along with a self-management guide. English- and Spanish-speaking patients with diabetes had one in-person session and two telephone follow-up calls with a non-clinical provider over a 12-16-week period. At each call and at the end of the study, we assessed success in achieving behavioral goals and problem solving toward those goals. Satisfaction with the self-management guide was assessed at the end of the study. We enrolled 250 patients across three sites and 229 patients completed the study. Most patients chose to set goals in diet and exercise domains. 93% of patients achieved at least one behavioral goal during the study and 73% achieved at least two behavioral goals. Many patients exhibited problem solving behavior to achieve their goals. We found no significant differences in reported achievement of behavior goals by literacy or language. Patients were very satisfied with the guide. A brief goal setting intervention along with a diabetes self-management guide helped patients set and achieve healthy behavioral goals. Non-clinical providers can successfully help a diverse range of patients with diabetes set and achieve behavioral goals.

Setting priorities in health care organizations: criteria, processes, and parameters of success.

PubMed

Gibson, Jennifer L; Martin, Douglas K; Singer, Peter A

2004-09-08

Hospitals and regional health authorities must set priorities in the face of resource constraints. Decision-makers seek practical ways to set priorities fairly in strategic planning, but find limited guidance from the literature. Very little has been reported from the perspective of Board members and senior managers about what criteria, processes and parameters of success they would use to set priorities fairly. We facilitated workshops for board members and senior leadership at three health care organizations to assist them in developing a strategy for fair priority setting. Workshop participants identified 8 priority setting criteria, 10 key priority setting process elements, and 6 parameters of success that they would use to set priorities in their organizations. Decision-makers in other organizations can draw lessons from these findings to enhance the fairness of their priority setting decision-making. Lessons learned in three workshops fill an important gap in the literature about what criteria, processes, and parameters of success Board members and senior managers would use to set priorities fairly.

Optimal experimental design for parameter estimation of a cell signaling model.

PubMed

Bandara, Samuel; Schlöder, Johannes P; Eils, Roland; Bock, Hans Georg; Meyer, Tobias

2009-11-01

Differential equation models that describe the dynamic changes of biochemical signaling states are important tools to understand cellular behavior. An essential task in building such representations is to infer the affinities, rate constants, and other parameters of a model from actual measurement data. However, intuitive measurement protocols often fail to generate data that restrict the range of possible parameter values. Here we utilized a numerical method to iteratively design optimal live-cell fluorescence microscopy experiments in order to reveal pharmacological and kinetic parameters of a phosphatidylinositol 3,4,5-trisphosphate (PIP(3)) second messenger signaling process that is deregulated in many tumors. The experimental approach included the activation of endogenous phosphoinositide 3-kinase (PI3K) by chemically induced recruitment of a regulatory peptide, reversible inhibition of PI3K using a kinase inhibitor, and monitoring of the PI3K-mediated production of PIP(3) lipids using the pleckstrin homology (PH) domain of Akt. We found that an intuitively planned and established experimental protocol did not yield data from which relevant parameters could be inferred. Starting from a set of poorly defined model parameters derived from the intuitively planned experiment, we calculated concentration-time profiles for both the inducing and the inhibitory compound that would minimize the predicted uncertainty of parameter estimates. Two cycles of optimization and experimentation were sufficient to narrowly confine the model parameters, with the mean variance of estimates dropping more than sixty-fold. Thus, optimal experimental design proved to be a powerful strategy to minimize the number of experiments needed to infer biological parameters from a cell signaling assay.

Exploratory behavior in mice selectively bred for developmental differences in aggressive behavior.

PubMed

Hood, Kathryn E; Quigley, Karen S

2008-01-01

The development and expression of exploratory behavior was assessed in the Cairns lines of Institute for Cancer Research (ICR) mice that were selectively bred for differences in aggressive behavior, with a high-aggressive 900 line, low-aggressive 100 line, and control 500 line. Four paradigms were employed. Developmental changes were evident in the complex novel arena, with older males faster to contact a novel object, and ambulating more than young males. Within the control 500 line, older males showed longer latency to emerge from the home cage, and shorter latency to contact novel objects. In the 900 line, younger males showed this same pattern. R. B. Cairns proposed that line differences in aggressive behavior arise through alterations in developmental timing [Cairns et al. [1983] Life-span developmental psychology (Vol. 5). New York: Academic Press; Gariépy et al. [2001] Animal Behaviour 61: 933-947]. The early appearance of mature patterns of exploratory behavior in 900 line males supports this interpretation. The 900 line males also appear to be behaviorally inhibited in novel settings such as the light-dark box and the neohypophagia paradigm, compared to the 500 and 100 lines (Experiments 1, 2, and 4). Moreover, in the most complex apparatus, the novel arena, 900 line males were slowest to exit the home cage, and fastest to contact a novel object. The apparent contrast in these parameters of exploratory behavior is discussed in relation to T. C. Schneirla's [1965 Advances in the study of behavior (Vol. 1). New York: PN Academic] approach-withdrawal theory. (c) 2007 Wiley Periodicals, Inc.

Detecting discordance enrichment among a series of two-sample genome-wide expression data sets.

PubMed

Lai, Yinglei; Zhang, Fanni; Nayak, Tapan K; Modarres, Reza; Lee, Norman H; McCaffrey, Timothy A

2017-01-25

With the current microarray and RNA-seq technologies, two-sample genome-wide expression data have been widely collected in biological and medical studies. The related differential expression analysis and gene set enrichment analysis have been frequently conducted. Integrative analysis can be conducted when multiple data sets are available. In practice, discordant molecular behaviors among a series of data sets can be of biological and clinical interest. In this study, a statistical method is proposed for detecting discordance gene set enrichment. Our method is based on a two-level multivariate normal mixture model. It is statistically efficient with linearly increased parameter space when the number of data sets is increased. The model-based probability of discordance enrichment can be calculated for gene set detection. We apply our method to a microarray expression data set collected from forty-five matched tumor/non-tumor pairs of tissues for studying pancreatic cancer. We divided the data set into a series of non-overlapping subsets according to the tumor/non-tumor paired expression ratio of gene PNLIP (pancreatic lipase, recently shown it association with pancreatic cancer). The log-ratio ranges from a negative value (e.g. more expressed in non-tumor tissue) to a positive value (e.g. more expressed in tumor tissue). Our purpose is to understand whether any gene sets are enriched in discordant behaviors among these subsets (when the log-ratio is increased from negative to positive). We focus on KEGG pathways. The detected pathways will be useful for our further understanding of the role of gene PNLIP in pancreatic cancer research. Among the top list of detected pathways, the neuroactive ligand receptor interaction and olfactory transduction pathways are the most significant two. Then, we consider gene TP53 that is well-known for its role as tumor suppressor in cancer research. The log-ratio also ranges from a negative value (e.g. more expressed in non-tumor tissue) to a positive value (e.g. more expressed in tumor tissue). We divided the microarray data set again according to the expression ratio of gene TP53. After the discordance enrichment analysis, we observed overall similar results and the above two pathways are still the most significant detections. More interestingly, only these two pathways have been identified for their association with pancreatic cancer in a pathway analysis of genome-wide association study (GWAS) data. This study illustrates that some disease-related pathways can be enriched in discordant molecular behaviors when an important disease-related gene changes its expression. Our proposed statistical method is useful in the detection of these pathways. Furthermore, our method can also be applied to genome-wide expression data collected by the recent RNA-seq technology.

Development of an Agent-Based Model to Investigate the Impact of HIV Self-Testing Programs on Men Who Have Sex With Men in Atlanta and Seattle.

PubMed

Luo, Wei; Katz, David A; Hamilton, Deven T; McKenney, Jennie; Jenness, Samuel M; Goodreau, Steven M; Stekler, Joanne D; Rosenberg, Eli S; Sullivan, Patrick S; Cassels, Susan

2018-06-29

In the United States HIV epidemic, men who have sex with men (MSM) remain the most profoundly affected group. Prevention science is increasingly being organized around HIV testing as a launch point into an HIV prevention continuum for MSM who are not living with HIV and into an HIV care continuum for MSM who are living with HIV. An increasing HIV testing frequency among MSM might decrease future HIV infections by linking men who are living with HIV to antiretroviral care, resulting in viral suppression. Distributing HIV self-test (HIVST) kits is a strategy aimed at increasing HIV testing. Our previous modeling work suggests that the impact of HIV self-tests on transmission dynamics will depend not only on the frequency of tests and testers' behaviors but also on the epidemiological and testing characteristics of the population. The objective of our study was to develop an agent-based model to inform public health strategies for promoting safe and effective HIV self-tests to decrease the HIV incidence among MSM in Atlanta, GA, and Seattle, WA, cities representing profoundly different epidemiological settings. We adapted and extended a network- and agent-based stochastic simulation model of HIV transmission dynamics that was developed and parameterized to investigate racial disparities in HIV prevalence among MSM in Atlanta. The extension comprised several activities: adding a new set of model parameters for Seattle MSM; adding new parameters for tester types (ie, regular, risk-based, opportunistic-only, or never testers); adding parameters for simplified pre-exposure prophylaxis uptake following negative results for HIV tests; and developing a conceptual framework for the ways in which the provision of HIV self-tests might change testing behaviors. We derived city-specific parameters from previous cohort and cross-sectional studies on MSM in Atlanta and Seattle. Each simulated population comprised 10,000 MSM and targeted HIV prevalences are equivalent to 28% and 11% in Atlanta and Seattle, respectively. Previous studies provided sufficient data to estimate the model parameters representing nuanced HIV testing patterns and HIV self-test distribution. We calibrated the models to simulate the epidemics representing Atlanta and Seattle, including matching the expected stable HIV prevalence. The revised model facilitated the estimation of changes in 10-year HIV incidence based on counterfactual scenarios of HIV self-test distribution strategies and their impact on testing behaviors. We demonstrated that the extension of an existing agent-based HIV transmission model was sufficient to simulate the HIV epidemics among MSM in Atlanta and Seattle, to accommodate a more nuanced depiction of HIV testing behaviors than previous models, and to serve as a platform to investigate how HIV self-tests might impact testing and HIV transmission patterns among MSM in Atlanta and Seattle. In our future studies, we will use the model to test how different HIV self-test distribution strategies might affect HIV incidence among MSM. ©Wei Luo, David A Katz, Deven T Hamilton, Jennie McKenney, Samuel M Jenness, Steven M Goodreau, Joanne D Stekler, Eli S Rosenberg, Patrick S Sullivan, Susan Cassels. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 29.06.2018.

VizieR Online Data Catalog: A catalog of exoplanet physical parameters (Foreman-Mackey+, 2014)

NASA Astrophysics Data System (ADS)

Foreman-Mackey, D.; Hogg, D. W.; Morton, T. D.

2017-05-01

The first ingredient for any probabilistic inference is a likelihood function, a description of the probability of observing a specific data set given a set of model parameters. In this particular project, the data set is a catalog of exoplanet measurements and the model parameters are the values that set the shape and normalization of the occurrence rate density. (2 data files).

Exploring the nonlinear cloud and rain equation

NASA Astrophysics Data System (ADS)

Koren, Ilan; Tziperman, Eli; Feingold, Graham

2017-01-01

Marine stratocumulus cloud decks are regarded as the reflectors of the climate system, returning back to space a significant part of the income solar radiation, thus cooling the atmosphere. Such clouds can exist in two stable modes, open and closed cells, for a wide range of environmental conditions. This emergent behavior of the system, and its sensitivity to aerosol and environmental properties, is captured by a set of nonlinear equations. Here, using linear stability analysis, we express the transition from steady to a limit-cycle state analytically, showing how it depends on the model parameters. We show that the control of the droplet concentration (N), the environmental carrying-capacity (H0), and the cloud recovery parameter (τ) can be linked by a single nondimensional parameter (μ=√{N }/(ατH0) ) , suggesting that for deeper clouds the transition from open (oscillating) to closed (stable fixed point) cells will occur for higher droplet concentration (i.e., higher aerosol loading). The analytical calculations of the possible states, and how they are affected by changes in aerosol and the environmental variables, provide an enhanced understanding of the complex interactions of clouds and rain.

The timbre model

NASA Astrophysics Data System (ADS)

Jensen, Kristoffer

2002-11-01

A timbre model is proposed for use in multiple applications. This model, which encompasses all voiced isolated musical instruments, has an intuitive parameter set, fixed size, and separates the sounds in dimensions akin to the timbre dimensions as proposed in timbre research. The analysis of the model parameters is fully documented, and it proposes, in particular, a method for the estimation of the difficult decay/release split-point. The main parameters of the model are the spectral envelope, the attack/release durations and relative amplitudes, and the inharmonicity and the shimmer and jitter (which provide both for the slow random variations of the frequencies and amplitudes, and also for additive noises). Some of the applications include synthesis, where a real-time application is being developed with an intuitive gui, classification, and search of sounds based on the content of the sounds, and a further understanding of acoustic musical instrument behavior. In order to present the background of the model, this presentation will start with sinusoidal A/S, some timbre perception research, then present the timbre model, show the validity for individual music instrument sounds, and finally introduce some expression additions to the model.

Expanded experimental parameter space of semiflexible polymer assemblies through programmable nanomaterials

NASA Astrophysics Data System (ADS)

Smith, David; Schuldt, Carsten; Lorenz, Jessica; Tschirner, Teresa; Moebius-Winkler, Maximilian; Kaes, Josef; Glaser, Martin; Haendler, Tina; Schnauss, Joerg

2015-03-01

Biologically evolved materials are often used as inspiration in the development of new materials as well as examinations into the underlying physical principles governing their behavior. For instance, the biopolymer constituents of the highly dynamic cellular cytoskeleton such as actin have inspired a deep understanding of soft polymer-based materials. However, the molecular toolbox provided by biological systems has been evolutionarily optimized to carry out the necessary functions of cells, and the inability modify basic properties such as biopolymer stiffness hinders a meticulous examination of parameter space. Using actin as inspiration, we circumvent these limitations using model systems assembled from programmable materials such as DNA. Nanorods with comparable, but controllable dimensions and mechanical properties as actin can be constructed from small sets of specially designed DNA strands. In entangled gels, these allow us to systematically determine the dependence of network mechanical properties on parameters such as persistence length and crosslink strength. At higher concentrations in the presence of local attractive forces, we see a transition to highly-ordered bundled and ``aster'' phases similar to those previously characterized in systems of actin or microtubules.

The effect of kinematic parameters on inelastic scattering of glyoxal.

PubMed

Duca, Mariana D

2004-10-08

The effect of kinematic parameters (relative velocity v(rel), relative momentum p(rel), and relative energy E(rel)) on the rotational and rovibrational inelastic scatterings of 0(0)K(0)S(1) trans-glyoxal has been investigated by colliding glyoxal seeded in He or Ar with target gases D2, He, or Ne at different scattering angles in crossed supersonic beams. The inelastic spectra for target gases He and D2 acquired with two different sets of kinematic parameters revealed no significant differences. This result shows that kinematic factors have the major influence in the inelastic scattering channel competition whereas the intermolecular potential energy surface plays only a secondary role. The well-defined exponential dependence of relative cross sections on exchanged angular momentum identifies angular momentum as the dominant kinematic factor in collision-induced rotationally and rovibrationally inelastic scatterings. This is supported by the behavior of the relative inelastic cross sections data in a "slope-p(rel)" representation. In this form, the data show a trend nearly independent of the target gas identity. Representations involving E(rel) and v(rel) show trends specific to the target gas.

Voronoi cell patterns: Theoretical model and applications

NASA Astrophysics Data System (ADS)

González, Diego Luis; Einstein, T. L.

2011-11-01

We use a simple fragmentation model to describe the statistical behavior of the Voronoi cell patterns generated by a homogeneous and isotropic set of points in 1D and in 2D. In particular, we are interested in the distribution of sizes of these Voronoi cells. Our model is completely defined by two probability distributions in 1D and again in 2D, the probability to add a new point inside an existing cell and the probability that this new point is at a particular position relative to the preexisting point inside this cell. In 1D the first distribution depends on a single parameter while the second distribution is defined through a fragmentation kernel; in 2D both distributions depend on a single parameter. The fragmentation kernel and the control parameters are closely related to the physical properties of the specific system under study. We use our model to describe the Voronoi cell patterns of several systems. Specifically, we study the island nucleation with irreversible attachment, the 1D car-parking problem, the formation of second-level administrative divisions, and the pattern formed by the Paris Métro stations.

Voronoi Cell Patterns: theoretical model and application to submonolayer growth

NASA Astrophysics Data System (ADS)

González, Diego Luis; Einstein, T. L.

2012-02-01

We use a simple fragmentation model to describe the statistical behavior of the Voronoi cell patterns generated by a homogeneous and isotropic set of points in 1D and in 2D. In particular, we are interested in the distribution of sizes of these Voronoi cells. Our model is completely defined by two probability distributions in 1D and again in 2D, the probability to add a new point inside an existing cell and the probability that this new point is at a particular position relative to the preexisting point inside this cell. In 1D the first distribution depends on a single parameter while the second distribution is defined through a fragmentation kernel; in 2D both distributions depend on a single parameter. The fragmentation kernel and the control parameters are closely related to the physical properties of the specific system under study. We apply our model to describe the Voronoi cell patterns of island nucleation for critical island sizes i=0,1,2,3. Experimental results for the Voronoi cells of InAs/GaAs quantum dots are also described by our model.

The electronegativity equalization method and the split charge equilibration applied to organic systems: parametrization, validation, and comparison.

PubMed

Verstraelen, Toon; Van Speybroeck, Veronique; Waroquier, Michel

2009-07-28

An extensive benchmark of the electronegativity equalization method (EEM) and the split charge equilibration (SQE) model on a very diverse set of organic molecules is presented. These models efficiently compute atomic partial charges and are used in the development of polarizable force fields. The predicted partial charges that depend on empirical parameters are calibrated to reproduce results from quantum mechanical calculations. Recently, SQE is presented as an extension of the EEM to obtain the correct size dependence of the molecular polarizability. In this work, 12 parametrization protocols are applied to each model and the optimal parameters are benchmarked systematically. The training data for the empirical parameters comprise of MP2/Aug-CC-pVDZ calculations on 500 organic molecules containing the elements H, C, N, O, F, S, Cl, and Br. These molecules have been selected by an ingenious and autonomous protocol from an initial set of almost 500,000 small organic molecules. It is clear that the SQE model outperforms the EEM in all benchmark assessments. When using Hirshfeld-I charges for the calibration, the SQE model optimally reproduces the molecular electrostatic potential from the ab initio calculations. Applications on chain molecules, i.e., alkanes, alkenes, and alpha alanine helices, confirm that the EEM gives rise to a divergent behavior for the polarizability, while the SQE model shows the correct trends. We conclude that the SQE model is an essential component of a polarizable force field, showing several advantages over the original EEM.

Predicting hydration Gibbs energies of alkyl-aromatics using molecular simulation: a comparison of current force fields and the development of a new parameter set for accurate solvation data.

PubMed

Garrido, Nuno M; Jorge, Miguel; Queimada, António J; Gomes, José R B; Economou, Ioannis G; Macedo, Eugénia A

2011-10-14

The Gibbs energy of hydration is an important quantity to understand the molecular behavior in aqueous systems at constant temperature and pressure. In this work we review the performance of some popular force fields, namely TraPPE, OPLS-AA and Gromos, in reproducing the experimental Gibbs energies of hydration of several alkyl-aromatic compounds--benzene, mono-, di- and tri-substituted alkylbenzenes--using molecular simulation techniques. In the second part of the paper, we report a new model that is able to improve such hydration energy predictions, based on Lennard Jones parameters from the recent TraPPE-EH force field and atomic partial charges obtained from natural population analysis of density functional theory calculations. We apply a scaling factor determined by fitting the experimental hydration energy of only two solutes, and then present a simple rule to generate atomic partial charges for different substituted alkyl-aromatics. This rule has the added advantages of eliminating the unnecessary assumption of fixed charge on every substituted carbon atom and providing a simple guideline for extrapolating the charge assignment to any multi-substituted alkyl-aromatic molecule. The point charges derived here yield excellent predictions of experimental Gibbs energies of hydration, with an overall absolute average deviation of less than 0.6 kJ mol(-1). This new parameter set can also give good predictive performance for other thermodynamic properties and liquid structural information.

Hysteresis and compensation behaviors of spin-3/2 cylindrical Ising nanotube system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kocakaplan, Yusuf; Keskin, Mustafa, E-mail: keskin@erciyes.edu.tr

2014-09-07

The hysteresis and compensation behaviors of the spin-3/2 cylindrical Ising nanotube system are studied within the framework of the effective-field theory with correlations. The effects of the Hamiltonian parameters are investigated on the magnetic and thermodynamic quantities, such as the total magnetization, hysteresis curves, and compensation behaviors of the system. Depending on the Hamiltonian parameters, some characteristic hysteresis behaviors are found, such as the existence of double and triple hysteresis loops. According to Néel classification nomenclature, the system displays Q-, R-, P-, N-, M-, and S- types of compensation behaviors for the appropriate values of the system parameters. We alsomore » compare our results with some recently published theoretical and experimental works and find a qualitatively good agreement.« less

Advanced interactive display formats for terminal area traffic control

NASA Technical Reports Server (NTRS)

Grunwald, Arthur J.

1996-01-01

This report describes the basic design considerations for perspective air traffic control displays. A software framework has been developed for manual viewing parameter setting (MVPS) in preparation for continued, ongoing developments on automated viewing parameter setting (AVPS) schemes. Two distinct modes of MVPS operations are considered, both of which utilize manipulation pointers imbedded in the three-dimensional scene: (1) direct manipulation of the viewing parameters -- in this mode the manipulation pointers act like the control-input device, through which the viewing parameter changes are made. Part of the parameters are rate controlled, and part of them position controlled. This mode is intended for making fast, iterative small changes in the parameters. (2) Indirect manipulation of the viewing parameters -- this mode is intended primarily for introducing large, predetermined changes in the parameters. Requests for changes in viewing parameter setting are entered manually by the operator by moving viewing parameter manipulation pointers on the screen. The motion of these pointers, which are an integral part of the 3-D scene, is limited to the boundaries of the screen. This arrangement has been chosen in order to preserve the correspondence between the spatial lay-outs of the new and the old viewing parameter setting, a feature which contributes to preventing spatial disorientation of the operator. For all viewing operations, e.g. rotation, translation and ranging, the actual change is executed automatically by the system, through gradual transitions with an exponentially damped, sinusoidal velocity profile, in this work referred to as 'slewing' motions. The slewing functions, which eliminate discontinuities in the viewing parameter changes, are designed primarily for enhancing the operator's impression that he, or she, is dealing with an actually existing physical system, rather than an abstract computer-generated scene. The proposed, continued research efforts will deal with the development of automated viewing parameter setting schemes. These schemes employ an optimization strategy, aimed at identifying the best possible vantage point, from which the air traffic control scene can be viewed for a given traffic situation. They determine whether a change in viewing parameter setting is required and determine the dynamic path along which the change to the new viewing parameter setting should take place.

Construction of a Computerized Adaptive Testing Version of the Quebec Adaptive Behavior Scale.

ERIC Educational Resources Information Center

Tasse, Marc J.; And Others

Multilog (Thissen, 1991) was used to estimate parameters of 225 items from the Quebec Adaptive Behavior Scale (QABS). A database containing actual data from 2,439 subjects was used for the parameterization procedures. The two-parameter-logistic model was used in estimating item parameters and in the testing strategy. MicroCAT (Assessment Systems…

Mixing behavior of chromophoric dissolved organic matter in the Pearl River Estuary in spring

NASA Astrophysics Data System (ADS)

Lei, Xia; Pan, Jiayi; Devlin, Adam T.

2018-02-01

Mixing behavior of chromophoric dissolved organic matter (CDOM) in the Pearl River Estuary (PRE) and relevant hydrodynamic parameters such as horizontal transport and vertical mixing are identified and discussed based on a set of sampling data obtained during a cruise in May 2014. Using a theoretical conservative mixing model, the surface CDOM in the PRE in spring is classified into two groups by the CDOM absorption-spectral slope relationship (a(300) vs S(275-295)): First, terrigenous CDOM under a non-conservative mixing condition, and removal processes such as photobleaching are suggested to happen; second, marine CDOM behaves conservatively during mixing. The mixing of CDOM at the bottom is shown to be conservative. Controlled by the two-layer gravitational circulation in the PRE, the northern and western estuary shows higher CDOM absorption and lower spectral slope than the southern and eastern estuary, and the surface CDOM presents higher absorption and lower spectral slope than the bottom. Horizontal transport is hypothesized to be the dominant hydrodynamic mechanism affecting CDOM variation and mixing behavior in the PRE, while the vertical mixing has less influence.

Numerical predictions of shock propagation through unreactive and reactive liquids with experimental validation

NASA Astrophysics Data System (ADS)

Stekovic, Svjetlana; Nissen, Erin; Bhowmick, Mithun; Stewart, Donald S.; Dlott, Dana D.

2017-06-01

The objective of this work is to numerically analyze shock behavior as it propagates through compressed, unreactive and reactive liquid, such as liquid water and liquid nitromethane. Parameters, such as pressure and density, are analyzed using the Mie-Gruneisen EOS and each multi-material system is modeled using the ALE3D software. The motivation for this study is based on provided high-resolution, optical interferometer (PDV) and optical pyrometer measurements. In the experimental set-up, a liquid is placed between an Al 1100 plate and Pyrex BK-7 glass. A laser-driven Al 1100 flyer impacts the plate, causing the liquid to be highly compressed. The numerical model investigates the influence of the high pressure, shock-compressed behavior in each liquid, the energy transfer, and the wave impedance at the interface of each material in contact. The numerical results using ALE3D will be validated by experimental data. This work aims to provide further understanding of shock-compressed behavior and how the shock influences phase transition in each liquid.

Consentaneous Agent-Based and Stochastic Model of the Financial Markets

PubMed Central

Gontis, Vygintas; Kononovicius, Aleksejus

2014-01-01

We are looking for the agent-based treatment of the financial markets considering necessity to build bridges between microscopic, agent based, and macroscopic, phenomenological modeling. The acknowledgment that agent-based modeling framework, which may provide qualitative and quantitative understanding of the financial markets, is very ambiguous emphasizes the exceptional value of well defined analytically tractable agent systems. Herding as one of the behavior peculiarities considered in the behavioral finance is the main property of the agent interactions we deal with in this contribution. Looking for the consentaneous agent-based and macroscopic approach we combine two origins of the noise: exogenous one, related to the information flow, and endogenous one, arising form the complex stochastic dynamics of agents. As a result we propose a three state agent-based herding model of the financial markets. From this agent-based model we derive a set of stochastic differential equations, which describes underlying macroscopic dynamics of agent population and log price in the financial markets. The obtained solution is then subjected to the exogenous noise, which shapes instantaneous return fluctuations. We test both Gaussian and q-Gaussian noise as a source of the short term fluctuations. The resulting model of the return in the financial markets with the same set of parameters reproduces empirical probability and spectral densities of absolute return observed in New York, Warsaw and NASDAQ OMX Vilnius Stock Exchanges. Our result confirms the prevalent idea in behavioral finance that herding interactions may be dominant over agent rationality and contribute towards bubble formation. PMID:25029364

An uncommon case of random fire-setting behavior associated with Todd paralysis: a case report.

PubMed

Kanehisa, Masayuki; Morinaga, Katsuhiko; Kohno, Hisae; Maruyama, Yoshihiro; Ninomiya, Taiga; Ishitobi, Yoshinobu; Tanaka, Yoshihiro; Tsuru, Jusen; Hanada, Hiroaki; Yoshikawa, Tomoya; Akiyoshi, Jotaro

2012-08-31

The association between fire-setting behavior and psychiatric or medical disorders remains poorly understood. Although a link between fire-setting behavior and various organic brain disorders has been established, associations between fire setting and focal brain lesions have not yet been reported. Here, we describe the case of a 24-year-old first time arsonist who suffered Todd's paralysis prior to the onset of a bizarre and random fire-setting behavior. A case of a 24-year-old man with a sudden onset of a bizarre and random fire-setting behavior is reported. The man, who had been arrested on felony arson charges, complained of difficulties concentrating and of recent memory disturbances with leg weakness. A video-EEG recording demonstrated a close relationship between the focal motor impairment and a clear-cut epileptic ictal discharge involving the bilateral motor cortical areas. The SPECT result was statistically analyzed by comparing with standard SPECT images obtained from our institute (easy Z-score imaging system; eZIS). eZIS revealed hypoperfusion in cingulate cortex, basal ganglia and hyperperfusion in frontal cortex,. A neuropsychological test battery revealed lower than normal scores for executive function, attention, and memory, consistent with frontal lobe dysfunction. The fire-setting behavior and Todd's paralysis, together with an unremarkable performance on tests measuring executive function fifteen months prior, suggested a causal relationship between this organic brain lesion and the fire-setting behavior. The case describes a rare and as yet unreported association between random, impulse-driven fire-setting behavior and damage to the brain and suggests a disconnection of frontal lobe structures as a possible pathogenic mechanism.

Modal description—A better way of characterizing human vibration behavior

NASA Astrophysics Data System (ADS)

Rützel, Sebastian; Hinz, Barbara; Wölfel, Horst Peter

2006-12-01

Biodynamic responses to whole body vibrations are usually characterized in terms of transfer functions, such as impedance or apparent mass. Data measurements from subjects are averaged and analyzed with respect to certain attributes (anthropometrics, posture, excitation intensity, etc.). Averaging involves the risk of identifying unnatural vibration characteristics. The use of a modal description as an alternative method is presented and its contribution to biodynamic modelling is discussed. Modal description is not limited to just one biodynamic function: The method holds for all transfer functions. This is shown in terms of the apparent mass and the seat-to-head transfer function. The advantages of modal description are illustrated using apparent mass data of six male individuals of the same mass percentile. From experimental data, modal parameters such as natural frequencies, damping ratios and modal masses are identified which can easily be used to set up a mathematical model. Following the phenomenological approach, this model will provide the global vibration behavior relating to the input data. The modal description could be used for the development of hardware vibration dummies. With respect to software models such as finite element models, the validation process for these models can be supported by the modal approach. Modal parameters of computational models and of the experimental data can establish a basis for comparison.

Elastic properties and mechanical stability of chiral and filled viral capsids

NASA Astrophysics Data System (ADS)

Buenemann, Mathias; Lenz, Peter

2008-11-01

The elasticity and mechanical stability of empty and filled viral capsids under external force loading are studied in a combined analytical and numerical approach. We analyze the influence of capsid structure and chirality on the mechanical properties. We find that generally skew shells have lower stretching energy. For large Föppl-von Kármán numbers γ (γ≈105) , skew structures are stiffer in their elastic response than nonchiral ones. The discrete structure of the capsules not only leads to buckling for large γ but also influences the breakage behavior of capsules below the buckling threshold: the rupture force shows a γ1/4 scaling rather than a γ1/2 scaling as expected from our analytical results for continuous shells. Filled viral capsids are exposed to internal anisotropic pressure distributions arising from regularly packaged DNA coils. We analyze their influence on the elastic properties and rupture behavior and we discuss possible experimental consequences. Finally, we numerically investigate specific sets of parameters corresponding to specific phages such as ϕ29 and cowpea chlorotic mottle virus (CCMV). From the experimentally measured spring constants we make predictions about specific material parameters (such as bending rigidity and Young’s modulus) for both empty and filled capsids.

Crystal structure, vibrational, spectral investigation, quantum chemical DFT calculations and thermal behavior of Diethyl [hydroxy (phenyl) methyl] phosphonate

NASA Astrophysics Data System (ADS)

Ouksel, Louiza; Chafaa, Salah; Bourzami, Riadh; Hamdouni, Noudjoud; Sebais, Miloud; Chafai, Nadjib

2017-09-01

Single Diethyl [hydroxy (phenyl) methyl] phosphonate (DHPMP) crystal with chemical formula C11H17O4P, was synthesized via the base-catalyzed Pudovik reaction and Lewis acid as catalyst. The results of SXRD analyzes indicate that this compound crystallizes into a mono-clinic system with space group P21/n symmetry and Z = 4. The crystal structure parameters are a = 9.293 Å, b = 8.103 Å, c = 17.542 Å, β = 95.329° and V = 1315.2 Å3, the structure displays one inter-molecular O-H⋯O hydrogen bonding. The UV-Visible absorption spectrum shows that the crystal exhibits a good optical transmission in the visible domain, and strong absorption in middle ultraviolet one. The vibrational frequencies of various functional groups present in DHPMP crystal have been deduced from FT-IR and FT-Raman spectra and then compared with theoretical values performed with DFT (B3LYP) method using 6-31G (p, d) basis sets. Chemical and thermodynamic parameters such as: ionization potential (I), electron affinity (A), hardness (σ), softness (η), electronegativity (χ) and electrophilicity index (ω), are also calculated using the same theoretical method. The thermal decomposition behavior of DHPMP, studied by using thermogravimetric analysis (TDG), shows a thermal stability until to 125 °C.

Adapting ISA system warnings to enhance user acceptance.

PubMed

Jiménez, Felipe; Liang, Yingzhen; Aparicio, Francisco

2012-09-01

Inappropriate speed is a major cause of traffic accidents. Different measures have been considered to control traffic speed, and intelligent speed adaptation (ISA) systems are one of the alternatives. These systems know the speed limits and try to improve compliance with them. This paper deals with an informative ISA system that provides the driver with an advance warning before reaching a road section with singular characteristics that require a lower safe speed than the current speed. In spite of the extensive tests performed using ISA systems, few works show how warnings can be adapted to the driver. This paper describes a method to adapt warning parameters (safe speed on curves, zone of influence of a singular stretch, deceleration process and reaction time) to normal driving behavior. The method is based on a set of tests with and without the ISA system. This adjustment, as well as the analysis of driver acceptance before and after the adaptation and changes in driver behavior (changes in speed and path) resulting from the tested ISA regarding a driver's normal driving style, is shown in this paper. The main conclusion is that acceptance by drivers increased significantly after redefining the warning parameters, but the effect of speed homogenization was not reduced. Copyright © 2010 Elsevier Ltd. All rights reserved.

Investigation of the leading and subleading high-energy behavior of hadron-hadron total cross sections using a best-fit analysis of hadronic scattering data

NASA Astrophysics Data System (ADS)

Giordano, M.; Meggiolaro, E.; Silva, P. V. R. G.

2017-08-01

In the present investigation we study the leading and subleading high-energy behavior of hadron-hadron total cross sections using a best-fit analysis of hadronic scattering data. The parametrization used for the hadron-hadron total cross sections at high energy is inspired by recent results obtained by Giordano and Meggiolaro [J. High Energy Phys. 03 (2014) 002, 10.1007/JHEP03(2014)002] using a nonperturbative approach in the framework of QCD, and it reads σtot˜B ln2s +C ln s ln ln s . We critically investigate if B and C can be obtained by means of best-fits to data for proton-proton and antiproton-proton scattering, including recent data obtained at the LHC, and also to data for other meson-baryon and baryon-baryon scattering processes. In particular, following the above-mentioned nonperturbative QCD approach, we also consider fits where the parameters B and C are set to B =κ Bth and C =κ Cth, where Bth and Cth are universal quantities related to the QCD stable spectrum, while κ (treated as an extra free parameter) is related to the asymptotic value of the ratio σel/σtot. Different possible scenarios are then considered and compared.

Optimization of multilayer neural network parameters for speaker recognition

NASA Astrophysics Data System (ADS)

Tovarek, Jaromir; Partila, Pavol; Rozhon, Jan; Voznak, Miroslav; Skapa, Jan; Uhrin, Dominik; Chmelikova, Zdenka

2016-05-01

This article discusses the impact of multilayer neural network parameters for speaker identification. The main task of speaker identification is to find a specific person in the known set of speakers. It means that the voice of an unknown speaker (wanted person) belongs to a group of reference speakers from the voice database. One of the requests was to develop the text-independent system, which means to classify wanted person regardless of content and language. Multilayer neural network has been used for speaker identification in this research. Artificial neural network (ANN) needs to set parameters like activation function of neurons, steepness of activation functions, learning rate, the maximum number of iterations and a number of neurons in the hidden and output layers. ANN accuracy and validation time are directly influenced by the parameter settings. Different roles require different settings. Identification accuracy and ANN validation time were evaluated with the same input data but different parameter settings. The goal was to find parameters for the neural network with the highest precision and shortest validation time. Input data of neural networks are a Mel-frequency cepstral coefficients (MFCC). These parameters describe the properties of the vocal tract. Audio samples were recorded for all speakers in a laboratory environment. Training, testing and validation data set were split into 70, 15 and 15 %. The result of the research described in this article is different parameter setting for the multilayer neural network for four speakers.

Goal setting frequency and the use of behavioral strategies related to diet and physical activity.

PubMed

Nothwehr, Faryle; Yang, Jingzhen

2007-08-01

Goal setting is an effective way to focus attention on behavior change. Theoretically, frequency of goal setting may indicate the level of commitment to diet and physical activity behavior change. Yet, little is known about the association between goal setting frequency and use of specific diet or physical activity-related strategies. This study examines whether changes in goal setting frequency predict changes in use of behavioral strategies over time, controlling for baseline strategy use, demographics and whether a person was trying to lose weight. Data are from a baseline and 1-year follow-up survey of adults in rural Iowa (n = 385). Overall, goal setting frequency was positively associated with use of the strategies measured, at baseline and overtime. Frequent goal setting that is focused specifically on diet or physical activity was more predictive of using dietary or physical activity strategies, respectively, than goal setting focused on weight loss overall. The study provides empirical support for what has been assumed theoretically, that is, frequent goal setting for weight management is an indicator of use of specific behavioral strategies. Significant challenges remain in regard to maintenance of this activity and attainment of weight loss goals.

Culture and Social Relationship as Factors of Affecting Communicative Non-verbal Behaviors

NASA Astrophysics Data System (ADS)

Akhter Lipi, Afia; Nakano, Yukiko; Rehm, Mathias

The goal of this paper is to link a bridge between social relationship and cultural variation to predict conversants' non-verbal behaviors. This idea serves as a basis of establishing a parameter based socio-cultural model, which determines non-verbal expressive parameters that specify the shapes of agent's nonverbal behaviors in HAI. As the first step, a comparative corpus analysis is done for two cultures in two specific social relationships. Next, by integrating the cultural and social parameters factors with the empirical data from corpus analysis, we establish a model that predicts posture. The predictions from our model successfully demonstrate that both cultural background and social relationship moderate communicative non-verbal behaviors.

The role of the electrolyte in the selective dissolution of metal alloys

NASA Astrophysics Data System (ADS)

Policastro, Steven A.

Dealloying plays an important role in several corrosion processes, including pitting corrosion through the formation of local cathodes from the selective dissolution of intermetallic particles and stress-corrosion cracking in which it is responsible for injecting cracks from the surface into the undealloyed bulk material. Additionally, directed dealloying in the laboratory to form nanoporous structures has been the subject of much recent study because of the unique structural properties that the porous layer provides. In order to better understand the physical reasons for dealloying as well as understand the parameters that influence the evolution of the microstructure, several models have been proposed. Current theoretical descriptions of dealloying have been very successful in explaining some features of selective dissolution but additional behaviors can be included into the model to improve understanding of the dealloying process. In the present work, the effects of electrolyte component interactions, temperature, alloy cohesive energies, and applied potential on the development of nanoporosity via the selective dissolution of the less-noble component from binary and ternary alloys are considered. Both a kinetic Monte-Carlo (KMC) model of the behavior of the metal atoms and the electrolyte ions at the metal-solution interface and a phase-yield model of ligament coarsening are developed. By adding these additional parameters into the KMC model, a rich set of behaviors is observed in the simulation results. From the simulation results, it is suggested that selectively dissolving a binary alloy in a very aggressive electrolyte that targeted the LN atoms could provide a porous microstructure that retained a higher concentration of the LN atoms in its ligaments and thus retain more of the mechanical properties of the bulk alloy. In addition, by adding even a small fraction of a third, noble component to form a ternary alloy the dissolution kinetics of the least noble component can be dramatically altered, providing a means of controlling dealloying depth. Some molecular dynamics calculations are used to justify the assumptions of metal atom motion in the KMC model. A recently developed parameter-space exploration technique, COERCE, is employed to optimize the process of obtaining meaningful parameter values from the KMC simulation.

Characterization and Remediation of Contaminated Sites:Modeling, Measurement and Assessment

NASA Astrophysics Data System (ADS)

Basu, N. B.; Rao, P. C.; Poyer, I. C.; Christ, J. A.; Zhang, C. Y.; Jawitz, J. W.; Werth, C. J.; Annable, M. D.; Hatfield, K.

2008-05-01

The complexity of natural systems makes it impossible to estimate parameters at the required level of spatial and temporal detail. Thus, it becomes necessary to transition from spatially distributed parameters to spatially integrated parameters that are capable of adequately capturing the system dynamics, without always accounting for local process behavior. Contaminant flux across the source control plane is proposed as an integrated metric that captures source behavior and links it to plume dynamics. Contaminant fluxes were measured using an innovative technology, the passive flux meter at field sites contaminated with dense non-aqueous phase liquids or DNAPLs in the US and Australia. Flux distributions were observed to be positively or negatively correlated with the conductivity distribution, depending on the source characteristics of the site. The impact of partial source depletion on the mean contaminant flux and flux architecture was investigated in three-dimensional complex heterogeneous settings using the multiphase transport code UTCHEM and the reactive transport code ISCO3D. Source mass depletion reduced the mean contaminant flux approximately linearly, while the contaminant flux standard deviation reduced proportionally with the mean (i.e., coefficient of variation of flux distribution is constant with time). Similar analysis was performed using data from field sites, and the results confirmed the numerical simulations. The linearity of the mass depletion-flux reduction relationship indicates the ability to design remediation systems that deplete mass to achieve target reduction in source strength. Stability of the flux distribution indicates the ability to characterize the distributions in time once the initial distribution is known. Lagrangian techniques were used to predict contaminant flux behavior during source depletion in terms of the statistics of the hydrodynamic and DNAPL distribution. The advantage of the Lagrangian techniques lies in their small computation time and their inclusion of spatially integrated parameters that can be measured in the field using tracer tests. Analytical models that couple source depletion to plume transport were used for optimization of source and plume treatment. These models are being used for the development of decision and management tools (for DNAPL sites) that consider uncertainty assessments as an integral part of the decision-making process for contaminated site remediation.

[Non-face-to-face sleep improvement program in a workplace: bibliotherapy with and without behavioral self-control procedure].

PubMed

Adachi, Yoshiko; Kunitsuka, Kouko; Taniyama, Katsuko; Hayashi, Chikako; Tanaka, Minori; Sato, Chifumi

2010-01-01

Sleep hygiene education has been important health issue in the health promotion and the prevention of lifestyle-related diseases. A feasible and effective method is necessary for population approach. To evaluate the effects of a non-face-to-face brief behavioral program for a sleep improvement in workplaces. Research design was a cluster control trial. Three hundred and thirty participants were allocated to the bibliotherapy group (BTG; n=130) or self-control group (SCG; n=200). Two groups were recruited from separated local sections of a Japanese company each other. There was no eligibility criteria and the intervention was open to every worker in the workplaces. All participants received a self-help booklet and information on recent topics of insomnia-related health problems. SCG participants set several behaviors for habit improvement and monitored those behaviors for 4 wk additionally. The replies to the questionnaire showed that almost all of them had any sleep disturbances. A total of 158 participants in SCG (79%) and a total of 106 participants in BTG (82%) responded to the post questionnaire. Sleep parameters of pre and post questionnaires were compared between SCG and BTG. Overall, sleep onset latency was reduced and sleep efficiency was improved. The significant changes were found in only SCG. Re-analysis of pre and post 3-days' sleep diaries showed that the subjects in both group improved significantly in the main variables (total sleep time, number of awakenings, time spent awake, sleep efficiency). Sleep onset latency, wake after sleep onset, and daytime sleepiness improved significantly in only SCG. These results suggest that an additional target setting and self-monitoring could promote the effectiveness for sleep improvement of a bibliotherapy.

Approximate scaling properties of RNA free energy landscapes

NASA Technical Reports Server (NTRS)

Baskaran, S.; Stadler, P. F.; Schuster, P.

1996-01-01

RNA free energy landscapes are analysed by means of "time-series" that are obtained from random walks restricted to excursion sets. The power spectra, the scaling of the jump size distribution, and the scaling of the curve length measured with different yard stick lengths are used to describe the structure of these "time series". Although they are stationary by construction, we find that their local behavior is consistent with both AR(1) and self-affine processes. Random walks confined to excursion sets (i.e., with the restriction that the fitness value exceeds a certain threshold at each step) exhibit essentially the same statistics as free random walks. We find that an AR(1) time series is in general approximately self-affine on timescales up to approximately the correlation length. We present an empirical relation between the correlation parameter rho of the AR(1) model and the exponents characterizing self-affinity.

Maximum Likelihood Item Easiness Models for Test Theory Without an Answer Key

PubMed Central

Batchelder, William H.

2014-01-01

Cultural consensus theory (CCT) is a data aggregation technique with many applications in the social and behavioral sciences. We describe the intuition and theory behind a set of CCT models for continuous type data using maximum likelihood inference methodology. We describe how bias parameters can be incorporated into these models. We introduce two extensions to the basic model in order to account for item rating easiness/difficulty. The first extension is a multiplicative model and the second is an additive model. We show how the multiplicative model is related to the Rasch model. We describe several maximum-likelihood estimation procedures for the models and discuss issues of model fit and identifiability. We describe how the CCT models could be used to give alternative consensus-based measures of reliability. We demonstrate the utility of both the basic and extended models on a set of essay rating data and give ideas for future research. PMID:29795812

Neuromorphic walking gait control.

PubMed

Still, Susanne; Hepp, Klaus; Douglas, Rodney J

2006-03-01

We present a neuromorphic pattern generator for controlling the walking gaits of four-legged robots which is inspired by central pattern generators found in the nervous system and which is implemented as a very large scale integrated (VLSI) chip. The chip contains oscillator circuits that mimic the output of motor neurons in a strongly simplified way. We show that four coupled oscillators can produce rhythmic patterns with phase relationships that are appropriate to generate all four-legged animal walking gaits. These phase relationships together with frequency and duty cycle of the oscillators determine the walking behavior of a robot driven by the chip, and they depend on a small set of stationary bias voltages. We give analytic expressions for these dependencies. This chip reduces the complex, dynamic inter-leg control problem associated with walking gait generation to the problem of setting a few stationary parameters. It provides a compact and low power solution for walking gait control in robots.

Spectroscopic Survey of Circumstellar Disks in Orion

NASA Astrophysics Data System (ADS)

Contreras, Maria; Hernandez, Jesus; Olguin, Lorenzo; Briceno, Cesar

2013-07-01

As a second stage of a project focused on characterizing candidate stars bearing a circumstellar disk in Orion, we present a spectroscopic follow-up of a set of about 170 bright stars. The present set of stars was selected by their optical (UBVRI) and infrared behavior in different color-color and color-magnitude diagrams. Observations were carried out at the Observatorio Astronomico Nacional located at the Sierra San Pedro Martir in B.C., Mexico and at the Observatorio Guillermo Haro in Cananea, Sonora, Mexico. Low-resolution spectra were obtained for all candidates in the sample. Using the SPTCLASS code, we have obtained spectral types and equivalent widths of the Li I 6707 and Halpha lines for each one of the stars. This project is a cornerstone of a large scale survey aimed to obtain stellar parameters in a homogeneous way using spectroscopic data. This work was partially supported by UNAM-PAPIIT grant IN-109311.

A semiempirical correlation between enthalpy of vaporization and saturation concentration for organic aerosol.

PubMed

Epstein, Scott A; Riipinen, Ilona; Donahue, Neil M

2010-01-15

To model the temperature-induced partitioning of semivolatile organics in laboratory experiments or atmospheric models, one must know the appropriate heats of vaporization. Current treatments typically assume a constant value of the heat of vaporization or else use specific values from a small set of surrogate compounds. With published experimental vapor-pressure data from over 800 organic compounds, we have developed a semiempirical correlation between the saturation concentration (C*, microg m(-3)) and the heat of vaporization (deltaH(VAP), kJ mol(-1)) for organics in the volatility basis set. Near room temperature, deltaH(VAP) = -11 log(10)C(300)(*) + 129. Knowledge of the relationship between C* and deltaH(VAP) constrains a free parameter in thermodenuder data analysis. A thermodenuder model using our deltaH(VAP) values agrees well with thermal behavior observed in laboratory experiments.

Vehicle dynamic analysis using neuronal network algorithms

NASA Astrophysics Data System (ADS)

Oloeriu, Florin; Mocian, Oana

2014-06-01

Theoretical developments of certain engineering areas, the emergence of new investigation tools, which are better and more precise and their implementation on-board the everyday vehicles, all these represent main influence factors that impact the theoretical and experimental study of vehicle's dynamic behavior. Once the implementation of these new technologies onto the vehicle's construction had been achieved, it had led to more and more complex systems. Some of the most important, such as the electronic control of engine, transmission, suspension, steering, braking and traction had a positive impact onto the vehicle's dynamic behavior. The existence of CPU on-board vehicles allows data acquisition and storage and it leads to a more accurate and better experimental and theoretical study of vehicle dynamics. It uses the information offered directly by the already on-board built-in elements of electronic control systems. The technical literature that studies vehicle dynamics is entirely focused onto parametric analysis. This kind of approach adopts two simplifying assumptions. Functional parameters obey certain distribution laws, which are known in classical statistics theory. The second assumption states that the mathematical models are previously known and have coefficients that are not time-dependent. Both the mentioned assumptions are not confirmed in real situations: the functional parameters do not follow any known statistical repartition laws and the mathematical laws aren't previously known and contain families of parameters and are mostly time-dependent. The purpose of the paper is to present a more accurate analysis methodology that can be applied when studying vehicle's dynamic behavior. A method that provides the setting of non-parametrical mathematical models for vehicle's dynamic behavior is relying on neuronal networks. This method contains coefficients that are time-dependent. Neuronal networks are mostly used in various types' system controls, thus being a non-linear process identification algorithm. The common use of neuronal networks for non-linear processes is justified by the fact that both have the ability to organize by themselves. That is why the neuronal networks best define intelligent systems, thus the word `neuronal' is sending one's mind to the biological neuron cell. The paper presents how to better interpret data fed from the on-board computer and a new way of processing that data to better model the real life dynamic behavior of the vehicle.

Goal setting in diabetes self-management: Taking the baby steps to success

PubMed Central

DeWalt, Darren A.; Davis, Terry C.; Wallace, Andrea S.; Seligman, Hilary K.; Bryant-Shilliday, Betsy; Arnold, Connie L.; Freburger, Janet; Schillinger, Dean

2014-01-01

Objective To evaluate the usefulness of a diabetes self-management guide and a brief counseling intervention in helping patients set and achieve their behavioral goals. Methods We conducted a quasi-experimental study using a one group pretest posttest design to assess the effectiveness of a goal setting intervention along with a self-management guide. English- and Spanish-speaking patients with diabetes had one in-person session and two telephone follow-up calls with a non-clinical provider over a 12–16-week period. At each call and at the end of the study, we assessed success in achieving behavioral goals and problem solving toward those goals. Satisfaction with the self-management guide was assessed at the end of the study. Results We enrolled 250 patients across three sites and 229 patients completed the study. Most patients chose to set goals in diet and exercise domains. 93% of patients achieved at least one behavioral goal during the study and 73% achieved at least two behavioral goals. Many patients exhibited problem solving behavior to achieve their goals. We found no significant differences in reported achievement of behavior goals by literacy or language. Patients were very satisfied with the guide. Conclusions A brief goal setting intervention along with a diabetes self-management guide helped patients set and achieve healthy behavioral goals. Practice implications Non-clinical providers can successfully help a diverse range of patients with diabetes set and achieve behavioral goals. PMID:19359123

Parameter Estimation for Geoscience Applications Using a Measure-Theoretic Approach

NASA Astrophysics Data System (ADS)

Dawson, C.; Butler, T.; Mattis, S. A.; Graham, L.; Westerink, J. J.; Vesselinov, V. V.; Estep, D.

2016-12-01

Effective modeling of complex physical systems arising in the geosciences is dependent on knowing parameters which are often difficult or impossible to measure in situ. In this talk we focus on two such problems, estimating parameters for groundwater flow and contaminant transport, and estimating parameters within a coastal ocean model. The approach we will describe, proposed by collaborators D. Estep, T. Butler and others, is based on a novel stochastic inversion technique based on measure theory. In this approach, given a probability space on certain observable quantities of interest, one searches for the sets of highest probability in parameter space which give rise to these observables. When viewed as mappings between sets, the stochastic inversion problem is well-posed in certain settings, but there are computational challenges related to the set construction. We will focus the talk on estimating scalar parameters and fields in a contaminant transport setting, and in estimating bottom friction in a complicated near-shore coastal application.

Practical Approaches for Achieving Integrated Behavioral Health Care in Primary Care Settings

PubMed Central

Ratzliff, Anna; Phillips, Kathryn E.; Sugarman, Jonathan R.; Unützer, Jürgen; Wagner, Edward H.

2016-01-01

Behavioral health problems are common, yet most patients do not receive effective treatment in primary care settings. Despite availability of effective models for integrating behavioral health care in primary care settings, uptake has been slow. The Behavioral Health Integration Implementation Guide provides practical guidance for adapting and implementing effective integrated behavioral health care into patient-centered medical homes. The authors gathered input from stakeholders involved in behavioral health integration efforts: safety net providers, subject matter experts in primary care and behavioral health, a behavioral health patient and peer specialist, and state and national policy makers. Stakeholder input informed development of the Behavioral Health Integration Implementation Guide and the GROW Pathway Planning Worksheet. The Behavioral Health Integration Implementation Guide is model neutral and allows organizations to take meaningful steps toward providing integrated care that achieves access and accountability. PMID:26698163

Practical Approaches for Achieving Integrated Behavioral Health Care in Primary Care Settings.

PubMed

Ratzliff, Anna; Phillips, Kathryn E; Sugarman, Jonathan R; Unützer, Jürgen; Wagner, Edward H

Behavioral health problems are common, yet most patients do not receive effective treatment in primary care settings. Despite availability of effective models for integrating behavioral health care in primary care settings, uptake has been slow. The Behavioral Health Integration Implementation Guide provides practical guidance for adapting and implementing effective integrated behavioral health care into patient-centered medical homes. The authors gathered input from stakeholders involved in behavioral health integration efforts: safety net providers, subject matter experts in primary care and behavioral health, a behavioral health patient and peer specialist, and state and national policy makers. Stakeholder input informed development of the Behavioral Health Integration Implementation Guide and the GROW Pathway Planning Worksheet. The Behavioral Health Integration Implementation Guide is model neutral and allows organizations to take meaningful steps toward providing integrated care that achieves access and accountability.

The psychomechanics of simulated sound sources: Material properties of impacted bars

NASA Astrophysics Data System (ADS)

McAdams, Stephen; Chaigne, Antoine; Roussarie, Vincent

2004-03-01

Sound can convey information about the materials composing an object that are often not directly available to the visual system. Material and geometric properties of synthesized impacted bars with a tube resonator were varied, their perceptual structure was inferred from multidimensional scaling of dissimilarity judgments, and the psychophysical relations between the two were quantified. Constant cross-section bars varying in mass density and viscoelastic damping coefficient were synthesized with a physical model in experiment 1. A two-dimensional perceptual space resulted, and the dimensions were correlated with the mechanical parameters after applying a power-law transformation. Variable cross-section bars varying in length and viscoelastic damping coefficient were synthesized in experiment 2 with two sets of lengths creating high- and low-pitched bars. In the low-pitched bars, there was a coupling between the bar and the resonator that modified the decay characteristics. Perceptual dimensions again corresponded to the mechanical parameters. A set of potential temporal, spectral, and spectrotemporal correlates of the auditory representation were derived from the signal. The dimensions related to mass density and bar length were correlated with the frequency of the lowest partial and are related to pitch perception. The correlate most likely to represent the viscoelastic damping coefficient across all three stimulus sets is a linear combination of a decay constant derived from the temporal envelope and the spectral center of gravity derived from a cochlear representation of the signal. These results attest to the perceptual salience of energy-loss phenomena in sound source behavior.

Proactive inhibitory control: A general biasing account☆

PubMed Central

Elchlepp, Heike; Lavric, Aureliu; Chambers, Christopher D.; Verbruggen, Frederick

2016-01-01

Flexible behavior requires a control system that can inhibit actions in response to changes in the environment. Recent studies suggest that people proactively adjust response parameters in anticipation of a stop signal. In three experiments, we tested the hypothesis that proactive inhibitory control involves adjusting both attentional and response settings, and we explored the relationship with other forms of proactive and anticipatory control. Subjects responded to the color of a stimulus. On some trials, an extra signal occurred. The response to this signal depended on the task context subjects were in: in the ‘ignore’ context, they ignored it; in the ‘stop’ context, they had to withhold their response; and in the ‘double-response’ context, they had to execute a secondary response. An analysis of event-related brain potentials for no-signal trials in the stop context revealed that proactive inhibitory control works by biasing the settings of lower-level systems that are involved in stimulus detection, action selection, and action execution. Furthermore, subjects made similar adjustments in the double-response and stop-signal contexts, indicating an overlap between various forms of proactive action control. The results of Experiment 1 also suggest an overlap between proactive inhibitory control and preparatory control in task-switching studies: both require reconfiguration of task-set parameters to bias or alter subordinate processes. We conclude that much of the top-down control in response inhibition tasks takes place before the inhibition signal is presented. PMID:26859519

The moral development of baccalaureate nursing students: understanding unethical behavior in classroom and clinical settings.

PubMed

Baxter, Pamela E; Boblin, Sheryl L

2007-01-01

Unethical behavior in both classroom and clinical settings is a concern for nurse educators and has the potential to greatly influence the quality of patient care. A review of the literature suggests that students may view unethical clinical behaviors as different from unethical classroom behaviors because they recognize that clinical behaviors may have a direct effect on patient care. An overview of three moral theories, proposed by Kohlberg, Gilligan, and Rest, provides insight into the reasons for unethical behavior. These theories provide the foundation for strategies nurse educators can use to help reduce unethical behavior in both classroom and clinical settings in an attempt to ensure quality patient care.

Competitive Modes for the Detection of Chaotic Parameter Regimes in the General Chaotic Bilinear System of Lorenz Type

NASA Astrophysics Data System (ADS)

Mallory, Kristina; van Gorder, Robert A.

We study chaotic behavior of solutions to the bilinear system of Lorenz type developed by Celikovsky and Vanecek [1994] through an application of competitive modes. This bilinear system of Lorenz type is one possible canonical form holding the Lorenz equation as a special case. Using a competitive modes analysis, which is a completely analytical method allowing one to identify parameter regimes for which chaos may occur, we are able to demonstrate a number of parameter regimes which admit a variety of distinct chaotic behaviors. Indeed, we are able to draw some interesting conclusions which relate the behavior of the mode frequencies arising from writing the state variables for the Celikovsky-Vanecek model as coupled oscillators, and the types of emergent chaotic behaviors observed. The competitive modes analysis is particularly useful if all but one of the model parameters are fixed, and the remaining free parameter is used to modify the chaos observed, in a manner analogous to a bifurcation parameter. Through a thorough application of the method, we are able to identify several parameter regimes which give new dynamics (such as specific forms of chaos) which were not observed or studied previously in the Celikovsky-Vanecek model. Therefore, the results demonstrate the advantage of the competitive modes approach for detecting new parameter regimes leading to chaos in third-order dynamical systems.

The exposure to Trichilia catigua (catuaba) crude extract impairs fertility of adult female rats but does not cause reproductive damage to male offspring.

PubMed

Dos Santos, Alice Hartmann; Ramos, Aline Camargo; Silveira, Kennia Moura; Kiss, Ana Carolina Inhasz; Longhini, Renata; Diniz, Andréa; de Mello, João Carlos Palazzo; Gerardin, Daniela Cristina Ceccatto

2015-05-26

Trichilia catigua is broadly used in folk medicine due to its mental and physical tonic activities and stimulant effects. In animal models, its antidepressant-like effects have been associated with the dopaminergic (DA) system modulation, which has an important role on maternal behavior and male offspring reproductive development. Since little is known about the adverse effects of the exposure to T. catigua crude extract (CAT) in rats, specially regarding maternal homeostasis and offspring development, the aim of the present study was to evaluate whether CAT exposure may influence maternal toxicity parameters and behavior or disrupt male offspring physical and reproductive development. Dams were treated daily (by gavage) with 400mg/kg of CAT or vehicle (control=CTR) throughout pregnancy and lactation. Fertility and maternal behavior tests were conducted in dams. Male offspring reproductive and behavioral parameters were analyzed. Dams exposed to CAT showed increased pre- and post-implantation losses rates when compared to CTR group. No significant changes regarding maternal behavior or male offspring parameters were observed. In conclusion, maternal exposure to CAT interfered with implantation during the initial phases of pregnancy but did not induce changes on maternal behavior or male offspring reproductive and behavioral parameters. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Limited Bandwidth Recognition of Collective Behaviors in Bio-Inspired Swarms

DTIC Science & Technology

2014-05-09

collective? Some swarm models exhibit multiple emergent behaviors from the same parameters. This provides increased expressivity at the cost of...swarms, namely, how do you know what the swarm is doing if you can’t ob- serve every agent in the collective? Some swarm models exhibit multiple ...flocking [15, 21, 12] or cyclic behavior [8, 7], and in some cases can exhibit multiple group behaviors depending on the model parameters used [6, 3, 17

Cognitive models of risky choice: parameter stability and predictive accuracy of prospect theory.

PubMed

Glöckner, Andreas; Pachur, Thorsten

2012-04-01

In the behavioral sciences, a popular approach to describe and predict behavior is cognitive modeling with adjustable parameters (i.e., which can be fitted to data). Modeling with adjustable parameters allows, among other things, measuring differences between people. At the same time, parameter estimation also bears the risk of overfitting. Are individual differences as measured by model parameters stable enough to improve the ability to predict behavior as compared to modeling without adjustable parameters? We examined this issue in cumulative prospect theory (CPT), arguably the most widely used framework to model decisions under risk. Specifically, we examined (a) the temporal stability of CPT's parameters; and (b) how well different implementations of CPT, varying in the number of adjustable parameters, predict individual choice relative to models with no adjustable parameters (such as CPT with fixed parameters, expected value theory, and various heuristics). We presented participants with risky choice problems and fitted CPT to each individual's choices in two separate sessions (which were 1 week apart). All parameters were correlated across time, in particular when using a simple implementation of CPT. CPT allowing for individual variability in parameter values predicted individual choice better than CPT with fixed parameters, expected value theory, and the heuristics. CPT's parameters thus seem to pick up stable individual differences that need to be considered when predicting risky choice. Copyright © 2011 Elsevier B.V. All rights reserved.

Cyclotron resonance in bilayer graphene.

PubMed

Henriksen, E A; Jiang, Z; Tung, L-C; Schwartz, M E; Takita, M; Wang, Y-J; Kim, P; Stormer, H L

2008-02-29

We present the first measurements of cyclotron resonance of electrons and holes in bilayer graphene. In magnetic fields up to B=18 T, we observe four distinct intraband transitions in both the conduction and valence bands. The transition energies are roughly linear in B between the lowest Landau levels, whereas they follow square root[B] for the higher transitions. This highly unusual behavior represents a change from a parabolic to a linear energy dispersion. The density of states derived from our data generally agrees with the existing lowest order tight binding calculation for bilayer graphene. However, in comparing data to theory, a single set of fitting parameters fails to describe the experimental results.

Cooperation and age structure in spatial games

NASA Astrophysics Data System (ADS)

Wang, Zhen; Wang, Zhen; Zhu, Xiaodan; Arenzon, Jeferson J.

2012-01-01

We study the evolution of cooperation in evolutionary spatial games when the payoff correlates with the increasing age of players (the level of correlation is set through a single parameter, α). The demographic heterogeneous age distribution, directly affecting the outcome of the game, is thus shown to be responsible for enhancing the cooperative behavior in the population. In particular, moderate values of α allow cooperators not only to survive but to outcompete defectors, even when the temptation to defect is large and the ageless, standard α=0 model does not sustain cooperation. The interplay between age structure and noise is also considered, and we obtain the conditions for optimal levels of cooperation.

Effective conductivity of a periodic dilute composite with perfect contact and its series expansion

NASA Astrophysics Data System (ADS)

Pukhtaievych, Roman

2018-06-01

We study the asymptotic behavior of the effective thermal conductivity of a periodic two-phase dilute composite obtained by introducing into an infinite homogeneous matrix a periodic set of inclusions of a different material, each of them of size proportional to a positive parameter ɛ . We assume a perfect thermal contact at constituent interfaces, i.e., a continuity of the normal component of the heat flux and of the temperature. For ɛ small, we prove that the effective conductivity can be represented as a convergent power series in ɛ and we determine the coefficients in terms of the solutions of explicit systems of integral equations.

Data on optimum recycle aggregate content in production of new structural concrete.

PubMed

Paul, Suvash Chandra

2017-12-01

This data presented herein are the research summary of "mechanical behavior and durability performance of concrete containing recycled concrete aggregate" (Paul, 2011) [1]. The results reported in this article relate to an important parameter of optimum content of recycle concrete aggregate (RCA) in production of new concrete for both structural and non-structural applications. For the purpose of the research various types of physical, mechanical and durability tests are performed for concrete made with different percentages of RCA. Therefore, this data set can be a great help of the readers to understand the mechanism of RCA in relates to the concrete properties.

Transcription, intercellular variability and correlated random walk.

PubMed

Müller, Johannes; Kuttler, Christina; Hense, Burkhard A; Zeiser, Stefan; Liebscher, Volkmar

2008-11-01

We develop a simple model for the random distribution of a gene product. It is assumed that the only source of variance is due to switching transcription on and off by a random process. Under the condition that the transition rates between on and off are constant we find that the amount of mRNA follows a scaled Beta distribution. Additionally, a simple positive feedback loop is considered. The simplicity of the model allows for an explicit solution also in this setting. These findings in turn allow, e.g., for easy parameter scans. We find that bistable behavior translates into bimodal distributions. These theoretical findings are in line with experimental results.

Personalizing knowledge delivery services: a conceptual framework

NASA Technical Reports Server (NTRS)

Majchrzak, Ann; Chelleppa, Ramnath K.; Cooper, Lynne P.; Hars, Alexander

2003-01-01

Consistent with the call of the Minnesota Symposium for new theory in knowledge management, we offer a new conceptualization of Knowledge Management Systems (KMS) as a portfolio of personalized knowledge delivery services. Borrowing from research on online consumer behavior, we describe the challenges imposed by personalized knowledge delivery services, and suggest design parameters that can help to overcome these challenges. We develop our design constructs through a set of hypotheses and discuss the research implications of our new conceptualization. Finally, we describe practical implications suggested by our conceptualization - practical suggestions that we hope to gain some experience with as part of an ongoing action research project at our partner organization.

Computer code for gas-liquid two-phase vortex motions: GLVM

NASA Technical Reports Server (NTRS)

Yeh, T. T.

1986-01-01

A computer program aimed at the phase separation between gas and liquid at zero gravity, induced by vortex motion, is developed. It utilizes an explicit solution method for a set of equations describing rotating gas-liquid flows. The vortex motion is established by a tangential fluid injection. A Lax-Wendroff two-step (McCormack's) numerical scheme is used. The program can be used to study the fluid dynamical behavior of the rotational two-phase fluids in a cylindrical tank. It provides a quick/easy sensitivity test on various parameters and thus provides the guidance for the design and use of actual physical systems for handling two-phase fluids.

Analysis of regional rainfall-runoff parameters for the Lake Michigan Diversion hydrological modeling

USGS Publications Warehouse

Soong, David T.; Over, Thomas M.

2015-01-01

Recalibration of the HSPF parameters to the updated inputs and land covers was completed on two representative watershed models selected from the nine by using a manual method (HSPEXP) and an automatic method (PEST). The objective of the recalibration was to develop a regional parameter set that improves the accuracy in runoff volume prediction for the nine study watersheds. Knowledge about flow and watershed characteristics plays a vital role for validating the calibration in both manual and automatic methods. The best performing parameter set was determined by the automatic calibration method on a two-watershed model. Applying this newly determined parameter set to the nine watersheds for runoff volume simulation resulted in “very good” ratings in five watersheds, an improvement as compared to “very good” ratings achieved for three watersheds by the North Branch parameter set.