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.

Adjoint-Based Aerodynamic Design of Complex Aerospace Configurations

NASA Technical Reports Server (NTRS)

Nielsen, Eric J.

2016-01-01

An overview of twenty years of adjoint-based aerodynamic design research at NASA Langley Research Center is presented. Adjoint-based algorithms provide a powerful tool for efficient sensitivity analysis of complex large-scale computational fluid dynamics (CFD) simulations. Unlike alternative approaches for which computational expense generally scales with the number of design parameters, adjoint techniques yield sensitivity derivatives of a simulation output with respect to all input parameters at the cost of a single additional simulation. With modern large-scale CFD applications often requiring millions of compute hours for a single analysis, the efficiency afforded by adjoint methods is critical in realizing a computationally tractable design optimization capability for such applications.

On the Influence of Material Parameters in a Complex Material Model for Powder Compaction

NASA Astrophysics Data System (ADS)

Staf, Hjalmar; Lindskog, Per; Andersson, Daniel C.; Larsson, Per-Lennart

2016-10-01

Parameters in a complex material model for powder compaction, based on a continuum mechanics approach, are evaluated using real insert geometries. The parameter sensitivity with respect to density and stress after compaction, pertinent to a wide range of geometries, is studied in order to investigate completeness and limitations of the material model. Finite element simulations with varied material parameters are used to build surrogate models for the sensitivity study. The conclusion from this analysis is that a simplification of the material model is relevant, especially for simple insert geometries. Parameters linked to anisotropy and the plastic strain evolution angle have a small impact on the final result.

Control of complex dynamics and chaos in distributed parameter systems

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

Chakravarti, S.; Marek, M.; Ray, W.H.

This paper discusses a methodology for controlling complex dynamics and chaos in distributed parameter systems. The reaction-diffusion system with Brusselator kinetics, where the torus-doubling or quasi-periodic (two characteristic incommensurate frequencies) route to chaos exists in a defined range of parameter values, is used as an example. Poincare maps are used for characterization of quasi-periodic and chaotic attractors. The dominant modes or topos, which are inherent properties of the system, are identified by means of the Singular Value Decomposition. Tested modal feedback control schemas based on identified dominant spatial modes confirm the possibility of stabilization of simple quasi-periodic trajectories in themore » complex quasi-periodic or chaotic spatiotemporal patterns.« less

META II Complex Systems Design and Analysis (CODA)

DTIC Science & Technology

2011-08-01

37  3.8.7  Variables, Parameters and Constraints ............................................................. 37  3.8.8  Objective...18  Figure 7: Inputs, States, Outputs and Parameters of System Requirements Specifications ......... 19...Design Rule Based on Device Parameter ....................................................... 57  Figure 35: AEE Device Design Rules (excerpt

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE PAGES

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

2015-10-30

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

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

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Monte Carlo sensitivity analysis of land surface parameters using the Variable Infiltration Capacity model

NASA Astrophysics Data System (ADS)

Demaria, Eleonora M.; Nijssen, Bart; Wagener, Thorsten

2007-06-01

Current land surface models use increasingly complex descriptions of the processes that they represent. Increase in complexity is accompanied by an increase in the number of model parameters, many of which cannot be measured directly at large spatial scales. A Monte Carlo framework was used to evaluate the sensitivity and identifiability of ten parameters controlling surface and subsurface runoff generation in the Variable Infiltration Capacity model (VIC). Using the Monte Carlo Analysis Toolbox (MCAT), parameter sensitivities were studied for four U.S. watersheds along a hydroclimatic gradient, based on a 20-year data set developed for the Model Parameter Estimation Experiment (MOPEX). Results showed that simulated streamflows are sensitive to three parameters when evaluated with different objective functions. Sensitivity of the infiltration parameter (b) and the drainage parameter (exp) were strongly related to the hydroclimatic gradient. The placement of vegetation roots played an important role in the sensitivity of model simulations to the thickness of the second soil layer (thick2). Overparameterization was found in the base flow formulation indicating that a simplified version could be implemented. Parameter sensitivity was more strongly dictated by climatic gradients than by changes in soil properties. Results showed how a complex model can be reduced to a more parsimonious form, leading to a more identifiable model with an increased chance of successful regionalization to ungauged basins. Although parameter sensitivities are strictly valid for VIC, this model is representative of a wider class of macroscale hydrological models. Consequently, the results and methodology will have applicability to other hydrological models.

Bottom-up modeling approach for the quantitative estimation of parameters in pathogen-host interactions

PubMed Central

Lehnert, Teresa; Timme, Sandra; Pollmächer, Johannes; Hünniger, Kerstin; Kurzai, Oliver; Figge, Marc Thilo

2015-01-01

Opportunistic fungal pathogens can cause bloodstream infection and severe sepsis upon entering the blood stream of the host. The early immune response in human blood comprises the elimination of pathogens by antimicrobial peptides and innate immune cells, such as neutrophils or monocytes. Mathematical modeling is a predictive method to examine these complex processes and to quantify the dynamics of pathogen-host interactions. Since model parameters are often not directly accessible from experiment, their estimation is required by calibrating model predictions with experimental data. Depending on the complexity of the mathematical model, parameter estimation can be associated with excessively high computational costs in terms of run time and memory. We apply a strategy for reliable parameter estimation where different modeling approaches with increasing complexity are used that build on one another. This bottom-up modeling approach is applied to an experimental human whole-blood infection assay for Candida albicans. Aiming for the quantification of the relative impact of different routes of the immune response against this human-pathogenic fungus, we start from a non-spatial state-based model (SBM), because this level of model complexity allows estimating a priori unknown transition rates between various system states by the global optimization method simulated annealing. Building on the non-spatial SBM, an agent-based model (ABM) is implemented that incorporates the migration of interacting cells in three-dimensional space. The ABM takes advantage of estimated parameters from the non-spatial SBM, leading to a decreased dimensionality of the parameter space. This space can be scanned using a local optimization approach, i.e., least-squares error estimation based on an adaptive regular grid search, to predict cell migration parameters that are not accessible in experiment. In the future, spatio-temporal simulations of whole-blood samples may enable timely stratification of sepsis patients by distinguishing hyper-inflammatory from paralytic phases in immune dysregulation. PMID:26150807

Bottom-up modeling approach for the quantitative estimation of parameters in pathogen-host interactions.

PubMed

Lehnert, Teresa; Timme, Sandra; Pollmächer, Johannes; Hünniger, Kerstin; Kurzai, Oliver; Figge, Marc Thilo

2015-01-01

Opportunistic fungal pathogens can cause bloodstream infection and severe sepsis upon entering the blood stream of the host. The early immune response in human blood comprises the elimination of pathogens by antimicrobial peptides and innate immune cells, such as neutrophils or monocytes. Mathematical modeling is a predictive method to examine these complex processes and to quantify the dynamics of pathogen-host interactions. Since model parameters are often not directly accessible from experiment, their estimation is required by calibrating model predictions with experimental data. Depending on the complexity of the mathematical model, parameter estimation can be associated with excessively high computational costs in terms of run time and memory. We apply a strategy for reliable parameter estimation where different modeling approaches with increasing complexity are used that build on one another. This bottom-up modeling approach is applied to an experimental human whole-blood infection assay for Candida albicans. Aiming for the quantification of the relative impact of different routes of the immune response against this human-pathogenic fungus, we start from a non-spatial state-based model (SBM), because this level of model complexity allows estimating a priori unknown transition rates between various system states by the global optimization method simulated annealing. Building on the non-spatial SBM, an agent-based model (ABM) is implemented that incorporates the migration of interacting cells in three-dimensional space. The ABM takes advantage of estimated parameters from the non-spatial SBM, leading to a decreased dimensionality of the parameter space. This space can be scanned using a local optimization approach, i.e., least-squares error estimation based on an adaptive regular grid search, to predict cell migration parameters that are not accessible in experiment. In the future, spatio-temporal simulations of whole-blood samples may enable timely stratification of sepsis patients by distinguishing hyper-inflammatory from paralytic phases in immune dysregulation.

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

Lopez-Ruiz, R.; Nagy, A.; Romera, E.

A two-parameter family of complexity measures C-tilde{sup ({alpha},{beta})} based on the Renyi entropies is introduced and characterized by a detailed study of its mathematical properties. This family is the generalization of a continuous version of the Lopez-Ruiz-Mancini-Calbet complexity, which is recovered for {alpha}=1 and {beta}=2. These complexity measures are obtained by multiplying two quantities bringing global information on the probability distribution defining the system. When one of the parameters, {alpha} or {beta}, goes to infinity, one of the global factors becomes a local factor. For this special case, the complexity is calculated on different quantum systems: H-atom, harmonic oscillator, andmore » square well.« less

Comparison of Degrees of Potential-Energy-Surface Anharmonicity for Complexes and Clusters with Hydrogen Bonds

NASA Astrophysics Data System (ADS)

Kozlovskaya, E. N.; Doroshenko, I. Yu.; Pogorelov, V. E.; Vaskivskyi, Ye. V.; Pitsevich, G. A.

2018-01-01

Previously calculated multidimensional potential-energy surfaces of the MeOH monomer and dimer, water dimer, malonaldehyde, formic acid dimer, free pyridine-N-oxide/trichloroacetic acid complex, and protonated water dimer were analyzed. The corresponding harmonic potential-energy surfaces near the global minima were constructed for series of clusters and complexes with hydrogen bonds of different strengths based on the behavior of the calculated multidimensional potential-energy surfaces. This enabled the introduction of an obvious anharmonicity parameter for the calculated potential-energy surfaces. The anharmonicity parameter was analyzed as functions of the size of the analyzed area near the energy minimum, the number of points over which energies were compared, and the dimensionality of the solved vibrational problem. Anharmonicity parameters for potential-energy surfaces in complexes with strong, medium, and weak H-bonds were calculated under identical conditions. The obtained anharmonicity parameters were compared with the corresponding diagonal anharmonicity constants for stretching vibrations of the bridging protons and the lengths of the hydrogen bridges.

Plasma Parameters From Reentry Signal Attenuation

DOE PAGES

Statom, T. K.

2018-02-27

This study presents the application of a theoretically developed method that provides plasma parameter solution space information from measured RF attenuation that occurs during reentry. The purpose is to provide reentry plasma parameter information from the communication signal attenuation. The theoretical development centers around the attenuation and the complex index of refraction. The methodology uses an imaginary index of the refraction matching algorithm with a tolerance to find suitable solutions that satisfy the theory. The imaginary matching terms are then used to determine the real index of refraction resulting in the complex index of refraction. Then a filter is usedmore » to reject nonphysical solutions. Signal attenuation-based plasma parameter properties investigated include the complex index of refraction, plasma frequency, electron density, collision frequency, propagation constant, attenuation constant, phase constant, complex plasma conductivity, and electron mobility. RF plasma thickness attenuation is investigated and compared to the literature. Finally, similar plasma thickness for a specific signal attenuation can have different plasma properties.« less

Plasma Parameters From Reentry Signal Attenuation

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

Statom, T. K.

This study presents the application of a theoretically developed method that provides plasma parameter solution space information from measured RF attenuation that occurs during reentry. The purpose is to provide reentry plasma parameter information from the communication signal attenuation. The theoretical development centers around the attenuation and the complex index of refraction. The methodology uses an imaginary index of the refraction matching algorithm with a tolerance to find suitable solutions that satisfy the theory. The imaginary matching terms are then used to determine the real index of refraction resulting in the complex index of refraction. Then a filter is usedmore » to reject nonphysical solutions. Signal attenuation-based plasma parameter properties investigated include the complex index of refraction, plasma frequency, electron density, collision frequency, propagation constant, attenuation constant, phase constant, complex plasma conductivity, and electron mobility. RF plasma thickness attenuation is investigated and compared to the literature. Finally, similar plasma thickness for a specific signal attenuation can have different plasma properties.« less

An Improved Method to Control the Critical Parameters of a Multivariable Control System

NASA Astrophysics Data System (ADS)

Subha Hency Jims, P.; Dharmalingam, S.; Wessley, G. Jims John

2017-10-01

The role of control systems is to cope with the process deficiencies and the undesirable effect of the external disturbances. Most of the multivariable processes are highly iterative and complex in nature. Aircraft systems, Modern Power Plants, Refineries, Robotic systems are few such complex systems that involve numerous critical parameters that need to be monitored and controlled. Control of these important parameters is not only tedious and cumbersome but also is crucial from environmental, safety and quality perspective. In this paper, one such multivariable system, namely, a utility boiler has been considered. A modern power plant is a complex arrangement of pipework and machineries with numerous interacting control loops and support systems. In this paper, the calculation of controller parameters based on classical tuning concepts has been presented. The controller parameters thus obtained and employed has controlled the critical parameters of a boiler during fuel switching disturbances. The proposed method can be applied to control the critical parameters like elevator, aileron, rudder, elevator trim rudder and aileron trim, flap control systems of aircraft systems.

Simple Proof of Jury Test for Complex Polynomials

NASA Astrophysics Data System (ADS)

Choo, Younseok; Kim, Dongmin

Recently some attempts have been made in the literature to give simple proofs of Jury test for real polynomials. This letter presents a similar result for complex polynomials. A simple proof of Jury test for complex polynomials is provided based on the Rouché's Theorem and a single-parameter characterization of Schur stability property for complex polynomials.

Parrondo's games based on complex networks and the paradoxical effect.

PubMed

Ye, Ye; Wang, Lu; Xie, Nenggang

2013-01-01

Parrondo's games were first constructed using a simple tossing scenario, which demonstrates the following paradoxical situation: in sequences of games, a winning expectation may be obtained by playing the games in a random order, although each game (game A or game B) in the sequence may result in losing when played individually. The available Parrondo's games based on the spatial niche (the neighboring environment) are applied in the regular networks. The neighbors of each node are the same in the regular graphs, whereas they are different in the complex networks. Here, Parrondo's model based on complex networks is proposed, and a structure of game B applied in arbitrary topologies is constructed. The results confirm that Parrondo's paradox occurs. Moreover, the size of the region of the parameter space that elicits Parrondo's paradox depends on the heterogeneity of the degree distributions of the networks. The higher heterogeneity yields a larger region of the parameter space where the strong paradox occurs. In addition, we use scale-free networks to show that the network size has no significant influence on the region of the parameter space where the strong or weak Parrondo's paradox occurs. The region of the parameter space where the strong Parrondo's paradox occurs reduces slightly when the average degree of the network increases.

Synthesis, spectral characterization, molecular modeling, biological activity and potentiometric studies of 4-amino-5-mercapto-3-methyl-S-triazole Schiff's base complexes

NASA Astrophysics Data System (ADS)

Alaghaz, Abdel-Nasser M. A.; Zayed, Mohamed E.; Alharbi, Suliman A.

2015-03-01

The Schiff's base derived from condensation of s-triazole (4-amino-5-mercapto-3-methyl-S-triazole) with pyridine-2-aldehyde and their corresponding Mn(II), Co(II), Ni(II), Cu(II) and Zn(II) complexes have been synthesized. The isolated solid complexes were characterized by elemental analyses, molar conductance, spectral (IR, UV-Vis, 1H NMR, mass), magnetic moment and thermal measurements. The IR spectral data suggest that the ligand coordinate in a tridentate manner (SNN) via the one thiol (SH), one pyridine ring and the azomethine (Cdbnd N) groups. The data show that the complexes have composition of ML2 type. The activation of thermodynamic parameters are calculated using Coats-Redfern, Horowitz-Metzger (HM), and Piloyan-Novikova (PN). The octahedral geometry of the complexes is confirmed using DFT method from DMOL3 calculations and ligand field parameters. Protonation constants of Schiff base and stability constants of their binary metal complexes have been determined potentiometrically in 50% DMSO-water media at 25 °C and ionic strength 0.10 M potassium nitrate. The biological activity of these compounds against various fungi has been investigated.

Model-based analysis of coupled equilibrium-kinetic processes: indirect kinetic studies of thermodynamic parameters using the dynamic data.

PubMed

Emami, Fereshteh; Maeder, Marcel; Abdollahi, Hamid

2015-05-07

Thermodynamic studies of equilibrium chemical reactions linked with kinetic procedures are mostly impossible by traditional approaches. In this work, the new concept of generalized kinetic study of thermodynamic parameters is introduced for dynamic data. The examples of equilibria intertwined with kinetic chemical mechanisms include molecular charge transfer complex formation reactions, pH-dependent degradation of chemical compounds and tautomerization kinetics in micellar solutions. Model-based global analysis with the possibility of calculating and embedding the equilibrium and kinetic parameters into the fitting algorithm has allowed the complete analysis of the complex reaction mechanisms. After the fitting process, the optimal equilibrium and kinetic parameters together with an estimate of their standard deviations have been obtained. This work opens up a promising new avenue for obtaining equilibrium constants through the kinetic data analysis for the kinetic reactions that involve equilibrium processes.

Solid phase extraction of copper(II) by fixed bed procedure on cation exchange complexing resins.

PubMed

Pesavento, Maria; Sturini, Michela; D'Agostino, Girolamo; Biesuz, Raffaela

2010-02-19

The efficiency of the metal ion recovery by solid phase extraction (SPE) in complexing resins columns is predicted by a simple model based on two parameters reflecting the sorption equilibria and kinetics of the metal ion on the considered resin. The parameter related to the adsorption equilibria was evaluated by the Gibbs-Donnan model, and that related to the kinetics by assuming that the ion exchange is the adsorption rate determining step. The predicted parameters make it possible to evaluate the breakthrough volume of the considered metal ion, Cu(II), from different kinds of complexing resins, and at different conditions, such as acidity and ionic composition. Copyright 2009. Published by Elsevier B.V.

Evaluating Text Complexity and Flesch-Kincaid Grade Level

ERIC Educational Resources Information Center

Solnyshkina, Marina I.; Zamaletdinov, Radif R.; Gorodetskaya, Ludmila A.; Gabitov, Azat I.

2017-01-01

The article presents the results of an exploratory study of the use of T.E.R.A., an automated tool measuring text complexity and readability based on the assessment of five text complexity parameters: narrativity, syntactic simplicity, word concreteness, referential cohesion and deep cohesion. Aimed at finding ways to utilize T.E.R.A. for…

A novel prediction method about single components of analog circuits based on complex field modeling.

PubMed

Zhou, Jingyu; Tian, Shulin; Yang, Chenglin

2014-01-01

Few researches pay attention to prediction about analog circuits. The few methods lack the correlation with circuit analysis during extracting and calculating features so that FI (fault indicator) calculation often lack rationality, thus affecting prognostic performance. To solve the above problem, this paper proposes a novel prediction method about single components of analog circuits based on complex field modeling. Aiming at the feature that faults of single components hold the largest number in analog circuits, the method starts with circuit structure, analyzes transfer function of circuits, and implements complex field modeling. Then, by an established parameter scanning model related to complex field, it analyzes the relationship between parameter variation and degeneration of single components in the model in order to obtain a more reasonable FI feature set via calculation. According to the obtained FI feature set, it establishes a novel model about degeneration trend of analog circuits' single components. At last, it uses particle filter (PF) to update parameters for the model and predicts remaining useful performance (RUP) of analog circuits' single components. Since calculation about the FI feature set is more reasonable, accuracy of prediction is improved to some extent. Finally, the foregoing conclusions are verified by experiments.

Identifying Typhoon Tracks based on Event Synchronization derived Spatially Embedded Climate Networks

NASA Astrophysics Data System (ADS)

Ozturk, Ugur; Marwan, Norbert; Kurths, Jürgen

2017-04-01

Complex networks are commonly used for investigating spatiotemporal dynamics of complex systems, e.g. extreme rainfall. Especially directed networks are very effective tools in identifying climatic patterns on spatially embedded networks. They can capture the network flux, so as the principal dynamics of spreading significant phenomena. Network measures, such as network divergence, bare the source-receptor relation of the directed networks. However, it is still a challenge how to catch fast evolving atmospheric events, i.e. typhoons. In this study, we propose a new technique, namely Radial Ranks, to detect the general pattern of typhoons forward direction based on the strength parameter of the event synchronization over Japan. We suggest to subset a circular zone of high correlation around the selected grid based on the strength parameter. Radial sums of the strength parameter along vectors within this zone, radial ranks are measured for potential directions, which allows us to trace the network flux over long distances. We employed also the delay parameter of event synchronization to identify and separate the frontal storms' and typhoons' individual behaviors.

Calibration of an Unsteady Groundwater Flow Model for a Complex, Strongly Heterogeneous Aquifer

NASA Astrophysics Data System (ADS)

Curtis, Z. K.; Liao, H.; Li, S. G.; Phanikumar, M. S.; Lusch, D.

2016-12-01

Modeling of groundwater systems characterized by complex three-dimensional structure and heterogeneity remains a significant challenge. Most of today's groundwater models are developed based on relatively simple conceptual representations in favor of model calibratibility. As more complexities are modeled, e.g., by adding more layers and/or zones, or introducing transient processes, more parameters have to be estimated and issues related to ill-posed groundwater problems and non-unique calibration arise. Here, we explore the use of an alternative conceptual representation for groundwater modeling that is fully three-dimensional and can capture complex 3D heterogeneity (both systematic and "random") without over-parameterizing the aquifer system. In particular, we apply Transition Probability (TP) geostatistics on high resolution borehole data from a water well database to characterize the complex 3D geology. Different aquifer material classes, e.g., `AQ' (aquifer material), `MAQ' (marginal aquifer material'), `PCM' (partially confining material), and `CM' (confining material), are simulated, with the hydraulic properties of each material type as tuning parameters during calibration. The TP-based approach is applied to simulate unsteady groundwater flow in a large, complex, and strongly heterogeneous glacial aquifer system in Michigan across multiple spatial and temporal scales. The resulting model is calibrated to observed static water level data over a time span of 50 years. The results show that the TP-based conceptualization enables much more accurate and robust calibration/simulation than that based on conventional deterministic layer/zone based conceptual representations.

Technical Note: Approximate Bayesian parameterization of a process-based tropical forest model

NASA Astrophysics Data System (ADS)

Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.

2014-02-01

Inverse parameter estimation of process-based models is a long-standing problem in many scientific disciplines. A key question for inverse parameter estimation is how to define the metric that quantifies how well model predictions fit to the data. This metric can be expressed by general cost or objective functions, but statistical inversion methods require a particular metric, the probability of observing the data given the model parameters, known as the likelihood. For technical and computational reasons, likelihoods for process-based stochastic models are usually based on general assumptions about variability in the observed data, and not on the stochasticity generated by the model. Only in recent years have new methods become available that allow the generation of likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional Markov chain Monte Carlo (MCMC) sampler, performs well in retrieving known parameter values from virtual inventory data generated by the forest model. We analyze the results of the parameter estimation, examine its sensitivity to the choice and aggregation of model outputs and observed data (summary statistics), and demonstrate the application of this method by fitting the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss how this approach differs from approximate Bayesian computation (ABC), another method commonly used to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation, can be successfully applied to process-based models of high complexity. The methodology is particularly suitable for heterogeneous and complex data structures and can easily be adjusted to other model types, including most stochastic population and individual-based models. Our study therefore provides a blueprint for a fairly general approach to parameter estimation of stochastic process-based models.

Spectral characterization, cyclic voltammetry, morphology, biological activities and DNA cleaving studies of amino acid Schiff base metal(II) complexes

NASA Astrophysics Data System (ADS)

Neelakantan, M. A.; Rusalraj, F.; Dharmaraja, J.; Johnsonraja, S.; Jeyakumar, T.; Sankaranarayana Pillai, M.

2008-12-01

Metal complexes are synthesized with Schiff bases derived from o-phthalaldehyde (opa) and amino acids viz., glycine (gly) L-alanine (ala), L-phenylalanine (pal). Metal ions coordinate in a tetradentate or hexadentate manner with these N 2O 2 donor ligands, which are characterized by elemental analysis, molar conductance, magnetic moments, IR, electronic, 1H NMR and EPR spectral studies. The elemental analysis suggests the stoichiometry to be 1:1 (metal:ligand). Based on EPR studies, spin-Hamiltonian and bonding parameters have been calculated. The g-values calculated for copper complexes at 300 K and in frozen DMSO (77 K) indicate the presence of the unpaired electron in the d orbital. The evaluated metal-ligand bonding parameters showed strong in-plane σ- and π-bonding. X-ray diffraction (XRD) and scanning electron micrography (SEM) analysis provide the crystalline nature and the morphology of the metal complexes. The cyclic voltammograms of the Cu(II)/Mn(II)/VO(II) complexes investigated in DMSO solution exhibit metal centered electroactivity in the potential range -1.5 to +1.5 V. The electrochemical data obtained for Cu(II) complexes explains the change of structural arrangement of the ligand around Cu(II) ions. The biological activity of the complexes has been tested on eight bacteria and three fungi. Cu(II) and Ni(II) complexes show an increased activity in comparison to the controls. The metal complexes of opapal Schiff base were evaluated for their DNA cleaving activities with calf-thymus DNA (CT DNA) under aerobic conditions. Cu(II) and VO(II) complexes show more pronounced activity in presence of the oxidant.

A unified inversion scheme to process multifrequency measurements of various dispersive electromagnetic properties

NASA Astrophysics Data System (ADS)

Han, Y.; Misra, S.

2018-04-01

Multi-frequency measurement of a dispersive electromagnetic (EM) property, such as electrical conductivity, dielectric permittivity, or magnetic permeability, is commonly analyzed for purposes of material characterization. Such an analysis requires inversion of the multi-frequency measurement based on a specific relaxation model, such as Cole-Cole model or Pelton's model. We develop a unified inversion scheme that can be coupled to various type of relaxation models to independently process multi-frequency measurement of varied EM properties for purposes of improved EM-based geomaterial characterization. The proposed inversion scheme is firstly tested in few synthetic cases in which different relaxation models are coupled into the inversion scheme and then applied to multi-frequency complex conductivity, complex resistivity, complex permittivity, and complex impedance measurements. The method estimates up to seven relaxation-model parameters exhibiting convergence and accuracy for random initializations of the relaxation-model parameters within up to 3-orders of magnitude variation around the true parameter values. The proposed inversion method implements a bounded Levenberg algorithm with tuning initial values of damping parameter and its iterative adjustment factor, which are fixed in all the cases shown in this paper and irrespective of the type of measured EM property and the type of relaxation model. Notably, jump-out step and jump-back-in step are implemented as automated methods in the inversion scheme to prevent the inversion from getting trapped around local minima and to honor physical bounds of model parameters. The proposed inversion scheme can be easily used to process various types of EM measurements without major changes to the inversion scheme.

Design of experiments for identification of complex biochemical systems with applications to mitochondrial bioenergetics.

PubMed

Vinnakota, Kalyan C; Beard, Daniel A; Dash, Ranjan K

2009-01-01

Identification of a complex biochemical system model requires appropriate experimental data. Models constructed on the basis of data from the literature often contain parameters that are not identifiable with high sensitivity and therefore require additional experimental data to identify those parameters. Here we report the application of a local sensitivity analysis to design experiments that will improve the identifiability of previously unidentifiable model parameters in a model of mitochondrial oxidative phosphorylation and tricaboxylic acid cycle. Experiments were designed based on measurable biochemical reactants in a dilute suspension of purified cardiac mitochondria with experimentally feasible perturbations to this system. Experimental perturbations and variables yielding the most number of parameters above a 5% sensitivity level are presented and discussed.

Intelligent methods for the process parameter determination of plastic injection molding

NASA Astrophysics Data System (ADS)

Gao, Huang; Zhang, Yun; Zhou, Xundao; Li, Dequn

2018-03-01

Injection molding is one of the most widely used material processing methods in producing plastic products with complex geometries and high precision. The determination of process parameters is important in obtaining qualified products and maintaining product quality. This article reviews the recent studies and developments of the intelligent methods applied in the process parameter determination of injection molding. These intelligent methods are classified into three categories: Case-based reasoning methods, expert system- based methods, and data fitting and optimization methods. A framework of process parameter determination is proposed after comprehensive discussions. Finally, the conclusions and future research topics are discussed.

A study of the electrical properties of complex resistor network based on NW model

NASA Astrophysics Data System (ADS)

Chang, Yunfeng; Li, Yunting; Yang, Liu; Guo, Lu; Liu, Gaochao

2015-04-01

The power and resistance of two-port complex resistor network based on NW small world network model are studied in this paper. Mainly, we study the dependence of the network power and resistance on the degree of port vertices, the connection probability and the shortest distance. Qualitative analysis and a simplified formula for network resistance are given out. Finally, we define a branching parameter and give out its physical meaning in the analysis of complex resistor network.

Complexity dynamics and Hopf bifurcation analysis based on the first Lyapunov coefficient about 3D IS-LM macroeconomics system

NASA Astrophysics Data System (ADS)

Ma, Junhai; Ren, Wenbo; Zhan, Xueli

2017-04-01

Based on the study of scholars at home and abroad, this paper improves the three-dimensional IS-LM model in macroeconomics, analyzes the equilibrium point of the system and stability conditions, focuses on the parameters and complex dynamic characteristics when Hopf bifurcation occurs in the three-dimensional IS-LM macroeconomics system. In order to analyze the stability of limit cycles when Hopf bifurcation occurs, this paper further introduces the first Lyapunov coefficient to judge the limit cycles, i.e. from a practical view of the business cycle. Numerical simulation results show that within the range of most of the parameters, the limit cycle of 3D IS-LM macroeconomics is stable, that is, the business cycle is stable; with the increase of the parameters, limit cycles becomes unstable, and the value range of the parameters in this situation is small. The research results of this paper have good guide significance for the analysis of macroeconomics system.

Efficient Characterization of Parametric Uncertainty of Complex (Bio)chemical Networks.

PubMed

Schillings, Claudia; Sunnåker, Mikael; Stelling, Jörg; Schwab, Christoph

2015-08-01

Parametric uncertainty is a particularly challenging and relevant aspect of systems analysis in domains such as systems biology where, both for inference and for assessing prediction uncertainties, it is essential to characterize the system behavior globally in the parameter space. However, current methods based on local approximations or on Monte-Carlo sampling cope only insufficiently with high-dimensional parameter spaces associated with complex network models. Here, we propose an alternative deterministic methodology that relies on sparse polynomial approximations. We propose a deterministic computational interpolation scheme which identifies most significant expansion coefficients adaptively. We present its performance in kinetic model equations from computational systems biology with several hundred parameters and state variables, leading to numerical approximations of the parametric solution on the entire parameter space. The scheme is based on adaptive Smolyak interpolation of the parametric solution at judiciously and adaptively chosen points in parameter space. As Monte-Carlo sampling, it is "non-intrusive" and well-suited for massively parallel implementation, but affords higher convergence rates. This opens up new avenues for large-scale dynamic network analysis by enabling scaling for many applications, including parameter estimation, uncertainty quantification, and systems design.

Efficient Characterization of Parametric Uncertainty of Complex (Bio)chemical Networks

PubMed Central

Schillings, Claudia; Sunnåker, Mikael; Stelling, Jörg; Schwab, Christoph

2015-01-01

Parametric uncertainty is a particularly challenging and relevant aspect of systems analysis in domains such as systems biology where, both for inference and for assessing prediction uncertainties, it is essential to characterize the system behavior globally in the parameter space. However, current methods based on local approximations or on Monte-Carlo sampling cope only insufficiently with high-dimensional parameter spaces associated with complex network models. Here, we propose an alternative deterministic methodology that relies on sparse polynomial approximations. We propose a deterministic computational interpolation scheme which identifies most significant expansion coefficients adaptively. We present its performance in kinetic model equations from computational systems biology with several hundred parameters and state variables, leading to numerical approximations of the parametric solution on the entire parameter space. The scheme is based on adaptive Smolyak interpolation of the parametric solution at judiciously and adaptively chosen points in parameter space. As Monte-Carlo sampling, it is “non-intrusive” and well-suited for massively parallel implementation, but affords higher convergence rates. This opens up new avenues for large-scale dynamic network analysis by enabling scaling for many applications, including parameter estimation, uncertainty quantification, and systems design. PMID:26317784

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

Xia, Shuangluo; Vashishtha, Ashwani; Bulkley, David

During DNA synthesis, base stacking and Watson-Crick (WC) hydrogen bonding increase the stability of nascent base pairs when they are in a ternary complex. To evaluate the contribution of base stacking to the incorporation efficiency of dNTPs when a DNA polymerase encounters an abasic site, we varied the penultimate base pairs (PBs) adjacent to the abasic site using all 16 possible combinations. We then determined pre-steady-state kinetic parameters with an RB69 DNA polymerase variant and solved nine structures of the corresponding ternary complexes. The efficiency of incorporation for incoming dNTPs opposite an abasic site varied between 2- and 210-fold dependingmore » on the identity of the PB. We propose that the A rule can be extended to encompass the fact that DNA polymerase can bypass dA/abasic sites more efficiently than other dN/abasic sites. Crystal structures of the ternary complexes show that the surface of the incoming base was stacked against the PB's interface and that the kinetic parameters for dNMP incorporation were consistent with specific features of base stacking, such as surface area and partial charge-charge interactions between the incoming base and the PB. Without a templating nucleotide residue, an incoming dNTP has no base with which it can hydrogen bond and cannot be desolvated, so that these surrounding water molecules become ordered and remain on the PB's surface in the ternary complex. When these water molecules are on top of a hydrophobic patch on the PB, they destabilize the ternary complex, and the incorporation efficiency of incoming dNTPs is reduced.« less

Genetic algorithm based input selection for a neural network function approximator with applications to SSME health monitoring

NASA Technical Reports Server (NTRS)

Peck, Charles C.; Dhawan, Atam P.; Meyer, Claudia M.

1991-01-01

A genetic algorithm is used to select the inputs to a neural network function approximator. In the application considered, modeling critical parameters of the space shuttle main engine (SSME), the functional relationship between measured parameters is unknown and complex. Furthermore, the number of possible input parameters is quite large. Many approaches have been used for input selection, but they are either subjective or do not consider the complex multivariate relationships between parameters. Due to the optimization and space searching capabilities of genetic algorithms they were employed to systematize the input selection process. The results suggest that the genetic algorithm can generate parameter lists of high quality without the explicit use of problem domain knowledge. Suggestions for improving the performance of the input selection process are also provided.

Physics-based statistical model and simulation method of RF propagation in urban environments

DOEpatents

Pao, Hsueh-Yuan; Dvorak, Steven L.

2010-09-14

A physics-based statistical model and simulation/modeling method and system of electromagnetic wave propagation (wireless communication) in urban environments. In particular, the model is a computationally efficient close-formed parametric model of RF propagation in an urban environment which is extracted from a physics-based statistical wireless channel simulation method and system. The simulation divides the complex urban environment into a network of interconnected urban canyon waveguides which can be analyzed individually; calculates spectral coefficients of modal fields in the waveguides excited by the propagation using a database of statistical impedance boundary conditions which incorporates the complexity of building walls in the propagation model; determines statistical parameters of the calculated modal fields; and determines a parametric propagation model based on the statistical parameters of the calculated modal fields from which predictions of communications capability may be made.

Manufacturing complexity analysis

NASA Technical Reports Server (NTRS)

Delionback, L. M.

1977-01-01

The analysis of the complexity of a typical system is presented. Starting with the subsystems of an example system, the step-by-step procedure for analysis of the complexity of an overall system is given. The learning curves for the various subsystems are determined as well as the concurrent numbers of relevant design parameters. Then trend curves are plotted for the learning curve slopes versus the various design-oriented parameters, e.g. number of parts versus slope of learning curve, or number of fasteners versus slope of learning curve, etc. Representative cuts are taken from each trend curve, and a figure-of-merit analysis is made for each of the subsystems. Based on these values, a characteristic curve is plotted which is indicative of the complexity of the particular subsystem. Each such characteristic curve is based on a universe of trend curve data taken from data points observed for the subsystem in question. Thus, a characteristic curve is developed for each of the subsystems in the overall system.

Multidimensional correlation among plan complexity, quality and deliverability parameters for volumetric-modulated arc therapy using canonical correlation analysis.

PubMed

Shen, Lanxiao; Chen, Shan; Zhu, Xiaoyang; Han, Ce; Zheng, Xiaomin; Deng, Zhenxiang; Zhou, Yongqiang; Gong, Changfei; Xie, Congying; Jin, Xiance

2018-03-01

A multidimensional exploratory statistical method, canonical correlation analysis (CCA), was applied to evaluate the impact of complexity parameters on the plan quality and deliverability of volumetric-modulated arc therapy (VMAT) and to determine parameters in the generation of an ideal VMAT plan. Canonical correlations among complexity, quality and deliverability parameters of VMAT, as well as the contribution weights of different parameters were investigated with 71 two-arc VMAT nasopharyngeal cancer (NPC) patients, and further verified with 28 one-arc VMAT prostate cancer patients. The average MU and MU per control point (MU/CP) for two-arc VMAT plans were 702.6 ± 55.7 and 3.9 ± 0.3 versus 504.6 ± 99.2 and 5.6 ± 1.1 for one-arc VMAT plans, respectively. The individual volume-based 3D gamma passing rates of clinical target volume (γCTV) and planning target volume (γPTV) for NPC and prostate cancer patients were 85.7% ± 9.0% vs 92.6% ± 7.8%, and 88.0% ± 7.6% vs 91.2% ± 7.7%, respectively. Plan complexity parameters of NPC patients were correlated with plan quality (P = 0.047) and individual volume-based 3D gamma indices γ(IV) (P = 0.01), in which, MU/CP and segment area (SA) per control point (SA/CP) were weighted highly in correlation with γ(IV) , and SA/CP, percentage of CPs with SA < 5 × 5 cm2 (%SA < 5 × 5 cm2) and PTV volume were weighted highly in correlation with plan quality with coefficients of 0.98, 0.68 and -0.99, respectively. Further verification with one-arc VMAT plans demonstrated similar results. In conclusion, MU, SA-related parameters and PTV volume were found to have strong effects on the plan quality and deliverability.

Multidimensional correlation among plan complexity, quality and deliverability parameters for volumetric-modulated arc therapy using canonical correlation analysis

PubMed Central

Shen, Lanxiao; Chen, Shan; Zhu, Xiaoyang; Han, Ce; Zheng, Xiaomin; Deng, Zhenxiang; Zhou, Yongqiang; Gong, Changfei; Jin, Xiance

2018-01-01

Abstract A multidimensional exploratory statistical method, canonical correlation analysis (CCA), was applied to evaluate the impact of complexity parameters on the plan quality and deliverability of volumetric-modulated arc therapy (VMAT) and to determine parameters in the generation of an ideal VMAT plan. Canonical correlations among complexity, quality and deliverability parameters of VMAT, as well as the contribution weights of different parameters were investigated with 71 two-arc VMAT nasopharyngeal cancer (NPC) patients, and further verified with 28 one-arc VMAT prostate cancer patients. The average MU and MU per control point (MU/CP) for two-arc VMAT plans were 702.6 ± 55.7 and 3.9 ± 0.3 versus 504.6 ± 99.2 and 5.6 ± 1.1 for one-arc VMAT plans, respectively. The individual volume-based 3D gamma passing rates of clinical target volume (γCTV) and planning target volume (γPTV) for NPC and prostate cancer patients were 85.7% ± 9.0% vs 92.6% ± 7.8%, and 88.0% ± 7.6% vs 91.2% ± 7.7%, respectively. Plan complexity parameters of NPC patients were correlated with plan quality (P = 0.047) and individual volume-based 3D gamma indices γ(IV) (P = 0.01), in which, MU/CP and segment area (SA) per control point (SA/CP) were weighted highly in correlation with γ(IV) , and SA/CP, percentage of CPs with SA < 5 × 5 cm2 (%SA < 5 × 5 cm2) and PTV volume were weighted highly in correlation with plan quality with coefficients of 0.98, 0.68 and −0.99, respectively. Further verification with one-arc VMAT plans demonstrated similar results. In conclusion, MU, SA-related parameters and PTV volume were found to have strong effects on the plan quality and deliverability. PMID:29415196

Entropy and equilibrium via games of complexity

NASA Astrophysics Data System (ADS)

Topsøe, Flemming

2004-09-01

It is suggested that thermodynamical equilibrium equals game theoretical equilibrium. Aspects of this thesis are discussed. The philosophy is consistent with maximum entropy thinking of Jaynes, but goes one step deeper by deriving the maximum entropy principle from an underlying game theoretical principle. The games introduced are based on measures of complexity. Entropy is viewed as minimal complexity. It is demonstrated that Tsallis entropy ( q-entropy) and Kaniadakis entropy ( κ-entropy) can be obtained in this way, based on suitable complexity measures. A certain unifying effect is obtained by embedding these measures in a two-parameter family of entropy functions.

New tetradentate Schiff bases of 2-amino-3,5-dibromobenzaldehyde with aliphatic diamines and their metal complexes: synthesis, characterization and thermal stability.

PubMed

Mohammadi, Khosro; Azad, Seyyedeh Sedigheh; Amoozegar, Ameneh

2015-07-05

The tetradentate Schiff base ligands (L(1)-L(4)), were synthesized by reaction between 2-amino-3,5-dibromobenzaldehyde and aliphatic diamines. Then, nickel and oxovanadium(IV) complexes of these ligands were synthesized and characterized by (1)H NMR, Mass, IR, UV-Vis spectroscopy and thermogravimetry. The kinetic parameters of oxovanadium(IV) complexes were calculated from thermal studies. According to the results of thermogravimetric data, the thermal stability of oxovanadium(IV) complexes is as follow: [Formula: see text]. Copyright © 2015 Elsevier B.V. All rights reserved.

Sampling ARG of multiple populations under complex configurations of subdivision and admixture.

PubMed

Carrieri, Anna Paola; Utro, Filippo; Parida, Laxmi

2016-04-01

Simulating complex evolution scenarios of multiple populations is an important task for answering many basic questions relating to population genomics. Apart from the population samples, the underlying Ancestral Recombinations Graph (ARG) is an additional important means in hypothesis checking and reconstruction studies. Furthermore, complex simulations require a plethora of interdependent parameters making even the scenario-specification highly non-trivial. We present an algorithm SimRA that simulates generic multiple population evolution model with admixture. It is based on random graphs that improve dramatically in time and space requirements of the classical algorithm of single populations.Using the underlying random graphs model, we also derive closed forms of expected values of the ARG characteristics i.e., height of the graph, number of recombinations, number of mutations and population diversity in terms of its defining parameters. This is crucial in aiding the user to specify meaningful parameters for the complex scenario simulations, not through trial-and-error based on raw compute power but intelligent parameter estimation. To the best of our knowledge this is the first time closed form expressions have been computed for the ARG properties. We show that the expected values closely match the empirical values through simulations.Finally, we demonstrate that SimRA produces the ARG in compact forms without compromising any accuracy. We demonstrate the compactness and accuracy through extensive experiments. SimRA (Simulation based on Random graph Algorithms) source, executable, user manual and sample input-output sets are available for downloading at: https://github.com/ComputationalGenomics/SimRA CONTACT: : parida@us.ibm.com Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Complex-ordered patterns in shaken convection.

PubMed

Rogers, Jeffrey L; Pesch, Werner; Brausch, Oliver; Schatz, Michael F

2005-06-01

We report and analyze complex patterns observed in a combination of two standard pattern forming experiments. These exotic states are composed of two distinct spatial scales, each displaying a different temporal dependence. The system is a fluid layer experiencing forcing from both a vertical temperature difference and vertical time-periodic oscillations. Depending on the parameters these forcing mechanisms produce fluid motion with either a harmonic or a subharmonic temporal response. Over a parameter range where these mechanisms have comparable influence the spatial scales associated with both responses are found to coexist, resulting in complex, yet highly ordered patterns. Phase diagrams of this region are reported and criteria to define the patterns as quasiperiodic crystals or superlattices are presented. These complex patterns are found to satisfy four-mode (resonant tetrad) conditions. The qualitative difference between the present formation mechanism and the resonant triads ubiquitously used to explain complex-ordered patterns in other nonequilibrium systems is discussed. The only exception to quantitative agreement between our analysis based on Boussinesq equations and laboratory investigations is found to be the result of breaking spatial symmetry in a small parameter region near onset.

The Influence of Solvent on the Structural Properties of trans-(NHC)PtI2Py Complex: A Platinum-Based Anticancer Drug

NASA Astrophysics Data System (ADS)

Sadigh Vishkaee, Teherh; Fazaeli, Reza

2018-06-01

Quantum chemical calculations using MPW1PW91 method were applied to analyze the solvent effect on the structural, spectral, and thermochemical parameters for a platinum-based anticancer drug trans-(NHC)PtI2Py complex. The solvent effects were examined by the self-consistent reaction field theory (SCRF) based on Polarizable Continuum Model (PCM). The linear correlations between the solvation energies, HOMO-LUMO gaps, IR-active stretching vibration of Pt-N bonds and N-H of NHC ligand with dielectric constants of solvents were studied. The wave numbers of these IR-active stretching vibrations in different solvents were correlated with the Kirkwood-Bauer-Magat equation (KBM). The thermodynamic activation parameter such free energy of solvation, enthalpy of solvation were also calculated.

Simultaneous determination of thermodynamic and kinetic parameters of aminopolycarbonate complexes of cobalt(II) and nickel(II) based on isothermal titration calorimetry data.

PubMed

Tesmar, Aleksandra; Wyrzykowski, Dariusz; Muñoz, Eva; Pilarski, Bogusław; Pranczk, Joanna; Jacewicz, Dagmara; Chmurzyński, Lech

2017-04-01

The influence of the different side chain residues on the thermodynamic and kinetic parameters for complexation reactions of the Co 2 + and Ni 2 + ions has been investigated by using the isothermal titration calorimetry (ITC) technique supported by potentiometric titration data. The study was concerned with the 2 common tripodal aminocarboxylate ligands, namely, nitrilotriacetic acid and N-(2-hydroxyethyl) iminodiacetic acid. Calorimetric measurements (ITC) were run in the 2-(N-morpholino)ethanesulfonic acid hydrate (2-(N-morpholino) ethanesulfonic acid), piperazine-N,N'-bis(2-ethanesulfonic acid), and dimethylarsenic acid buffers (0.1 mol L -1 , pH 6) at 298.15 K. The quantification of the metal-buffer interactions and their incorporation into the ITC data analysis enabled to obtain the pH-independent and buffer-independent thermodynamic parameters (K, ΔG, ΔH, and ΔS) for the reactions under study. Furthermore, the kinITC method was applied to obtain kinetic information on complexation reactions from the ITC data. Correlations, based on kinetic and thermodynamic data, between the kinetics of formation of Co 2 + and Ni 2 + complexes and their thermodynamic stabilities are discussed. Copyright © 2016 John Wiley & Sons, Ltd.

A Novel Prediction Method about Single Components of Analog Circuits Based on Complex Field Modeling

PubMed Central

Tian, Shulin; Yang, Chenglin

2014-01-01

Few researches pay attention to prediction about analog circuits. The few methods lack the correlation with circuit analysis during extracting and calculating features so that FI (fault indicator) calculation often lack rationality, thus affecting prognostic performance. To solve the above problem, this paper proposes a novel prediction method about single components of analog circuits based on complex field modeling. Aiming at the feature that faults of single components hold the largest number in analog circuits, the method starts with circuit structure, analyzes transfer function of circuits, and implements complex field modeling. Then, by an established parameter scanning model related to complex field, it analyzes the relationship between parameter variation and degeneration of single components in the model in order to obtain a more reasonable FI feature set via calculation. According to the obtained FI feature set, it establishes a novel model about degeneration trend of analog circuits' single components. At last, it uses particle filter (PF) to update parameters for the model and predicts remaining useful performance (RUP) of analog circuits' single components. Since calculation about the FI feature set is more reasonable, accuracy of prediction is improved to some extent. Finally, the foregoing conclusions are verified by experiments. PMID:25147853

Effect of substituents on prediction of TLC retention of tetra-dentate Schiff bases and their Copper(II) and Nickel(II) complexes.

PubMed

Stevanović, Nikola R; Perušković, Danica S; Gašić, Uroš M; Antunović, Vesna R; Lolić, Aleksandar Đ; Baošić, Rada M

2017-03-01

The objectives of this study were to gain insights into structure-retention relationships and to propose the model to estimating their retention. Chromatographic investigation of series of 36 Schiff bases and their copper(II) and nickel(II) complexes was performed under both normal- and reverse-phase conditions. Chemical structures of the compounds were characterized by molecular descriptors which are calculated from the structure and related to the chromatographic retention parameters by multiple linear regression analysis. Effects of chelation on retention parameters of investigated compounds, under normal- and reverse-phase chromatographic conditions, were analyzed by principal component analysis, quantitative structure-retention relationship and quantitative structure-activity relationship models were developed on the basis of theoretical molecular descriptors, calculated exclusively from molecular structure, and parameters of retention and lipophilicity. Copyright © 2016 John Wiley & Sons, Ltd.

Optimization of the dressing parameters in cylindrical grinding based on a generalized utility function

NASA Astrophysics Data System (ADS)

Aleksandrova, Irina

2016-01-01

The existing studies, concerning the dressing process, focus on the major influence of the dressing conditions on the grinding response variables. However, the choice of the dressing conditions is often made, based on the experience of the qualified staff or using data from reference books. The optimal dressing parameters, which are only valid for the particular methods and dressing and grinding conditions, are also used. The paper presents a methodology for optimization of the dressing parameters in cylindrical grinding. The generalized utility function has been chosen as an optimization parameter. It is a complex indicator determining the economic, dynamic and manufacturing characteristics of the grinding process. The developed methodology is implemented for the dressing of aluminium oxide grinding wheels by using experimental diamond roller dressers with different grit sizes made of medium- and high-strength synthetic diamonds type ??32 and ??80. To solve the optimization problem, a model of the generalized utility function is created which reflects the complex impact of dressing parameters. The model is built based on the results from the conducted complex study and modeling of the grinding wheel lifetime, cutting ability, production rate and cutting forces during grinding. They are closely related to the dressing conditions (dressing speed ratio, radial in-feed of the diamond roller dresser and dress-out time), the diamond roller dresser grit size/grinding wheel grit size ratio, the type of synthetic diamonds and the direction of dressing. Some dressing parameters are determined for which the generalized utility function has a maximum and which guarantee an optimum combination of the following: the lifetime and cutting ability of the abrasive wheels, the tangential cutting force magnitude and the production rate of the grinding process. The results obtained prove the possibility of control and optimization of grinding by selecting particular dressing parameters.

Good Trellises for IC Implementation of Viterbi Decoders for Linear Block Codes

NASA Technical Reports Server (NTRS)

Moorthy, Hari T.; Lin, Shu; Uehara, Gregory T.

1997-01-01

This paper investigates trellis structures of linear block codes for the integrated circuit (IC) implementation of Viterbi decoders capable of achieving high decoding speed while satisfying a constraint on the structural complexity of the trellis in terms of the maximum number of states at any particular depth. Only uniform sectionalizations of the code trellis diagram are considered. An upper-bound on the number of parallel and structurally identical (or isomorphic) subtrellises in a proper trellis for a code without exceeding the maximum state complexity of the minimal trellis of the code is first derived. Parallel structures of trellises with various section lengths for binary BCH and Reed-Muller (RM) codes of lengths 32 and 64 are analyzed. Next, the complexity of IC implementation of a Viterbi decoder based on an L-section trellis diagram for a code is investigated. A structural property of a Viterbi decoder called add-compare-select (ACS)-connectivity which is related to state connectivity is introduced. This parameter affects the complexity of wire-routing (interconnections within the IC). The effect of five parameters namely: (1) effective computational complexity; (2) complexity of the ACS-circuit; (3) traceback complexity; (4) ACS-connectivity; and (5) branch complexity of a trellis diagram on the very large scale integration (VISI) complexity of a Viterbi decoder is investigated. It is shown that an IC implementation of a Viterbi decoder based on a nonminimal trellis requires less area and is capable of operation at higher speed than one based on the minimal trellis when the commonly used ACS-array architecture is considered.

Good trellises for IC implementation of viterbi decoders for linear block codes

NASA Technical Reports Server (NTRS)

Lin, Shu; Moorthy, Hari T.; Uehara, Gregory T.

1996-01-01

This paper investigates trellis structures of linear block codes for the IC (integrated circuit) implementation of Viterbi decoders capable of achieving high decoding speed while satisfying a constraint on the structural complexity of the trellis in terms of the maximum number of states at any particular depth. Only uniform sectionalizations of the code trellis diagram are considered. An upper bound on the number of parallel and structurally identical (or isomorphic) subtrellises in a proper trellis for a code without exceeding the maximum state complexity of the minimal trellis of the code is first derived. Parallel structures of trellises with various section lengths for binary BCH and Reed-Muller (RM) codes of lengths 32 and 64 are analyzed. Next, the complexity of IC implementation of a Viterbi decoder based on an L-section trellis diagram for a code is investigated. A structural property of a Viterbi decoder called ACS-connectivity which is related to state connectivity is introduced. This parameter affects the complexity of wire-routing (interconnections within the IC). The effect of five parameters namely: (1) effective computational complexity; (2) complexity of the ACS-circuit; (3) traceback complexity; (4) ACS-connectivity; and (5) branch complexity of a trellis diagram on the VLSI complexity of a Viterbi decoder is investigated. It is shown that an IC implementation of a Viterbi decoder based on a non-minimal trellis requires less area and is capable of operation at higher speed than one based on the minimal trellis when the commonly used ACS-array architecture is considered.

A framework for scalable parameter estimation of gene circuit models using structural information.

PubMed

Kuwahara, Hiroyuki; Fan, Ming; Wang, Suojin; Gao, Xin

2013-07-01

Systematic and scalable parameter estimation is a key to construct complex gene regulatory models and to ultimately facilitate an integrative systems biology approach to quantitatively understand the molecular mechanisms underpinning gene regulation. Here, we report a novel framework for efficient and scalable parameter estimation that focuses specifically on modeling of gene circuits. Exploiting the structure commonly found in gene circuit models, this framework decomposes a system of coupled rate equations into individual ones and efficiently integrates them separately to reconstruct the mean time evolution of the gene products. The accuracy of the parameter estimates is refined by iteratively increasing the accuracy of numerical integration using the model structure. As a case study, we applied our framework to four gene circuit models with complex dynamics based on three synthetic datasets and one time series microarray data set. We compared our framework to three state-of-the-art parameter estimation methods and found that our approach consistently generated higher quality parameter solutions efficiently. Although many general-purpose parameter estimation methods have been applied for modeling of gene circuits, our results suggest that the use of more tailored approaches to use domain-specific information may be a key to reverse engineering of complex biological systems. http://sfb.kaust.edu.sa/Pages/Software.aspx. Supplementary data are available at Bioinformatics online.

On the use of Empirical Data to Downscale Non-scientific Scepticism About Results From Complex Physical Based Models

NASA Astrophysics Data System (ADS)

Germer, S.; Bens, O.; Hüttl, R. F.

2008-12-01

The scepticism of non-scientific local stakeholders about results from complex physical based models is a major problem concerning the development and implementation of local climate change adaptation measures. This scepticism originates from the high complexity of such models. Local stakeholders perceive complex models as black-box models, as it is impossible to gasp all underlying assumptions and mathematically formulated processes at a glance. The use of physical based models is, however, indispensible to study complex underlying processes and to predict future environmental changes. The increase of climate change adaptation efforts following the release of the latest IPCC report indicates that the communication of facts about what has already changed is an appropriate tool to trigger climate change adaptation. Therefore we suggest increasing the practice of empirical data analysis in addition to modelling efforts. The analysis of time series can generate results that are easier to comprehend for non-scientific stakeholders. Temporal trends and seasonal patterns of selected hydrological parameters (precipitation, evapotranspiration, groundwater levels and river discharge) can be identified and the dependence of trends and seasonal patters to land use, topography and soil type can be highlighted. A discussion about lag times between the hydrological parameters can increase the awareness of local stakeholders for delayed environment responses.

Code IN Exhibits - Supercomputing 2000

NASA Technical Reports Server (NTRS)

Yarrow, Maurice; McCann, Karen M.; Biswas, Rupak; VanderWijngaart, Rob F.; Kwak, Dochan (Technical Monitor)

2000-01-01

The creation of parameter study suites has recently become a more challenging problem as the parameter studies have become multi-tiered and the computational environment has become a supercomputer grid. The parameter spaces are vast, the individual problem sizes are getting larger, and researchers are seeking to combine several successive stages of parameterization and computation. Simultaneously, grid-based computing offers immense resource opportunities but at the expense of great difficulty of use. We present ILab, an advanced graphical user interface approach to this problem. Our novel strategy stresses intuitive visual design tools for parameter study creation and complex process specification, and also offers programming-free access to grid-based supercomputer resources and process automation.

Classical Control System Design: A non-Graphical Method for Finding the Exact System Parameters

NASA Astrophysics Data System (ADS)

Hussein, Mohammed Tawfik

2008-06-01

The Root Locus method of control system design was developed in the 1940's. It is a set of rules that helps in sketching the path traced by the roots of the closed loop characteristic equation of the system, as a parameter such as a controller gain, k, is varied. The procedure provides approximate sketching guidelines. Designs on control systems using the method are therefore not exact. This paper aims at a non-graphical method for finding the exact system parameters to place a pair of complex conjugate poles on a specified damping ratio line. The overall procedure is based on the exact solution of complex equations on the PC using numerical methods.

Adaptative synchronization in multi-output fractional-order complex dynamical networks and secure communications

NASA Astrophysics Data System (ADS)

Mata-Machuca, Juan L.; Aguilar-López, Ricardo

2018-01-01

This work deals with the adaptative synchronization of complex dynamical networks with fractional-order nodes and its application in secure communications employing chaotic parameter modulation. The complex network is composed of multiple fractional-order systems with mismatch parameters and the coupling functions are given to realize the network synchronization. We introduce a fractional algebraic synchronizability condition (FASC) and a fractional algebraic identifiability condition (FAIC) which are used to know if the synchronization and parameters estimation problems can be solved. To overcome these problems, an adaptative synchronization methodology is designed; the strategy consists in proposing multiple receiver systems which tend to follow asymptotically the uncertain transmitters systems. The coupling functions and parameters of the receiver systems are adjusted continually according to a convenient sigmoid-like adaptative controller (SLAC), until the measurable output errors converge to zero, hence, synchronization between transmitter and receivers is achieved and message signals are recovered. Indeed, the stability analysis of the synchronization error is based on the fractional Lyapunov direct method. Finally, numerical results corroborate the satisfactory performance of the proposed scheme by means of the synchronization of a complex network consisting of several fractional-order unified chaotic systems.

Fast dictionary generation and searching for magnetic resonance fingerprinting.

PubMed

Jun Xie; Mengye Lyu; Jian Zhang; Hui, Edward S; Wu, Ed X; Ze Wang

2017-07-01

A super-fast dictionary generation and searching (DGS) algorithm was developed for MR parameter quantification using magnetic resonance fingerprinting (MRF). MRF is a new technique for simultaneously quantifying multiple MR parameters using one temporally resolved MR scan. But it has a multiplicative computation complexity, resulting in a big burden of dictionary generating, saving, and retrieving, which can easily be intractable for any state-of-art computers. Based on retrospective analysis of the dictionary matching object function, a multi-scale ZOOM like DGS algorithm, dubbed as MRF-ZOOM, was proposed. MRF ZOOM is quasi-parameter-separable so the multiplicative computation complexity is broken into additive one. Evaluations showed that MRF ZOOM was hundreds or thousands of times faster than the original MRF parameter quantification method even without counting the dictionary generation time in. Using real data, it yielded nearly the same results as produced by the original method. MRF ZOOM provides a super-fast solution for MR parameter quantification.

SU-E-J-261: Statistical Analysis and Chaotic Dynamics of Respiratory Signal of Patients in BodyFix

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

Michalski, D; Huq, M; Bednarz, G

Purpose: To quantify respiratory signal of patients in BodyFix undergoing 4DCT scan with and without immobilization cover. Methods: 20 pairs of respiratory tracks recorded with RPM system during 4DCT scan were analyzed. Descriptive statistic was applied to selected parameters of exhale-inhale decomposition. Standardized signals were used with the delay method to build orbits in embedded space. Nonlinear behavior was tested with surrogate data. Sample entropy SE, Lempel-Ziv complexity LZC and the largest Lyapunov exponents LLE were compared. Results: Statistical tests show difference between scans for inspiration time and its variability, which is bigger for scans without cover. The same ismore » for variability of the end of exhalation and inhalation. Other parameters fail to show the difference. For both scans respiratory signals show determinism and nonlinear stationarity. Statistical test on surrogate data reveals their nonlinearity. LLEs show signals chaotic nature and its correlation with breathing period and its embedding delay time. SE, LZC and LLE measure respiratory signal complexity. Nonlinear characteristics do not differ between scans. Conclusion: Contrary to expectation cover applied to patients in BodyFix appears to have limited effect on signal parameters. Analysis based on trajectories of delay vectors shows respiratory system nonlinear character and its sensitive dependence on initial conditions. Reproducibility of respiratory signal can be evaluated with measures of signal complexity and its predictability window. Longer respiratory period is conducive for signal reproducibility as shown by these gauges. Statistical independence of the exhale and inhale times is also supported by the magnitude of LLE. The nonlinear parameters seem more appropriate to gauge respiratory signal complexity since its deterministic chaotic nature. It contrasts with measures based on harmonic analysis that are blind for nonlinear features. Dynamics of breathing, so crucial for 4D-based clinical technologies, can be better controlled if nonlinear-based methodology, which reflects respiration characteristic, is applied. Funding provided by Varian Medical Systems via Investigator Initiated Research Project.« less

Exploring Several Methods of Groundwater Model Selection

NASA Astrophysics Data System (ADS)

Samani, Saeideh; Ye, Ming; Asghari Moghaddam, Asghar

2017-04-01

Selecting reliable models for simulating groundwater flow and solute transport is essential to groundwater resources management and protection. This work is to explore several model selection methods for avoiding over-complex and/or over-parameterized groundwater models. We consider six groundwater flow models with different numbers (6, 10, 10, 13, 13 and 15) of model parameters. These models represent alternative geological interpretations, recharge estimates, and boundary conditions at a study site in Iran. The models were developed with Model Muse, and calibrated against observations of hydraulic head using UCODE. Model selection was conducted by using the following four approaches: (1) Rank the models using their root mean square error (RMSE) obtained after UCODE-based model calibration, (2) Calculate model probability using GLUE method, (3) Evaluate model probability using model selection criteria (AIC, AICc, BIC, and KIC), and (4) Evaluate model weights using the Fuzzy Multi-Criteria-Decision-Making (MCDM) approach. MCDM is based on the fuzzy analytical hierarchy process (AHP) and fuzzy technique for order performance, which is to identify the ideal solution by a gradual expansion from the local to the global scale of model parameters. The KIC and MCDM methods are superior to other methods, as they consider not only the fit between observed and simulated data and the number of parameter, but also uncertainty in model parameters. Considering these factors can prevent from occurring over-complexity and over-parameterization, when selecting the appropriate groundwater flow models. These methods selected, as the best model, one with average complexity (10 parameters) and the best parameter estimation (model 3).

Computer-aided molecular modeling techniques for predicting the stability of drug cyclodextrin inclusion complexes in aqueous solutions

NASA Astrophysics Data System (ADS)

Faucci, Maria Teresa; Melani, Fabrizio; Mura, Paola

2002-06-01

Molecular modeling was used to investigate factors influencing complex formation between cyclodextrins and guest molecules and predict their stability through a theoretical model based on the search for a correlation between experimental stability constants ( Ks) and some theoretical parameters describing complexation (docking energy, host-guest contact surfaces, intermolecular interaction fields) calculated from complex structures at a minimum conformational energy, obtained through stochastic methods based on molecular dynamic simulations. Naproxen, ibuprofen, ketoprofen and ibuproxam were used as model drug molecules. Multiple Regression Analysis allowed identification of the significant factors for the complex stability. A mathematical model ( r=0.897) related log Ks with complex docking energy and lipophilic molecular fields of cyclodextrin and drug.

Ensemble-Based Parameter Estimation in a Coupled GCM Using the Adaptive Spatial Average Method

DOE PAGES

Liu, Y.; Liu, Z.; Zhang, S.; ...

2014-05-29

Ensemble-based parameter estimation for a climate model is emerging as an important topic in climate research. And for a complex system such as a coupled ocean–atmosphere general circulation model, the sensitivity and response of a model variable to a model parameter could vary spatially and temporally. An adaptive spatial average (ASA) algorithm is proposed to increase the efficiency of parameter estimation. Refined from a previous spatial average method, the ASA uses the ensemble spread as the criterion for selecting “good” values from the spatially varying posterior estimated parameter values; these good values are then averaged to give the final globalmore » uniform posterior parameter. In comparison with existing methods, the ASA parameter estimation has a superior performance: faster convergence and enhanced signal-to-noise ratio.« less

Four-dimensional computed tomography based respiratory-gated radiotherapy with respiratory guidance system: analysis of respiratory signals and dosimetric comparison.

PubMed

Lee, Jung Ae; Kim, Chul Yong; Yang, Dae Sik; Yoon, Won Sup; Park, Young Je; Lee, Suk; Kim, Young Bum

2014-01-01

To investigate the effectiveness of respiratory guidance system in 4-dimensional computed tomography (4 DCT) based respiratory-gated radiation therapy (RGRT) by comparing respiratory signals and dosimetric analysis of treatment plans. The respiratory amplitude and period of the free, the audio device-guided, and the complex system-guided breathing were evaluated in eleven patients with lung or liver cancers. The dosimetric parameters were assessed by comparing free breathing CT plan and 4 DCT-based 30-70% maximal intensity projection (MIP) plan. The use of complex system-guided breathing showed significantly less variation in respiratory amplitude and period compared to the free or audio-guided breathing regarding the root mean square errors (RMSE) of full inspiration (P = 0.031), full expiration (P = 0.007), and period (P = 0.007). The dosimetric parameters including V(5 Gy), V(10 Gy), V(20 Gy), V(30 Gy), V(40 Gy), and V(50 Gy) of normal liver or lung in 4 DCT MIP plan were superior over free breathing CT plan. The reproducibility and regularity of respiratory amplitude and period were significantly improved with the complex system-guided breathing compared to the free or the audio-guided breathing. In addition, the treatment plan based on the 4D CT-based MIP images acquired with the complex system guided breathing showed better normal tissue sparing than that on the free breathing CT.

Automatic QRS complex detection using two-level convolutional neural network.

PubMed

Xiang, Yande; Lin, Zhitao; Meng, Jianyi

2018-01-29

The QRS complex is the most noticeable feature in the electrocardiogram (ECG) signal, therefore, its detection is critical for ECG signal analysis. The existing detection methods largely depend on hand-crafted manual features and parameters, which may introduce significant computational complexity, especially in the transform domains. In addition, fixed features and parameters are not suitable for detecting various kinds of QRS complexes under different circumstances. In this study, based on 1-D convolutional neural network (CNN), an accurate method for QRS complex detection is proposed. The CNN consists of object-level and part-level CNNs for extracting different grained ECG morphological features automatically. All the extracted morphological features are used by multi-layer perceptron (MLP) for QRS complex detection. Additionally, a simple ECG signal preprocessing technique which only contains difference operation in temporal domain is adopted. Based on the MIT-BIH arrhythmia (MIT-BIH-AR) database, the proposed detection method achieves overall sensitivity Sen = 99.77%, positive predictivity rate PPR = 99.91%, and detection error rate DER = 0.32%. In addition, the performance variation is performed according to different signal-to-noise ratio (SNR) values. An automatic QRS detection method using two-level 1-D CNN and simple signal preprocessing technique is proposed for QRS complex detection. Compared with the state-of-the-art QRS complex detection approaches, experimental results show that the proposed method acquires comparable accuracy.

The Limitations of Model-Based Experimental Design and Parameter Estimation in Sloppy Systems.

PubMed

White, Andrew; Tolman, Malachi; Thames, Howard D; Withers, Hubert Rodney; Mason, Kathy A; Transtrum, Mark K

2016-12-01

We explore the relationship among experimental design, parameter estimation, and systematic error in sloppy models. We show that the approximate nature of mathematical models poses challenges for experimental design in sloppy models. In many models of complex biological processes it is unknown what are the relevant physical mechanisms that must be included to explain system behaviors. As a consequence, models are often overly complex, with many practically unidentifiable parameters. Furthermore, which mechanisms are relevant/irrelevant vary among experiments. By selecting complementary experiments, experimental design may inadvertently make details that were ommitted from the model become relevant. When this occurs, the model will have a large systematic error and fail to give a good fit to the data. We use a simple hyper-model of model error to quantify a model's discrepancy and apply it to two models of complex biological processes (EGFR signaling and DNA repair) with optimally selected experiments. We find that although parameters may be accurately estimated, the discrepancy in the model renders it less predictive than it was in the sloppy regime where systematic error is small. We introduce the concept of a sloppy system-a sequence of models of increasing complexity that become sloppy in the limit of microscopic accuracy. We explore the limits of accurate parameter estimation in sloppy systems and argue that identifying underlying mechanisms controlling system behavior is better approached by considering a hierarchy of models of varying detail rather than focusing on parameter estimation in a single model.

The Limitations of Model-Based Experimental Design and Parameter Estimation in Sloppy Systems

PubMed Central

Tolman, Malachi; Thames, Howard D.; Mason, Kathy A.

2016-01-01

We explore the relationship among experimental design, parameter estimation, and systematic error in sloppy models. We show that the approximate nature of mathematical models poses challenges for experimental design in sloppy models. In many models of complex biological processes it is unknown what are the relevant physical mechanisms that must be included to explain system behaviors. As a consequence, models are often overly complex, with many practically unidentifiable parameters. Furthermore, which mechanisms are relevant/irrelevant vary among experiments. By selecting complementary experiments, experimental design may inadvertently make details that were ommitted from the model become relevant. When this occurs, the model will have a large systematic error and fail to give a good fit to the data. We use a simple hyper-model of model error to quantify a model’s discrepancy and apply it to two models of complex biological processes (EGFR signaling and DNA repair) with optimally selected experiments. We find that although parameters may be accurately estimated, the discrepancy in the model renders it less predictive than it was in the sloppy regime where systematic error is small. We introduce the concept of a sloppy system–a sequence of models of increasing complexity that become sloppy in the limit of microscopic accuracy. We explore the limits of accurate parameter estimation in sloppy systems and argue that identifying underlying mechanisms controlling system behavior is better approached by considering a hierarchy of models of varying detail rather than focusing on parameter estimation in a single model. PMID:27923060

Complex-enhanced chaotic signals with time-delay signature suppression based on vertical-cavity surface-emitting lasers subject to chaotic optical injection

NASA Astrophysics Data System (ADS)

Chen, Jianjun; Duan, Yingni; Zhong, Zhuqiang

2018-06-01

A chaotic system is constructed on the basis of vertical-cavity surface-emitting lasers (VCSELs), where a slave VCSEL subject to chaotic optical injection (COI) from a master VCSEL with the external feedback. The complex degree (CD) and time-delay signature (TDS) of chaotic signals generated by this chaotic system are investigated numerically via permutation entropy (PE) and self-correlation function (SF) methods, respectively. The results show that, compared with master VCSEL subject to optical feedback, complex-enhanced chaotic signals with TDS suppression can be achieved for S-VCSEL subject to COI. Meanwhile, the influences of several controllable parameters on the evolution maps of CD of chaotic signals are carefully considered. It is shown that the CD of chaotic signals for S-VCSEL is always higher than that for M-VCSEL due to the CIO effect. The TDS of chaotic signals can be significantly suppressed by choosing the reasonable parameters in this system. Furthermore, TDS suppression and high CD chaos can be obtained simultaneously in the specific parameter ranges. The results confirm that this chaotic system may effectively improve the security of a chaos-based communication scheme.

Complex-enhanced chaotic signals with time-delay signature suppression based on vertical-cavity surface-emitting lasers subject to chaotic optical injection

NASA Astrophysics Data System (ADS)

Chen, Jianjun; Duan, Yingni; Zhong, Zhuqiang

2018-03-01

A chaotic system is constructed on the basis of vertical-cavity surface-emitting lasers (VCSELs), where a slave VCSEL subject to chaotic optical injection (COI) from a master VCSEL with the external feedback. The complex degree (CD) and time-delay signature (TDS) of chaotic signals generated by this chaotic system are investigated numerically via permutation entropy (PE) and self-correlation function (SF) methods, respectively. The results show that, compared with master VCSEL subject to optical feedback, complex-enhanced chaotic signals with TDS suppression can be achieved for S-VCSEL subject to COI. Meanwhile, the influences of several controllable parameters on the evolution maps of CD of chaotic signals are carefully considered. It is shown that the CD of chaotic signals for S-VCSEL is always higher than that for M-VCSEL due to the CIO effect. The TDS of chaotic signals can be significantly suppressed by choosing the reasonable parameters in this system. Furthermore, TDS suppression and high CD chaos can be obtained simultaneously in the specific parameter ranges. The results confirm that this chaotic system may effectively improve the security of a chaos-based communication scheme.

Parameter estimation procedure for complex non-linear systems: calibration of ASM No. 1 for N-removal in a full-scale oxidation ditch.

PubMed

Abusam, A; Keesman, K J; van Straten, G; Spanjers, H; Meinema, K

2001-01-01

When applied to large simulation models, the process of parameter estimation is also called calibration. Calibration of complex non-linear systems, such as activated sludge plants, is often not an easy task. On the one hand, manual calibration of such complex systems is usually time-consuming, and its results are often not reproducible. On the other hand, conventional automatic calibration methods are not always straightforward and often hampered by local minima problems. In this paper a new straightforward and automatic procedure, which is based on the response surface method (RSM) for selecting the best identifiable parameters, is proposed. In RSM, the process response (output) is related to the levels of the input variables in terms of a first- or second-order regression model. Usually, RSM is used to relate measured process output quantities to process conditions. However, in this paper RSM is used for selecting the dominant parameters, by evaluating parameters sensitivity in a predefined region. Good results obtained in calibration of ASM No. 1 for N-removal in a full-scale oxidation ditch proved that the proposed procedure is successful and reliable.

Sonication-assisted synthesis of a new cationic zinc nitrate complex with a tetradentate Schiff base ligand: Crystal structure, Hirshfeld surface analysis and investigation of different parameters influence on morphological properties.

PubMed

Mousavi, S A; Montazerozohori, M; Masoudiasl, A; Mahmoudi, G; White, J M

2018-09-01

A nanostructured cationic zinc nitrate complex with a formula of [ZnLNO 3 ]NO 3 (where L = (N 2 E,N 2' E)-N 1 ,N 1' -(ethane-1,2-diyl)bis(N 2 -((E)-3-phenylallylidene)ethane-1,2-diamine)) was prepared by sonochemical process and characterized by single crystal X-ray crystallography, scanning electron microscopy (SEM), FT-IR and NMR spectroscopy and X-ray powder diffraction (XRPD). The X-ray analysis demonstrates the formation of a cationic complex that metal center is five-coordinated by four nitrogen atom from Schiff base ligand and one oxygen atom from nitrate group. The crystal packing analysis demonstrates the essential role of the nitrate groups in the organization of supramolecular structure. The morphology and size of ultrasound-assisted synthesized zinc nitrate complex have been investigated using scanning electron microscopy (SEM) by changing parameters such as the concentration of initial reactants, the sonication power and reaction temperature. In addition the calcination of zinc nitrate complex in air atmosphere led to production of zinc oxide nanoparticles. Copyright © 2018. Published by Elsevier B.V.

Analysis of spontaneous MEG activity in mild cognitive impairment and Alzheimer's disease using spectral entropies and statistical complexity measures

NASA Astrophysics Data System (ADS)

Bruña, Ricardo; Poza, Jesús; Gómez, Carlos; García, María; Fernández, Alberto; Hornero, Roberto

2012-06-01

Alzheimer's disease (AD) is the most common cause of dementia. Over the last few years, a considerable effort has been devoted to exploring new biomarkers. Nevertheless, a better understanding of brain dynamics is still required to optimize therapeutic strategies. In this regard, the characterization of mild cognitive impairment (MCI) is crucial, due to the high conversion rate from MCI to AD. However, only a few studies have focused on the analysis of magnetoencephalographic (MEG) rhythms to characterize AD and MCI. In this study, we assess the ability of several parameters derived from information theory to describe spontaneous MEG activity from 36 AD patients, 18 MCI subjects and 26 controls. Three entropies (Shannon, Tsallis and Rényi entropies), one disequilibrium measure (based on Euclidean distance ED) and three statistical complexities (based on Lopez Ruiz-Mancini-Calbet complexity LMC) were used to estimate the irregularity and statistical complexity of MEG activity. Statistically significant differences between AD patients and controls were obtained with all parameters (p < 0.01). In addition, statistically significant differences between MCI subjects and controls were achieved by ED and LMC (p < 0.05). In order to assess the diagnostic ability of the parameters, a linear discriminant analysis with a leave-one-out cross-validation procedure was applied. The accuracies reached 83.9% and 65.9% to discriminate AD and MCI subjects from controls, respectively. Our findings suggest that MCI subjects exhibit an intermediate pattern of abnormalities between normal aging and AD. Furthermore, the proposed parameters provide a new description of brain dynamics in AD and MCI.

A search for optimal parameters of resonance circuits ensuring damping of electroelastic structure vibrations based on the solution of natural vibration problem

NASA Astrophysics Data System (ADS)

Oshmarin, D.; Sevodina, N.; Iurlov, M.; Iurlova, N.

2017-06-01

In this paper, with the aim of providing passive control of structure vibrations a new approach has been proposed for selecting optimal parameters of external electric shunt circuits connected to piezoelectric elements located on the surface of the structure. The approach is based on the mathematical formulation of the natural vibration problem. The results of solution of this problem are the complex eigenfrequencies, the real part of which represents the vibration frequency and the imaginary part corresponds to the damping ratio, characterizing the rate of damping. A criterion of search for optimal parameters of the external passive shunt circuits, which can provide the system with desired dissipative properties, has been derived based on the analysis of responses of the real and imaginary parts of different complex eigenfrequencies to changes in the values of the parameters of the electric circuit. The efficiency of this approach has been verified in the context of natural vibration problem of rigidly clamped plate and semi-cylindrical shell, which is solved for series-connected and parallel -connected external resonance (consisting of resistive and inductive elements) R-L circuits. It has been shown that at lower (more energy-intensive) frequencies, a series-connected external circuit has the advantage of providing lower values of the circuit parameters, which renders it more attractive in terms of practical applications.

Parameter Optimization for Turbulent Reacting Flows Using Adjoints

NASA Astrophysics Data System (ADS)

Lapointe, Caelan; Hamlington, Peter E.

2017-11-01

The formulation of a new adjoint solver for topology optimization of turbulent reacting flows is presented. This solver provides novel configurations (e.g., geometries and operating conditions) based on desired system outcomes (i.e., objective functions) for complex reacting flow problems of practical interest. For many such problems, it would be desirable to know optimal values of design parameters (e.g., physical dimensions, fuel-oxidizer ratios, and inflow-outflow conditions) prior to real-world manufacture and testing, which can be expensive, time-consuming, and dangerous. However, computational optimization of these problems is made difficult by the complexity of most reacting flows, necessitating the use of gradient-based optimization techniques in order to explore a wide design space at manageable computational cost. The adjoint method is an attractive way to obtain the required gradients, because the cost of the method is determined by the dimension of the objective function rather than the size of the design space. Here, the formulation of a novel solver is outlined that enables gradient-based parameter optimization of turbulent reacting flows using the discrete adjoint method. Initial results and an outlook for future research directions are provided.

Complex approach to the investigation of short fiber-optic comunication lines

NASA Astrophysics Data System (ADS)

Sukhoivanov, I. A.; Kontar', A. A.; Kublik, A. V.; Makarevich, V. S.

The paper proposes a method of complex measurements based on the consideration of the parameters of all the elements used in a specific multimode fiber-optic communication line. It is shown that the error in measuring losses in waveguides up to 20 m long can reach a value of 60 percent.

Tetrel bond-σ-hole bond as a preliminary stage of the SN2 reaction.

PubMed

Grabowski, Sławomir J

2014-02-07

MP2/aug-cc-pVTZ calculations were carried out on complexes of ZH4, ZFH3 and ZF4 (Z = C, Si and Ge) molecules with HCN, LiCN and Cl(-) species acting as Lewis bases through nitrogen centre or chlorine ion. Z-Atoms in these complexes usually act as Lewis acid centres forming σ-hole bonds with Lewis bases. Such noncovalent interactions may adopt a name of tetrel bonds since they concern the elements of the group IV. There are exceptions for complexes of CH4 and CF4, as well as for the F4SiNCH complex where the tetrel bond is not formed. The energetic and geometrical parameters of the complexes were analyzed and numerous correlations between them were found. The Quantum Theory of 'Atoms in Molecules' and Natural Bonds Orbital (NBO) method used here should deepen the understanding of the nature of the tetrel bond. An analysis of the electrostatic potential surfaces of the interacting species is performed. The electron charge redistribution, being the result of the tetrel bond formation, is the same as that of the SN2 reaction. The energetic and geometrical parameters of the complexes analyzed here correspond to different stages of the SN2 process.

Associations Between PET Textural Features and GLUT1 Expression, and the Prognostic Significance of Textural Features in Lung Adenocarcinoma.

PubMed

Koh, Young Wha; Park, Seong Yong; Hyun, Seung Hyup; Lee, Su Jin

2018-02-01

We evaluated the association between positron emission tomography (PET) textural features and glucose transporter 1 (GLUT1) expression level and further investigated the prognostic significance of textural features in lung adenocarcinoma. We evaluated 105 adenocarcinoma patients. We extracted texture-based PET parameters of primary tumors. Conventional PET parameters were also measured. The relationships between PET parameters and GLUT1 expression levels were evaluated. The association between PET parameters and overall survival (OS) was assessed using Cox's proportional hazard regression models. In terms of PET textural features, tumors expressing high levels of GLUT1 exhibited significantly lower coarseness, contrast, complexity, and strength, but significantly higher busyness. On univariate analysis, the metabolic tumor volume, total lesion glycolysis, contrast, busyness, complexity, and strength were significant predictors of OS. Multivariate analysis showed that lower complexity (HR=2.017, 95%CI=1.032-3.942, p=0.040) was independently associated with poorer survival. PET textural features may aid risk stratification in lung adenocarcinoma patients. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Synthesis, characterization, and antipathogenic studies of some transition metal complexes with N,O-chelating Schiff's base ligand incorporating azo and sulfonamide Moieties

NASA Astrophysics Data System (ADS)

Alaghaz, Abdel-Nasser M. A.; Bayoumi, Hoda A.; Ammar, Yousry A.; Aldhlmani, Sharah A.

2013-03-01

Chromium(III), Manganese(II), Cobalt(II), nickel(II), copper(II) and cadmium(II) complexes of 4-[4-hydroxy-3-(phenyliminomethyl)-phenylazo]benzenesulfonamide, were prepared and characterized on the basis of elemental analyses, spectral, magnetic, molar conductance and thermal analysis. Square planar, tetrahedral and octahedral geometries have been assigned to the prepared complexes. Dimeric complexes are obtained with 2:2 molar ratio except chromium(III) complex is monomeric which is obtained with 1:1 molar ratios. The IR spectra of the prepared complexes were suggested that the Schiff base ligand(HL) behaves as a bi-dentate ligand through the azomethine nitrogen atom and phenolic oxygen atom. The crystal field splitting, Racah repulsion and nepheloauxetic parameters and determined from the electronic spectra of the complexes. Thermal studies suggest a mechanism for degradation of HL and its metal complexes as function of temperature supporting the chelation modes. Also, the activation thermodynamic parameters, such as ΔE*, ΔH*, ΔS* and ΔG* for the different thermal decomposition steps of HL and its metal complexes were calculated. The pathogenic activities of the synthesized compounds were tested in vitro against the sensitive organisms Staphylococcus aureus (RCMB010027), Staphylococcus epidermidis (RCMB010024) as Gram positive bacteria, Klebsiella pneumonia (RCMB 010093), Shigella flexneri (RCMB 0100542), as Gram negative bacteria and Aspergillus fumigates (RCMB 02564), Aspergillus clavatus (RCMB 02593) and Candida albicans (RCMB05035) as fungus strain, and the results are discussed.

Spectral Entropies as Information-Theoretic Tools for Complex Network Comparison

NASA Astrophysics Data System (ADS)

De Domenico, Manlio; Biamonte, Jacob

2016-10-01

Any physical system can be viewed from the perspective that information is implicitly represented in its state. However, the quantification of this information when it comes to complex networks has remained largely elusive. In this work, we use techniques inspired by quantum statistical mechanics to define an entropy measure for complex networks and to develop a set of information-theoretic tools, based on network spectral properties, such as Rényi q entropy, generalized Kullback-Leibler and Jensen-Shannon divergences, the latter allowing us to define a natural distance measure between complex networks. First, we show that by minimizing the Kullback-Leibler divergence between an observed network and a parametric network model, inference of model parameter(s) by means of maximum-likelihood estimation can be achieved and model selection can be performed with appropriate information criteria. Second, we show that the information-theoretic metric quantifies the distance between pairs of networks and we can use it, for instance, to cluster the layers of a multilayer system. By applying this framework to networks corresponding to sites of the human microbiome, we perform hierarchical cluster analysis and recover with high accuracy existing community-based associations. Our results imply that spectral-based statistical inference in complex networks results in demonstrably superior performance as well as a conceptual backbone, filling a gap towards a network information theory.

A new concept of a unified parameter management, experiment control, and data analysis in fMRI: application to real-time fMRI at 3T and 7T.

PubMed

Hollmann, M; Mönch, T; Mulla-Osman, S; Tempelmann, C; Stadler, J; Bernarding, J

2008-10-30

In functional MRI (fMRI) complex experiments and applications require increasingly complex parameter handling as the experimental setup usually consists of separated soft- and hardware systems. Advanced real-time applications such as neurofeedback-based training or brain computer interfaces (BCIs) may even require adaptive changes of the paradigms and experimental setup during the measurement. This would be facilitated by an automated management of the overall workflow and a control of the communication between all experimental components. We realized a concept based on an XML software framework called Experiment Description Language (EDL). All parameters relevant for real-time data acquisition, real-time fMRI (rtfMRI) statistical data analysis, stimulus presentation, and activation processing are stored in one central EDL file, and processed during the experiment. A usability study comparing the central EDL parameter management with traditional approaches showed an improvement of the complete experimental handling. Based on this concept, a feasibility study realizing a dynamic rtfMRI-based brain computer interface showed that the developed system in combination with EDL was able to reliably detect and evaluate activation patterns in real-time. The implementation of a centrally controlled communication between the subsystems involved in the rtfMRI experiments reduced potential inconsistencies, and will open new applications for adaptive BCIs.

Gradient-based model calibration with proxy-model assistance

NASA Astrophysics Data System (ADS)

Burrows, Wesley; Doherty, John

2016-02-01

Use of a proxy model in gradient-based calibration and uncertainty analysis of a complex groundwater model with large run times and problematic numerical behaviour is described. The methodology is general, and can be used with models of all types. The proxy model is based on a series of analytical functions that link all model outputs used in the calibration process to all parameters requiring estimation. In enforcing history-matching constraints during the calibration and post-calibration uncertainty analysis processes, the proxy model is run for the purposes of populating the Jacobian matrix, while the original model is run when testing parameter upgrades; the latter process is readily parallelized. Use of a proxy model in this fashion dramatically reduces the computational burden of complex model calibration and uncertainty analysis. At the same time, the effect of model numerical misbehaviour on calculation of local gradients is mitigated, this allowing access to the benefits of gradient-based analysis where lack of integrity in finite-difference derivatives calculation would otherwise have impeded such access. Construction of a proxy model, and its subsequent use in calibration of a complex model, and in analysing the uncertainties of predictions made by that model, is implemented in the PEST suite.

TU-F-12A-05: Sensitivity of Textural Features to 3D Vs. 4D FDG-PET/CT Imaging in NSCLC Patients

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

Yang, F; Nyflot, M; Bowen, S

2014-06-15

Purpose: Neighborhood Gray-level difference matrices (NGLDM) based texture parameters extracted from conventional (3D) 18F-FDG PET scans in patients with NSCLC have been previously shown to associate with response to chemoradiation and poorer patient outcome. However, the change in these parameters when utilizing respiratory-correlated (4D) FDG-PET scans has not yet been characterized for NSCLC. The Objectives: of this study was to assess the extent to which NGLDM-based texture parameters on 4D PET images vary with reference to values derived from 3D scans in NSCLC. Methods: Eight patients with newly diagnosed NSCLC treated with concomitant chemoradiotherapy were included in this study. 4Dmore » PET scans were reconstructed with OSEM-IR in 5 respiratory phase-binned images and corresponding CT data of each phase were employed for attenuation correction. NGLDM-based texture features, consisting of coarseness, contrast, busyness, complexity and strength, were evaluated for gross tumor volumes defined on 3D/4D PET scans by radiation oncologists. Variation of the obtained texture parameters over the respiratory cycle were examined with respect to values extracted from 3D scans. Results: Differences between texture parameters derived from 4D scans at different respiratory phases and those extracted from 3D scans ranged from −30% to 13% for coarseness, −12% to 40% for contrast, −5% to 50% for busyness, −7% to 38% for complexity, and −43% to 20% for strength. Furthermore, no evident correlations were observed between respiratory phase and 4D scan texture parameters. Conclusion: Results of the current study showed that NGLDM-based texture parameters varied considerably based on choice of 3D PET and 4D PET reconstruction of NSCLC patient images, indicating that standardized image acquisition and analysis protocols need to be established for clinical studies, especially multicenter clinical trials, intending to validate prognostic values of texture features for NSCLC.« less

Sensitivity of geological, geochemical and hydrologic parameters in complex reactive transport systems for in-situ uranium bioremediation

NASA Astrophysics Data System (ADS)

Yang, G.; Maher, K.; Caers, J.

2015-12-01

Groundwater contamination associated with remediated uranium mill tailings is a challenging environmental problem, particularly within the Colorado River Basin. To examine the effectiveness of in-situ bioremediation of U(VI), acetate injection has been proposed and tested at the Rifle pilot site. There have been several geologic modeling and simulated contaminant transport investigations, to evaluate the potential outcomes of the process and identify crucial factors for successful uranium reduction. Ultimately, findings from these studies would contribute to accurate predictions of the efficacy of uranium reduction. However, all these previous studies have considered limited model complexities, either because of the concern that data is too sparse to resolve such complex systems or because some parameters are assumed to be less important. Such simplified initial modeling, however, limits the predictive power of the model. Moreover, previous studies have not yet focused on spatial heterogeneity of various modeling components and its impact on the spatial distribution of the immobilized uranium (U(IV)). In this study, we study the impact of uncertainty on 21 parameters on model responses by means of recently developed distance-based global sensitivity analysis (DGSA), to study the main effects and interactions of parameters of various types. The 21 parameters include, for example, spatial variability of initial uranium concentration, mean hydraulic conductivity, and variogram structures of hydraulic conductivity. DGSA allows for studying multi-variate model responses based on spatial and non-spatial model parameters. When calculating the distances between model responses, in addition to the overall uranium reduction efficacy, we also considered the spatial profiles of the immobilized uranium concentration as target response. Results show that the mean hydraulic conductivity and the mineral reaction rate are the two most sensitive parameters with regard to the overall uranium reduction. But in terms of spatial distribution of immobilized uranium, initial conditions of uranium concentration and spatial uncertainty in hydraulic conductivity also become important. These analyses serve as the first step of further prediction practices of the complex uranium transport and reaction systems.

The physical and biological basis of quantitative parameters derived from diffusion MRI

PubMed Central

2012-01-01

Diffusion magnetic resonance imaging is a quantitative imaging technique that measures the underlying molecular diffusion of protons. Diffusion-weighted imaging (DWI) quantifies the apparent diffusion coefficient (ADC) which was first used to detect early ischemic stroke. However this does not take account of the directional dependence of diffusion seen in biological systems (anisotropy). Diffusion tensor imaging (DTI) provides a mathematical model of diffusion anisotropy and is widely used. Parameters, including fractional anisotropy (FA), mean diffusivity (MD), parallel and perpendicular diffusivity can be derived to provide sensitive, but non-specific, measures of altered tissue structure. They are typically assessed in clinical studies by voxel-based or region-of-interest based analyses. The increasing recognition of the limitations of the diffusion tensor model has led to more complex multi-compartment models such as CHARMED, AxCaliber or NODDI being developed to estimate microstructural parameters including axonal diameter, axonal density and fiber orientations. However these are not yet in routine clinical use due to lengthy acquisition times. In this review, I discuss how molecular diffusion may be measured using diffusion MRI, the biological and physical bases for the parameters derived from DWI and DTI, how these are used in clinical studies and the prospect of more complex tissue models providing helpful micro-structural information. PMID:23289085

Simulation of the microwave heating of a thin multilayered composite material: A parameter analysis

NASA Astrophysics Data System (ADS)

Tertrais, Hermine; Barasinski, Anaïs; Chinesta, Francisco

2018-05-01

Microwave (MW) technology relies on volumetric heating. Thermal energy is transferred to the material that can absorb it at specific frequencies. The complex physics involved in this process is far from being understood and that is why a simulation tool has been developed in order to solve the electromagnetic and thermal equations in such a complex material as a multilayered composite part. The code is based on the in-plane-out-of-plane separated representation within the Proper Generalized Decomposition framework. To improve the knowledge on the process, a parameter study in carried out in this paper.

Rapid and precise determination of zero-field splittings by terahertz time-domain electron paramagnetic resonance spectroscopy.

PubMed

Lu, Jian; Ozel, I Ozge; Belvin, Carina A; Li, Xian; Skorupskii, Grigorii; Sun, Lei; Ofori-Okai, Benjamin K; Dincă, Mircea; Gedik, Nuh; Nelson, Keith A

2017-11-01

Zero-field splitting (ZFS) parameters are fundamentally tied to the geometries of metal ion complexes. Despite their critical importance for understanding the magnetism and spectroscopy of metal complexes, they are not routinely available through general laboratory-based techniques, and are often inferred from magnetism data. Here we demonstrate a simple tabletop experimental approach that enables direct and reliable determination of ZFS parameters in the terahertz (THz) regime. We report time-domain measurements of electron paramagnetic resonance (EPR) signals associated with THz-frequency ZFSs in molecular complexes containing high-spin transition-metal ions. We measure the temporal profiles of the free-induction decays of spin resonances in the complexes at zero and nonzero external magnetic fields, and we derive the EPR spectra via numerical Fourier transformation of the time-domain signals. In most cases, absolute values of the ZFS parameters are extracted from the measured zero-field EPR frequencies, and the signs can be determined by zero-field measurements at two different temperatures. Field-dependent EPR measurements further allow refined determination of the ZFS parameters and access to the g -factor. The results show good agreement with those obtained by other methods. The simplicity of the method portends wide applicability in chemistry, biology and material science.

Entropy-based complexity of the cardiovascular control in Parkinson disease: comparison between binning and k-nearest-neighbor approaches.

PubMed

Porta, Alberto; Bari, Vlasta; Bassani, Tito; Marchi, Andrea; Tassin, Stefano; Canesi, Margherita; Barbic, Franca; Furlan, Raffaello

2013-01-01

Entropy-based approaches are frequently used to quantify complexity of short-term cardiovascular control from spontaneous beat-to-beat variability of heart period (HP) and systolic arterial pressure (SAP). Among these tools the ones optimizing a critical parameter such as the pattern length are receiving more and more attention. This study compares two entropy-based techniques for the quantification of complexity making use of completely different strategies to optimize the pattern length. Comparison was carried out over HP and SAP variability series recorded from 12 Parkinson's disease (PD) patients without orthostatic hypotension or symptoms of orthostatic intolerance and 12 age-matched healthy control (HC) subjects. Regardless of the method, complexity of cardiovascular control increased in PD group, thus suggesting the early impairment of cardiovascular function.

Exploiting Bounded Signal Flow for Graph Orientation Based on Cause-Effect Pairs

NASA Astrophysics Data System (ADS)

Dorn, Britta; Hüffner, Falk; Krüger, Dominikus; Niedermeier, Rolf; Uhlmann, Johannes

We consider the following problem: Given an undirected network and a set of sender-receiver pairs, direct all edges such that the maximum number of "signal flows" defined by the pairs can be routed respecting edge directions. This problem has applications in communication networks and in understanding protein interaction based cell regulation mechanisms. Since this problem is NP-hard, research so far concentrated on polynomial-time approximation algorithms and tractable special cases. We take the viewpoint of parameterized algorithmics and examine several parameters related to the maximum signal flow over vertices or edges. We provide several fixed-parameter tractability results, and in one case a sharp complexity dichotomy between a linear-time solvable case and a slightly more general NP-hard case. We examine the value of these parameters for several real-world network instances. For many relevant cases, the NP-hard problem can be solved to optimality. In this way, parameterized analysis yields both deeper insight into the computational complexity and practical solving strategies.

Hybrid modeling and empirical analysis of automobile supply chain network

NASA Astrophysics Data System (ADS)

Sun, Jun-yan; Tang, Jian-ming; Fu, Wei-ping; Wu, Bing-ying

2017-05-01

Based on the connection mechanism of nodes which automatically select upstream and downstream agents, a simulation model for dynamic evolutionary process of consumer-driven automobile supply chain is established by integrating ABM and discrete modeling in the GIS-based map. Firstly, the rationality is proved by analyzing the consistency of sales and changes in various agent parameters between the simulation model and a real automobile supply chain. Second, through complex network theory, hierarchical structures of the model and relationships of networks at different levels are analyzed to calculate various characteristic parameters such as mean distance, mean clustering coefficients, and degree distributions. By doing so, it verifies that the model is a typical scale-free network and small-world network. Finally, the motion law of this model is analyzed from the perspective of complex self-adaptive systems. The chaotic state of the simulation system is verified, which suggests that this system has typical nonlinear characteristics. This model not only macroscopically illustrates the dynamic evolution of complex networks of automobile supply chain but also microcosmically reflects the business process of each agent. Moreover, the model construction and simulation of the system by means of combining CAS theory and complex networks supplies a novel method for supply chain analysis, as well as theory bases and experience for supply chain analysis of auto companies.

Matching of energetic, mechanic and control characteristics of positioning actuator

NASA Astrophysics Data System (ADS)

Y Nosova, N.; Misyurin, S. Yu; Kreinin, G. V.

2017-12-01

The problem of preliminary choice of parameters of the automated drive power channel is discussed. The drive of the mechatronic complex divides into two main units - power and control. The first determines the energy capabilities and, as a rule, the overall dimensions of the complex. The sufficient capacity of the power unit is a necessary condition for successful solution of control tasks without excessive complication of the control system structure. Preliminary selection of parameters is carried out based on the condition of providing the necessary drive power. The proposed approach is based on: a research of a sufficiently developed but not excessive dynamic model of the power block with the help of a conditional test control system; a transition to a normalized model with the formation of similarity criteria; constructing the synthesis procedure.

Magnetic localization and orientation of the capsule endoscope based on a random complex algorithm.

PubMed

He, Xiaoqi; Zheng, Zizhao; Hu, Chao

2015-01-01

The development of the capsule endoscope has made possible the examination of the whole gastrointestinal tract without much pain. However, there are still some important problems to be solved, among which, one important problem is the localization of the capsule. Currently, magnetic positioning technology is a suitable method for capsule localization, and this depends on a reliable system and algorithm. In this paper, based on the magnetic dipole model as well as magnetic sensor array, we propose nonlinear optimization algorithms using a random complex algorithm, applied to the optimization calculation for the nonlinear function of the dipole, to determine the three-dimensional position parameters and two-dimensional direction parameters. The stability and the antinoise ability of the algorithm is compared with the Levenberg-Marquart algorithm. The simulation and experiment results show that in terms of the error level of the initial guess of magnet location, the random complex algorithm is more accurate, more stable, and has a higher "denoise" capacity, with a larger range for initial guess values.

Parameter optimization, sensitivity, and uncertainty analysis of an ecosystem model at a forest flux tower site in the United States

USGS Publications Warehouse

Wu, Yiping; Liu, Shuguang; Huang, Zhihong; Yan, Wende

2014-01-01

Ecosystem models are useful tools for understanding ecological processes and for sustainable management of resources. In biogeochemical field, numerical models have been widely used for investigating carbon dynamics under global changes from site to regional and global scales. However, it is still challenging to optimize parameters and estimate parameterization uncertainty for complex process-based models such as the Erosion Deposition Carbon Model (EDCM), a modified version of CENTURY, that consider carbon, water, and nutrient cycles of ecosystems. This study was designed to conduct the parameter identifiability, optimization, sensitivity, and uncertainty analysis of EDCM using our developed EDCM-Auto, which incorporated a comprehensive R package—Flexible Modeling Framework (FME) and the Shuffled Complex Evolution (SCE) algorithm. Using a forest flux tower site as a case study, we implemented a comprehensive modeling analysis involving nine parameters and four target variables (carbon and water fluxes) with their corresponding measurements based on the eddy covariance technique. The local sensitivity analysis shows that the plant production-related parameters (e.g., PPDF1 and PRDX) are most sensitive to the model cost function. Both SCE and FME are comparable and performed well in deriving the optimal parameter set with satisfactory simulations of target variables. Global sensitivity and uncertainty analysis indicate that the parameter uncertainty and the resulting output uncertainty can be quantified, and that the magnitude of parameter-uncertainty effects depends on variables and seasons. This study also demonstrates that using the cutting-edge R functions such as FME can be feasible and attractive for conducting comprehensive parameter analysis for ecosystem modeling.

Hydrological model parameter dimensionality is a weak measure of prediction uncertainty

NASA Astrophysics Data System (ADS)

Pande, S.; Arkesteijn, L.; Savenije, H.; Bastidas, L. A.

2015-04-01

This paper shows that instability of hydrological system representation in response to different pieces of information and associated prediction uncertainty is a function of model complexity. After demonstrating the connection between unstable model representation and model complexity, complexity is analyzed in a step by step manner. This is done measuring differences between simulations of a model under different realizations of input forcings. Algorithms are then suggested to estimate model complexity. Model complexities of the two model structures, SAC-SMA (Sacramento Soil Moisture Accounting) and its simplified version SIXPAR (Six Parameter Model), are computed on resampled input data sets from basins that span across the continental US. The model complexities for SIXPAR are estimated for various parameter ranges. It is shown that complexity of SIXPAR increases with lower storage capacity and/or higher recession coefficients. Thus it is argued that a conceptually simple model structure, such as SIXPAR, can be more complex than an intuitively more complex model structure, such as SAC-SMA for certain parameter ranges. We therefore contend that magnitudes of feasible model parameters influence the complexity of the model selection problem just as parameter dimensionality (number of parameters) does and that parameter dimensionality is an incomplete indicator of stability of hydrological model selection and prediction problems.

Flight control application of new stability robustness bounds for linear uncertain systems

NASA Technical Reports Server (NTRS)

Yedavalli, Rama K.

1993-01-01

This paper addresses the issue of obtaining bounds on the real parameter perturbations of a linear state-space model for robust stability. Based on Kronecker algebra, new, easily computable sufficient bounds are derived that are much less conservative than the existing bounds since the technique is meant for only real parameter perturbations (in contrast to specializing complex variation case to real parameter case). The proposed theory is illustrated with application to several flight control examples.

Testing the criterion for correct convergence in the complex Langevin method

NASA Astrophysics Data System (ADS)

Nagata, Keitaro; Nishimura, Jun; Shimasaki, Shinji

2018-05-01

Recently the complex Langevin method (CLM) has been attracting attention as a solution to the sign problem, which occurs in Monte Carlo calculations when the effective Boltzmann weight is not real positive. An undesirable feature of the method, however, was that it can happen in some parameter regions that the method yields wrong results even if the Langevin process reaches equilibrium without any problem. In our previous work, we proposed a practical criterion for correct convergence based on the probability distribution of the drift term that appears in the complex Langevin equation. Here we demonstrate the usefulness of this criterion in two solvable theories with many dynamical degrees of freedom, i.e., two-dimensional Yang-Mills theory with a complex coupling constant and the chiral Random Matrix Theory for finite density QCD, which were studied by the CLM before. Our criterion can indeed tell the parameter regions in which the CLM gives correct results.

Fast graph-based relaxed clustering for large data sets using minimal enclosing ball.

PubMed

Qian, Pengjiang; Chung, Fu-Lai; Wang, Shitong; Deng, Zhaohong

2012-06-01

Although graph-based relaxed clustering (GRC) is one of the spectral clustering algorithms with straightforwardness and self-adaptability, it is sensitive to the parameters of the adopted similarity measure and also has high time complexity O(N(3)) which severely weakens its usefulness for large data sets. In order to overcome these shortcomings, after introducing certain constraints for GRC, an enhanced version of GRC [constrained GRC (CGRC)] is proposed to increase the robustness of GRC to the parameters of the adopted similarity measure, and accordingly, a novel algorithm called fast GRC (FGRC) based on CGRC is developed in this paper by using the core-set-based minimal enclosing ball approximation. A distinctive advantage of FGRC is that its asymptotic time complexity is linear with the data set size N. At the same time, FGRC also inherits the straightforwardness and self-adaptability from GRC, making the proposed FGRC a fast and effective clustering algorithm for large data sets. The advantages of FGRC are validated by various benchmarking and real data sets.

Precision and accuracy in smFRET based structural studies—A benchmark study of the Fast-Nano-Positioning System

NASA Astrophysics Data System (ADS)

Nagy, Julia; Eilert, Tobias; Michaelis, Jens

2018-03-01

Modern hybrid structural analysis methods have opened new possibilities to analyze and resolve flexible protein complexes where conventional crystallographic methods have reached their limits. Here, the Fast-Nano-Positioning System (Fast-NPS), a Bayesian parameter estimation-based analysis method and software, is an interesting method since it allows for the localization of unknown fluorescent dye molecules attached to macromolecular complexes based on single-molecule Förster resonance energy transfer (smFRET) measurements. However, the precision, accuracy, and reliability of structural models derived from results based on such complex calculation schemes are oftentimes difficult to evaluate. Therefore, we present two proof-of-principle benchmark studies where we use smFRET data to localize supposedly unknown positions on a DNA as well as on a protein-nucleic acid complex. Since we use complexes where structural information is available, we can compare Fast-NPS localization to the existing structural data. In particular, we compare different dye models and discuss how both accuracy and precision can be optimized.

Remote sensing of environmental particulate pollutants - Optical methods for determinations of size distribution and complex refractive index

NASA Technical Reports Server (NTRS)

Fymat, A. L.

1978-01-01

A unifying approach, based on a generalization of Pearson's differential equation of statistical theory, is proposed for both the representation of particulate size distribution and the interpretation of radiometric measurements in terms of this parameter. A single-parameter gamma-type distribution is introduced, and it is shown that inversion can only provide the dimensionless parameter, r/ab (where r = particle radius, a = effective radius, b = effective variance), at least when the distribution vanishes at both ends. The basic inversion problem in reconstructing the particle size distribution is analyzed, and the existing methods are reviewed (with emphasis on their capabilities) and classified. A two-step strategy is proposed for simultaneously determining the complex refractive index and reconstructing the size distribution of atmospheric particulates.

The multiple complex exponential model and its application to EEG analysis

NASA Astrophysics Data System (ADS)

Chen, Dao-Mu; Petzold, J.

The paper presents a novel approach to the analysis of the EEG signal, which is based on a multiple complex exponential (MCE) model. Parameters of the model are estimated using a nonharmonic Fourier expansion algorithm. The central idea of the algorithm is outlined, and the results, estimated on the basis of simulated data, are presented and compared with those obtained by the conventional methods of signal analysis. Preliminary work on various application possibilities of the MCE model in EEG data analysis is described. It is shown that the parameters of the MCE model reflect the essential information contained in an EEG segment. These parameters characterize the EEG signal in a more objective way because they are closer to the recent supposition of the nonlinear character of the brain's dynamic behavior.

Determining fundamental properties of matter created in ultrarelativistic heavy-ion collisions

NASA Astrophysics Data System (ADS)

Novak, J.; Novak, K.; Pratt, S.; Vredevoogd, J.; Coleman-Smith, C. E.; Wolpert, R. L.

2014-03-01

Posterior distributions for physical parameters describing relativistic heavy-ion collisions, such as the viscosity of the quark-gluon plasma, are extracted through a comparison of hydrodynamic-based transport models to experimental results from 100AGeV+100AGeV Au +Au collisions at the Relativistic Heavy Ion Collider. By simultaneously varying six parameters and by evaluating several classes of observables, we are able to explore the complex intertwined dependencies of observables on model parameters. The methods provide a full multidimensional posterior distribution for the model output, including a range of acceptable values for each parameter, and reveal correlations between them. The breadth of observables and the number of parameters considered here go beyond previous studies in this field. The statistical tools, which are based upon Gaussian process emulators, are tested in detail and should be extendable to larger data sets and a higher number of parameters.

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.

Dimensional Precision Research of Wax Molding Rapid Prototyping based on Droplet Injection

NASA Astrophysics Data System (ADS)

Mingji, Huang; Geng, Wu; yan, Shan

2017-11-01

The traditional casting process is complex, the mold is essential products, mold quality directly affect the quality of the product. With the method of rapid prototyping 3D printing to produce mold prototype. The utility wax model has the advantages of high speed, low cost and complex structure. Using the orthogonal experiment as the main method, analysis each factors of size precision. The purpose is to obtain the optimal process parameters, to improve the dimensional accuracy of production based on droplet injection molding.

The design of dual-mode complex signal processors based on quadratic modular number codes

NASA Astrophysics Data System (ADS)

Jenkins, W. K.; Krogmeier, J. V.

1987-04-01

It has been known for a long time that quadratic modular number codes admit an unusual representation of complex numbers which leads to complete decoupling of the real and imaginary channels, thereby simplifying complex multiplication and providing error isolation between the real and imaginary channels. This paper first presents a tutorial review of the theory behind the different types of complex modular rings (fields) that result from particular parameter selections, and then presents a theory for a 'dual-mode' complex signal processor based on the choice of augmented power-of-2 moduli. It is shown how a diminished-1 binary code, used by previous designers for the realization of Fermat number transforms, also leads to efficient realizations for dual-mode complex arithmetic for certain augmented power-of-2 moduli. Then a design is presented for a recursive complex filter based on a ROM/ACCUMULATOR architecture and realized in an augmented power-of-2 quadratic code, and a computer-generated example of a complex recursive filter is shown to illustrate the principles of the theory.

Cadmium stress assessment based on the electrocardiogram characteristics of zebra fish (Danio rerio): QRS complex could play an important role.

PubMed

Xing, Na; Ji, Lizhen; Song, Jie; Ma, Jingchun; Li, Shangge; Ren, Zongming; Xu, Fei; Zhu, Jianping

2017-10-01

The electrocardiogram (ECG) of zebra fish (Danio rerio) expresses cardiac features that are similar to humans. Here we use sharp microelectrode measurements to obtain ECG characteristics in adult zebra fish and analyze the effects of cadmium chloride (CdCl 2 ) on the heart. We observe the overall changes of ECG parameters in different treatments (0.1 TU, 0.5 TU and 1.0 TU CdCl 2 ), including P wave, Q wave, R wave, S wave, T wave, PR interval (atrial contraction), QRS complex (ventricular depolarization), ST segment, and QT interval (ventricular repolarization). The trends of the ECG parameters showed some responses to the concentration and exposure time of CdCl 2 , but it was difficult to obtain more information about the useful indicators in water quality assessment depending on tendency analysis alone. A self-organizing map (SOM) showed that P values, R values, and T values were similar; R wave and T wave amplitude were similar; and most important, QRS value was similar to the CdCl 2 stress according to the classified data patterns including CdCl 2 stress (E) and ECG components based on the Ward linkage. It suggested that the duration of QRS complex was related to environmental stress E directly. The specification and evaluation of ECG parameters in Cd 2+ pollution suggested that there is a markedly significant correlation between QRS complex and CdCl 2 stress with the highest r (0.729) and the smallest p (0.002) among all ECG characteristics. In this case, it is concluded that QRS complex can be used as an indicator in the CdCl 2 stress assessment due to the lowest AIC data abased on the linear regression model between the CdCl 2 stress and ECG parameters. Copyright © 2017 Elsevier B.V. All rights reserved.

Development and evaluation of a musculoskeletal model of the elbow joint complex

NASA Technical Reports Server (NTRS)

Gonzalez, Roger V.; Hutchins, E. L.; Barr, Ronald E.; Abraham, Lawrence D.

1993-01-01

This paper describes the development and evaluation of a musculoskeletal model that represents human elbow flexion-extension and forearm pronation-supination. The length, velocity, and moment arm for each of the eight musculotendon actuators were based on skeletal anatomy and position. Musculotendon parameters were determined for each actuator and verified by comparing analytical torque-angle curves with experimental joint torque data. The parameters and skeletal geometry were also utilized in the musculoskeletal model for the analysis of ballistic elbow joint complex movements. The key objective was to develop a computational model, guided by parameterized optimal control, to investigate the relationship among patterns of muscle excitation, individual muscle forces, and movement kinematics. The model was verified using experimental kinematic, torque, and electromyographic data from volunteer subjects performing ballistic elbow joint complex movements.

Synthesis, spectroscopic characterization, antimicrobial and antitumor studies of mono-, bi- and tri-nuclear metal complexes of a new Schiff base ligand derived from o-acetoacetylphenol

NASA Astrophysics Data System (ADS)

Adly, Omima M. I.; Shebl, Magdy; El-Shafiy, Hoda F.; Khalil, Saied M. E.; Taha, A.; Mahdi, Mohammed A. N.

2017-12-01

New mono-, bi- and trinuclear metal complexes of Cr(III), Mn(II), Fe(III), Co(II), Ni(II), Cu(II), Zn(II), Cd(II) and UO2(VI) with a new Schiff base ligand H3L; ((E)-2-hydroxy-N‧-(4-(2-hydroxyphenyl)-4-oxobutan-2-ylidene)) benzohydrazide (H3L) have been synthesized. The ligand and its metal complexes were characterized by elemental analyses, IR, 1H NMR, electronic, ESR and mass spectra, conductivity and magnetic susceptibility measurements as well as thermal analyses. The metal complexes exhibited octahedral and tetrahedral geometrical arrangements. Kinetic parameters (Ea, A, ΔH, ΔS and ΔG) of the thermal decomposition stages have been evaluated using Coats-Redfern equations. Structural parameters of the synthesized compounds were calculated on the basis of DFT level implemented in the Gaussian 09 program and Hyperchem 7.52 and correlated with the experimental data. The antimicrobial activity of the present compounds was screened against Gram-positive bacteria (Staphylococcus aureus and Bacillus subtilis), Gram-negative bacteria (Salmonella typhimurium and Escherichia coli), yeast (Candida albicans) and fungus (Aspergillus fumigatus). The antitumor activity of the ligand and its Ni(II) and Cu(II) complexes was investigated against HepG2 cell line.

Generation of Long-time Complex Signals for Testing the Instruments for Detection of Voltage Quality Disturbances

NASA Astrophysics Data System (ADS)

Živanović, Dragan; Simić, Milan; Kokolanski, Zivko; Denić, Dragan; Dimcev, Vladimir

2018-04-01

Software supported procedure for generation of long-time complex test sentences, suitable for testing the instruments for detection of standard voltage quality (VQ) disturbances is presented in this paper. This solution for test signal generation includes significant improvements of computer-based signal generator presented and described in the previously published paper [1]. The generator is based on virtual instrumentation software for defining the basic signal parameters, data acquisition card NI 6343, and power amplifier for amplification of output voltage level to the nominal RMS voltage value of 230 V. Definition of basic signal parameters in LabVIEW application software is supported using Script files, which allows simple repetition of specific test signals and combination of more different test sequences in the complex composite test waveform. The basic advantage of this generator compared to the similar solutions for signal generation is the possibility for long-time test sequence generation according to predefined complex test scenarios, including various combinations of VQ disturbances defined in accordance with the European standard EN50160. Experimental verification of the presented signal generator capability is performed by testing the commercial power quality analyzer Fluke 435 Series II. In this paper are shown some characteristic complex test signals with various disturbances and logged data obtained from the tested power quality analyzer.

Rainfall runoff modelling of the Upper Ganga and Brahmaputra basins using PERSiST.

PubMed

Futter, M N; Whitehead, P G; Sarkar, S; Rodda, H; Crossman, J

2015-06-01

There are ongoing discussions about the appropriate level of complexity and sources of uncertainty in rainfall runoff models. Simulations for operational hydrology, flood forecasting or nutrient transport all warrant different levels of complexity in the modelling approach. More complex model structures are appropriate for simulations of land-cover dependent nutrient transport while more parsimonious model structures may be adequate for runoff simulation. The appropriate level of complexity is also dependent on data availability. Here, we use PERSiST; a simple, semi-distributed dynamic rainfall-runoff modelling toolkit to simulate flows in the Upper Ganges and Brahmaputra rivers. We present two sets of simulations driven by single time series of daily precipitation and temperature using simple (A) and complex (B) model structures based on uniform and hydrochemically relevant land covers respectively. Models were compared based on ensembles of Bayesian Information Criterion (BIC) statistics. Equifinality was observed for parameters but not for model structures. Model performance was better for the more complex (B) structural representations than for parsimonious model structures. The results show that structural uncertainty is more important than parameter uncertainty. The ensembles of BIC statistics suggested that neither structural representation was preferable in a statistical sense. Simulations presented here confirm that relatively simple models with limited data requirements can be used to credibly simulate flows and water balance components needed for nutrient flux modelling in large, data-poor basins.

Innovation Analysis Approach to Design Parameters of High Speed Train Carriage and Their Intrinsic Complexity Relationships

NASA Astrophysics Data System (ADS)

Xiao, Shou-Ne; Wang, Ming-Meng; Hu, Guang-Zhong; Yang, Guang-Wu

2017-09-01

In view of the problem that it's difficult to accurately grasp the influence range and transmission path of the vehicle top design requirements on the underlying design parameters. Applying directed-weighted complex network to product parameter model is an important method that can clarify the relationships between product parameters and establish the top-down design of a product. The relationships of the product parameters of each node are calculated via a simple path searching algorithm, and the main design parameters are extracted by analysis and comparison. A uniform definition of the index formula for out-in degree can be provided based on the analysis of out-in-degree width and depth and control strength of train carriage body parameters. Vehicle gauge, axle load, crosswind and other parameters with higher values of the out-degree index are the most important boundary conditions; the most considerable performance indices are the parameters that have higher values of the out-in-degree index including torsional stiffness, maximum testing speed, service life of the vehicle, and so on; the main design parameters contain train carriage body weight, train weight per extended metre, train height and other parameters with higher values of the in-degree index. The network not only provides theoretical guidance for exploring the relationship of design parameters, but also further enriches the application of forward design method to high-speed trains.

Stochastic inversion of cross-borehole radar data from metalliferous vein detection

NASA Astrophysics Data System (ADS)

Zeng, Zhaofa; Huai, Nan; Li, Jing; Zhao, Xueyu; Liu, Cai; Hu, Yingsa; Zhang, Ling; Hu, Zuzhi; Yang, Hui

2017-12-01

In the exploration and evaluation of the metalliferous veins with a cross-borehole radar system, traditional linear inversion methods (least squares inversion, LSQR) only get indirect parameters (permittivity, resistivity, or velocity) to estimate the target structure. They cannot accurately reflect the geological parameters of the metalliferous veins’ media properties. In order to get the intrinsic geological parameters and internal distribution, in this paper, we build a metalliferous veins model based on the stochastic effective medium theory, and carry out stochastic inversion and parameter estimation based on the Monte Carlo sampling algorithm. Compared with conventional LSQR, the stochastic inversion can get higher resolution inversion permittivity and velocity of the target body. We can estimate more accurately the distribution characteristics of abnormality and target internal parameters. It provides a new research idea to evaluate the properties of complex target media.

Intelligent Decisions Need Intelligent Choice of Models and Data - a Bayesian Justifiability Analysis for Models with Vastly Different Complexity

NASA Astrophysics Data System (ADS)

Nowak, W.; Schöniger, A.; Wöhling, T.; Illman, W. A.

2016-12-01

Model-based decision support requires justifiable models with good predictive capabilities. This, in turn, calls for a fine adjustment between predictive accuracy (small systematic model bias that can be achieved with rather complex models), and predictive precision (small predictive uncertainties that can be achieved with simpler models with fewer parameters). The implied complexity/simplicity trade-off depends on the availability of informative data for calibration. If not available, additional data collection can be planned through optimal experimental design. We present a model justifiability analysis that can compare models of vastly different complexity. It rests on Bayesian model averaging (BMA) to investigate the complexity/performance trade-off dependent on data availability. Then, we disentangle the complexity component from the performance component. We achieve this by replacing actually observed data by realizations of synthetic data predicted by the models. This results in a "model confusion matrix". Based on this matrix, the modeler can identify the maximum model complexity that can be justified by the available (or planned) amount and type of data. As a side product, the matrix quantifies model (dis-)similarity. We apply this analysis to aquifer characterization via hydraulic tomography, comparing four models with a vastly different number of parameters (from a homogeneous model to geostatistical random fields). As a testing scenario, we consider hydraulic tomography data. Using subsets of these data, we determine model justifiability as a function of data set size. The test case shows that geostatistical parameterization requires a substantial amount of hydraulic tomography data to be justified, while a zonation-based model can be justified with more limited data set sizes. The actual model performance (as opposed to model justifiability), however, depends strongly on the quality of prior geological information.

Synthesis, characterization, crystal structure, DNA/BSA binding ability and antibacterial activity of asymmetric europium complex based on 1,10- phenanthroline

NASA Astrophysics Data System (ADS)

Alfi, Nafiseh; Khorasani-Motlagh, Mozhgan; Rezvani, Ali Reza; Noroozifar, Meissam; Molčanov, Krešimir

2017-06-01

A heteroleptic europium coordination compound formulated as [Eu(phen)2(OH2)2(Cl)2](Cl)(H2O) (phen = 1,10-phenanthroline), has been synthesized and characterized by elemental analysis, FT-IR spectroscopy, and single-crystal X-ray diffractometer. Crystal structure analysis reveals the complex is crystallized in orthorhombic system with Pca21 space group. Electronic absorption and various emission methods for investigation of the binding system of europium(III) complex to Fish Salmon deoxyribonucleic acid (FS-DNA) and Bovamin Serum Albumin (BSA) have been explored. Furthermore, the binding constants, binding sites and the corresponding thermodynamic parameters of the interaction system based on the van't Hoff equation for FS-DNA and BSA were calculated. The thermodynamic parameters reflect the exothermic nature of emission process (ΔH°<0 and ΔS°<0). The experimental results seem to indicate that the [Eu(phen)2(OH2)2(Cl)2](Cl)(H2O) bound to FS-DNA by non-intercalative mode which the groove binding is preferable mode. Also, the complex exhibits a brilliant antimicrobial activity in vitro against standard bacterial strains.

Deficiencies of the cryptography based on multiple-parameter fractional Fourier transform.

PubMed

Ran, Qiwen; Zhang, Haiying; Zhang, Jin; Tan, Liying; Ma, Jing

2009-06-01

Methods of image encryption based on fractional Fourier transform have an incipient flaw in security. We show that the schemes have the deficiency that one group of encryption keys has many groups of keys to decrypt the encrypted image correctly for several reasons. In some schemes, many factors result in the deficiencies, such as the encryption scheme based on multiple-parameter fractional Fourier transform [Opt. Lett.33, 581 (2008)]. A modified method is proposed to avoid all the deficiencies. Security and reliability are greatly improved without increasing the complexity of the encryption process. (c) 2009 Optical Society of America.

Uncertainties of flood frequency estimation approaches based on continuous simulation using data resampling

NASA Astrophysics Data System (ADS)

Arnaud, Patrick; Cantet, Philippe; Odry, Jean

2017-11-01

Flood frequency analyses (FFAs) are needed for flood risk management. Many methods exist ranging from classical purely statistical approaches to more complex approaches based on process simulation. The results of these methods are associated with uncertainties that are sometimes difficult to estimate due to the complexity of the approaches or the number of parameters, especially for process simulation. This is the case of the simulation-based FFA approach called SHYREG presented in this paper, in which a rainfall generator is coupled with a simple rainfall-runoff model in an attempt to estimate the uncertainties due to the estimation of the seven parameters needed to estimate flood frequencies. The six parameters of the rainfall generator are mean values, so their theoretical distribution is known and can be used to estimate the generator uncertainties. In contrast, the theoretical distribution of the single hydrological model parameter is unknown; consequently, a bootstrap method is applied to estimate the calibration uncertainties. The propagation of uncertainty from the rainfall generator to the hydrological model is also taken into account. This method is applied to 1112 basins throughout France. Uncertainties coming from the SHYREG method and from purely statistical approaches are compared, and the results are discussed according to the length of the recorded observations, basin size and basin location. Uncertainties of the SHYREG method decrease as the basin size increases or as the length of the recorded flow increases. Moreover, the results show that the confidence intervals of the SHYREG method are relatively small despite the complexity of the method and the number of parameters (seven). This is due to the stability of the parameters and takes into account the dependence of uncertainties due to the rainfall model and the hydrological calibration. Indeed, the uncertainties on the flow quantiles are on the same order of magnitude as those associated with the use of a statistical law with two parameters (here generalised extreme value Type I distribution) and clearly lower than those associated with the use of a three-parameter law (here generalised extreme value Type II distribution). For extreme flood quantiles, the uncertainties are mostly due to the rainfall generator because of the progressive saturation of the hydrological model.

Research on On-Line Modeling of Fed-Batch Fermentation Process Based on v-SVR

NASA Astrophysics Data System (ADS)

Ma, Yongjun

The fermentation process is very complex and non-linear, many parameters are not easy to measure directly on line, soft sensor modeling is a good solution. This paper introduces v-support vector regression (v-SVR) for soft sensor modeling of fed-batch fermentation process. v-SVR is a novel type of learning machine. It can control the accuracy of fitness and prediction error by adjusting the parameter v. An on-line training algorithm is discussed in detail to reduce the training complexity of v-SVR. The experimental results show that v-SVR has low error rate and better generalization with appropriate v.

Ensemble-Based Parameter Estimation in a Coupled General Circulation Model

DOE PAGES

Liu, Y.; Liu, Z.; Zhang, S.; ...

2014-09-10

Parameter estimation provides a potentially powerful approach to reduce model bias for complex climate models. Here, in a twin experiment framework, the authors perform the first parameter estimation in a fully coupled ocean–atmosphere general circulation model using an ensemble coupled data assimilation system facilitated with parameter estimation. The authors first perform single-parameter estimation and then multiple-parameter estimation. In the case of the single-parameter estimation, the error of the parameter [solar penetration depth (SPD)] is reduced by over 90% after ~40 years of assimilation of the conventional observations of monthly sea surface temperature (SST) and salinity (SSS). The results of multiple-parametermore » estimation are less reliable than those of single-parameter estimation when only the monthly SST and SSS are assimilated. Assimilating additional observations of atmospheric data of temperature and wind improves the reliability of multiple-parameter estimation. The errors of the parameters are reduced by 90% in ~8 years of assimilation. Finally, the improved parameters also improve the model climatology. With the optimized parameters, the bias of the climatology of SST is reduced by ~90%. Altogether, this study suggests the feasibility of ensemble-based parameter estimation in a fully coupled general circulation model.« less

Deriving urban dynamic evolution rules from self-adaptive cellular automata with multi-temporal remote sensing images

NASA Astrophysics Data System (ADS)

He, Yingqing; Ai, Bin; Yao, Yao; Zhong, Fajun

2015-06-01

Cellular automata (CA) have proven to be very effective for simulating and predicting the spatio-temporal evolution of complex geographical phenomena. Traditional methods generally pose problems in determining the structure and parameters of CA for a large, complex region or a long-term simulation. This study presents a self-adaptive CA model integrated with an artificial immune system to discover dynamic transition rules automatically. The model's parameters are allowed to be self-modified with the application of multi-temporal remote sensing images: that is, the CA can adapt itself to the changed and complex environment. Therefore, urban dynamic evolution rules over time can be efficiently retrieved by using this integrated model. The proposed AIS-based CA model was then used to simulate the rural-urban land conversion of Guangzhou city, located in the core of China's Pearl River Delta. The initial urban land was directly classified from TM satellite image in the year 1990. Urban land in the years 1995, 2000, 2005, 2009 and 2012 was correspondingly used as the observed data to calibrate the model's parameters. With the quantitative index figure of merit (FoM) and pattern similarity, the comparison was further performed between the AIS-based model and a Logistic CA model. The results indicate that the AIS-based CA model can perform better and with higher precision in simulating urban evolution, and the simulated spatial pattern is closer to the actual development situation.

Determination of full piezoelectric complex parameters using gradient-based optimization algorithm

NASA Astrophysics Data System (ADS)

Kiyono, C. Y.; Pérez, N.; Silva, E. C. N.

2016-02-01

At present, numerical techniques allow the precise simulation of mechanical structures, but the results are limited by the knowledge of the material properties. In the case of piezoelectric ceramics, the full model determination in the linear range involves five elastic, three piezoelectric, and two dielectric complex parameters. A successful solution to obtaining piezoceramic properties consists of comparing the experimental measurement of the impedance curve and the results of a numerical model by using the finite element method (FEM). In the present work, a new systematic optimization method is proposed to adjust the full piezoelectric complex parameters in the FEM model. Once implemented, the method only requires the experimental data (impedance modulus and phase data acquired by an impedometer), material density, geometry, and initial values for the properties. This method combines a FEM routine implemented using an 8-noded axisymmetric element with a gradient-based optimization routine based on the method of moving asymptotes (MMA). The main objective of the optimization procedure is minimizing the quadratic difference between the experimental and numerical electrical conductance and resistance curves (to consider resonance and antiresonance frequencies). To assure the convergence of the optimization procedure, this work proposes restarting the optimization loop whenever the procedure ends in an undesired or an unfeasible solution. Two experimental examples using PZ27 and APC850 samples are presented to test the precision of the method and to check the dependency of the frequency range used, respectively.

Complex Impedance of Fast Optical Transition Edge Sensors up to 30 MHz

NASA Astrophysics Data System (ADS)

Hattori, K.; Kobayashi, R.; Numata, T.; Inoue, S.; Fukuda, D.

2018-03-01

Optical transition edge sensors (TESs) are characterized by a very fast response, of the order of μs, which is 10^3 times faster than TESs for X-ray and gamma-ray. To extract important parameters associated with the optical TES, complex impedances at high frequencies (> 1 MHz) need to be measured, where the parasitic impedance in the circuit and reflections of electrical signals due to discontinuities in the characteristic impedance of the readout circuits become significant. This prevents the measurements of the current sensitivity β , which can be extracted from the complex impedance. In usual setups, it is hard to build a circuit model taking into account the parasitic impedances and reflections. In this study, we present an alternative method to estimate a transfer function without investigating the details of the entire circuit. Based on this method, the complex impedance up to 30 MHz was measured. The parameters were extracted from the impedance and were compared with other measurements. Using these parameters, we calculated the theoretical limit on an energy resolution and compared it with the measured energy resolution. In this paper, the reasons for the deviation of the measured value from theoretically predicted values will be discussed.

Rapid and precise determination of zero-field splittings by terahertz time-domain electron paramagnetic resonance spectroscopy† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7sc00830a Click here for additional data file.

PubMed Central

Lu, Jian; Ozel, I. Ozge; Belvin, Carina A.; Li, Xian; Skorupskii, Grigorii; Sun, Lei; Ofori-Okai, Benjamin K.; Dincă, Mircea; Gedik, Nuh

2017-01-01

Zero-field splitting (ZFS) parameters are fundamentally tied to the geometries of metal ion complexes. Despite their critical importance for understanding the magnetism and spectroscopy of metal complexes, they are not routinely available through general laboratory-based techniques, and are often inferred from magnetism data. Here we demonstrate a simple tabletop experimental approach that enables direct and reliable determination of ZFS parameters in the terahertz (THz) regime. We report time-domain measurements of electron paramagnetic resonance (EPR) signals associated with THz-frequency ZFSs in molecular complexes containing high-spin transition-metal ions. We measure the temporal profiles of the free-induction decays of spin resonances in the complexes at zero and nonzero external magnetic fields, and we derive the EPR spectra via numerical Fourier transformation of the time-domain signals. In most cases, absolute values of the ZFS parameters are extracted from the measured zero-field EPR frequencies, and the signs can be determined by zero-field measurements at two different temperatures. Field-dependent EPR measurements further allow refined determination of the ZFS parameters and access to the g-factor. The results show good agreement with those obtained by other methods. The simplicity of the method portends wide applicability in chemistry, biology and material science. PMID:29163882

Affinity to bovine serum albumin and anticancer activity of some new water-soluble metal Schiff base complexes

NASA Astrophysics Data System (ADS)

Asadi, Mozaffar; Asadi, Zahra; Zarei, Leila; Sadi, Somaye Barzegar; Amirghofran, Zahra

2014-12-01

Metal Schiff-base complexes show biological activity but they are usually insoluble in water so four new water-soluble metal Schiff base complexes of Na2[M(5-SO3-1,2-salben]; (5-SO3-1,2-salben denoted N,N";-bis(5-sulphosalicyliden)-1,2-diaminobenzylamine and M = Mg, Mn, Cu, Zn) were synthesized and characterized. The formation constants of the metal complexes were determined by UV-Vis absorption spectroscopy. The interaction of these complexes with bovine serum albumin (BSA) was studied by fluorescence spectroscopy. Type of quenching, binding constants, number of binding sites and binding stoichiometries were determined by fluorescence quenching method. The results showed that the mentioned complexes strongly bound to BSA. Thermodynamic parameters indicated that hydrophobic association was the major binding force and that the interaction was entropy driven and enthalpically disfavoured. The displacement experiment showed that these complexes could bind to the subdomain IIA (site I) of albumin. Furthermore the synchronous fluorescence spectra showed that the microenvironment of the tryptophan residues was not apparently changed. Based on the Förster theory of non-radiation energy transfer, the distance between the donor (Trp residues) and the acceptor metal complexes was obtained. The growth inhibitory effect of complexes toward the K562 cancer cell line was measured.

Joint histogram-based cost aggregation for stereo matching.

PubMed

Min, Dongbo; Lu, Jiangbo; Do, Minh N

2013-10-01

This paper presents a novel method for performing efficient cost aggregation in stereo matching. The cost aggregation problem is reformulated from the perspective of a histogram, giving us the potential to reduce the complexity of the cost aggregation in stereo matching significantly. Differently from previous methods which have tried to reduce the complexity in terms of the size of an image and a matching window, our approach focuses on reducing the computational redundancy that exists among the search range, caused by a repeated filtering for all the hypotheses. Moreover, we also reduce the complexity of the window-based filtering through an efficient sampling scheme inside the matching window. The tradeoff between accuracy and complexity is extensively investigated by varying the parameters used in the proposed method. Experimental results show that the proposed method provides high-quality disparity maps with low complexity and outperforms existing local methods. This paper also provides new insights into complexity-constrained stereo-matching algorithm design.

Automated Selection of Regions of Interest for Intensity-based FRET Analysis of Transferrin Endocytic Trafficking in Normal vs. Cancer Cells

PubMed Central

Talati, Ronak; Vanderpoel, Andrew; Eladdadi, Amina; Anderson, Kate; Abe, Ken; Barroso, Margarida

2013-01-01

The overexpression of certain membrane-bound receptors is a hallmark of cancer progression and it has been suggested to affect the organization, activation, recycling and down-regulation of receptor-ligand complexes in human cancer cells. Thus, comparing receptor trafficking pathways in normal vs. cancer cells requires the ability to image cells expressing dramatically different receptor expression levels. Here, we have presented a significant technical advance to the analysis and processing of images collected using intensity based Förster resonance energy transfer (FRET) confocal microscopy. An automated Image J macro was developed to select region of interests (ROI) based on intensity and statistical-based thresholds within cellular images with reduced FRET signal. Furthermore, SSMD (strictly standardized mean differences), a statistical signal-to-noise ratio (SNR) evaluation parameter, was used to validate the quality of FRET analysis, in particular of ROI database selection. The Image J ROI selection macro together with SSMD as an evaluation parameter of SNR levels, were used to investigate the endocytic recycling of Tfn-TFR complexes at nanometer range resolution in human normal vs. breast cancer cells expressing significantly different levels of endogenous TFR. Here, the FRET-based assay demonstrates that Tfn-TFR complexes in normal epithelial vs. breast cancer cells show a significantly different E% behavior during their endocytic recycling pathway. Since E% is a relative measure of distance, we propose that these changes in E% levels represent conformational changes in Tfn-TFR complexes during endocytic pathway. Thus, our results indicate that Tfn-TFR complexes undergo different conformational changes in normal vs. cancer cells, indicating that the organization of Tfn-TFR complexes at the nanometer range is significantly altered during the endocytic recycling pathway in cancer cells. In summary, improvements in the automated selection of FRET ROI datasets allowed us to detect significant changes in E% with potential biological significance in human normal vs. cancer cells. PMID:23994873

Spectral characterization, thermal and biological activity studies of Schiff base complexes derived from 4,4‧-Methylenedianiline, ethanol amine and benzil

NASA Astrophysics Data System (ADS)

Emam, Sanaa Moustafa

2017-04-01

Some new metal(II) complexes of asymmetric Schiff base ligand were prepared by template technique. The shaped complexes are in binuclear structures and were explained through elemental analysis, molar conductivity, various spectroscopic methods (IR, U.V-Vis, XRD, ESR), thermal (TG) and magnetic moment measurements. The IR spectra were done demonstrating that the Schiff base ligand acts as neutral tetradentate moiety in all metal complexes. The electronic absorption spectra represented octahedral geometry for all complexes, while, the ESR spectra for Cu(II) complex showed axially symmetric g-tensor parameter with g׀׀ > g⊥ > 2.0023 indicating to 2B1g ground state with (dx2-y2)1 configuration. The nature of the solid residue created from TG estimations was affirmed utilizing IR and XRD spectra. The biological activity of the prepared complexes was studied against Land Snails. Additionally, the in vitro antitumor activity of the synthesized complexes with Hepatocellular Carcinoma cell (Hep-G2) was examined. It was observed that Zn(II) complex (5), exhibits a high inhibition of growth of the cell line with IC50 of 7.09 μg/mL.

Multi-objective calibration and uncertainty analysis of hydrologic models; A comparative study between formal and informal methods

NASA Astrophysics Data System (ADS)

Shafii, M.; Tolson, B.; Matott, L. S.

2012-04-01

Hydrologic modeling has benefited from significant developments over the past two decades. This has resulted in building of higher levels of complexity into hydrologic models, which eventually makes the model evaluation process (parameter estimation via calibration and uncertainty analysis) more challenging. In order to avoid unreasonable parameter estimates, many researchers have suggested implementation of multi-criteria calibration schemes. Furthermore, for predictive hydrologic models to be useful, proper consideration of uncertainty is essential. Consequently, recent research has emphasized comprehensive model assessment procedures in which multi-criteria parameter estimation is combined with statistically-based uncertainty analysis routines such as Bayesian inference using Markov Chain Monte Carlo (MCMC) sampling. Such a procedure relies on the use of formal likelihood functions based on statistical assumptions, and moreover, the Bayesian inference structured on MCMC samplers requires a considerably large number of simulations. Due to these issues, especially in complex non-linear hydrological models, a variety of alternative informal approaches have been proposed for uncertainty analysis in the multi-criteria context. This study aims at exploring a number of such informal uncertainty analysis techniques in multi-criteria calibration of hydrological models. The informal methods addressed in this study are (i) Pareto optimality which quantifies the parameter uncertainty using the Pareto solutions, (ii) DDS-AU which uses the weighted sum of objective functions to derive the prediction limits, and (iii) GLUE which describes the total uncertainty through identification of behavioral solutions. The main objective is to compare such methods with MCMC-based Bayesian inference with respect to factors such as computational burden, and predictive capacity, which are evaluated based on multiple comparative measures. The measures for comparison are calculated both for calibration and evaluation periods. The uncertainty analysis methodologies are applied to a simple 5-parameter rainfall-runoff model, called HYMOD.

Plasmonic complex fluids of nematiclike and helicoidal self-assemblies of gold nanorods with a negative order parameter.

PubMed

Liu, Qingkun; Senyuk, Bohdan; Tang, Jianwei; Lee, Taewoo; Qian, Jun; He, Sailing; Smalyukh, Ivan I

2012-08-24

We describe a soft matter system of self-organized oblate micelles and plasmonic gold nanorods that exhibit a negative orientational order parameter. Because of anisotropic surface anchoring interactions, colloidal gold nanorods tend to align perpendicular to the director describing the average orientation of normals to the discoidal micelles. Helicoidal structures of highly concentrated nanorods with a negative order parameter are realized by adding a chiral additive and are further controlled by means of confinement and mechanical stress. Polarization-sensitive absorption, scattering, and two-photon luminescence are used to characterize orientations and spatial distributions of nanorods. Self-alignment and effective-medium optical properties of these hybrid inorganic-organic complex fluids match predictions of a simple model based on anisotropic surface anchoring interactions of nanorods with the structured host medium.

Frequentist and Bayesian Orbital Parameter Estimaton from Radial Velocity Data Using RVLIN, BOOTTRAN, and RUN DMC

NASA Astrophysics Data System (ADS)

Nelson, Benjamin Earl; Wright, Jason Thomas; Wang, Sharon

2015-08-01

For this hack session, we will present three tools used in analyses of radial velocity exoplanet systems. RVLIN is a set of IDL routines used to quickly fit an arbitrary number of Keplerian curves to radial velocity data to find adequate parameter point estimates. BOOTTRAN is an IDL-based extension of RVLIN to provide orbital parameter uncertainties using bootstrap based on a Keplerian model. RUN DMC is a highly parallelized Markov chain Monte Carlo algorithm that employs an n-body model, primarily used for dynamically complex or poorly constrained exoplanet systems. We will compare the performance of these tools and their applications to various exoplanet systems.

Origami-inspired building block and parametric design for mechanical metamaterials

NASA Astrophysics Data System (ADS)

Jiang, Wei; Ma, Hua; Feng, Mingde; Yan, Leilei; Wang, Jiafu; Wang, Jun; Qu, Shaobo

2016-08-01

An origami-based building block of mechanical metamaterials is proposed and explained by introducing a mechanism model based on its geometry. According to our model, this origami mechanism supports response to uniaxial tension that depends on structure parameters. Hence, its mechanical properties can be tunable by adjusting the structure parameters. Experiments for poly lactic acid (PLA) samples were carried out, and the results are in good agreement with those of finite element analysis (FEA). This work may be useful for designing building blocks of mechanical metamaterials or other complex mechanical structures.

TWT transmitter fault prediction based on ANFIS

NASA Astrophysics Data System (ADS)

Li, Mengyan; Li, Junshan; Li, Shuangshuang; Wang, Wenqing; Li, Fen

2017-11-01

Fault prediction is an important component of health management, and plays an important role in the reliability guarantee of complex electronic equipments. Transmitter is a unit with high failure rate. The cathode performance of TWT is a common fault of transmitter. In this dissertation, a model based on a set of key parameters of TWT is proposed. By choosing proper parameters and applying adaptive neural network training model, this method, combined with analytic hierarchy process (AHP), has a certain reference value for the overall health judgment of TWT transmitters.

MCPB.py: A Python Based Metal Center Parameter Builder.

PubMed

Li, Pengfei; Merz, Kenneth M

2016-04-25

MCPB.py, a python based metal center parameter builder, has been developed to build force fields for the simulation of metal complexes employing the bonded model approach. It has an optimized code structure, with far fewer required steps than the previous developed MCPB program. It supports various AMBER force fields and more than 80 metal ions. A series of parametrization schemes to derive force constants and charge parameters are available within the program. We give two examples (one metalloprotein example and one organometallic compound example), indicating the program's ability to build reliable force fields for different metal ion containing complexes. The original version was released with AmberTools15. It is provided via the GNU General Public License v3.0 (GNU_GPL_v3) agreement and is free to download and distribute. MCPB.py provides a bridge between quantum mechanical calculations and molecular dynamics simulation software packages thereby enabling the modeling of metal ion centers. It offers an entry into simulating metal ions in a number of situations by providing an efficient way for researchers to handle the vagaries and difficulties associated with metal ion modeling.

Protonation of Different Goethite Surfaces - Unified Models for NaNO3 and NaCl Media.

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

Lutzenkirchen, Johannes; Boily, Jean F.; Gunneriusson, Lars

2008-01-01

Acid-base titration data for two goethites samples in sodium nitrate and sodium chloride media are discussed. The data are modelled based on various surface complexation models in the framework of the MUlti SIte Complexation (MUSIC) model. Various assumptions with respect to the goethite morphology are considered in determining the site density of the surface functional groups. The results from the various model applications are not statistically significant in terms of goodness of fit. More importantly, various published assumptions with respect to the goethite morphology (i.e. the contributions of different crystal planes and their repercussions on the “overall” site densities ofmore » the various surface functional groups) do not significantly affect the final model parameters. The simultaneous fit of the chloride and nitrate data results in electrolyte binding constants, which are applicable over a wide range of electrolyte concentrations including mixtures of chloride and nitrate. Model parameters for the high surface area goethite sample are in excellent agreement with parameters that were independently obtained by another group on different goethite titration data sets.« less

Lightweight filter architecture for energy efficient mobile vehicle localization based on a distributed acoustic sensor network.

PubMed

Kim, Keonwook

2013-08-23

The generic properties of an acoustic signal provide numerous benefits for localization by applying energy-based methods over a deployed wireless sensor network (WSN). However, the signal generated by a stationary target utilizes a significant amount of bandwidth and power in the system without providing further position information. For vehicle localization, this paper proposes a novel proximity velocity vector estimator (PVVE) node architecture in order to capture the energy from a moving vehicle and reject the signal from motionless automobiles around the WSN node. A cascade structure between analog envelope detector and digital exponential smoothing filter presents the velocity vector-sensitive output with low analog circuit and digital computation complexity. The optimal parameters in the exponential smoothing filter are obtained by analytical and mathematical methods for maximum variation over the vehicle speed. For stationary targets, the derived simulation based on the acoustic field parameters demonstrates that the system significantly reduces the communication requirements with low complexity and can be expected to extend the operation time considerably.

Effects of model complexity and priors on estimation using sequential importance sampling/resampling for species conservation

USGS Publications Warehouse

Dunham, Kylee; Grand, James B.

2016-01-01

We examined the effects of complexity and priors on the accuracy of models used to estimate ecological and observational processes, and to make predictions regarding population size and structure. State-space models are useful for estimating complex, unobservable population processes and making predictions about future populations based on limited data. To better understand the utility of state space models in evaluating population dynamics, we used them in a Bayesian framework and compared the accuracy of models with differing complexity, with and without informative priors using sequential importance sampling/resampling (SISR). Count data were simulated for 25 years using known parameters and observation process for each model. We used kernel smoothing to reduce the effect of particle depletion, which is common when estimating both states and parameters with SISR. Models using informative priors estimated parameter values and population size with greater accuracy than their non-informative counterparts. While the estimates of population size and trend did not suffer greatly in models using non-informative priors, the algorithm was unable to accurately estimate demographic parameters. This model framework provides reasonable estimates of population size when little to no information is available; however, when information on some vital rates is available, SISR can be used to obtain more precise estimates of population size and process. Incorporating model complexity such as that required by structured populations with stage-specific vital rates affects precision and accuracy when estimating latent population variables and predicting population dynamics. These results are important to consider when designing monitoring programs and conservation efforts requiring management of specific population segments.

Eigencentrality based on dissimilarity measures reveals central nodes in complex networks

PubMed Central

Alvarez-Socorro, A. J.; Herrera-Almarza, G. C.; González-Díaz, L. A.

2015-01-01

One of the most important problems in complex network’s theory is the location of the entities that are essential or have a main role within the network. For this purpose, the use of dissimilarity measures (specific to theory of classification and data mining) to enrich the centrality measures in complex networks is proposed. The centrality method used is the eigencentrality which is based on the heuristic that the centrality of a node depends on how central are the nodes in the immediate neighbourhood (like rich get richer phenomenon). This can be described by an eigenvalues problem, however the information of the neighbourhood and the connections between neighbours is not taken in account, neglecting their relevance when is one evaluates the centrality/importance/influence of a node. The contribution calculated by the dissimilarity measure is parameter independent, making the proposed method is also parameter independent. Finally, we perform a comparative study of our method versus other methods reported in the literature, obtaining more accurate and less expensive computational results in most cases. PMID:26603652

A LSQR-type method provides a computationally efficient automated optimal choice of regularization parameter in diffuse optical tomography.

PubMed

Prakash, Jaya; Yalavarthy, Phaneendra K

2013-03-01

Developing a computationally efficient automated method for the optimal choice of regularization parameter in diffuse optical tomography. The least-squares QR (LSQR)-type method that uses Lanczos bidiagonalization is known to be computationally efficient in performing the reconstruction procedure in diffuse optical tomography. The same is effectively deployed via an optimization procedure that uses the simplex method to find the optimal regularization parameter. The proposed LSQR-type method is compared with the traditional methods such as L-curve, generalized cross-validation (GCV), and recently proposed minimal residual method (MRM)-based choice of regularization parameter using numerical and experimental phantom data. The results indicate that the proposed LSQR-type and MRM-based methods performance in terms of reconstructed image quality is similar and superior compared to L-curve and GCV-based methods. The proposed method computational complexity is at least five times lower compared to MRM-based method, making it an optimal technique. The LSQR-type method was able to overcome the inherent limitation of computationally expensive nature of MRM-based automated way finding the optimal regularization parameter in diffuse optical tomographic imaging, making this method more suitable to be deployed in real-time.

Calibration of a flexible measurement system based on industrial articulated robot and structured light sensor

NASA Astrophysics Data System (ADS)

Mu, Nan; Wang, Kun; Xie, Zexiao; Ren, Ping

2017-05-01

To realize online rapid measurement for complex workpieces, a flexible measurement system based on an articulated industrial robot with a structured light sensor mounted on the end-effector is developed. A method for calibrating the system parameters is proposed in which the hand-eye transformation parameters and the robot kinematic parameters are synthesized in the calibration process. An initial hand-eye calibration is first performed using a standard sphere as the calibration target. By applying the modified complete and parametrically continuous method, we establish a synthesized kinematic model that combines the initial hand-eye transformation and distal link parameters as a whole with the sensor coordinate system as the tool frame. According to the synthesized kinematic model, an error model is constructed based on spheres' center-to-center distance errors. Consequently, the error model parameters can be identified in a calibration experiment using a three-standard-sphere target. Furthermore, the redundancy of error model parameters is eliminated to ensure the accuracy and robustness of the parameter identification. Calibration and measurement experiments are carried out based on an ER3A-C60 robot. The experimental results show that the proposed calibration method enjoys high measurement accuracy, and this efficient and flexible system is suitable for online measurement in industrial scenes.

Complex multifractal nature in Mycobacterium tuberculosis genome

PubMed Central

Mandal, Saurav; Roychowdhury, Tanmoy; Chirom, Keilash; Bhattacharya, Alok; Brojen Singh, R. K.

2017-01-01

The mutifractal and long range correlation (C(r)) properties of strings, such as nucleotide sequence can be a useful parameter for identification of underlying patterns and variations. In this study C(r) and multifractal singularity function f(α) have been used to study variations in the genomes of a pathogenic bacteria Mycobacterium tuberculosis. Genomic sequences of M. tuberculosis isolates displayed significant variations in C(r) and f(α) reflecting inherent differences in sequences among isolates. M. tuberculosis isolates can be categorised into different subgroups based on sensitivity to drugs, these are DS (drug sensitive isolates), MDR (multi-drug resistant isolates) and XDR (extremely drug resistant isolates). C(r) follows significantly different scaling rules in different subgroups of isolates, but all the isolates follow one parameter scaling law. The richness in complexity of each subgroup can be quantified by the measures of multifractal parameters displaying a pattern in which XDR isolates have highest value and lowest for drug sensitive isolates. Therefore C(r) and multifractal functions can be useful parameters for analysis of genomic sequences. PMID:28440326

Complex multifractal nature in Mycobacterium tuberculosis genome

NASA Astrophysics Data System (ADS)

Mandal, Saurav; Roychowdhury, Tanmoy; Chirom, Keilash; Bhattacharya, Alok; Brojen Singh, R. K.

2017-04-01

The mutifractal and long range correlation (C(r)) properties of strings, such as nucleotide sequence can be a useful parameter for identification of underlying patterns and variations. In this study C(r) and multifractal singularity function f(α) have been used to study variations in the genomes of a pathogenic bacteria Mycobacterium tuberculosis. Genomic sequences of M. tuberculosis isolates displayed significant variations in C(r) and f(α) reflecting inherent differences in sequences among isolates. M. tuberculosis isolates can be categorised into different subgroups based on sensitivity to drugs, these are DS (drug sensitive isolates), MDR (multi-drug resistant isolates) and XDR (extremely drug resistant isolates). C(r) follows significantly different scaling rules in different subgroups of isolates, but all the isolates follow one parameter scaling law. The richness in complexity of each subgroup can be quantified by the measures of multifractal parameters displaying a pattern in which XDR isolates have highest value and lowest for drug sensitive isolates. Therefore C(r) and multifractal functions can be useful parameters for analysis of genomic sequences.

Complex bifurcation patterns in a discrete predator-prey model with periodic environmental modulation

NASA Astrophysics Data System (ADS)

Harikrishnan, K. P.

2018-02-01

We consider the simplest model in the family of discrete predator-prey system and introduce for the first time an environmental factor in the evolution of the system by periodically modulating the natural death rate of the predator. We show that with the introduction of environmental modulation, the bifurcation structure becomes much more complex with bubble structure and inverse period doubling bifurcation. The model also displays the peculiar phenomenon of coexistence of multiple limit cycles in the domain of attraction for a given parameter value that combine and finally gets transformed into a single strange attractor as the control parameter is increased. To identify the chaotic regime in the parameter plane of the model, we apply the recently proposed scheme based on the correlation dimension analysis. We show that the environmental modulation is more favourable for the stable coexistence of the predator and the prey as the regions of fixed point and limit cycle in the parameter plane increase at the expense of chaotic domain.

The quality estimation of exterior wall’s and window filling’s construction design

NASA Astrophysics Data System (ADS)

Saltykov, Ivan; Bovsunovskaya, Maria

2017-10-01

The article reveals the term of “artificial envelope” in dwelling building. Authors offer a complex multifactorial approach to the design quality estimation of external fencing structures, which is based on various parameters impact. These referred parameters are: functional, exploitation, cost, and also, the environmental index is among them. The quality design index Qк is inputting for the complex characteristic of observed above parameters. The mathematical relation of this index from these parameters is the target function for the quality design estimation. For instance, the article shows the search of optimal variant for wall and window designs in small, middle and large square dwelling premises of economic class buildings. The graphs of target function single parameters are expressed for the three types of residual chamber’s dimensions. As a result of the showing example, there is a choice of window opening’s dimensions, which make the wall’s and window’s constructions properly correspondent to the producible complex requirements. The authors reveal the comparison of recommended window filling’s square in accordance with the building standards, and the square, due to the finding of the optimal variant of the design quality index. The multifactorial approach for optimal design searching, which is mentioned in this article, can be used in consideration of various construction elements of dwelling buildings in accounting of suitable climate, social and economic construction area features.

Permutation entropy analysis of financial time series based on Hill's diversity number

NASA Astrophysics Data System (ADS)

Zhang, Yali; Shang, Pengjian

2017-12-01

In this paper the permutation entropy based on Hill's diversity number (Nn,r) is introduced as a new way to assess the complexity of a complex dynamical system such as stock market. We test the performance of this method with simulated data. Results show that Nn,r with appropriate parameters is more sensitive to the change of system and describes the trends of complex systems clearly. In addition, we research the stock closing price series from different data that consist of six indices: three US stock indices and three Chinese stock indices during different periods, Nn,r can quantify the changes of complexity for stock market data. Moreover, we get richer information from Nn,r, and obtain some properties about the differences between the US and Chinese stock indices.

Optimization of operating parameters in polysilicon chemical vapor deposition reactor with response surface methodology

NASA Astrophysics Data System (ADS)

An, Li-sha; Liu, Chun-jiao; Liu, Ying-wen

2018-05-01

In the polysilicon chemical vapor deposition reactor, the operating parameters are complex to affect the polysilicon's output. Therefore, it is very important to address the coupling problem of multiple parameters and solve the optimization in a computationally efficient manner. Here, we adopted Response Surface Methodology (RSM) to analyze the complex coupling effects of different operating parameters on silicon deposition rate (R) and further achieve effective optimization of the silicon CVD system. Based on finite numerical experiments, an accurate RSM regression model is obtained and applied to predict the R with different operating parameters, including temperature (T), pressure (P), inlet velocity (V), and inlet mole fraction of H2 (M). The analysis of variance is conducted to describe the rationality of regression model and examine the statistical significance of each factor. Consequently, the optimum combination of operating parameters for the silicon CVD reactor is: T = 1400 K, P = 3.82 atm, V = 3.41 m/s, M = 0.91. The validation tests and optimum solution show that the results are in good agreement with those from CFD model and the deviations of the predicted values are less than 4.19%. This work provides a theoretical guidance to operate the polysilicon CVD process.

Synthesis, spectroscopic, thermal and electrical conductivity studies of three charge transfer complexes formed between 1,3-di[( E)-1-(2-hydroxyphenyl)methylideneamino]-2-propanol Schiff base and different acceptors

NASA Astrophysics Data System (ADS)

Refat, Moamen S.; Ibrahim, Mohamed M.; Moussa, Mohamed A. A.

2012-01-01

Charge-transfer complexes (CTC) resulting from interactions of 1,3-di[( E)-1-(2-hydroxyphenyl) methylideneamino]-2-propanol Schiff base with some acceptors such as iodine (I2), bromine (Br2), and picric acid (PiA) have been isolated in the solid state in a chloroform solvent at room temperature. Based on elemental analysis, UV-Vis, infrared, and 1H NMR spectra, and thermogravimetric analysis (TG/DTG) of the solid CTC, [(Schiff)(I2)] (1), [(Schiff)(Br2)] complexes with a ratio of 1:1 and [(Schiff)(PiA)3] complexes with 1:3 have been prepared. In the picric acid complex, infrared and 1H NMR spectroscopic data indicate that the charge-transfer interaction is associated with a hydrogen bonding, whereas the iodine and bromine complexes were interpreted in terms of the formation of dative ion pairs [Schiff+, I{2/•-}] and [Schiff+, Br{2/•-}], respectively. Kinetic parameters were obtained for each stage of thermal degradation of the CT complexes using Coats-Redfern and Horowitz-Metzger methods. DC electrical properties as a function of temperature of these charge transfer complexes have been studied.

The Complicate Observations and Multi-Parameter Land Information Constructions on Allied Telemetry Experiment (COMPLICATE)

PubMed Central

Tian, Xin; Li, Zengyuan; Chen, Erxue; Liu, Qinhuo; Yan, Guangjian; Wang, Jindi; Niu, Zheng; Zhao, Shaojie; Li, Xin; Pang, Yong; Su, Zhongbo; van der Tol, Christiaan; Liu, Qingwang; Wu, Chaoyang; Xiao, Qing; Yang, Le; Mu, Xihan; Bo, Yanchen; Qu, Yonghua; Zhou, Hongmin; Gao, Shuai; Chai, Linna; Huang, Huaguo; Fan, Wenjie; Li, Shihua; Bai, Junhua; Jiang, Lingmei; Zhou, Ji

2015-01-01

The Complicate Observations and Multi-Parameter Land Information Constructions on Allied Telemetry Experiment (COMPLICATE) comprises a network of remote sensing experiments designed to enhance the dynamic analysis and modeling of remotely sensed information for complex land surfaces. Two types of experimental campaigns were established under the framework of COMPLICATE. The first was designed for continuous and elaborate experiments. The experimental strategy helps enhance our understanding of the radiative and scattering mechanisms of soil and vegetation and modeling of remotely sensed information for complex land surfaces. To validate the methodologies and models for dynamic analyses of remote sensing for complex land surfaces, the second campaign consisted of simultaneous satellite-borne, airborne, and ground-based experiments. During field campaigns, several continuous and intensive observations were obtained. Measurements were undertaken to answer key scientific issues, as follows: 1) Determine the characteristics of spatial heterogeneity and the radiative and scattering mechanisms of remote sensing on complex land surfaces. 2) Determine the mechanisms of spatial and temporal scale extensions for remote sensing on complex land surfaces. 3) Determine synergist inversion mechanisms for soil and vegetation parameters using multi-mode remote sensing on complex land surfaces. Here, we introduce the background, the objectives, the experimental designs, the observations and measurements, and the overall advances of COMPLICATE. As a result of the implementation of COMLICATE and for the next several years, we expect to contribute to quantitative remote sensing science and Earth observation techniques. PMID:26332035

On the classification of mixed floating pollutants on the Yellow Sea of China by using a quad-polarized SAR image

NASA Astrophysics Data System (ADS)

Wang, Xiaochen; Shao, Yun; Tian, Wei; Li, Kun

2018-06-01

This study explored different methodologies using a C-band RADARSAT-2 quad-polarized Synthetic Aperture Radar (SAR) image located over China's Yellow Sea to investigate polarization decomposition parameters for identifying mixed floating pollutants from a complex ocean background. It was found that solitary polarization decomposition did not meet the demand for detecting and classifying multiple floating pollutants, even after applying a polarized SAR image. Furthermore, considering that Yamaguchi decomposition is sensitive to vegetation and the algal variety Enteromorpha prolifera, while H/A/alpha decomposition is sensitive to oil spills, a combination of parameters which was deduced from these two decompositions was proposed for marine environmental monitoring of mixed floating sea surface pollutants. A combination of volume scattering, surface scattering, and scattering entropy was the best indicator for classifying mixed floating pollutants from a complex ocean background. The Kappa coefficients for Enteromorpha prolifera and oil spills were 0.7514 and 0.8470, respectively, evidence that the composite polarized parameters based on quad-polarized SAR imagery proposed in this research is an effective monitoring method for complex marine pollution.

The pyramid system for multiscale raster analysis

USGS Publications Warehouse

De Cola, L.; Montagne, N.

1993-01-01

Geographical research requires the management and analysis of spatial data at multiple scales. As part of the U.S. Geological Survey's global change research program a software system has been developed that reads raster data (such as an image or digital elevation model) and produces a pyramid of aggregated lattices as well as various measurements of spatial complexity. For a given raster dataset the system uses the pyramid to report: (1) mean, (2) variance, (3) a spatial autocorrelation parameter based on multiscale analysis of variance, and (4) a monofractal scaling parameter based on the analysis of isoline lengths. The system is applied to 1-km digital elevation model (DEM) data for a 256-km2 region of central California, as well as to 64 partitions of the region. PYRAMID, which offers robust descriptions of data complexity, also is used to describe the behavior of topographic aspect with scale. ?? 1993.

Analysis of complex environment effect on near-field emission

NASA Astrophysics Data System (ADS)

Ravelo, B.; Lalléchère, S.; Bonnet, P.; Paladian, F.

2014-10-01

The article is dealing with uncertainty analyses of radiofrequency circuits electromagnetic compatibility emission based on the near-field/near-field (NF/NF) transform combined with stochastic approach. By using 2D data corresponding to electromagnetic (EM) field (X=E or H) scanned in the observation plane placed at the position z0 above the circuit under test (CUT), the X field map was extracted. Then, uncertainty analyses were assessed via the statistical moments from X component. In addition, stochastic collocation based was considered and calculations were applied to planar EM NF radiated by the CUTs as Wilkinson power divider and a microstrip line operating at GHz levels. After Matlab implementation, the mean and standard deviation were assessed. The present study illustrates how the variations of environmental parameters may impact EM fields. The NF uncertainty methodology can be applied to any physical parameter effects in complex environment and useful for printed circuit board (PCBs) design guideline.

Synthesis, spectroscopic, molecular structure, antioxidant, antimicrobial and antitumor behavior of Mn(II), Co(II), Ni(II), Cu(II) and Zn(II) complexes of O2N type tridentate chromone-2-carboxaldehyde Schiff's base ligand

NASA Astrophysics Data System (ADS)

Ammar, Reda A.; Alaghaz, Abdel-Nasser M. A.; Zayed, Mohamed E.; Al-Bedair, Lamia A.

2017-08-01

Tridentate Schiff's base (HL) ligand was synthesized via condensation of salicylaldehyde and 3-hydroxypyridin-2-yliminomethyl-4H-chromen-4-one and their corresponding Mn(II), Co(II), Ni(II), Cu(II) and Zn(II) complexes have been synthesized. The isolated solid complexes were characterized by elemental analyses, molar conductance, spectral (IR, UV-Vis, 1H NMR), magnetic moment, EPR, and thermal measurements. The IR spectra showed that HL was coordinated to the metal ions in tridentate manner with O2N donor sites of the azomethine N, deprotonated phenolic-OH and carbonyl-O. The activation of thermodynamic parameters are calculated using Coast-Redfern and Horowitz-Metzger (HM). The octahedral geometry of the complexes is confirmed using DFT method from DMOL3 calculations, UV-Vis and magnetic moment measurements, ESR and ligand field parameters. Antioxidant activities have also been performed for all the compounds. The investigated ligand and metal complexes were screened for their in-vitro antimicrobial activities against different types of fungal and bacterial strains. The resulting data assert on the inspected compounds as a highly promising bactericides and fungicides. The antitumor activities of all inspected compounds were evaluated towards human liver Carcinoma (HepG2) cell line.

Time-Related Decay or Interference-Based Forgetting in Working Memory?

ERIC Educational Resources Information Center

Portrat, Sophie; Barrouillet, Pierre; Camos, Valerie

2008-01-01

The time-based resource-sharing model of working memory assumes that memory traces suffer from a time-related decay when attention is occupied by concurrent activities. Using complex continuous span tasks in which temporal parameters are carefully controlled, P. Barrouillet, S. Bernardin, S. Portrat, E. Vergauwe, & V. Camos (2007) recently…

Lumped Parameter Models for Predicting Nitrogen Transport in Lower Coastal Plain Watersheds

Treesearch

Devendra M. Amatya; George M. Chescheir; Glen P. Fernandez; R. Wayne Skaggs; F. Birgand; J.W. Gilliam

2003-01-01

hl recent years physically based comprehensive disfributed watershed scale hydrologic/water quality models have been developed and applied 10 evaluate cumulative effects of land arld water management practices on receiving waters, Although fhesc complex physically based models are capable of simulating the impacts ofthese changes in large watersheds, they are often...

Acoustic invisibility cloaks of arbitrary shapes for complex background media

NASA Astrophysics Data System (ADS)

Zhu, Jian; Chen, Tianning; Liang, Qingxuan; Wang, Xiaopeng; Xiong, Jie; Jiang, Ping

2016-04-01

We report on the theoretical investigation of the acoustic cloaks working in complex background media in this paper. The constitutive parameters of arbitrary-shape cloaks are derived based on the transformation acoustic theory and coordinate transformation technique. The detailed analysis of boundaries conditions and potential applications of the cloaks are also presented in our work. To overcome the difficulty of achieving the materials with ideal parameters in nature, concentric alternating layered isotropic materials is adopted to approximate the required properties of the cloak. Theoretical design and excellent invisibility are demonstrated by numerical simulations. The inhomogeneous medium and arbitrary-shape acoustic cloaks grow closer to real application and may be a new hot spot in future.

Research on Optimization of GLCM Parameter in Cell Classification

NASA Astrophysics Data System (ADS)

Zhang, Xi-Kun; Hou, Jie; Hu, Xin-Hua

2016-05-01

Real-time classification of biological cells according to their 3D morphology is highly desired in a flow cytometer setting. Gray level co-occurrence matrix (GLCM) algorithm has been developed to extract feature parameters from measured diffraction images ,which are too complicated to coordinate with the real-time system for a large amount of calculation. An optimization of GLCM algorithm is provided based on correlation analysis of GLCM parameters. The results of GLCM analysis and subsequent classification demonstrate optimized method can lower the time complexity significantly without loss of classification accuracy.

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.

Determination of thermodynamic values of acidic dissociation constants and complexation constants of profens and their utilization for optimization of separation conditions by Simul 5 Complex.

PubMed

Riesová, Martina; Svobodová, Jana; Ušelová, Kateřina; Tošner, Zdeněk; Zusková, Iva; Gaš, Bohuslav

2014-10-17

In this paper we determine acid dissociation constants, limiting ionic mobilities, complexation constants with β-cyclodextrin or heptakis(2,3,6-tri-O-methyl)-β-cyclodextrin, and mobilities of resulting complexes of profens, using capillary zone electrophoresis and affinity capillary electrophoresis. Complexation parameters are determined for both neutral and fully charged forms of profens and further corrected for actual ionic strength and variable viscosity in order to obtain thermodynamic values of complexation constants. The accuracy of obtained complexation parameters is verified by multidimensional nonlinear regression of affinity capillary electrophoretic data, which provides the acid dissociation and complexation parameters within one set of measurements, and by NMR technique. A good agreement among all discussed methods was obtained. Determined complexation parameters were used as input parameters for simulations of electrophoretic separation of profens by Simul 5 Complex. An excellent agreement of experimental and simulated results was achieved in terms of positions, shapes, and amplitudes of analyte peaks, confirming the applicability of Simul 5 Complex to complex systems, and accuracy of obtained physical-chemical constants. Simultaneously, we were able to demonstrate the influence of electromigration dispersion on the separation efficiency, which is not possible using the common theoretical approaches, and predict the electromigration order reversals of profen peaks. We have shown that determined acid dissociation and complexation parameters in combination with tool Simul 5 Complex software can be used for optimization of separation conditions in capillary electrophoresis. Copyright © 2014 Elsevier B.V. All rights reserved.

Waste management under multiple complexities: Inexact piecewise-linearization-based fuzzy flexible programming

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

Sun Wei; Huang, Guo H., E-mail: huang@iseis.org; Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, Saskatchewan, S4S 0A2

2012-06-15

Highlights: Black-Right-Pointing-Pointer Inexact piecewise-linearization-based fuzzy flexible programming is proposed. Black-Right-Pointing-Pointer It's the first application to waste management under multiple complexities. Black-Right-Pointing-Pointer It tackles nonlinear economies-of-scale effects in interval-parameter constraints. Black-Right-Pointing-Pointer It estimates costs more accurately than the linear-regression-based model. Black-Right-Pointing-Pointer Uncertainties are decreased and more satisfactory interval solutions are obtained. - Abstract: To tackle nonlinear economies-of-scale (EOS) effects in interval-parameter constraints for a representative waste management problem, an inexact piecewise-linearization-based fuzzy flexible programming (IPFP) model is developed. In IPFP, interval parameters for waste amounts and transportation/operation costs can be quantified; aspiration levels for net system costs, as well as tolerancemore » intervals for both capacities of waste treatment facilities and waste generation rates can be reflected; and the nonlinear EOS effects transformed from objective function to constraints can be approximated. An interactive algorithm is proposed for solving the IPFP model, which in nature is an interval-parameter mixed-integer quadratically constrained programming model. To demonstrate the IPFP's advantages, two alternative models are developed to compare their performances. One is a conventional linear-regression-based inexact fuzzy programming model (IPFP2) and the other is an IPFP model with all right-hand-sides of fussy constraints being the corresponding interval numbers (IPFP3). The comparison results between IPFP and IPFP2 indicate that the optimized waste amounts would have the similar patterns in both models. However, when dealing with EOS effects in constraints, the IPFP2 may underestimate the net system costs while the IPFP can estimate the costs more accurately. The comparison results between IPFP and IPFP3 indicate that their solutions would be significantly different. The decreased system uncertainties in IPFP's solutions demonstrate its effectiveness for providing more satisfactory interval solutions than IPFP3. Following its first application to waste management, the IPFP can be potentially applied to other environmental problems under multiple complexities.« less

Crystal structures and catalytic performance of three new methoxy substituted salen type nickel(II) Schiff base complexes derived from meso-1,2-diphenyl-1,2-ethylenediamine

NASA Astrophysics Data System (ADS)

Ghaffari, Abolfazl; Behzad, Mahdi; Pooyan, Mahsa; Amiri Rudbari, Hadi; Bruno, Giuseppe

2014-04-01

Three new nickel(II) complexes of a series of methoxy substituted salen type Schiff base ligands were synthesized and characterized by IR, UV-Vis and 1H NMR spectroscopy and elemental analysis. The ligands were synthesized from the condensation of meso-1,2-diphenyl-1,2-ethylenediamine with n-methoxysalicylaldehyde (n = 3, 4 and 5). Crystal structures of these complexes were determined. Electrochemical behavior of the complexes was studied by means of cyclic voltammetry in DMSO solutions. Catalytic performance of the complexes was studied in the epoxidation of cyclooctene using tert-butylhydroperoxide (TBHP) as oxidant under various conditions to find the optimum operating parameters. Low catalytic activity with moderate epoxide selectivity was observed in in-solvent conditions but in the solvent-free conditions, enhanced catalytic activity with high epoxide selectivity was achieved.

Configuration complexity assessment of convergent supply chain systems

NASA Astrophysics Data System (ADS)

Modrak, Vladimir; Marton, David

2014-07-01

System designers usually generate alternative configurations of supply chains (SCs) by varying especially fixed assets to satisfy a desired production scope and rate. Such alternatives often vary in associated costs and other facets including degrees of complexity. Hence, a measure of configuration complexity can be a tool for comparison and decision-making. This paper presents three approaches to assessment of configuration complexity and their applications to designing convergent SC systems. Presented approaches are conceptually distinct ways of measuring structural complexity parameters based on different preconditions and circumstances of assembly systems which are typical representatives of convergent SCs. There are applied two similar approaches based on different preconditions that are related to demand shares. Third approach does not consider any special condition relating to character of final product demand. Subsequently, we propose a framework for modeling of assembly SC models, which are dividing to classes.

Generalized sample entropy analysis for traffic signals based on similarity measure

NASA Astrophysics Data System (ADS)

Shang, Du; Xu, Mengjia; Shang, Pengjian

2017-05-01

Sample entropy is a prevailing method used to quantify the complexity of a time series. In this paper a modified method of generalized sample entropy and surrogate data analysis is proposed as a new measure to assess the complexity of a complex dynamical system such as traffic signals. The method based on similarity distance presents a different way of signals patterns match showing distinct behaviors of complexity. Simulations are conducted over synthetic data and traffic signals for providing the comparative study, which is provided to show the power of the new method. Compared with previous sample entropy and surrogate data analysis, the new method has two main advantages. The first one is that it overcomes the limitation about the relationship between the dimension parameter and the length of series. The second one is that the modified sample entropy functions can be used to quantitatively distinguish time series from different complex systems by the similar measure.

[Measurement and analysis on complex refraction indices of pear pollen in infrared band].

PubMed

Li, Le; Hu, Yi-hua; Gu, You-lin; Chen, Wei; Zhao, Yi-zheng; Chen, Shan-jing

2015-01-01

Pollen is an important part of bioaerosols, and its complex refractive index is a crucial parameter for study on optical characteristics and detection, identification of bioaerosols. The reflection spectra of pear pollen within the 2. 5 - 15µm waveband were measured by squash method. Based on the measured data, the complex refractive index of pear pollen within the wave-band of 2. 5 to 15 µm was calculated by using Kramers-Kroning (K-K) relation, and calculation deviation about incident angle and different reflectivities at high and low frequencies.were analyzed. The results indicate that 18 degrees angle of incidence and different reflectivities at high and low frequencies have little effect on the results, and it is practicable to calculate the complex refractive index of pollen based on its reflection spectral data. The data of complex refractive index of pollen have some reference value for optical characteristics of pollen, detection and identification of bioaerosols.

Adaptive identifier for uncertain complex nonlinear systems based on continuous neural networks.

PubMed

Alfaro-Ponce, Mariel; Cruz, Amadeo Argüelles; Chairez, Isaac

2014-03-01

This paper presents the design of a complex-valued differential neural network identifier for uncertain nonlinear systems defined in the complex domain. This design includes the construction of an adaptive algorithm to adjust the parameters included in the identifier. The algorithm is obtained based on a special class of controlled Lyapunov functions. The quality of the identification process is characterized using the practical stability framework. Indeed, the region where the identification error converges is derived by the same Lyapunov method. This zone is defined by the power of uncertainties and perturbations affecting the complex-valued uncertain dynamics. Moreover, this convergence zone is reduced to its lowest possible value using ideas related to the so-called ellipsoid methodology. Two simple but informative numerical examples are developed to show how the identifier proposed in this paper can be used to approximate uncertain nonlinear systems valued in the complex domain.

General molecular mechanics method for transition metal carboxylates and its application to the multiple coordination modes in mono- and dinuclear Mn(II) complexes.

PubMed

Deeth, Robert J

2008-08-04

A general molecular mechanics method is presented for modeling the symmetric bidentate, asymmetric bidentate, and bridging modes of metal-carboxylates with a single parameter set by using a double-minimum M-O-C angle-bending potential. The method is implemented within the Molecular Operating Environment (MOE) with parameters based on the Merck molecular force field although, with suitable modifications, other MM packages and force fields could easily be used. Parameters for high-spin d (5) manganese(II) bound to carboxylate and water plus amine, pyridyl, imidazolyl, and pyrazolyl donors are developed based on 26 mononuclear and 29 dinuclear crystallographically characterized complexes. The average rmsd for Mn-L distances is 0.08 A, which is comparable to the experimental uncertainty required to cover multiple binding modes, and the average rmsd in heavy atom positions is around 0.5 A. In all cases, whatever binding mode is reported is also computed to be a stable local minimum. In addition, the structure-based parametrization implicitly captures the energetics and gives the same relative energies of symmetric and asymmetric coordination modes as density functional theory calculations in model and "real" complexes. Molecular dynamics simulations show that carboxylate rotation is favored over "flipping" while a stochastic search algorithm is described for randomly searching conformational space. The model reproduces Mn-Mn distances in dinuclear systems especially accurately, and this feature is employed to illustrate how MM calculations on models for the dimanganese active site of methionine aminopeptidase can help determine some of the details which may be missing from the experimental structure.

Melatonin charge transfer complex with 2,3-dichloro-5,6-dicyano-1,4-benzoquinone: Molecular structure, DFT studies, thermal analyses, evaluation of biological activity and utility for determination of melatonin in pure and dosage forms

NASA Astrophysics Data System (ADS)

Mohamed, Gehad G.; Hamed, Maher M.; Zaki, Nadia G.; Abdou, Mohamed M.; Mohamed, Marwa El-Badry; Abdallah, Abanoub Mosaad

2017-07-01

A simple, accurate and fast spectrophotometric method for the quantitative determination of melatonin (ML) drug in its pure and pharmaceutical forms was developed based on the formation of its charge transfer complex with 2,3-dichloro-5,6-dicyano-1,4-benzoquinone (DDQ) as an electron acceptor. The different conditions for this method were optimized accurately. The Lambert-Beer's law was found to be valid over the concentration range of 4-100 μg mL- 1 ML. The solid form of the CT complex was structurally characterized by means of different spectral methods. Density functional theory (DFT) and time-dependent density functional theory (TD-DFT) calculations were carried out. The different quantum chemical parameters of the CT complex were calculated. Thermal properties of the CT complex and its kinetic thermodynamic parameters were studied, as well as its antimicrobial and antifungal activities were investigated. Molecular docking studies were performed to predict the binding modes of the CT complex components towards E. coli bacterial RNA and the receptor of breast cancer mutant oxidoreductase.

Melatonin charge transfer complex with 2,3-dichloro-5,6-dicyano-1,4-benzoquinone: Molecular structure, DFT studies, thermal analyses, evaluation of biological activity and utility for determination of melatonin in pure and dosage forms.

PubMed

Mohamed, Gehad G; Hamed, Maher M; Zaki, Nadia G; Abdou, Mohamed M; Mohamed, Marwa El-Badry; Abdallah, Abanoub Mosaad

2017-07-05

A simple, accurate and fast spectrophotometric method for the quantitative determination of melatonin (ML) drug in its pure and pharmaceutical forms was developed based on the formation of its charge transfer complex with 2,3-dichloro-5,6-dicyano-1,4-benzoquinone (DDQ) as an electron acceptor. The different conditions for this method were optimized accurately. The Lambert-Beer's law was found to be valid over the concentration range of 4-100μgmL -1 ML. The solid form of the CT complex was structurally characterized by means of different spectral methods. Density functional theory (DFT) and time-dependent density functional theory (TD-DFT) calculations were carried out. The different quantum chemical parameters of the CT complex were calculated. Thermal properties of the CT complex and its kinetic thermodynamic parameters were studied, as well as its antimicrobial and antifungal activities were investigated. Molecular docking studies were performed to predict the binding modes of the CT complex components towards E. coli bacterial RNA and the receptor of breast cancer mutant oxidoreductase. Copyright © 2017 Elsevier B.V. All rights reserved.

Measurement of complex terahertz dielectric properties of polymers using an improved free-space technique

NASA Astrophysics Data System (ADS)

Chang, Tianying; Zhang, Xiansheng; Yang, Chuanfa; Sun, Zhonglin; Cui, Hong-Liang

2017-04-01

The complex dielectric properties of non-polar solid polymer materials were measured in the terahertz (THz) band by a free-space technique employing a frequency-extended vector network analyzer (VNA), and by THz time-domain spectroscopy (TDS). Mindful of THz wave’s unique characteristics, the free-space method for measurement of material dielectric properties in the microwave band was expanded and improved for application in the THz frequency region. To ascertain the soundness and utility of the proposed method, measurements of the complex dielectric properties of a variety of polymers were carried out, including polytetrafluoroethylene (PTFE, known also by the brand name Teflon), polypropylene (PP), polyethylene (PE), and glass fiber resin (Composite Stone). The free-space method relies on the determination of electromagnetic scattering parameters (S-parameters) of the sample, with the gated-reflect-line (GRL) calibration technique commonly employed using a VNA. Subsequently, based on the S-parameters, the dielectric constant and loss characteristic of the sample were calculated by using a Newtonian iterative algorithm. To verify the calculated results, THz TDS technique, which produced Fresnel parameters such as reflection and transmission coefficients, was also used to independently determine the dielectric properties of these polymer samples, with results satisfactorily corroborating those obtained by the free-space extended microwave technique.

An approach to determination of shunt circuits parameters for damping vibrations

NASA Astrophysics Data System (ADS)

Matveenko; Iurlova; Oshmarin; Sevodina; Iurlov

2018-04-01

This paper considers the problem of natural vibrations of a deformable structure containing elements made of piezomaterials. The piezoelectric elements are connected through electrodes to an external electric circuit, which consists of resistive, inductive and capacitive elements. Based on the solution of this problem, the parameters of external electric circuits are searched for to allow optimal passive control of the structural vibrations. The solution to the problem is complex natural vibration frequencies, the real part of which corresponds to the circular eigenfrequency of vibrations and the imaginary part corresponds to its damping rate (damping ratio). The analysis of behaviour of the imaginary parts of complex eigenfrequencies in the space of external circuit parameters allows one to damp given modes of structure vibrations. The effectiveness of the proposed approach is demonstrated using a cantilever-clamped plate and a shell structure in the form of a semi-cylinder connected to series resonant ? circuits.

Hierarchical calibration and validation of computational fluid dynamics models for solid sorbent-based carbon capture

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

Lai, Canhai; Xu, Zhijie; Pan, Wenxiao

2016-01-01

To quantify the predictive confidence of a solid sorbent-based carbon capture design, a hierarchical validation methodology—consisting of basic unit problems with increasing physical complexity coupled with filtered model-based geometric upscaling has been developed and implemented. This paper describes the computational fluid dynamics (CFD) multi-phase reactive flow simulations and the associated data flows among different unit problems performed within the said hierarchical validation approach. The bench-top experiments used in this calibration and validation effort were carefully designed to follow the desired simple-to-complex unit problem hierarchy, with corresponding data acquisition to support model parameters calibrations at each unit problem level. A Bayesianmore » calibration procedure is employed and the posterior model parameter distributions obtained at one unit-problem level are used as prior distributions for the same parameters in the next-tier simulations. Overall, the results have demonstrated that the multiphase reactive flow models within MFIX can be used to capture the bed pressure, temperature, CO2 capture capacity, and kinetics with quantitative accuracy. The CFD modeling methodology and associated uncertainty quantification techniques presented herein offer a solid framework for estimating the predictive confidence in the virtual scale up of a larger carbon capture device.« less

Displacement-based back-analysis of the model parameters of the Nuozhadu high earth-rockfill dam.

PubMed

Wu, Yongkang; Yuan, Huina; Zhang, Bingyin; Zhang, Zongliang; Yu, Yuzhen

2014-01-01

The parameters of the constitutive model, the creep model, and the wetting model of materials of the Nuozhadu high earth-rockfill dam were back-analyzed together based on field monitoring displacement data by employing an intelligent back-analysis method. In this method, an artificial neural network is used as a substitute for time-consuming finite element analysis, and an evolutionary algorithm is applied for both network training and parameter optimization. To avoid simultaneous back-analysis of many parameters, the model parameters of the three main dam materials are decoupled and back-analyzed separately in a particular order. Displacement back-analyses were performed at different stages of the construction period, with and without considering the creep and wetting deformations. Good agreement between the numerical results and the monitoring data was obtained for most observation points, which implies that the back-analysis method and decoupling method are effective for solving complex problems with multiple models and parameters. The comparison of calculation results based on different sets of back-analyzed model parameters indicates the necessity of taking the effects of creep and wetting into consideration in the numerical analyses of high earth-rockfill dams. With the resulting model parameters, the stress and deformation distributions at completion are predicted and analyzed.

Synthesis, characterization and biological assay of Salicylaldehyde Schiff base Cu(II) complexes and their precursors

NASA Astrophysics Data System (ADS)

Iftikhar, Bushra; Javed, Kanwal; Khan, Muhammad Saif Ullah; Akhter, Zareen; Mirza, Bushra; Mckee, Vickie

2018-03-01

Three new Schiff base ligands were synthesized by the reaction of Salicylaldehyde with semi-aromatic diamines, prepared by the reduction of corresponding dinitro-compounds, and were further used for the formation of complexes with Cu(II) metal ion. The structural features of the synthesized compounds were confirmed by their physical properties and infrared, electronic and NMR spectroscopic techniques. The studies revealed that the synthesized Schiff bases existed as tetradentate ligands and bonded to the metal ion through the phenolic oxygen and azomethine nitrogen. One of the dinitro precursors was also analyzed by single crystal X-ray crystallography, which showed that it crystallizes in monoclinic system with space group P2/n. The thermal behavior of the Cu(II) complexes was determined by thermogravimetric analysis (TGA) and kinetic parameters were evaluated from the data. Schiff base ligands, their precursors and metal complexes were also screened for antibacterial, antifungal, antitumor, Brine shrimp lethality, DPPH free radical scavenging and DNA damage assays. The results of these analyses indicated the substantial potential of the synthesized Schiff bases, their precursors and Cu(II) complexes in biological field as future drugs.

Estimating Sobol Sensitivity Indices Using Correlations

EPA Science Inventory

Sensitivity analysis is a crucial tool in the development and evaluation of complex mathematical models. Sobol's method is a variance-based global sensitivity analysis technique that has been applied to computational models to assess the relative importance of input parameters on...

Hydraulic fracture propagation modeling and data-based fracture identification

NASA Astrophysics Data System (ADS)

Zhou, Jing

Successful shale gas and tight oil production is enabled by the engineering innovation of horizontal drilling and hydraulic fracturing. Hydraulically induced fractures will most likely deviate from the bi-wing planar pattern and generate complex fracture networks due to mechanical interactions and reservoir heterogeneity, both of which render the conventional fracture simulators insufficient to characterize the fractured reservoir. Moreover, in reservoirs with ultra-low permeability, the natural fractures are widely distributed, which will result in hydraulic fractures branching and merging at the interface and consequently lead to the creation of more complex fracture networks. Thus, developing a reliable hydraulic fracturing simulator, including both mechanical interaction and fluid flow, is critical in maximizing hydrocarbon recovery and optimizing fracture/well design and completion strategy in multistage horizontal wells. A novel fully coupled reservoir flow and geomechanics model based on the dual-lattice system is developed to simulate multiple nonplanar fractures' propagation in both homogeneous and heterogeneous reservoirs with or without pre-existing natural fractures. Initiation, growth, and coalescence of the microcracks will lead to the generation of macroscopic fractures, which is explicitly mimicked by failure and removal of bonds between particles from the discrete element network. This physics-based modeling approach leads to realistic fracture patterns without using the empirical rock failure and fracture propagation criteria required in conventional continuum methods. Based on this model, a sensitivity study is performed to investigate the effects of perforation spacing, in-situ stress anisotropy, rock properties (Young's modulus, Poisson's ratio, and compressive strength), fluid properties, and natural fracture properties on hydraulic fracture propagation. In addition, since reservoirs are buried thousands of feet below the surface, the parameters used in the reservoir flow simulator have large uncertainty. Those biased and uncertain parameters will result in misleading oil and gas recovery predictions. The Ensemble Kalman Filter is used to estimate and update both the state variables (pressure and saturations) and uncertain reservoir parameters (permeability). In order to directly incorporate spatial information such as fracture location and formation heterogeneity into the algorithm, a new covariance matrix method is proposed. This new method has been applied to a simplified single-phase reservoir and a complex black oil reservoir with complex structures to prove its capability in calibrating the reservoir parameters.

On Finding and Using Identifiable Parameter Combinations in Nonlinear Dynamic Systems Biology Models and COMBOS: A Novel Web Implementation

PubMed Central

DiStefano, Joseph

2014-01-01

Parameter identifiability problems can plague biomodelers when they reach the quantification stage of development, even for relatively simple models. Structural identifiability (SI) is the primary question, usually understood as knowing which of P unknown biomodel parameters p 1,…, pi,…, pP are-and which are not-quantifiable in principle from particular input-output (I-O) biodata. It is not widely appreciated that the same database also can provide quantitative information about the structurally unidentifiable (not quantifiable) subset, in the form of explicit algebraic relationships among unidentifiable pi. Importantly, this is a first step toward finding what else is needed to quantify particular unidentifiable parameters of interest from new I–O experiments. We further develop, implement and exemplify novel algorithms that address and solve the SI problem for a practical class of ordinary differential equation (ODE) systems biology models, as a user-friendly and universally-accessible web application (app)–COMBOS. Users provide the structural ODE and output measurement models in one of two standard forms to a remote server via their web browser. COMBOS provides a list of uniquely and non-uniquely SI model parameters, and–importantly-the combinations of parameters not individually SI. If non-uniquely SI, it also provides the maximum number of different solutions, with important practical implications. The behind-the-scenes symbolic differential algebra algorithms are based on computing Gröbner bases of model attributes established after some algebraic transformations, using the computer-algebra system Maxima. COMBOS was developed for facile instructional and research use as well as modeling. We use it in the classroom to illustrate SI analysis; and have simplified complex models of tumor suppressor p53 and hormone regulation, based on explicit computation of parameter combinations. It’s illustrated and validated here for models of moderate complexity, with and without initial conditions. Built-in examples include unidentifiable 2 to 4-compartment and HIV dynamics models. PMID:25350289

Modelling and identification for control of gas bearings

NASA Astrophysics Data System (ADS)

Theisen, Lukas R. S.; Niemann, Hans H.; Santos, Ilmar F.; Galeazzi, Roberto; Blanke, Mogens

2016-03-01

Gas bearings are popular for their high speed capabilities, low friction and clean operation, but suffer from poor damping, which poses challenges for safe operation in presence of disturbances. Feedback control can achieve enhanced damping but requires low complexity models of the dominant dynamics over its entire operating range. Models from first principles are complex and sensitive to parameter uncertainty. This paper presents an experimental technique for "in situ" identification of a low complexity model of a rotor-bearing-actuator system and demonstrates identification over relevant ranges of rotational speed and gas injection pressure. This is obtained using parameter-varying linear models that are found to capture the dominant dynamics. The approach is shown to be easily applied and to suit subsequent control design. Based on the identified models, decentralised proportional control is designed and shown to obtain the required damping in theory and in a laboratory test rig.

Methods for performing fast discrete curvelet transforms of data

DOEpatents

Candes, Emmanuel; Donoho, David; Demanet, Laurent

2010-11-23

Fast digital implementations of the second generation curvelet transform for use in data processing are disclosed. One such digital transformation is based on unequally-spaced fast Fourier transforms (USFFT) while another is based on the wrapping of specially selected Fourier samples. Both digital transformations return a table of digital curvelet coefficients indexed by a scale parameter, an orientation parameter, and a spatial location parameter. Both implementations are fast in the sense that they run in about O(n.sup.2 log n) flops for n by n Cartesian arrays or about O(N log N) flops for Cartesian arrays of size N=n.sup.3; in addition, they are also invertible, with rapid inversion algorithms of about the same complexity.

Optical Coherence Tomography Noise Reduction Using Anisotropic Local Bivariate Gaussian Mixture Prior in 3D Complex Wavelet Domain.

PubMed

Rabbani, Hossein; Sonka, Milan; Abramoff, Michael D

2013-01-01

In this paper, MMSE estimator is employed for noise-free 3D OCT data recovery in 3D complex wavelet domain. Since the proposed distribution for noise-free data plays a key role in the performance of MMSE estimator, a priori distribution for the pdf of noise-free 3D complex wavelet coefficients is proposed which is able to model the main statistical properties of wavelets. We model the coefficients with a mixture of two bivariate Gaussian pdfs with local parameters which are able to capture the heavy-tailed property and inter- and intrascale dependencies of coefficients. In addition, based on the special structure of OCT images, we use an anisotropic windowing procedure for local parameters estimation that results in visual quality improvement. On this base, several OCT despeckling algorithms are obtained based on using Gaussian/two-sided Rayleigh noise distribution and homomorphic/nonhomomorphic model. In order to evaluate the performance of the proposed algorithm, we use 156 selected ROIs from 650 × 512 × 128 OCT dataset in the presence of wet AMD pathology. Our simulations show that the best MMSE estimator using local bivariate mixture prior is for the nonhomomorphic model in the presence of Gaussian noise which results in an improvement of 7.8 ± 1.7 in CNR.

Complex-Morphology Metal-Based Nanostructures: Fabrication, Characterization, and Applications

PubMed Central

Gentile, Antonella; Ruffino, Francesco; Grimaldi, Maria Grazia

2016-01-01

Due to their peculiar qualities, metal-based nanostructures have been extensively used in applications such as catalysis, electronics, photography, and information storage, among others. New applications for metals in areas such as photonics, sensing, imaging, and medicine are also being developed. Significantly, most of these applications require the use of metals in the form of nanostructures with specific controlled properties. The properties of nanoscale metals are determined by a set of physical parameters that include size, shape, composition, and structure. In recent years, many research fields have focused on the synthesis of nanoscale-sized metallic materials with complex shape and composition in order to optimize the optical and electrical response of devices containing metallic nanostructures. The present paper aims to overview the most recent results—in terms of fabrication methodologies, characterization of the physico-chemical properties and applications—of complex-morphology metal-based nanostructures. The paper strongly focuses on the correlation between the complex morphology and the structures’ properties, showing how the morphological complexity (and its nanoscale control) can often give access to a wide range of innovative properties exploitable for innovative functional device production. We begin with an overview of the basic concepts on the correlation between structural and optical parameters of nanoscale metallic materials with complex shape and composition, and the possible solutions offered by nanotechnology in a large range of applications (catalysis, electronics, photonics, sensing). The aim is to assess the state of the art, and then show the innovative contributions that can be proposed in this research field. We subsequently report on innovative, versatile and low-cost synthesis techniques, suitable for providing a good control on the size, surface density, composition and geometry of the metallic nanostructures. The main purpose of this study is the fabrication of functional nanoscale-sized materials, whose properties can be tailored (in a wide range) simply by controlling the structural characteristics. The modulation of the structural parameters is required to tune the plasmonic properties of the nanostructures for applications such as biosensors, opto-electronic or photovoltaic devices and surface-enhanced Raman scattering (SERS) substrates. The structural characterization of the obtained nanoscale materials is employed in order to define how the synthesis parameters affect the structural characteristics of the resulting metallic nanostructures. Then, macroscopic measurements are used to probe their electrical and optical properties. Phenomenological growth models are drafted to explain the processes involved in the growth and evolution of such composite systems. After the synthesis and characterization of the metallic nanostructures, we study the effects of the incorporation of the complex morphologies on the optical and electrical responses of each specific device. PMID:28335236

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.

Comparison between splines and fractional polynomials for multivariable model building with continuous covariates: a simulation study with continuous response.

PubMed

Binder, Harald; Sauerbrei, Willi; Royston, Patrick

2013-06-15

In observational studies, many continuous or categorical covariates may be related to an outcome. Various spline-based procedures or the multivariable fractional polynomial (MFP) procedure can be used to identify important variables and functional forms for continuous covariates. This is the main aim of an explanatory model, as opposed to a model only for prediction. The type of analysis often guides the complexity of the final model. Spline-based procedures and MFP have tuning parameters for choosing the required complexity. To compare model selection approaches, we perform a simulation study in the linear regression context based on a data structure intended to reflect realistic biomedical data. We vary the sample size, variance explained and complexity parameters for model selection. We consider 15 variables. A sample size of 200 (1000) and R(2)  = 0.2 (0.8) is the scenario with the smallest (largest) amount of information. For assessing performance, we consider prediction error, correct and incorrect inclusion of covariates, qualitative measures for judging selected functional forms and further novel criteria. From limited information, a suitable explanatory model cannot be obtained. Prediction performance from all types of models is similar. With a medium amount of information, MFP performs better than splines on several criteria. MFP better recovers simpler functions, whereas splines better recover more complex functions. For a large amount of information and no local structure, MFP and the spline procedures often select similar explanatory models. Copyright © 2012 John Wiley & Sons, Ltd.

Analysis of material parameter effects on fluidlastic isolators performance

NASA Astrophysics Data System (ADS)

Cheng, Q. Y.; Deng, J. H.; Feng, Z. Z.; Qian, F.

2018-01-01

Control of vibration in helicopters has always been a complex and challenging task. The fluidlastic isolators become more and more widely used because the fluids are non-toxic, non-corrosive, nonflammable, and compatible with most elastomers and adhesives. In the field of the fluidlastic isolators design, the selection of design parameters of fluid and rubber is very important to obtain efficient vibration-suppressed. Aiming at getting the property of fluidlastic isolator to material design parameters, a dynamic equation is set up based on the dynamic theory. And the dynamic analysis is carried out. The influences of design parameters on the property of fluidlastic isolator are calculated. The material parameters examined are the properties of fluid and rubber. Analysis results showed that the design parameters such as density of fluid, viscosity coefficient of fluid, stiffness of rubber (K1) and loss coefficient of rubber have obvious influence on the performance of isolator. Base on the results of the study it is concluded that the efficient vibration-suppressed can be obtained by the selection of design parameters.

Inverse modeling approach for evaluation of kinetic parameters of a biofilm reactor using tabu search.

PubMed

Kumar, B Shiva; Venkateswarlu, Ch

2014-08-01

The complex nature of biological reactions in biofilm reactors often poses difficulties in analyzing such reactors experimentally. Mathematical models could be very useful for their design and analysis. However, application of biofilm reactor models to practical problems proves somewhat ineffective due to the lack of knowledge of accurate kinetic models and uncertainty in model parameters. In this work, we propose an inverse modeling approach based on tabu search (TS) to estimate the parameters of kinetic and film thickness models. TS is used to estimate these parameters as a consequence of the validation of the mathematical models of the process with the aid of measured data obtained from an experimental fixed-bed anaerobic biofilm reactor involving the treatment of pharmaceutical industry wastewater. The results evaluated for different modeling configurations of varying degrees of complexity illustrate the effectiveness of TS for accurate estimation of kinetic and film thickness model parameters of the biofilm process. The results show that the two-dimensional mathematical model with Edward kinetics (with its optimum parameters as mu(max)rho(s)/Y = 24.57, Ks = 1.352 and Ki = 102.36) and three-parameter film thickness expression (with its estimated parameters as a = 0.289 x 10(-5), b = 1.55 x 10(-4) and c = 15.2 x 10(-6)) better describes the biofilm reactor treating the industry wastewater.

Nanofluid MHD natural convection through a porous complex shaped cavity considering thermal radiation

NASA Astrophysics Data System (ADS)

Sheikholeslami, M.; Li, Zhixiong; Shamlooei, M.

2018-06-01

Control volume based finite element method (CVFEM) is applied to simulate H2O based nanofluid radiative and convective heat transfer inside a porous medium. Non-Darcy model is employed for porous media. Influences of Hartmann number, nanofluid volume fraction, radiation parameter, Darcy number, number of undulations and Rayleigh number on nanofluid behavior were demonstrated. Thermal conductivity of nanofluid is estimated by means of previous experimental correlation. Results show that Nusselt number enhances with augment of permeability of porous media. Effect of Hartmann number on rate of heat transfer is opposite of radiation parameter.

High-performance lighting evaluated by photobiological parameters.

PubMed

Rebec, Katja Malovrh; Gunde, Marta Klanjšek

2014-08-10

The human reception of light includes image-forming and non-image-forming effects which are triggered by spectral distribution and intensity of light. Ideal lighting is similar to daylight, which could be evaluated by spectral or chromaticity match. LED-based and CFL-based lighting were analyzed here, proposed according to spectral and chromaticity match, respectively. The photobiological effects were expressed by effectiveness for blue light hazard, cirtopic activity, and photopic vision. Good spectral match provides light with more similar effects to those obtained by the chromaticity match. The new parameters are useful for better evaluation of complex human responses caused by lighting.

Interspecies interactions are an integral determinant of microbial community dynamics

PubMed Central

Aziz, Fatma A. A.; Suzuki, Kenshi; Ohtaki, Akihiro; Sagegami, Keita; Hirai, Hidetaka; Seno, Jun; Mizuno, Naoko; Inuzuka, Yuma; Saito, Yasuhisa; Tashiro, Yosuke; Hiraishi, Akira; Futamata, Hiroyuki

2015-01-01

This study investigated the factors that determine the dynamics of bacterial communities in a complex system using multidisciplinary methods. Since natural and engineered microbial ecosystems are too complex to study, six types of synthetic microbial ecosystems (SMEs) were constructed under chemostat conditions with phenol as the sole carbon and energy source. Two to four phenol-degrading, phylogenetically and physiologically different bacterial strains were used in each SME. Phylogeny was based on the nucleotide sequence of 16S rRNA genes, while physiologic traits were based on kinetic and growth parameters on phenol. Two indices, J parameter and “interspecies interaction,” were compared to predict which strain would become dominant in an SME. The J parameter was calculated from kinetic and growth parameters. On the other hand, “interspecies interaction,” a new index proposed in this study, was evaluated by measuring the specific growth activity, which was determined on the basis of relative growth of a strain with or without the supernatant prepared from other bacterial cultures. Population densities of strains used in SMEs were enumerated by real-time quantitative PCR (qPCR) targeting the gene encoding the large subunit of phenol hydroxylase and were compared to predictions made from J parameter and interspecies interaction calculations. In 4 of 6 SEMs tested the final dominant strain shown by real-time qPCR analyses coincided with the strain predicted by both the J parameter and the interspecies interaction. However, in SMEII-2 and SMEII-3 the final dominant Variovorax strains coincided with prediction of the interspecies interaction but not the J parameter. These results demonstrate that the effects of interspecies interactions within microbial communities contribute to determining the dynamics of the microbial ecosystem. PMID:26539177

Automated source term and wind parameter estimation for atmospheric transport and dispersion applications

NASA Astrophysics Data System (ADS)

Bieringer, Paul E.; Rodriguez, Luna M.; Vandenberghe, Francois; Hurst, Jonathan G.; Bieberbach, George; Sykes, Ian; Hannan, John R.; Zaragoza, Jake; Fry, Richard N.

2015-12-01

Accurate simulations of the atmospheric transport and dispersion (AT&D) of hazardous airborne materials rely heavily on the source term parameters necessary to characterize the initial release and meteorological conditions that drive the downwind dispersion. In many cases the source parameters are not known and consequently based on rudimentary assumptions. This is particularly true of accidental releases and the intentional releases associated with terrorist incidents. When available, meteorological observations are often not representative of the conditions at the location of the release and the use of these non-representative meteorological conditions can result in significant errors in the hazard assessments downwind of the sensors, even when the other source parameters are accurately characterized. Here, we describe a computationally efficient methodology to characterize both the release source parameters and the low-level winds (eg. winds near the surface) required to produce a refined downwind hazard. This methodology, known as the Variational Iterative Refinement Source Term Estimation (STE) Algorithm (VIRSA), consists of a combination of modeling systems. These systems include a back-trajectory based source inversion method, a forward Gaussian puff dispersion model, a variational refinement algorithm that uses both a simple forward AT&D model that is a surrogate for the more complex Gaussian puff model and a formal adjoint of this surrogate model. The back-trajectory based method is used to calculate a ;first guess; source estimate based on the available observations of the airborne contaminant plume and atmospheric conditions. The variational refinement algorithm is then used to iteratively refine the first guess STE parameters and meteorological variables. The algorithm has been evaluated across a wide range of scenarios of varying complexity. It has been shown to improve the source parameters for location by several hundred percent (normalized by the distance from source to the closest sampler), and improve mass estimates by several orders of magnitude. Furthermore, it also has the ability to operate in scenarios with inconsistencies between the wind and airborne contaminant sensor observations and adjust the wind to provide a better match between the hazard prediction and the observations.

Simple taper: Taper equations for the field forester

Treesearch

David R. Larsen

2017-01-01

"Simple taper" is set of linear equations that are based on stem taper rates; the intent is to provide taper equation functionality to field foresters. The equation parameters are two taper rates based on differences in diameter outside bark at two points on a tree. The simple taper equations are statistically equivalent to more complex equations. The linear...

Using a system of differential equations that models cattle growth to uncover the genetic basis of complex traits.

PubMed

Freua, Mateus Castelani; Santana, Miguel Henrique de Almeida; Ventura, Ricardo Vieira; Tedeschi, Luis Orlindo; Ferraz, José Bento Sterman

2017-08-01

The interplay between dynamic models of biological systems and genomics is based on the assumption that genetic variation of the complex trait (i.e., outcome of model behavior) arises from component traits (i.e., model parameters) in lower hierarchical levels. In order to provide a proof of concept of this statement for a cattle growth model, we ask whether model parameters map genomic regions that harbor quantitative trait loci (QTLs) already described for the complex trait. We conducted a genome-wide association study (GWAS) with a Bayesian hierarchical LASSO method in two parameters of the Davis Growth Model, a system of three ordinary differential equations describing DNA accretion, protein synthesis and degradation, and fat synthesis. Phenotypic and genotypic data were available for 893 Nellore (Bos indicus) cattle. Computed values for parameter k 1 (DNA accretion rate) ranged from 0.005 ± 0.003 and for α (constant for energy for maintenance requirement) 0.134 ± 0.024. The expected biological interpretation of the parameters is confirmed by QTLs mapped for k 1 and α. QTLs within genomic regions mapped for k 1 are expected to be correlated with the DNA pool: body size and weight. Single nucleotide polymorphisms (SNPs) which were significant for α mapped QTLs that had already been associated with residual feed intake, feed conversion ratio, average daily gain (ADG), body weight, and also dry matter intake. SNPs identified for k 1 were able to additionally explain 2.2% of the phenotypic variability of the complex ADG, even when SNPs for k 1 did not match the genomic regions associated with ADG. Although improvements are needed, our findings suggest that genomic analysis on component traits may help to uncover the genetic basis of more complex traits, particularly when lower biological hierarchies are mechanistically described by mathematical simulation models.

Spectroscopic and electrochemical characterization of some Schiff base metal complexes containing benzoin moiety

NASA Astrophysics Data System (ADS)

El-Shahawi, M. S.; Al-Jahdali, M. S.; Bashammakh, A. S.; Al-Sibaai, A. A.; Nassef, H. M.

2013-09-01

The ligation behavior of bis-benzoin ethylenediamine (B2ED) and benzoin thiosemicarbazone (BTS) Schiff bases towards Ru3+, Rh3+, Pd2+, Ni2+ and Cu2+ were determined. The bond length of M-N and spectrochemical parameters (10Dq, β, B and LFSE) of the complexes were evaluated. The redox characteristics of selected complexes were explored by cyclic voltammetry (CV) at Pt working electrode in non aqueous solvents. Au mesh (100 w/in.) optically transparent thin layer electrode (OTTLE) was also used for recording thin layer CV for selected Ru complex. Oxidation of some complexes occurs in a consecutive chemical reaction of an EC type mechanism. The characteristics of electron transfer process of the couples M2+/M3+ and M3+/M4+ (M = Ru3+, Rh3+) and the stability of the complexes towards oxidation and/or reduction were assigned. The nature of the electroactive species and reduction mechanism of selected electrode couples were assigned.

Application of Differential Evolutionary Optimization Methodology for Parameter Structure Identification in Groundwater Modeling

NASA Astrophysics Data System (ADS)

Chiu, Y.; Nishikawa, T.

2013-12-01

With the increasing complexity of parameter-structure identification (PSI) in groundwater modeling, there is a need for robust, fast, and accurate optimizers in the groundwater-hydrology field. For this work, PSI is defined as identifying parameter dimension, structure, and value. In this study, Voronoi tessellation and differential evolution (DE) are used to solve the optimal PSI problem. Voronoi tessellation is used for automatic parameterization, whereby stepwise regression and the error covariance matrix are used to determine the optimal parameter dimension. DE is a novel global optimizer that can be used to solve nonlinear, nondifferentiable, and multimodal optimization problems. It can be viewed as an improved version of genetic algorithms and employs a simple cycle of mutation, crossover, and selection operations. DE is used to estimate the optimal parameter structure and its associated values. A synthetic numerical experiment of continuous hydraulic conductivity distribution was conducted to demonstrate the proposed methodology. The results indicate that DE can identify the global optimum effectively and efficiently. A sensitivity analysis of the control parameters (i.e., the population size, mutation scaling factor, crossover rate, and mutation schemes) was performed to examine their influence on the objective function. The proposed DE was then applied to solve a complex parameter-estimation problem for a small desert groundwater basin in Southern California. Hydraulic conductivity, specific yield, specific storage, fault conductance, and recharge components were estimated simultaneously. Comparison of DE and a traditional gradient-based approach (PEST) shows DE to be more robust and efficient. The results of this work not only provide an alternative for PSI in groundwater models, but also extend DE applications towards solving complex, regional-scale water management optimization problems.

Simulation Based Earthquake Forecasting with RSQSim

NASA Astrophysics Data System (ADS)

Gilchrist, J. J.; Jordan, T. H.; Dieterich, J. H.; Richards-Dinger, K. B.

2016-12-01

We are developing a physics-based forecasting model for earthquake ruptures in California. We employ the 3D boundary element code RSQSim to generate synthetic catalogs with millions of events that span up to a million years. The simulations incorporate rate-state fault constitutive properties in complex, fully interacting fault systems. The Unified California Earthquake Rupture Forecast Version 3 (UCERF3) model and data sets are used for calibration of the catalogs and specification of fault geometry. Fault slip rates match the UCERF3 geologic slip rates and catalogs are tuned such that earthquake recurrence matches the UCERF3 model. Utilizing the Blue Waters Supercomputer, we produce a suite of million-year catalogs to investigate the epistemic uncertainty in the physical parameters used in the simulations. In particular, values of the rate- and state-friction parameters a and b, the initial shear and normal stress, as well as the earthquake slip speed, are varied over several simulations. In addition to testing multiple models with homogeneous values of the physical parameters, the parameters a, b, and the normal stress are varied with depth as well as in heterogeneous patterns across the faults. Cross validation of UCERF3 and RSQSim is performed within the SCEC Collaboratory for Interseismic Simulation and Modeling (CISM) to determine the affect of the uncertainties in physical parameters observed in the field and measured in the lab, on the uncertainties in probabilistic forecasting. We are particularly interested in the short-term hazards of multi-event sequences due to complex faulting and multi-fault ruptures.

Support vector machines-based modelling of seismic liquefaction potential

NASA Astrophysics Data System (ADS)

Pal, Mahesh

2006-08-01

This paper investigates the potential of support vector machines (SVM)-based classification approach to assess the liquefaction potential from actual standard penetration test (SPT) and cone penetration test (CPT) field data. SVMs are based on statistical learning theory and found to work well in comparison to neural networks in several other applications. Both CPT and SPT field data sets is used with SVMs for predicting the occurrence and non-occurrence of liquefaction based on different input parameter combination. With SPT and CPT test data sets, highest accuracy of 96 and 97%, respectively, was achieved with SVMs. This suggests that SVMs can effectively be used to model the complex relationship between different soil parameter and the liquefaction potential. Several other combinations of input variable were used to assess the influence of different input parameters on liquefaction potential. Proposed approach suggest that neither normalized cone resistance value with CPT data nor the calculation of standardized SPT value is required with SPT data. Further, SVMs required few user-defined parameters and provide better performance in comparison to neural network approach.

Agent-Based Model with Asymmetric Trading and Herding for Complex Financial Systems

PubMed Central

Chen, Jun-Jie; Zheng, Bo; Tan, Lei

2013-01-01

Background For complex financial systems, the negative and positive return-volatility correlations, i.e., the so-called leverage and anti-leverage effects, are particularly important for the understanding of the price dynamics. However, the microscopic origination of the leverage and anti-leverage effects is still not understood, and how to produce these effects in agent-based modeling remains open. On the other hand, in constructing microscopic models, it is a promising conception to determine model parameters from empirical data rather than from statistical fitting of the results. Methods To study the microscopic origination of the return-volatility correlation in financial systems, we take into account the individual and collective behaviors of investors in real markets, and construct an agent-based model. The agents are linked with each other and trade in groups, and particularly, two novel microscopic mechanisms, i.e., investors’ asymmetric trading and herding in bull and bear markets, are introduced. Further, we propose effective methods to determine the key parameters in our model from historical market data. Results With the model parameters determined for six representative stock-market indices in the world, respectively, we obtain the corresponding leverage or anti-leverage effect from the simulation, and the effect is in agreement with the empirical one on amplitude and duration. At the same time, our model produces other features of the real markets, such as the fat-tail distribution of returns and the long-term correlation of volatilities. Conclusions We reveal that for the leverage and anti-leverage effects, both the investors’ asymmetric trading and herding are essential generation mechanisms. Among the six markets, however, the investors’ trading is approximately symmetric for the five markets which exhibit the leverage effect, thus contributing very little. These two microscopic mechanisms and the methods for the determination of the key parameters can be applied to other complex systems with similar asymmetries. PMID:24278146

Data Mining for Efficient and Accurate Large Scale Retrieval of Geophysical Parameters

NASA Astrophysics Data System (ADS)

Obradovic, Z.; Vucetic, S.; Peng, K.; Han, B.

2004-12-01

Our effort is devoted to developing data mining technology for improving efficiency and accuracy of the geophysical parameter retrievals by learning a mapping from observation attributes to the corresponding parameters within the framework of classification and regression. We will describe a method for efficient learning of neural network-based classification and regression models from high-volume data streams. The proposed procedure automatically learns a series of neural networks of different complexities on smaller data stream chunks and then properly combines them into an ensemble predictor through averaging. Based on the idea of progressive sampling the proposed approach starts with a very simple network trained on a very small chunk and then gradually increases the model complexity and the chunk size until the learning performance no longer improves. Our empirical study on aerosol retrievals from data obtained with the MISR instrument mounted at Terra satellite suggests that the proposed method is successful in learning complex concepts from large data streams with near-optimal computational effort. We will also report on a method that complements deterministic retrievals by constructing accurate predictive algorithms and applying them on appropriately selected subsets of observed data. The method is based on developing more accurate predictors aimed to catch global and local properties synthesized in a region. The procedure starts by learning the global properties of data sampled over the entire space, and continues by constructing specialized models on selected localized regions. The global and local models are integrated through an automated procedure that determines the optimal trade-off between the two components with the objective of minimizing the overall mean square errors over a specific region. Our experimental results on MISR data showed that the combined model can increase the retrieval accuracy significantly. The preliminary results on various large heterogeneous spatial-temporal datasets provide evidence that the benefits of the proposed methodology for efficient and accurate learning exist beyond the area of retrieval of geophysical parameters.

Agent-based model with asymmetric trading and herding for complex financial systems.

PubMed

Chen, Jun-Jie; Zheng, Bo; Tan, Lei

2013-01-01

For complex financial systems, the negative and positive return-volatility correlations, i.e., the so-called leverage and anti-leverage effects, are particularly important for the understanding of the price dynamics. However, the microscopic origination of the leverage and anti-leverage effects is still not understood, and how to produce these effects in agent-based modeling remains open. On the other hand, in constructing microscopic models, it is a promising conception to determine model parameters from empirical data rather than from statistical fitting of the results. To study the microscopic origination of the return-volatility correlation in financial systems, we take into account the individual and collective behaviors of investors in real markets, and construct an agent-based model. The agents are linked with each other and trade in groups, and particularly, two novel microscopic mechanisms, i.e., investors' asymmetric trading and herding in bull and bear markets, are introduced. Further, we propose effective methods to determine the key parameters in our model from historical market data. With the model parameters determined for six representative stock-market indices in the world, respectively, we obtain the corresponding leverage or anti-leverage effect from the simulation, and the effect is in agreement with the empirical one on amplitude and duration. At the same time, our model produces other features of the real markets, such as the fat-tail distribution of returns and the long-term correlation of volatilities. We reveal that for the leverage and anti-leverage effects, both the investors' asymmetric trading and herding are essential generation mechanisms. Among the six markets, however, the investors' trading is approximately symmetric for the five markets which exhibit the leverage effect, thus contributing very little. These two microscopic mechanisms and the methods for the determination of the key parameters can be applied to other complex systems with similar asymmetries.

Spectral, coordination and thermal properties of 5-arylidene thiobarbituric acids

NASA Astrophysics Data System (ADS)

Masoud, Mamdouh S.; El-Marghany, Adel; Orabi, Adel; Ali, Alaa E.; Sayed, Reham

2013-04-01

Synthesis of 5-arylidine thiobarbituric acids containing different functional groups with variable electronic characters were described and their Co2+, Ni2+ and Cu2+ complexes. The stereochemistry and mode of bonding of 5-(substituted benzylidine)-2-TBA complexes were achieved based on elemental analysis, spectral (UV-VIS, IR, 1H NMR, MS), magnetic susceptibility and conductivity measurements. The ligands were of bidentate and tridentate bonding through S, N and O of pyrimidine nucleolus. All complexes were of octahedral configuration. The thermal data of the complexes pointed to their stability. The mechanism of the thermal decomposition is discussed. The thermodynamic parameters of the dissociation steps were evaluated and discussed.

Modeling complexity in pathologist workload measurement: the Automatable Activity-Based Approach to Complexity Unit Scoring (AABACUS).

PubMed

Cheung, Carol C; Torlakovic, Emina E; Chow, Hung; Snover, Dale C; Asa, Sylvia L

2015-03-01

Pathologists provide diagnoses relevant to the disease state of the patient and identify specific tissue characteristics relevant to response to therapy and prognosis. As personalized medicine evolves, there is a trend for increased demand of tissue-derived parameters. Pathologists perform increasingly complex analyses on the same 'cases'. Traditional methods of workload assessment and reimbursement, based on number of cases sometimes with a modifier (eg, the relative value unit (RVU) system used in the United States), often grossly underestimate the amount of work needed for complex cases and may overvalue simple, small biopsy cases. We describe a new approach to pathologist workload measurement that aligns with this new practice paradigm. Our multisite institution with geographically diverse partner institutions has developed the Automatable Activity-Based Approach to Complexity Unit Scoring (AABACUS) model that captures pathologists' clinical activities from parameters documented in departmental laboratory information systems (LISs). The model's algorithm includes: 'capture', 'export', 'identify', 'count', 'score', 'attribute', 'filter', and 'assess filtered results'. Captured data include specimen acquisition, handling, analysis, and reporting activities. Activities were counted and complexity units (CUs) generated using a complexity factor for each activity. CUs were compared between institutions, practice groups, and practice types and evaluated over a 5-year period (2008-2012). The annual load of a clinical service pathologist, irrespective of subspecialty, was ∼40,000 CUs using relative benchmarking. The model detected changing practice patterns and was appropriate for monitoring clinical workload for anatomical pathology, neuropathology, and hematopathology in academic and community settings, and encompassing subspecialty and generalist practices. AABACUS is objective, can be integrated with an LIS and automated, is reproducible, backwards compatible, and future adaptable. It can be applied as a robust decision support tool for the assessment of overall and targeted staffing needs as well as utilization analyses for resource allocation.

Range image segmentation using Zernike moment-based generalized edge detector

NASA Technical Reports Server (NTRS)

Ghosal, S.; Mehrotra, R.

1992-01-01

The authors proposed a novel Zernike moment-based generalized step edge detection method which can be used for segmenting range and intensity images. A generalized step edge detector is developed to identify different kinds of edges in range images. These edge maps are thinned and linked to provide final segmentation. A generalized edge is modeled in terms of five parameters: orientation, two slopes, one step jump at the location of the edge, and the background gray level. Two complex and two real Zernike moment-based masks are required to determine all these parameters of the edge model. Theoretical noise analysis is performed to show that these operators are quite noise tolerant. Experimental results are included to demonstrate edge-based segmentation technique.

[Analysis of Conformational Features of Watson-Crick Duplex Fragments by Molecular Mechanics and Quantum Mechanics Methods].

PubMed

Poltev, V I; Anisimov, V M; Sanchez, C; Deriabina, A; Gonzalez, E; Garcia, D; Rivas, F; Polteva, N A

2016-01-01

It is generally accepted that the important characteristic features of the Watson-Crick duplex originate from the molecular structure of its subunits. However, it still remains to elucidate what properties of each subunit are responsible for the significant characteristic features of the DNA structure. The computations of desoxydinucleoside monophosphates complexes with Na-ions using density functional theory revealed a pivotal role of DNA conformational properties of single-chain minimal fragments in the development of unique features of the Watson-Crick duplex. We found that directionality of the sugar-phosphate backbone and the preferable ranges of its torsion angles, combined with the difference between purines and pyrimidines. in ring bases, define the dependence of three-dimensional structure of the Watson-Crick duplex on nucleotide base sequence. In this work, we extended these density functional theory computations to the minimal' fragments of DNA duplex, complementary desoxydinucleoside monophosphates complexes with Na-ions. Using several computational methods and various functionals, we performed a search for energy minima of BI-conformation for complementary desoxydinucleoside monophosphates complexes with different nucleoside sequences. Two sequences are optimized using ab initio method at the MP2/6-31++G** level of theory. The analysis of torsion angles, sugar ring puckering and mutual base positions of optimized structures demonstrates that the conformational characteristic features of complementary desoxydinucleoside monophosphates complexes with Na-ions remain within BI ranges and become closer to the corresponding characteristic features of the Watson-Crick duplex crystals. Qualitatively, the main characteristic features of each studied complementary desoxydinucleoside monophosphates complex remain invariant when different computational methods are used, although the quantitative values of some conformational parameters could vary lying within the limits typical for the corresponding family. We observe that popular functionals in density functional theory calculations lead to the overestimated distances between base pairs, while MP2 computations and the newer complex functionals produce the structures that have too close atom-atom contacts. A detailed study of some complementary desoxydinucleoside monophosphate complexes with Na-ions highlights the existence of several energy minima corresponding to BI-conformations, in other words, the complexity of the relief pattern of the potential energy surface of complementary desoxydinucleoside monophosphate complexes. This accounts for variability of conformational parameters of duplex fragments with the same base sequence. Popular molecular mechanics force fields AMBER and CHARMM reproduce most of the conformational characteristics of desoxydinucleoside monophosphates and their complementary complexes with Na-ions but fail to reproduce some details of the dependence of the Watson-Crick duplex conformation on the nucleotide sequence.

Impact of earthquake source complexity and land elevation data resolution on tsunami hazard assessment and fatality estimation

NASA Astrophysics Data System (ADS)

Muhammad, Ario; Goda, Katsuichiro

2018-03-01

This study investigates the impact of model complexity in source characterization and digital elevation model (DEM) resolution on the accuracy of tsunami hazard assessment and fatality estimation through a case study in Padang, Indonesia. Two types of earthquake source models, i.e. complex and uniform slip models, are adopted by considering three resolutions of DEMs, i.e. 150 m, 50 m, and 10 m. For each of the three grid resolutions, 300 complex source models are generated using new statistical prediction models of earthquake source parameters developed from extensive finite-fault models of past subduction earthquakes, whilst 100 uniform slip models are constructed with variable fault geometry without slip heterogeneity. The results highlight that significant changes to tsunami hazard and fatality estimates are observed with regard to earthquake source complexity and grid resolution. Coarse resolution (i.e. 150 m) leads to inaccurate tsunami hazard prediction and fatality estimation, whilst 50-m and 10-m resolutions produce similar results. However, velocity and momentum flux are sensitive to the grid resolution and hence, at least 10-m grid resolution needs to be implemented when considering flow-based parameters for tsunami hazard and risk assessments. In addition, the results indicate that the tsunami hazard parameters and fatality number are more sensitive to the complexity of earthquake source characterization than the grid resolution. Thus, the uniform models are not recommended for probabilistic tsunami hazard and risk assessments. Finally, the findings confirm that uncertainties of tsunami hazard level and fatality in terms of depth, velocity and momentum flux can be captured and visualized through the complex source modeling approach. From tsunami risk management perspectives, this indeed creates big data, which are useful for making effective and robust decisions.

Compact continuum brain model for human electroencephalogram

NASA Astrophysics Data System (ADS)

Kim, J. W.; Shin, H.-B.; Robinson, P. A.

2007-12-01

A low-dimensional, compact brain model has recently been developed based on physiologically based mean-field continuum formulation of electric activity of the brain. The essential feature of the new compact model is a second order time-delayed differential equation that has physiologically plausible terms, such as rapid corticocortical feedback and delayed feedback via extracortical pathways. Due to its compact form, the model facilitates insight into complex brain dynamics via standard linear and nonlinear techniques. The model successfully reproduces many features of previous models and experiments. For example, experimentally observed typical rhythms of electroencephalogram (EEG) signals are reproduced in a physiologically plausible parameter region. In the nonlinear regime, onsets of seizures, which often develop into limit cycles, are illustrated by modulating model parameters. It is also shown that a hysteresis can occur when the system has multiple attractors. As a further illustration of this approach, power spectra of the model are fitted to those of sleep EEGs of two subjects (one with apnea, the other with narcolepsy). The model parameters obtained from the fittings show good matches with previous literature. Our results suggest that the compact model can provide a theoretical basis for analyzing complex EEG signals.

Synthesis, structural characterization, fluorescence, antimicrobial, antioxidant and DNA cleavage studies of Cu(II) complexes of formyl chromone Schiff bases.

PubMed

Kavitha, P; Saritha, M; Laxma Reddy, K

2013-02-01

Cu(II) complexes have been synthesized from different Schiff bases, such as 3-((2-hydroxy phenylimino)methyl)-4H-chromen-4-one (HL(1)), 2-((4-oxo-4H-chromen-3-yl)methylneamino) benzoicacid (HL(2)), 3-((3-hydroxypyridin-2-ylimino)methyl)-4H-chromen-4-one (HL(3)) and 3-((2-mercaptophenylimino)methyl)-4H-chromen-4-one (HL(4)). The complexes were characterized by analytical, molar conductance, IR, electronic, magnetic, ESR, thermal, powder XRD and SEM studies. The analytical data reveal that metal to ligand molar ratio is 1:2 in all the complexes. Molar conductivity data indicates that all the Cu(II) complexes are neutral. On the basis of magnetic and electronic spectral data, distorted octahedral geometry is proposed for all the Cu(II) complexes. Thermal behaviour of the synthesized complexes illustrates the presence of lattice water molecules in the complexes. X-ray diffraction studies reveal that all the ligands and their Cu(II) complexes have triclinic system with different unit cell parameters. Antimicrobial, antioxidant and DNA cleavage activities indicate that metal complexes exhibited greater activity as compared with ligands. Copyright © 2012 Elsevier B.V. All rights reserved.

Glaucoma diagnosis by mapping macula with Fourier domain optical coherence tomography

NASA Astrophysics Data System (ADS)

Tan, Ou; Lu, Ake; Chopra, Vik; Varma, Rohit; Hiroshi, Ishikawa; Schuman, Joel; Huang, David

2008-03-01

A new image segmentation method was developed to detect macular retinal sub-layers boundary on newly-developed Fourier-Domain Optical Coherence Tomography (FD-OCT) with macular grid scan pattern. The segmentation results were used to create thickness map of macular ganglion cell complex (GCC), which contains the ganglion cell dendrites, cell bodies and axons. Overall average and several pattern analysis parameters were defined on the GCC thickness map and compared for the diagnosis of glaucoma. Intraclass correlation (ICC) is used to compare the reproducibility of the parameters. Area under receiving operative characteristic curve (AROC) was calculated to compare the diagnostic power. The result is also compared to the output of clinical time-domain OCT (TD-OCT). We found that GCC based parameters had good repeatability and comparable diagnostic power with circumpapillary nerve fiber layer (cpNFL) thickness. Parameters based on pattern analysis can increase the diagnostic power of GCC macular mapping.

Material parameter estimation with terahertz time-domain spectroscopy.

PubMed

Dorney, T D; Baraniuk, R G; Mittleman, D M

2001-07-01

Imaging systems based on terahertz (THz) time-domain spectroscopy offer a range of unique modalities owing to the broad bandwidth, subpicosecond duration, and phase-sensitive detection of the THz pulses. Furthermore, the possibility exists for combining spectroscopic characterization or identification with imaging because the radiation is broadband in nature. To achieve this, we require novel methods for real-time analysis of THz waveforms. This paper describes a robust algorithm for extracting material parameters from measured THz waveforms. Our algorithm simultaneously obtains both the thickness and the complex refractive index of an unknown sample under certain conditions. In contrast, most spectroscopic transmission measurements require knowledge of the sample's thickness for an accurate determination of its optical parameters. Our approach relies on a model-based estimation, a gradient descent search, and the total variation measure. We explore the limits of this technique and compare the results with literature data for optical parameters of several different materials.

Bayesian parameter inference for stochastic biochemical network models using particle Markov chain Monte Carlo

PubMed Central

Golightly, Andrew; Wilkinson, Darren J.

2011-01-01

Computational systems biology is concerned with the development of detailed mechanistic models of biological processes. Such models are often stochastic and analytically intractable, containing uncertain parameters that must be estimated from time course data. In this article, we consider the task of inferring the parameters of a stochastic kinetic model defined as a Markov (jump) process. Inference for the parameters of complex nonlinear multivariate stochastic process models is a challenging problem, but we find here that algorithms based on particle Markov chain Monte Carlo turn out to be a very effective computationally intensive approach to the problem. Approximations to the inferential model based on stochastic differential equations (SDEs) are considered, as well as improvements to the inference scheme that exploit the SDE structure. We apply the methodology to a Lotka–Volterra system and a prokaryotic auto-regulatory network. PMID:23226583

Surrogate models for efficient stability analysis of brake systems

NASA Astrophysics Data System (ADS)

Nechak, Lyes; Gillot, Frédéric; Besset, Sébastien; Sinou, Jean-Jacques

2015-07-01

This study assesses capacities of the global sensitivity analysis combined together with the kriging formalism to be useful in the robust stability analysis of brake systems, which is too costly when performed with the classical complex eigenvalues analysis (CEA) based on finite element models (FEMs). By considering a simplified brake system, the global sensitivity analysis is first shown very helpful for understanding the effects of design parameters on the brake system's stability. This is allowed by the so-called Sobol indices which discriminate design parameters with respect to their influence on the stability. Consequently, only uncertainty of influent parameters is taken into account in the following step, namely, the surrogate modelling based on kriging. The latter is then demonstrated to be an interesting alternative to FEMs since it allowed, with a lower cost, an accurate estimation of the system's proportions of instability corresponding to the influent parameters.

Dependence of quantitative accuracy of CT perfusion imaging on system parameters

NASA Astrophysics Data System (ADS)

Li, Ke; Chen, Guang-Hong

2017-03-01

Deconvolution is a popular method to calculate parametric perfusion parameters from four dimensional CT perfusion (CTP) source images. During the deconvolution process, the four dimensional space is squeezed into three-dimensional space by removing the temporal dimension, and a prior knowledge is often used to suppress noise associated with the process. These additional complexities confound the understanding about deconvolution-based CTP imaging system and how its quantitative accuracy depends on parameters and sub-operations involved in the image formation process. Meanwhile, there has been a strong clinical need in answering this question, as physicians often rely heavily on the quantitative values of perfusion parameters to make diagnostic decisions, particularly during an emergent clinical situation (e.g. diagnosis of acute ischemic stroke). The purpose of this work was to develop a theoretical framework that quantitatively relates the quantification accuracy of parametric perfusion parameters with CTP acquisition and post-processing parameters. This goal was achieved with the help of a cascaded systems analysis for deconvolution-based CTP imaging systems. Based on the cascaded systems analysis, the quantitative relationship between regularization strength, source image noise, arterial input function, and the quantification accuracy of perfusion parameters was established. The theory could potentially be used to guide developments of CTP imaging technology for better quantification accuracy and lower radiation dose.

Synthesis, spectroscopic, thermal and molecular modeling studies of Zn2+, Cd2+ and UO22+ complexes of Schiff bases containing triazole moiety. Antimicrobial, anticancer, antioxidant and DNA binding studies.

PubMed

Gaber, Mohamed; El-Ghamry, Hoda A; Fathalla, Shaimaa K; Mansour, Mohammed A

2018-02-01

A novel series of Zn 2+ , Cd 2+ and UO 2 2+ complexes of ligands namely 1-[(5-mercapto-1H-1,2,4-triazole-3-ylimino) methyl]naphthalene-2-ol (HL 1 ) and [(1H-1,2,4-triazole-3-ylimino) methyl] naphthalene-2-ol (HL 2 ) have been prepared and characterized by different analytical and spectral techniques. The stoichiometry, stereochemistry, conductivity measurements and mode of bonding of the complexes have been elucidated. Accurate comparison of the IR spectra of the ligands with their metal chelates proved the involvement of nitrogen atoms of the azomethine group and/or triazole ring in chelation in addition to the deprotonated hydroxyl oxygen. The UV-Vis and molar conductance data supported the octahedral geometry for the metal complexes. TGA technique has been used to study the thermal decomposition way of the metal complexes and the thermo kinetic parameters were estimated. Valuable information is obtained from calculations of molecular parameters using the molecular modeling techniques. The interaction between the metal complexes and CT-DNA has been studied from which the binding constants (k b ) were calculated. The Schiff bases and their metal chelates have shown potent antimicrobial, antioxidant and antitumor activities. The antitumor activities of the compounds have been tested in vitro against HEPG2 cell line and in silico by the molecular docking analysis with the VEGFR-2 receptor responsible for angiogenesis. Copyright © 2017 Elsevier B.V. All rights reserved.

Charge transfer complexes of adenosine-5‧-monophosphate and cytidine-5‧-monophosphate with water-soluble cobalt(II) Schiff base complexes in aqueous solution

NASA Astrophysics Data System (ADS)

Boghaei, Davar M.; Gharagozlou, Mehrnaz

2006-01-01

Water-soluble cobalt(II) tetradentate Schiff base complexes have been shown to form charge transfer (CT) complexes with a series of nucleoside monophosphates including adenosine-5‧-monophosphate (AMP) and cytidine-5‧-monophosphate (CMP). The investigated water-soluble cobalt(II) Schiff base complexes are (i) disodium[{bis(5-sulfo-salicylaldehyde)-o-phenylenediiminato}cobalt(II)], Na2[Co(SO3-salophen)] (1); (ii) disodium[{bis(5-sulfo-salicylaldehyde)-4,5-dimethyl-o-phenylenediiminato}cobalt(II)], Na2[Co(SO3-sal-4,5-dmophen)] (2) and (iii) disodium[{bis(4-methoxy-5-sulfo-salicylaldehyde)-4,5-dimethyl-o-phenylenediiminato}cobalt(II)], Na2[Co(SO3-4-meosal-4,5-dmophen)] (3). The formation constant and thermodynamic parameters for charge transfer complex formation of water-soluble cobalt(II) Schiff base complexes with nucleoside monophosphates were determined spectrophotometrically in aqueous solution at constant ionic strength (I = 0.2 mol dm-3 KNO3) under physiological condition (pH 7.0) and at various temperatures between 288 and 308 K. The stoichiometry has been found to be 1:1 (water-soluble cobalt(II) Schiff base complex: nucleoside monophosphate) in each case. Our spectroscopic and thermodynamic results show that the interaction of water-soluble cobalt(II) Schiff base complexes with the investigated nucleoside monophosphates occurs mainly through the phosphate group. The trend of the interaction according to the cobalt(II) Schiff base complexes due to electronic and steric factors is as follows: Na2[Co(SO3-salophen)] > Na2[Co(SO3-sal-4,5-dmophen)] > Na2[Co(SO3-4-meosal-4,5-dmophen)]. Also the trend of the interaction of a given cobalt(II) Schiff base complex according to the nucleoside monophosphate is as follows: CMP > AMP.

Toward simulating complex systems with quantum effects

NASA Astrophysics Data System (ADS)

Kenion-Hanrath, Rachel Lynn

Quantum effects like tunneling, coherence, and zero point energy often play a significant role in phenomena on the scales of atoms and molecules. However, the exact quantum treatment of a system scales exponentially with dimensionality, making it impractical for characterizing reaction rates and mechanisms in complex systems. An ongoing effort in the field of theoretical chemistry and physics is extending scalable, classical trajectory-based simulation methods capable of capturing quantum effects to describe dynamic processes in many-body systems; in the work presented here we explore two such techniques. First, we detail an explicit electron, path integral (PI)-based simulation protocol for predicting the rate of electron transfer in condensed-phase transition metal complex systems. Using a PI representation of the transferring electron and a classical representation of the transition metal complex and solvent atoms, we compute the outer sphere free energy barrier and dynamical recrossing factor of the electron transfer rate while accounting for quantum tunneling and zero point energy effects. We are able to achieve this employing only a single set of force field parameters to describe the system rather than parameterizing along the reaction coordinate. Following our success in describing a simple model system, we discuss our next steps in extending our protocol to technologically relevant materials systems. The latter half focuses on the Mixed Quantum-Classical Initial Value Representation (MQC-IVR) of real-time correlation functions, a semiclassical method which has demonstrated its ability to "tune'' between quantum- and classical-limit correlation functions while maintaining dynamic consistency. Specifically, this is achieved through a parameter that determines the quantumness of individual degrees of freedom. Here, we derive a semiclassical correction term for the MQC-IVR to systematically characterize the error introduced by different choices of simulation parameters, and demonstrate the ability of this approach to optimize MQC-IVR simulations.

PeTTSy: a computational tool for perturbation analysis of complex systems biology models.

PubMed

Domijan, Mirela; Brown, Paul E; Shulgin, Boris V; Rand, David A

2016-03-10

Over the last decade sensitivity analysis techniques have been shown to be very useful to analyse complex and high dimensional Systems Biology models. However, many of the currently available toolboxes have either used parameter sampling, been focused on a restricted set of model observables of interest, studied optimisation of a objective function, or have not dealt with multiple simultaneous model parameter changes where the changes can be permanent or temporary. Here we introduce our new, freely downloadable toolbox, PeTTSy (Perturbation Theory Toolbox for Systems). PeTTSy is a package for MATLAB which implements a wide array of techniques for the perturbation theory and sensitivity analysis of large and complex ordinary differential equation (ODE) based models. PeTTSy is a comprehensive modelling framework that introduces a number of new approaches and that fully addresses analysis of oscillatory systems. It examines sensitivity analysis of the models to perturbations of parameters, where the perturbation timing, strength, length and overall shape can be controlled by the user. This can be done in a system-global setting, namely, the user can determine how many parameters to perturb, by how much and for how long. PeTTSy also offers the user the ability to explore the effect of the parameter perturbations on many different types of outputs: period, phase (timing of peak) and model solutions. PeTTSy can be employed on a wide range of mathematical models including free-running and forced oscillators and signalling systems. To enable experimental optimisation using the Fisher Information Matrix it efficiently allows one to combine multiple variants of a model (i.e. a model with multiple experimental conditions) in order to determine the value of new experiments. It is especially useful in the analysis of large and complex models involving many variables and parameters. PeTTSy is a comprehensive tool for analysing large and complex models of regulatory and signalling systems. It allows for simulation and analysis of models under a variety of environmental conditions and for experimental optimisation of complex combined experiments. With its unique set of tools it makes a valuable addition to the current library of sensitivity analysis toolboxes. We believe that this software will be of great use to the wider biological, systems biology and modelling communities.

Synthesis, spectral, thermal and optical properties of Schiff-base complexes derived from 2(E)-2-((z)-4-hydroxypent-3-en-2-ylideneamino)-5-guanidinopentanoic acid and acetylacetone

NASA Astrophysics Data System (ADS)

Hosny, Nasser Mohammed; Hussien, Mostafa A.; Radwan, Fatima M.; Nawar, Nagwa

2017-09-01

New metal complexes derived from the in situ reaction of Cu(II), Co(II), Ni(II) and Zn(II) acetates with the Schiff-base ligand (H2L) resulted from the condensation of 2-amino-5-guanidinopentanoic acid (arginine) and acetylacetone have been synthesized. The resulting complexes have been characterized by, elemental analyses, ES-MS, IR, Raman spectra, UV-Vis., 1HNMR, ESR, thermal analyses (TGA and DTG) and magnetic measurements. The results showed that, The Schiff-base ligand acts as bi-negative tridentate coordinating via azomethine nitrogen, enolic carbonyl oxygen and carboxylate oxygen after displacement of hydrogen. The thermodynamic parameters E∗, ΔH, ΔG and ΔS of the isolated complexes have been calculated. The optical band gap (Eg) values of Cu, Co, Ni and Zn were found to be 3.3, 3.4, 3.7 and 4.3 eV, respectively, arising from direct transitions. Optical band gap measurements indicate the semi-conductivity nature of these complexes.

Complex Rotation Quantum Dynamic Neural Networks (CRQDNN) using Complex Quantum Neuron (CQN): Applications to time series prediction.

PubMed

Cui, Yiqian; Shi, Junyou; Wang, Zili

2015-11-01

Quantum Neural Networks (QNN) models have attracted great attention since it innovates a new neural computing manner based on quantum entanglement. However, the existing QNN models are mainly based on the real quantum operations, and the potential of quantum entanglement is not fully exploited. In this paper, we proposes a novel quantum neuron model called Complex Quantum Neuron (CQN) that realizes a deep quantum entanglement. Also, a novel hybrid networks model Complex Rotation Quantum Dynamic Neural Networks (CRQDNN) is proposed based on Complex Quantum Neuron (CQN). CRQDNN is a three layer model with both CQN and classical neurons. An infinite impulse response (IIR) filter is embedded in the Networks model to enable the memory function to process time series inputs. The Levenberg-Marquardt (LM) algorithm is used for fast parameter learning. The networks model is developed to conduct time series predictions. Two application studies are done in this paper, including the chaotic time series prediction and electronic remaining useful life (RUL) prediction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Reliability analysis in interdependent smart grid systems

NASA Astrophysics Data System (ADS)

Peng, Hao; Kan, Zhe; Zhao, Dandan; Han, Jianmin; Lu, Jianfeng; Hu, Zhaolong

2018-06-01

Complex network theory is a useful way to study many real complex systems. In this paper, a reliability analysis model based on complex network theory is introduced in interdependent smart grid systems. In this paper, we focus on understanding the structure of smart grid systems and studying the underlying network model, their interactions, and relationships and how cascading failures occur in the interdependent smart grid systems. We propose a practical model for interdependent smart grid systems using complex theory. Besides, based on percolation theory, we also study the effect of cascading failures effect and reveal detailed mathematical analysis of failure propagation in such systems. We analyze the reliability of our proposed model caused by random attacks or failures by calculating the size of giant functioning components in interdependent smart grid systems. Our simulation results also show that there exists a threshold for the proportion of faulty nodes, beyond which the smart grid systems collapse. Also we determine the critical values for different system parameters. In this way, the reliability analysis model based on complex network theory can be effectively utilized for anti-attack and protection purposes in interdependent smart grid systems.

Correlating contact line capillarity and dynamic contact angle hysteresis in surfactant-nanoparticle based complex fluids

NASA Astrophysics Data System (ADS)

Harikrishnan, A. R.; Dhar, Purbarun; Agnihotri, Prabhat K.; Gedupudi, Sateesh; Das, Sarit K.

2018-04-01

Dynamic wettability and contact angle hysteresis can be correlated to shed insight onto any solid-liquid interaction. Complex fluids are capable of altering the expected hysteresis and dynamic wetting behavior due to interfacial interactions. We report the effect of capillary number on the dynamic advancing and receding contact angles of surfactant-based nanocolloidal solutions on hydrophilic, near hydrophobic, and superhydrophobic surfaces by performing forced wetting and de-wetting experiments by employing the embedded needle method. A segregated study is performed to infer the contributing effects of the constituents and effects of particle morphology. The static contact angle hysteresis is found to be a function of particle and surfactant concentrations and greatly depends on the nature of the morphology of the particles. An order of estimate of line energy and a dynamic flow parameter called spreading factor and the transient variations of these parameters are explored which sheds light on the dynamics of contact line movement and response to perturbation of three-phase contact. The Cox-Voinov-Tanner law was found to hold for hydrophilic and a weak dependency on superhydrophobic surfaces with capillary number, and even for the complex fluids, with a varying degree of dependency for different fluids.

Influence of amino acids Shiff bases on irradiated DNA stability in vivo.

PubMed

Karapetyan, N H; Malakyan, M H; Bajinyan, S A; Torosyan, A L; Grigoryan, I E; Haroutiunian, S G

2013-01-01

To reveal protective role of the new Mn(II) complexes with Nicotinyl-L-Tyrosinate and Nicotinyl-L-Tryptophanate Schiff Bases against ionizing radiation. The DNA of the rats liver was isolated on 7, 14, and 30 days after X-ray irradiation. The differences between the DNA of irradiated rats and rats pre-treated with Mn(II) complexes were studied using the melting, microcalorimetry, and electrophoresis methods. The melting parameters and the melting enthalpy of rats livers DNA were changed after the X-ray irradiation: melting temperature and melting enthalpy were decreased and melting interval was increased. These results can be explained by destruction of DNA molecules. It was shown that pre-treatment of rats with Mn(II) complexes approximates the melting parameters to norm. Agarose gel electrophoresis data confirmed the results of melting studies. The separate DNA fragments were revealed in DNA samples isolated from irradiated animals. The DNA isolated from animals pre-treated with the Mn(II) chelates had better electrophoretic characteristics, which correspond to healthy DNA. Pre-treatment of the irradiated rats with Mn(II)(Nicotinil-L-Tyrosinate) and Mn(II)(Nicotinil-L-Tryptophanate)2 improves the DNA characteristics.

Identification of inelastic parameters based on deep drawing forming operations using a global-local hybrid Particle Swarm approach

NASA Astrophysics Data System (ADS)

Vaz, Miguel; Luersen, Marco A.; Muñoz-Rojas, Pablo A.; Trentin, Robson G.

2016-04-01

Application of optimization techniques to the identification of inelastic material parameters has substantially increased in recent years. The complex stress-strain paths and high nonlinearity, typical of this class of problems, require the development of robust and efficient techniques for inverse problems able to account for an irregular topography of the fitness surface. Within this framework, this work investigates the application of the gradient-based Sequential Quadratic Programming method, of the Nelder-Mead downhill simplex algorithm, of Particle Swarm Optimization (PSO), and of a global-local PSO-Nelder-Mead hybrid scheme to the identification of inelastic parameters based on a deep drawing operation. The hybrid technique has shown to be the best strategy by combining the good PSO performance to approach the global minimum basin of attraction with the efficiency demonstrated by the Nelder-Mead algorithm to obtain the minimum itself.

Different Manhattan project: automatic statistical model generation

NASA Astrophysics Data System (ADS)

Yap, Chee Keng; Biermann, Henning; Hertzmann, Aaron; Li, Chen; Meyer, Jon; Pao, Hsing-Kuo; Paxia, Salvatore

2002-03-01

We address the automatic generation of large geometric models. This is important in visualization for several reasons. First, many applications need access to large but interesting data models. Second, we often need such data sets with particular characteristics (e.g., urban models, park and recreation landscape). Thus we need the ability to generate models with different parameters. We propose a new approach for generating such models. It is based on a top-down propagation of statistical parameters. We illustrate the method in the generation of a statistical model of Manhattan. But the method is generally applicable in the generation of models of large geographical regions. Our work is related to the literature on generating complex natural scenes (smoke, forests, etc) based on procedural descriptions. The difference in our approach stems from three characteristics: modeling with statistical parameters, integration of ground truth (actual map data), and a library-based approach for texture mapping.

Development, sensitivity and uncertainty analysis of LASH model

USDA-ARS?s Scientific Manuscript database

Many hydrologic models have been developed to help manage natural resources all over the world. Nevertheless, most models have presented a high complexity regarding data base requirements, as well as, many calibration parameters. This has brought serious difficulties for applying them in watersheds ...

Anticipatory Monitoring and Control of Complex Systems using a Fuzzy based Fusion of Support Vector Regressors

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

Miltiadis Alamaniotis; Vivek Agarwal

This paper places itself in the realm of anticipatory systems and envisions monitoring and control methods being capable of making predictions over system critical parameters. Anticipatory systems allow intelligent control of complex systems by predicting their future state. In the current work, an intelligent model aimed at implementing anticipatory monitoring and control in energy industry is presented and tested. More particularly, a set of support vector regressors (SVRs) are trained using both historical and observed data. The trained SVRs are used to predict the future value of the system based on current operational system parameter. The predicted values are thenmore » inputted to a fuzzy logic based module where the values are fused to obtain a single value, i.e., final system output prediction. The methodology is tested on real turbine degradation datasets. The outcome of the approach presented in this paper highlights the superiority over single support vector regressors. In addition, it is shown that appropriate selection of fuzzy sets and fuzzy rules plays an important role in improving system performance.« less

Complex motion measurement using genetic algorithm

NASA Astrophysics Data System (ADS)

Shen, Jianjun; Tu, Dan; Shen, Zhenkang

1997-12-01

Genetic algorithm (GA) is an optimization technique that provides an untraditional approach to deal with many nonlinear, complicated problems. The notion of motion measurement using genetic algorithm arises from the fact that the motion measurement is virtually an optimization process based on some criterions. In the paper, we propose a complex motion measurement method using genetic algorithm based on block-matching criterion. The following three problems are mainly discussed and solved in the paper: (1) apply an adaptive method to modify the control parameters of GA that are critical to itself, and offer an elitism strategy at the same time (2) derive an evaluate function of motion measurement for GA based on block-matching technique (3) employ hill-climbing (HC) method hybridly to assist GA's search for the global optimal solution. Some other related problems are also discussed. At the end of paper, experiments result is listed. We employ six motion parameters for measurement in our experiments. Experiments result shows that the performance of our GA is good. The GA can find the object motion accurately and rapidly.

Practical image registration concerns overcome by the weighted and filtered mutual information metric

NASA Astrophysics Data System (ADS)

Keane, Tommy P.; Saber, Eli; Rhody, Harvey; Savakis, Andreas; Raj, Jeffrey

2012-04-01

Contemporary research in automated panorama creation utilizes camera calibration or extensive knowledge of camera locations and relations to each other to achieve successful results. Research in image registration attempts to restrict these same camera parameters or apply complex point-matching schemes to overcome the complications found in real-world scenarios. This paper presents a novel automated panorama creation algorithm by developing an affine transformation search based on maximized mutual information (MMI) for region-based registration. Standard MMI techniques have been limited to applications with airborne/satellite imagery or medical images. We show that a novel MMI algorithm can approximate an accurate registration between views of realistic scenes of varying depth distortion. The proposed algorithm has been developed using stationary, color, surveillance video data for a scenario with no a priori camera-to-camera parameters. This algorithm is robust for strict- and nearly-affine-related scenes, while providing a useful approximation for the overlap regions in scenes related by a projective homography or a more complex transformation, allowing for a set of efficient and accurate initial conditions for pixel-based registration.

Lightweight Filter Architecture for Energy Efficient Mobile Vehicle Localization Based on a Distributed Acoustic Sensor Network

PubMed Central

Kim, Keonwook

2013-01-01

The generic properties of an acoustic signal provide numerous benefits for localization by applying energy-based methods over a deployed wireless sensor network (WSN). However, the signal generated by a stationary target utilizes a significant amount of bandwidth and power in the system without providing further position information. For vehicle localization, this paper proposes a novel proximity velocity vector estimator (PVVE) node architecture in order to capture the energy from a moving vehicle and reject the signal from motionless automobiles around the WSN node. A cascade structure between analog envelope detector and digital exponential smoothing filter presents the velocity vector-sensitive output with low analog circuit and digital computation complexity. The optimal parameters in the exponential smoothing filter are obtained by analytical and mathematical methods for maximum variation over the vehicle speed. For stationary targets, the derived simulation based on the acoustic field parameters demonstrates that the system significantly reduces the communication requirements with low complexity and can be expected to extend the operation time considerably. PMID:23979482

Prosthetic avian vocal organ controlled by a freely behaving bird based on a low dimensional model of the biomechanical periphery.

PubMed

Arneodo, Ezequiel M; Perl, Yonatan Sanz; Goller, Franz; Mindlin, Gabriel B

2012-01-01

Because of the parallels found with human language production and acquisition, birdsong is an ideal animal model to study general mechanisms underlying complex, learned motor behavior. The rich and diverse vocalizations of songbirds emerge as a result of the interaction between a pattern generator in the brain and a highly nontrivial nonlinear periphery. Much of the complexity of this vocal behavior has been understood by studying the physics of the avian vocal organ, particularly the syrinx. A mathematical model describing the complex periphery as a nonlinear dynamical system leads to the conclusion that nontrivial behavior emerges even when the organ is commanded by simple motor instructions: smooth paths in a low dimensional parameter space. An analysis of the model provides insight into which parameters are responsible for generating a rich variety of diverse vocalizations, and what the physiological meaning of these parameters is. By recording the physiological motor instructions elicited by a spontaneously singing muted bird and computing the model on a Digital Signal Processor in real-time, we produce realistic synthetic vocalizations that replace the bird's own auditory feedback. In this way, we build a bio-prosthetic avian vocal organ driven by a freely behaving bird via its physiologically coded motor commands. Since it is based on a low-dimensional nonlinear mathematical model of the peripheral effector, the emulation of the motor behavior requires light computation, in such a way that our bio-prosthetic device can be implemented on a portable platform.

The Hydrothermal Chemistry of Gold, Arsenic, Antimony, Mercury and Silver

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

Bessinger, Brad; Apps, John A.

2003-03-23

A comprehensive thermodynamic database based on the Helgeson-Kirkham-Flowers (HKF) equation of state was developed for metal complexes in hydrothermal systems. Because this equation of state has been shown to accurately predict standard partial molal thermodynamic properties of aqueous species at elevated temperatures and pressures, this study provides the necessary foundation for future exploration into transport and depositional processes in polymetallic ore deposits. The HKF equation of state parameters for gold, arsenic, antimony, mercury, and silver sulfide and hydroxide complexes were derived from experimental equilibrium constants using nonlinear regression calculations. In order to ensure that the resulting parameters were internally consistent,more » those experiments utilizing incompatible thermodynamic data were re-speciated prior to regression. Because new experimental studies were used to revise the HKF parameters for H2S0 and HS-1, those metal complexes for which HKF parameters had been previously derived were also updated. It was found that predicted thermodynamic properties of metal complexes are consistent with linear correlations between standard partial molal thermodynamic properties. This result allowed assessment of several complexes for which experimental data necessary to perform regression calculations was limited. Oxygen fugacity-temperature diagrams were calculated to illustrate how thermodynamic data improves our understanding of depositional processes. Predicted thermodynamic properties were used to investigate metal transport in Carlin-type gold deposits. Assuming a linear relationship between temperature and pressure, metals are predicted to predominantly be transported as sulfide complexes at a total aqueous sulfur concentration of 0.05 m. Also, the presence of arsenic and antimony mineral phases in the deposits are shown to restrict mineralization within a limited range of chemical conditions. Finally, at a lesser aqueous sulfur concentration of 0.01 m, host rock sulfidation can explain the origin of arsenic and antimony minerals within the paragenetic sequence.« less

Molecular dynamics study of some non-hydrogen-bonding base pair DNA strands

NASA Astrophysics Data System (ADS)

Tiwari, Rakesh K.; Ojha, Rajendra P.; Tiwari, Gargi; Pandey, Vishnudatt; Mall, Vijaysree

2018-05-01

In order to elucidate the structural activity of hydrophobic modified DNA, the DMMO2-D5SICS, base pair is introduced as a constituent in different set of 12-mer and 14-mer DNA sequences for the molecular dynamics (MD) simulation in explicit water solvent. AMBER 14 force field was employed for each set of duplex during the 200ns production-dynamics simulation in orthogonal-box-water solvent by the Particle-Mesh-Ewald (PME) method in infinite periodic boundary conditions (PBC) to determine conformational parameters of the complex. The force-field parameters of modified base-pair were calculated by Gaussian-code using Hartree-Fock /ab-initio methodology. RMSD Results reveal that the conformation of the duplex is sequence dependent and the binding energy of the complex depends on the position of the modified base-pair in the nucleic acid strand. We found that non-bonding energy had a significant contribution to stabilising such type of duplex in comparison to electrostatic energy. The distortion produced within strands by such type of base-pair was local and destabilised the duplex integrity near to substitution, moreover the binding energy of duplex depends on the position of substitution of hydrophobic base-pair and the DNA sequence and strongly supports the corresponding experimental study.

Automatic physical inference with information maximizing neural networks

NASA Astrophysics Data System (ADS)

Charnock, Tom; Lavaux, Guilhem; Wandelt, Benjamin D.

2018-04-01

Compressing large data sets to a manageable number of summaries that are informative about the underlying parameters vastly simplifies both frequentist and Bayesian inference. When only simulations are available, these summaries are typically chosen heuristically, so they may inadvertently miss important information. We introduce a simulation-based machine learning technique that trains artificial neural networks to find nonlinear functionals of data that maximize Fisher information: information maximizing neural networks (IMNNs). In test cases where the posterior can be derived exactly, likelihood-free inference based on automatically derived IMNN summaries produces nearly exact posteriors, showing that these summaries are good approximations to sufficient statistics. In a series of numerical examples of increasing complexity and astrophysical relevance we show that IMNNs are robustly capable of automatically finding optimal, nonlinear summaries of the data even in cases where linear compression fails: inferring the variance of Gaussian signal in the presence of noise, inferring cosmological parameters from mock simulations of the Lyman-α forest in quasar spectra, and inferring frequency-domain parameters from LISA-like detections of gravitational waveforms. In this final case, the IMNN summary outperforms linear data compression by avoiding the introduction of spurious likelihood maxima. We anticipate that the automatic physical inference method described in this paper will be essential to obtain both accurate and precise cosmological parameter estimates from complex and large astronomical data sets, including those from LSST and Euclid.

Evolution of Geometric Sensitivity Derivatives from Computer Aided Design Models

NASA Technical Reports Server (NTRS)

Jones, William T.; Lazzara, David; Haimes, Robert

2010-01-01

The generation of design parameter sensitivity derivatives is required for gradient-based optimization. Such sensitivity derivatives are elusive at best when working with geometry defined within the solid modeling context of Computer-Aided Design (CAD) systems. Solid modeling CAD systems are often proprietary and always complex, thereby necessitating ad hoc procedures to infer parameter sensitivity. A new perspective is presented that makes direct use of the hierarchical associativity of CAD features to trace their evolution and thereby track design parameter sensitivity. In contrast to ad hoc methods, this method provides a more concise procedure following the model design intent and determining the sensitivity of CAD geometry directly to its respective defining parameters.

Efficient generalized cross-validation with applications to parametric image restoration and resolution enhancement.

PubMed

Nguyen, N; Milanfar, P; Golub, G

2001-01-01

In many image restoration/resolution enhancement applications, the blurring process, i.e., point spread function (PSF) of the imaging system, is not known or is known only to within a set of parameters. We estimate these PSF parameters for this ill-posed class of inverse problem from raw data, along with the regularization parameters required to stabilize the solution, using the generalized cross-validation method (GCV). We propose efficient approximation techniques based on the Lanczos algorithm and Gauss quadrature theory, reducing the computational complexity of the GCV. Data-driven PSF and regularization parameter estimation experiments with synthetic and real image sequences are presented to demonstrate the effectiveness and robustness of our method.

Improvement of economic security management system of municipalities with account of transportation system development: methods of assessment

NASA Astrophysics Data System (ADS)

Khe Sun, Pak; Vorona-Slivinskaya, Lubov; Voskresenskay, Elena

2017-10-01

The article highlights the necessity of a complex approach to assess economic security of municipalities, which would consider municipal management specifics. The approach allows comparing the economic security level of municipalities, but it does not describe parameter differences between compared municipalities. Therefore, there is a second method suggested: parameter rank order method. Applying these methods allowed to figure out the leaders and outsiders of the economic security among municipalities and rank all economic security parameters according to the significance level. Complex assessment of the economic security of municipalities, based on the combination of the two approaches, allowed to assess the security level more accurate. In order to assure economic security and equalize its threshold values, one should pay special attention to transportation system development in municipalities. Strategic aims of projects in the area of transportation infrastructure development in municipalities include the following issues: contribution into creating and elaborating transportation logistics and manufacture transport complexes, development of transportation infrastructure with account of internal and external functions of the region, public transport development, improvement of transport security and reducing its negative influence on the environment.

Fuzzy logic modeling of the resistivity parameter and topography features for aquifer assessment in hydrogeological investigation of a crystalline basement complex

NASA Astrophysics Data System (ADS)

Adabanija, M. A.; Omidiora, E. O.; Olayinka, A. I.

2008-05-01

A linguistic fuzzy logic system (LFLS)-based expert system model has been developed for the assessment of aquifers for the location of productive water boreholes in a crystalline basement complex. The model design employed a multiple input/single output (MISO) approach with geoelectrical parameters and topographic features as input variables and control crisp value as the output. The application of the method to the data acquired in Khondalitic terrain, a basement complex in Vizianagaram District, south India, shows that potential groundwater resource zones that have control output values in the range 0.3295-0.3484 have a yield greater than 6,000 liters per hour (LPH). The range 0.3174-0.3226 gives a yield less than 4,000 LPH. The validation of the control crisp value using data acquired from Oban Massif, a basement complex in southeastern Nigeria, indicates a yield less than 3,000 LPH for control output values in the range 0.2938-0.3065. This validation corroborates the ability of control output values to predict a yield, thereby vindicating the applicability of linguistic fuzzy logic system in siting productive water boreholes in a basement complex.

A comprehensive approach to identify dominant controls of the behavior of a land surface-hydrology model across various hydroclimatic conditions

NASA Astrophysics Data System (ADS)

Haghnegahdar, Amin; Elshamy, Mohamed; Yassin, Fuad; Razavi, Saman; Wheater, Howard; Pietroniro, Al

2017-04-01

Complex physically-based environmental models are being increasingly used as the primary tool for watershed planning and management due to advances in computation power and data acquisition. Model sensitivity analysis plays a crucial role in understanding the behavior of these complex models and improving their performance. Due to the non-linearity and interactions within these complex models, Global sensitivity analysis (GSA) techniques should be adopted to provide a comprehensive understanding of model behavior and identify its dominant controls. In this study we adopt a multi-basin multi-criteria GSA approach to systematically assess the behavior of the Modélisation Environmentale-Surface et Hydrologie (MESH) across various hydroclimatic conditions in Canada including areas in the Great Lakes Basin, Mackenzie River Basin, and South Saskatchewan River Basin. MESH is a semi-distributed physically-based coupled land surface-hydrology modelling system developed by Environment and Climate Change Canada (ECCC) for various water resources management purposes in Canada. We use a novel method, called Variogram Analysis of Response Surfaces (VARS), to perform sensitivity analysis. VARS is a variogram-based GSA technique that can efficiently provide a spectrum of sensitivity information across a range of scales within the parameter space. We use multiple metrics to identify dominant controls of model response (e.g. streamflow) to model parameters under various conditions such as high flows, low flows, and flow volume. We also investigate the influence of initial conditions on model behavior as part of this study. Our preliminary results suggest that this type of GSA can significantly help with estimating model parameters, decreasing calibration computational burden, and reducing prediction uncertainty.

Large-Scale Optimization for Bayesian Inference in Complex Systems

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

Willcox, Karen; Marzouk, Youssef

2013-11-12

The SAGUARO (Scalable Algorithms for Groundwater Uncertainty Analysis and Robust Optimization) Project focused on the development of scalable numerical algorithms for large-scale Bayesian inversion in complex systems that capitalize on advances in large-scale simulation-based optimization and inversion methods. The project was a collaborative effort among MIT, the University of Texas at Austin, Georgia Institute of Technology, and Sandia National Laboratories. The research was directed in three complementary areas: efficient approximations of the Hessian operator, reductions in complexity of forward simulations via stochastic spectral approximations and model reduction, and employing large-scale optimization concepts to accelerate sampling. The MIT--Sandia component of themore » SAGUARO Project addressed the intractability of conventional sampling methods for large-scale statistical inverse problems by devising reduced-order models that are faithful to the full-order model over a wide range of parameter values; sampling then employs the reduced model rather than the full model, resulting in very large computational savings. Results indicate little effect on the computed posterior distribution. On the other hand, in the Texas--Georgia Tech component of the project, we retain the full-order model, but exploit inverse problem structure (adjoint-based gradients and partial Hessian information of the parameter-to-observation map) to implicitly extract lower dimensional information on the posterior distribution; this greatly speeds up sampling methods, so that fewer sampling points are needed. We can think of these two approaches as ``reduce then sample'' and ``sample then reduce.'' In fact, these two approaches are complementary, and can be used in conjunction with each other. Moreover, they both exploit deterministic inverse problem structure, in the form of adjoint-based gradient and Hessian information of the underlying parameter-to-observation map, to achieve their speedups.« less

Final Report: Large-Scale Optimization for Bayesian Inference in Complex Systems

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

Ghattas, Omar

2013-10-15

The SAGUARO (Scalable Algorithms for Groundwater Uncertainty Analysis and Robust Optimiza- tion) Project focuses on the development of scalable numerical algorithms for large-scale Bayesian inversion in complex systems that capitalize on advances in large-scale simulation-based optimiza- tion and inversion methods. Our research is directed in three complementary areas: efficient approximations of the Hessian operator, reductions in complexity of forward simulations via stochastic spectral approximations and model reduction, and employing large-scale optimization concepts to accelerate sampling. Our efforts are integrated in the context of a challenging testbed problem that considers subsurface reacting flow and transport. The MIT component of the SAGUAROmore » Project addresses the intractability of conventional sampling methods for large-scale statistical inverse problems by devising reduced-order models that are faithful to the full-order model over a wide range of parameter values; sampling then employs the reduced model rather than the full model, resulting in very large computational savings. Results indicate little effect on the computed posterior distribution. On the other hand, in the Texas-Georgia Tech component of the project, we retain the full-order model, but exploit inverse problem structure (adjoint-based gradients and partial Hessian information of the parameter-to- observation map) to implicitly extract lower dimensional information on the posterior distribution; this greatly speeds up sampling methods, so that fewer sampling points are needed. We can think of these two approaches as "reduce then sample" and "sample then reduce." In fact, these two approaches are complementary, and can be used in conjunction with each other. Moreover, they both exploit deterministic inverse problem structure, in the form of adjoint-based gradient and Hessian information of the underlying parameter-to-observation map, to achieve their speedups.« less

Data and Model Uncertainties associated with Biogeochemical Groundwater Remediation and their impact on Decision Analysis

NASA Astrophysics Data System (ADS)

Pandey, S.; Vesselinov, V. V.; O'Malley, D.; Karra, S.; Hansen, S. K.

2016-12-01

Models and data are used to characterize the extent of contamination and remediation, both of which are dependent upon the complex interplay of processes ranging from geochemical reactions, microbial metabolism, and pore-scale mixing to heterogeneous flow and external forcings. Characterization is wrought with important uncertainties related to the model itself (e.g. conceptualization, model implementation, parameter values) and the data used for model calibration (e.g. sparsity, measurement errors). This research consists of two primary components: (1) Developing numerical models that incorporate the complex hydrogeology and biogeochemistry that drive groundwater contamination and remediation; (2) Utilizing novel techniques for data/model-based analyses (such as parameter calibration and uncertainty quantification) to aid in decision support for optimal uncertainty reduction related to characterization and remediation of contaminated sites. The reactive transport models are developed using PFLOTRAN and are capable of simulating a wide range of biogeochemical and hydrologic conditions that affect the migration and remediation of groundwater contaminants under diverse field conditions. Data/model-based analyses are achieved using MADS, which utilizes Bayesian methods and Information Gap theory to address the data/model uncertainties discussed above. We also use these tools to evaluate different models, which vary in complexity, in order to weigh and rank models based on model accuracy (in representation of existing observations), model parsimony (everything else being equal, models with smaller number of model parameters are preferred), and model robustness (related to model predictions of unknown future states). These analyses are carried out on synthetic problems, but are directly related to real-world problems; for example, the modeled processes and data inputs are consistent with the conditions at the Los Alamos National Laboratory contamination sites (RDX and Chromium).

New insights into the mechanism of interaction between CO2 and polymers from thermodynamic parameters obtained by in situ ATR-FTIR spectroscopy.

PubMed

Gabrienko, Anton A; Ewing, Andrew V; Chibiryaev, Andrey M; Agafontsev, Alexander M; Dubkov, Konstantin A; Kazarian, Sergei G

2016-03-07

This work reports new physical insights of the thermodynamic parameters and mechanisms of possible interactions occurring in polymers subjected to high-pressure CO2. ATR-FTIR spectroscopy has been used in situ to determine the thermodynamic parameters of the intermolecular interactions between CO2 and different functional groups of the polymers capable of specific interactions with sorbed CO2 molecules. Based on the measured ATR-FTIR spectra of the polymer samples subjected to high-pressure CO2 (30 bar) at different temperatures (300-340 K), it was possible to characterize polymer-polymer and CO2-polymer interactions. Particularly, the enthalpy and entropy of the formation of the specific non-covalent complexes between CO2 and the hydroxy (-OH), carbonyl (C[double bond, length as m-dash]O) and hydroxyimino ([double bond, length as m-dash]N-OH) functional groups of the polymer samples have been measured. Furthermore, the obtained spectroscopic results have provided an opportunity for the structure of these complexes to be proposed. An interesting phenomenon regarding the behavior of CO2/polymer systems has also been observed. It has been found that only for the polyketone, the value of enthalpy was negative indicating an exothermic process during the formation of the CO2-polymer non-covalent complexes. Conversely, for the polyoxime and polyalcohol samples there is a positive enthalpy determined. This is a result of the initial polymer-polymer interactions requiring more energy to break than is released during the formation of the CO2-polymer complex. The effect of increasing temperature to facilitate the breaking of the polymer-polymer interactions has also been observed. Hence, a mechanism for the formation of CO2-polymer complexes was suggested based on these results, which occurs via a two-step process: (1) the breaking of the existing polymer-polymer interactions followed by (2) the formation of new CO2-polymer non-covalent interactions.

Model development and validation of geometrically complex eddy current coils using finite element methods

NASA Astrophysics Data System (ADS)

Brown, Alexander; Eviston, Connor

2017-02-01

Multiple FEM models of complex eddy current coil geometries were created and validated to calculate the change of impedance due to the presence of a notch. Capable realistic simulations of eddy current inspections are required for model assisted probability of detection (MAPOD) studies, inversion algorithms, experimental verification, and tailored probe design for NDE applications. An FEM solver was chosen to model complex real world situations including varying probe dimensions and orientations along with complex probe geometries. This will also enable creation of a probe model library database with variable parameters. Verification and validation was performed using other commercially available eddy current modeling software as well as experimentally collected benchmark data. Data analysis and comparison showed that the created models were able to correctly model the probe and conductor interactions and accurately calculate the change in impedance of several experimental scenarios with acceptable error. The promising results of the models enabled the start of an eddy current probe model library to give experimenters easy access to powerful parameter based eddy current models for alternate project applications.

Improving Generalization Based on l1-Norm Regularization for EEG-Based Motor Imagery Classification

PubMed Central

Zhao, Yuwei; Han, Jiuqi; Chen, Yushu; Sun, Hongji; Chen, Jiayun; Ke, Ang; Han, Yao; Zhang, Peng; Zhang, Yi; Zhou, Jin; Wang, Changyong

2018-01-01

Multichannel electroencephalography (EEG) is widely used in typical brain-computer interface (BCI) systems. In general, a number of parameters are essential for a EEG classification algorithm due to redundant features involved in EEG signals. However, the generalization of the EEG method is often adversely affected by the model complexity, considerably coherent with its number of undetermined parameters, further leading to heavy overfitting. To decrease the complexity and improve the generalization of EEG method, we present a novel l1-norm-based approach to combine the decision value obtained from each EEG channel directly. By extracting the information from different channels on independent frequency bands (FB) with l1-norm regularization, the method proposed fits the training data with much less parameters compared to common spatial pattern (CSP) methods in order to reduce overfitting. Moreover, an effective and efficient solution to minimize the optimization object is proposed. The experimental results on dataset IVa of BCI competition III and dataset I of BCI competition IV show that, the proposed method contributes to high classification accuracy and increases generalization performance for the classification of MI EEG. As the training set ratio decreases from 80 to 20%, the average classification accuracy on the two datasets changes from 85.86 and 86.13% to 84.81 and 76.59%, respectively. The classification performance and generalization of the proposed method contribute to the practical application of MI based BCI systems. PMID:29867307

Adaptive control for a class of nonlinear complex dynamical systems with uncertain complex parameters and perturbations

PubMed Central

Liu, Jian; Liu, Kexin; Liu, Shutang

2017-01-01

In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic) systems (CVCSs) in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results. PMID:28467431

Adaptive control for a class of nonlinear complex dynamical systems with uncertain complex parameters and perturbations.

PubMed

Liu, Jian; Liu, Kexin; Liu, Shutang

2017-01-01

In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic) systems (CVCSs) in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results.

Using evolutionary algorithms for fitting high-dimensional models to neuronal data.

PubMed

Svensson, Carl-Magnus; Coombes, Stephen; Peirce, Jonathan Westley

2012-04-01

In the study of neurosciences, and of complex biological systems in general, there is frequently a need to fit mathematical models with large numbers of parameters to highly complex datasets. Here we consider algorithms of two different classes, gradient following (GF) methods and evolutionary algorithms (EA) and examine their performance in fitting a 9-parameter model of a filter-based visual neuron to real data recorded from a sample of 107 neurons in macaque primary visual cortex (V1). Although the GF method converged very rapidly on a solution, it was highly susceptible to the effects of local minima in the error surface and produced relatively poor fits unless the initial estimates of the parameters were already very good. Conversely, although the EA required many more iterations of evaluating the model neuron's response to a series of stimuli, it ultimately found better solutions in nearly all cases and its performance was independent of the starting parameters of the model. Thus, although the fitting process was lengthy in terms of processing time, the relative lack of human intervention in the evolutionary algorithm, and its ability ultimately to generate model fits that could be trusted as being close to optimal, made it far superior in this particular application than the gradient following methods. This is likely to be the case in many further complex systems, as are often found in neuroscience.

Stability of uncertain impulsive complex-variable chaotic systems with time-varying delays.

PubMed

Zheng, Song

2015-09-01

In this paper, the robust exponential stabilization of uncertain impulsive complex-variable chaotic delayed systems is considered with parameters perturbation and delayed impulses. It is assumed that the considered complex-variable chaotic systems have bounded parametric uncertainties together with the state variables on the impulses related to the time-varying delays. Based on the theories of adaptive control and impulsive control, some less conservative and easily verified stability criteria are established for a class of complex-variable chaotic delayed systems with delayed impulses. Some numerical simulations are given to validate the effectiveness of the proposed criteria of impulsive stabilization for uncertain complex-variable chaotic delayed systems. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Structural and magnetic characterization of a tetranuclear copper(II) cubane stabilized by intramolecular metal cation-π interactions.

PubMed

Papadakis, Raffaello; Rivière, Eric; Giorgi, Michel; Jamet, Hélène; Rousselot-Pailley, Pierre; Réglier, Marius; Simaan, A Jalila; Tron, Thierry

2013-05-20

A novel tetranuclear copper(II) complex (1) was synthesized from the self-assembly of copper(II) perchlorate and the ligand N-benzyl-1-(2-pyridyl)methaneimine (L(1)). Single-crystal X-ray diffraction studies revealed that complex 1 consists of a Cu4(OH)4 cubane core, where the four copper(II) centers are linked by μ3-hydroxo bridges. Each copper(II) ion is in a distorted square-pyramidal geometry. X-ray analysis also evidenced an unusual metal cation-π interaction between the copper ions and phenyl substituents of the ligand. Calculations based on the density functional theory method were used to quantify the strength of this metal-π interaction, which appears as an important stabilizing parameter of the cubane core, possibly acting as a driving parameter in the self-aggregation process. In contrast, using the ligand N-phenethyl-1-(2-pyridyl)methaneimine (L(2)), which only differs from L(1) by one methylene group, the same synthetic procedure led to a binuclear bis(μ-hydroxo)copper(II) complex (2) displaying intermolecular π-π interactions or, by a slight variation of the experimental conditions, to a mononuclear complex (3). These complexes were studied by X-ray diffraction techniques. The magnetic properties of complexes 1 and 2 are reported and discussed.

A new approach to interpretation of heterogeneity of fluorescence decay in complex biological systems

NASA Astrophysics Data System (ADS)

Wlodarczyk, Jakub; Kierdaszuk, Borys

2005-08-01

Decays of tyrosine fluorescence in protein-ligand complexes are described by a model of continuous distribution of fluorescence lifetimes. Resulted analytical power-like decay function provides good fits to highly complex fluorescence kinetics. Moreover, this is a manifestation of so-called Tsallis q-exponential function, which is suitable for description of the systems with long-range interactions, memory effect, as well as with fluctuations of the characteristic lifetime of fluorescence. The proposed decay functions were applied to analysis of fluorescence decays of tyrosine in a protein, i.e. the enzyme purine nucleoside phosphorylase from E. coli (the product of the deoD gene), free in aqueous solution and in a complex with formycin A (an inhibitor) and orthophosphate (a co-substrate). The power-like function provides new information about enzyme-ligand complex formation based on the physically justified heterogeneity parameter directly related to the lifetime distribution. A measure of the heterogeneity parameter in the enzyme systems is provided by a variance of fluorescence lifetime distribution. The possible number of deactivation channels and excited state mean lifetime can be easily derived without a priori knowledge of the complexity of studied system. Moreover, proposed model is simpler then traditional multi-exponential one, and better describes heterogeneous nature of studied systems.

Conditional Probabilities of Large Earthquake Sequences in California from the Physics-based Rupture Simulator RSQSim

NASA Astrophysics Data System (ADS)

Gilchrist, J. J.; Jordan, T. H.; Shaw, B. E.; Milner, K. R.; Richards-Dinger, K. B.; Dieterich, J. H.

2017-12-01

Within the SCEC Collaboratory for Interseismic Simulation and Modeling (CISM), we are developing physics-based forecasting models for earthquake ruptures in California. We employ the 3D boundary element code RSQSim (Rate-State Earthquake Simulator of Dieterich & Richards-Dinger, 2010) to generate synthetic catalogs with tens of millions of events that span up to a million years each. This code models rupture nucleation by rate- and state-dependent friction and Coulomb stress transfer in complex, fully interacting fault systems. The Uniform California Earthquake Rupture Forecast Version 3 (UCERF3) fault and deformation models are used to specify the fault geometry and long-term slip rates. We have employed the Blue Waters supercomputer to generate long catalogs of simulated California seismicity from which we calculate the forecasting statistics for large events. We have performed probabilistic seismic hazard analysis with RSQSim catalogs that were calibrated with system-wide parameters and found a remarkably good agreement with UCERF3 (Milner et al., this meeting). We build on this analysis, comparing the conditional probabilities of sequences of large events from RSQSim and UCERF3. In making these comparisons, we consider the epistemic uncertainties associated with the RSQSim parameters (e.g., rate- and state-frictional parameters), as well as the effects of model-tuning (e.g., adjusting the RSQSim parameters to match UCERF3 recurrence rates). The comparisons illustrate how physics-based rupture simulators might assist forecasters in understanding the short-term hazards of large aftershocks and multi-event sequences associated with complex, multi-fault ruptures.

A framework for conducting mechanistic based reliability assessments of components operating in complex systems

NASA Astrophysics Data System (ADS)

Wallace, Jon Michael

2003-10-01

Reliability prediction of components operating in complex systems has historically been conducted in a statistically isolated manner. Current physics-based, i.e. mechanistic, component reliability approaches focus more on component-specific attributes and mathematical algorithms and not enough on the influence of the system. The result is that significant error can be introduced into the component reliability assessment process. The objective of this study is the development of a framework that infuses the needs and influence of the system into the process of conducting mechanistic-based component reliability assessments. The formulated framework consists of six primary steps. The first three steps, identification, decomposition, and synthesis, are primarily qualitative in nature and employ system reliability and safety engineering principles to construct an appropriate starting point for the component reliability assessment. The following two steps are the most unique. They involve a step to efficiently characterize and quantify the system-driven local parameter space and a subsequent step using this information to guide the reduction of the component parameter space. The local statistical space quantification step is accomplished using two proposed multivariate probability models: Multi-Response First Order Second Moment and Taylor-Based Inverse Transformation. Where existing joint probability models require preliminary distribution and correlation information of the responses, these models combine statistical information of the input parameters with an efficient sampling of the response analyses to produce the multi-response joint probability distribution. Parameter space reduction is accomplished using Approximate Canonical Correlation Analysis (ACCA) employed as a multi-response screening technique. The novelty of this approach is that each individual local parameter and even subsets of parameters representing entire contributing analyses can now be rank ordered with respect to their contribution to not just one response, but the entire vector of component responses simultaneously. The final step of the framework is the actual probabilistic assessment of the component. Although the same multivariate probability tools employed in the characterization step can be used for the component probability assessment, variations of this final step are given to allow for the utilization of existing probabilistic methods such as response surface Monte Carlo and Fast Probability Integration. The overall framework developed in this study is implemented to assess the finite-element based reliability prediction of a gas turbine airfoil involving several failure responses. Results of this implementation are compared to results generated using the conventional 'isolated' approach as well as a validation approach conducted through large sample Monte Carlo simulations. The framework resulted in a considerable improvement to the accuracy of the part reliability assessment and an improved understanding of the component failure behavior. Considerable statistical complexity in the form of joint non-normal behavior was found and accounted for using the framework. Future applications of the framework elements are discussed.

A NIST Kinetic Data Base for PAH Reaction and Soot Particle Inception During Combusion

DTIC Science & Technology

2007-12-01

in Computational Fluid Dynamics (CFD) codes hat have lead to the capability of describing complex reactive flow problems and thus simulating... parameters . However in the absence of data estimates must be made. Since the chemistry of combustion is extremely complex and for proper description...118:381-389 9. Babushok, V. and Tsang, W., J. Prop. and Pwr . 20 (2004) 403-414. 10. . Fournet, R., Warth, V., Glaude, P.A., Battin-Leclerc, F

An Additive Definition of Molecular Complexity.

PubMed

Böttcher, Thomas

2016-03-28

A framework for molecular complexity is established that is based on information theory and consistent with chemical knowledge. The resulting complexity index Cm is derived from abstracting the information content of a molecule by the degrees of freedom in the microenvironments on a per-atom basis, allowing the molecular complexity to be calculated in a simple and additive way. This index allows the complexity of any molecule to be universally assessed and is sensitive to stereochemistry, heteroatoms, and symmetry. The performance of this complexity index is evaluated and compared against the current state of the art. Its additive character gives consistent values also for very large molecules and supports direct comparisons of chemical reactions. Finally, this approach may provide a useful tool for medicinal chemistry in drug design and lead selection, as demonstrated by correlating molecular complexities of antibiotics with compound-specific parameters.

Insight into model mechanisms through automatic parameter fitting: a new methodological framework for model development

PubMed Central

2014-01-01

Background Striking a balance between the degree of model complexity and parameter identifiability, while still producing biologically feasible simulations using modelling is a major challenge in computational biology. While these two elements of model development are closely coupled, parameter fitting from measured data and analysis of model mechanisms have traditionally been performed separately and sequentially. This process produces potential mismatches between model and data complexities that can compromise the ability of computational frameworks to reveal mechanistic insights or predict new behaviour. In this study we address this issue by presenting a generic framework for combined model parameterisation, comparison of model alternatives and analysis of model mechanisms. Results The presented methodology is based on a combination of multivariate metamodelling (statistical approximation of the input–output relationships of deterministic models) and a systematic zooming into biologically feasible regions of the parameter space by iterative generation of new experimental designs and look-up of simulations in the proximity of the measured data. The parameter fitting pipeline includes an implicit sensitivity analysis and analysis of parameter identifiability, making it suitable for testing hypotheses for model reduction. Using this approach, under-constrained model parameters, as well as the coupling between parameters within the model are identified. The methodology is demonstrated by refitting the parameters of a published model of cardiac cellular mechanics using a combination of measured data and synthetic data from an alternative model of the same system. Using this approach, reduced models with simplified expressions for the tropomyosin/crossbridge kinetics were found by identification of model components that can be omitted without affecting the fit to the parameterising data. Our analysis revealed that model parameters could be constrained to a standard deviation of on average 15% of the mean values over the succeeding parameter sets. Conclusions Our results indicate that the presented approach is effective for comparing model alternatives and reducing models to the minimum complexity replicating measured data. We therefore believe that this approach has significant potential for reparameterising existing frameworks, for identification of redundant model components of large biophysical models and to increase their predictive capacity. PMID:24886522

Characterization of complex systems using the design of experiments approach: transient protein expression in tobacco as a case study.

PubMed

Buyel, Johannes Felix; Fischer, Rainer

2014-01-31

Plants provide multiple benefits for the production of biopharmaceuticals including low costs, scalability, and safety. Transient expression offers the additional advantage of short development and production times, but expression levels can vary significantly between batches thus giving rise to regulatory concerns in the context of good manufacturing practice. We used a design of experiments (DoE) approach to determine the impact of major factors such as regulatory elements in the expression construct, plant growth and development parameters, and the incubation conditions during expression, on the variability of expression between batches. We tested plants expressing a model anti-HIV monoclonal antibody (2G12) and a fluorescent marker protein (DsRed). We discuss the rationale for selecting certain properties of the model and identify its potential limitations. The general approach can easily be transferred to other problems because the principles of the model are broadly applicable: knowledge-based parameter selection, complexity reduction by splitting the initial problem into smaller modules, software-guided setup of optimal experiment combinations and step-wise design augmentation. Therefore, the methodology is not only useful for characterizing protein expression in plants but also for the investigation of other complex systems lacking a mechanistic description. The predictive equations describing the interconnectivity between parameters can be used to establish mechanistic models for other complex systems.

Synthesis and spectral characterization of mono- and binuclear copper(II) complexes derived from 2-benzoylpyridine-N4-methyl-3-thiosemicarbazone: Crystal structure of a novel sulfur bridged copper(II) box-dimer

NASA Astrophysics Data System (ADS)

Jayakumar, K.; Sithambaresan, M.; Aiswarya, N.; Kurup, M. R. Prathapachandra

2015-03-01

Mononuclear and binuclear copper(II) complexes of 2-benzoylpyridine-N4-methyl thiosemicarbazone (HL) were prepared and characterized by a variety of spectroscopic techniques. Structural evidence for the novel sulfur bridged copper(II) iodo binuclear complex is obtained by single crystal X-ray diffraction analysis. The complex [Cu2L2I2], a non-centrosymmetric box dimer, crystallizes in monoclinic C2/c space group and it was found to have distorted square pyramidal geometry (Addison parameter, τ = 0.238) with the square basal plane occupied by the thiosemicarbazone moiety and iodine atom whereas the sulfur atom from the other coordinated thiosemicarbazone moiety occupies the apical position. This is the first crystallographically studied system having non-centrosymmetrical entities bridged via thiolate S atoms with Cu(II)sbnd I bond. The tridentate thiosemicarbazone coordinates in mono deprotonated thionic tautomeric form in all complexes except in sulfato complex, [Cu(HL)(SO4)]·H2O (1) where it binds to the metal centre in neutral form. The magnetic moment values and the EPR spectral studies reflect the binuclearity of some of the complexes. The spin Hamiltonian and bonding parameters are calculated based on EPR studies. In all the complexes g|| > g⊥ > 2.0023 and the g values in frozen DMF are consistent with the dx2-y2 ground state. The thermal stabilities of some of the complexes were also determined.

Numerical Investigations of Interactions between the Knee-Thigh-Hip Complex with Vehicle Interior Structures.

PubMed

Kim, Yong Sun; Choi, Hyeong Ho; Cho, Young Nam; Park, Yong Jae; Lee, Jong B; Yang, King H; King, Albert I

2005-11-01

Although biomechanical studies on the knee-thigh-hip (KTH) complex have been extensive, interactions between the KTH and various vehicular interior design parameters in frontal automotive crashes for newer models have not been reported in the open literature to the best of our knowledge. A 3D finite element (FE) model of a 50(th) percentile male KTH complex, which includes explicit representations of the iliac wing, acetabulum, pubic rami, sacrum, articular cartilage, femoral head, femoral neck, femoral condyles, patella, and patella tendon, has been developed to simulate injuries such as fracture of the patella, femoral neck, acetabulum, and pubic rami of the KTH complex. Model results compared favorably against regional component test data including a three-point bending test of the femur, axial loading of the isolated knee-patella, axial loading of the KTH complex, axial loading of the femoral head, and lateral loading of the isolated pelvis. The model was further integrated into a Wayne State University upper torso model and validated against data obtained from whole body sled tests. The model was validated against these experimental data over a range of impact speeds, impactor masses and boundary conditions. Using Design Of Experiment (DOE) methods based on Taguchi's approach and the developed FE model of the whole body, including the KTH complex, eight vehicular interior design parameters, namely the load limiter force, seat belt elongation, pretensioner inlet amount, knee-knee bolster distance, knee bolster angle, knee bolster stiffness, toe board angle and impact speed, each with either two or three design levels, were simulated to predict their respective effects on the potential of KTH injury in frontal impacts. Simulation results proposed best design levels for vehicular interior design parameters to reduce the injury potential of the KTH complex due to frontal automotive crashes. This study is limited by the fact that prediction of bony fracture was based on an element elimination method available in the LS-DYNA code. No validation study was conducted to determine if this method is suitable when simulating fractures of biological tissues. More work is still needed to further validate the FE model of the KTH complex to increase its reliability in the assessment of various impact loading conditions associated with vehicular crash scenarios.

Anticipatory control: A software retrofit for current plant controllers

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

Parthasarathy, S.; Parlos, A.G.; Atiya, A.F.

1993-01-01

The design and simulated testing of an artificial neural network (ANN)-based self-adapting controller for complex process systems are presented in this paper. The proposed controller employs concepts based on anticipatory systems, which have been widely used in the petroleum and chemical industries, and they are slowly finding their way into the power industry. In particular, model predictive control (MPC) is used for the systematic adaptation of the controller parameters to achieve desirable plant performance over the entire operating envelope. The versatile anticipatory control algorithm developed in this study is projected to enhance plant performance and lend robustness to drifts inmore » plant parameters and to modeling uncertainties. This novel technique of integrating recurrent ANNs with a conventional controller structure appears capable of controlling complex, nonlinear, and nonminimum phase process systems. The direct, on-line adaptive control algorithm presented in this paper considers the plant response over a finite time horizon, diminishing the need for manual control or process interruption for controller gain tuning.« less

Complexes of oligo(poly)nucleotides with structural anomalies

NASA Astrophysics Data System (ADS)

Dolinnaya, N. G.; Gryaznova, O. I.

1989-08-01

The results of studies on the structure and properties of DNA-RNA hybrids and complexes of oligo(poly)nucleotides containing non-canonical base pairs or unpaired bases both within and at the ends of the double helix are surveyed. The methods used in the study of such systems are briefly characterised: X-ray diffraction analysis, NMR and UV spectroscopy, circular dichroism, scanning microcalorimetry, etc. A comparative analysis of the influence of the non-canonical pairs on the structure and the energetic and kinetic parameters of the formation and dissociation of the oligonucleotide complexes has been carried out. The question of the stability of the non-canonical pairs as a function of their nature and position in the double helix is considered. The mechanisms of the formation of the hydrogen bonds between the bases of non-complementary pairs are discussed. The bibliography includes 171 references.

Analysis and application of classification methods of complex carbonate reservoirs

NASA Astrophysics Data System (ADS)

Li, Xiongyan; Qin, Ruibao; Ping, Haitao; Wei, Dan; Liu, Xiaomei

2018-06-01

There are abundant carbonate reservoirs from the Cenozoic to Mesozoic era in the Middle East. Due to variation in sedimentary environment and diagenetic process of carbonate reservoirs, several porosity types coexist in carbonate reservoirs. As a result, because of the complex lithologies and pore types as well as the impact of microfractures, the pore structure is very complicated. Therefore, it is difficult to accurately calculate the reservoir parameters. In order to accurately evaluate carbonate reservoirs, based on the pore structure evaluation of carbonate reservoirs, the classification methods of carbonate reservoirs are analyzed based on capillary pressure curves and flow units. Based on the capillary pressure curves, although the carbonate reservoirs can be classified, the relationship between porosity and permeability after classification is not ideal. On the basis of the flow units, the high-precision functional relationship between porosity and permeability after classification can be established. Therefore, the carbonate reservoirs can be quantitatively evaluated based on the classification of flow units. In the dolomite reservoirs, the average absolute error of calculated permeability decreases from 15.13 to 7.44 mD. Similarly, the average absolute error of calculated permeability of limestone reservoirs is reduced from 20.33 to 7.37 mD. Only by accurately characterizing pore structures and classifying reservoir types, reservoir parameters could be calculated accurately. Therefore, characterizing pore structures and classifying reservoir types are very important to accurate evaluation of complex carbonate reservoirs in the Middle East.

High-order dynamic modeling and parameter identification of structural discontinuities in Timoshenko beams by using reflection coefficients

NASA Astrophysics Data System (ADS)

Fan, Qiang; Huang, Zhenyu; Zhang, Bing; Chen, Dayue

2013-02-01

Properties of discontinuities, such as bolt joints and cracks in the waveguide structures, are difficult to evaluate by either analytical or numerical methods due to the complexity and uncertainty of the discontinuities. In this paper, the discontinuity in a Timoshenko beam is modeled with high-order parameters and then these parameters are identified by using reflection coefficients at the discontinuity. The high-order model is composed of several one-order sub-models in series and each sub-model consists of inertia, stiffness and damping components in parallel. The order of the discontinuity model is determined based on the characteristics of the reflection coefficient curve and the accuracy requirement of the dynamic modeling. The model parameters are identified through the least-square fitting iteration method, of which the undetermined model parameters are updated in iteration to fit the dynamic reflection coefficient curve with the wave-based one. By using the spectral super-element method (SSEM), simulation cases, including one-order discontinuities on infinite- and finite-beams and a two-order discontinuity on an infinite beam, were employed to evaluate both the accuracy of the discontinuity model and the effectiveness of the identification method. For practical considerations, effects of measurement noise on the discontinuity parameter identification are investigated by adding different levels of noise to the simulated data. The simulation results were then validated by the corresponding experiments. Both the simulation and experimental results show that (1) the one-order discontinuities can be identified accurately with the maximum errors of 6.8% and 8.7%, respectively; (2) and the high-order discontinuities can be identified with the maximum errors of 15.8% and 16.2%, respectively; and (3) the high-order model can predict the complex discontinuity much more accurately than the one-order discontinuity model.

Dynamic Parameter Identification of Subject-Specific Body Segment Parameters Using Robotics Formalism: Case Study Head Complex.

PubMed

Díaz-Rodríguez, Miguel; Valera, Angel; Page, Alvaro; Besa, Antonio; Mata, Vicente

2016-05-01

Accurate knowledge of body segment inertia parameters (BSIP) improves the assessment of dynamic analysis based on biomechanical models, which is of paramount importance in fields such as sport activities or impact crash test. Early approaches for BSIP identification rely on the experiments conducted on cadavers or through imaging techniques conducted on living subjects. Recent approaches for BSIP identification rely on inverse dynamic modeling. However, most of the approaches are focused on the entire body, and verification of BSIP for dynamic analysis for distal segment or chain of segments, which has proven to be of significant importance in impact test studies, is rarely established. Previous studies have suggested that BSIP should be obtained by using subject-specific identification techniques. To this end, our paper develops a novel approach for estimating subject-specific BSIP based on static and dynamics identification models (SIM, DIM). We test the validity of SIM and DIM by comparing the results using parameters obtained from a regression model proposed by De Leva (1996, "Adjustments to Zatsiorsky-Seluyanov's Segment Inertia Parameters," J. Biomech., 29(9), pp. 1223-1230). Both SIM and DIM are developed considering robotics formalism. First, the static model allows the mass and center of gravity (COG) to be estimated. Second, the results from the static model are included in the dynamics equation allowing us to estimate the moment of inertia (MOI). As a case study, we applied the approach to evaluate the dynamics modeling of the head complex. Findings provide some insight into the validity not only of the proposed method but also of the application proposed by De Leva (1996, "Adjustments to Zatsiorsky-Seluyanov's Segment Inertia Parameters," J. Biomech., 29(9), pp. 1223-1230) for dynamic modeling of body segments.

Optical Coherence Tomography Noise Reduction Using Anisotropic Local Bivariate Gaussian Mixture Prior in 3D Complex Wavelet Domain

PubMed Central

Sonka, Milan; Abramoff, Michael D.

2013-01-01

In this paper, MMSE estimator is employed for noise-free 3D OCT data recovery in 3D complex wavelet domain. Since the proposed distribution for noise-free data plays a key role in the performance of MMSE estimator, a priori distribution for the pdf of noise-free 3D complex wavelet coefficients is proposed which is able to model the main statistical properties of wavelets. We model the coefficients with a mixture of two bivariate Gaussian pdfs with local parameters which are able to capture the heavy-tailed property and inter- and intrascale dependencies of coefficients. In addition, based on the special structure of OCT images, we use an anisotropic windowing procedure for local parameters estimation that results in visual quality improvement. On this base, several OCT despeckling algorithms are obtained based on using Gaussian/two-sided Rayleigh noise distribution and homomorphic/nonhomomorphic model. In order to evaluate the performance of the proposed algorithm, we use 156 selected ROIs from 650 × 512 × 128 OCT dataset in the presence of wet AMD pathology. Our simulations show that the best MMSE estimator using local bivariate mixture prior is for the nonhomomorphic model in the presence of Gaussian noise which results in an improvement of 7.8 ± 1.7 in CNR. PMID:24222760

Virtual Construction of Space Habitats: Connecting Building Information Models (BIM) and SysML

NASA Technical Reports Server (NTRS)

Polit-Casillas, Raul; Howe, A. Scott

2013-01-01

Current trends in design, construction and management of complex projects make use of Building Information Models (BIM) connecting different types of data to geometrical models. This information model allow different types of analysis beyond pure graphical representations. Space habitats, regardless their size, are also complex systems that require the synchronization of many types of information and disciplines beyond mass, volume, power or other basic volumetric parameters. For this, the state-of-the-art model based systems engineering languages and processes - for instance SysML - represent a solid way to tackle this problem from a programmatic point of view. Nevertheless integrating this with a powerful geometrical architectural design tool with BIM capabilities could represent a change in the workflow and paradigm of space habitats design applicable to other aerospace complex systems. This paper shows some general findings and overall conclusions based on the ongoing research to create a design protocol and method that practically connects a systems engineering approach with a BIM architectural and engineering design as a complete Model Based Engineering approach. Therefore, one hypothetical example is created and followed during the design process. In order to make it possible this research also tackles the application of IFC categories and parameters in the aerospace field starting with the application upon the space habitats design as way to understand the information flow between disciplines and tools. By building virtual space habitats we can potentially improve in the near future the way more complex designs are developed from very little detail from concept to manufacturing.

Identifying Hierarchical and Overlapping Protein Complexes Based on Essential Protein-Protein Interactions and “Seed-Expanding” Method

PubMed Central

Ren, Jun; Zhou, Wei; Wang, Jianxin

2014-01-01

Many evidences have demonstrated that protein complexes are overlapping and hierarchically organized in PPI networks. Meanwhile, the large size of PPI network wants complex detection methods have low time complexity. Up to now, few methods can identify overlapping and hierarchical protein complexes in a PPI network quickly. In this paper, a novel method, called MCSE, is proposed based on λ-module and “seed-expanding.” First, it chooses seeds as essential PPIs or edges with high edge clustering values. Then, it identifies protein complexes by expanding each seed to a λ-module. MCSE is suitable for large PPI networks because of its low time complexity. MCSE can identify overlapping protein complexes naturally because a protein can be visited by different seeds. MCSE uses the parameter λ_th to control the range of seed expanding and can detect a hierarchical organization of protein complexes by tuning the value of λ_th. Experimental results of S. cerevisiae show that this hierarchical organization is similar to that of known complexes in MIPS database. The experimental results also show that MCSE outperforms other previous competing algorithms, such as CPM, CMC, Core-Attachment, Dpclus, HC-PIN, MCL, and NFC, in terms of the functional enrichment and matching with known protein complexes. PMID:25143945

Antimicrobial Applications of Transition Metal Complexes of Benzothiazole Based Terpolymer: Synthesis, Characterization, and Effect on Bacterial and Fungal Strains

PubMed Central

Riswan Ahamed, Mohamed A.; Azarudeen, Raja S.; Kani, N. Mujafar

2014-01-01

Terpolymer of 2-amino-6-nitro-benzothiazole-ethylenediamine-formaldehyde (BEF) has been synthesized and characterized by elemental analysis and various spectral techniques like FTIR, UV-Visible, and 1H and 13C-NMR. The terpolymer metal complexes were prepared with Cu2+, Ni2+, and Zn2+ metal ions using BEF terpolymer as a ligand. The complexes have been characterized by elemental analysis and IR, UV-Visible, ESR, 1H-NMR, and 13C-NMR spectral studies. Gel permeation chromatography was used to determine the molecular weight of the ligand. The surface features and crystalline behavior of the ligand and its complexes were analyzed by scanning electron microscope and X-ray diffraction methods. Thermogravimetric analysis was used to analyze the thermal stability of the ligand and its metal complexes. Kinetic parameters such as activation energy (E a) and order of reaction (n) and thermodynamic parameters, namely, ΔS, ΔF, S*, and Z, were calculated using Freeman-Carroll (FC), Sharp-Wentworth (SW), and Phadnis-Deshpande (PD) methods. Thermal degradation model of the terpolymer and its metal complexes was also proposed using PD method. Biological activities of the ligand and its complexes were tested against Shigella sonnei, Escherichia coli, Klebsiella species, Staphylococcus aureus, Bacillus subtilis, and Salmonella typhimurium bacteria and Aspergillus flavus, Aspergillus niger, Penicillium species, Candida albicans, Cryptococcus neoformans, Mucor species fungi. PMID:25298760

Frequency analysis via the method of moment functionals

NASA Technical Reports Server (NTRS)

Pearson, A. E.; Pan, J. Q.

1990-01-01

Several variants are presented of a linear-in-parameters least squares formulation for determining the transfer function of a stable linear system at specified frequencies given a finite set of Fourier series coefficients calculated from transient nonstationary input-output data. The basis of the technique is Shinbrot's classical method of moment functionals using complex Fourier based modulating functions to convert a differential equation model on a finite time interval into an algebraic equation which depends linearly on frequency-related parameters.

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

Yoshii, Kazutomo; Llopis, Pablo; Zhang, Kaicheng

As CMOS scaling nears its end, parameter variations (process, temperature and voltage) are becoming a major concern. To overcome parameter variations and provide stability, modern processors are becoming dynamic, opportunistically adjusting voltage and frequency based on thermal and energy constraints, which negatively impacts traditional bulk-synchronous parallelism-minded hardware and software designs. As node-level architecture is growing in complexity, implementing variation control mechanisms only with hardware can be a challenging task. In this paper we investigate a software strategy to manage hardwareinduced variations, leveraging low-level monitoring/controlling mechanisms.

Lithospheric Models of the Middle East to Improve Seismic Source Parameter Determination/Event Location Accuracy

DTIC Science & Technology

2012-09-01

State Award Nos. DE-AC52-07NA27344/24.2.3.2 and DOS_SIAA-11-AVC/NMA-1 ABSTRACT The Middle East is a tectonically complex and seismically...active region. The ability to accurately locate earthquakes and other seismic events in this region is complicated by tectonics , the uneven...and seismic source parameters show that this activity comes from tectonic events. This work is informed by continuous or event-based regional

Parameter Estimation of a Spiking Silicon Neuron

PubMed Central

Russell, Alexander; Mazurek, Kevin; Mihalaş, Stefan; Niebur, Ernst; Etienne-Cummings, Ralph

2012-01-01

Spiking neuron models are used in a multitude of tasks ranging from understanding neural behavior at its most basic level to neuroprosthetics. Parameter estimation of a single neuron model, such that the model’s output matches that of a biological neuron is an extremely important task. Hand tuning of parameters to obtain such behaviors is a difficult and time consuming process. This is further complicated when the neuron is instantiated in silicon (an attractive medium in which to implement these models) as fabrication imperfections make the task of parameter configuration more complex. In this paper we show two methods to automate the configuration of a silicon (hardware) neuron’s parameters. First, we show how a Maximum Likelihood method can be applied to a leaky integrate and fire silicon neuron with spike induced currents to fit the neuron’s output to desired spike times. We then show how a distance based method which approximates the negative log likelihood of the lognormal distribution can also be used to tune the neuron’s parameters. We conclude that the distance based method is better suited for parameter configuration of silicon neurons due to its superior optimization speed. PMID:23852978

Adaptive quantization-parameter clip scheme for smooth quality in H.264/AVC.

PubMed

Hu, Sudeng; Wang, Hanli; Kwong, Sam

2012-04-01

In this paper, we investigate the issues over the smooth quality and the smooth bit rate during rate control (RC) in H.264/AVC. An adaptive quantization-parameter (Q(p)) clip scheme is proposed to optimize the quality smoothness while keeping the bit-rate fluctuation at an acceptable level. First, the frame complexity variation is studied by defining a complexity ratio between two nearby frames. Second, the range of the generated bits is analyzed to prevent the encoder buffer from overflow and underflow. Third, based on the safe range of the generated bits, an optimal Q(p) clip range is developed to reduce the quality fluctuation. Experimental results demonstrate that the proposed Q(p) clip scheme can achieve excellent performance in quality smoothness and buffer regulation.

Electron impact ionization of cycloalkanes, aldehydes, and ketones

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

Gupta, Dhanoj; Antony, Bobby, E-mail: bka.ism@gmail.com

The theoretical calculations of electron impact total ionization cross section for cycloalkane, aldehyde, and ketone group molecules are undertaken from ionization threshold to 2 keV. The present calculations are based on the spherical complex optical potential formalism and complex scattering potential ionization contribution method. The results of most of the targets studied compare fairly well with the recent measurements, wherever available and the cross sections for many targets are predicted for the first time. The correlation between the peak of ionization cross sections with number of target electrons and target parameters is also reported. It was found that the crossmore » sections at their maximum depend linearly with the number of target electrons and with other target parameters, confirming the consistency of the values reported here.« less

An Image Encryption Algorithm Based on Information Hiding

NASA Astrophysics Data System (ADS)

Ge, Xin; Lu, Bin; Liu, Fenlin; Gong, Daofu

Aiming at resolving the conflict between security and efficiency in the design of chaotic image encryption algorithms, an image encryption algorithm based on information hiding is proposed based on the “one-time pad” idea. A random parameter is introduced to ensure a different keystream for each encryption, which has the characteristics of “one-time pad”, improving the security of the algorithm rapidly without significant increase in algorithm complexity. The random parameter is embedded into the ciphered image with information hiding technology, which avoids negotiation for its transport and makes the application of the algorithm easier. Algorithm analysis and experiments show that the algorithm is secure against chosen plaintext attack, differential attack and divide-and-conquer attack, and has good statistical properties in ciphered images.

Are our dynamic water quality models too complex? A comparison of a new parsimonious phosphorus model, SimplyP, and INCA-P

NASA Astrophysics Data System (ADS)

Jackson-Blake, L. A.; Sample, J. E.; Wade, A. J.; Helliwell, R. C.; Skeffington, R. A.

2017-07-01

Catchment-scale water quality models are increasingly popular tools for exploring the potential effects of land management, land use change and climate change on water quality. However, the dynamic, catchment-scale nutrient models in common usage are complex, with many uncertain parameters requiring calibration, limiting their usability and robustness. A key question is whether this complexity is justified. To explore this, we developed a parsimonious phosphorus model, SimplyP, incorporating a rainfall-runoff model and a biogeochemical model able to simulate daily streamflow, suspended sediment, and particulate and dissolved phosphorus dynamics. The model's complexity was compared to one popular nutrient model, INCA-P, and the performance of the two models was compared in a small rural catchment in northeast Scotland. For three land use classes, less than six SimplyP parameters must be determined through calibration, the rest may be based on measurements, while INCA-P has around 40 unmeasurable parameters. Despite substantially simpler process-representation, SimplyP performed comparably to INCA-P in both calibration and validation and produced similar long-term projections in response to changes in land management. Results support the hypothesis that INCA-P is overly complex for the study catchment. We hope our findings will help prompt wider model comparison exercises, as well as debate among the water quality modeling community as to whether today's models are fit for purpose. Simpler models such as SimplyP have the potential to be useful management and research tools, building blocks for future model development (prototype code is freely available), or benchmarks against which more complex models could be evaluated.

Magnetic Resonance Imaging (MRI): Operative Findings Correlation in 229 Fistula-in-Ano Patients.

PubMed

Garg, Pankaj; Singh, Pratiksha; Kaur, Baljit

2017-06-01

To correlate the operative findings of patients with fistula-in-ano with preoperative MRI and quantify the information added with MRI. All consecutive fistula-in-ano patients operated between July 2013 and May 2015 were prospectively enrolled. Preoperative MRI was done in every patient. The details of tracts, internal opening and "complex parameters" (additional tract or additional internal opening, horseshoe tract, associated abscess and supralevator extension) found at surgery were compared to the findings determined by MRI. A total of 229 patients (424 tracts) with mean age-49.0 ± 11.3 years were included. M/F 198/31. James hospital classification: Type I 58, II 20, III 49, IV 86 and V 16. The sensitivity and specificity of MRI in diagnosing fistula tracts were 98.8 and 99.7%, respectively, and in identifying internal opening were 97.7 and 98.6%, respectively. MRI added significant information in 46.7% (107/229) patients which was presence of additional tracts in 71 (66.3%), horseshoe tract in 63 (58.8%), supralevator extension in 16 (14.9%), unsuspected abscess in 11 (10.3%) and multiple internal openings in one patient (1%). The proportion of simple/complex fistula (based on history and clinical examination alone) was 32.8/67.2% which changed to 21.4/78.6% after the MRI scan. MRI added significant information about unsuspecting complex parameters which were missed on history and clinical examination in more than one-third (26/75: 34.6%) of simple fistulae and more than half (81/154: 52.5%) of already known complex fistulae. MRI is highly accurate in diagnosing fistula-in-ano and added significant information about unsuspected complex parameters in over one-third (34.6%) of simple and in half (52.5%) of complex fistula-in-ano.

Immobilized magnetic beads-based multi-target affinity selection coupled with HPLC-MS for screening active compounds from traditional Chinese medicine and natural products.

PubMed

Chen, Yaqi; Chen, Zhui; Wang, Yi

2015-01-01

Screening and identifying active compounds from traditional Chinese medicine (TCM) and other natural products plays an important role in drug discovery. Here, we describe a magnetic beads-based multi-target affinity selection-mass spectrometry approach for screening bioactive compounds from natural products. Key steps and parameters including activation of magnetic beads, enzyme/protein immobilization, characterization of functional magnetic beads, screening and identifying active compounds from a complex mixture by LC/MS, are illustrated. The proposed approach is rapid and efficient in screening and identification of bioactive compounds from complex natural products.

Combining the ‘bottom up’ and ‘top down’ approaches in pharmacokinetic modelling: fitting PBPK models to observed clinical data

PubMed Central

Tsamandouras, Nikolaos; Rostami-Hodjegan, Amin; Aarons, Leon

2015-01-01

Pharmacokinetic models range from being entirely exploratory and empirical, to semi-mechanistic and ultimately complex physiologically based pharmacokinetic (PBPK) models. This choice is conditional on the modelling purpose as well as the amount and quality of the available data. The main advantage of PBPK models is that they can be used to extrapolate outside the studied population and experimental conditions. The trade-off for this advantage is a complex system of differential equations with a considerable number of model parameters. When these parameters cannot be informed from in vitro or in silico experiments they are usually optimized with respect to observed clinical data. Parameter estimation in complex models is a challenging task associated with many methodological issues which are discussed here with specific recommendations. Concepts such as structural and practical identifiability are described with regards to PBPK modelling and the value of experimental design and sensitivity analyses is sketched out. Parameter estimation approaches are discussed, while we also highlight the importance of not neglecting the covariance structure between model parameters and the uncertainty and population variability that is associated with them. Finally the possibility of using model order reduction techniques and minimal semi-mechanistic models that retain the physiological-mechanistic nature only in the parts of the model which are relevant to the desired modelling purpose is emphasized. Careful attention to all the above issues allows us to integrate successfully information from in vitro or in silico experiments together with information deriving from observed clinical data and develop mechanistically sound models with clinical relevance. PMID:24033787

In vivo potency revisited - Keep the target in sight.

PubMed

Gabrielsson, Johan; Peletier, Lambertus A; Hjorth, Stephan

2018-04-01

Potency is a central parameter in pharmacological and biochemical sciences, as well as in drug discovery and development endeavors. It is however typically defined in terms only of ligand to target binding affinity also in in vivo experimentation, thus in a manner analogous to in in vitro studies. As in vivo potency is in fact a conglomerate of events involving ligand, target, and target-ligand complex processes, overlooking some of the fundamental differences between in vivo and in vitro may result in serious mispredictions of in vivo efficacious dose and exposure. The analysis presented in this paper compares potency measures derived from three model situations. Model A represents the closed in vitro system, defining target binding of a ligand when total target and ligand concentrations remain static and constant. Model B describes an open in vivo system with ligand input and clearance (Cl (L) ), adding in parallel to the turnover (k syn , k deg ) of the target. Model C further adds to the open in vivo system in Model B also the elimination of the target-ligand complex (k e(RL) ) via a first-order process. We formulate corresponding equations of the equilibrium (steady-state) relationships between target and ligand, and complex and ligand for each of the three model systems and graphically illustrate the resulting simulations. These equilibrium relationships demonstrate the relative impact of target and target-ligand complex turnover, and are easier to interpret than the more commonly used ligand-, target- and complex concentration-time courses. A new potency expression, labeled L 50 , is then derived. L 50 is the ligand concentration at half-maximal target and complex concentrations and is an amalgamation of target turnover, target-ligand binding and complex elimination parameters estimated from concentration-time data. L 50 is then compared to the dissociation constant K d (target-ligand binding affinity), the conventional Black & Leff potency estimate EC 50 , and the derived Michaelis-Menten parameter K m (target-ligand binding and complex removal) across a set of literature data. It is evident from a comparison between parameters derived from in vitro vs. in vivo experiments that L 50 can be either numerically greater or smaller than the K d (or K m ) parameter, primarily depending on the ratio of k deg -to-k e(RL) . Contrasting the limit values of target R and target-ligand complex RL for ligand concentrations approaching infinity demonstrates that the outcome of the three models differs to a great extent. Based on the analysis we propose that a better understanding of in vivo pharmacological potency requires simultaneous assessment of the impact of its underlying determinants in the open system setting. We propose that L 50 will be a useful parameter guiding predictions of the effective concentration range, for translational purposes, and assessment of in vivo target occupancy/suppression by ligand, since it also encompasses target turnover - in turn also subject to influence by pathophysiology and drug treatment. Different compounds may have similar binding affinity for a target in vitro (same K d ), but vastly different potencies in vivo. L 50 points to what parameters need to be taken into account, and particularly that closed-system (in vitro) parameters should not be first choice when ranking compounds in vivo (open system). Copyright © 2017 Elsevier Inc. All rights reserved.

On approaches to analyze the sensitivity of simulated hydrologic fluxes to model parameters in the community land model

DOE PAGES

Bao, Jie; Hou, Zhangshuan; Huang, Maoyi; ...

2015-12-04

Here, effective sensitivity analysis approaches are needed to identify important parameters or factors and their uncertainties in complex Earth system models composed of multi-phase multi-component phenomena and multiple biogeophysical-biogeochemical processes. In this study, the impacts of 10 hydrologic parameters in the Community Land Model on simulations of runoff and latent heat flux are evaluated using data from a watershed. Different metrics, including residual statistics, the Nash-Sutcliffe coefficient, and log mean square error, are used as alternative measures of the deviations between the simulated and field observed values. Four sensitivity analysis (SA) approaches, including analysis of variance based on the generalizedmore » linear model, generalized cross validation based on the multivariate adaptive regression splines model, standardized regression coefficients based on a linear regression model, and analysis of variance based on support vector machine, are investigated. Results suggest that these approaches show consistent measurement of the impacts of major hydrologic parameters on response variables, but with differences in the relative contributions, particularly for the secondary parameters. The convergence behaviors of the SA with respect to the number of sampling points are also examined with different combinations of input parameter sets and output response variables and their alternative metrics. This study helps identify the optimal SA approach, provides guidance for the calibration of the Community Land Model parameters to improve the model simulations of land surface fluxes, and approximates the magnitudes to be adjusted in the parameter values during parametric model optimization.« less

Spectroscopic and electrochemical characterization of some Schiff base metal complexes containing benzoin moiety.

PubMed

El-Shahawi, M S; Al-Jahdali, M S; Bashammakh, A S; Al-Sibaai, A A; Nassef, H M

2013-09-01

The ligation behavior of bis-benzoin ethylenediamine (B2ED) and benzoin thiosemicarbazone (BTS) Schiff bases towards Ru(3+), Rh(3+), Pd(2+), Ni(2+) and Cu(2+) were determined. The bond length of M-N and spectrochemical parameters (10Dq, β, B and LFSE) of the complexes were evaluated. The redox characteristics of selected complexes were explored by cyclic voltammetry (CV) at Pt working electrode in non aqueous solvents. Au mesh (100 w/in.) optically transparent thin layer electrode (OTTLE) was also used for recording thin layer CV for selected Ru complex. Oxidation of some complexes occurs in a consecutive chemical reaction of an EC type mechanism. The characteristics of electron transfer process of the couples M(2+)/M(3+) and M(3+)/M(4+) (M=Ru(3+), Rh(3+)) and the stability of the complexes towards oxidation and/or reduction were assigned. The nature of the electroactive species and reduction mechanism of selected electrode couples were assigned. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Parameter-induced uncertainty quantification of crop yields, soil N2O and CO2 emission for 8 arable sites across Europe using the LandscapeDNDC model

NASA Astrophysics Data System (ADS)

Santabarbara, Ignacio; Haas, Edwin; Kraus, David; Herrera, Saul; Klatt, Steffen; Kiese, Ralf

2014-05-01

When using biogeochemical models to estimate greenhouse gas emissions at site to regional/national levels, the assessment and quantification of the uncertainties of simulation results are of significant importance. The uncertainties in simulation results of process-based ecosystem models may result from uncertainties of the process parameters that describe the processes of the model, model structure inadequacy as well as uncertainties in the observations. Data for development and testing of uncertainty analisys were corp yield observations, measurements of soil fluxes of nitrous oxide (N2O) and carbon dioxide (CO2) from 8 arable sites across Europe. Using the process-based biogeochemical model LandscapeDNDC for simulating crop yields, N2O and CO2 emissions, our aim is to assess the simulation uncertainty by setting up a Bayesian framework based on Metropolis-Hastings algorithm. Using Gelman statistics convergence criteria and parallel computing techniques, enable multi Markov Chains to run independently in parallel and create a random walk to estimate the joint model parameter distribution. Through means distribution we limit the parameter space, get probabilities of parameter values and find the complex dependencies among them. With this parameter distribution that determines soil-atmosphere C and N exchange, we are able to obtain the parameter-induced uncertainty of simulation results and compare them with the measurements data.

Series Hybrid Electric Vehicle Power System Optimization Based on Genetic Algorithm

NASA Astrophysics Data System (ADS)

Zhu, Tianjun; Li, Bin; Zong, Changfu; Wu, Yang

2017-09-01

Hybrid electric vehicles (HEV), compared with conventional vehicles, have complex structures and more component parameters. If variables optimization designs are carried on all these parameters, it will increase the difficulty and the convergence of algorithm program, so this paper chooses the parameters which has a major influence on the vehicle fuel consumption to make it all work at maximum efficiency. First, HEV powertrain components modelling are built. Second, taking a tandem hybrid structure as an example, genetic algorithm is used in this paper to optimize fuel consumption and emissions. Simulation results in ADVISOR verify the feasibility of the proposed genetic optimization algorithm.

Reliability Estimation of Aero-engine Based on Mixed Weibull Distribution Model

NASA Astrophysics Data System (ADS)

Yuan, Zhongda; Deng, Junxiang; Wang, Dawei

2018-02-01

Aero-engine is a complex mechanical electronic system, based on analysis of reliability of mechanical electronic system, Weibull distribution model has an irreplaceable role. Till now, only two-parameter Weibull distribution model and three-parameter Weibull distribution are widely used. Due to diversity of engine failure modes, there is a big error with single Weibull distribution model. By contrast, a variety of engine failure modes can be taken into account with mixed Weibull distribution model, so it is a good statistical analysis model. Except the concept of dynamic weight coefficient, in order to make reliability estimation result more accurately, three-parameter correlation coefficient optimization method is applied to enhance Weibull distribution model, thus precision of mixed distribution reliability model is improved greatly. All of these are advantageous to popularize Weibull distribution model in engineering applications.

Economical analysis of saturation mutagenesis experiments

PubMed Central

Acevedo-Rocha, Carlos G.; Reetz, Manfred T.; Nov, Yuval

2015-01-01

Saturation mutagenesis is a powerful technique for engineering proteins, metabolic pathways and genomes. In spite of its numerous applications, creating high-quality saturation mutagenesis libraries remains a challenge, as various experimental parameters influence in a complex manner the resulting diversity. We explore from the economical perspective various aspects of saturation mutagenesis library preparation: We introduce a cheaper and faster control for assessing library quality based on liquid media; analyze the role of primer purity and supplier in libraries with and without redundancy; compare library quality, yield, randomization efficiency, and annealing bias using traditional and emergent randomization schemes based on mixtures of mutagenic primers; and establish a methodology for choosing the most cost-effective randomization scheme given the screening costs and other experimental parameters. We show that by carefully considering these parameters, laboratory expenses can be significantly reduced. PMID:26190439

Modulation indices for volumetric modulated arc therapy.

PubMed

Park, Jong Min; Park, So-Yeon; Kim, Hyoungnyoun; Kim, Jin Ho; Carlson, Joel; Ye, Sung-Joon

2014-12-07

The aim of this study is to present a modulation index (MI) for volumetric modulated arc therapy (VMAT) based on the speed and acceleration analysis of modulating-parameters such as multi-leaf collimator (MLC) movements, gantry rotation and dose-rate, comprehensively. The performance of the presented MI (MIt) was evaluated with correlation analyses to the pre-treatment quality assurance (QA) results, differences in modulating-parameters between VMAT plans versus dynamic log files, and differences in dose-volumetric parameters between VMAT plans versus reconstructed plans using dynamic log files. For comparison, the same correlation analyses were performed for the previously suggested modulation complexity score (MCS(v)), leaf travel modulation complexity score (LTMCS) and MI by Li and Xing (MI Li&Xing). In the two-tailed unpaired parameter condition, p values were acquired. The Spearman's rho (r(s)) values of MIt, MCSv, LTMCS and MI Li&Xing to the local gamma passing rate with 2%/2 mm criterion were -0.658 (p < 0.001), 0.186 (p = 0.251), 0.312 (p = 0.05) and -0.455 (p = 0.003), respectively. The values of rs to the modulating-parameter (MLC positions) differences were 0.917, -0.635, -0.857 and 0.795, respectively (p < 0.001). For dose-volumetric parameters, MIt showed higher statistically significant correlations than the conventional MIs. The MIt showed good performance for the evaluation of the modulation-degree of VMAT plans.

[Intraobserver reliability of the Handball-specific complex test (HBKT)].

PubMed

Schwesig, R; Koke, A; Jungermann, P; Fischer, D; Noack, F; Becker, S; Fieseler, G; Delank, K-S

2014-09-01

There are clearly no complex and sports-specific tests in handball. So far, no specific complex test has been developed and verified for its intraobserver reliability (IR). The aim of this study was to determine the IR of the Handball-specific complex test (HBKT). The HBKT was applied twice at an interval of two days to two teams of the German Third League (n = 30; age 25.7 ± 3.9 years, range: 19 - 33 years). Within the HBKT, the stress parameters lactate and heart rate as well as the loading parameters time, throwing velocity and number of errors were collected. Overall, 23 % (3/13) of the stress parameters showed a high relative [intraclass correlation coefficient (ICC) > 0.75] and absolute [coefficient of variation (CV) ≤ 5 %] IR. On average, a sufficient absolute (∅CV = 11.3 %) and relative (∅ICC = 0.67) IR was observed. Without the parameters "missed throws" and "technical errors" in both rounds, the IR increased significantly (∅ICC: from 0.67 to 0.72 & ∅CV from 11.3 to 6.3 %). The heart rate was comparatively more reliable than lactate (∅ICC = 0.71 & ∅CV = 4.23 % vs. ∅ICC = 0.65 & ∅CV = 15.1 %). With respect to load parameters in round one, 50 % (5/10) showed a high IR; in round two, these values decreased to 40 % (4/10). The mean IR of the parameters in round one was higher than in round two (∅ICC = 0.71 & ∅CV = 12.2 % vs. ∅ICC = 0.60 & ∅CV = 14.3 %). Overall, there was an improvement of the athletes in most stress and load parameters from session one to session two. The HBKT can be attested with a sufficient intraobserver reliability. When the parameters "missed throws" and "technical errors" were excluded, the IR further increased significantly. Therefore, these parameters should be recorded in order to standardized the HBKT, but not be included in the statistical analysis. There are discrete adaptation and learning effects. For this reason, it is essential to familiarise trainers and players with the HBKT test procedure before the first measurement. Otherwise training effects can be easily overrated. Moreover, the test concept of HBKT can be used as a blueprint for the development of sport-specific tests in other team sports (e. g., soccer, basketball). For example, we generated a complex soccer-specific field test 1 based on the HBKT. © Georg Thieme Verlag KG Stuttgart · New York.

Hyperspectral imaging simulation of object under sea-sky background

NASA Astrophysics Data System (ADS)

Wang, Biao; Lin, Jia-xuan; Gao, Wei; Yue, Hui

2016-10-01

Remote sensing image simulation plays an important role in spaceborne/airborne load demonstration and algorithm development. Hyperspectral imaging is valuable in marine monitoring, search and rescue. On the demand of spectral imaging of objects under the complex sea scene, physics based simulation method of spectral image of object under sea scene is proposed. On the development of an imaging simulation model considering object, background, atmosphere conditions, sensor, it is able to examine the influence of wind speed, atmosphere conditions and other environment factors change on spectral image quality under complex sea scene. Firstly, the sea scattering model is established based on the Philips sea spectral model, the rough surface scattering theory and the water volume scattering characteristics. The measured bi directional reflectance distribution function (BRDF) data of objects is fit to the statistical model. MODTRAN software is used to obtain solar illumination on the sea, sky brightness, the atmosphere transmittance from sea to sensor and atmosphere backscattered radiance, and Monte Carlo ray tracing method is used to calculate the sea surface object composite scattering and spectral image. Finally, the object spectrum is acquired by the space transformation, radiation degradation and adding the noise. The model connects the spectrum image with the environmental parameters, the object parameters, and the sensor parameters, which provide a tool for the load demonstration and algorithm development.

Modeling of Processing-Induced Pore Morphology in an Additively-Manufactured Ti-6Al-4V Alloy

PubMed Central

Kabir, Mohammad Rizviul; Richter, Henning

2017-01-01

A selective laser melting (SLM)-based, additively-manufactured Ti-6Al-4V alloy is prone to the accumulation of undesirable defects during layer-by-layer material build-up. Defects in the form of complex-shaped pores are one of the critical issues that need to be considered during the processing of this alloy. Depending on the process parameters, pores with concave or convex boundaries may occur. To exploit the full potential of additively-manufactured Ti-6Al-4V, the interdependency between the process parameters, pore morphology, and resultant mechanical properties, needs to be understood. By incorporating morphological details into numerical models for micromechanical analyses, an in-depth understanding of how these pores interact with the Ti-6Al-4V microstructure can be gained. However, available models for pore analysis lack a realistic description of both the Ti-6Al-4V grain microstructure, and the pore geometry. To overcome this, we propose a comprehensive approach for modeling and discretizing pores with complex geometry, situated in a polycrystalline microstructure. In this approach, the polycrystalline microstructure is modeled by means of Voronoi tessellations, and the complex pore geometry is approximated by strategically combining overlapping spheres of varied sizes. The proposed approach provides an elegant way to model the microstructure of SLM-processed Ti-6Al-4V containing pores or crack-like voids, and makes it possible to investigate the relationship between process parameters, pore morphology, and resultant mechanical properties in a finite-element-based simulation framework. PMID:28772504

Prosthetic Avian Vocal Organ Controlled by a Freely Behaving Bird Based on a Low Dimensional Model of the Biomechanical Periphery

PubMed Central

Arneodo, Ezequiel M.; Perl, Yonatan Sanz; Goller, Franz; Mindlin, Gabriel B.

2012-01-01

Because of the parallels found with human language production and acquisition, birdsong is an ideal animal model to study general mechanisms underlying complex, learned motor behavior. The rich and diverse vocalizations of songbirds emerge as a result of the interaction between a pattern generator in the brain and a highly nontrivial nonlinear periphery. Much of the complexity of this vocal behavior has been understood by studying the physics of the avian vocal organ, particularly the syrinx. A mathematical model describing the complex periphery as a nonlinear dynamical system leads to the conclusion that nontrivial behavior emerges even when the organ is commanded by simple motor instructions: smooth paths in a low dimensional parameter space. An analysis of the model provides insight into which parameters are responsible for generating a rich variety of diverse vocalizations, and what the physiological meaning of these parameters is. By recording the physiological motor instructions elicited by a spontaneously singing muted bird and computing the model on a Digital Signal Processor in real-time, we produce realistic synthetic vocalizations that replace the bird's own auditory feedback. In this way, we build a bio-prosthetic avian vocal organ driven by a freely behaving bird via its physiologically coded motor commands. Since it is based on a low-dimensional nonlinear mathematical model of the peripheral effector, the emulation of the motor behavior requires light computation, in such a way that our bio-prosthetic device can be implemented on a portable platform. PMID:22761555

Parallel Markov chain Monte Carlo - bridging the gap to high-performance Bayesian computation in animal breeding and genetics.

PubMed

Wu, Xiao-Lin; Sun, Chuanyu; Beissinger, Timothy M; Rosa, Guilherme Jm; Weigel, Kent A; Gatti, Natalia de Leon; Gianola, Daniel

2012-09-25

Most Bayesian models for the analysis of complex traits are not analytically tractable and inferences are based on computationally intensive techniques. This is true of Bayesian models for genome-enabled selection, which uses whole-genome molecular data to predict the genetic merit of candidate animals for breeding purposes. In this regard, parallel computing can overcome the bottlenecks that can arise from series computing. Hence, a major goal of the present study is to bridge the gap to high-performance Bayesian computation in the context of animal breeding and genetics. Parallel Monte Carlo Markov chain algorithms and strategies are described in the context of animal breeding and genetics. Parallel Monte Carlo algorithms are introduced as a starting point including their applications to computing single-parameter and certain multiple-parameter models. Then, two basic approaches for parallel Markov chain Monte Carlo are described: one aims at parallelization within a single chain; the other is based on running multiple chains, yet some variants are discussed as well. Features and strategies of the parallel Markov chain Monte Carlo are illustrated using real data, including a large beef cattle dataset with 50K SNP genotypes. Parallel Markov chain Monte Carlo algorithms are useful for computing complex Bayesian models, which does not only lead to a dramatic speedup in computing but can also be used to optimize model parameters in complex Bayesian models. Hence, we anticipate that use of parallel Markov chain Monte Carlo will have a profound impact on revolutionizing the computational tools for genomic selection programs.

Modeling of Processing-Induced Pore Morphology in an Additively-Manufactured Ti-6Al-4V Alloy.

PubMed

Kabir, Mohammad Rizviul; Richter, Henning

2017-02-08

A selective laser melting (SLM)-based, additively-manufactured Ti-6Al-4V alloy is prone to the accumulation of undesirable defects during layer-by-layer material build-up. Defects in the form of complex-shaped pores are one of the critical issues that need to be considered during the processing of this alloy. Depending on the process parameters, pores with concave or convex boundaries may occur. To exploit the full potential of additively-manufactured Ti-6Al-4V, the interdependency between the process parameters, pore morphology, and resultant mechanical properties, needs to be understood. By incorporating morphological details into numerical models for micromechanical analyses, an in-depth understanding of how these pores interact with the Ti-6Al-4V microstructure can be gained. However, available models for pore analysis lack a realistic description of both the Ti-6Al-4V grain microstructure, and the pore geometry. To overcome this, we propose a comprehensive approach for modeling and discretizing pores with complex geometry, situated in a polycrystalline microstructure. In this approach, the polycrystalline microstructure is modeled by means of Voronoi tessellations, and the complex pore geometry is approximated by strategically combining overlapping spheres of varied sizes. The proposed approach provides an elegant way to model the microstructure of SLM-processed Ti-6Al-4V containing pores or crack-like voids, and makes it possible to investigate the relationship between process parameters, pore morphology, and resultant mechanical properties in a finite-element-based simulation framework.

Parallel Markov chain Monte Carlo - bridging the gap to high-performance Bayesian computation in animal breeding and genetics

PubMed Central

2012-01-01

Background Most Bayesian models for the analysis of complex traits are not analytically tractable and inferences are based on computationally intensive techniques. This is true of Bayesian models for genome-enabled selection, which uses whole-genome molecular data to predict the genetic merit of candidate animals for breeding purposes. In this regard, parallel computing can overcome the bottlenecks that can arise from series computing. Hence, a major goal of the present study is to bridge the gap to high-performance Bayesian computation in the context of animal breeding and genetics. Results Parallel Monte Carlo Markov chain algorithms and strategies are described in the context of animal breeding and genetics. Parallel Monte Carlo algorithms are introduced as a starting point including their applications to computing single-parameter and certain multiple-parameter models. Then, two basic approaches for parallel Markov chain Monte Carlo are described: one aims at parallelization within a single chain; the other is based on running multiple chains, yet some variants are discussed as well. Features and strategies of the parallel Markov chain Monte Carlo are illustrated using real data, including a large beef cattle dataset with 50K SNP genotypes. Conclusions Parallel Markov chain Monte Carlo algorithms are useful for computing complex Bayesian models, which does not only lead to a dramatic speedup in computing but can also be used to optimize model parameters in complex Bayesian models. Hence, we anticipate that use of parallel Markov chain Monte Carlo will have a profound impact on revolutionizing the computational tools for genomic selection programs. PMID:23009363

Performance of a distributed semi-conceptual hydrological model under tropical watershed conditions

USDA-ARS?s Scientific Manuscript database

Many hydrologic models have been developed to help manage natural resources all over the world. Nevertheless, most models have presented a high complexity in terms of data base requirements, as well as, many calibration parameters. This has resulted in serious difficulties to application in catchmen...

Analysis of the sensitivity properties of a model of vector-borne bubonic plague.

PubMed

Buzby, Megan; Neckels, David; Antolin, Michael F; Estep, Donald

2008-09-06

Model sensitivity is a key to evaluation of mathematical models in ecology and evolution, especially in complex models with numerous parameters. In this paper, we use some recently developed methods for sensitivity analysis to study the parameter sensitivity of a model of vector-borne bubonic plague in a rodent population proposed by Keeling & Gilligan. The new sensitivity tools are based on a variational analysis involving the adjoint equation. The new approach provides a relatively inexpensive way to obtain derivative information about model output with respect to parameters. We use this approach to determine the sensitivity of a quantity of interest (the force of infection from rats and their fleas to humans) to various model parameters, determine a region over which linearization at a specific parameter reference point is valid, develop a global picture of the output surface, and search for maxima and minima in a given region in the parameter space.

Parameter screening: the use of a dummy parameter to identify non-influential parameters in a global sensitivity analysis

NASA Astrophysics Data System (ADS)

Khorashadi Zadeh, Farkhondeh; Nossent, Jiri; van Griensven, Ann; Bauwens, Willy

2017-04-01

Parameter estimation is a major concern in hydrological modeling, which may limit the use of complex simulators with a large number of parameters. To support the selection of parameters to include in or exclude from the calibration process, Global Sensitivity Analysis (GSA) is widely applied in modeling practices. Based on the results of GSA, the influential and the non-influential parameters are identified (i.e. parameters screening). Nevertheless, the choice of the screening threshold below which parameters are considered non-influential is a critical issue, which has recently received more attention in GSA literature. In theory, the sensitivity index of a non-influential parameter has a value of zero. However, since numerical approximations, rather than analytical solutions, are utilized in GSA methods to calculate the sensitivity indices, small but non-zero indices may be obtained for the indices of non-influential parameters. In order to assess the threshold that identifies non-influential parameters in GSA methods, we propose to calculate the sensitivity index of a "dummy parameter". This dummy parameter has no influence on the model output, but will have a non-zero sensitivity index, representing the error due to the numerical approximation. Hence, the parameters whose indices are above the sensitivity index of the dummy parameter can be classified as influential, whereas the parameters whose indices are below this index are within the range of the numerical error and should be considered as non-influential. To demonstrated the effectiveness of the proposed "dummy parameter approach", 26 parameters of a Soil and Water Assessment Tool (SWAT) model are selected to be analyzed and screened, using the variance-based Sobol' and moment-independent PAWN methods. The sensitivity index of the dummy parameter is calculated from sampled data, without changing the model equations. Moreover, the calculation does not even require additional model evaluations for the Sobol' method. A formal statistical test validates these parameter screening results. Based on the dummy parameter screening, 11 model parameters are identified as influential. Therefore, it can be denoted that the "dummy parameter approach" can facilitate the parameter screening process and provide guidance for GSA users to define a screening-threshold, with only limited additional resources. Key words: Parameter screening, Global sensitivity analysis, Dummy parameter, Variance-based method, Moment-independent method

Method for Constructing Composite Response Surfaces by Combining Neural Networks with Polynominal Interpolation or Estimation Techniques

NASA Technical Reports Server (NTRS)

Rai, Man Mohan (Inventor); Madavan, Nateri K. (Inventor)

2007-01-01

A method and system for data modeling that incorporates the advantages of both traditional response surface methodology (RSM) and neural networks is disclosed. The invention partitions the parameters into a first set of s simple parameters, where observable data are expressible as low order polynomials, and c complex parameters that reflect more complicated variation of the observed data. Variation of the data with the simple parameters is modeled using polynomials; and variation of the data with the complex parameters at each vertex is analyzed using a neural network. Variations with the simple parameters and with the complex parameters are expressed using a first sequence of shape functions and a second sequence of neural network functions. The first and second sequences are multiplicatively combined to form a composite response surface, dependent upon the parameter values, that can be used to identify an accurate mode

Parametrization study of the land multiparameter VTI elastic waveform inversion

NASA Astrophysics Data System (ADS)

He, W.; Plessix, R.-É.; Singh, S.

2018-06-01

Multiparameter inversion of seismic data remains challenging due to the trade-off between the different elastic parameters and the non-uniqueness of the solution. The sensitivity of the seismic data to a given subsurface elastic parameter depends on the source and receiver ray/wave path orientations at the subsurface point. In a high-frequency approximation, this is commonly analysed through the study of the radiation patterns that indicate the sensitivity of each parameter versus the incoming (from the source) and outgoing (to the receiver) angles. In practice, this means that the inversion result becomes sensitive to the choice of parametrization, notably because the null-space of the inversion depends on this choice. We can use a least-overlapping parametrization that minimizes the overlaps between the radiation patterns, in this case each parameter is only sensitive in a restricted angle domain, or an overlapping parametrization that contains a parameter sensitive to all angles, in this case overlaps between the radiation parameters occur. Considering a multiparameter inversion in an elastic vertically transverse isotropic medium and a complex land geological setting, we show that the inversion with the least-overlapping parametrization gives less satisfactory results than with the overlapping parametrization. The difficulties come from the complex wave paths that make difficult to predict the areas of sensitivity of each parameter. This shows that the parametrization choice should not only be based on the radiation pattern analysis but also on the angular coverage at each subsurface point that depends on geology and the acquisition layout.

Derivation of Continuum Models from An Agent-based Cancer Model: Optimization and Sensitivity Analysis.

PubMed

Voulgarelis, Dimitrios; Velayudhan, Ajoy; Smith, Frank

2017-01-01

Agent-based models provide a formidable tool for exploring complex and emergent behaviour of biological systems as well as accurate results but with the drawback of needing a lot of computational power and time for subsequent analysis. On the other hand, equation-based models can more easily be used for complex analysis in a much shorter timescale. This paper formulates an ordinary differential equations and stochastic differential equations model to capture the behaviour of an existing agent-based model of tumour cell reprogramming and applies it to optimization of possible treatment as well as dosage sensitivity analysis. For certain values of the parameter space a close match between the equation-based and agent-based models is achieved. The need for division of labour between the two approaches is explored. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Intrinsic Thermodynamics and Structure Correlation of Benzenesulfonamides with a Pyrimidine Moiety Binding to Carbonic Anhydrases I, II, VII, XII, and XIII

PubMed Central

Kišonaitė, Miglė; Zubrienė, Asta; Čapkauskaitė, Edita; Smirnov, Alexey; Smirnovienė, Joana; Kairys, Visvaldas; Michailovienė, Vilma; Manakova, Elena; Gražulis, Saulius; Matulis, Daumantas

2014-01-01

The early stage of drug discovery is often based on selecting the highest affinity lead compound. To this end the structural and energetic characterization of the binding reaction is important. The binding energetics can be resolved into enthalpic and entropic contributions to the binding Gibbs free energy. Most compound binding reactions are coupled to the absorption or release of protons by the protein or the compound. A distinction between the observed and intrinsic parameters of the binding energetics requires the dissection of the protonation/deprotonation processes. Since only the intrinsic parameters can be correlated with molecular structural perturbations associated with complex formation, it is these parameters that are required for rational drug design. Carbonic anhydrase (CA) isoforms are important therapeutic targets to treat a range of disorders including glaucoma, obesity, epilepsy, and cancer. For effective treatment isoform-specific inhibitors are needed. In this work we investigated the binding and protonation energetics of sixteen [(2-pyrimidinylthio)acetyl]benzenesulfonamide CA inhibitors using isothermal titration calorimetry and fluorescent thermal shift assay. The compounds were built by combining four sulfonamide headgroups with four tailgroups yielding 16 compounds. Their intrinsic binding thermodynamics showed the limitations of the functional group energetic additivity approach used in fragment-based drug design, especially at the level of enthalpies and entropies of binding. Combined with high resolution crystal structural data correlations were drawn between the chemical functional groups on selected inhibitors and intrinsic thermodynamic parameters of CA-inhibitor complex formation. PMID:25493428

Structure-dependent metallokinetics of antidiabetic vanadyl-picolinate complexes in rats: studies on solution structure, insulinomimetic activity, and metallokinetics.

PubMed

Yasui, Hiroyuki; Tamura, Asuka; Takino, Toshikazu; Sakurai, Hiromu

2002-07-25

The insulinomimetic effect of vanadium is the most remarkable and important among its several biological actions. Vanadyl ion (+4 oxidation state of vanadium) and its complexes have been found to normalize the blood glucose levels of both type 1 and 2 diabetic animals. We have developed insulinomimetic vanadyl complexes having different coordination modes, emphasizing the possible usefulness of vanadyl-picolinate [VO(pa)(2)] and its related complexes with the VO(N(2)O(2)) coordination mode. In order to apply these complexes clinically in the future, the relationship between the chemical structure, insulinomimetic action, organ distribution of vanadium, and blood disposition of vanadyl species must be closely investigated. In the present investigation, we studied the blood disposition of the vanadyl-picolinate complexes in healthy rats, and tried to understand comprehensively the relationship between the structures, insulinomimetic activity, and metallokinetic parameters of the complexes, which had been recently prepared and specifically synthesized for the present study, by using an in vivo blood circulation monitoring -- electron spin resonance (BCM-ESR) method for analyzing ESR signals due to paramagnetic metal ions and complexes in the blood in real time. Metallokinetic parameters were estimated based on the blood clearance curves in terms of a two-compartment pharmacokinetic model, and vanadyl species were indicated to be distributed in peripheral tissues and gradually eliminated from the circulating blood, depending on their chemical structures. Vanadyl concentrations in the blood of rats given bis(5-iodopicolinato)oxovanadium(IV) [VO(5ipa)(2)] and bis(3-methylpicolinato)oxovanadium(IV) [VO(3mpa)(2)] with electron-withdrawing and donating groups, respectively, remained significantly higher and longer, due to their slower clearance rates from the blood, than in rats given other complexes, suggesting that the high exposure and long residence of vanadyl species bring about the high normoglyceric effect in diabetic animals. We then examined the relationship between insulinomimetic activity and metallokinetic parameters in the family of VO(pa)(2) for further development of insulinomimetic vanadyl complexes. IC(50), the 50% inhibitory concentration of the complexes on the free fatty acid release from isolated rat adipocytes treated with epinephrine, was found to be sufficiently correlated with metallokinetic parameters such as area under the concentration curve, mean residence time, total clearance, and distribution volume at steady-state. Furthermore, the in vivo antidiabetic activity of the complexes was enhanced with increasing exposure and residence of vanadyl species in the blood of animals. On the basis of these results, we concluded that in vitro insulinomimetic activity, metallokinetic character, and in vivo antidiabetic action of vanadyl-picolinate complexes are closely related to their chemical structures.

78 FR 37870 - Self-Regulatory Organizations; International Securities Exchange, LLC; Notice of Filing of...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-24

... Market Maker Risk Parameters and Complex Orders June 18, 2013. Pursuant to Section 19(b)(1) of the... makers to enter values in the Exchange-provided risk parameters and by limiting the types of complex... complex instruments on the complex order book. Market makers establish a time frame during which the...

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

Wang, Shi-bing, E-mail: wang-shibing@dlut.edu.cn, E-mail: wangxy@dlut.edu.cn; Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024; Wang, Xing-yuan, E-mail: wang-shibing@dlut.edu.cn, E-mail: wangxy@dlut.edu.cn

With comprehensive consideration of generalized synchronization, combination synchronization and adaptive control, this paper investigates a novel adaptive generalized combination complex synchronization (AGCCS) scheme for different real and complex nonlinear systems with unknown parameters. On the basis of Lyapunov stability theory and adaptive control, an AGCCS controller and parameter update laws are derived to achieve synchronization and parameter identification of two real drive systems and a complex response system, as well as two complex drive systems and a real response system. Two simulation examples, namely, ACGCS for chaotic real Lorenz and Chen systems driving a hyperchaotic complex Lü system, and hyperchaoticmore » complex Lorenz and Chen systems driving a real chaotic Lü system, are presented to verify the feasibility and effectiveness of the proposed scheme.« less

An Observation-Driven Agent-Based Modeling and Analysis Framework for C. elegans Embryogenesis.

PubMed

Wang, Zi; Ramsey, Benjamin J; Wang, Dali; Wong, Kwai; Li, Husheng; Wang, Eric; Bao, Zhirong

2016-01-01

With cutting-edge live microscopy and image analysis, biologists can now systematically track individual cells in complex tissues and quantify cellular behavior over extended time windows. Computational approaches that utilize the systematic and quantitative data are needed to understand how cells interact in vivo to give rise to the different cell types and 3D morphology of tissues. An agent-based, minimum descriptive modeling and analysis framework is presented in this paper to study C. elegans embryogenesis. The framework is designed to incorporate the large amounts of experimental observations on cellular behavior and reserve data structures/interfaces that allow regulatory mechanisms to be added as more insights are gained. Observed cellular behaviors are organized into lineage identity, timing and direction of cell division, and path of cell movement. The framework also includes global parameters such as the eggshell and a clock. Division and movement behaviors are driven by statistical models of the observations. Data structures/interfaces are reserved for gene list, cell-cell interaction, cell fate and landscape, and other global parameters until the descriptive model is replaced by a regulatory mechanism. This approach provides a framework to handle the ongoing experiments of single-cell analysis of complex tissues where mechanistic insights lag data collection and need to be validated on complex observations.

Optimal Output of Distributed Generation Based On Complex Power Increment

NASA Astrophysics Data System (ADS)

Wu, D.; Bao, H.

2017-12-01

In order to meet the growing demand for electricity and improve the cleanliness of power generation, new energy generation, represented by wind power generation, photovoltaic power generation, etc has been widely used. The new energy power generation access to distribution network in the form of distributed generation, consumed by local load. However, with the increase of the scale of distribution generation access to the network, the optimization of its power output is becoming more and more prominent, which needs further study. Classical optimization methods often use extended sensitivity method to obtain the relationship between different power generators, but ignore the coupling parameter between nodes makes the results are not accurate; heuristic algorithm also has defects such as slow calculation speed, uncertain outcomes. This article proposes a method called complex power increment, the essence of this method is the analysis of the power grid under steady power flow. After analyzing the results we can obtain the complex scaling function equation between the power supplies, the coefficient of the equation is based on the impedance parameter of the network, so the description of the relation of variables to the coefficients is more precise Thus, the method can accurately describe the power increment relationship, and can obtain the power optimization scheme more accurately and quickly than the extended sensitivity method and heuristic method.

Spectroscopic characterization of metal complexes of novel Schiff base. Synthesis, thermal and biological activity studies

NASA Astrophysics Data System (ADS)

Omar, M. M.; Mohamed, Gehad G.; Ibrahim, Amr A.

2009-07-01

Novel Schiff base (HL) ligand is prepared via condensation of 4-aminoantipyrine and 2-aminobenzoic acid. The ligand is characterized based on elemental analysis, mass, IR and 1H NMR spectra. Metal complexes are reported and characterized based on elemental analyses, IR, 1H NMR, solid reflectance, magnetic moment, molar conductance and thermal analyses (TGA, DrTGA and DTA). The molar conductance data reveal that all the metal chelates are non-electrolytes. IR spectra show that HL is coordinated to the metal ions in a uninegatively tridentate manner with NNO donor sites of the azomethine N, amino N and deprotonated caroxylic-O. From the magnetic and solid reflectance spectra, it is found that the geometrical structures of these complexes are octahedral. The thermal behaviour of these chelates shows that the hydrated complexes losses water molecules of hydration in the first step followed immediately by decomposition of the anions and ligand molecules in the subsequent steps. The activation thermodynamic parameters, such as, E*, ΔH*, ΔS* and ΔG* are calculated from the DrTG curves using Coats-Redfern method. The synthesized ligands, in comparison to their metal complexes also were screened for their antibacterial activity against bacterial species, Escherichia Coli, Pseudomonas aeruginosa, Staphylococcus Pyogones and Fungi (Candida). The activity data show that the metal complexes to be more potent/antibacterial than the parent Shciff base ligand against one or more bacterial species.

Uncertainty in temperature-based determination of time of death

NASA Astrophysics Data System (ADS)

Weiser, Martin; Erdmann, Bodo; Schenkl, Sebastian; Muggenthaler, Holger; Hubig, Michael; Mall, Gita; Zachow, Stefan

2018-03-01

Temperature-based estimation of time of death (ToD) can be performed either with the help of simple phenomenological models of corpse cooling or with detailed mechanistic (thermodynamic) heat transfer models. The latter are much more complex, but allow a higher accuracy of ToD estimation as in principle all relevant cooling mechanisms can be taken into account. The potentially higher accuracy depends on the accuracy of tissue and environmental parameters as well as on the geometric resolution. We investigate the impact of parameter variations and geometry representation on the estimated ToD. For this, numerical simulation of analytic heat transport models is performed on a highly detailed 3D corpse model, that has been segmented and geometrically reconstructed from a computed tomography (CT) data set, differentiating various organs and tissue types. From that and prior information available on thermal parameters and their variability, we identify the most crucial parameters to measure or estimate, and obtain an a priori uncertainty quantification for the ToD.

Spectral gap optimization of order parameters for sampling complex molecular systems

PubMed Central

Tiwary, Pratyush; Berne, B. J.

2016-01-01

In modern-day simulations of many-body systems, much of the computational complexity is shifted to the identification of slowly changing molecular order parameters called collective variables (CVs) or reaction coordinates. A vast array of enhanced-sampling methods are based on the identification and biasing of these low-dimensional order parameters, whose fluctuations are important in driving rare events of interest. Here, we describe a new algorithm for finding optimal low-dimensional CVs for use in enhanced-sampling biasing methods like umbrella sampling, metadynamics, and related methods, when limited prior static and dynamic information is known about the system, and a much larger set of candidate CVs is specified. The algorithm involves estimating the best combination of these candidate CVs, as quantified by a maximum path entropy estimate of the spectral gap for dynamics viewed as a function of that CV. The algorithm is called spectral gap optimization of order parameters (SGOOP). Through multiple practical examples, we show how this postprocessing procedure can lead to optimization of CV and several orders of magnitude improvement in the convergence of the free energy calculated through metadynamics, essentially giving the ability to extract useful information even from unsuccessful metadynamics runs. PMID:26929365

Effect of the nature of phospholipids on the degree of their interaction with isobornylphenol antioxidants

NASA Astrophysics Data System (ADS)

Marakulina, K. M.; Kramor, R. V.; Lukanina, Yu. K.; Plashchina, I. G.; Polyakov, A. V.; Fedorova, I. V.; Chukicheva, I. Yu.; Kutchin, A. V.; Shishkina, L. N.

2016-02-01

The parameters of complexation between natural phospholipids (lecithin, sphingomyelin, and cephalin) with antioxidants of a new class, isobornylphenols (IBPs), were determined by UV and IR spectroscopy. The self-organization of phospholipids (PLs) was studied depending on the structure of IBPs by dynamic light scattering. The nature of phospholipids and the structure of IBPs was found to produce a substantial effect both on the degree of complexation and on the size of PL aggregates in a nonpolar solvent. Based on the obtained data it was concluded that the structure of biological membranes mainly depends on the complexation of IBP with sphingomyelin.

Small-time Scale Network Traffic Prediction Based on Complex-valued Neural Network

NASA Astrophysics Data System (ADS)

Yang, Bin

2017-07-01

Accurate models play an important role in capturing the significant characteristics of the network traffic, analyzing the network dynamic, and improving the forecasting accuracy for system dynamics. In this study, complex-valued neural network (CVNN) model is proposed to further improve the accuracy of small-time scale network traffic forecasting. Artificial bee colony (ABC) algorithm is proposed to optimize the complex-valued and real-valued parameters of CVNN model. Small-scale traffic measurements data namely the TCP traffic data is used to test the performance of CVNN model. Experimental results reveal that CVNN model forecasts the small-time scale network traffic measurement data very accurately

Intercalation of a Zn(II) complex containing ciprofloxacin drug between DNA base pairs.

PubMed

Shahabadi, Nahid; Asadian, Ali Ashraf; Mahdavi, Mryam

2017-11-02

In this study, an attempt has been made to study the interaction of a Zn(II) complex containing an antibiotic drug, ciprofloxacin, with calf thymus DNA using spectroscopic methods. It was found that Zn(II) complex could bind with DNA via intercalation mode as evidenced by: hyperchromism in UV-Vis spectrum; these spectral characteristics suggest that the Zn(II) complex interacts with DNA most likely through a mode that involves a stacking interaction between the aromatic chromophore and the base pairs of DNA. DNA binding constant (K b = 1.4 × 10 4 M -1 ) from spectrophotometric studies of the interaction of Zn(II) complex with DNA is comparable to those of some DNA intercalative polypyridyl Ru(II) complexes 1.0 -4.8 × 10 4 M -1 . CD study showed stabilization of the right-handed B form of DNA in the presence of Zn(II) complex as observed for the classical intercalator methylene blue. Thermodynamic parameters (ΔH < 0 and ΔS < 0) indicated that hydrogen bond and Van der Waals play main roles in this binding prose. Competitive fluorimetric studies with methylene blue (MB) dye have shown that Zn(II) complex exhibits the ability of this complex to displace with DNA-MB, indicating that it binds to DNA in strong competition with MB for the intercalation.

Accurate detection of hierarchical communities in complex networks based on nonlinear dynamical evolution

NASA Astrophysics Data System (ADS)

Zhuo, Zhao; Cai, Shi-Min; Tang, Ming; Lai, Ying-Cheng

2018-04-01

One of the most challenging problems in network science is to accurately detect communities at distinct hierarchical scales. Most existing methods are based on structural analysis and manipulation, which are NP-hard. We articulate an alternative, dynamical evolution-based approach to the problem. The basic principle is to computationally implement a nonlinear dynamical process on all nodes in the network with a general coupling scheme, creating a networked dynamical system. Under a proper system setting and with an adjustable control parameter, the community structure of the network would "come out" or emerge naturally from the dynamical evolution of the system. As the control parameter is systematically varied, the community hierarchies at different scales can be revealed. As a concrete example of this general principle, we exploit clustered synchronization as a dynamical mechanism through which the hierarchical community structure can be uncovered. In particular, for quite arbitrary choices of the nonlinear nodal dynamics and coupling scheme, decreasing the coupling parameter from the global synchronization regime, in which the dynamical states of all nodes are perfectly synchronized, can lead to a weaker type of synchronization organized as clusters. We demonstrate the existence of optimal choices of the coupling parameter for which the synchronization clusters encode accurate information about the hierarchical community structure of the network. We test and validate our method using a standard class of benchmark modular networks with two distinct hierarchies of communities and a number of empirical networks arising from the real world. Our method is computationally extremely efficient, eliminating completely the NP-hard difficulty associated with previous methods. The basic principle of exploiting dynamical evolution to uncover hidden community organizations at different scales represents a "game-change" type of approach to addressing the problem of community detection in complex networks.

Charge transfer complex between 2,3-diaminopyridine with chloranilic acid. Synthesis, characterization and DFT, TD-DFT computational studies

NASA Astrophysics Data System (ADS)

Al-Ahmary, Khairia M.; Habeeb, Moustafa M.; Al-Obidan, Areej H.

2018-05-01

New charge transfer complex (CTC) between the electron donor 2,3-diaminopyridine (DAP) with the electron acceptor chloranilic (CLA) acid has been synthesized and characterized experimentally and theoretically using a variety of physicochemical techniques. The experimental work included the use of elemental analysis, UV-vis, IR and 1H NMR studies to characterize the complex. Electronic spectra have been carried out in different hydrogen bonded solvents, methanol (MeOH), acetonitrile (AN) and 1:1 mixture from AN-MeOH. The molecular composition of the complex was identified to be 1:1 from Jobs and molar ratio methods. The stability constant was determined using minimum-maximum absorbances method where it recorded high values confirming the high stability of the formed complex. The solid complex was prepared and characterized by elemental analysis that confirmed its formation in 1:1 stoichiometric ratio. Both IR and NMR studies asserted the existence of proton and charge transfers in the formed complex. For supporting the experimental results, DFT computations were carried out using B3LYP/6-31G(d,p) method to compute the optimized structures of the reactants and complex, their geometrical parameters, reactivity parameters, molecular electrostatic potential map and frontier molecular orbitals. The analysis of DFT results strongly confirmed the high stability of the formed complex based on existing charge transfer beside proton transfer hydrogen bonding concordant with experimental results. The origin of electronic spectra was analyzed using TD-DFT method where the observed λmax are strongly consisted with the computed ones. TD-DFT showed the contributed states for various electronic transitions.

Synthesis and spectral characterization of mono- and binuclear copper(II) complexes derived from 2-benzoylpyridine-N⁴-methyl-3-thiosemicarbazone: crystal structure of a novel sulfur bridged copper(II) box-dimer.

PubMed

Jayakumar, K; Sithambaresan, M; Aiswarya, N; Kurup, M R Prathapachandra

2015-03-15

Mononuclear and binuclear copper(II) complexes of 2-benzoylpyridine-N(4)-methyl thiosemicarbazone (HL) were prepared and characterized by a variety of spectroscopic techniques. Structural evidence for the novel sulfur bridged copper(II) iodo binuclear complex is obtained by single crystal X-ray diffraction analysis. The complex [Cu2L2I2], a non-centrosymmetric box dimer, crystallizes in monoclinic C2/c space group and it was found to have distorted square pyramidal geometry (Addison parameter, τ=0.238) with the square basal plane occupied by the thiosemicarbazone moiety and iodine atom whereas the sulfur atom from the other coordinated thiosemicarbazone moiety occupies the apical position. This is the first crystallographically studied system having non-centrosymmetrical entities bridged via thiolate S atoms with Cu(II)I bond. The tridentate thiosemicarbazone coordinates in mono deprotonated thionic tautomeric form in all complexes except in sulfato complex, [Cu(HL)(SO4)]·H2O (1) where it binds to the metal centre in neutral form. The magnetic moment values and the EPR spectral studies reflect the binuclearity of some of the complexes. The spin Hamiltonian and bonding parameters are calculated based on EPR studies. In all the complexes g||>g⊥>2.0023 and the g values in frozen DMF are consistent with the d(x2-y2) ground state. The thermal stabilities of some of the complexes were also determined. Copyright © 2014 Elsevier B.V. All rights reserved.

Genome-wide predicting disease-related protein complexes by walking on the heterogeneous network based on data integration and laplacian normalization.

PubMed

Liu, Zhiming; Luo, Jiawei

2017-08-01

Associating protein complexes to human inherited diseases is critical for better understanding of biological processes and functional mechanisms of the disease. Many protein complexes have been identified and functionally annotated by computational and purification methods so far, however, the particular roles they were playing in causing disease have not yet been well determined. In this study, we present a novel method to identify associations between protein complexes and diseases. First, we construct a disease-protein heterogeneous network based on data integration and laplacian normalization. Second, we apply a random walk with restart on heterogeneous network (RWRH) algorithm on this network to quantify the strength of the association between proteins and the query disease. Third, we sum over the scores of member proteins to obtain a summary score for each candidate protein complex, and then rank all candidate protein complexes according to their scores. With a series of leave-one-out cross-validation experiments, we found that our method not only possesses high performance but also demonstrates robustness regarding the parameters and the network structure. We test our approach with breast cancer and select top 20 highly ranked protein complexes, 17 of the selected protein complexes are evidenced to be connected with breast cancer. Our proposed method is effective in identifying disease-related protein complexes based on data integration and laplacian normalization. Copyright © 2017. Published by Elsevier Ltd.

Ab Initio Crystal Field for Lanthanides.

PubMed

Ungur, Liviu; Chibotaru, Liviu F

2017-03-13

An ab initio methodology for the first-principle derivation of crystal-field (CF) parameters for lanthanides is described. The methodology is applied to the analysis of CF parameters in [Tb(Pc) 2 ] - (Pc=phthalocyanine) and Dy 4 K 2 ([Dy 4 K 2 O(OtBu) 12 ]) complexes, and compared with often used approximate and model descriptions. It is found that the application of geometry symmetrization, and the use of electrostatic point-charge and phenomenological CF models, lead to unacceptably large deviations from predictions based on ab initio calculations for experimental geometry. It is shown how the predictions of standard CASSCF (Complete Active Space Self-Consistent Field) calculations (with 4f orbitals in the active space) can be systematically improved by including effects of dynamical electronic correlation (CASPT2 step) and by admixing electronic configurations of the 5d shell. This is exemplified for the well-studied Er-trensal complex (H 3 trensal=2,2',2"-tris(salicylideneimido)trimethylamine). The electrostatic contributions to CF parameters in this complex, calculated with true charge distributions in the ligands, yield less than half of the total CF splitting, thus pointing to the dominant role of covalent effects. This analysis allows the conclusion that ab initio crystal field is an essential tool for the decent description of lanthanides. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Study of T-wave morphology parameters based on Principal Components Analysis during acute myocardial ischemia

NASA Astrophysics Data System (ADS)

Baglivo, Fabricio Hugo; Arini, Pedro David

2011-12-01

Electrocardiographic repolarization abnormalities can be detected by Principal Components Analysis of the T-wave. In this work we studied the efect of signal averaging on the mean value and reproducibility of the ratio of the 2nd to the 1st eigenvalue of T-wave (T21W) and the absolute and relative T-wave residuum (TrelWR and TabsWR) in the ECG during ischemia induced by Percutaneous Coronary Intervention. Also, the intra-subject and inter-subject variability of T-wave parameters have been analyzed. Results showed that TrelWR and TabsWR evaluated from the average of 10 complexes had lower values and higher reproducibility than those obtained from 1 complex. On the other hand T21W calculated from 10 complexes did not show statistical diferences versus the T21W calculated on single beats. The results of this study corroborate that, with a signal averaging technique, the 2nd and the 1st eigenvalue are not afected by noise while the 4th to 8th eigenvalues are so much afected by this, suggesting the use of the signal averaged technique before calculation of absolute and relative T-wave residuum. Finally, we have shown that T-wave morphology parameters present high intra-subject stability.

High dimensional model representation method for fuzzy structural dynamics

NASA Astrophysics Data System (ADS)

Adhikari, S.; Chowdhury, R.; Friswell, M. I.

2011-03-01

Uncertainty propagation in multi-parameter complex structures possess significant computational challenges. This paper investigates the possibility of using the High Dimensional Model Representation (HDMR) approach when uncertain system parameters are modeled using fuzzy variables. In particular, the application of HDMR is proposed for fuzzy finite element analysis of linear dynamical systems. The HDMR expansion is an efficient formulation for high-dimensional mapping in complex systems if the higher order variable correlations are weak, thereby permitting the input-output relationship behavior to be captured by the terms of low-order. The computational effort to determine the expansion functions using the α-cut method scales polynomically with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is first illustrated for multi-parameter nonlinear mathematical test functions with fuzzy variables. The method is then integrated with a commercial finite element software (ADINA). Modal analysis of a simplified aircraft wing with fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations. It is shown that using the proposed HDMR approach, the number of finite element function calls can be reduced without significantly compromising the accuracy.

Simultaneous versus sequential optimal experiment design for the identification of multi-parameter microbial growth kinetics as a function of temperature.

PubMed

Van Derlinden, E; Bernaerts, K; Van Impe, J F

2010-05-21

Optimal experiment design for parameter estimation (OED/PE) has become a popular tool for efficient and accurate estimation of kinetic model parameters. When the kinetic model under study encloses multiple parameters, different optimization strategies can be constructed. The most straightforward approach is to estimate all parameters simultaneously from one optimal experiment (single OED/PE strategy). However, due to the complexity of the optimization problem or the stringent limitations on the system's dynamics, the experimental information can be limited and parameter estimation convergence problems can arise. As an alternative, we propose to reduce the optimization problem to a series of two-parameter estimation problems, i.e., an optimal experiment is designed for a combination of two parameters while presuming the other parameters known. Two different approaches can be followed: (i) all two-parameter optimal experiments are designed based on identical initial parameter estimates and parameters are estimated simultaneously from all resulting experimental data (global OED/PE strategy), and (ii) optimal experiments are calculated and implemented sequentially whereby the parameter values are updated intermediately (sequential OED/PE strategy). This work exploits OED/PE for the identification of the Cardinal Temperature Model with Inflection (CTMI) (Rosso et al., 1993). This kinetic model describes the effect of temperature on the microbial growth rate and encloses four parameters. The three OED/PE strategies are considered and the impact of the OED/PE design strategy on the accuracy of the CTMI parameter estimation is evaluated. Based on a simulation study, it is observed that the parameter values derived from the sequential approach deviate more from the true parameters than the single and global strategy estimates. The single and global OED/PE strategies are further compared based on experimental data obtained from design implementation in a bioreactor. Comparable estimates are obtained, but global OED/PE estimates are, in general, more accurate and reliable. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

SDS-binding assay based on tyrosine fluorescence as a tool to determine binding properties of human serum albumin in blood plasma

NASA Astrophysics Data System (ADS)

Zhdanova, Nadezda; Shirshin, Evgeny; Fadeev, Victor; Priezzhev, Alexander

2016-04-01

Among all plasma proteins human serum albumin (HSA) is the most studied one as it is the main transport protein and can bind a wide variety of ligands especially fatty acids (FAs). The concentration of FAs bound to HSA in human blood plasma differs by three times under abnormal conditions (fasting, physical exercises or in case of social important diseases). In the present study a surfactant sodium dodecyl sulfate (SDS) was used to simulate FAs binding to HSA. It was shown that the increase of Tyr fluorescence of human blood plasma due to SDS addition can be completely explained by HSA-SDS complex formation. Binding parameters of SDS-HSA complex (average number of sites and apparent constant of complex formation) were determined from titration curves based on tyrosine (Tyr) fluorescence.

Complexity reduction of biochemical rate expressions.

PubMed

Schmidt, Henning; Madsen, Mads F; Danø, Sune; Cedersund, Gunnar

2008-03-15

The current trend in dynamical modelling of biochemical systems is to construct more and more mechanistically detailed and thus complex models. The complexity is reflected in the number of dynamic state variables and parameters, as well as in the complexity of the kinetic rate expressions. However, a greater level of complexity, or level of detail, does not necessarily imply better models, or a better understanding of the underlying processes. Data often does not contain enough information to discriminate between different model hypotheses, and such overparameterization makes it hard to establish the validity of the various parts of the model. Consequently, there is an increasing demand for model reduction methods. We present a new reduction method that reduces complex rational rate expressions, such as those often used to describe enzymatic reactions. The method is a novel term-based identifiability analysis, which is easy to use and allows for user-specified reductions of individual rate expressions in complete models. The method is one of the first methods to meet the classical engineering objective of improved parameter identifiability without losing the systems biology demand of preserved biochemical interpretation. The method has been implemented in the Systems Biology Toolbox 2 for MATLAB, which is freely available from http://www.sbtoolbox2.org. The Supplementary Material contains scripts that show how to use it by applying the method to the example models, discussed in this article.

Application of Biologically Based Lumping To Investigate the Toxicokinetic Interactions of a Complex Gasoline Mixture.

PubMed

Jasper, Micah N; Martin, Sheppard A; Oshiro, Wendy M; Ford, Jermaine; Bushnell, Philip J; El-Masri, Hisham

2016-03-15

People are often exposed to complex mixtures of environmental chemicals such as gasoline, tobacco smoke, water contaminants, or food additives. We developed an approach that applies chemical lumping methods to complex mixtures, in this case gasoline, based on biologically relevant parameters used in physiologically based pharmacokinetic (PBPK) modeling. Inhalation exposures were performed with rats to evaluate the performance of our PBPK model and chemical lumping method. There were 109 chemicals identified and quantified in the vapor in the chamber. The time-course toxicokinetic profiles of 10 target chemicals were also determined from blood samples collected during and following the in vivo experiments. A general PBPK model was used to compare the experimental data to the simulated values of blood concentration for 10 target chemicals with various numbers of lumps, iteratively increasing from 0 to 99. Large reductions in simulation error were gained by incorporating enzymatic chemical interactions, in comparison to simulating the individual chemicals separately. The error was further reduced by lumping the 99 nontarget chemicals. The same biologically based lumping approach can be used to simplify any complex mixture with tens, hundreds, or thousands of constituents.

SU-F-P-64: The Impact of Plan Complexity Parameters On the Plan Quality and Deliverability of Volumetric Modulated Arc Therapy with Canonical Correlation Analysis

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

Jin, X; Yi, J; Xie, C

Purpose: To evaluate the impact of complexity indices on the plan quality and deliverability of volumetric modulated arc therapy (VMAT), and to determine the most significant parameters in the generation of an ideal VMAT plan. Methods: A multi-dimensional exploratory statistical method, canonical correlation analysis (CCA) was adopted to study the correlations between VMAT parameters of complexity, quality and deliverability, as well as their contribution weights with 32 two-arc VMAT nasopharyngeal cancer (NPC) patients and 31 one-arc VMAT prostate cancer patients. Results: The MU per arc (MU/Arc) and MU per control point (MU/CP) of NPC were 337.8±25.2 and 3.7±0.3, respectively, whichmore » were significantly lower than those of prostate cancer patients (MU/Arc : 506.9±95.4, MU/CP : 5.6±1.1). The plan complexity indices indicated that two-arc VMAT plans were more complex than one-arc VMAT plans. Plan quality comparison confirmed that one-arc VMAT plans had a high quality than two-arc VMAT plans. CCA results implied that plan complexity parameters were highly correlated with plan quality with the first two canonical correlations of 0.96, 0.88 (both p<0.001) and significantly correlated with deliverability with the first canonical correlation of 0.79 (p<0.001), plan quality and deliverability was also correlated with the first canonical correlation of 0.71 (p=0.02). Complexity parameters of MU/CP, segment area (SA) per CP, percent of MU/CP less 3 and planning target volume (PTV) were weighted heavily in correlation with plan quality and deliveability . Similar results obtained from individual NPC and prostate CCA analysis. Conclusion: Relationship between complexity, quality, and deliverability parameters were investigated with CCA. MU, SA related parameters and PTV volume were found to have strong effect on the plan quality and deliverability. The presented correlation among different quantified parameters could be used to improve the plan quality and the efficiency of the radiotherapy process when creating a complex VMAT plan.« less

Quantitative Assessment of Heart Rate Dynamics during Meditation: An ECG Based Study with Multi-Fractality and Visibility Graph

PubMed Central

Bhaduri, Anirban; Ghosh, Dipak

2016-01-01

The cardiac dynamics during meditation is explored quantitatively with two chaos-based non-linear techniques viz. multi-fractal detrended fluctuation analysis and visibility network analysis techniques. The data used are the instantaneous heart rate (in beats/minute) of subjects performing Kundalini Yoga and Chi meditation from PhysioNet. The results show consistent differences between the quantitative parameters obtained by both the analysis techniques. This indicates an interesting phenomenon of change in the complexity of the cardiac dynamics during meditation supported with quantitative parameters. The results also produce a preliminary evidence that these techniques can be used as a measure of physiological impact on subjects performing meditation. PMID:26909045

Quantitative Assessment of Heart Rate Dynamics during Meditation: An ECG Based Study with Multi-Fractality and Visibility Graph.

PubMed

Bhaduri, Anirban; Ghosh, Dipak

2016-01-01

The cardiac dynamics during meditation is explored quantitatively with two chaos-based non-linear techniques viz. multi-fractal detrended fluctuation analysis and visibility network analysis techniques. The data used are the instantaneous heart rate (in beats/minute) of subjects performing Kundalini Yoga and Chi meditation from PhysioNet. The results show consistent differences between the quantitative parameters obtained by both the analysis techniques. This indicates an interesting phenomenon of change in the complexity of the cardiac dynamics during meditation supported with quantitative parameters. The results also produce a preliminary evidence that these techniques can be used as a measure of physiological impact on subjects performing meditation.

An Idealized, Single Radial Swirler, Lean-Direct-Injection (LDI) Concept Meshing Script

NASA Technical Reports Server (NTRS)

Iannetti, Anthony C.; Thompson, Daniel

2008-01-01

To easily study combustor design parameters using computational fluid dynamics codes (CFD), a Gridgen Glyph-based macro (based on the Tcl scripting language) dubbed BladeMaker has been developed for the meshing of an idealized, single radial swirler, lean-direct-injection (LDI) combustor. BladeMaker is capable of taking in a number of parameters, such as blade width, blade tilt with respect to the perpendicular, swirler cup radius, and grid densities, and producing a three-dimensional meshed radial swirler with a can-annular (canned) combustor. This complex script produces a data format suitable for but not specific to the National Combustion Code (NCC), a state-of-the-art CFD code developed for reacting flow processes.

Evaluation of Several Two-Step Scoring Functions Based on Linear Interaction Energy, Effective Ligand Size, and Empirical Pair Potentials for Prediction of Protein-Ligand Binding Geometry and Free Energy

PubMed Central

Rahaman, Obaidur; Estrada, Trilce P.; Doren, Douglas J.; Taufer, Michela; Brooks, Charles L.; Armen, Roger S.

2011-01-01

The performance of several two-step scoring approaches for molecular docking were assessed for their ability to predict binding geometries and free energies. Two new scoring functions designed for “step 2 discrimination” were proposed and compared to our CHARMM implementation of the linear interaction energy (LIE) approach using the Generalized-Born with Molecular Volume (GBMV) implicit solvation model. A scoring function S1 was proposed by considering only “interacting” ligand atoms as the “effective size” of the ligand, and extended to an empirical regression-based pair potential S2. The S1 and S2 scoring schemes were trained and five-fold cross validated on a diverse set of 259 protein-ligand complexes from the Ligand Protein Database (LPDB). The regression-based parameters for S1 and S2 also demonstrated reasonable transferability in the CSARdock 2010 benchmark using a new dataset (NRC HiQ) of diverse protein-ligand complexes. The ability of the scoring functions to accurately predict ligand geometry was evaluated by calculating the discriminative power (DP) of the scoring functions to identify native poses. The parameters for the LIE scoring function with the optimal discriminative power (DP) for geometry (step 1 discrimination) were found to be very similar to the best-fit parameters for binding free energy over a large number of protein-ligand complexes (step 2 discrimination). Reasonable performance of the scoring functions in enrichment of active compounds in four different protein target classes established that the parameters for S1 and S2 provided reasonable accuracy and transferability. Additional analysis was performed to definitively separate scoring function performance from molecular weight effects. This analysis included the prediction of ligand binding efficiencies for a subset of the CSARdock NRC HiQ dataset where the number of ligand heavy atoms ranged from 17 to 35. This range of ligand heavy atoms is where improved accuracy of predicted ligand efficiencies is most relevant to real-world drug design efforts. PMID:21644546

Evaluation of several two-step scoring functions based on linear interaction energy, effective ligand size, and empirical pair potentials for prediction of protein-ligand binding geometry and free energy.

PubMed

Rahaman, Obaidur; Estrada, Trilce P; Doren, Douglas J; Taufer, Michela; Brooks, Charles L; Armen, Roger S

2011-09-26

The performances of several two-step scoring approaches for molecular docking were assessed for their ability to predict binding geometries and free energies. Two new scoring functions designed for "step 2 discrimination" were proposed and compared to our CHARMM implementation of the linear interaction energy (LIE) approach using the Generalized-Born with Molecular Volume (GBMV) implicit solvation model. A scoring function S1 was proposed by considering only "interacting" ligand atoms as the "effective size" of the ligand and extended to an empirical regression-based pair potential S2. The S1 and S2 scoring schemes were trained and 5-fold cross-validated on a diverse set of 259 protein-ligand complexes from the Ligand Protein Database (LPDB). The regression-based parameters for S1 and S2 also demonstrated reasonable transferability in the CSARdock 2010 benchmark using a new data set (NRC HiQ) of diverse protein-ligand complexes. The ability of the scoring functions to accurately predict ligand geometry was evaluated by calculating the discriminative power (DP) of the scoring functions to identify native poses. The parameters for the LIE scoring function with the optimal discriminative power (DP) for geometry (step 1 discrimination) were found to be very similar to the best-fit parameters for binding free energy over a large number of protein-ligand complexes (step 2 discrimination). Reasonable performance of the scoring functions in enrichment of active compounds in four different protein target classes established that the parameters for S1 and S2 provided reasonable accuracy and transferability. Additional analysis was performed to definitively separate scoring function performance from molecular weight effects. This analysis included the prediction of ligand binding efficiencies for a subset of the CSARdock NRC HiQ data set where the number of ligand heavy atoms ranged from 17 to 35. This range of ligand heavy atoms is where improved accuracy of predicted ligand efficiencies is most relevant to real-world drug design efforts.

Delineating parameter unidentifiabilities in complex models

NASA Astrophysics Data System (ADS)

Raman, Dhruva V.; Anderson, James; Papachristodoulou, Antonis

2017-03-01

Scientists use mathematical modeling as a tool for understanding and predicting the properties of complex physical systems. In highly parametrized models there often exist relationships between parameters over which model predictions are identical, or nearly identical. These are known as structural or practical unidentifiabilities, respectively. They are hard to diagnose and make reliable parameter estimation from data impossible. They furthermore imply the existence of an underlying model simplification. We describe a scalable method for detecting unidentifiabilities, as well as the functional relations defining them, for generic models. This allows for model simplification, and appreciation of which parameters (or functions thereof) cannot be estimated from data. Our algorithm can identify features such as redundant mechanisms and fast time-scale subsystems, as well as the regimes in parameter space over which such approximations are valid. We base our algorithm on a quantification of regional parametric sensitivity that we call `multiscale sloppiness'. Traditionally, the link between parametric sensitivity and the conditioning of the parameter estimation problem is made locally, through the Fisher information matrix. This is valid in the regime of infinitesimal measurement uncertainty. We demonstrate the duality between multiscale sloppiness and the geometry of confidence regions surrounding parameter estimates made where measurement uncertainty is non-negligible. Further theoretical relationships are provided linking multiscale sloppiness to the likelihood-ratio test. From this, we show that a local sensitivity analysis (as typically done) is insufficient for determining the reliability of parameter estimation, even with simple (non)linear systems. Our algorithm can provide a tractable alternative. We finally apply our methods to a large-scale, benchmark systems biology model of necrosis factor (NF)-κ B , uncovering unidentifiabilities.

Lidar inelastic multiple-scattering parameters of cirrus particle ensembles determined with geometrical-optics crystal phase functions.

PubMed

Reichardt, J; Hess, M; Macke, A

2000-04-20

Multiple-scattering correction factors for cirrus particle extinction coefficients measured with Raman and high spectral resolution lidars are calculated with a radiative-transfer model. Cirrus particle-ensemble phase functions are computed from single-crystal phase functions derived in a geometrical-optics approximation. Seven crystal types are considered. In cirrus clouds with height-independent particle extinction coefficients the general pattern of the multiple-scattering parameters has a steep onset at cloud base with values of 0.5-0.7 followed by a gradual and monotonic decrease to 0.1-0.2 at cloud top. The larger the scattering particles are, the more gradual is the rate of decrease. Multiple-scattering parameters of complex crystals and of imperfect hexagonal columns and plates can be well approximated by those of projected-area equivalent ice spheres, whereas perfect hexagonal crystals show values as much as 70% higher than those of spheres. The dependencies of the multiple-scattering parameters on cirrus particle spectrum, base height, and geometric depth and on the lidar parameters laser wavelength and receiver field of view, are discussed, and a set of multiple-scattering parameter profiles for the correction of extinction measurements in homogeneous cirrus is provided.

A three-dimensional bioprinting system for use with a hydrogel-based biomaterial and printing parameter characterization.

PubMed

Song, Seung-Joon; Choi, Jaesoon; Park, Yong-Doo; Lee, Jung-Joo; Hong, So Young; Sun, Kyung

2010-11-01

Bioprinting is an emerging technology for constructing tissue or bioartificial organs with complex three-dimensional (3D) structures. It provides high-precision spatial shape forming ability on a larger scale than conventional tissue engineering methods, and simultaneous multiple components composition ability. Bioprinting utilizes a computer-controlled 3D printer mechanism for 3D biological structure construction. To implement minimal pattern width in a hydrogel-based bioprinting system, a study on printing characteristics was performed by varying printer control parameters. The experimental results showed that printing pattern width depends on associated printer control parameters such as printing flow rate, nozzle diameter, and nozzle velocity. The system under development showed acceptable feasibility of potential use for accurate printing pattern implementation in tissue engineering applications and is another example of novel techniques for regenerative medicine based on computer-aided biofabrication system. © 2010, Copyright the Authors. Artificial Organs © 2010, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

On the performance of energy detection-based CR with SC diversity over IG channel

NASA Astrophysics Data System (ADS)

Verma, Pappu Kumar; Soni, Sanjay Kumar; Jain, Priyanka

2017-12-01

Cognitive radio (CR) is a viable 5G technology to address the scarcity of the spectrum. Energy detection-based sensing is known to be the simplest method as far as hardware complexity is concerned. In this paper, the performance of spectrum sensing-based energy detection technique in CR networks over inverse Gaussian channel for selection combining diversity technique is analysed. More specifically, accurate analytical expressions for the average detection probability under different detection scenarios such as single channel (no diversity) and with diversity reception are derived and evaluated. Further, the detection threshold parameter is optimised by minimising the probability of error over several diversity branches. The results clearly show the significant improvement in the probability of detection when optimised threshold parameter is applied. The impact of shadowing parameters on the performance of energy detector is studied in terms of complimentary receiver operating characteristic curve. To verify the correctness of our analysis, the derived analytical expressions are corroborated via exact result and Monte Carlo simulations.

Accounting for Intraligand Interactions in Flexible Ligand Docking with a PMF-Based Scoring Function.

PubMed

Lizunov, A Y; Gonchar, A L; Zaitseva, N I; Zosimov, V V

2015-10-26

We analyzed the frequency with which intraligand contacts occurred in a set of 1300 protein-ligand complexes [ Plewczynski et al. J. Comput. Chem. 2011 , 32 , 742 - 755 .]. Our analysis showed that flexible ligands often form intraligand hydrophobic contacts, while intraligand hydrogen bonds are rare. The test set was also thoroughly investigated and classified. We suggest a universal method for enhancement of a scoring function based on a potential of mean force (PMF-based score) by adding a term accounting for intraligand interactions. The method was implemented via in-house developed program, utilizing an Algo_score scoring function [ Ramensky et al. Proteins: Struct., Funct., Genet. 2007 , 69 , 349 - 357 .] based on the Tarasov-Muryshev PMF [ Muryshev et al. J. Comput.-Aided Mol. Des. 2003 , 17 , 597 - 605 .]. The enhancement of the scoring function was shown to significantly improve the docking and scoring quality for flexible ligands in the test set of 1300 protein-ligand complexes [ Plewczynski et al. J. Comput. Chem. 2011 , 32 , 742 - 755 .]. We then investigated the correlation of the docking results with two parameters of intraligand interactions estimation. These parameters are the weight of intraligand interactions and the minimum number of bonds between the ligand atoms required to take their interaction into account.

Preparation, characterization and biological activity of novel metal-NNNN donor Schiff base complexes

NASA Astrophysics Data System (ADS)

Mohamed, Gehad G.; Omar, M. M.; Ibrahim, Amr A.

2010-02-01

Novel Schiff base (H 2L) ligand is prepared via condensation of benzil and triethylenetetraamine. The ligand is characterized based on elemental analysis, mass, IR and 1H NMR spectra. Metal complexes are reported and characterized based on elemental analyses, IR, 1H NMR, solid reflectance, magnetic moment, molar conductance, and thermal analyses (TG, DTG and DTA). 1:1 [M]:[H 2L] complexes are found from the elemental analyses data having the formulae [M(H 2L)Cl 2]· yH 2O (M = Mn(II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II)), [Fe(H 2L)Cl 2]Cl·H 2O, [Th(H 2L)Cl 2]Cl 2·3H 2O and [UO 2(H 2L)](CH 3COO) 2·2H 2O. The metal chelates are found to be non-electrolytes except Fe(III), Th(IV) and UO 2(II) complexes are electrolytes. IR spectra show that H 2L is coordinated to the metal ions in a neutral tetradentate manner with 4Ns donor sites of the two azomethine N and two NH groups. The geometrical structures of these complexes are found to be octahedral. The thermal behaviour of these chelates is studied where the hydrated complexes lose water molecules of hydration in the first step followed immediately by decomposition of the anions and ligand molecules in the subsequent steps. The activation thermodynamic parameters are calculated using Coats-Redfern method. The ligand (H 2L), in comparison to its metal complexes, is screened for its antibacterial activity. The activity data show that the metal complexes have antibacterial activity more than the parent Schiff base ligand and cefepime standard against one or more bacterial species.

DGSA: A Matlab toolbox for distance-based generalized sensitivity analysis of geoscientific computer experiments

NASA Astrophysics Data System (ADS)

Park, Jihoon; Yang, Guang; Satija, Addy; Scheidt, Céline; Caers, Jef

2016-12-01

Sensitivity analysis plays an important role in geoscientific computer experiments, whether for forecasting, data assimilation or model calibration. In this paper we focus on an extension of a method of regionalized sensitivity analysis (RSA) to applications typical in the Earth Sciences. Such applications involve the building of large complex spatial models, the application of computationally extensive forward modeling codes and the integration of heterogeneous sources of model uncertainty. The aim of this paper is to be practical: 1) provide a Matlab code, 2) provide novel visualization methods to aid users in getting a better understanding in the sensitivity 3) provide a method based on kernel principal component analysis (KPCA) and self-organizing maps (SOM) to account for spatial uncertainty typical in Earth Science applications and 4) provide an illustration on a real field case where the above mentioned complexities present themselves. We present methods that extend the original RSA method in several ways. First we present the calculation of conditional effects, defined as the sensitivity of a parameter given a level of another parameters. Second, we show how this conditional effect can be used to choose nominal values or ranges to fix insensitive parameters aiming to minimally affect uncertainty in the response. Third, we develop a method based on KPCA and SOM to assign a rank to spatial models in order to calculate the sensitivity on spatial variability in the models. A large oil/gas reservoir case is used as illustration of these ideas.

Algorthms and prigrams complex for chaotic dynamics investigation of the Earth artificial sat-ellites. (Russian Title: Комплекс алгоритмов и программ для исследования хаотичности в динамике искусственных спутников Земли )

NASA Astrophysics Data System (ADS)

Bordovitsyna, T. V.; Aleksandrova, A. G.; Chuvashov, I. N.

2010-12-01

In this paper complex of algorithms and programs for revelation and investigation of dynamical chaotic state in the motion of the Earth artificial satellites by parallel computing is presented. Complex has been based on the program "Numerical model of the system artificial satellites motion" for cluster "Skiff Cyberia". Factor MEGNO as main indicator of chaotic state has been used. The factor is computed by combined numerical integration of equations of the motion, equations in variation and equations of MEGNO parameters. The results of program complex testing in the problem of MEGNO parameters calculation for different types of geostationary orbits are presented.

Optimizing structure of complex technical system by heterogeneous vector criterion in interval form

NASA Astrophysics Data System (ADS)

Lysenko, A. V.; Kochegarov, I. I.; Yurkov, N. K.; Grishko, A. K.

2018-05-01

The article examines the methods of development and multi-criteria choice of the preferred structural variant of the complex technical system at the early stages of its life cycle in the absence of sufficient knowledge of parameters and variables for optimizing this structure. The suggested methods takes into consideration the various fuzzy input data connected with the heterogeneous quality criteria of the designed system and the parameters set by their variation range. The suggested approach is based on the complex use of methods of interval analysis, fuzzy sets theory, and the decision-making theory. As a result, the method for normalizing heterogeneous quality criteria has been developed on the basis of establishing preference relations in the interval form. The method of building preferential relations in the interval form on the basis of the vector of heterogeneous quality criteria suggest the use of membership functions instead of the coefficients considering the criteria value. The former show the degree of proximity of the realization of the designed system to the efficient or Pareto optimal variants. The study analyzes the example of choosing the optimal variant for the complex system using heterogeneous quality criteria.

A trap potential model investigation of the optical activity induced in dye-DNA intercalation complexes

NASA Astrophysics Data System (ADS)

Kamiya, Mamoru

1988-02-01

The fundamental features of the optical activity induced in dye-DNA intercalation complexes are studied by application of the trap potential model which is useful to evaluate the induced rotational strength without reference to detailed geometrical information about the intercalation complexes. The specific effect of the potential depth upon the induced optical activity is explained in terms of the relative magnitudes of the wave-phase and helix-phase variations in the path of an electron moving on a restricted helical segment just like an exciton trapped around the dye intercalation site. The parallel and perpendicular components of the induced rotational strength well reflect basic properties of the helicity effects about the longitudinal and tangential axes of the DNA helical cylinder. The trap potential model is applied to optimize the potential parameters so as to reproduce the ionic strength effect upon the optical activity induced to proflavine-DNA intercalation complexes. From relationships between the optimized potential parameters and ionic strengths, it is inferred that increase in the ionic strength contributes to the optical activity induced by the nearest-neighbour interaction between intercalated proflavine and DNA base pairs.

Partitioning degrees of freedom in hierarchical and other richly-parameterized models.

PubMed

Cui, Yue; Hodges, James S; Kong, Xiaoxiao; Carlin, Bradley P

2010-02-01

Hodges & Sargent (2001) developed a measure of a hierarchical model's complexity, degrees of freedom (DF), that is consistent with definitions for scatterplot smoothers, interpretable in terms of simple models, and that enables control of a fit's complexity by means of a prior distribution on complexity. DF describes complexity of the whole fitted model but in general it is unclear how to allocate DF to individual effects. We give a new definition of DF for arbitrary normal-error linear hierarchical models, consistent with Hodges & Sargent's, that naturally partitions the n observations into DF for individual effects and for error. The new conception of an effect's DF is the ratio of the effect's modeled variance matrix to the total variance matrix. This gives a way to describe the sizes of different parts of a model (e.g., spatial clustering vs. heterogeneity), to place DF-based priors on smoothing parameters, and to describe how a smoothed effect competes with other effects. It also avoids difficulties with the most common definition of DF for residuals. We conclude by comparing DF to the effective number of parameters p(D) of Spiegelhalter et al (2002). Technical appendices and a dataset are available online as supplemental materials.

Automating calibration, sensitivity and uncertainty analysis of complex models using the R package Flexible Modeling Environment (FME): SWAT as an example

USGS Publications Warehouse

Wu, Y.; Liu, S.

2012-01-01

Parameter optimization and uncertainty issues are a great challenge for the application of large environmental models like the Soil and Water Assessment Tool (SWAT), which is a physically-based hydrological model for simulating water and nutrient cycles at the watershed scale. In this study, we present a comprehensive modeling environment for SWAT, including automated calibration, and sensitivity and uncertainty analysis capabilities through integration with the R package Flexible Modeling Environment (FME). To address challenges (e.g., calling the model in R and transferring variables between Fortran and R) in developing such a two-language coupling framework, 1) we converted the Fortran-based SWAT model to an R function (R-SWAT) using the RFortran platform, and alternatively 2) we compiled SWAT as a Dynamic Link Library (DLL). We then wrapped SWAT (via R-SWAT) with FME to perform complex applications including parameter identifiability, inverse modeling, and sensitivity and uncertainty analysis in the R environment. The final R-SWAT-FME framework has the following key functionalities: automatic initialization of R, running Fortran-based SWAT and R commands in parallel, transferring parameters and model output between SWAT and R, and inverse modeling with visualization. To examine this framework and demonstrate how it works, a case study simulating streamflow in the Cedar River Basin in Iowa in the United Sates was used, and we compared it with the built-in auto-calibration tool of SWAT in parameter optimization. Results indicate that both methods performed well and similarly in searching a set of optimal parameters. Nonetheless, the R-SWAT-FME is more attractive due to its instant visualization, and potential to take advantage of other R packages (e.g., inverse modeling and statistical graphics). The methods presented in the paper are readily adaptable to other model applications that require capability for automated calibration, and sensitivity and uncertainty analysis.

Complexity of generic biochemical circuits: topology versus strength of interactions.

PubMed

Tikhonov, Mikhail; Bialek, William

2016-12-06

The historical focus on network topology as a determinant of biological function is still largely maintained today, illustrated by the rise of structure-only approaches to network analysis. However, biochemical circuits and genetic regulatory networks are defined both by their topology and by a multitude of continuously adjustable parameters, such as the strength of interactions between nodes, also recognized as important. Here we present a class of simple perceptron-based Boolean models within which comparing the relative importance of topology versus interaction strengths becomes a quantitatively well-posed problem. We quantify the intuition that for generic networks, optimization of interaction strengths is a crucial ingredient of achieving high complexity, defined here as the number of fixed points the network can accommodate. We propose a new methodology for characterizing the relative role of parameter optimization for topologies of a given class.

A MS-lesion pattern discrimination plot based on geostatistics.

PubMed

Marschallinger, Robert; Schmidt, Paul; Hofmann, Peter; Zimmer, Claus; Atkinson, Peter M; Sellner, Johann; Trinka, Eugen; Mühlau, Mark

2016-03-01

A geostatistical approach to characterize MS-lesion patterns based on their geometrical properties is presented. A dataset of 259 binary MS-lesion masks in MNI space was subjected to directional variography. A model function was fit to express the observed spatial variability in x, y, z directions by the geostatistical parameters Range and Sill. Parameters Range and Sill correlate with MS-lesion pattern surface complexity and total lesion volume. A scatter plot of ln(Range) versus ln(Sill), classified by pattern anisotropy, enables a consistent and clearly arranged presentation of MS-lesion patterns based on geometry: the so-called MS-Lesion Pattern Discrimination Plot. The geostatistical approach and the graphical representation of results are considered efficient exploratory data analysis tools for cross-sectional, follow-up, and medication impact analysis.

Normal contour error measurement on-machine and compensation method for polishing complex surface by MRF

NASA Astrophysics Data System (ADS)

Chen, Hua; Chen, Jihong; Wang, Baorui; Zheng, Yongcheng

2016-10-01

The Magnetorheological finishing (MRF) process, based on the dwell time method with the constant normal spacing for flexible polishing, would bring out the normal contour error in the fine polishing complex surface such as aspheric surface. The normal contour error would change the ribbon's shape and removal characteristics of consistency for MRF. Based on continuously scanning the normal spacing between the workpiece and the finder by the laser range finder, the novel method was put forward to measure the normal contour errors while polishing complex surface on the machining track. The normal contour errors was measured dynamically, by which the workpiece's clamping precision, multi-axis machining NC program and the dynamic performance of the MRF machine were achieved for the verification and security check of the MRF process. The unit for measuring the normal contour errors of complex surface on-machine was designed. Based on the measurement unit's results as feedback to adjust the parameters of the feed forward control and the multi-axis machining, the optimized servo control method was presented to compensate the normal contour errors. The experiment for polishing 180mm × 180mm aspherical workpiece of fused silica by MRF was set up to validate the method. The results show that the normal contour error was controlled in less than 10um. And the PV value of the polished surface accuracy was improved from 0.95λ to 0.09λ under the conditions of the same process parameters. The technology in the paper has been being applied in the PKC600-Q1 MRF machine developed by the China Academe of Engineering Physics for engineering application since 2014. It is being used in the national huge optical engineering for processing the ultra-precision optical parts.

Ionospheric effects during severe space weather events seen in ionospheric service data products

NASA Astrophysics Data System (ADS)

Jakowski, Norbert; Danielides, Michael; Mayer, Christoph; Borries, Claudia

Space weather effects are closely related to complex perturbation processes in the magnetosphere-ionosphere-thermosphere systems, initiated by enhanced solar energy input. To understand and model complex space weather processes, different views on the same subject are helpful. One of the ionosphere key parameters is the Total Electron Content (TEC) which provides a first or-der approximation of the ionospheric range error in Global Navigation Satellite System (GNSS) applications. Additionally, horizontal gradients and time rate of change of TEC are important for estimating the perturbation degree of the ionosphere. TEC maps can effectively be gener-ated using ground based GNSS measurements from global receiver networks. Whereas ground based GNSS measurements provide good horizontal resolution, space based radio occultation measurements can complete the view by providing information on the vertical plasma density distribution. The combination of ground based TEC and vertical sounding measurements pro-vide essential information on the shape of the vertical electron density profile by computing the equivalent slab thickness at the ionosonde station site. Since radio beacon measurements at 150/400 MHz are well suited to trace the horizontal structure of Travelling Ionospheric Dis-turbances (TIDs), these data products essentially complete GNSS based TEC mapping results. Radio scintillation data products, characterising small scale irregularities in the ionosphere, are useful to estimate the continuity and availability of transionospheric radio signals. The different data products are addressed while discussing severe space weather events in the ionosphere e.g. events in October/November 2003. The complementary view of different near real time service data products is helpful to better understand the complex dynamics of ionospheric perturbation processes and to forecast the development of parameters customers are interested in.

A geostatistics-informed hierarchical sensitivity analysis method for complex groundwater flow and transport modeling

NASA Astrophysics Data System (ADS)

Dai, Heng; Chen, Xingyuan; Ye, Ming; Song, Xuehang; Zachara, John M.

2017-05-01

Sensitivity analysis is an important tool for development and improvement of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study, we developed a new sensitivity analysis method that integrates the concept of variance-based method with a hierarchical uncertainty quantification framework. Different uncertain inputs are grouped and organized into a multilayer framework based on their characteristics and dependency relationships to reduce the dimensionality of the sensitivity analysis. A set of new sensitivity indices are defined for the grouped inputs using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially distributed input variables.

A Geostatistics-Informed Hierarchical Sensitivity Analysis Method for Complex Groundwater Flow and Transport Modeling

NASA Astrophysics Data System (ADS)

Dai, H.; Chen, X.; Ye, M.; Song, X.; Zachara, J. M.

2017-12-01

Sensitivity analysis is an important tool for development and improvement of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study we developed a new sensitivity analysis method that integrates the concept of variance-based method with a hierarchical uncertainty quantification framework. Different uncertain inputs are grouped and organized into a multi-layer framework based on their characteristics and dependency relationships to reduce the dimensionality of the sensitivity analysis. A set of new sensitivity indices are defined for the grouped inputs using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially-distributed input variables.

Mission activities planning for a Hermes mission by means of AI-technology

NASA Technical Reports Server (NTRS)

Pape, U.; Hajen, G.; Schielow, N.; Mitschdoerfer, P.; Allard, F.

1993-01-01

Mission Activities Planning is a complex task to be performed by mission control centers. AI technology can offer attractive solutions to the planning problem. This paper presents the use of a new AI-based Mission Planning System for crew activity planning. Based on a HERMES servicing mission to the COLUMBUS Man Tended Free Flyer (MTFF) with complex time and resource constraints, approximately 2000 activities with 50 different resources have been generated, processed, and planned with parametric variation of operationally sensitive parameters. The architecture, as well as the performance of the mission planning system, is discussed. An outlook to future planning scenarios, the requirements, and how a system like MARS can fulfill those requirements is given.

Logic-based models in systems biology: a predictive and parameter-free network analysis method†

PubMed Central

Wynn, Michelle L.; Consul, Nikita; Merajver, Sofia D.

2012-01-01

Highly complex molecular networks, which play fundamental roles in almost all cellular processes, are known to be dysregulated in a number of diseases, most notably in cancer. As a consequence, there is a critical need to develop practical methodologies for constructing and analysing molecular networks at a systems level. Mathematical models built with continuous differential equations are an ideal methodology because they can provide a detailed picture of a network’s dynamics. To be predictive, however, differential equation models require that numerous parameters be known a priori and this information is almost never available. An alternative dynamical approach is the use of discrete logic-based models that can provide a good approximation of the qualitative behaviour of a biochemical system without the burden of a large parameter space. Despite their advantages, there remains significant resistance to the use of logic-based models in biology. Here, we address some common concerns and provide a brief tutorial on the use of logic-based models, which we motivate with biological examples. PMID:23072820

Analysis of the Wtb vertex from the measurement of triple-differential angular decay rates of single top quarks produced in the t-channel at √{s}=8 TeV with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Abidi, S. H.; AbouZeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adachi, S.; Adamczyk, L.; Adelman, J.; Adersberger, M.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Agheorghiesei, C.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akatsuka, S.; Akerstedt, H.; Åkesson, T. P. A.; Akilli, E.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albicocco, P.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alshehri, A. A.; Alstaty, M. I.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Angerami, A.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Antrim, D. J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Araujo Ferraz, V.; Arce, A. T. H.; Ardell, R. E.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagnaia, P.; Bahrasemani, H.; Baines, J. T.; Bajic, M.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barkeloo, J. T.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beermann, T. A.; Begalli, M.; Begel, M.; Behr, J. K.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Benoit, M.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernardi, G.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethani, A.; Bethke, S.; Bevan, A. J.; Beyer, J.; Bianchi, R. M.; Biebel, O.; Biedermann, D.; Bielski, R.; Biesuz, N. V.; Biglietti, M.; Bilbao De Mendizabal, J.; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bittrich, C.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blair, R. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blue, A.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bolz, A. E.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Briglin, D. L.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruni, A.; Bruni, G.; Bruni, L. S.; Brunt, BH; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burch, T. J.; Burckhart, H.; Burdin, S.; Burgard, C. D.; Burger, A. M.; Burghgrave, B.; Burka, K.; Burke, S.; Burmeister, I.; Burr, J. T. P.; Busato, E.; Büscher, D.; Büscher, V.; Bussey, P.; Butler, J. M.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Buzykaev, A. R.; Cabrera Urbán, S.; Caforio, D.; Cairo, V. M.; Cakir, O.; Calace, N.; Calafiura, P.; Calandri, A.; Calderini, G.; Calfayan, P.; Callea, G.; Caloba, L. P.; Calvente Lopez, S.; Calvet, D.; Calvet, S.; Calvet, T. P.; Camacho Toro, R.; Camarda, S.; Camarri, P.; Cameron, D.; Caminal Armadans, R.; Camincher, C.; Campana, S.; Campanelli, M.; Camplani, A.; Campoverde, A.; Canale, V.; Cano Bret, M.; Cantero, J.; Cao, T.; Capeans Garrido, M. D. M.; Caprini, I.; Caprini, M.; Capua, M.; Carbone, R. M.; Cardarelli, R.; Cardillo, F.; Carli, I.; Carli, T.; Carlino, G.; Carlson, B. T.; Carminati, L.; Carney, R. M. D.; Caron, S.; Carquin, E.; Carrá, S.; Carrillo-Montoya, G. D.; Carvalho, J.; Casadei, D.; Casado, M. P.; Casolino, M.; Casper, D. W.; Castelijn, R.; Castillo Gimenez, V.; Castro, N. F.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Caudron, J.; Cavaliere, V.; Cavallaro, E.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Celebi, E.; Ceradini, F.; Cerda Alberich, L.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chan, S. K.; Chan, W. S.; Chan, Y. L.; Chang, P.; Chapman, J. D.; Charlton, D. G.; Chau, C. C.; Chavez Barajas, C. A.; Che, S.; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, S.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, H. J.; Cheplakov, A.; Cheremushkina, E.; Cherkaoui El Moursli, R.; Chernyatin, V.; Cheu, E.; Cheung, K.; Chevalier, L.; Chiarella, V.; Chiarelli, G.; Chiodini, G.; Chisholm, A. S.; Chitan, A.; Chiu, Y. H.; Chizhov, M. V.; Choi, K.; Chomont, A. R.; Chouridou, S.; Christodoulou, V.; Chromek-Burckhart, D.; Chu, M. C.; Chudoba, J.; Chuinard, A. J.; Chwastowski, J. J.; Chytka, L.; Ciftci, A. K.; Cinca, D.; Cindro, V.; Cioara, I. A.; Ciocca, C.; Ciocio, A.; Cirotto, F.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, B. L.; Clark, M. R.; Clark, P. J.; Clarke, R. N.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Colasurdo, L.; Cole, B.; Colijn, A. P.; Collot, J.; Colombo, T.; Conde Muiño, P.; Coniavitis, E.; Connell, S. H.; Connelly, I. A.; Constantinescu, S.; Conti, G.; Conventi, F.; Cooke, M.; Cooper-Sarkar, A. M.; Cormier, F.; Cormier, K. J. R.; Corradi, M.; Corriveau, F.; Cortes-Gonzalez, A.; Cortiana, G.; Costa, G.; Costa, M. J.; Costanzo, D.; Cottin, G.; Cowan, G.; Cox, B. E.; Cranmer, K.; Crawley, S. J.; Creager, R. A.; Cree, G.; Crépé-Renaudin, S.; Crescioli, F.; Cribbs, W. A.; Cristinziani, M.; Croft, V.; Crosetti, G.; Cueto, A.; Cuhadar Donszelmann, T.; Cukierman, A. R.; Cummings, J.; Curatolo, M.; Cúth, J.; Czirr, H.; Czodrowski, P.; D'amen, G.; D'Auria, S.; D'eramo, L.; D'Onofrio, M.; Da Cunha Sargedas De Sousa, M. J.; Da Via, C.; Dabrowski, W.; Dado, T.; Dai, T.; Dale, O.; Dallaire, F.; Dallapiccola, C.; Dam, M.; Dandoy, J. R.; Daneri, M. F.; Dang, N. P.; Daniells, A. C.; Dann, N. S.; Danninger, M.; Dano Hoffmann, M.; Dao, V.; Darbo, G.; Darmora, S.; Dassoulas, J.; Dattagupta, A.; Daubney, T.; Davey, W.; David, C.; Davidek, T.; Davies, M.; Davis, D. R.; Davison, P.; Dawe, E.; Dawson, I.; De, K.; de Asmundis, R.; De Benedetti, A.; De Castro, S.; De Cecco, S.; De Groot, N.; de Jong, P.; De la Torre, H.; De Lorenzi, F.; De Maria, A.; De Pedis, D.; De Salvo, A.; De Sanctis, U.; De Santo, A.; De Vasconcelos Corga, K.; De Vivie De Regie, J. B.; Dearnaley, W. J.; Debbe, R.; Debenedetti, C.; Dedovich, D. V.; Dehghanian, N.; Deigaard, I.; Del Gaudio, M.; Del Peso, J.; Del Prete, T.; Delgove, D.; Deliot, F.; Delitzsch, C. M.; Dell'Acqua, A.; Dell'Asta, L.; Dell'Orso, M.; Della Pietra, M.; della Volpe, D.; Delmastro, M.; Delporte, C.; Delsart, P. A.; DeMarco, D. A.; Demers, S.; Demichev, M.; Demilly, A.; Denisov, S. P.; Denysiuk, D.; Derendarz, D.; Derkaoui, J. E.; Derue, F.; Dervan, P.; Desch, K.; Deterre, C.; Dette, K.; Devesa, M. R.; Deviveiros, P. O.; Dewhurst, A.; Dhaliwal, S.; Di Bello, F. A.; Di Ciaccio, A.; Di Ciaccio, L.; Di Clemente, W. K.; Di Donato, C.; Di Girolamo, A.; Di Girolamo, B.; Di Micco, B.; Di Nardo, R.; Di Petrillo, K. F.; Di Simone, A.; Di Sipio, R.; Di Valentino, D.; Diaconu, C.; Diamond, M.; Dias, F. A.; Diaz, M. A.; Diehl, E. B.; Dietrich, J.; Díez Cornell, S.; Dimitrievska, A.; Dingfelder, J.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; Djuvsland, J. I.; do Vale, M. A. B.; Dobos, D.; Dobre, M.; Doglioni, C.; Dolejsi, J.; Dolezal, Z.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Drechsler, E.; Dris, M.; Du, Y.; Duarte-Campderros, J.; Dubreuil, A.; Duchovni, E.; Duckeck, G.; Ducourthial, A.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudder, A. Chr.; Duffield, E. M.; Duflot, L.; Dührssen, M.; Dumancic, M.; Dumitriu, A. E.; Duncan, A. K.; Dunford, M.; Duran Yildiz, H.; Düren, M.; Durglishvili, A.; Duschinger, D.; Dutta, B.; Dyndal, M.; Dziedzic, B. S.; Eckardt, C.; Ecker, K. M.; Edgar, R. C.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; El Kosseifi, R.; Ellajosyula, V.; Ellert, M.; Elles, S.; Ellinghaus, F.; Elliot, A. A.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Ennis, J. S.; Erdmann, J.; Ereditato, A.; Ernis, G.; Ernst, M.; Errede, S.; Escalier, M.; Escobar, C.; Esposito, B.; Estrada Pastor, O.; Etienvre, A. I.; Etzion, E.; Evans, H.; Ezhilov, A.; Ezzi, M.; Fabbri, F.; Fabbri, L.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Falla, R. J.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farina, C.; Farina, E. M.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Faucci Giannelli, M.; Favareto, A.; Fawcett, W. J.; Fayard, L.; Fedin, O. L.; Fedorko, W.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenton, M. J.; Fenyuk, A. B.; Feremenga, L.; Fernandez Martinez, P.; Fernandez Perez, S.; Ferrando, J.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Fischer, A.; Fischer, C.; Fischer, J.; Fisher, W. C.; Flaschel, N.; Fleck, I.; Fleischmann, P.; Fletcher, R. R. M.; Flick, T.; Flierl, B. M.; Flores Castillo, L. R.; Flowerdew, M. J.; Forcolin, G. T.; Formica, A.; Förster, F. A.; Forti, A.; Foster, A. G.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Franchino, S.; Francis, D.; Franconi, L.; Franklin, M.; Frate, M.; Fraternali, M.; Freeborn, D.; Fressard-Batraneanu, S. M.; Freund, B.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Fusayasu, T.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gach, G. P.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, L. G.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Ganguly, S.; Gao, Y.; Gao, Y. S.; Garay Walls, F. M.; García, C.; García Navarro, J. E.; García Pascual, J. A.; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gascon Bravo, A.; Gasnikova, K.; Gatti, C.; Gaudiello, A.; Gaudio, G.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Gee, C. N. P.; Geisen, J.; Geisen, M.; Geisler, M. P.; Gellerstedt, K.; Gemme, C.; Genest, M. H.; Geng, C.; Gentile, S.; Gentsos, C.; George, S.; Gerbaudo, D.; Gershon, A.; Geßner, G.; Ghasemi, S.; Ghneimat, M.; Giacobbe, B.; Giagu, S.; Giannetti, P.; Gibson, S. M.; Gignac, M.; Gilchriese, M.; Gillberg, D.; Gilles, G.; Gingrich, D. M.; Giokaris, N.; Giordani, M. P.; Giorgi, F. M.; Giraud, P. F.; Giromini, P.; Giugni, D.; Giuli, F.; Giuliani, C.; Giulini, M.; Gjelsten, B. K.; Gkaitatzis, S.; Gkialas, I.; Gkougkousis, E. L.; Gkountoumis, P.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. F.; Glazov, A.; Goblirsch-Kolb, M.; Godlewski, J.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Gonçalo, R.; Goncalves Gama, R.; Goncalves Pinto Firmino Da Costa, J.; Gonella, G.; Gonella, L.; Gongadze, A.; González de la Hoz, S.; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorini, B.; Gorini, E.; Gorišek, A.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Gottardo, C. A.; Goudet, C. R.; Goujdami, D.; Goussiou, A. G.; Govender, N.; Gozani, E.; Graber, L.; Grabowska-Bold, I.; Gradin, P. O. J.; Gramling, J.; Gramstad, E.; Grancagnolo, S.; Gratchev, V.; Gravila, P. M.; Gray, C.; Gray, H. M.; Greenwood, Z. D.; Grefe, C.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Grevtsov, K.; Griffiths, J.; Grillo, A. A.; Grimm, K.; Grinstein, S.; Gris, Ph.; Grivaz, J.-F.; Groh, S.; Gross, E.; Grosse-Knetter, J.; Grossi, G. C.; Grout, Z. 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S.; Polychronakos, V.; Pommès, K.; Ponomarenko, D.; Pontecorvo, L.; Pope, B. G.; Popeneciu, G. A.; Poppleton, A.; Pospisil, S.; Potamianos, K.; Potrap, I. N.; Potter, C. J.; Poulard, G.; Poulsen, T.; Poveda, J.; Pozo Astigarraga, M. E.; Pralavorio, P.; Pranko, A.; Prell, S.; Price, D.; Price, L. E.; Primavera, M.; Prince, S.; Proklova, N.; Prokofiev, K.; Prokoshin, F.; Protopopescu, S.; Proudfoot, J.; Przybycien, M.; Puri, A.; Puzo, P.; Qian, J.; Qin, G.; Qin, Y.; Quadt, A.; Queitsch-Maitland, M.; Quilty, D.; Raddum, S.; Radeka, V.; Radescu, V.; Radhakrishnan, S. K.; Radloff, P.; Rados, P.; Ragusa, F.; Rahal, G.; Raine, J. A.; Rajagopalan, S.; Rangel-Smith, C.; Rashid, T.; Raspopov, S.; Ratti, M. G.; Rauch, D. M.; Rauscher, F.; Rave, S.; Ravinovich, I.; Rawling, J. H.; Raymond, M.; Read, A. L.; Readioff, N. P.; Reale, M.; Rebuzzi, D. M.; Redelbach, A.; Redlinger, G.; Reece, R.; Reed, R. G.; Reeves, K.; Rehnisch, L.; Reichert, J.; Reiss, A.; Rembser, C.; Ren, H.; Rescigno, M.; Resconi, S.; Resseguie, E. D.; Rettie, S.; Reynolds, E.; Rezanova, O. L.; Reznicek, P.; Rezvani, R.; Richter, R.; Richter, S.; Richter-Was, E.; Ricken, O.; Ridel, M.; Rieck, P.; Riegel, C. J.; Rieger, J.; Rifki, O.; Rijssenbeek, M.; Rimoldi, A.; Rimoldi, M.; Rinaldi, L.; Ripellino, G.; Ristić, B.; Ritsch, E.; Riu, I.; Rizatdinova, F.; Rizvi, E.; Rizzi, C.; Roberts, R. T.; Robertson, S. H.; Robichaud-Veronneau, A.; Robinson, D.; Robinson, J. E. M.; Robson, A.; Rocco, E.; Roda, C.; Rodina, Y.; Rodriguez Bosca, S.; Rodriguez Perez, A.; Rodriguez Rodriguez, D.; Roe, S.; Rogan, C. S.; Røhne, O.; Roloff, J.; Romaniouk, A.; Romano, M.; Romano Saez, S. M.; Romero Adam, E.; Rompotis, N.; Ronzani, M.; Roos, L.; Rosati, S.; Rosbach, K.; Rose, P.; Rosien, N.-A.; Rossi, E.; Rossi, L. P.; Rosten, J. H. N.; Rosten, R.; Rotaru, M.; Roth, I.; Rothberg, J.; Rousseau, D.; Rozanov, A.; Rozen, Y.; Ruan, X.; Rubbo, F.; Rühr, F.; Ruiz-Martinez, A.; Rurikova, Z.; Rusakovich, N. A.; Russell, H. L.; Rutherfoord, J. P.; Ruthmann, N.; Ryabov, Y. F.; Rybar, M.; Rybkin, G.; Ryu, S.; Ryzhov, A.; Rzehorz, G. F.; Saavedra, A. F.; Sabato, G.; Sacerdoti, S.; Sadrozinski, H. F.-W.; Sadykov, R.; Safai Tehrani, F.; Saha, P.; Sahinsoy, M.; Saimpert, M.; Saito, M.; Saito, T.; Sakamoto, H.; Sakurai, Y.; Salamanna, G.; Salazar Loyola, J. E.; Salek, D.; Sales De Bruin, P. H.; Salihagic, D.; Salnikov, A.; Salt, J.; Salvatore, D.; Salvatore, F.; Salvucci, A.; Salzburger, A.; Sammel, D.; Sampsonidis, D.; Sampsonidou, D.; Sánchez, J.; Sanchez Martinez, V.; Sanchez Pineda, A.; Sandaker, H.; Sandbach, R. L.; Sander, C. O.; Sandhoff, M.; Sandoval, C.; Sankey, D. P. C.; Sannino, M.; Sano, Y.; Sansoni, A.; Santoni, C.; Santonico, R.; Santos, H.; Santoyo Castillo, I.; Sapronov, A.; Saraiva, J. G.; Sarrazin, B.; Sasaki, O.; Sato, K.; Sauvan, E.; Savage, G.; Savard, P.; Savic, N.; Sawyer, C.; Sawyer, L.; Saxon, J.; Sbarra, C.; Sbrizzi, A.; Scanlon, T.; Scannicchio, D. A.; Scarcella, M.; Scarfone, V.; Schaarschmidt, J.; Schacht, P.; Schachtner, B. M.; Schaefer, D.; Schaefer, L.; Schaefer, R.; Schaeffer, J.; Schaepe, S.; Schaetzel, S.; Schäfer, U.; Schaffer, A. C.; Schaile, D.; Schamberger, R. D.; Scharf, V.; Schegelsky, V. A.; Scheirich, D.; Schernau, M.; Schiavi, C.; Schier, S.; Schildgen, L. K.; Schillo, C.; Schioppa, M.; Schlenker, S.; Schmidt-Sommerfeld, K. R.; Schmieden, K.; Schmitt, C.; Schmitt, S.; Schmitz, S.; Schnoor, U.; Schoeffel, L.; Schoening, A.; Schoenrock, B. D.; Schopf, E.; Schott, M.; Schouwenberg, J. F. P.; Schovancova, J.; Schramm, S.; Schuh, N.; Schulte, A.; Schultens, M. J.; Schultz-Coulon, H.-C.; Schulz, H.; Schumacher, M.; Schumm, B. A.; Schune, Ph.; Schwartzman, A.; Schwarz, T. A.; Schweiger, H.; Schwemling, Ph.; Schwienhorst, R.; Schwindling, J.; Sciandra, A.; Sciolla, G.; Scornajenghi, M.; Scuri, F.; Scutti, F.; Searcy, J.; Seema, P.; Seidel, S. C.; Seiden, A.; Seixas, J. M.; Sekhniaidze, G.; Sekhon, K.; Sekula, S. J.; Semprini-Cesari, N.; Senkin, S.; Serfon, C.; Serin, L.; Serkin, L.; Sessa, M.; Seuster, R.; Severini, H.; Sfiligoj, T.; Sforza, F.; Sfyrla, A.; Shabalina, E.; Shaikh, N. W.; Shan, L. Y.; Shang, R.; Shank, J. T.; Shapiro, M.; Shatalov, P. B.; Shaw, K.; Shaw, S. M.; Shcherbakova, A.; Shehu, C. Y.; Shen, Y.; Sherafati, N.; Sherwood, P.; Shi, L.; Shimizu, S.; Shimmin, C. O.; Shimojima, M.; Shipsey, I. P. J.; Shirabe, S.; Shiyakova, M.; Shlomi, J.; Shmeleva, A.; Shoaleh Saadi, D.; Shochet, M. J.; Shojaii, S.; Shope, D. R.; Shrestha, S.; Shulga, E.; Shupe, M. A.; Sicho, P.; Sickles, A. M.; Sidebo, P. E.; Sideras Haddad, E.; Sidiropoulou, O.; Sidoti, A.; Siegert, F.; Sijacki, Dj.; Silva, J.; Silverstein, S. B.; Simak, V.; Simic, Lj.; Simion, S.; Simioni, E.; Simmons, B.; Simon, M.; Sinervo, P.; Sinev, N. B.; Sioli, M.; Siragusa, G.; Siral, I.; Sivoklokov, S. Yu.; Sjölin, J.; Skinner, M. B.; Skubic, P.; Slater, M.; Slavicek, T.; Slawinska, M.; Sliwa, K.; Slovak, R.; Smakhtin, V.; Smart, B. H.; Smiesko, J.; Smirnov, N.; Smirnov, S. Yu.; Smirnov, Y.; Smirnova, L. N.; Smirnova, O.; Smith, J. W.; Smith, M. N. K.; Smith, R. W.; Smizanska, M.; Smolek, K.; Snesarev, A. A.; Snyder, I. M.; Snyder, S.; Sobie, R.; Socher, F.; Soffer, A.; Soh, D. A.; Sokhrannyi, G.; Solans Sanchez, C. A.; Solar, M.; Soldatov, E. Yu.; Soldevila, U.; Solodkov, A. A.; Soloshenko, A.; Solovyanov, O. V.; Solovyev, V.; Sommer, P.; Son, H.; Sopczak, A.; Sosa, D.; Sotiropoulou, C. L.; Soualah, R.; Soukharev, A. M.; South, D.; Sowden, B. C.; Spagnolo, S.; Spalla, M.; Spangenberg, M.; Spanò, F.; Sperlich, D.; Spettel, F.; Spieker, T. M.; Spighi, R.; Spigo, G.; Spiller, L. A.; Spousta, M.; St. Denis, R. D.; Stabile, A.; Stamen, R.; Stamm, S.; Stanecka, E.; Stanek, R. W.; Stanescu, C.; Stanitzki, M. M.; Stapf, B. S.; Stapnes, S.; Starchenko, E. A.; Stark, G. H.; Stark, J.; Stark, S. H.; Staroba, P.; Starovoitov, P.; Stärz, S.; Staszewski, R.; Steinberg, P.; Stelzer, B.; Stelzer, H. J.; Stelzer-Chilton, O.; Stenzel, H.; Stewart, G. A.; Stockton, M. C.; Stoebe, M.; Stoicea, G.; Stolte, P.; Stonjek, S.; Stradling, A. R.; Straessner, A.; Stramaglia, M. E.; Strandberg, J.; Strandberg, S.; Strauss, M.; Strizenec, P.; Ströhmer, R.; Strom, D. M.; Stroynowski, R.; Strubig, A.; Stucci, S. A.; Stugu, B.; Styles, N. A.; Su, D.; Su, J.; Suchek, S.; Sugaya, Y.; Suk, M.; Sulin, V. V.; Sultan, DMS; Sultansoy, S.; Sumida, T.; Sun, S.; Sun, X.; Suruliz, K.; Suster, C. J. E.; Sutton, M. R.; Suzuki, S.; Svatos, M.; Swiatlowski, M.; Swift, S. P.; Sykora, I.; Sykora, T.; Ta, D.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takai, H.; Takashima, R.; Takasugi, E. H.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tanaka, J.; Tanaka, M.; Tanaka, R.; Tanaka, S.; Tanioka, R.; Tannenwald, B. B.; Tapia Araya, S.; Tapprogge, S.; Tarem, S.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Tavares Delgado, A.; Tayalati, Y.; Taylor, A. C.; Taylor, G. N.; Taylor, P. T. E.; Taylor, W.; Teixeira-Dias, P.; Temple, D.; Ten Kate, H.; Teng, P. K.; Teoh, J. J.; Tepel, F.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Theveneaux-Pelzer, T.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Tibbetts, M. J.; Ticse Torres, R. E.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorova-Nova, S.; Todt, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Tornambe, P.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Treado, C. J.; Trefzger, T.; Tresoldi, F.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tsang, K. W.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tulbure, T. T.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turgeman, D.; Turk Cakir, I.; Turra, R.; Tuts, P. M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usui, J.; Vacavant, L.; Vacek, V.; Vachon, B.; Vaidya, A.; Valderanis, C.; Valdes Santurio, E.; Valentinetti, S.; Valero, A.; Valéry, L.; Valkar, S.; Vallier, A.; Valls Ferrer, J. A.; Van Den Wollenberg, W.; van der Graaf, H.; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varni, C.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veeraraghavan, V.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, A. T.; Vermeulen, J. C.; Vetterli, M. C.; Viaux Maira, N.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vishwakarma, A.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vogel, M.; Vokac, P.; Volpi, G.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Wagner, P.; Wagner, W.; Wagner-Kuhr, J.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, Q.; Wang, R.; Wang, S. M.; Wang, T.; Wang, W.; Wang, W.; Wang, Z.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, A. F.; Webb, S.; Weber, M. S.; Weber, S. W.; Weber, S. A.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weirich, M.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M. D.; Werner, P.; Wessels, M.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A. S.; White, A.; White, M. J.; White, R.; Whiteson, D.; Whitmore, B. W.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winkels, E.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wobisch, M.; Wolf, T. M. H.; Wolff, R.; Wolter, M. W.; Wolters, H.; Wong, V. W. S.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Wozniak, K. W.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xi, Z.; Xia, L.; Xu, D.; Xu, L.; Xu, T.; Yabsley, B.; Yacoob, S.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamatani, M.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yigitbasi, E.; Yildirim, E.; Yorita, K.; Yoshihara, K.; Young, C.; Young, C. J. S.; Yu, J.; Yu, J.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zacharis, G.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanzi, D.; Zeitnitz, C.; Zemaityte, G.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, L.; Zhang, M.; Zhang, P.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Y.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, M.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zou, R.; zur Nedden, M.; Zwalinski, L.

2017-12-01

The electroweak production and subsequent decay of single top quarks in the t-channel is determined by the properties of the Wtb vertex, which can be described by the complex parameters of an effective Lagrangian. An analysis of a triple-differential decay rate in t-channel production is used to simultaneously determine five generalised helicity fractions and phases, as well as the polarisation of the produced top quark. The complex parameters are then constrained. This analysis is based on 20.2 fb-1 of proton-proton collision data at a centre-of-mass energy of 8 TeV collected with the ATLAS detector at the LHC. The fraction of decays containing transversely polarised W bosons is measured to be f 1 = 0.30 ± 0.05. The phase between amplitudes for transversely and longitudinally polarised W bosons recoiling against left-handed b-quarks is measured to be δ - = 0.002 π + 0.017 π + 0.016 π , giving no indication of CP violation. The fractions of longitudinal or transverse W bosons accompanied by right-handed b-quarks are also constrained. Based on these measurements, limits are placed at 95% CL on the ratio of the complex coupling parameters Re [ g R/V L ∈ [-0.12, 0.17] and Im [ g R/VL ∈ [-0.07, 0.06]. Constraints are also placed on the ratios | V R/ V L| and | g L/ V L|. In addition, the polarisation of single top quarks in the t-channel is constrained to be P > 0.72 (95% CL). None of the above measurements make assumptions about the value of any of the other parameters or couplings and all of them are in agreement with the Standard Model. [Figure not available: see fulltext.

Influence of coronal mass ejections on parameters of high-speed solar wind: a case study

NASA Astrophysics Data System (ADS)

Shugay, Yulia; Slemzin, Vladimir; Rodkin, Denis; Yermolaev, Yuri; Veselovsky, Igor

2018-05-01

We investigate the case of disagreement between predicted and observed in-situ parameters of the recurrent high-speed solar wind streams (HSSs) existing for Carrington rotation (CR) 2118 (December 2011) in comparison with CRs 2117 and 2119. The HSSs originated at the Sun from a recurrent polar coronal hole (CH) expanding to mid-latitudes, and its area in the central part of the solar disk increased with the rotation number. This part of the CH was responsible for the equatorial flank of the HSS directed to the Earth. The time and speed of arrival for this part of the HSS to the Earth were predicted by the hierarchical empirical model based on EUV-imaging and the Wang-Sheeley-Arge ENLIL semi-empirical replace model and compared with the parameters measured in-situ by model. The predicted parameters were compared with those measured in-situ. It was found, that for CR 2117 and CR 2119, the predicted HSS speed values agreed with the measured ones within the typical accuracy of ±100 km s-1. During CR 2118, the measured speed was on 217 km s-1 less than the value predicted in accordance with the increased area of the CH. We suppose that at CR 2118, the HSS overtook and interacted with complex ejecta formed from three merged coronal mass ejections (CMEs) with a mean speed about 400 km s-1. According to simulations of the Drag-based model, this complex ejecta might be created by several CMEs starting from the Sun in the period between 25 and 27 December 2011 and arriving to the Earth simultaneously with the HSS. Due to its higher density and magnetic field strength, the complex ejecta became an obstacle for the equatorial flank of the HSS and slowed it down. During CR 2117 and CR 2119, the CMEs appeared before the arrival of the HSSs, so the CMEs did not influence on the HSSs kinematics.

Analysis of the Wtb vertex from the measurement of triple-differential angular decay rates of single top quarks produced in the t-channel at s=8$$ \\sqrt{s}=8 $$ TeV with the ATLAS detector

DOE PAGES

Aaboud, M.; Aad, G.; Abbott, B.; ...

2017-12-04

The electroweak production and subsequent decay of single top quarks in the t-channel is determined by the properties of the Wtb vertex, which can be described by the complex parameters of an effective Lagrangian. We use an analysis of a triple-differential decay rate in t-channel production to simultaneously determine five generalised helicity fractions and phases, as well as the polarisation of the produced top quark. The complex parameters are then constrained. This analysis is based on 20.2 fb -1 of proton-proton collision data at a centre-of-mass energy of 8 TeV collected with the ATLAS detector at the LHC. The fractionmore » of decays containing transversely polarised W bosons is measured to be f 1 = 0.30 ± 0.05. The phase between amplitudes for transversely and longitudinally polarised W bosons recoiling against left-handed b-quarks is measured to be δ -= 0.002π + 0.017π + 0.016π , giving no indication of CP violation. The fractions of longitudinal or transverse W bosons accompanied by right-handed b-quarks are also constrained. Based on these measurements, limits are placed at 95% CL on the ratio of the complex coupling parameters Re [g R/V L ϵ [-0.12, 0.17] and Im [g R/V L ϵ [-0.07, 0.06]. Constraints are also placed on the ratios |V R/V L| and |g L/V L|. Additionally, the polarisation of single top quarks in the t-channel is constrained to be P > 0.72 (95% CL). None of the above measurements make assumptions about the value of any of the other parameters or couplings and all of them are in agreement with the Standard Model.« less

Analysis of the Wtb vertex from the measurement of triple-differential angular decay rates of single top quarks produced in the t-channel at $$ \\sqrt{s}=8 $$ TeV with the ATLAS detector

DOE PAGES

Aaboud, M.; Aad, G.; Abbott, B.; ...

2017-12-04

The electroweak production and subsequent decay of single top quarks in the t-channel is determined by the properties of the Wtb vertex, which can be described by the complex parameters of an effective Lagrangian. We use an analysis of a triple-differential decay rate in t-channel production to simultaneously determine five generalised helicity fractions and phases, as well as the polarisation of the produced top quark. The complex parameters are then constrained. This analysis is based on 20.2 fb -1 of proton-proton collision data at a centre-of-mass energy of 8 TeV collected with the ATLAS detector at the LHC. The fractionmore » of decays containing transversely polarised W bosons is measured to be f 1 = 0.30 ± 0.05. The phase between amplitudes for transversely and longitudinally polarised W bosons recoiling against left-handed b-quarks is measured to be δ -= 0.002π + 0.017π + 0.016π , giving no indication of CP violation. The fractions of longitudinal or transverse W bosons accompanied by right-handed b-quarks are also constrained. Based on these measurements, limits are placed at 95% CL on the ratio of the complex coupling parameters Re [g R/V L ϵ [-0.12, 0.17] and Im [g R/V L ϵ [-0.07, 0.06]. Constraints are also placed on the ratios |V R/V L| and |g L/V L|. Additionally, the polarisation of single top quarks in the t-channel is constrained to be P > 0.72 (95% CL). None of the above measurements make assumptions about the value of any of the other parameters or couplings and all of them are in agreement with the Standard Model.« less

Analysis of the Wtb vertex from the measurement of triple-differential angular decay rates of single top quarks produced in the t-channel at s=8$$ \\sqrt{s}=8 $$ TeV with the ATLAS detector

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

Aaboud, M.; Aad, G.; Abbott, B.

The electroweak production and subsequent decay of single top quarks in the t-channel is determined by the properties of the Wtb vertex, which can be described by the complex parameters of an effective Lagrangian. We use an analysis of a triple-differential decay rate in t-channel production to simultaneously determine five generalised helicity fractions and phases, as well as the polarisation of the produced top quark. The complex parameters are then constrained. This analysis is based on 20.2 fb -1 of proton-proton collision data at a centre-of-mass energy of 8 TeV collected with the ATLAS detector at the LHC. The fractionmore » of decays containing transversely polarised W bosons is measured to be f 1 = 0.30 ± 0.05. The phase between amplitudes for transversely and longitudinally polarised W bosons recoiling against left-handed b-quarks is measured to be δ -= 0.002π + 0.017π + 0.016π , giving no indication of CP violation. The fractions of longitudinal or transverse W bosons accompanied by right-handed b-quarks are also constrained. Based on these measurements, limits are placed at 95% CL on the ratio of the complex coupling parameters Re [g R/V L ϵ [-0.12, 0.17] and Im [g R/V L ϵ [-0.07, 0.06]. Constraints are also placed on the ratios |V R/V L| and |g L/V L|. Additionally, the polarisation of single top quarks in the t-channel is constrained to be P > 0.72 (95% CL). None of the above measurements make assumptions about the value of any of the other parameters or couplings and all of them are in agreement with the Standard Model.« less

Analysis of the Wtb vertex from the measurement of triple-differential angular decay rates of single top quarks produced in the t-channel at $$ \\sqrt{s}=8 $$ TeV with the ATLAS detector

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

Aaboud, M.; Aad, G.; Abbott, B.

The electroweak production and subsequent decay of single top quarks in the t-channel is determined by the properties of the Wtb vertex, which can be described by the complex parameters of an effective Lagrangian. We use an analysis of a triple-differential decay rate in t-channel production to simultaneously determine five generalised helicity fractions and phases, as well as the polarisation of the produced top quark. The complex parameters are then constrained. This analysis is based on 20.2 fb -1 of proton-proton collision data at a centre-of-mass energy of 8 TeV collected with the ATLAS detector at the LHC. The fractionmore » of decays containing transversely polarised W bosons is measured to be f 1 = 0.30 ± 0.05. The phase between amplitudes for transversely and longitudinally polarised W bosons recoiling against left-handed b-quarks is measured to be δ -= 0.002π + 0.017π + 0.016π , giving no indication of CP violation. The fractions of longitudinal or transverse W bosons accompanied by right-handed b-quarks are also constrained. Based on these measurements, limits are placed at 95% CL on the ratio of the complex coupling parameters Re [g R/V L ϵ [-0.12, 0.17] and Im [g R/V L ϵ [-0.07, 0.06]. Constraints are also placed on the ratios |V R/V L| and |g L/V L|. Additionally, the polarisation of single top quarks in the t-channel is constrained to be P > 0.72 (95% CL). None of the above measurements make assumptions about the value of any of the other parameters or couplings and all of them are in agreement with the Standard Model.« less

Mining manufacturing data for discovery of high productivity process characteristics.

PubMed

Charaniya, Salim; Le, Huong; Rangwala, Huzefa; Mills, Keri; Johnson, Kevin; Karypis, George; Hu, Wei-Shou

2010-06-01

Modern manufacturing facilities for bioproducts are highly automated with advanced process monitoring and data archiving systems. The time dynamics of hundreds of process parameters and outcome variables over a large number of production runs are archived in the data warehouse. This vast amount of data is a vital resource to comprehend the complex characteristics of bioprocesses and enhance production robustness. Cell culture process data from 108 'trains' comprising production as well as inoculum bioreactors from Genentech's manufacturing facility were investigated. Each run constitutes over one-hundred on-line and off-line temporal parameters. A kernel-based approach combined with a maximum margin-based support vector regression algorithm was used to integrate all the process parameters and develop predictive models for a key cell culture performance parameter. The model was also used to identify and rank process parameters according to their relevance in predicting process outcome. Evaluation of cell culture stage-specific models indicates that production performance can be reliably predicted days prior to harvest. Strong associations between several temporal parameters at various manufacturing stages and final process outcome were uncovered. This model-based data mining represents an important step forward in establishing a process data-driven knowledge discovery in bioprocesses. Implementation of this methodology on the manufacturing floor can facilitate a real-time decision making process and thereby improve the robustness of large scale bioprocesses. 2010 Elsevier B.V. All rights reserved.

DEM Calibration Approach: design of experiment

NASA Astrophysics Data System (ADS)

Boikov, A. V.; Savelev, R. V.; Payor, V. A.

2018-05-01

The problem of DEM models calibration is considered in the article. It is proposed to divide models input parameters into those that require iterative calibration and those that are recommended to measure directly. A new method for model calibration based on the design of the experiment for iteratively calibrated parameters is proposed. The experiment is conducted using a specially designed stand. The results are processed with technical vision algorithms. Approximating functions are obtained and the error of the implemented software and hardware complex is estimated. The prospects of the obtained results are discussed.

On the determination of certain astronomical, selenodesic, and gravitational parameters of the moon

NASA Technical Reports Server (NTRS)

Aleksashin, Y. P.; Ziman, Y. L.; Isavnina, I. V.; Krasikov, V. A.; Nepoklonov, B. V.; Rodionov, B. N.; Tischenko, A. P.

1974-01-01

A method was examined for joint construction of a selenocentric fundamental system which can be realized by a coordinate catalog of reference contour points uniformly positioned over the entire lunar surface, and determination of the parameters characterizing the gravitational field, rotation, and orbital motion of the moon. Characteristic of the problem formulation is the introduction of a new complex of inconometric measurements which can be made using pictures obtained from an artificial lunar satellite. The proposed method can be used to solve similar problems on any other planet for which surface images can be obtained from a spacecraft. Characteristic of the proposed technique for solving the problem is the joint statistical analysis of all forms of measurements: orbital iconometric, earth-based trajectory, and also a priori information on the parameters in question which is known from earth-based astronomical studies.

Effects of correlated parameters and uncertainty in electronic-structure-based chemical kinetic modelling

NASA Astrophysics Data System (ADS)

Sutton, Jonathan E.; Guo, Wei; Katsoulakis, Markos A.; Vlachos, Dionisios G.

2016-04-01

Kinetic models based on first principles are becoming common place in heterogeneous catalysis because of their ability to interpret experimental data, identify the rate-controlling step, guide experiments and predict novel materials. To overcome the tremendous computational cost of estimating parameters of complex networks on metal catalysts, approximate quantum mechanical calculations are employed that render models potentially inaccurate. Here, by introducing correlative global sensitivity analysis and uncertainty quantification, we show that neglecting correlations in the energies of species and reactions can lead to an incorrect identification of influential parameters and key reaction intermediates and reactions. We rationalize why models often underpredict reaction rates and show that, despite the uncertainty being large, the method can, in conjunction with experimental data, identify influential missing reaction pathways and provide insights into the catalyst active site and the kinetic reliability of a model. The method is demonstrated in ethanol steam reforming for hydrogen production for fuel cells.

Automatic Sleep Stage Determination by Multi-Valued Decision Making Based on Conditional Probability with Optimal Parameters

NASA Astrophysics Data System (ADS)

Wang, Bei; Sugi, Takenao; Wang, Xingyu; Nakamura, Masatoshi

Data for human sleep study may be affected by internal and external influences. The recorded sleep data contains complex and stochastic factors, which increase the difficulties for the computerized sleep stage determination techniques to be applied for clinical practice. The aim of this study is to develop an automatic sleep stage determination system which is optimized for variable sleep data. The main methodology includes two modules: expert knowledge database construction and automatic sleep stage determination. Visual inspection by a qualified clinician is utilized to obtain the probability density function of parameters during the learning process of expert knowledge database construction. Parameter selection is introduced in order to make the algorithm flexible. Automatic sleep stage determination is manipulated based on conditional probability. The result showed close agreement comparing with the visual inspection by clinician. The developed system can meet the customized requirements in hospitals and institutions.

Morphological characterization of coral reefs by combining lidar and MBES data: A case study from Yuanzhi Island, South China Sea

NASA Astrophysics Data System (ADS)

Zhang, Kai; Yang, Fanlin; Zhang, Hande; Su, Dianpeng; Li, QianQian

2017-06-01

The correlation between seafloor morphological features and biological complexity has been identified in numerous recent studies. This research focused on the potential for accurate characterization of coral reefs based on high-resolution bathymetry from multiple sources. A standard deviation (STD) based method for quantitatively characterizing terrain complexity was developed that includes robust estimation to correct for irregular bathymetry and a calibration for the depth-dependent variablity of measurement noise. Airborne lidar and shipborne sonar bathymetry measurements from Yuanzhi Island, South China Sea, were merged to generate seamless high-resolution coverage of coral bathymetry from the shoreline to deep water. The new algorithm was applied to the Yuanzhi Island surveys to generate maps of quantitive terrain complexity, which were then compared to in situ video observations of coral abundance. The terrain complexity parameter is significantly correlated with seafloor coral abundance, demonstrating the potential for accurately and efficiently mapping coral abundance through seafloor surveys, including combinations of surveys using different sensors.

Studying light-harvesting models with superconducting circuits.

PubMed

Potočnik, Anton; Bargerbos, Arno; Schröder, Florian A Y N; Khan, Saeed A; Collodo, Michele C; Gasparinetti, Simone; Salathé, Yves; Creatore, Celestino; Eichler, Christopher; Türeci, Hakan E; Chin, Alex W; Wallraff, Andreas

2018-03-02

The process of photosynthesis, the main source of energy in the living world, converts sunlight into chemical energy. The high efficiency of this process is believed to be enabled by an interplay between the quantum nature of molecular structures in photosynthetic complexes and their interaction with the environment. Investigating these effects in biological samples is challenging due to their complex and disordered structure. Here we experimentally demonstrate a technique for studying photosynthetic models based on superconducting quantum circuits, which complements existing experimental, theoretical, and computational approaches. We demonstrate a high degree of freedom in design and experimental control of our approach based on a simplified three-site model of a pigment protein complex with realistic parameters scaled down in energy by a factor of 10 5 . We show that the excitation transport between quantum-coherent sites disordered in energy can be enabled through the interaction with environmental noise. We also show that the efficiency of the process is maximized for structured noise resembling intramolecular phononic environments found in photosynthetic complexes.

An Integrated Framework for Parameter-based Optimization of Scientific Workflows.

PubMed

Kumar, Vijay S; Sadayappan, P; Mehta, Gaurang; Vahi, Karan; Deelman, Ewa; Ratnakar, Varun; Kim, Jihie; Gil, Yolanda; Hall, Mary; Kurc, Tahsin; Saltz, Joel

2009-01-01

Data analysis processes in scientific applications can be expressed as coarse-grain workflows of complex data processing operations with data flow dependencies between them. Performance optimization of these workflows can be viewed as a search for a set of optimal values in a multi-dimensional parameter space. While some performance parameters such as grouping of workflow components and their mapping to machines do not a ect the accuracy of the output, others may dictate trading the output quality of individual components (and of the whole workflow) for performance. This paper describes an integrated framework which is capable of supporting performance optimizations along multiple dimensions of the parameter space. Using two real-world applications in the spatial data analysis domain, we present an experimental evaluation of the proposed framework.

Simulation of the right-angle car collision based on identified parameters

NASA Astrophysics Data System (ADS)

Kostek, R.; Aleksandrowicz, P.

2017-10-01

This article presents an influence of contact parameters on the collision pattern of vehicles. In this case a crash of two Fiat Cinquecentos with perpendicular median planes was simulated. The first vehicle was driven with a speed 50 km/h and crashed into the other one, standing still. It is a typical collision at junctions. For the first simulation, the default parameters of the V-SIM simulation program were assumed and then the parameters identified from the crash test of a Fiat Cinquecento, published by ADAC (Allgemeiner Deutscher Automobil-Club) were used. Various post-impact movements were observed for both simulations, which demonstrates a sensitivity of the simulation results to the assumed parameters. Applying the default parameters offered by the program can lead to inadequate evaluation of the collision part due to its only approximate reconstruction, which in consequence, influences the court decision. It was demonstrated how complex it is to reconstruct the pattern of the vehicles’ crash and what problems are faced by expert witnesses who tend to use default parameters.

Hexaammine Complexes of Cr(III) and Co(III): A Spectral Study.

ERIC Educational Resources Information Center

Brown, D. R.; Pavlis, R. R.

1985-01-01

Procedures are provided for experiments containing complex ions with octahedral symmetry, hexaamminecobalt(III) chloride and hexaamminechromium(III) nitrate, so students can interpret fully the ultra violet/visible spectra of the complex cations in terms of the ligand field parameters, 10 "Dq," the Racah interelectron repulsion parameters, "B,"…

Nano-sized, quaternary titanium(IV) metal-organic frameworks with multidentate ligands.

PubMed

Baranwal, Balram Prasad; Singh, Alok Kumar

2010-12-01

Some mononuclear nano-sized, quaternary titanium(IV) complexes having the general formula [Ti(acac)(OOCR)2(SB)] (where Hacac=acetylacetone, R=C15H31 or C17H35, HSB=Schiff bases) have been synthesized using different multidentate ligands. These were characterized by elemental analyses, molecular weight determinations and spectral (FTIR, 1H NMR and powder XRD) studies. Conductance measurement indicated their non-conducting nature which may behave like insulators. Structural parameters like the values of limiting indices h, k, l, cell constants a, b, c, angles α, β, γ and particle size are calculated from powder XRD data for complex 1 which indicated nano-sized triclinic system in them. Bidentate chelating nature of acetylacetone, carboxylate and Schiff base anions in the complexes was established by their infrared spectra. Molecular weight determinations confirmed mononuclear nature of the complexes. On the basis of physico-chemical studies, coordination number 8 was assigned for titanium(IV) in the complexes. Transmission electron microscopy (TEM) and the selected area electron diffraction (SAED) studies indicated spherical particles with poor crystallinity. Copyright © 2010 Elsevier B.V. All rights reserved.

Polymer complexes.. XXXX. Supramolecular assembly on coordination models of mixed-valence-ligand poly[1-acrylamido-2-(2-pyridyl)ethane] complexes

NASA Astrophysics Data System (ADS)

El-Sonbati, A. Z.; El-Bindary, A. A.; Diab, M. A.

2003-02-01

The build-up of polymer metallic supramolecules based on homopolymer (1-acrylamido-2-(2-pyridyl)ethane (AEPH)) and ruthenium, rhodium, palladium as well as platinum complexes has been pursued with great interest. The homopolymer shows three types of coordination behaviour. In the mixed valence paramagnetic trinuclear polymer complexes [( 11)+( 12)] in the paper and in mononuclear polymer complexes ( 1)-( 5) it acts as a neutral bidentate ligand coordinating through the N-pyridine and NH-imino atoms, while in the mixed ligand diamagnetic poly-chelates, which are obtained from the reaction of AEPH with PdX 2 and KPtCl 4 in the presence of N-heterocyclic base consisting of polymer complexes ( 9)+( 10), and in monouclear compounds ( 6)-( 8), it behaves as a monobasic bidentate ligand coordinating through the same donor atoms. In mononuclear compounds ( 13)+( 14) it acts as a monobasic and neutral bidentate ligand coordinating only through the same donor atoms. Monomeric distorted octahedral or trimeric chlorine-bridged, approximately octahedral structures are proposed for these polymer complexes. The poly-chelates are of 1:1, 1:2 and 3:2 (metal-homopolymer) stoichiometry and exhibit six coordination. The values of ligand field parameters were calculated. The homopolymer and their polymer complexes have been characterized physicochemically.

Polymer complexes. XXXX. Supramolecular assembly on coordination models of mixed-valence-ligand poly[1-acrylamido-2-(2-pyridyl)ethane] complexes.

PubMed

El-Sonbati, A Z; El-Bindary, A A; Diab, M A

2003-02-01

The build-up of polymer metallic supramolecules based on homopolymer (1-acrylamido-2-(2-pyridyl)ethane (AEPH)) and ruthenium, rhodium, palladium as well as platinum complexes has been pursued with great interest. The homopolymer shows three types of coordination behaviour. In the mixed valence paramagnetic trinuclear polymer complexes [(11)+(12)] in the paper and in mononuclear polymer complexes (1)-(5) it acts as a neutral bidentate ligand coordinating through the N-pyridine and NH-imino atoms, while in the mixed ligand diamagnetic poly-chelates, which are obtained from the reaction of AEPH with PdX2 and KPtCl4 in the presence of N-heterocyclic base consisting of polymer complexes (9)+(10), and in monouclear compounds (6)-(8), it behaves as a monobasic bidentate ligand coordinating through the same donor atoms. In mononuclear compounds (13)+(14) it acts as a monobasic and neutral bidentate ligand coordinating only through the same donor atoms. Monomeric distorted octahedral or trimeric chlorine-bridged, approximately octahedral structures are proposed for these polymer complexes. The poly-chelates are of 1:1, 1:2 and 3:2 (metal-homopolymer) stoichiometry and exhibit six coordination. The values of ligand field parameters were calculated. The homopolymer and their polymer complexes have been characterized physicochemically.

Synthesis, structural characterization and photoluminescence properties of a novel La(III) complex

NASA Astrophysics Data System (ADS)

Köse, Muhammet; Ceyhan, Gökhan; Atcı, Emine; McKee, Vickie; Tümer, Mehmet

2015-05-01

In this study, a novel La(III) complex [La(H2L)2(NO3)3(MeOH)] of a Schiff base ligand was synthesized and characterized by spectroscopic and analytical methods. Single crystals of the complex suitable for X-ray diffraction study were obtained by slow diffusion of diethyl ether into a MeOH solution of the complex which was found to crystallise as [La(H2L)2(NO3)3(MeOH)]ṡ2MeOHṡH2O. The structure was solved in monoclinic crystal system, P21/n space group with unit cell parameters a = 10.5641(11), b = 12.6661(16), c = 16.0022(17) Å, α = 67.364(2), β = 83.794(2)°, γ = 70.541(2)°, V = 1862.9(4) Å3 and Z = 2 with R final value of 0.526. In the complex, the La(III) ion is ten-coordinated by O atoms, five of which come from three nitrate ions, four from the two Schiff base ligands and one from MeOH oxygen atom. The Schiff base ligands in the structure are in a zwitter ion form with the phenolic H transferred to the imine N atom. Thermal properties of the La(III) complex were examined by thermogravimetric analysis and the complex was found to be thermally stable up to 310 °C. The Schiff base ligand and its La(II) complex were screened for their in vitro antimicrobial activity against Bacillus megaterium, Staphylococcus aureus, Bacillus subtilis, Micrococcus luteus (Gram positive bacteria), Klebsiella pneumonia, Escherichia coli, Enterobacter aerogenes, Pseudomonas aeruginosa (Gram negative bacteria), Candida albicans,Yarrowia lipolytica (fungus) and Saccharomyces cerevisiae (yeast). The complex shows more antimicrobial activity than the free ligand.

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

Liu, Y.; Liu, Z.; Zhang, S.

Parameter estimation provides a potentially powerful approach to reduce model bias for complex climate models. Here, in a twin experiment framework, the authors perform the first parameter estimation in a fully coupled ocean–atmosphere general circulation model using an ensemble coupled data assimilation system facilitated with parameter estimation. The authors first perform single-parameter estimation and then multiple-parameter estimation. In the case of the single-parameter estimation, the error of the parameter [solar penetration depth (SPD)] is reduced by over 90% after ~40 years of assimilation of the conventional observations of monthly sea surface temperature (SST) and salinity (SSS). The results of multiple-parametermore » estimation are less reliable than those of single-parameter estimation when only the monthly SST and SSS are assimilated. Assimilating additional observations of atmospheric data of temperature and wind improves the reliability of multiple-parameter estimation. The errors of the parameters are reduced by 90% in ~8 years of assimilation. Finally, the improved parameters also improve the model climatology. With the optimized parameters, the bias of the climatology of SST is reduced by ~90%. Altogether, this study suggests the feasibility of ensemble-based parameter estimation in a fully coupled general circulation model.« less

Heavy ligand atom induced large magnetic anisotropy in Mn(ii) complexes.

PubMed

Chowdhury, Sabyasachi Roy; Mishra, Sabyashachi

2017-06-28

In the search for single molecule magnets, metal ions are considered pivotal towards achieving large magnetic anisotropy barriers. In this context, the influence of ligands with heavy elements, showing large spin-orbit coupling, on magnetic anisotropy barriers was investigated using a series of Mn(ii)-based complexes, in which the metal ion did not have any orbital contribution. The mixing of metal and ligand orbitals was achieved by explicitly correlating the metal and ligand valence electrons with CASSCF calculations. The CASSCF wave functions were further used for evaluating spin-orbit coupling and zero-field splitting parameters for these complexes. For Mn(ii) complexes with heavy ligand atoms, such as Br and I, several interesting inter-state mixings occur via the spin-orbit operator, which results in large magnetic anisotropy in these Mn(ii) complexes.

Restricted Complexity Framework for Nonlinear Adaptive Control in Complex Systems

NASA Astrophysics Data System (ADS)

Williams, Rube B.

2004-02-01

Control law adaptation that includes implicit or explicit adaptive state estimation, can be a fundamental underpinning for the success of intelligent control in complex systems, particularly during subsystem failures, where vital system states and parameters can be impractical or impossible to measure directly. A practical algorithm is proposed for adaptive state filtering and control in nonlinear dynamic systems when the state equations are unknown or are too complex to model analytically. The state equations and inverse plant model are approximated by using neural networks. A framework for a neural network based nonlinear dynamic inversion control law is proposed, as an extrapolation of prior developed restricted complexity methodology used to formulate the adaptive state filter. Examples of adaptive filter performance are presented for an SSME simulation with high pressure turbine failure to support extrapolations to adaptive control problems.

Modeling bed load transport and step-pool morphology with a reduced-complexity approach

NASA Astrophysics Data System (ADS)

Saletti, Matteo; Molnar, Peter; Hassan, Marwan A.; Burlando, Paolo

2016-04-01

Steep mountain channels are complex fluvial systems, where classical methods developed for lowland streams fail to capture the dynamics of sediment transport and bed morphology. Estimations of sediment transport based on average conditions have more than one order of magnitude of uncertainty because of the wide grain-size distribution of the bed material, the small relative submergence of coarse grains, the episodic character of sediment supply, and the complex boundary conditions. Most notably, bed load transport is modulated by the structure of the bed, where grains are imbricated in steps and similar bedforms and, therefore, they are much more stable then predicted. In this work we propose a new model based on a reduced-complexity (RC) approach focused on the reproduction of the step-pool morphology. In our 2-D cellular-automaton model entrainment, transport and deposition of particles are considered via intuitive rules based on physical principles. A parsimonious set of parameters allows the control of the behavior of the system, and the basic processes can be considered in a deterministic or stochastic way. The probability of entrainment of grains (and, as a consequence, particle travel distances and resting times) is a function of flow conditions and bed topography. Sediment input is fed at the upper boundary of the channel at a constant or variable rate. Our model yields realistic results in terms of longitudinal bed profiles and sediment transport trends. Phases of aggradation and degradation can be observed in the channel even under a constant input and the memory of the morphology can be quantified with long-range persistence indicators. Sediment yield at the channel outlet shows intermittency as observed in natural streams. Steps are self-formed in the channel and their stability is tested against the model parameters. Our results show the potential of RC models as complementary tools to more sophisticated models. They provide a realistic description of complex morphological systems and help to better identify the key physical principles that rule their dynamics.

Utility of charge-transfer complexation for the assessment of macrocyclic polyethers: Spectroscopic, thermal and surface morphology characteristics of two highly crown ethers complexed with acido acceptors

NASA Astrophysics Data System (ADS)

Refat, Moamen S.; Adam, Abdel Majid A.; Saad, Hosam A.

2015-04-01

The study of the complexing ability of macrocyclic compounds to organic and inorganic substances is of great interest. The aim of this work is to provide basic data that can be used to the assessment of macrocyclic crown ethers quantitatively based on charge-transfer (CT) complexation. This goal was achieved by preparing CT complexes of two interesting mixed nitrogen-oxygen crown ethers with acido acceptors (chloranilic and picric acid), which were fully structurally characterized. The crown ethers are 4,7,13,16,21,24-hexaoxa-1,10-diazabicyclo[8.8.8]hexacosane (HDHC) and 1,4,10-trioxa-7,13-diaza-cyclopentadecane (TDPD). The obtained complexes were structurally characterized via elemental analysis, IR, Raman, 1H NMR, and UV-visible spectroscopy. Thermal properties of these complexes were also studied, and their kinetic thermodynamic parameters were calculated. Furthermore, the microstructure properties of these complexes have also been investigated using X-ray diffraction (XRD) and scanning electron microscope (SEM).

Regional estimation of response routine parameters

NASA Astrophysics Data System (ADS)

Tøfte, Lena S.

2015-04-01

Reducing the number of calibration parameters is of a considerable advantage when area distributed hydrological models are to be calibrated, both due to equifinality and over-parameterization of the model in general, and for making the calibration process more efficient. A simple non-threshold response model for drainage in natural catchments based on among others Kirchner's article in WRR 2009 is implemented in the gridded hydrological model in the ENKI framework. This response model takes only the hydrogram into account; it has one state and two parameters, and is adapted to catchments that are dominated by terrain drainage. In former analyses of natural discharge series from a large number of catchments in different regions of Norway, we found that these response model parameters can be calculated from some known catchment characteristics, as catchment area and lake percentage, found in maps or data bases, meaning that the parameters can easily be found also for ungauged catchments. In the presented work from the EU project COMPLEX a large region in Mid-Norway containing 27 simulated catchments of different sizes and characteristics is calibrated. Results from two different calibration strategies are compared: 1) removing the response parameters from the calibration by calculating them in advance, based on the results from our former studies, and 2) including the response parameters in the calibration, both as maps with different values for each catchment, and as a constant number for the total region. The resulting simulation performances are compared and discussed.

Predicting protein complex geometries with a neural network.

PubMed

Chae, Myong-Ho; Krull, Florian; Lorenzen, Stephan; Knapp, Ernst-Walter

2010-03-01

A major challenge of the protein docking problem is to define scoring functions that can distinguish near-native protein complex geometries from a large number of non-native geometries (decoys) generated with noncomplexed protein structures (unbound docking). In this study, we have constructed a neural network that employs the information from atom-pair distance distributions of a large number of decoys to predict protein complex geometries. We found that docking prediction can be significantly improved using two different types of polar hydrogen atoms. To train the neural network, 2000 near-native decoys of even distance distribution were used for each of the 185 considered protein complexes. The neural network normalizes the information from different protein complexes using an additional protein complex identity input neuron for each complex. The parameters of the neural network were determined such that they mimic a scoring funnel in the neighborhood of the native complex structure. The neural network approach avoids the reference state problem, which occurs in deriving knowledge-based energy functions for scoring. We show that a distance-dependent atom pair potential performs much better than a simple atom-pair contact potential. We have compared the performance of our scoring function with other empirical and knowledge-based scoring functions such as ZDOCK 3.0, ZRANK, ITScore-PP, EMPIRE, and RosettaDock. In spite of the simplicity of the method and its functional form, our neural network-based scoring function achieves a reasonable performance in rigid-body unbound docking of proteins. Proteins 2010. (c) 2009 Wiley-Liss, Inc.

Ground Data System Analysis Tools to Track Flight System State Parameters for the Mars Science Laboratory (MSL) and Beyond

NASA Technical Reports Server (NTRS)

Allard, Dan; Deforrest, Lloyd

2014-01-01

Flight software parameters enable space mission operators fine-tuned control over flight system configurations, enabling rapid and dynamic changes to ongoing science activities in a much more flexible manner than can be accomplished with (otherwise broadly used) configuration file based approaches. The Mars Science Laboratory (MSL), Curiosity, makes extensive use of parameters to support complex, daily activities via commanded changes to said parameters in memory. However, as the loss of Mars Global Surveyor (MGS) in 2006 demonstrated, flight system management by parameters brings with it risks, including the possibility of losing track of the flight system configuration and the threat of invalid command executions. To mitigate this risk a growing number of missions have funded efforts to implement parameter tracking parameter state software tools and services including MSL and the Soil Moisture Active Passive (SMAP) mission. This paper will discuss the engineering challenges and resulting software architecture of MSL's onboard parameter state tracking software and discuss the road forward to make parameter management tools suitable for use on multiple missions.

Quantitative structure-property relationship modeling of beta-cyclodextrin complexation free energies.

PubMed

Katritzky, Alan R; Fara, Dan C; Yang, Hongfang; Karelson, Mati; Suzuki, Takahiro; Solov'ev, Vitaly P; Varnek, Alexandre

2004-01-01

CODESSA-PRO was used to model binding energies for 1:1 complexation systems between 218 organic guest molecules and beta-cyclodextrin, using a seven-parameter equation with R2 = 0.796 and Rcv2 = 0.779. Fragment-based TRAIL calculations gave a better fit with R2 = 0.943 and Rcv2 = 0.848 for 195 data points in the database. The advantages and disadvantages of each approach are discussed, and it is concluded that a combination of the two approaches has much promise from a practical viewpoint.

Mutually unbiased bases and semi-definite programming

NASA Astrophysics Data System (ADS)

Brierley, Stephen; Weigert, Stefan

2010-11-01

A complex Hilbert space of dimension six supports at least three but not more than seven mutually unbiased bases. Two computer-aided analytical methods to tighten these bounds are reviewed, based on a discretization of parameter space and on Gröbner bases. A third algorithmic approach is presented: the non-existence of more than three mutually unbiased bases in composite dimensions can be decided by a global optimization method known as semidefinite programming. The method is used to confirm that the spectral matrix cannot be part of a complete set of seven mutually unbiased bases in dimension six.

Bayesian analysis of physiologically based toxicokinetic and toxicodynamic models.

PubMed

Hack, C Eric

2006-04-17

Physiologically based toxicokinetic (PBTK) and toxicodynamic (TD) models of bromate in animals and humans would improve our ability to accurately estimate the toxic doses in humans based on available animal studies. These mathematical models are often highly parameterized and must be calibrated in order for the model predictions of internal dose to adequately fit the experimentally measured doses. Highly parameterized models are difficult to calibrate and it is difficult to obtain accurate estimates of uncertainty or variability in model parameters with commonly used frequentist calibration methods, such as maximum likelihood estimation (MLE) or least squared error approaches. The Bayesian approach called Markov chain Monte Carlo (MCMC) analysis can be used to successfully calibrate these complex models. Prior knowledge about the biological system and associated model parameters is easily incorporated in this approach in the form of prior parameter distributions, and the distributions are refined or updated using experimental data to generate posterior distributions of parameter estimates. The goal of this paper is to give the non-mathematician a brief description of the Bayesian approach and Markov chain Monte Carlo analysis, how this technique is used in risk assessment, and the issues associated with this approach.

Information spreading dynamics in hypernetworks

NASA Astrophysics Data System (ADS)

Suo, Qi; Guo, Jin-Li; Shen, Ai-Zhong

2018-04-01

Contact pattern and spreading strategy fundamentally influence the spread of information. Current mathematical methods largely assume that contacts between individuals are fixed by networks. In fact, individuals are affected by all his/her neighbors in different social relationships. Here, we develop a mathematical approach to depict the information spreading process in hypernetworks. Each individual is viewed as a node, and each social relationship containing the individual is viewed as a hyperedge. Based on SIS epidemic model, we construct two spreading models. One model is based on global transmission, corresponding to RP strategy. The other is based on local transmission, corresponding to CP strategy. These models can degenerate into complex network models with a special parameter. Thus hypernetwork models extend the traditional models and are more realistic. Further, we discuss the impact of parameters including structure parameters of hypernetwork, spreading rate, recovering rate as well as information seed on the models. Propagation time and density of informed nodes can reveal the overall trend of information dissemination. Comparing these two models, we find out that there is no spreading threshold in RP, while there exists a spreading threshold in CP. The RP strategy induces a broader and faster information spreading process under the same parameters.

Infrared and Raman studies of hydrogen bonded complexes involving acetone, acetophenone and benzophenone—I. Thermodynamic constants and frequency shifts of the ν OH and ν CO stretching vibrations

NASA Astrophysics Data System (ADS)

Thijs, R.; Zeegers-Huyskens, Th.

The hydrogen bonded complexes between phenol derivatives and acetone ( I), acetophenone ( II) and benzophenone ( III) have been studied in carbon tetrachloride solution by i.r. spectroscopy. The formation constants, the enthalpies of complex formation, the Δν OH and Δν CO values have been determined. For a given phenol derivative, the thermodynamic constants and Δν OH are ordered according to I > II > III and the influence of a substituent implanted on the phenolic ring can be expressed by the Hammett relationship. The ϱ coefficients of the Hammett equation are related to the complexation enthalpies. The Badger—Bauer relation is valid for the three bases. The comparison with complexes involving other carbonyl bases allows to precise the influence of the substituent implanted on the carbonyl group. The Δν OH values obey the dual substituent parameter equation using σ I and σ +R; the ϱ I/ϱ R ratio is higher than one. The Δν CO values are shown to depend on the complexation enthalpy and on the delocalization effect of the substituents.

Parameter identification for nonlinear aerodynamic systems

NASA Technical Reports Server (NTRS)

Pearson, Allan E.

1990-01-01

Parameter identification for nonlinear aerodynamic systems is examined. It is presumed that the underlying model can be arranged into an input/output (I/O) differential operator equation of a generic form. The algorithm estimation is especially efficient since the equation error can be integrated exactly given any I/O pair to obtain an algebraic function of the parameters. The algorithm for parameter identification was extended to the order determination problem for linear differential system. The degeneracy in a least squares estimate caused by feedback was addressed. A method of frequency analysis for determining the transfer function G(j omega) from transient I/O data was formulated using complex valued Fourier based modulating functions in contrast with the trigonometric modulating functions for the parameter estimation problem. A simulation result of applying the algorithm is given under noise-free conditions for a system with a low pass transfer function.

Parasitic Parameters Extraction for InP DHBT Based on EM Method and Validation up to H-Band

NASA Astrophysics Data System (ADS)

Li, Oupeng; Zhang, Yong; Wang, Lei; Xu, Ruimin; Cheng, Wei; Wang, Yuan; Lu, Haiyan

2017-05-01

This paper presents a small-signal model for InGaAs/InP double heterojunction bipolar transistor (DHBT). Parasitic parameters of access via and electrode finger are extracted by 3-D electromagnetic (EM) simulation. By analyzing the equivalent circuit of seven special structures and using the EM simulation results, the parasitic parameters are extracted systematically. Compared with multi-port s-parameter EM model, the equivalent circuit model has clear physical intension and avoids the complex internal ports setting. The model is validated on a 0.5 × 7 μm2 InP DHBT up to 325 GHz. The model provides a good fitting result between measured and simulated multi-bias s-parameters in full band. At last, an H-band amplifier is designed and fabricated for further verification. The measured amplifier performance is highly agreed with the model prediction, which indicates the model has good accuracy in submillimeterwave band.

The need for control of magnetic parameters for energy efficient performance of magnetic tunnel junctions

NASA Astrophysics Data System (ADS)

Farhat, I. A. H.; Gale, E.; Alpha, C.; Isakovic, A. F.

2017-07-01

Optimizing energy performance of Magnetic Tunnel Junctions (MTJs) is the key for embedding Spin Transfer Torque-Random Access Memory (STT-RAM) in low power circuits. Due to the complex interdependencies of the parameters and variables of the device operating energy, it is important to analyse parameters with most effective control of MTJ power. The impact of threshold current density, Jco , on the energy and the impact of HK on Jco are studied analytically, following the expressions that stem from Landau-Lifshitz-Gilbert-Slonczewski (LLGS-STT) model. In addition, the impact of other magnetic material parameters, such as Ms , and geometric parameters such as tfree and λ is discussed. Device modelling study was conducted to analyse the impact at the circuit level. Nano-magnetism simulation based on NMAGTM package was conducted to analyse the impact of controlling HK on the switching dynamics of the film.

Coupling Network Computing Applications in Air-cooled Turbine Blades Optimization

NASA Astrophysics Data System (ADS)

Shi, Liang; Yan, Peigang; Xie, Ming; Han, Wanjin

2018-05-01

Through establishing control parameters from blade outside to inside, the parametric design of air-cooled turbine blade based on airfoil has been implemented. On the basis of fast updating structure features and generating solid model, a complex cooling system has been created. Different flow units are modeled into a complex network topology with parallel and serial connection. Applying one-dimensional flow theory, programs have been composed to get pipeline network physical quantities along flow path, including flow rate, pressure, temperature and other parameters. These inner units parameters set as inner boundary conditions for external flow field calculation program HIT-3D by interpolation, thus to achieve full field thermal coupling simulation. Referring the studies in literatures to verify the effectiveness of pipeline network program and coupling algorithm. After that, on the basis of a modified design, and with the help of iSIGHT-FD, an optimization platform had been established. Through MIGA mechanism, the target of enhancing cooling efficiency has been reached, and the thermal stress has been effectively reduced. Research work in this paper has significance for rapid deploying the cooling structure design.

Parameter Estimation in Epidemiology: from Simple to Complex Dynamics

NASA Astrophysics Data System (ADS)

Aguiar, Maíra; Ballesteros, Sebastién; Boto, João Pedro; Kooi, Bob W.; Mateus, Luís; Stollenwerk, Nico

2011-09-01

We revisit the parameter estimation framework for population biological dynamical systems, and apply it to calibrate various models in epidemiology with empirical time series, namely influenza and dengue fever. When it comes to more complex models like multi-strain dynamics to describe the virus-host interaction in dengue fever, even most recently developed parameter estimation techniques, like maximum likelihood iterated filtering, come to their computational limits. However, the first results of parameter estimation with data on dengue fever from Thailand indicate a subtle interplay between stochasticity and deterministic skeleton. The deterministic system on its own already displays complex dynamics up to deterministic chaos and coexistence of multiple attractors.

Water Quality Assessment in the Harbin Reach of the Songhuajiang River (China) Based on a Fuzzy Rough Set and an Attribute Recognition Theoretical Model

PubMed Central

An, Yan; Zou, Zhihong; Li, Ranran

2014-01-01

A large number of parameters are acquired during practical water quality monitoring. If all the parameters are used in water quality assessment, the computational complexity will definitely increase. In order to reduce the input space dimensions, a fuzzy rough set was introduced to perform attribute reduction. Then, an attribute recognition theoretical model and entropy method were combined to assess water quality in the Harbin reach of the Songhuajiang River in China. A dataset consisting of ten parameters was collected from January to October in 2012. Fuzzy rough set was applied to reduce the ten parameters to four parameters: BOD5, NH3-N, TP, and F. coli (Reduct A). Considering that DO is a usual parameter in water quality assessment, another reduct, including DO, BOD5, NH3-N, TP, TN, F, and F. coli (Reduct B), was obtained. The assessment results of Reduct B show a good consistency with those of Reduct A, and this means that DO is not always necessary to assess water quality. The results with attribute reduction are not exactly the same as those without attribute reduction, which can be attributed to the α value decided by subjective experience. The assessment results gained by the fuzzy rough set obviously reduce computational complexity, and are acceptable and reliable. The model proposed in this paper enhances the water quality assessment system. PMID:24675643

Appropriate use of the increment entropy for electrophysiological time series.

PubMed

Liu, Xiaofeng; Wang, Xue; Zhou, Xu; Jiang, Aimin

2018-04-01

The increment entropy (IncrEn) is a new measure for quantifying the complexity of a time series. There are three critical parameters in the IncrEn calculation: N (length of the time series), m (dimensionality), and q (quantifying precision). However, the question of how to choose the most appropriate combination of IncrEn parameters for short datasets has not been extensively explored. The purpose of this research was to provide guidance on choosing suitable IncrEn parameters for short datasets by exploring the effects of varying the parameter values. We used simulated data, epileptic EEG data and cardiac interbeat (RR) data to investigate the effects of the parameters on the calculated IncrEn values. The results reveal that IncrEn is sensitive to changes in m, q and N for short datasets (N≤500). However, IncrEn reaches stability at a data length of N=1000 with m=2 and q=2, and for short datasets (N=100), it shows better relative consistency with 2≤m≤6 and 2≤q≤8 We suggest that the value of N should be no less than 100. To enable a clear distinction between different classes based on IncrEn, we recommend that m and q should take values between 2 and 4. With appropriate parameters, IncrEn enables the effective detection of complexity variations in physiological time series, suggesting that IncrEn should be useful for the analysis of physiological time series in clinical applications. Copyright © 2018 Elsevier Ltd. All rights reserved.

Defense Resource Planning Under Uncertainty: An Application of Robust Decision Making to Munitions Mix Planning

DTIC Science & Technology

2016-02-01

In addition , the parser updates some parameters based on uncertainties. For example, Analytica was very slow to update Pk values based on...moderate range. The additional security environments helped to fill gaps in lower severity. Weapons Effectiveness Pk values were modified to account for two...project is to help improve the value and character of defense resource planning in an era of growing uncertainty and complex strategic challenges

Inferring interactions in complex microbial communities from nucleotide sequence data and environmental parameters

PubMed Central

Shang, Yu; Sikorski, Johannes; Bonkowski, Michael; Fiore-Donno, Anna-Maria; Kandeler, Ellen; Marhan, Sven; Boeddinghaus, Runa S.; Solly, Emily F.; Schrumpf, Marion; Schöning, Ingo; Wubet, Tesfaye; Buscot, Francois; Overmann, Jörg

2017-01-01

Interactions occur between two or more organisms affecting each other. Interactions are decisive for the ecology of the organisms. Without direct experimental evidence the analysis of interactions is difficult. Correlation analyses that are based on co-occurrences are often used to approximate interaction. Here, we present a new mathematical model to estimate the interaction strengths between taxa, based on changes in their relative abundances across environmental gradients. PMID:28288199

Assessing the applicability of WRF optimal parameters under the different precipitation simulations in the Greater Beijing Area

NASA Astrophysics Data System (ADS)

Di, Zhenhua; Duan, Qingyun; Wang, Chen; Ye, Aizhong; Miao, Chiyuan; Gong, Wei

2018-03-01

Forecasting skills of the complex weather and climate models have been improved by tuning the sensitive parameters that exert the greatest impact on simulated results based on more effective optimization methods. However, whether the optimal parameter values are still work when the model simulation conditions vary, which is a scientific problem deserving of study. In this study, a highly-effective optimization method, adaptive surrogate model-based optimization (ASMO), was firstly used to tune nine sensitive parameters from four physical parameterization schemes of the Weather Research and Forecasting (WRF) model to obtain better summer precipitation forecasting over the Greater Beijing Area in China. Then, to assess the applicability of the optimal parameter values, simulation results from the WRF model with default and optimal parameter values were compared across precipitation events, boundary conditions, spatial scales, and physical processes in the Greater Beijing Area. The summer precipitation events from 6 years were used to calibrate and evaluate the optimal parameter values of WRF model. Three boundary data and two spatial resolutions were adopted to evaluate the superiority of the calibrated optimal parameters to default parameters under the WRF simulations with different boundary conditions and spatial resolutions, respectively. Physical interpretations of the optimal parameters indicating how to improve precipitation simulation results were also examined. All the results showed that the optimal parameters obtained by ASMO are superior to the default parameters for WRF simulations for predicting summer precipitation in the Greater Beijing Area because the optimal parameters are not constrained by specific precipitation events, boundary conditions, and spatial resolutions. The optimal values of the nine parameters were determined from 127 parameter samples using the ASMO method, which showed that the ASMO method is very highly-efficient for optimizing WRF model parameters.

A novel approach to the dynamical complexity of the Earth's magnetosphere at geomagnetic storm time-scales based on recurrences

NASA Astrophysics Data System (ADS)

Donner, Reik; Balasis, Georgios; Stolbova, Veronika; Wiedermann, Marc; Georgiou, Marina; Kurths, Jürgen

2016-04-01

Magnetic storms are the most prominent global manifestations of out-of-equilibrium magnetospheric dynamics. Investigating the dynamical complexity exhibited by geomagnetic observables can provide valuable insights into relevant physical processes as well as temporal scales associated with this phenomenon. In this work, we introduce several innovative data analysis techniques enabling a quantitative analysis of the Dst index non-stationary behavior. Using recurrence quantification analysis (RQA) and recurrence network analysis (RNA), we obtain a variety of complexity measures serving as markers of quiet- and storm-time magnetospheric dynamics. We additionally apply these techniques to the main driver of Dst index variations, the V BSouth coupling function and interplanetary medium parameters Bz and Pdyn in order to discriminate internal processes from the magnetosphere's response directly induced by the external forcing by the solar wind. The derived recurrence-based measures allow us to improve the accuracy with which magnetospheric storms can be classified based on ground-based observations. The new methodology presented here could be of significant interest for the space weather research community working on time series analysis for magnetic storm forecasts.

Expert-guided optimization for 3D printing of soft and liquid materials.

PubMed

Abdollahi, Sara; Davis, Alexander; Miller, John H; Feinberg, Adam W

2018-01-01

Additive manufacturing (AM) has rapidly emerged as a disruptive technology to build mechanical parts, enabling increased design complexity, low-cost customization and an ever-increasing range of materials. Yet these capabilities have also created an immense challenge in optimizing the large number of process parameters in order achieve a high-performance part. This is especially true for AM of soft, deformable materials and for liquid-like resins that require experimental printing methods. Here, we developed an expert-guided optimization (EGO) strategy to provide structure in exploring and improving the 3D printing of liquid polydimethylsiloxane (PDMS) elastomer resin. EGO uses three steps, starting first with expert screening to select the parameter space, factors, and factor levels. Second is a hill-climbing algorithm to search the parameter space defined by the expert for the best set of parameters. Third is expert decision making to try new factors or a new parameter space to improve on the best current solution. We applied the algorithm to two calibration objects, a hollow cylinder and a five-sided hollow cube that were evaluated based on a multi-factor scoring system. The optimum print settings were then used to print complex PDMS and epoxy 3D objects, including a twisted vase, water drop, toe, and ear, at a level of detail and fidelity previously not obtained.

Expert-guided optimization for 3D printing of soft and liquid materials

PubMed Central

Abdollahi, Sara; Davis, Alexander; Miller, John H.

2018-01-01

Additive manufacturing (AM) has rapidly emerged as a disruptive technology to build mechanical parts, enabling increased design complexity, low-cost customization and an ever-increasing range of materials. Yet these capabilities have also created an immense challenge in optimizing the large number of process parameters in order achieve a high-performance part. This is especially true for AM of soft, deformable materials and for liquid-like resins that require experimental printing methods. Here, we developed an expert-guided optimization (EGO) strategy to provide structure in exploring and improving the 3D printing of liquid polydimethylsiloxane (PDMS) elastomer resin. EGO uses three steps, starting first with expert screening to select the parameter space, factors, and factor levels. Second is a hill-climbing algorithm to search the parameter space defined by the expert for the best set of parameters. Third is expert decision making to try new factors or a new parameter space to improve on the best current solution. We applied the algorithm to two calibration objects, a hollow cylinder and a five-sided hollow cube that were evaluated based on a multi-factor scoring system. The optimum print settings were then used to print complex PDMS and epoxy 3D objects, including a twisted vase, water drop, toe, and ear, at a level of detail and fidelity previously not obtained. PMID:29621286

Ga metal nanoparticle-GaAs quantum molecule complexes for Terahertz generation.

PubMed

Bietti, Sergio; Basso Basset, Francesco; Scarpellini, David; Fedorov, Alexey; Ballabio, Andrea; Esposito, Luca; Elborg, Martin; Kuroda, Takashi; Nemcsics, Akos; Toth, Lajos; Manzoni, Cristian; Vozzi, Caterina; Sanguinetti, Stefano

2018-06-18

A hybrid metal-semiconductor nanosystem for the generation of THz radiation, based on the fabrication of GaAs quantum molecules-Ga metal nanoparticles complexes through a self assembly approach, is proposed. The role of the growth parameters, the substrate temperature, the Ga and As flux during the quantum dot molecule fabrication and the metal nanoparticle alignment is discussed. The tuning of the relative positioning of quantum dot molecules and metal nanoparticles is obtained through the careful control of Ga droplet nucleation sites via Ga surface diffusion. The electronic structure of a typical quantum dot molecule was evaluated on the base of the morphological characterizations performed by Atomic Force Microscopy and cross sectional Scanning Electron Microscopy, and the predicted results confirmed by micro-photoluminescence experiments, showing that the Ga metal nanoparticle-GaAs quantum molecule complexes are suitable for terahertz generation from intraband transition. . © 2018 IOP Publishing Ltd.

Ground-based remote sensing observation of the complex behaviour of the Marseille boundary layer during ESCOMPTE

NASA Astrophysics Data System (ADS)

Delbarre, H.; Augustin, P.; Saïd, F.; Campistron, B.; Bénech, B.; Lohou, F.; Puygrenier, V.; Moppert, C.; Cousin, F.; Fréville, P.; Fréjafon, E.

2005-03-01

Ground-based remote sensing systems have been used during the ESCOMPTE campaign, to continuously characterize the boundary-layer behaviour through many atmospheric parameters (wind, extinction and ozone concentration distribution, reflectivity, turbulence). This analysis is focused on the comparison of the atmospheric stratification retrieved from a UV angular ozone lidar, an Ultra High Frequency wind profiler and a sodar, above the area of Marseille, on June 26th 2001 (Intensive Observation Period 2b). The atmospheric stratification is shown to be very complex including two superimposed sea breezes, with an important contribution of advection. The temporal and spatial evolution of the stratification observed by the UV lidar and by the UHF radar are in good agreement although the origin of the echoes of these systems is quite different. The complexity of the dynamic situation has only partially been retrieved by a non-hydrostatic mesoscale model used with a 3 km resolution.

Synthesis, structure and antidiabetic activity of chromium(III) complexes of metformin Schiff-bases

NASA Astrophysics Data System (ADS)

Mahmoud, M. A.; Zaitone, S. A.; Ammar, A. M.; Sallam, S. A.

2016-03-01

A series of Cr3+ complexes with Schiff-bases of metformin with each of salicylaldehyde (HL1); 2,3-dihydroxybenzaldehyde (H2L2); 2,4-dihydroxybenzaldehyde (H2L3); 2,5-dihydroxybenzaldehyde (H2L4); 3,4-dihydroxybenzaldehyde (H2L5) and 2-hydroxynaphthaldehyde (HL6) were synthesized by template reaction. The new compounds were characterized through elemental analysis, conductivity and magnetic moment measurements, IR, UV-Vis., NMR and mass spectroscopy. The complexes have octahedral structure with μ value of hexacoordinated chromium ion. TGA, DTG and DTA analysis confirm the proposed stereochemistry and a mechanism for thermal decomposition was proposed. Thermodynamic parameters are calculated for the second and third decomposition steps. [CrL4Cl(H2O)2].3H2O and [CrL5Cl(H2O)2].2½H2O were able to produce significant decreases in the blood glucose level.

A parametric model for the changes in the complex valued conductivity of a lung during tidal breathing

NASA Astrophysics Data System (ADS)

Nordebo, Sven; Dalarsson, Mariana; Khodadad, Davood; Müller, Beat; Waldmann, Andreas D.; Becher, Tobias; Frerichs, Inez; Sophocleous, Louiza; Sjöberg, Daniel; Seifnaraghi, Nima; Bayford, Richard

2018-05-01

Classical homogenization theory based on the Hashin–Shtrikman coated ellipsoids is used to model the changes in the complex valued conductivity (or admittivity) of a lung during tidal breathing. Here, the lung is modeled as a two-phase composite material where the alveolar air-filling corresponds to the inclusion phase. The theory predicts a linear relationship between the real and the imaginary parts of the change in the complex valued conductivity of a lung during tidal breathing, and where the loss cotangent of the change is approximately the same as of the effective background conductivity and hence easy to estimate. The theory is illustrated with numerical examples based on realistic parameter values and frequency ranges used with electrical impedance tomography (EIT). The theory may be potentially useful for imaging and clinical evaluations in connection with lung EIT for respiratory management and control.

Accuracy and Calibration of High Explosive Thermodynamic Equations of State

NASA Astrophysics Data System (ADS)

Baker, Ernest L.; Capellos, Christos; Stiel, Leonard I.; Pincay, Jack

2010-10-01

The Jones-Wilkins-Lee-Baker (JWLB) equation of state (EOS) was developed to more accurately describe overdriven detonation while maintaining an accurate description of high explosive products expansion work output. The increased mathematical complexity of the JWLB high explosive equations of state provides increased accuracy for practical problems of interest. Increased numbers of parameters are often justified based on improved physics descriptions but can also mean increased calibration complexity. A generalized extent of aluminum reaction Jones-Wilkins-Lee (JWL)-based EOS was developed in order to more accurately describe the observed behavior of aluminized explosives detonation products expansion. A calibration method was developed to describe the unreacted, partially reacted, and completely reacted explosive using nonlinear optimization. A reasonable calibration of a generalized extent of aluminum reaction JWLB EOS as a function of aluminum reaction fraction has not yet been achieved due to the increased mathematical complexity of the JWLB form.

Model-based spectral estimation of Doppler signals using parallel genetic algorithms.

PubMed

Solano González, J; Rodríguez Vázquez, K; García Nocetti, D F

2000-05-01

Conventional spectral analysis methods use a fast Fourier transform (FFT) on consecutive or overlapping windowed data segments. For Doppler ultrasound signals, this approach suffers from an inadequate frequency resolution due to the time segment duration and the non-stationarity characteristics of the signals. Parametric or model-based estimators can give significant improvements in the time-frequency resolution at the expense of a higher computational complexity. This work describes an approach which implements in real-time a parametric spectral estimator method using genetic algorithms (GAs) in order to find the optimum set of parameters for the adaptive filter that minimises the error function. The aim is to reduce the computational complexity of the conventional algorithm by using the simplicity associated to GAs and exploiting its parallel characteristics. This will allow the implementation of higher order filters, increasing the spectrum resolution, and opening a greater scope for using more complex methods.

Ensemble urban flood simulation in comparison with laboratory-scale experiments: Impact of interaction models for manhole, sewer pipe, and surface flow

NASA Astrophysics Data System (ADS)

Noh, Seong Jin; Lee, Seungsoo; An, Hyunuk; Kawaike, Kenji; Nakagawa, Hajime

2016-11-01

An urban flood is an integrated phenomenon that is affected by various uncertainty sources such as input forcing, model parameters, complex geometry, and exchanges of flow among different domains in surfaces and subsurfaces. Despite considerable advances in urban flood modeling techniques, limited knowledge is currently available with regard to the impact of dynamic interaction among different flow domains on urban floods. In this paper, an ensemble method for urban flood modeling is presented to consider the parameter uncertainty of interaction models among a manhole, a sewer pipe, and surface flow. Laboratory-scale experiments on urban flood and inundation are performed under various flow conditions to investigate the parameter uncertainty of interaction models. The results show that ensemble simulation using interaction models based on weir and orifice formulas reproduces experimental data with high accuracy and detects the identifiability of model parameters. Among interaction-related parameters, the parameters of the sewer-manhole interaction show lower uncertainty than those of the sewer-surface interaction. Experimental data obtained under unsteady-state conditions are more informative than those obtained under steady-state conditions to assess the parameter uncertainty of interaction models. Although the optimal parameters vary according to the flow conditions, the difference is marginal. Simulation results also confirm the capability of the interaction models and the potential of the ensemble-based approaches to facilitate urban flood simulation.

Robust estimation of fractal measures for characterizing the structural complexity of the human brain: optimization and reproducibility

PubMed Central

Goñi, Joaquín; Sporns, Olaf; Cheng, Hu; Aznárez-Sanado, Maite; Wang, Yang; Josa, Santiago; Arrondo, Gonzalo; Mathews, Vincent P; Hummer, Tom A; Kronenberger, William G; Avena-Koenigsberger, Andrea; Saykin, Andrew J.; Pastor, María A.

2013-01-01

High-resolution isotropic three-dimensional reconstructions of human brain gray and white matter structures can be characterized to quantify aspects of their shape, volume and topological complexity. In particular, methods based on fractal analysis have been applied in neuroimaging studies to quantify the structural complexity of the brain in both healthy and impaired conditions. The usefulness of such measures for characterizing individual differences in brain structure critically depends on their within-subject reproducibility in order to allow the robust detection of between-subject differences. This study analyzes key analytic parameters of three fractal-based methods that rely on the box-counting algorithm with the aim to maximize within-subject reproducibility of the fractal characterizations of different brain objects, including the pial surface, the cortical ribbon volume, the white matter volume and the grey matter/white matter boundary. Two separate datasets originating from different imaging centers were analyzed, comprising, 50 subjects with three and 24 subjects with four successive scanning sessions per subject, respectively. The reproducibility of fractal measures was statistically assessed by computing their intra-class correlations. Results reveal differences between different fractal estimators and allow the identification of several parameters that are critical for high reproducibility. Highest reproducibility with intra-class correlations in the range of 0.9–0.95 is achieved with the correlation dimension. Further analyses of the fractal dimensions of parcellated cortical and subcortical gray matter regions suggest robustly estimated and region-specific patterns of individual variability. These results are valuable for defining appropriate parameter configurations when studying changes in fractal descriptors of human brain structure, for instance in studies of neurological diseases that do not allow repeated measurements or for disease-course longitudinal studies. PMID:23831414

Validation and uncertainty analysis of a pre-treatment 2D dose prediction model

NASA Astrophysics Data System (ADS)

Baeza, Jose A.; Wolfs, Cecile J. A.; Nijsten, Sebastiaan M. J. J. G.; Verhaegen, Frank

2018-02-01

Independent verification of complex treatment delivery with megavolt photon beam radiotherapy (RT) has been effectively used to detect and prevent errors. This work presents the validation and uncertainty analysis of a model that predicts 2D portal dose images (PDIs) without a patient or phantom in the beam. The prediction model is based on an exponential point dose model with separable primary and secondary photon fluence components. The model includes a scatter kernel, off-axis ratio map, transmission values and penumbra kernels for beam-delimiting components. These parameters were derived through a model fitting procedure supplied with point dose and dose profile measurements of radiation fields. The model was validated against a treatment planning system (TPS; Eclipse) and radiochromic film measurements for complex clinical scenarios, including volumetric modulated arc therapy (VMAT). Confidence limits on fitted model parameters were calculated based on simulated measurements. A sensitivity analysis was performed to evaluate the effect of the parameter uncertainties on the model output. For the maximum uncertainty, the maximum deviating measurement sets were propagated through the fitting procedure and the model. The overall uncertainty was assessed using all simulated measurements. The validation of the prediction model against the TPS and the film showed a good agreement, with on average 90.8% and 90.5% of pixels passing a (2%,2 mm) global gamma analysis respectively, with a low dose threshold of 10%. The maximum and overall uncertainty of the model is dependent on the type of clinical plan used as input. The results can be used to study the robustness of the model. A model for predicting accurate 2D pre-treatment PDIs in complex RT scenarios can be used clinically and its uncertainties can be taken into account.

Ranking streamflow model performance based on Information theory metrics

NASA Astrophysics Data System (ADS)

Martinez, Gonzalo; Pachepsky, Yakov; Pan, Feng; Wagener, Thorsten; Nicholson, Thomas

2016-04-01

The accuracy-based model performance metrics not necessarily reflect the qualitative correspondence between simulated and measured streamflow time series. The objective of this work was to use the information theory-based metrics to see whether they can be used as complementary tool for hydrologic model evaluation and selection. We simulated 10-year streamflow time series in five watersheds located in Texas, North Carolina, Mississippi, and West Virginia. Eight model of different complexity were applied. The information-theory based metrics were obtained after representing the time series as strings of symbols where different symbols corresponded to different quantiles of the probability distribution of streamflow. The symbol alphabet was used. Three metrics were computed for those strings - mean information gain that measures the randomness of the signal, effective measure complexity that characterizes predictability and fluctuation complexity that characterizes the presence of a pattern in the signal. The observed streamflow time series has smaller information content and larger complexity metrics than the precipitation time series. Watersheds served as information filters and and streamflow time series were less random and more complex than the ones of precipitation. This is reflected the fact that the watershed acts as the information filter in the hydrologic conversion process from precipitation to streamflow. The Nash Sutcliffe efficiency metric increased as the complexity of models increased, but in many cases several model had this efficiency values not statistically significant from each other. In such cases, ranking models by the closeness of the information-theory based parameters in simulated and measured streamflow time series can provide an additional criterion for the evaluation of hydrologic model performance.

Empirical scoring functions for advanced protein-ligand docking with PLANTS.

PubMed

Korb, Oliver; Stützle, Thomas; Exner, Thomas E

2009-01-01

In this paper we present two empirical scoring functions, PLANTS(CHEMPLP) and PLANTS(PLP), designed for our docking algorithm PLANTS (Protein-Ligand ANT System), which is based on ant colony optimization (ACO). They are related, regarding their functional form, to parts of already published scoring functions and force fields. The parametrization procedure described here was able to identify several parameter settings showing an excellent performance for the task of pose prediction on two test sets comprising 298 complexes in total. Up to 87% of the complexes of the Astex diverse set and 77% of the CCDC/Astex clean listnc (noncovalently bound complexes of the clean list) could be reproduced with root-mean-square deviations of less than 2 A with respect to the experimentally determined structures. A comparison with the state-of-the-art docking tool GOLD clearly shows that this is, especially for the druglike Astex diverse set, an improvement in pose prediction performance. Additionally, optimized parameter settings for the search algorithm were identified, which can be used to balance pose prediction reliability and search speed.

A Relationship Between Visual Complexity and Aesthetic Appraisal of Car Front Images: An Eye-Tracker Study.

PubMed

Chassy, Philippe; Lindell, Trym A E; Jones, Jessica A; Paramei, Galina V

2015-01-01

Image aesthetic pleasure (AP) is conjectured to be related to image visual complexity (VC). The aim of the present study was to investigate whether (a) two image attributes, AP and VC, are reflected in eye-movement parameters; and (b) subjective measures of AP and VC are related. Participants (N=26) explored car front images (M=50) while their eye movements were recorded. Following image exposure (10 seconds), its VC and AP were rated. Fixation count was found to positively correlate with the subjective VC and its objective proxy, JPEG compression size, suggesting that this eye-movement parameter can be considered an objective behavioral measure of VC. AP, in comparison, positively correlated with average dwelling time. Subjective measures of AP and VC were related too, following an inverted U-shape function best-fit by a quadratic equation. In addition, AP was found to be modulated by car prestige. Our findings reveal a close relationship between subjective and objective measures of complexity and aesthetic appraisal, which is interpreted within a prototype-based theory framework. © The Author(s) 2015.

Design of a transverse-flux permanent-magnet linear generator and controller for use with a free-piston stirling engine

NASA Astrophysics Data System (ADS)

Zheng, Jigui; Huang, Yuping; Wu, Hongxing; Zheng, Ping

2016-07-01

Transverse-flux with high efficiency has been applied in Stirling engine and permanent magnet synchronous linear generator system, however it is restricted for large application because of low and complex process. A novel type of cylindrical, non-overlapping, transverse-flux, and permanent-magnet linear motor(TFPLM) is investigated, furthermore, a high power factor and less process complexity structure research is developed. The impact of magnetic leakage factor on power factor is discussed, by using the Finite Element Analysis(FEA) model of stirling engine and TFPLM, an optimization method for electro-magnetic design of TFPLM is proposed based on magnetic leakage factor. The relation between power factor and structure parameter is investigated, and a structure parameter optimization method is proposed taking power factor maximum as a goal. At last, the test bench is founded, starting experimental and generating experimental are performed, and a good agreement of simulation and experimental is achieved. The power factor is improved and the process complexity is decreased. This research provides the instruction to design high-power factor permanent-magnet linear generator.

Spectroscopic Study of the Binding of Netropsin and Hoechst 33258 to Nucleic Acids

NASA Astrophysics Data System (ADS)

Vardevanyan, P. O.; Parsadanyan, M. A.; Antonyan, A. P.; Sahakyan, V. G.

2018-05-01

The interaction of groove binding compounds — peptide antibiotic (polyamide) netropsin and fluorescent dye (bisbenzimidazole) Hoechst 33258 — with the double-stranded DNA and synthetic double-stranded polynucleotide poly(rA)-poly(rU) has been studied by spectrophotometry. Absorption spectra of these ligand complexes with nucleic acids have been obtained. Spectral changes at the complexation of individual ligands with the mentioned nucleic acids reveal the similarity of binding of each of these ligands with both DNA and RNA. Based on the spectroscopic measurements, the binding parameters of netropsin and Hoechst 33258 binding to DNA and poly(rA)-poly(rU) - K and n, as well as the thermodynamic parameters ΔS, ΔG, and ΔH have been determined. It was found that the binding of Hoechst 33258 to both nucleic acids is accompanied by a positive change in enthalpy, while in the case of netropsin the change in enthalpy is negative. Moreover, the contribution of entropy to the formation of the complexes is more pronounced in the case of Hoechst 33258.

Structural variety of mono- and binuclear transition metal complexes of 3-[(2-hydroxy-benzylidene)-hydrazono]-1-(2-hydroxyphenyl)-butan-1-one: Synthesis, spectral, thermal, molecular modeling, antimicrobial and antitumor studies

NASA Astrophysics Data System (ADS)

Shebl, Magdy; Adly, Omima M. I.; El-Shafiy, Hoda F.; Khalil, Saied M. E.; Taha, A.; Mahdi, Mohammed A. N.

2017-04-01

A new polydentate Schiff base ligand and its metal complexes were synthesized and characterized by elemental analyses, IR, 1H NMR, electronic, ESR and mass spectra, conductivity and magnetic susceptibility measurements as well as thermal analyses. The free ligand was synthesized by condensation of o-acetoacetylphenol with salicylaldehyde hydrazone. The analytical and spectroscopic tools showed that the obtained complexes are mono- and binuclear complexes, which can be generally formulated as: [(L)M2X2(H2O)m]·nZ; M = Cr, Fe, Ni or Cu, X = OAc or NO3, m = 5 or nil and n = 3, 1.5 or 0.5 and Z = EtOH or H2O, [(H2L)2M(X)m].nH2O; M = Mn, Zn, or Cd, X = EtOH, H2O or nil, m = 2 or nil and n = 3.5 or 0, [(HL)2Co2]·0.5H2O and [(H2L)2UO2(H2O)]. The metal complexes displayed octahedral, tetrahedral and square-planar geometrical arrangements, while uranium complex displayed seven-coordinate. Kinetic parameters (Ea, A, ΔH, ΔS and ΔG) of the thermal decomposition stages have been evaluated using Coats-Redfern equations. The molecular structural parameters of the ligand and its metal complexes have been calculated and correlated with the experimental data such as IR. The antimicrobial activity of the ligand and its complexes was screened against some kinds of bacteria and fungi. The antitumor activity of the ligand and its Ni(II) and Cu(II) complexes was investigated against HepG2 cell line.

Noise-margin limitations on gallium-arsenide VLSI

NASA Technical Reports Server (NTRS)

Long, Stephen I.; Sundaram, Mani

1988-01-01

Two factors which limit the complexity of GaAs MESFET VLSI circuits are considered. Power dissipation sets an upper complexity limit for a given logic circuit implementation and thermal design. Uniformity of device characteristics and the circuit configuration determines the electrical functional yield. Projection of VLSI complexity based on these factors indicates that logic chips of 15,000 gates are feasible with the most promising static circuits if a maximum power dissipation of 5 W per chip is assumed. While lower power per gate and therefore more gates per chip can be obtained by using a popular E/D FET circuit, yields are shown to be small when practical device parameter tolerances are applied. Further improvements in materials, devices, and circuits wil be needed to extend circuit complexity to the range currently dominated by silicon.

A review of surrogate models and their application to groundwater modeling

NASA Astrophysics Data System (ADS)

Asher, M. J.; Croke, B. F. W.; Jakeman, A. J.; Peeters, L. J. M.

2015-08-01

The spatially and temporally variable parameters and inputs to complex groundwater models typically result in long runtimes which hinder comprehensive calibration, sensitivity, and uncertainty analysis. Surrogate modeling aims to provide a simpler, and hence faster, model which emulates the specified output of a more complex model in function of its inputs and parameters. In this review paper, we summarize surrogate modeling techniques in three categories: data-driven, projection, and hierarchical-based approaches. Data-driven surrogates approximate a groundwater model through an empirical model that captures the input-output mapping of the original model. Projection-based models reduce the dimensionality of the parameter space by projecting the governing equations onto a basis of orthonormal vectors. In hierarchical or multifidelity methods the surrogate is created by simplifying the representation of the physical system, such as by ignoring certain processes, or reducing the numerical resolution. In discussing the application to groundwater modeling of these methods, we note several imbalances in the existing literature: a large body of work on data-driven approaches seemingly ignores major drawbacks to the methods; only a fraction of the literature focuses on creating surrogates to reproduce outputs of fully distributed groundwater models, despite these being ubiquitous in practice; and a number of the more advanced surrogate modeling methods are yet to be fully applied in a groundwater modeling context.

Match of Solubility Parameters Between Oil and Surfactants as a Rational Approach for the Formulation of Microemulsion with a High Dispersed Volume of Copaiba Oil and Low Surfactant Content.

PubMed

Xavier-Junior, Francisco Humberto; Huang, Nicolas; Vachon, Jean-Jacques; Rehder, Vera Lucia Garcia; do Egito, Eryvaldo Sócrates Tabosa; Vauthier, Christine

2016-12-01

Aim was to formulate oil-in-water (O/W) microemulsion with a high volume ratio of complex natural oil, i.e. copaiba oil and low surfactant content. The strategy of formulation was based on (i) the selection of surfactants based on predictive calculations of chemical compatibility between their hydrophobic moiety and oil components and (ii) matching the HLB of the surfactants with the required HLB of the oil. Solubility parameters of the hydrophobic moiety of the surfactants and of the main components found in the oil were calculated and compared. In turn, required HLB of oils were calculated. Selection of surfactants was achieved matching their solubility parameters with those of oil components. Blends of surfactants were prepared with HLB matching the required HLB of the oils. Oil:water mixtures (15:85 and 25:75) were the titrated with surfactant blends until a microemulsion was formed. Two surfactant blends were identified from the predictive calculation approach. Microemulsions containing up to 19.6% and 13.7% of selected surfactant blends were obtained. O/W microemulsions with a high volume fraction of complex natural oil and a reasonable surfactant concentration were formulated. These microemulsions can be proposed as delivery systems for the oral administration of poorly soluble drugs.

Approximate median regression for complex survey data with skewed response.

PubMed

Fraser, Raphael André; Lipsitz, Stuart R; Sinha, Debajyoti; Fitzmaurice, Garrett M; Pan, Yi

2016-12-01

The ready availability of public-use data from various large national complex surveys has immense potential for the assessment of population characteristics using regression models. Complex surveys can be used to identify risk factors for important diseases such as cancer. Existing statistical methods based on estimating equations and/or utilizing resampling methods are often not valid with survey data due to complex survey design features. That is, stratification, multistage sampling, and weighting. In this article, we accommodate these design features in the analysis of highly skewed response variables arising from large complex surveys. Specifically, we propose a double-transform-both-sides (DTBS)'based estimating equations approach to estimate the median regression parameters of the highly skewed response; the DTBS approach applies the same Box-Cox type transformation twice to both the outcome and regression function. The usual sandwich variance estimate can be used in our approach, whereas a resampling approach would be needed for a pseudo-likelihood based on minimizing absolute deviations (MAD). Furthermore, the approach is relatively robust to the true underlying distribution, and has much smaller mean square error than a MAD approach. The method is motivated by an analysis of laboratory data on urinary iodine (UI) concentration from the National Health and Nutrition Examination Survey. © 2016, The International Biometric Society.

Approximate Median Regression for Complex Survey Data with Skewed Response

PubMed Central

Fraser, Raphael André; Lipsitz, Stuart R.; Sinha, Debajyoti; Fitzmaurice, Garrett M.; Pan, Yi

2016-01-01

Summary The ready availability of public-use data from various large national complex surveys has immense potential for the assessment of population characteristics using regression models. Complex surveys can be used to identify risk factors for important diseases such as cancer. Existing statistical methods based on estimating equations and/or utilizing resampling methods are often not valid with survey data due to complex survey design features. That is, stratification, multistage sampling and weighting. In this paper, we accommodate these design features in the analysis of highly skewed response variables arising from large complex surveys. Specifically, we propose a double-transform-both-sides (DTBS) based estimating equations approach to estimate the median regression parameters of the highly skewed response; the DTBS approach applies the same Box-Cox type transformation twice to both the outcome and regression function. The usual sandwich variance estimate can be used in our approach, whereas a resampling approach would be needed for a pseudo-likelihood based on minimizing absolute deviations (MAD). Furthermore, the approach is relatively robust to the true underlying distribution, and has much smaller mean square error than a MAD approach. The method is motivated by an analysis of laboratory data on urinary iodine (UI) concentration from the National Health and Nutrition Examination Survey. PMID:27062562

An evaluative model of system performance in manned teleoperational systems

NASA Technical Reports Server (NTRS)

Haines, Richard F.

1989-01-01

Manned teleoperational systems are used in aerospace operations in which humans must interact with machines remotely. Manual guidance of remotely piloted vehicles, controling a wind tunnel, carrying out a scientific procedure remotely are examples of teleoperations. A four input parameter throughput (Tp) model is presented which can be used to evaluate complex, manned, teleoperations-based systems and make critical comparisons among candidate control systems. The first two parameters of this model deal with nominal (A) and off-nominal (B) predicted events while the last two focus on measured events of two types, human performance (C) and system performance (D). Digital simulations showed that the expression A(1-B)/C+D) produced the greatest homogeneity of variance and distribution symmetry. Results from a recently completed manned life science telescience experiment will be used to further validate the model. Complex, interacting teleoperational systems may be systematically evaluated using this expression much like a computer benchmark is used.

Electronic structures and magnetic/optical properties of metal phthalocyanine complexes

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

Baba, Shintaro; Suzuki, Atsushi, E-mail: suzuki@mat.usp.ac.jp; Oku, Takeo

2016-02-01

Electronic structures and magnetic / optical properties of metal phthalocyanine complexes were studied by quantum calculations using density functional theory. Effects of central metal and expansion of π orbital on aromatic ring as conjugation system on the electronic structures, magnetic, optical properties and vibration modes of infrared and Raman spectra of metal phthalocyanines were investigated. Electron and charge density distribution and energy levels near frontier orbital and excited states were influenced by the deformed structures varied with central metal and charge. The magnetic parameters of chemical shifts in {sup 13}C-nuclear magnetic resonance ({sup 13}C-NMR), principle g-tensor, A-tensor, V-tensor of electricmore » field gradient and asymmetry parameters derived from the deformed structures with magnetic interaction of nuclear quadruple interaction based on electron and charge density distribution with a bias of charge near ligand under crystal field.« less

Complex absorbing potentials within EOM-CC family of methods: Theory, implementation, and benchmarks

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

Zuev, Dmitry; Jagau, Thomas-C.; Krylov, Anna I.

2014-07-14

A production-level implementation of equation-of-motion coupled-cluster singles and doubles (EOM-CCSD) for electron attachment and excitation energies augmented by a complex absorbing potential (CAP) is presented. The new method enables the treatment of metastable states within the EOM-CC formalism in a similar manner as bound states. The numeric performance of the method and the sensitivity of resonance positions and lifetimes to the CAP parameters and the choice of one-electron basis set are investigated. A protocol for studying molecular shape resonances based on the use of standard basis sets and a universal criterion for choosing the CAP parameters are presented. Our resultsmore » for a variety of π{sup *} shape resonances of small to medium-size molecules demonstrate that CAP-augmented EOM-CCSD is competitive relative to other theoretical approaches for the treatment of resonances and is often able to reproduce experimental results.« less

The complex networks approach for authorship attribution of books

NASA Astrophysics Data System (ADS)

Mehri, Ali; Darooneh, Amir H.; Shariati, Ashrafalsadat

2012-04-01

Authorship analysis by means of textual features is an important task in linguistic studies. We employ complex networks theory to tackle this disputed problem. In this work, we focus on some measurable quantities of word co-occurrence network of each book for authorship characterization. Based on the network features, attribution probability is defined for authorship identification. Furthermore, two scaling exponents, q-parameter and α-exponent, are combined to classify personal writing style with acceptable high resolution power. The q-parameter, generally known as the nonextensivity measure, is calculated for degree distribution and the α-exponent comes from a power law relationship between number of links and number of nodes in the co-occurrence network constructed for different books written by each author. The applicability of the presented method is evaluated in an experiment with thirty six books of five Persian litterateurs. Our results show high accuracy rate in authorship attribution.

Effect of Longitudinal Magnetic Field on Vibration Characteristics of Single-Walled Carbon Nanotubes in a Viscoelastic Medium

NASA Astrophysics Data System (ADS)

Zhang, D. P.; Lei, Y.; Shen, Z. B.

2017-12-01

The effect of longitudinal magnetic field on vibration response of a sing-walled carbon nanotube (SWCNT) embedded in viscoelastic medium is investigated. Based on nonlocal Euler-Bernoulli beam theory, Maxwell's relations, and Kelvin viscoelastic foundation model, the governing equations of motion for vibration analysis are established. The complex natural frequencies and corresponding mode shapes in closed form for the embedded SWCNT with arbitrary boundary conditions are obtained using transfer function method (TFM). The new analytical expressions for the complex natural frequencies are also derived for certain typical boundary conditions and Kelvin-Voigt model. Numerical results from the model are presented to show the effects of nonlocal parameter, viscoelastic parameter, boundary conditions, aspect ratio, and strength of the magnetic field on vibration characteristics for the embedded SWCNT in longitudinal magnetic field. The results demonstrate the efficiency of the proposed methods for vibration analysis of embedded SWCNTs under magnetic field.

Comparison and experimental validation of two potential resonant viscosity sensors in the kilohertz range

NASA Astrophysics Data System (ADS)

Lemaire, Etienne; Heinisch, Martin; Caillard, Benjamin; Jakoby, Bernhard; Dufour, Isabelle

2013-08-01

Oscillating microstructures are well established and find application in many fields. These include force sensors, e.g. AFM micro-cantilevers or accelerometers based on resonant suspended plates. This contribution presents two vibrating mechanical structures acting as force sensors in liquid media in order to measure hydrodynamic interactions. Rectangular cross section microcantilevers as well as circular cross section wires are investigated. Each structure features specific benefits, which are discussed in detail. Furthermore, their mechanical parameters and their deflection in liquids are characterized. Finally, an inverse analytical model is applied to calculate the complex viscosity near the resonant frequency for both types of structures. With this approach it is possible to determine rheological parameters in the kilohertz range in situ within a few seconds. The monitoring of the complex viscosity of yogurt during the fermentation process is used as a proof of concept to qualify at least one of the two sensors in opaque mixtures.

Deep Learning Methods for Improved Decoding of Linear Codes

NASA Astrophysics Data System (ADS)

Nachmani, Eliya; Marciano, Elad; Lugosch, Loren; Gross, Warren J.; Burshtein, David; Be'ery, Yair

2018-02-01

The problem of low complexity, close to optimal, channel decoding of linear codes with short to moderate block length is considered. It is shown that deep learning methods can be used to improve a standard belief propagation decoder, despite the large example space. Similar improvements are obtained for the min-sum algorithm. It is also shown that tying the parameters of the decoders across iterations, so as to form a recurrent neural network architecture, can be implemented with comparable results. The advantage is that significantly less parameters are required. We also introduce a recurrent neural decoder architecture based on the method of successive relaxation. Improvements over standard belief propagation are also observed on sparser Tanner graph representations of the codes. Furthermore, we demonstrate that the neural belief propagation decoder can be used to improve the performance, or alternatively reduce the computational complexity, of a close to optimal decoder of short BCH codes.

Target-in-the-loop remote sensing of laser beam and atmospheric turbulence characteristics.

PubMed

Vorontsov, Mikhail A; Lachinova, Svetlana L; Majumdar, Arun K

2016-07-01

A new target-in-the-loop (TIL) atmospheric sensing concept for in situ remote measurements of major laser beam characteristics and atmospheric turbulence parameters is proposed and analyzed numerically. The technique is based on utilization of an integral relationship between complex amplitudes of the counterpropagating optical waves known as overlapping integral or interference metric, whose value is preserved along the propagation path. It is shown that the interference metric can be directly measured using the proposed TIL sensing system composed of a single-mode fiber-based optical transceiver and a remotely located retro-target. The measured signal allows retrieval of key beam and atmospheric turbulence characteristics including scintillation index and the path-integrated refractive index structure parameter.

Neural network-based adaptive dynamic surface control for permanent magnet synchronous motors.

PubMed

Yu, Jinpeng; Shi, Peng; Dong, Wenjie; Chen, Bing; Lin, Chong

2015-03-01

This brief considers the problem of neural networks (NNs)-based adaptive dynamic surface control (DSC) for permanent magnet synchronous motors (PMSMs) with parameter uncertainties and load torque disturbance. First, NNs are used to approximate the unknown and nonlinear functions of PMSM drive system and a novel adaptive DSC is constructed to avoid the explosion of complexity in the backstepping design. Next, under the proposed adaptive neural DSC, the number of adaptive parameters required is reduced to only one, and the designed neural controllers structure is much simpler than some existing results in literature, which can guarantee that the tracking error converges to a small neighborhood of the origin. Then, simulations are given to illustrate the effectiveness and potential of the new design technique.

Biomedical properties of a series of ruthenium-N-heterocyclic carbene complexes based on oxidant activity in vitro and assessment in vivo of biosafety in zebrafish embryos.

PubMed

Alfaro, Juan M; Prades, Amparo; del Carmen Ramos, María; Peris, Eduardo; Ripoll-Gómez, Jorge; Poyatos, Macarena; Burgos, Javier S

2010-03-01

N-Heterocyclic carbene (NHC) ligands have attracted great interest over the last decade for their use in the design of homogenous catalysts. NHC-based metal complexes have interesting potential biomedical applications, such as in antimicrobial and cancer therapy, which are beginning to be explored more fully. We have studied here the oxidant activities of a series of Ru(II) complexes in vitro and zebrafish (Danio rerio) have been used as a model in vivo to investigate and characterize the toxicity of some of these compounds. Dual behavior was observed for the NHC-based complexes as they behaved as antioxidants at low concentrations but showed pro-oxidant capacity at higher concentrations. Zebrafish embryos were exposed to Ru(II) complexes under several different conditions (0 or 24 h postfertilization, with or without the chorion) and various parameters, such as viability, edema, heart rate, blood coagulation, pigmentation, scoliosis, malformation, and hatching, were tested. In general, zebrafish embryos were not harmed by exposure to Ru(II) complexes whatever the experimental conditions. Several toxicity profiles were observed depending upon the chemical structure of the compound in question. Their characteristics as pro-oxidant and/or antioxidant agents together with their biosafety may point to their having biomedical applications as antitumoral or neuroprotective drugs.

A geostatistics-informed hierarchical sensitivity analysis method for complex groundwater flow and transport modeling: GEOSTATISTICAL SENSITIVITY ANALYSIS

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

Dai, Heng; Chen, Xingyuan; Ye, Ming

Sensitivity analysis is an important tool for quantifying uncertainty in the outputs of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study we developed a hierarchical sensitivity analysis method that (1) constructs an uncertainty hierarchy by analyzing the input uncertainty sources, and (2) accounts for the spatial correlation among parameters at each level ofmore » the hierarchy using geostatistical tools. The contribution of uncertainty source at each hierarchy level is measured by sensitivity indices calculated using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport in model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally as driven by the dynamic interaction between groundwater and river water at the site. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially-distributed parameters.« less

Synthesis, spectroscopic, fluorescence properties and biological evaluation of novel Pd(II) and Cd(II) complexes of NOON tetradentate Schiff bases.

PubMed

Ali, Omyma A M

2014-01-01

The solid complexes of Pd(II) and Cd(II) with N,N/bis(salicylaldehyde)4,5-dimethyl-1,2-phenylenediamine (H2L(1)), and N,N/bis(salicylaldehyde)4,5-dichloro-1,2-phenylenediamine (H2L(2)) have been synthesized and characterized by several techniques using elemental analysis (CHN), FT-IR, (1)H NMR, UV-Vis spectra and thermal analysis. Elemental analysis data proved 1:1 stoichiometry for the reported complexes while spectroscopic data indicated square planar and octahedral geometries for Pd(II) and Cd(II) complexes, respectively. The prepared ligands, Pd(II) and Cd(II) complexes exhibited intraligand (π-π(∗)) fluorescence and can potentially serve as photoactive materials. Thermal behavior of the complexes was studied and kinetic parameters were determined by Coats-Redfern method. Both the ligands and their complexes have been screened for antimicrobial activities. Copyright © 2013 Elsevier B.V. All rights reserved.

Using machine learning tools to model complex toxic interactions with limited sampling regimes.

PubMed

Bertin, Matthew J; Moeller, Peter; Guillette, Louis J; Chapman, Robert W

2013-03-19

A major impediment to understanding the impact of environmental stress, including toxins and other pollutants, on organisms, is that organisms are rarely challenged by one or a few stressors in natural systems. Thus, linking laboratory experiments that are limited by practical considerations to a few stressors and a few levels of these stressors to real world conditions is constrained. In addition, while the existence of complex interactions among stressors can be identified by current statistical methods, these methods do not provide a means to construct mathematical models of these interactions. In this paper, we offer a two-step process by which complex interactions of stressors on biological systems can be modeled in an experimental design that is within the limits of practicality. We begin with the notion that environment conditions circumscribe an n-dimensional hyperspace within which biological processes or end points are embedded. We then randomly sample this hyperspace to establish experimental conditions that span the range of the relevant parameters and conduct the experiment(s) based upon these selected conditions. Models of the complex interactions of the parameters are then extracted using machine learning tools, specifically artificial neural networks. This approach can rapidly generate highly accurate models of biological responses to complex interactions among environmentally relevant toxins, identify critical subspaces where nonlinear responses exist, and provide an expedient means of designing traditional experiments to test the impact of complex mixtures on biological responses. Further, this can be accomplished with an astonishingly small sample size.

Accurate in situ measurement of complex refractive index and particle size in intralipid emulsions

NASA Astrophysics Data System (ADS)

Dong, Miao L.; Goyal, Kashika G.; Worth, Bradley W.; Makkar, Sorab S.; Calhoun, William R.; Bali, Lalit M.; Bali, Samir

2013-08-01

A first accurate measurement of the complex refractive index in an intralipid emulsion is demonstrated, and thereby the average scatterer particle size using standard Mie scattering calculations is extracted. Our method is based on measurement and modeling of the reflectance of a divergent laser beam from the sample surface. In the absence of any definitive reference data for the complex refractive index or particle size in highly turbid intralipid emulsions, we base our claim of accuracy on the fact that our work offers several critically important advantages over previously reported attempts. First, our measurements are in situ in the sense that they do not require any sample dilution, thus eliminating dilution errors. Second, our theoretical model does not employ any fitting parameters other than the two quantities we seek to determine, i.e., the real and imaginary parts of the refractive index, thus eliminating ambiguities arising from multiple extraneous fitting parameters. Third, we fit the entire reflectance-versus-incident-angle data curve instead of focusing on only the critical angle region, which is just a small subset of the data. Finally, despite our use of highly scattering opaque samples, our experiment uniquely satisfies a key assumption behind the Mie scattering formalism, namely, no multiple scattering occurs. Further proof of our method's validity is given by the fact that our measured particle size finds good agreement with the value obtained by dynamic light scattering.

Accurate in situ measurement of complex refractive index and particle size in intralipid emulsions.

PubMed

Dong, Miao L; Goyal, Kashika G; Worth, Bradley W; Makkar, Sorab S; Calhoun, William R; Bali, Lalit M; Bali, Samir

2013-08-01

A first accurate measurement of the complex refractive index in an intralipid emulsion is demonstrated, and thereby the average scatterer particle size using standard Mie scattering calculations is extracted. Our method is based on measurement and modeling of the reflectance of a divergent laser beam from the sample surface. In the absence of any definitive reference data for the complex refractive index or particle size in highly turbid intralipid emulsions, we base our claim of accuracy on the fact that our work offers several critically important advantages over previously reported attempts. First, our measurements are in situ in the sense that they do not require any sample dilution, thus eliminating dilution errors. Second, our theoretical model does not employ any fitting parameters other than the two quantities we seek to determine, i.e., the real and imaginary parts of the refractive index, thus eliminating ambiguities arising from multiple extraneous fitting parameters. Third, we fit the entire reflectance-versus-incident-angle data curve instead of focusing on only the critical angle region, which is just a small subset of the data. Finally, despite our use of highly scattering opaque samples, our experiment uniquely satisfies a key assumption behind the Mie scattering formalism, namely, no multiple scattering occurs. Further proof of our method's validity is given by the fact that our measured particle size finds good agreement with the value obtained by dynamic light scattering.

Robust Design of Sheet Metal Forming Process Based on Kriging Metamodel

NASA Astrophysics Data System (ADS)

Xie, Yanmin

2011-08-01

Nowadays, sheet metal forming processes design is not a trivial task due to the complex issues to be taken into account (conflicting design goals, complex shapes forming and so on). Optimization methods have also been widely applied in sheet metal forming. Therefore, proper design methods to reduce time and costs have to be developed mostly based on computer aided procedures. At the same time, the existence of variations during manufacturing processes significantly may influence final product quality, rendering non-robust optimal solutions. In this paper, a small size of design of experiments is conducted to investigate how a stochastic behavior of noise factors affects drawing quality. The finite element software (LS_DYNA) is used to simulate the complex sheet metal stamping processes. The Kriging metamodel is adopted to map the relation between input process parameters and part quality. Robust design models for sheet metal forming process integrate adaptive importance sampling with Kriging model, in order to minimize impact of the variations and achieve reliable process parameters. In the adaptive sample, an improved criterion is used to provide direction in which additional training samples can be added to better the Kriging model. Nonlinear functions as test functions and a square stamping example (NUMISHEET'93) are employed to verify the proposed method. Final results indicate application feasibility of the aforesaid method proposed for multi-response robust design.

Parameter Estimation of Computationally Expensive Watershed Models Through Efficient Multi-objective Optimization and Interactive Decision Analytics

NASA Astrophysics Data System (ADS)

Akhtar, Taimoor; Shoemaker, Christine

2016-04-01

Watershed model calibration is inherently a multi-criteria problem. Conflicting trade-offs exist between different quantifiable calibration criterions indicating the non-existence of a single optimal parameterization. Hence, many experts prefer a manual approach to calibration where the inherent multi-objective nature of the calibration problem is addressed through an interactive, subjective, time-intensive and complex decision making process. Multi-objective optimization can be used to efficiently identify multiple plausible calibration alternatives and assist calibration experts during the parameter estimation process. However, there are key challenges to the use of multi objective optimization in the parameter estimation process which include: 1) multi-objective optimization usually requires many model simulations, which is difficult for complex simulation models that are computationally expensive; and 2) selection of one from numerous calibration alternatives provided by multi-objective optimization is non-trivial. This study proposes a "Hybrid Automatic Manual Strategy" (HAMS) for watershed model calibration to specifically address the above-mentioned challenges. HAMS employs a 3-stage framework for parameter estimation. Stage 1 incorporates the use of an efficient surrogate multi-objective algorithm, GOMORS, for identification of numerous calibration alternatives within a limited simulation evaluation budget. The novelty of HAMS is embedded in Stages 2 and 3 where an interactive visual and metric based analytics framework is available as a decision support tool to choose a single calibration from the numerous alternatives identified in Stage 1. Stage 2 of HAMS provides a goodness-of-fit measure / metric based interactive framework for identification of a small subset (typically less than 10) of meaningful and diverse set of calibration alternatives from the numerous alternatives obtained in Stage 1. Stage 3 incorporates the use of an interactive visual analytics framework for decision support in selection of one parameter combination from the alternatives identified in Stage 2. HAMS is applied for calibration of flow parameters of a SWAT model, (Soil and Water Assessment Tool) designed to simulate flow in the Cannonsville watershed in upstate New York. Results from the application of HAMS to Cannonsville indicate that efficient multi-objective optimization and interactive visual and metric based analytics can bridge the gap between the effective use of both automatic and manual strategies for parameter estimation of computationally expensive watershed models.

Preparation, spectroscopic, thermal, antihepatotoxicity, hematological parameters and liver antioxidant capacity characterizations of Cd(II), Hg(II), and Pb(II) mononuclear complexes of paracetamol anti-inflammatory drug

NASA Astrophysics Data System (ADS)

El-Megharbel, Samy M.; Hamza, Reham Z.; Refat, Moamen S.

2014-10-01

Keeping in view that some metal complexes are found to be more potent than their parent drugs, therefore, our present paper aimed to synthesized Cd(II), Hg(II) and Pb(II) complexes of paracetamol (Para) anti-inflammatory drug. Paracetamol complexes with general formula [M(Para)2(H2O)2]·nH2O have been synthesized and characterized on the basis of elemental analysis, conductivity, IR and thermal (TG/DTG), 1H NMR, electronic spectral studies. The conductivity data of these complexes have non-electrolytic nature. Comparative antimicrobial (bacteria and fungi) behaviors and molecular weights of paracetamol with their complexes have been studied. In vivo the antihepatotoxicity effect and some liver function parameters levels (serum total protein, ALT, AST, and LDH) were measured. Hematological parameters and liver antioxidant capacities of both Para and their complexes were performed. The Cd2+ + Para complex was recorded amelioration of antioxidant capacities in liver homogenates compared to other Para complexes treated groups.

Fluid flow in porous media using image-based modelling to parametrize Richards' equation.

PubMed

Cooper, L J; Daly, K R; Hallett, P D; Naveed, M; Koebernick, N; Bengough, A G; George, T S; Roose, T

2017-11-01

The parameters in Richards' equation are usually calculated from experimentally measured values of the soil-water characteristic curve and saturated hydraulic conductivity. The complex pore structures that often occur in porous media complicate such parametrization due to hysteresis between wetting and drying and the effects of tortuosity. Rather than estimate the parameters in Richards' equation from these indirect measurements, image-based modelling is used to investigate the relationship between the pore structure and the parameters. A three-dimensional, X-ray computed tomography image stack of a soil sample with voxel resolution of 6 μm has been used to create a computational mesh. The Cahn-Hilliard-Stokes equations for two-fluid flow, in this case water and air, were applied to this mesh and solved using the finite-element method in COMSOL Multiphysics. The upscaled parameters in Richards' equation are then obtained via homogenization. The effect on the soil-water retention curve due to three different contact angles, 0°, 20° and 60°, was also investigated. The results show that the pore structure affects the properties of the flow on the large scale, and different contact angles can change the parameters for Richards' equation.

New Geophysical Technique for Mineral Exploration and Mineral Discrimination Based on Electromagnetic Methods

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

Michael S. Zhdanov

2005-03-09

The research during the first year of the project was focused on developing the foundations of a new geophysical technique for mineral exploration and mineral discrimination, based on electromagnetic (EM) methods. The proposed new technique is based on examining the spectral induced polarization effects in electromagnetic data using modern distributed acquisition systems and advanced methods of 3-D inversion. The analysis of IP phenomena is usually based on models with frequency dependent complex conductivity distribution. One of the most popular is the Cole-Cole relaxation model. In this progress report we have constructed and analyzed a different physical and mathematical model ofmore » the IP effect based on the effective-medium theory. We have developed a rigorous mathematical model of multi-phase conductive media, which can provide a quantitative tool for evaluation of the type of mineralization, using the conductivity relaxation model parameters. The parameters of the new conductivity relaxation model can be used for discrimination of the different types of rock formations, which is an important goal in mineral exploration. The solution of this problem requires development of an effective numerical method for EM forward modeling in 3-D inhomogeneous media. During the first year of the project we have developed a prototype 3-D IP modeling algorithm using the integral equation (IP) method. Our IE forward modeling code INTEM3DIP is based on the contraction IE method, which improves the convergence rate of the iterative solvers. This code can handle various types of sources and receivers to compute the effect of a complex resistivity model. We have tested the working version of the INTEM3DIP code for computer simulation of the IP data for several models including a southwest US porphyry model and a Kambalda-style nickel sulfide deposit. The numerical modeling study clearly demonstrates how the various complex resistivity models manifest differently in the observed EM data. These modeling studies lay a background for future development of the IP inversion method, directed at determining the electrical conductivity and the intrinsic chargeability distributions, as well as the other parameters of the relaxation model simultaneously. The new technology envisioned in this proposal, will be used for the discrimination of different rocks, and in this way will provide an ability to distinguish between uneconomic mineral deposits and the location of zones of economic mineralization and geothermal resources.« less

Nested Sampling for Bayesian Model Comparison in the Context of Salmonella Disease Dynamics

PubMed Central

Dybowski, Richard; McKinley, Trevelyan J.; Mastroeni, Pietro; Restif, Olivier

2013-01-01

Understanding the mechanisms underlying the observed dynamics of complex biological systems requires the statistical assessment and comparison of multiple alternative models. Although this has traditionally been done using maximum likelihood-based methods such as Akaike's Information Criterion (AIC), Bayesian methods have gained in popularity because they provide more informative output in the form of posterior probability distributions. However, comparison between multiple models in a Bayesian framework is made difficult by the computational cost of numerical integration over large parameter spaces. A new, efficient method for the computation of posterior probabilities has recently been proposed and applied to complex problems from the physical sciences. Here we demonstrate how nested sampling can be used for inference and model comparison in biological sciences. We present a reanalysis of data from experimental infection of mice with Salmonella enterica showing the distribution of bacteria in liver cells. In addition to confirming the main finding of the original analysis, which relied on AIC, our approach provides: (a) integration across the parameter space, (b) estimation of the posterior parameter distributions (with visualisations of parameter correlations), and (c) estimation of the posterior predictive distributions for goodness-of-fit assessments of the models. The goodness-of-fit results suggest that alternative mechanistic models and a relaxation of the quasi-stationary assumption should be considered. PMID:24376528

Coagulation Management in Jersey Calves: An ex vivo Study.

PubMed

Gröning, Sabine; Maas, Judith; van Geul, Svenja; Rossaint, Rolf; Steinseifer, Ulrich; Grottke, Oliver

2017-01-01

Jersey calves are frequently used as an experimental animal model for in vivo testing of cardiac assist devices or orthopedic implants. In this ex vivo study, we analyzed the coagulation system of the Jersey calves and the potential of human-based coagulation management to circumvent perioperative bleeding complications during surgery. Experimental Procedure: Blood from 7 Jersey calves was subjected to standard laboratory tests and thromboelastometry analysis. An ex vivo model of dilutional coagulopathy was used to study the effects of fibrinogen or prothrombin complex concentrate supplementation. Fibrinolysis was induced with tissue plasminogen activator to identify potential therapeutic strategies involving tranexamic acid or aprotinin. Furthermore, anticoagulation strategies were evaluated by incubating the blood samples with dabigatran or rivaroxaban. Baseline values for thromboelastometry and standard laboratory parameters, including prothrombin time, activated partial thromboplastin time, fibrinogen, antithrombin III, and D-dimers, were established. Fifty percent diluted blood showed a statistically significant impairment of hemostasis. The parameters significantly improved after the administration of fibrinogen or prothrombin complex concentrate. Tranexamic acid and aprotinin ameliorated tissue plasminogen activator-induced fibrinolysis. Both dabigatran and rivaroxaban significantly prolonged the coagulation parameters. In this ex vivo study, coagulation factors, factor concentrate, antifibrinolytic reagents, and anticoagulants regularly used in the clinic positively impacted coagulation parameters in Jersey calf blood. © 2017 S. Karger AG, Basel.

Minimizing the cost of translocation failure with decision-tree models that predict species' behavioral response in translocation sites.

PubMed

Ebrahimi, Mehregan; Ebrahimie, Esmaeil; Bull, C Michael

2015-08-01

The high number of failures is one reason why translocation is often not recommended. Considering how behavior changes during translocations may improve translocation success. To derive decision-tree models for species' translocation, we used data on the short-term responses of an endangered Australian skink in 5 simulated translocations with different release conditions. We used 4 different decision-tree algorithms (decision tree, decision-tree parallel, decision stump, and random forest) with 4 different criteria (gain ratio, information gain, gini index, and accuracy) to investigate how environmental and behavioral parameters may affect the success of a translocation. We assumed behavioral changes that increased dispersal away from a release site would reduce translocation success. The trees became more complex when we included all behavioral parameters as attributes, but these trees yielded more detailed information about why and how dispersal occurred. According to these complex trees, there were positive associations between some behavioral parameters, such as fight and dispersal, that showed there was a higher chance, for example, of dispersal among lizards that fought than among those that did not fight. Decision trees based on parameters related to release conditions were easier to understand and could be used by managers to make translocation decisions under different circumstances. © 2015 Society for Conservation Biology.

A generic implementation of replica exchange with solute tempering (REST2) algorithm in NAMD for complex biophysical simulations

NASA Astrophysics Data System (ADS)

Jo, Sunhwan; Jiang, Wei

2015-12-01

Replica Exchange with Solute Tempering (REST2) is a powerful sampling enhancement algorithm of molecular dynamics (MD) in that it needs significantly smaller number of replicas but achieves higher sampling efficiency relative to standard temperature exchange algorithm. In this paper, we extend the applicability of REST2 for quantitative biophysical simulations through a robust and generic implementation in greatly scalable MD software NAMD. The rescaling procedure of force field parameters controlling REST2 "hot region" is implemented into NAMD at the source code level. A user can conveniently select hot region through VMD and write the selection information into a PDB file. The rescaling keyword/parameter is written in NAMD Tcl script interface that enables an on-the-fly simulation parameter change. Our implementation of REST2 is within communication-enabled Tcl script built on top of Charm++, thus communication overhead of an exchange attempt is vanishingly small. Such a generic implementation facilitates seamless cooperation between REST2 and other modules of NAMD to provide enhanced sampling for complex biomolecular simulations. Three challenging applications including native REST2 simulation for peptide folding-unfolding transition, free energy perturbation/REST2 for absolute binding affinity of protein-ligand complex and umbrella sampling/REST2 Hamiltonian exchange for free energy landscape calculation were carried out on IBM Blue Gene/Q supercomputer to demonstrate efficacy of REST2 based on the present implementation.

Characterization of polymeric substance classes in cereal-based beverages using asymmetrical flow field-flow fractionation with a multi-detection system.

PubMed

Krebs, Georg; Becker, Thomas; Gastl, Martina

2017-09-01

Cereal-based beverages contain a complex mixture of various polymeric macromolecules including polysaccharides, peptides, and polyphenols. The molar mass of polymers and their degradation products affect different technological and especially sensory parameters of beverages. Asymmetrical flow field-flow fractionation (AF4) coupled with multi-angle light scattering (MALS) and refractive index detection (dRI) or UV detection (UV) is a technique for structure and molar mass distribution analysis of macromolecules commonly used for pure compound solutions. The objective of this study was to develop a systematic approach for identifying the polymer classes in an AF4//MALS/dRI/UV fractogram of the complex matrix in beer, a yeast-fermented cereal-based beverage. Assignment of fractogram fractions to polymer substance classes was achieved by targeted precipitations, enzymatic hydrolysis, and alignments with purified polymer standards. Corresponding effects on dRI and UV signals were evaluated according to the detector's sensitivities. Using these techniques, the AF4 fractogram of beer was classified into different fractions: (1) the low molar mass fraction was assigned to proteinaceous molecules with different degrees of glycosylation, (2) the middle molar mass fraction was attributed to protein-polyphenol complexes with a coelution of non-starch polysaccharides, and (3) the high molar mass fraction was identified as a mixture of the cell wall polysaccharides (i.e., β-glucan and arabinoxylan) with a low content of polysaccharide-protein association. In addition, dextrins derived from incomplete starch hydrolysis were identified in all fractions and over the complete molar mass range. The ability to assess the components of an AF4 fractogram is beneficial for the targeted design and evaluation of polymers in fermented cereal-based beverages and for controlling and monitoring quality parameters.

Slow Perceptual Processing at the Core of Developmental Dyslexia: A Parameter-Based Assessment of Visual Attention

ERIC Educational Resources Information Center

Stenneken, Prisca; Egetemeir, Johanna; Schulte-Korne, Gerd; Muller, Hermann J.; Schneider, Werner X.; Finke, Kathrin

2011-01-01

The cognitive causes as well as the neurological and genetic basis of developmental dyslexia, a complex disorder of written language acquisition, are intensely discussed with regard to multiple-deficit models. Accumulating evidence has revealed dyslexics' impairments in a variety of tasks requiring visual attention. The heterogeneity of these…

Vocoders and Speech Perception: Uses of Computer-Based Speech Analysis-Synthesis in Stimulus Generation.

ERIC Educational Resources Information Center

Tierney, Joseph; Mack, Molly

1987-01-01

Stimuli used in research on the perception of the speech signal have often been obtained from simple filtering and distortion of the speech waveform, sometimes accompanied by noise. However, for more complex stimulus generation, the parameters of speech can be manipulated, after analysis and before synthesis, using various types of algorithms to…

Nonlinear functional approximation with networks using adaptive neurons

NASA Technical Reports Server (NTRS)

Tawel, Raoul

1992-01-01

A novel mathematical framework for the rapid learning of nonlinear mappings and topological transformations is presented. It is based on allowing the neuron's parameters to adapt as a function of learning. This fully recurrent adaptive neuron model (ANM) has been successfully applied to complex nonlinear function approximation problems such as the highly degenerate inverse kinematics problem in robotics.

A hybrid approach to parameter identification of linear delay differential equations involving multiple delays

NASA Astrophysics Data System (ADS)

Marzban, Hamid Reza

2018-05-01

In this paper, we are concerned with the parameter identification of linear time-invariant systems containing multiple delays. The approach is based upon a hybrid of block-pulse functions and Legendre's polynomials. The convergence of the proposed procedure is established and an upper error bound with respect to the L2-norm associated with the hybrid functions is derived. The problem under consideration is first transformed into a system of algebraic equations. The least squares technique is then employed for identification of the desired parameters. Several multi-delay systems of varying complexity are investigated to evaluate the performance and capability of the proposed approximation method. It is shown that the proposed approach is also applicable to a class of nonlinear multi-delay systems. It is demonstrated that the suggested procedure provides accurate results for the desired parameters.

Accurate complex scaling of three dimensional numerical potentials

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

Cerioni, Alessandro; Genovese, Luigi; Duchemin, Ivan

2013-05-28

The complex scaling method, which consists in continuing spatial coordinates into the complex plane, is a well-established method that allows to compute resonant eigenfunctions of the time-independent Schroedinger operator. Whenever it is desirable to apply the complex scaling to investigate resonances in physical systems defined on numerical discrete grids, the most direct approach relies on the application of a similarity transformation to the original, unscaled Hamiltonian. We show that such an approach can be conveniently implemented in the Daubechies wavelet basis set, featuring a very promising level of generality, high accuracy, and no need for artificial convergence parameters. Complex scalingmore » of three dimensional numerical potentials can be efficiently and accurately performed. By carrying out an illustrative resonant state computation in the case of a one-dimensional model potential, we then show that our wavelet-based approach may disclose new exciting opportunities in the field of computational non-Hermitian quantum mechanics.« less

Microfluidic 3D cell culture: potential application for tissue-based bioassays

PubMed Central

Li, XiuJun (James); Valadez, Alejandra V.; Zuo, Peng; Nie, Zhihong

2014-01-01

Current fundamental investigations of human biology and the development of therapeutic drugs, commonly rely on two-dimensional (2D) monolayer cell culture systems. However, 2D cell culture systems do not accurately recapitulate the structure, function, physiology of living tissues, as well as highly complex and dynamic three-dimensional (3D) environments in vivo. The microfluidic technology can provide micro-scale complex structures and well-controlled parameters to mimic the in vivo environment of cells. The combination of microfluidic technology with 3D cell culture offers great potential for in vivo-like tissue-based applications, such as the emerging organ-on-a-chip system. This article will review recent advances in microfluidic technology for 3D cell culture and their biological applications. PMID:22793034

Examination of biogenic selenium-containing nanosystems based on polyelectrolyte complexes by atomic force, Kelvin probe force and electron microscopy methods

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

Sukhanova, T. E., E-mail: tat-sukhanova@mail.ru; Vylegzhanina, M. E.; Valueva, S. V.

The morphology and electrical properties of biogenic selenium-containing nanosystems based on polyelectrolyte complexes (PECs) were examined using AFM, Kelvin Probe Force and electron microscopy methods. It has been found, that prepared nanostructures significantly differed in their morphological types and parameters. In particular, multilayers capsules can be produced via varying synthesis conditions, especially, the selenium–PEC mass ratio ν. At the “special point” (ν = 0.1), filled and hollow nano- and microcapsules are formed in the system. The multilayer character of the capsules walls is visible in the phase images. Kelvin Probe Force images showed the inhomogeneity of potential distribution in capsulesmore » and outside them.« less

Spectrum simulation in DTSA-II.

PubMed

Ritchie, Nicholas W M

2009-10-01

Spectrum simulation is a useful practical and pedagogical tool. Particularly with complex samples or trace constituents, a simulation can help to understand the limits of the technique and the instrument parameters for the optimal measurement. DTSA-II, software for electron probe microanalysis, provides both easy to use and flexible tools for simulating common and less common sample geometries and materials. Analytical models based on (rhoz) curves provide quick simulations of simple samples. Monte Carlo models based on electron and X-ray transport provide more sophisticated models of arbitrarily complex samples. DTSA-II provides a broad range of simulation tools in a framework with many different interchangeable physical models. In addition, DTSA-II provides tools for visualizing, comparing, manipulating, and quantifying simulated and measured spectra.

Improved FFT-based numerical inversion of Laplace transforms via fast Hartley transform algorithm

NASA Technical Reports Server (NTRS)

Hwang, Chyi; Lu, Ming-Jeng; Shieh, Leang S.

1991-01-01

The disadvantages of numerical inversion of the Laplace transform via the conventional fast Fourier transform (FFT) are identified and an improved method is presented to remedy them. The improved method is based on introducing a new integration step length Delta(omega) = pi/mT for trapezoidal-rule approximation of the Bromwich integral, in which a new parameter, m, is introduced for controlling the accuracy of the numerical integration. Naturally, this method leads to multiple sets of complex FFT computations. A new inversion formula is derived such that N equally spaced samples of the inverse Laplace transform function can be obtained by (m/2) + 1 sets of N-point complex FFT computations or by m sets of real fast Hartley transform (FHT) computations.

Waste management under multiple complexities: inexact piecewise-linearization-based fuzzy flexible programming.

PubMed

Sun, Wei; Huang, Guo H; Lv, Ying; Li, Gongchen

2012-06-01

To tackle nonlinear economies-of-scale (EOS) effects in interval-parameter constraints for a representative waste management problem, an inexact piecewise-linearization-based fuzzy flexible programming (IPFP) model is developed. In IPFP, interval parameters for waste amounts and transportation/operation costs can be quantified; aspiration levels for net system costs, as well as tolerance intervals for both capacities of waste treatment facilities and waste generation rates can be reflected; and the nonlinear EOS effects transformed from objective function to constraints can be approximated. An interactive algorithm is proposed for solving the IPFP model, which in nature is an interval-parameter mixed-integer quadratically constrained programming model. To demonstrate the IPFP's advantages, two alternative models are developed to compare their performances. One is a conventional linear-regression-based inexact fuzzy programming model (IPFP2) and the other is an IPFP model with all right-hand-sides of fussy constraints being the corresponding interval numbers (IPFP3). The comparison results between IPFP and IPFP2 indicate that the optimized waste amounts would have the similar patterns in both models. However, when dealing with EOS effects in constraints, the IPFP2 may underestimate the net system costs while the IPFP can estimate the costs more accurately. The comparison results between IPFP and IPFP3 indicate that their solutions would be significantly different. The decreased system uncertainties in IPFP's solutions demonstrate its effectiveness for providing more satisfactory interval solutions than IPFP3. Following its first application to waste management, the IPFP can be potentially applied to other environmental problems under multiple complexities. Copyright © 2012 Elsevier Ltd. All rights reserved.

Synthesis, spectroscopic and biological activities studies of acyclic and macrocyclic mono and binuclear metal complexes containing a hard-soft Schiff base

NASA Astrophysics Data System (ADS)

Abou-Hussein, Azza A. A.; Linert, Wolfgang

Mono- and bi-nuclear acyclic and macrocyclic complexes with hard-soft Schiff base, H2L, ligand derived from the reaction of 4,6-diacetylresorcinol and thiocabohydrazide, in the molar ratio 1:2 have been prepared. The H2L ligand reacts with Co(II), Ni(II), Cu(II), Zn(II), Mn(II) and UO2(VI) nitrates, VO(IV) sulfate and Ru(III) chloride to get acyclic binuclear complexes except for VO(IV) and Ru(III) which gave acyclic mono-nuclear complexes. Reaction of the acyclic mono-nuclear VO(IV) and Ru(III) complexes with 4,6-diacetylresorcinol afforded the corresponding macrocyclic mono-nuclear VO(IV) and Ru(IIII) complexes. Template reactions of the 4,6-diacetylresorcinol and thiocarbohydrazide with either VO(IV) or Ru(III) salts afforded the macrocyclic binuclear VO(IV) and Ru(III) complexes. The Schiff base, H2L, ligand acts as dibasic with two NSO-tridentate sites and can coordinate with two metal ions to form binuclear complexes after the deprotonation of the hydrogen atoms of the phenolic groups in all the complexes, except in the case of the acyclic mononuclear Ru(III) and VO(IV) complexes, where the Schiff base behaves as neutral tetradentate chelate with N2S2 donor atoms. The ligands and the metal complexes were characterized by elemental analysis, IR, UV-vis 1H-NMR, thermal gravimetric analysis (TGA) and ESR, as well as the measurements of conductivity and magnetic moments at room temperature. Electronic spectra and magnetic moments of the complexes indicate the geometries of the metal centers are either tetrahedral, square planar or octahedral. Kinetic and thermodynamic parameters were calculated using Coats-Redfern equation, for the different thermal decomposition steps of the complexes. The ligands and the metal complexes were screened for their antimicrobial activity against Staphylococcus aureus as Gram-positive bacteria, and Pseudomonas fluorescens as Gram-negative bacteria in addition to Fusarium oxysporum fungus. Most of the complexes exhibit mild antibacterial and antifungal activities against these organisms.

Synthesis, spectroscopic and biological activities studies of acyclic and macrocyclic mono and binuclear metal complexes containing a hard-soft Schiff base.

PubMed

Abou-Hussein, Azza A A; Linert, Wolfgang

2012-09-01

Mono- and bi-nuclear acyclic and macrocyclic complexes with hard-soft Schiff base, H(2)L, ligand derived from the reaction of 4,6-diacetylresorcinol and thiocabohydrazide, in the molar ratio 1:2 have been prepared. The H(2)L ligand reacts with Co(II), Ni(II), Cu(II), Zn(II), Mn(II) and UO(2)(VI) nitrates, VO(IV) sulfate and Ru(III) chloride to get acyclic binuclear complexes except for VO(IV) and Ru(III) which gave acyclic mono-nuclear complexes. Reaction of the acyclic mono-nuclear VO(IV) and Ru(III) complexes with 4,6-diacetylresorcinol afforded the corresponding macrocyclic mono-nuclear VO(IV) and Ru(IIII) complexes. Template reactions of the 4,6-diacetylresorcinol and thiocarbohydrazide with either VO(IV) or Ru(III) salts afforded the macrocyclic binuclear VO(IV) and Ru(III) complexes. The Schiff base, H(2)L, ligand acts as dibasic with two NSO-tridentate sites and can coordinate with two metal ions to form binuclear complexes after the deprotonation of the hydrogen atoms of the phenolic groups in all the complexes, except in the case of the acyclic mononuclear Ru(III) and VO(IV) complexes, where the Schiff base behaves as neutral tetradentate chelate with N(2)S(2) donor atoms. The ligands and the metal complexes were characterized by elemental analysis, IR, UV-vis (1)H-NMR, thermal gravimetric analysis (TGA) and ESR, as well as the measurements of conductivity and magnetic moments at room temperature. Electronic spectra and magnetic moments of the complexes indicate the geometries of the metal centers are either tetrahedral, square planar or octahedral. Kinetic and thermodynamic parameters were calculated using Coats-Redfern equation, for the different thermal decomposition steps of the complexes. The ligands and the metal complexes were screened for their antimicrobial activity against Staphylococcus aureus as Gram-positive bacteria, and Pseudomonas fluorescens as Gram-negative bacteria in addition to Fusarium oxysporum fungus. Most of the complexes exhibit mild antibacterial and antifungal activities against these organisms. Copyright © 2012 Elsevier B.V. All rights reserved.

Assessment of wear dependence parameters in complex model of cutting tool wear

NASA Astrophysics Data System (ADS)

Antsev, A. V.; Pasko, N. I.; Antseva, N. V.

2018-03-01

This paper addresses wear dependence of the generic efficient life period of cutting tools taken as an aggregate of the law of tool wear rate distribution and dependence of parameters of this law's on the cutting mode, factoring in the random factor as exemplified by the complex model of wear. The complex model of wear takes into account the variance of cutting properties within one batch of tools, variance in machinability within one batch of workpieces, and the stochastic nature of the wear process itself. A technique of assessment of wear dependence parameters in a complex model of cutting tool wear is provided. The technique is supported by a numerical example.

Invited commentary: Lost in estimation--searching for alternatives to markov chains to fit complex Bayesian models.

PubMed

Molitor, John

2012-03-01

Bayesian methods have seen an increase in popularity in a wide variety of scientific fields, including epidemiology. One of the main reasons for their widespread application is the power of the Markov chain Monte Carlo (MCMC) techniques generally used to fit these models. As a result, researchers often implicitly associate Bayesian models with MCMC estimation procedures. However, Bayesian models do not always require Markov-chain-based methods for parameter estimation. This is important, as MCMC estimation methods, while generally quite powerful, are complex and computationally expensive and suffer from convergence problems related to the manner in which they generate correlated samples used to estimate probability distributions for parameters of interest. In this issue of the Journal, Cole et al. (Am J Epidemiol. 2012;175(5):368-375) present an interesting paper that discusses non-Markov-chain-based approaches to fitting Bayesian models. These methods, though limited, can overcome some of the problems associated with MCMC techniques and promise to provide simpler approaches to fitting Bayesian models. Applied researchers will find these estimation approaches intuitively appealing and will gain a deeper understanding of Bayesian models through their use. However, readers should be aware that other non-Markov-chain-based methods are currently in active development and have been widely published in other fields.

Coordination behavior of new bis Schiff base ligand derived from 2-furan carboxaldehyde and propane-1,3-diamine. Spectroscopic, thermal, anticancer and antibacterial activity studies

NASA Astrophysics Data System (ADS)

Mohamed, Gehad G.; Zayed, Ehab M.; Hindy, Ahmed M. M.

2015-06-01

Novel bis Schiff base ligand, [N1,N3-bis(furan-2-ylmethylene)propane-1,3-diamine], was prepared by the condensation of furan-2-carboxaldehyde with propane-1,3-diamine. Its conformational changes on complexation with transition metal ions [Co(II), Ni(II), Cu(II), Mn(II), Cd(II), Zn(II) and Fe(III)] have been studied on the basis of elemental analysis, conductivity measurements, spectral (infrared, 1H NMR, electronic), magnetic and thermogravimetric studies. The conductance data of the complexes revealed their electrolytic nature suggesting them as 1:2 (for bivalent metal ions) and 1:3 (for Fe(III) ion) electrolytes. The complexes were found to have octahedral geometry based on magnetic moment and solid reflectance measurements. Thermal analysis data revealed the decomposition of the complexes in successive steps with the removal of anions, coordinated water and bis Schiff base ligand. The thermodynamic parameters were calculated using Coats-Redfern equation. The Anticancer screening studies were performed on human colorectal cancer (HCT), hepatic cancer (HepG2) and breast cancer (MCF-7) cell lines. The antimicrobial activity of all the compounds was studied against Gram negative (Escherichia coli and Proteus vulgaris) and Gram positive (Bacillus vulgaris and Staphylococcus pyogones) bacteria. It was observed that the coordination of metal ion has a pronounced effect on the microbial activities of the bis Schiff base ligand. All the metal complexes have shown higher antimicrobial effect than the free bis Schiff base ligand.

Modeling complex metabolic reactions, ecological systems, and financial and legal networks with MIANN models based on Markov-Wiener node descriptors.

PubMed

Duardo-Sánchez, Aliuska; Munteanu, Cristian R; Riera-Fernández, Pablo; López-Díaz, Antonio; Pazos, Alejandro; González-Díaz, Humberto

2014-01-27

The use of numerical parameters in Complex Network analysis is expanding to new fields of application. At a molecular level, we can use them to describe the molecular structure of chemical entities, protein interactions, or metabolic networks. However, the applications are not restricted to the world of molecules and can be extended to the study of macroscopic nonliving systems, organisms, or even legal or social networks. On the other hand, the development of the field of Artificial Intelligence has led to the formulation of computational algorithms whose design is based on the structure and functioning of networks of biological neurons. These algorithms, called Artificial Neural Networks (ANNs), can be useful for the study of complex networks, since the numerical parameters that encode information of the network (for example centralities/node descriptors) can be used as inputs for the ANNs. The Wiener index (W) is a graph invariant widely used in chemoinformatics to quantify the molecular structure of drugs and to study complex networks. In this work, we explore for the first time the possibility of using Markov chains to calculate analogues of node distance numbers/W to describe complex networks from the point of view of their nodes. These parameters are called Markov-Wiener node descriptors of order k(th) (W(k)). Please, note that these descriptors are not related to Markov-Wiener stochastic processes. Here, we calculated the W(k)(i) values for a very high number of nodes (>100,000) in more than 100 different complex networks using the software MI-NODES. These networks were grouped according to the field of application. Molecular networks include the Metabolic Reaction Networks (MRNs) of 40 different organisms. In addition, we analyzed other biological and legal and social networks. These include the Interaction Web Database Biological Networks (IWDBNs), with 75 food webs or ecological systems and the Spanish Financial Law Network (SFLN). The calculated W(k)(i) values were used as inputs for different ANNs in order to discriminate correct node connectivity patterns from incorrect random patterns. The MIANN models obtained present good values of Sensitivity/Specificity (%): MRNs (78/78), IWDBNs (90/88), and SFLN (86/84). These preliminary results are very promising from the point of view of a first exploratory study and suggest that the use of these models could be extended to the high-throughput re-evaluation of connectivity in known complex networks (collation).

Scalability of carbon-nanotube-based thin film transistors for flexible electronic devices manufactured using an all roll-to-roll gravure printing system

PubMed Central

Koo, Hyunmo; Lee, Wookyu; Choi, Younchang; Sun, Junfeng; Bak, Jina; Noh, Jinsoo; Subramanian, Vivek; Azuma, Yasuo; Majima, Yutaka; Cho, Gyoujin

2015-01-01

To demonstrate that roll-to-roll (R2R) gravure printing is a suitable advanced manufacturing method for flexible thin film transistor (TFT)-based electronic circuits, three different nanomaterial-based inks (silver nanoparticles, BaTiO3 nanoparticles and single-walled carbon nanotubes (SWNTs)) were selected and optimized to enable the realization of fully printed SWNT-based TFTs (SWNT-TFTs) on 150-m-long rolls of 0.25-m-wide poly(ethylene terephthalate) (PET). SWNT-TFTs with 5 different channel lengths, namely, 30, 80, 130, 180, and 230 μm, were fabricated using a printing speed of 8 m/min. These SWNT-TFTs were characterized, and the obtained electrical parameters were related to major mechanical factors such as web tension, registration accuracy, impression roll pressure and printing speed to determine whether these mechanical factors were the sources of the observed device-to-device variations. By utilizing the electrical parameters from the SWNT-TFTs, a Monte Carlo simulation for a 1-bit adder circuit, as a reference, was conducted to demonstrate that functional circuits with reasonable complexity can indeed be manufactured using R2R gravure printing. The simulation results suggest that circuits with complexity, similar to the full adder circuit, can be printed with a 76% circuit yield if threshold voltage (Vth) variations of less than 30% can be maintained. PMID:26411839

Determination of Irreducible Water Saturation from nuclear magnetic resonance based on fractal theory — a case study of sandstone with complex pore structure

NASA Astrophysics Data System (ADS)

Peng, L.; Pan, H.; Ma, H.; Zhao, P.; Qin, R.; Deng, C.

2017-12-01

The irreducible water saturation (Swir) is a vital parameter for permeability prediction and original oil and gas estimation. However, the complex pore structure of the rocks makes the parameter difficult to be calculated from both laboratory and conventional well logging methods. In this study, an effective statistical method to predict Swir is derived directly from nuclear magnetic resonance (NMR) data based on fractal theory. The spectrum of transversal relaxation time (T2) is normally considered as an indicator of pore size distribution, and the micro- and meso-pore's fractal dimension in two specific range of T2 spectrum distribution are calculated. Based on the analysis of the fractal characteristics of 22 core samples, which were drilled from four boreholes of tight lithologic oil reservoirs of Ordos Basin in China, the positive correlation between Swir and porosity is derived. Afterwards a predicting model for Swir based on linear regressions of fractal dimensions is proposed. It reveals that the Swir is controlled by the pore size and the roughness of the pore. The reliability of this model is tested and an ideal consistency between predicted results and experimental data is found. This model is a reliable supplementary to predict the irreducible water saturation in the case that T2 cutoff value cannot be accurately determined.

Experimental validation of a numerical 3-D finite model applied to wind turbines design under vibration constraints: TREVISE platform

NASA Astrophysics Data System (ADS)

Sellami, Takwa; Jelassi, Sana; Darcherif, Abdel Moumen; Berriri, Hanen; Mimouni, Med Faouzi

2018-04-01

With the advancement of wind turbines towards complex structures, the requirement of trusty structural models has become more apparent. Hence, the vibration characteristics of the wind turbine components, like the blades and the tower, have to be extracted under vibration constraints. Although extracting the modal properties of blades is a simple task, calculating precise modal data for the whole wind turbine coupled to its tower/foundation is still a perplexing task. In this framework, this paper focuses on the investigation of the structural modeling approach of modern commercial micro-turbines. Thus, the structural model a complex designed wind turbine, which is Rutland 504, is established based on both experimental and numerical methods. A three-dimensional (3-D) numerical model of the structure was set up based on the finite volume method (FVM) using the academic finite element analysis software ANSYS. To validate the created model, experimental vibration tests were carried out using the vibration test system of TREVISE platform at ECAM-EPMI. The tests were based on the experimental modal analysis (EMA) technique, which is one of the most efficient techniques for identifying structures parameters. Indeed, the poles and residues of the frequency response functions (FRF), between input and output spectra, were calculated to extract the mode shapes and the natural frequencies of the structure. Based on the obtained modal parameters, the numerical designed model was up-dated.

Descriptive Characteristics of Surface Water Quality in Hong Kong by a Self-Organising Map

PubMed Central

An, Yan; Zou, Zhihong; Li, Ranran

2016-01-01

In this study, principal component analysis (PCA) and a self-organising map (SOM) were used to analyse a complex dataset obtained from the river water monitoring stations in the Tolo Harbor and Channel Water Control Zone (Hong Kong), covering the period of 2009–2011. PCA was initially applied to identify the principal components (PCs) among the nonlinear and complex surface water quality parameters. SOM followed PCA, and was implemented to analyze the complex relationships and behaviors of the parameters. The results reveal that PCA reduced the multidimensional parameters to four significant PCs which are combinations of the original ones. The positive and inverse relationships of the parameters were shown explicitly by pattern analysis in the component planes. It was found that PCA and SOM are efficient tools to capture and analyze the behavior of multivariable, complex, and nonlinear related surface water quality data. PMID:26761018

Descriptive Characteristics of Surface Water Quality in Hong Kong by a Self-Organising Map.

PubMed

An, Yan; Zou, Zhihong; Li, Ranran

2016-01-08

In this study, principal component analysis (PCA) and a self-organising map (SOM) were used to analyse a complex dataset obtained from the river water monitoring stations in the Tolo Harbor and Channel Water Control Zone (Hong Kong), covering the period of 2009-2011. PCA was initially applied to identify the principal components (PCs) among the nonlinear and complex surface water quality parameters. SOM followed PCA, and was implemented to analyze the complex relationships and behaviors of the parameters. The results reveal that PCA reduced the multidimensional parameters to four significant PCs which are combinations of the original ones. The positive and inverse relationships of the parameters were shown explicitly by pattern analysis in the component planes. It was found that PCA and SOM are efficient tools to capture and analyze the behavior of multivariable, complex, and nonlinear related surface water quality data.

Influence of novel gallium complexes on the homeostasis of some biochemical and hematological parameters in rats.

PubMed

Gârban, Gabriela; Silaghi-Dumitrescu, Radu; Ioniţă, Hortensia; Gârban, Zeno; Hădărugă, Nicoleta-Gabriela; Ghibu, George-Daniel; Baltă, Cornel; Simiz, Florin-Dan; Mitar, Carmen

2013-12-01

The aim of this study was to detect possible homeostasis changes in some biochemical and hematological parameters after the administration of gallium (Ga) complexes C (24) and C (85) on an experimental animal model (Wistar strain rats). In order to observe chronobiological aspects, a morning (m) and an evening (e) animal series were constituted. Further on, each series were divided into three groups: control (C), experimental I (EI), and experimental II (EII). Both Ga complexes were solubilized in a carrier solution containing polyethylene glycol (PEG) 400, water, and ethanol. Animals of the C groups received the carrier solution by intraperitoneal injection, those from the EI groups received the solubilized C(24) gallium complex, and those of the EII groups received the solubilized C(85) gallium complex. At the end of the experiment, blood and tissue samples were taken and the following parameters were determined: serum concentration of the nonprotein nitrogenous compounds (uric acid, creatinine, and blood urea nitrogen), hematological parameters (erythrocytes, hemoglobin, leukocytes, and platelets), and the kidney tissue concentration of three essential trace elements (Fe, Cu, and Zn). With the exception of uric acid, the results revealed increased concentrations of the nonprotein nitrogenous compounds both in the morning and in the evening experimental groups. Hematological data showed increased levels of erythrocytes, hemoglobin, and leukocytes and decreased platelet levels in the experimental group given the C(24) gallium complex in the morning (EI-m) group; increased levels of leukocytes and decreased levels of the other parameters in the experimental group given the C(24) gallium complex in the evening (EI-e) group; and increased levels of all hematological parameters in the experimental groups receiving the C(85) gallium complex in the morning (EII-m) group and in the evening (EII-e) group. Decreased kidney tissue concentrations of metals were found in all the experimental groups. Fe levels were significantly decreased in the EI-m receiving the C(24) gallium complex and EII-m which received the C(85) gallium complex and in the EII-e group which received the C(85) gallium complex. In the EI-e group which received the C(24) gallium complex, a significant decrease of Cu concentration was reported.

Sobol Sensitivity Analysis: A Tool to Guide the Development and Evaluation of Systems Pharmacology Models

PubMed Central

Trame, MN; Lesko, LJ

2015-01-01

A systems pharmacology model typically integrates pharmacokinetic, biochemical network, and systems biology concepts into a unifying approach. It typically consists of a large number of parameters and reaction species that are interlinked based upon the underlying (patho)physiology and the mechanism of drug action. The more complex these models are, the greater the challenge of reliably identifying and estimating respective model parameters. Global sensitivity analysis provides an innovative tool that can meet this challenge. CPT Pharmacometrics Syst. Pharmacol. (2015) 4, 69–79; doi:10.1002/psp4.6; published online 25 February 2015 PMID:27548289

Reflow dynamics of thin patterned viscous films

NASA Astrophysics Data System (ADS)

Leveder, T.; Landis, S.; Davoust, L.

2008-01-01

This letter presents a study of viscous smoothening dynamics of a nanopatterned thin film. Ultrathin film manufacturing processes appearing to be a key point of nanotechnology engineering and numerous studies have been recently led in order to exhibit driving parameters of this transient surface motion, focusing on time scale accuracy method. Based on nanomechanical analysis, this letter shows that controlled shape measurements provided much more detailed information about reflow mechanism. Control of reflow process of any complex surface shape, or measurement of material parameter as thin film viscosity, free surface energy, or even Hamaker constant are therefore possible.

Comparative absorption spectroscopy involving 4f-4f transitions to explore the kinetics of simultaneous coordination of uracil with Nd(III) and Zn(II) and its associated thermodynamics

NASA Astrophysics Data System (ADS)

Victory Devi, Ch.; Rajmuhon Singh, N.

2011-10-01

The interaction of uracil with Nd(III) has been explored in presence and absence of Zn(II) using the comparative absorption spectroscopy involving the 4f-4f transitions in different solvents. The complexation of uracil with Nd(III) is indicated by the change in intensity of 4f-4f bands expressing in terms of significant change in oscillator strength and Judd-Ofelt parameters. Intensification of this bands became more prominent in presence of Zn(II) suggesting the stimulative effect of Zn(II) towards the complexation of Nd(III) with uracil. Other spectral parameters namely Slator-Condon ( Fk's), nephelauxetic effect ( β), bonding ( b1/2) and percent covalency ( δ) parameters are computed to correlate their simultaneous binding of metal ions with uracil. The sensitivities of the observed 4f-4f transitions towards the minor coordination changes around Nd(III) has been used to monitor the simultaneous coordination of uracil with Nd(III) and Zn(II). The variation of intensities (oscillator strengths and Judd-Ofelt parameters) of 4f-4f bands during the complexation has helped in following the heterobimetallic complexation of uracil. Rate of complexation with respect to hypersensitive transition was evaluated. Energy of activation and thermodynamic parameters for the complexation reaction were also determined.

Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model

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

Urrego-Blanco, Jorge Rolando; Urban, Nathan Mark; Hunke, Elizabeth Clare

Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual modelmore » parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. Lastly, it is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.« less

Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model

DOE PAGES

Urrego-Blanco, Jorge Rolando; Urban, Nathan Mark; Hunke, Elizabeth Clare; ...

2016-04-01

Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual modelmore » parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. Lastly, it is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.« less

Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model

NASA Astrophysics Data System (ADS)

Urrego-Blanco, Jorge R.; Urban, Nathan M.; Hunke, Elizabeth C.; Turner, Adrian K.; Jeffery, Nicole

2016-04-01

Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual model parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. It is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.

Sensitivity Analysis in Agent-Based Models of Socio-Ecological Systems: An Example in Agricultural Land Conservation for Lake Water Quality Improvement

NASA Astrophysics Data System (ADS)

Ligmann-Zielinska, A.; Kramer, D. B.; Spence Cheruvelil, K.; Soranno, P.

2012-12-01

Socio-ecological systems are dynamic and nonlinear. To account for this complexity, we employ agent-based models (ABMs) to study macro-scale phenomena resulting from micro-scale interactions among system components. Because ABMs typically have many parameters, it is challenging to identify which parameters contribute to the emerging macro-scale patterns. In this paper, we address the following question: What is the extent of participation in agricultural land conservation programs given heterogeneous landscape, economic, social, and individual decision making criteria in complex lakesheds? To answer this question, we: [1] built an ABM for our model system; [2] simulated land use change resulting from agent decision making, [3] estimated the uncertainty of the model output, decomposed it and apportioned it to each of the parameters in the model. Our model system is a freshwater socio-ecological system - that of farmland and lake water quality within a region containing a large number of lakes and high proportions of agricultural lands. Our study focuses on examining how agricultural land conversion from active to fallow reduces freshwater nutrient loading and improves water quality. Consequently, our ABM is composed of farmer agents who make decisions related to participation in a government-sponsored Conservation Reserve Program (CRP) managed by the Farm Service Agency (FSA). We also include an FSA agent, who selects enrollment offers made by farmers and announces the signup results leading to land use change. The model is executed in a Monte Carlo simulation framework to generate a distribution of maps of fallow lands that are used for calculating nutrient loading to lakes. What follows is a variance-based sensitivity analysis of the results. We compute sensitivity indices for individual parameters and their combinations, allowing for identification of the most influential as well as the insignificant inputs. In the case study, we observe that farmland conservation is first and foremost driven by the FSA signup choices. Environmental criteria used in FSA offer selection play a secondary role in farmland-to-fallow-land conversion. Farmer decision making is mainly influenced by the willingness to reduce the potential annual rental payments. As the case study demonstrates, our approach leads to ABM simplification without the loss of outcome variability. It also shows how to represent the magnitude of ABM complexity and isolate the effects of the interconnected explanatory variables on the simulated emergent phenomena. More importantly, the results of our research indicate that some of the parameters exert influence on model outcomes only if analyzed in combination with other parameters. Without evaluating the interaction effects among inputs, we risk losing important functional relationships among ABM components and, consequently, we potentially reduce its explanatory power.

A study on a wheel-based stair-climbing robot with a hopping mechanism

NASA Astrophysics Data System (ADS)

Kikuchi, Koki; Sakaguchi, Keisuke; Sudo, Takayuki; Bushida, Naoki; Chiba, Yasuhiro; Asai, Yuji

2008-08-01

In this study, we propose a simple hopping mechanism using the vibration of a two-degree-of-freedom system for a wheel-based stair-climbing robot. The robot, consisting of two bodies connected by springs and a wire, hops by releasing energy stored in the springs and quickly travels using wheels mounted in its lower body. The trajectories of the bodies during hopping change in accordance with the design parameters, such as the reduced mass of the two bodies, the mass ratio between the upper and lower bodies, the spring constant, the control parameters such as the initial contraction of the spring and the wire tension. This property allows the robot to quickly and economically climb up and down stairs, leap over obstacles, and landing softly without complex control. In this paper, the characteristics of hopping motion for the design and control parameters are clarified by both numerical simulations and experiments. Furthermore, using the robot design based on the results the abilities to hop up and down a step, leap over a cable, and land softly are demonstrated.

Design of bearings for rotor systems based on stability

NASA Technical Reports Server (NTRS)

Dhar, D.; Barrett, L. E.; Knospe, C. R.

1992-01-01

Design of rotor systems incorporating stable behavior is of great importance to manufacturers of high speed centrifugal machinery since destabilizing mechanisms (from bearings, seals, aerodynamic cross coupling, noncolocation effects from magnetic bearings, etc.) increase with machine efficiency and power density. A new method of designing bearing parameters (stiffness and damping coefficients or coefficients of the controller transfer function) is proposed, based on a numerical search in the parameter space. The feedback control law is based on a decentralized low order controller structure, and the various design requirements are specified as constraints in the specification and parameter spaces. An algorithm is proposed for solving the problem as a sequence of constrained 'minimax' problems, with more and more eigenvalues into an acceptable region in the complex plane. The algorithm uses the method of feasible directions to solve the nonlinear constrained minimization problem at each stage. This methodology emphasizes the designer's interaction with the algorithm to generate acceptable designs by relaxing various constraints and changing initial guesses interactively. A design oriented user interface is proposed to facilitate the interaction.

RSA-Based Password-Authenticated Key Exchange, Revisited

NASA Astrophysics Data System (ADS)

Shin, Seonghan; Kobara, Kazukuni; Imai, Hideki

The RSA-based Password-Authenticated Key Exchange (PAKE) protocols have been proposed to realize both mutual authentication and generation of secure session keys where a client is sharing his/her password only with a server and the latter should generate its RSA public/private key pair (e, n), (d, n) every time due to the lack of PKI (Public-Key Infrastructures). One of the ways to avoid a special kind of off-line (so called e-residue) attacks in the RSA-based PAKE protocols is to deploy a challenge/response method by which a client verifies the relative primality of e and φ(n) interactively with a server. However, this kind of RSA-based PAKE protocols did not give any proof of the underlying challenge/response method and therefore could not specify the exact complexity of their protocols since there exists another security parameter, needed in the challenge/response method. In this paper, we first present an RSA-based PAKE (RSA-PAKE) protocol that can deploy two different challenge/response methods (denoted by Challenge/Response Method1 and Challenge/Response Method2). The main contributions of this work include: (1) Based on the number theory, we prove that the Challenge/Response Method1 and the Challenge/Response Method2 are secure against e-residue attacks for any odd prime e (2) With the security parameter for the on-line attacks, we show that the RSA-PAKE protocol is provably secure in the random oracle model where all of the off-line attacks are not more efficient than on-line dictionary attacks; and (3) By considering the Hamming weight of e and its complexity in the. RSA-PAKE protocol, we search for primes to be recommended for a practical use. We also compare the RSA-PAKE protocol with the previous ones mainly in terms of computation and communication complexities.

A Waterborne Outbreak and Detection of Cryptosporidium Oocysts in Drinking Water of an Older High-Rise Apartment Complex in Seoul

PubMed Central

Yang, Jin-Young; Lee, Eun-Sook; Kim, Se-Chul; Cha, So-Yang; Kim, Sung-Tek; Lee, Man-Ho; Han, Sun-Hee; Park, Young-Sang

2013-01-01

From May to June 2012, a waterborne outbreak of 124 cases of cryptosporidiosis occurred in the plumbing systems of an older high-rise apartment complex in Seoul, Republic of Korea. The residents of this apartment complex had symptoms of watery diarrhea and vomiting. Tap water samples in the apartment complex and its adjacent buildings were collected and tested for 57 parameters under the Korean Drinking Water Standards and for additional 11 microbiological parameters. The microbiological parameters included total colony counts, Clostridium perfringens, Enterococcus, fecal streptococcus, Salmonella, Shigella, Pseudomonas aeruginosa, Cryptosporidium oocysts, Giardia cysts, total culturable viruses, and Norovirus. While the tap water samples of the adjacent buildings complied with the Korean Drinking Water Standards for all parameters, fecal bacteria and Cryptosporidium oocysts were detected in the tap water samples of the outbreak apartment complex. It turned out that the agent of the disease was Cryptosporidium parvum. The drinking water was polluted with sewage from a septic tank in the apartment complex. To remove C. parvum oocysts, we conducted physical processes of cleaning the water storage tanks, flushing the indoor pipes, and replacing old pipes with new ones. Finally we restored the clean drinking water to the apartment complex after identification of no oocysts. PMID:24039290

A waterborne outbreak and detection of cryptosporidium oocysts in drinking water of an older high-rise apartment complex in seoul.

PubMed

Cho, Eun-Joo; Yang, Jin-Young; Lee, Eun-Sook; Kim, Se-Chul; Cha, So-Yang; Kim, Sung-Tek; Lee, Man-Ho; Han, Sun-Hee; Park, Young-Sang

2013-08-01

From May to June 2012, a waterborne outbreak of 124 cases of cryptosporidiosis occurred in the plumbing systems of an older high-rise apartment complex in Seoul, Republic of Korea. The residents of this apartment complex had symptoms of watery diarrhea and vomiting. Tap water samples in the apartment complex and its adjacent buildings were collected and tested for 57 parameters under the Korean Drinking Water Standards and for additional 11 microbiological parameters. The microbiological parameters included total colony counts, Clostridium perfringens, Enterococcus, fecal streptococcus, Salmonella, Shigella, Pseudomonas aeruginosa, Cryptosporidium oocysts, Giardia cysts, total culturable viruses, and Norovirus. While the tap water samples of the adjacent buildings complied with the Korean Drinking Water Standards for all parameters, fecal bacteria and Cryptosporidium oocysts were detected in the tap water samples of the outbreak apartment complex. It turned out that the agent of the disease was Cryptosporidium parvum. The drinking water was polluted with sewage from a septic tank in the apartment complex. To remove C. parvum oocysts, we conducted physical processes of cleaning the water storage tanks, flushing the indoor pipes, and replacing old pipes with new ones. Finally we restored the clean drinking water to the apartment complex after identification of no oocysts.

Binding affinities of Schiff base Fe(II) complex with BSA and calf-thymus DNA: Spectroscopic investigations and molecular docking analysis

NASA Astrophysics Data System (ADS)

Rudra, Suparna; Dasmandal, Somnath; Patra, Chiranjit; Kundu, Arjama; Mahapatra, Ambikesh

2016-09-01

The binding interaction of a synthesized Schiff base Fe(II) complex with biological macromolecules viz., bovine serum albumin (BSA) and calf thymus(ct)-DNA have been investigated using different spectroscopic techniques coupled with viscosity measurements at physiological pH and 298 K. Regular amendments in emission intensities of BSA upon the action of the complex indicate significant interaction between them, and the binding interaction have been characterized by Stern Volmer plots and thermodynamic binding parameters. On the basis of this quenching technique one binding site with binding constant (Kb = (7.6 ± 0.21) × 105) between complex and protein have been obtained at 298 K. Time-resolved fluorescence studies have also been encountered to understand the mechanism of quenching induced by the complex. Binding affinities of the complex to the fluorophores of BSA namely tryptophan (Trp) and tyrosine (Tyr) have been judged by synchronous fluorescence studies. Secondary structural changes of BSA rooted by the complex has been revealed by CD spectra. On the other hand, hypochromicity of absorption spectra of the complex with the addition of ct-DNA and the gradual reduction in emission intensities of ethidium bromide bound ct-DNA in presence of the complex indicate noticeable interaction between ct-DNA and the complex with the binding constant (4.2 ± 0.11) × 106 M- 1. Life-time measurements have been studied to determine the relative amplitude of binding of the complex to ct-DNA base pairs. Mode of binding interaction of the complex with ct-DNA has been deciphered by viscosity measurements. CD spectra have also been used to understand the changes in ct-DNA structure upon binding with the metal complex. Density functional theory (DFT) and molecular docking analysis have been employed in highlighting the interactive phenomenon and binding location of the complex with the macromolecules.

Synthesis, spectroscopic, molecular orbital calculation, cytotoxic, molecular docking of DNA binding and DNA cleavage studies of transition metal complexes with N-benzylidene-N'-salicylidene-1,1-diaminopropane

NASA Astrophysics Data System (ADS)

Al-Mogren, Muneerah M.; Alaghaz, Abdel-Nasser M. A.; Elbohy, Salwa A. H.

2013-10-01

Eight mononuclear chromium(III), manganese(II), iron(III), cobalt(II), nickel(II), copper(II), zinc(II) and cadmium(II) complexes of Schiff's base ligand were synthesized and determined by different physical techniques. The complexes are insoluble in common organic solvents but soluble in DMF and DMSO. The measured molar conductance values in DMSO indicate that the complexes are non-electrolytic in nature. All the eight metal complexes have been fully characterized with the help of elemental analyses, molecular weights, molar conductance values, magnetic moments and spectroscopic data. The analytical data helped to elucidate the structure of the metal complexes. The Schiff base is found to act as tridentate ligand using N2O donor set of atoms leading to an octahedral geometry for the complexes around all the metal ions. Quantum chemical calculations were performed with semi-empirical method to find the optimum geometry of the ligand and its complexes. Additionally in silico, the docking studies and the calculated pharmacokinetic parameters show promising futures for application of the ligand and complexes as high potency agents for DNA binding activity. The interaction of the complexes with calf thymus DNA (CT-DNA) has been investigated by UV absorption method, and the mode of CT-DNA binding to the complexes has been explored. Furthermore, the DNA cleavage activity by the complexes was performed. The Schiff base and their complexes have been screened for their antibacterial activity against bacterial strains [Staphylococcus aureus (RCMB010027), Staphylococcus epidermidis (RCMB010024), Bacillis subtilis (RCMB010063), Proteous vulgaris (RCMB 010085), Klebsiella pneumonia (RCMB 010093) and Shigella flexneri (RCMB 0100542)] and fungi [(Aspergillus fumigates (RCMB 02564), Aspergillus clavatus (RCMB 02593) and Candida albicans (RCMB05035)] by disk diffusion method. All the metal complexes have potent biocidal activity than the free ligand.

Improved model reduction and tuning of fractional-order PI(λ)D(μ) controllers for analytical rule extraction with genetic programming.

PubMed

Das, Saptarshi; Pan, Indranil; Das, Shantanu; Gupta, Amitava

2012-03-01

Genetic algorithm (GA) has been used in this study for a new approach of suboptimal model reduction in the Nyquist plane and optimal time domain tuning of proportional-integral-derivative (PID) and fractional-order (FO) PI(λ)D(μ) controllers. Simulation studies show that the new Nyquist-based model reduction technique outperforms the conventional H(2)-norm-based reduced parameter modeling technique. With the tuned controller parameters and reduced-order model parameter dataset, optimum tuning rules have been developed with a test-bench of higher-order processes via genetic programming (GP). The GP performs a symbolic regression on the reduced process parameters to evolve a tuning rule which provides the best analytical expression to map the data. The tuning rules are developed for a minimum time domain integral performance index described by a weighted sum of error index and controller effort. From the reported Pareto optimal front of the GP-based optimal rule extraction technique, a trade-off can be made between the complexity of the tuning formulae and the control performance. The efficacy of the single-gene and multi-gene GP-based tuning rules has been compared with the original GA-based control performance for the PID and PI(λ)D(μ) controllers, handling four different classes of representative higher-order processes. These rules are very useful for process control engineers, as they inherit the power of the GA-based tuning methodology, but can be easily calculated without the requirement for running the computationally intensive GA every time. Three-dimensional plots of the required variation in PID/fractional-order PID (FOPID) controller parameters with reduced process parameters have been shown as a guideline for the operator. Parametric robustness of the reported GP-based tuning rules has also been shown with credible simulation examples. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Online selective kernel-based temporal difference learning.

PubMed

Chen, Xingguo; Gao, Yang; Wang, Ruili

2013-12-01

In this paper, an online selective kernel-based temporal difference (OSKTD) learning algorithm is proposed to deal with large scale and/or continuous reinforcement learning problems. OSKTD includes two online procedures: online sparsification and parameter updating for the selective kernel-based value function. A new sparsification method (i.e., a kernel distance-based online sparsification method) is proposed based on selective ensemble learning, which is computationally less complex compared with other sparsification methods. With the proposed sparsification method, the sparsified dictionary of samples is constructed online by checking if a sample needs to be added to the sparsified dictionary. In addition, based on local validity, a selective kernel-based value function is proposed to select the best samples from the sample dictionary for the selective kernel-based value function approximator. The parameters of the selective kernel-based value function are iteratively updated by using the temporal difference (TD) learning algorithm combined with the gradient descent technique. The complexity of the online sparsification procedure in the OSKTD algorithm is O(n). In addition, two typical experiments (Maze and Mountain Car) are used to compare with both traditional and up-to-date O(n) algorithms (GTD, GTD2, and TDC using the kernel-based value function), and the results demonstrate the effectiveness of our proposed algorithm. In the Maze problem, OSKTD converges to an optimal policy and converges faster than both traditional and up-to-date algorithms. In the Mountain Car problem, OSKTD converges, requires less computation time compared with other sparsification methods, gets a better local optima than the traditional algorithms, and converges much faster than the up-to-date algorithms. In addition, OSKTD can reach a competitive ultimate optima compared with the up-to-date algorithms.

Information geometric methods for complexity

NASA Astrophysics Data System (ADS)

Felice, Domenico; Cafaro, Carlo; Mancini, Stefano

2018-03-01

Research on the use of information geometry (IG) in modern physics has witnessed significant advances recently. In this review article, we report on the utilization of IG methods to define measures of complexity in both classical and, whenever available, quantum physical settings. A paradigmatic example of a dramatic change in complexity is given by phase transitions (PTs). Hence, we review both global and local aspects of PTs described in terms of the scalar curvature of the parameter manifold and the components of the metric tensor, respectively. We also report on the behavior of geodesic paths on the parameter manifold used to gain insight into the dynamics of PTs. Going further, we survey measures of complexity arising in the geometric framework. In particular, we quantify complexity of networks in terms of the Riemannian volume of the parameter space of a statistical manifold associated with a given network. We are also concerned with complexity measures that account for the interactions of a given number of parts of a system that cannot be described in terms of a smaller number of parts of the system. Finally, we investigate complexity measures of entropic motion on curved statistical manifolds that arise from a probabilistic description of physical systems in the presence of limited information. The Kullback-Leibler divergence, the distance to an exponential family and volumes of curved parameter manifolds, are examples of essential IG notions exploited in our discussion of complexity. We conclude by discussing strengths, limits, and possible future applications of IG methods to the physics of complexity.

Synthesis, structure elucidation, biological screening, molecular modeling and DNA binding of some Cu(II) chelates incorporating imines derived from amino acids

NASA Astrophysics Data System (ADS)

Abdel-Rahman, Laila H.; Abu-Dief, Ahmed M.; Ismael, Mohammed; Mohamed, Mounir A. A.; Hashem, Nahla Ali

2016-01-01

Three tridentate Schiff bases amino acids were prepared by direct condensation of 3-methoxysalicylaldehyde (MS) or 4-diethylaminosalicylaldehyde (DS) with α-amino acid ligands [L-phenylalanine (P), L-histidine (H) and DL-tryptophan (T)]. The prepared Schiff bases amino acids were investigated by melting points, elemental analysis, 1HNMR and 13CNMR, IR, UV-Vis spectra, conductivity and magnetic measurements analyses. Subsequently, copper was introduced and Cu(II) complexes formed. These complexes were analyzed by thermal and elemental analyses and further investigated by FT-IR and UV/Vis spectroscopies. The experimental results indicating that all Cu(II) complexes contain hydrated water molecules (except DSPCu complex) and don't contain coordinated water molecules. The kinetic and thermal parameters were extracted from the thermal data using Coast and Redfern method. The molar conductance values of the Schiff base amino acid ligands and their Cu(II) complexes were relatively low, showing that these compounds have non-electrolytic nature. Magnetic susceptibility measurements showed the diamagnetic nature of the Schiff base amino acid ligands and paramagnetic nature of their complexes. Additionally, a spectrophotometric method was determined to extract their stability constants. It was found that the complexes possess 1:2 (M:L) stoichiometry. The results suggested that 3-methoxysalicylaldehyde and 4-diethylaminosalicylaldehyde amino acid Schiff bases behave as monobasic tridentate ONO ligands and coordinate Cu(II) ions in octahedral geometry according to the general formula [Cu(HL)2]·nH2O. To further understanding the structural and electronic properties of these complexes, Density Functional Theory (DFT) calculations were employed and provided a satisfactory description. The optimized structures of MST Schiff base ligand and its complex were calculated using DFT. The antimicrobial activity of the Schiff base ligands and their complexes were screened against some types of bacteria such as Bacillus subtilis (+ve), Escherichia coli (-ve) and Micrococcus luteus (+ve) and some types of fungi such as Asperagillus niger, Candida glabrata and Saccharomyces cerevisiae. The results of these studies indicated that the metal complexes exhibit a stronger antibacterial and antifungal efficiency compared to their corresponding ligands. The complexes were screened for antiviral activity against a panel of DNA and RNA viruses. Minimum cytotoxic and minimum virus inhibitory concentrations of these complexes were determined. The mode of interaction between complexes and CT-DNA was monitored using absorption spectra, viscosity measurements and gel electrophoreses.

Model-Based Thermal System Design Optimization for the James Webb Space Telescope

NASA Technical Reports Server (NTRS)

Cataldo, Giuseppe; Niedner, Malcolm B.; Fixsen, Dale J.; Moseley, Samuel H.

2017-01-01

Spacecraft thermal model validation is normally performed by comparing model predictions with thermal test data and reducing their discrepancies to meet the mission requirements. Based on thermal engineering expertise, the model input parameters are adjusted to tune the model output response to the test data. The end result is not guaranteed to be the best solution in terms of reduced discrepancy and the process requires months to complete. A model-based methodology was developed to perform the validation process in a fully automated fashion and provide mathematical bases to the search for the optimal parameter set that minimizes the discrepancies between model and data. The methodology was successfully applied to several thermal subsystems of the James Webb Space Telescope (JWST). Global or quasiglobal optimal solutions were found and the total execution time of the model validation process was reduced to about two weeks. The model sensitivities to the parameters, which are required to solve the optimization problem, can be calculated automatically before the test begins and provide a library for sensitivity studies. This methodology represents a crucial commodity when testing complex, large-scale systems under time and budget constraints. Here, results for the JWST Core thermal system will be presented in detail.

Model-based thermal system design optimization for the James Webb Space Telescope

NASA Astrophysics Data System (ADS)

Cataldo, Giuseppe; Niedner, Malcolm B.; Fixsen, Dale J.; Moseley, Samuel H.

2017-10-01

Spacecraft thermal model validation is normally performed by comparing model predictions with thermal test data and reducing their discrepancies to meet the mission requirements. Based on thermal engineering expertise, the model input parameters are adjusted to tune the model output response to the test data. The end result is not guaranteed to be the best solution in terms of reduced discrepancy and the process requires months to complete. A model-based methodology was developed to perform the validation process in a fully automated fashion and provide mathematical bases to the search for the optimal parameter set that minimizes the discrepancies between model and data. The methodology was successfully applied to several thermal subsystems of the James Webb Space Telescope (JWST). Global or quasiglobal optimal solutions were found and the total execution time of the model validation process was reduced to about two weeks. The model sensitivities to the parameters, which are required to solve the optimization problem, can be calculated automatically before the test begins and provide a library for sensitivity studies. This methodology represents a crucial commodity when testing complex, large-scale systems under time and budget constraints. Here, results for the JWST Core thermal system will be presented in detail.

New horizons in selective laser sintering surface roughness characterization

NASA Astrophysics Data System (ADS)

Vetterli, M.; Schmid, M.; Knapp, W.; Wegener, K.

2017-12-01

Powder-based additive manufacturing of polymers and metals has evolved from a prototyping technology to an industrial process for the fabrication of small to medium series of complex geometry parts. Unfortunately due to the processing of powder as a basis material and the successive addition of layers to produce components, a significant surface roughness inherent to the process has been observed since the first use of such technologies. A novel characterization method based on an elastomeric pad coated with a reflective layer, the Gelsight, was found to be reliable and fast to characterize surfaces processed by selective laser sintering (SLS) of polymers. With help of this method, a qualitative and quantitative investigation of SLS surfaces is feasible. Repeatability and reproducibility investigations are performed for both 2D and 3D areal roughness parameters. Based on the good results, the Gelsight is used for the optimization of vertical SLS surfaces. A model built on laser scanning parameters is proposed and after confirmation could achieve a roughness reduction of 10% based on the S q parameter. The Gelsight could be successfully identified as a fast, reliable and versatile surface topography characterization method as it applies to all kind of surfaces.

Complex network approach to classifying classical piano compositions

NASA Astrophysics Data System (ADS)

Xin, Chen; Zhang, Huishu; Huang, Jiping

2016-10-01

Complex network has been regarded as a useful tool handling systems with vague interactions. Hence, numerous applications have arised. In this paper we construct complex networks for 770 classical piano compositions of Mozart, Beethoven and Chopin based on musical note pitches and lengths. We find prominent distinctions among network edges of different composers. Some stylized facts can be explained by such parameters of network structures and topologies. Further, we propose two classification methods for music styles and genres according to the discovered distinctions. These methods are easy to implement and the results are sound. This work suggests that complex network could be a decent way to analyze the characteristics of musical notes, since it could provide a deep view into understanding of the relationships among notes in musical compositions and evidence for classification of different composers, styles and genres of music.

Study on Material Parameters Identification of Brain Tissue Considering Uncertainty of Friction Coefficient

NASA Astrophysics Data System (ADS)

Guan, Fengjiao; Zhang, Guanjun; Liu, Jie; Wang, Shujing; Luo, Xu; Zhu, Feng

2017-10-01

Accurate material parameters are critical to construct the high biofidelity finite element (FE) models. However, it is hard to obtain the brain tissue parameters accurately because of the effects of irregular geometry and uncertain boundary conditions. Considering the complexity of material test and the uncertainty of friction coefficient, a computational inverse method for viscoelastic material parameters identification of brain tissue is presented based on the interval analysis method. Firstly, the intervals are used to quantify the friction coefficient in the boundary condition. And then the inverse problem of material parameters identification under uncertain friction coefficient is transformed into two types of deterministic inverse problem. Finally the intelligent optimization algorithm is used to solve the two types of deterministic inverse problems quickly and accurately, and the range of material parameters can be easily acquired with no need of a variety of samples. The efficiency and convergence of this method are demonstrated by the material parameters identification of thalamus. The proposed method provides a potential effective tool for building high biofidelity human finite element model in the study of traffic accident injury.

Adjoint-Based Climate Model Tuning: Application to the Planet Simulator

NASA Astrophysics Data System (ADS)

Lyu, Guokun; Köhl, Armin; Matei, Ion; Stammer, Detlef

2018-01-01

The adjoint method is used to calibrate the medium complexity climate model "Planet Simulator" through parameter estimation. Identical twin experiments demonstrate that this method can retrieve default values of the control parameters when using a long assimilation window of the order of 2 months. Chaos synchronization through nudging, required to overcome limits in the temporal assimilation window in the adjoint method, is employed successfully to reach this assimilation window length. When assimilating ERA-Interim reanalysis data, the observations of air temperature and the radiative fluxes are the most important data for adjusting the control parameters. The global mean net longwave fluxes at the surface and at the top of the atmosphere are significantly improved by tuning two model parameters controlling the absorption of clouds and water vapor. The global mean net shortwave radiation at the surface is improved by optimizing three model parameters controlling cloud optical properties. The optimized parameters improve the free model (without nudging terms) simulation in a way similar to that in the assimilation experiments. Results suggest a promising way for tuning uncertain parameters in nonlinear coupled climate models.

[Role of the medium acidity in the complexes formation of pyropheophorbide a with albumin and lipoproteins].

PubMed

Golovina, G V; Ol'shevskaia, V A; Kalinina, V N; Shtil', A A; Kuz'min, V A

2011-01-01

The spectral characteristics of the photosensitizer pyropheophorbide a (PPP) complexes with its carriers, that is, serum albumin and low density lipoproteins, were investigated in aqueous solutions at pH 7.4 and 5.0. The acidic pH had no effect on the quantitative parameters of PPP binding to lipoproteins but reduces its affinity for albumin. Differential role of acidification in the binding of PPP to biomacromolecules should be considered in the design of PPP-based drugs given that pH is frequently lowered in the sites of the disease.

d +i d chiral superconductivity in a triangular lattice from trigonal bipyramidal complexes

NASA Astrophysics Data System (ADS)

Lu, Chen; Zhang, Li-Da; Wu, Xianxin; Yang, Fan; Hu, Jiangping

2018-04-01

We model the newly predicted high-Tc superconducting candidates constructed by corner-shared trigonal bipyramidal complexes with an effective three-orbital tight-binding Hamiltonian and investigate the pairing symmetry of their superconducting states driven by electron-electron interactions. Our combined weak- and strong-coupling-based calculations consistently identify the chiral d +i d superconductivity as the leading pairing symmetry in a wide doping range with realistic interaction parameters. This pairing state has a nontrivial topological Chern number and can host gapless chiral edge modes, and the vortex cores under magnetic field can carry Majorana zero modes.

Usefulness of charge-transfer complexation for the assessment of sympathomimetic drugs: Spectroscopic properties of drug ephedrine hydrochloride complexed with some π-acceptors

NASA Astrophysics Data System (ADS)

Refat, Moamen S.; Ibrahim, Omar B.; Saad, Hosam A.; Adam, Abdel Majid A.

2014-05-01

Recently, ephedrine (Eph) assessment in food products, pharmaceutical formulations, human fluids of athletes and detection of drug toxicity and abuse, has gained a growing interest. To provide basic data that can be used to assessment of Eph quantitatively based on charge-transfer (CT) complexation, the CT complexes of Eph with 7‧,8,8‧-tetracyanoquinodimethane (TCNQ), dichlorodicyanobenzoquinone (DDQ), 1,3-dinitrobenzene (DNB) or tetrabromothiophene (TBT) were synthesized and spectroscopically investigated. The newly synthesized complexes have been characterized via elemental analysis, IR, Raman, 1H NMR, and UV-visible spectroscopy. The formation constant (KCT), molar extinction coefficient (εCT) and other spectroscopic data have been determined using the Benesi-Hildebrand method and its modifications. The sharp, well-defined Bragg reflections at specific 2θ angles have been identified from the powder X-ray diffraction patterns. Thermal decomposition behavior of these complexes was also studied, and their kinetic thermodynamic parameters were calculated with Coats-Redfern and Horowitz-Metzger equations.

Thermodynamic study of dihydrogen phosphate dimerisation and complexation with novel urea- and thiourea-based receptors.

PubMed

Bregović, Nikola; Cindro, Nikola; Frkanec, Leo; Užarević, Krunoslav; Tomišić, Vladislav

2014-11-24

Complexation of dihydrogen phosphate by novel thiourea and urea receptors in acetonitrile and dimethyl sulfoxide was studied in detail by an integrated approach by using several methods (isothermal titration calorimetry, ESI-MS, and (1)H NMR and UV spectroscopy). Thermodynamic investigations into H2PO4(-) dimerisation, which is a process that has been frequently recognised, but rarely quantitatively described, were carried out as well. The corresponding equilibrium was taken into account in the anion-binding studies, which enabled reliable determination of the complexation thermodynamic quantities. In both solvents the thiourea derivatives exhibited considerably higher binding affinities with respect to those containing the urea moiety. In acetonitrile, 1:1 and 2:1 (anion/receptor) complexes formed, whereas in dimethyl sulfoxide only the significantly less stable complexes of 1:1 stoichiometry were detected. The solvent effects on the thermodynamic parameters of dihydrogen phosphate dimerisation and complexation reactions are discussed. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Fast computation of derivative based sensitivities of PSHA models via algorithmic differentiation

NASA Astrophysics Data System (ADS)

Leövey, Hernan; Molkenthin, Christian; Scherbaum, Frank; Griewank, Andreas; Kuehn, Nicolas; Stafford, Peter

2015-04-01

Probabilistic seismic hazard analysis (PSHA) is the preferred tool for estimation of potential ground-shaking hazard due to future earthquakes at a site of interest. A modern PSHA represents a complex framework which combines different models with possible many inputs. Sensitivity analysis is a valuable tool for quantifying changes of a model output as inputs are perturbed, identifying critical input parameters and obtaining insight in the model behavior. Differential sensitivity analysis relies on calculating first-order partial derivatives of the model output with respect to its inputs. Moreover, derivative based global sensitivity measures (Sobol' & Kucherenko '09) can be practically used to detect non-essential inputs of the models, thus restricting the focus of attention to a possible much smaller set of inputs. Nevertheless, obtaining first-order partial derivatives of complex models with traditional approaches can be very challenging, and usually increases the computation complexity linearly with the number of inputs appearing in the models. In this study we show how Algorithmic Differentiation (AD) tools can be used in a complex framework such as PSHA to successfully estimate derivative based sensitivities, as is the case in various other domains such as meteorology or aerodynamics, without no significant increase in the computation complexity required for the original computations. First we demonstrate the feasibility of the AD methodology by comparing AD derived sensitivities to analytically derived sensitivities for a basic case of PSHA using a simple ground-motion prediction equation. In a second step, we derive sensitivities via AD for a more complex PSHA study using a ground motion attenuation relation based on a stochastic method to simulate strong motion. The presented approach is general enough to accommodate more advanced PSHA studies of higher complexity.

Complex Dynamics of Droplet Traffic in a Bifurcating Microfluidic Channel: Periodicity, Multistability, and Selection Rules

NASA Astrophysics Data System (ADS)

Sessoms, D. A.; Amon, A.; Courbin, L.; Panizza, P.

2010-10-01

The binary path selection of droplets reaching a T junction is regulated by time-delayed feedback and nonlinear couplings. Such mechanisms result in complex dynamics of droplet partitioning: numerous discrete bifurcations between periodic regimes are observed. We introduce a model based on an approximation that makes this problem tractable. This allows us to derive analytical formulae that predict the occurrence of the bifurcations between consecutive regimes, establish selection rules for the period of a regime, and describe the evolutions of the period and complexity of droplet pattern in a cycle with the key parameters of the system. We discuss the validity and limitations of our model which describes semiquantitatively both numerical simulations and microfluidic experiments.