Hyperbolic scaling and computing in social crowds: Comment on "Human behaviours in evacuation crowd dynamics: From modelling to "big data" toward crisis management" by Nicola Bellomo et al.

NASA Astrophysics Data System (ADS)

Outada, Nisrine

2016-09-01

I have read with great interest the paper [5] where the authors present an overview and critical analysis of the literature on the modeling of the crowd dynamics with special attention to evacuation dynamics. The approach developed is based on suitable development of methods of the kinetic theory. Interactions, which lead to the decision choice, are modeled by theoretical tools of stochastic evolutionary game theory [11,12]. However, the paper [5] provides not only a survey focused on topics of great interest for our society, but also it looks ahead to a variety of interesting and challenging mathematical problems. Specifically, I am interested in the derivation of macroscopic (hydrodynamic) models from the underlying description given from the kinetic theory approach, more specifically by the kinetic theory for active particles [8]. A general reference on crowd modeling is the recently published book [10].

Exploration of the folding dynamics of human telomeric G-quadruplex with a hybrid atomistic structure-based model

NASA Astrophysics Data System (ADS)

Bian, Yunqiang; Ren, Weitong; Song, Feng; Yu, Jiafeng; Wang, Jihua

2018-05-01

Structure-based models or Gō-like models, which are built from one or multiple particular experimental structures, have been successfully applied to the folding of proteins and RNAs. Recently, a variant termed the hybrid atomistic model advances the description of backbone and side chain interactions of traditional structure-based models, by borrowing the description of local interactions from classical force fields. In this study, we assessed the validity of this model in the folding problem of human telomeric DNA G-quadruplex, where local dihedral terms play important roles. A two-state model was developed and a set of molecular dynamics simulations was conducted to study the folding dynamics of sequence Htel24, which was experimentally validated to adopt two different (3 + 1) hybrid G-quadruplex topologies in K+ solution. Consistent with the experimental observations, the hybrid-1 conformation was found to be more stable and the hybrid-2 conformation was kinetically more favored. The simulations revealed that the hybrid-2 conformation folded in a higher cooperative manner, which may be the reason why it was kinetically more accessible. Moreover, by building a Markov state model, a two-quartet G-quadruplex state and a misfolded state were identified as competing states to complicate the folding process of Htel24. Besides, the simulations also showed that the transition between hybrid-1 and hybrid-2 conformations may proceed an ensemble of hairpin structures. The hybrid atomistic structure-based model reproduced the kinetic partitioning folding dynamics of Htel24 between two different folds, and thus can be used to study the complex folding processes of other G-quadruplex structures.

Dynamic Model of Basic Oxygen Steelmaking Process Based on Multizone Reaction Kinetics: Modeling of Decarburization

NASA Astrophysics Data System (ADS)

Rout, Bapin Kumar; Brooks, Geoffrey; Akbar Rhamdhani, M.; Li, Zushu; Schrama, Frank N. H.; Overbosch, Aart

2018-06-01

In a previous study by the authors (Rout et al. in Metall Mater Trans B 49:537-557, 2018), a dynamic model for the BOF, employing the concept of multizone kinetics was developed. In the current study, the kinetics of decarburization reaction is investigated. The jet impact and slag-metal emulsion zones were identified to be primary zones for carbon oxidation. The dynamic parameters in the rate equation of decarburization such as residence time of metal drops in the emulsion, interfacial area evolution, initial size, and the effects of surface-active oxides have been included in the kinetic rate equation of the metal droplet. A modified mass-transfer coefficient based on the ideal Langmuir adsorption equilibrium has been proposed to take into account the surface blockage effects of SiO2 and P2O5 in slag on the decarburization kinetics of a metal droplet in the emulsion. Further, a size distribution function has been included in the rate equation to evaluate the effect of droplet size on reaction kinetics. The mathematical simulation indicates that decarburization of the droplet in the emulsion is a strong function of the initial size and residence time. A modified droplet generation rate proposed previously by the authors has been used to estimate the total decarburization rate by slag-metal emulsion. The model's prediction shows that about 76 pct of total carbon is removed by reactions in the emulsion, and the remaining is removed by reactions at the jet impact zone. The predicted bath carbon by the model has been found to be in good agreement with the industrially measured data.

Dynamic Model of Basic Oxygen Steelmaking Process Based on Multizone Reaction Kinetics: Modeling of Decarburization

NASA Astrophysics Data System (ADS)

Rout, Bapin Kumar; Brooks, Geoffrey; Akbar Rhamdhani, M.; Li, Zushu; Schrama, Frank N. H.; Overbosch, Aart

2018-03-01

In a previous study by the authors (Rout et al. in Metall Mater Trans B 49:537-557, 2018), a dynamic model for the BOF, employing the concept of multizone kinetics was developed. In the current study, the kinetics of decarburization reaction is investigated. The jet impact and slag-metal emulsion zones were identified to be primary zones for carbon oxidation. The dynamic parameters in the rate equation of decarburization such as residence time of metal drops in the emulsion, interfacial area evolution, initial size, and the effects of surface-active oxides have been included in the kinetic rate equation of the metal droplet. A modified mass-transfer coefficient based on the ideal Langmuir adsorption equilibrium has been proposed to take into account the surface blockage effects of SiO2 and P2O5 in slag on the decarburization kinetics of a metal droplet in the emulsion. Further, a size distribution function has been included in the rate equation to evaluate the effect of droplet size on reaction kinetics. The mathematical simulation indicates that decarburization of the droplet in the emulsion is a strong function of the initial size and residence time. A modified droplet generation rate proposed previously by the authors has been used to estimate the total decarburization rate by slag-metal emulsion. The model's prediction shows that about 76 pct of total carbon is removed by reactions in the emulsion, and the remaining is removed by reactions at the jet impact zone. The predicted bath carbon by the model has been found to be in good agreement with the industrially measured data.

Uncertainty in a Markov state model with missing states and rates: Application to a room temperature kinetic model obtained using high temperature molecular dynamics.

PubMed

Chatterjee, Abhijit; Bhattacharya, Swati

2015-09-21

Several studies in the past have generated Markov State Models (MSMs), i.e., kinetic models, of biomolecular systems by post-analyzing long standard molecular dynamics (MD) calculations at the temperature of interest and focusing on the maximally ergodic subset of states. Questions related to goodness of these models, namely, importance of the missing states and kinetic pathways, and the time for which the kinetic model is valid, are generally left unanswered. We show that similar questions arise when we generate a room-temperature MSM (denoted MSM-A) for solvated alanine dipeptide using state-constrained MD calculations at higher temperatures and Arrhenius relation — the main advantage of such a procedure being a speed-up of several thousand times over standard MD-based MSM building procedures. Bounds for rate constants calculated using probability theory from state-constrained MD at room temperature help validate MSM-A. However, bounds for pathways possibly missing in MSM-A show that alternate kinetic models exist that produce the same dynamical behaviour at short time scales as MSM-A but diverge later. Even in the worst case scenario, MSM-A is found to be valid longer than the time required to generate it. Concepts introduced here can be straightforwardly extended to other MSM building techniques.

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

Nguyen, Thao; Luscher, D. J.; Wilkerson, J. W.

We developed a framework for dislocation-based viscoplasticity and dynamic ductile failure to model high strain rate deformation and damage in single crystals. The rate-dependence of the crystal plasticity formulation is based on the physics of relativistic dislocation kinetics suited for extremely high strain rates. The damage evolution is based on the dynamics of void growth, which are governed by both micro-inertia as well as dislocation kinetics and dislocation substructure evolution. Furthermore, an averaging scheme is proposed in order to approximate the evolution of the dislocation substructure in both the macroscale as well as its spatial distribution at the microscale. Inmore » addition, a concept of a single equivalent dislocation density that effectively captures the collective influence of dislocation density on all active slip systems is proposed here. Together, these concepts and approximations enable the use of semi-analytic solutions for void growth dynamics developed in [J. Wilkerson and K. Ramesh. A dynamic void growth model governed by dislocation kinetics. J. Mech. Phys. Solids, 70:262–280, 2014.], which greatly reduce the computational overhead that would otherwise be required. The resulting homogenized framework has been implemented into a commercially available finite element package, and a validation study against a suite of direct numerical simulations was carried out.« less

A Computational Fluid Dynamic Model for a Novel Flash Ironmaking Process

NASA Astrophysics Data System (ADS)

Perez-Fontes, Silvia E.; Sohn, Hong Yong; Olivas-Martinez, Miguel

A computational fluid dynamic model for a novel flash ironmaking process based on the direct gaseous reduction of iron oxide concentrates is presented. The model solves the three-dimensional governing equations including both gas-phase and gas-solid reaction kinetics. The turbulence-chemistry interaction in the gas-phase is modeled by the eddy dissipation concept incorporating chemical kinetics. The particle cloud model is used to track the particle phase in a Lagrangian framework. A nucleation and growth kinetics rate expression is adopted to calculate the reduction rate of magnetite concentrate particles. Benchmark experiments reported in the literature for a nonreacting swirling gas jet and a nonpremixed hydrogen jet flame were simulated for validation. The model predictions showed good agreement with measurements in terms of gas velocity, gas temperature and species concentrations. The relevance of the computational model for the analysis of a bench reactor operation and the design of an industrial-pilot plant is discussed.

Multi-step cure kinetic model of ultra-thin glass fiber epoxy prepreg exhibiting both autocatalytic and diffusion-controlled regimes under isothermal and dynamic-heating conditions

NASA Astrophysics Data System (ADS)

Kim, Ye Chan; Min, Hyunsung; Hong, Sungyong; Wang, Mei; Sun, Hanna; Park, In-Kyung; Choi, Hyouk Ryeol; Koo, Ja Choon; Moon, Hyungpil; Kim, Kwang J.; Suhr, Jonghwan; Nam, Jae-Do

2017-08-01

As packaging technologies are demanded that reduce the assembly area of substrate, thin composite laminate substrates require the utmost high performance in such material properties as the coefficient of thermal expansion (CTE), and stiffness. Accordingly, thermosetting resin systems, which consist of multiple fillers, monomers and/or catalysts in thermoset-based glass fiber prepregs, are extremely complicated and closely associated with rheological properties, which depend on the temperature cycles for cure. For the process control of these complex systems, it is usually required to obtain a reliable kinetic model that could be used for the complex thermal cycles, which usually includes both the isothermal and dynamic-heating segments. In this study, an ultra-thin prepreg with highly loaded silica beads and glass fibers in the epoxy/amine resin system was investigated as a model system by isothermal/dynamic heating experiments. The maximum degree of cure was obtained as a function of temperature. The curing kinetics of the model prepreg system exhibited a multi-step reaction and a limited conversion as a function of isothermal curing temperatures, which are often observed in epoxy cure system because of the rate-determining diffusion of polymer chain growth. The modified kinetic equation accurately described the isothermal behavior and the beginning of the dynamic-heating behavior by integrating the obtained maximum degree of cure into the kinetic model development.

Influence of the partial volume correction method on 18F-fluorodeoxyglucose brain kinetic modelling from dynamic PET images reconstructed with resolution model based OSEM

NASA Astrophysics Data System (ADS)

Bowen, Spencer L.; Byars, Larry G.; Michel, Christian J.; Chonde, Daniel B.; Catana, Ciprian

2013-10-01

Kinetic parameters estimated from dynamic 18F-fluorodeoxyglucose (18F-FDG) PET acquisitions have been used frequently to assess brain function in humans. Neglecting partial volume correction (PVC) for a dynamic series has been shown to produce significant bias in model estimates. Accurate PVC requires a space-variant model describing the reconstructed image spatial point spread function (PSF) that accounts for resolution limitations, including non-uniformities across the field of view due to the parallax effect. For ordered subsets expectation maximization (OSEM), image resolution convergence is local and influenced significantly by the number of iterations, the count density, and background-to-target ratio. As both count density and background-to-target values for a brain structure can change during a dynamic scan, the local image resolution may also concurrently vary. When PVC is applied post-reconstruction the kinetic parameter estimates may be biased when neglecting the frame-dependent resolution. We explored the influence of the PVC method and implementation on kinetic parameters estimated by fitting 18F-FDG dynamic data acquired on a dedicated brain PET scanner and reconstructed with and without PSF modelling in the OSEM algorithm. The performance of several PVC algorithms was quantified with a phantom experiment, an anthropomorphic Monte Carlo simulation, and a patient scan. Using the last frame reconstructed image only for regional spread function (RSF) generation, as opposed to computing RSFs for each frame independently, and applying perturbation geometric transfer matrix PVC with PSF based OSEM produced the lowest magnitude bias kinetic parameter estimates in most instances, although at the cost of increased noise compared to the PVC methods utilizing conventional OSEM. Use of the last frame RSFs for PVC with no PSF modelling in the OSEM algorithm produced the lowest bias in cerebral metabolic rate of glucose estimates, although by less than 5% in most cases compared to the other PVC methods. The results indicate that the PVC implementation and choice of PSF modelling in the reconstruction can significantly impact model parameters.

Influence of the partial volume correction method on (18)F-fluorodeoxyglucose brain kinetic modelling from dynamic PET images reconstructed with resolution model based OSEM.

PubMed

Bowen, Spencer L; Byars, Larry G; Michel, Christian J; Chonde, Daniel B; Catana, Ciprian

2013-10-21

Kinetic parameters estimated from dynamic (18)F-fluorodeoxyglucose ((18)F-FDG) PET acquisitions have been used frequently to assess brain function in humans. Neglecting partial volume correction (PVC) for a dynamic series has been shown to produce significant bias in model estimates. Accurate PVC requires a space-variant model describing the reconstructed image spatial point spread function (PSF) that accounts for resolution limitations, including non-uniformities across the field of view due to the parallax effect. For ordered subsets expectation maximization (OSEM), image resolution convergence is local and influenced significantly by the number of iterations, the count density, and background-to-target ratio. As both count density and background-to-target values for a brain structure can change during a dynamic scan, the local image resolution may also concurrently vary. When PVC is applied post-reconstruction the kinetic parameter estimates may be biased when neglecting the frame-dependent resolution. We explored the influence of the PVC method and implementation on kinetic parameters estimated by fitting (18)F-FDG dynamic data acquired on a dedicated brain PET scanner and reconstructed with and without PSF modelling in the OSEM algorithm. The performance of several PVC algorithms was quantified with a phantom experiment, an anthropomorphic Monte Carlo simulation, and a patient scan. Using the last frame reconstructed image only for regional spread function (RSF) generation, as opposed to computing RSFs for each frame independently, and applying perturbation geometric transfer matrix PVC with PSF based OSEM produced the lowest magnitude bias kinetic parameter estimates in most instances, although at the cost of increased noise compared to the PVC methods utilizing conventional OSEM. Use of the last frame RSFs for PVC with no PSF modelling in the OSEM algorithm produced the lowest bias in cerebral metabolic rate of glucose estimates, although by less than 5% in most cases compared to the other PVC methods. The results indicate that the PVC implementation and choice of PSF modelling in the reconstruction can significantly impact model parameters.

Model and system learners, optimal process constructors and kinetic theory-based goal-oriented design: A new paradigm in materials and processes informatics

NASA Astrophysics Data System (ADS)

Abisset-Chavanne, Emmanuelle; Duval, Jean Louis; Cueto, Elias; Chinesta, Francisco

2018-05-01

Traditionally, Simulation-Based Engineering Sciences (SBES) has relied on the use of static data inputs (model parameters, initial or boundary conditions, … obtained from adequate experiments) to perform simulations. A new paradigm in the field of Applied Sciences and Engineering has emerged in the last decade. Dynamic Data-Driven Application Systems [9, 10, 11, 12, 22] allow the linkage of simulation tools with measurement devices for real-time control of simulations and applications, entailing the ability to dynamically incorporate additional data into an executing application, and in reverse, the ability of an application to dynamically steer the measurement process. It is in that context that traditional "digital-twins" are giving raise to a new generation of goal-oriented data-driven application systems, also known as "hybrid-twins", embracing models based on physics and models exclusively based on data adequately collected and assimilated for filling the gap between usual model predictions and measurements. Within this framework new methodologies based on model learners, machine learning and kinetic goal-oriented design are defining a new paradigm in materials, processes and systems engineering.

Further steps in the modeling of behavioural crowd dynamics, good news for safe handling. Comment on "Human behaviours in evacuation crowd dynamics: From modelling to "big data" toward crisis management" by Nicola Bellomo et al.

NASA Astrophysics Data System (ADS)

Knopoff, Damián A.

2016-09-01

The recent review paper [4] constitutes a valuable contribution on the understanding, modeling and simulation of crowd dynamics in extreme situations. It provides a very comprehensive revision about the complexity features of the system under consideration, scaling and the consequent justification of the used methods. In particular, macro and microscopic models have so far been used to model crowd dynamics [9] and authors appropriately explain that working at the mesoscale is a good choice to deal with the heterogeneous behaviour of walkers as well as with the difficulty of their deterministic identification. In this way, methods based on the kinetic theory and statistical dynamics are employed, more precisely the so-called kinetic theory for active particles [7]. This approach has successfully been applied in the modeling of several complex dynamics, with recent applications to learning [2,8] that constitutes the key to understand communication and is of great importance in social dynamics and behavioral sciences.

Rapid freezing of water under dynamic compression

NASA Astrophysics Data System (ADS)

Myint, Philip C.; Belof, Jonathan L.

2018-06-01

Understanding the behavior of materials at extreme pressures is a central issue in fields like aerodynamics, astronomy, and geology, as well as for advancing technological grand challenges such as inertial confinement fusion. Dynamic compression experiments to probe high-pressure states often encounter rapid phase transitions that may cause the materials to behave in unexpected ways, and understanding the kinetics of these phase transitions remains an area of great interest. In this review, we examine experimental and theoretical/computational efforts to study the freezing kinetics of water to a high-pressure solid phase known as ice VII. We first present a detailed analysis of dynamic compression experiments in which water has been observed to freeze on sub-microsecond time scales to ice VII. This is followed by a discussion of the limitations of currently available molecular and continuum simulation methods in modeling these experiments. We then describe how our phase transition kinetics models, which are based on classical nucleation theory, provide a more physics-based framework that overcomes some of these limitations. Finally, we give suggestions on future experimental and modeling work on the liquid–ice VII transition, including an outline of the development of a predictive multiscale model in which molecular and continuum simulations are intimately coupled.

Rapid freezing of water under dynamic compression.

PubMed

Myint, Philip C; Belof, Jonathan L

2018-06-13

Understanding the behavior of materials at extreme pressures is a central issue in fields like aerodynamics, astronomy, and geology, as well as for advancing technological grand challenges such as inertial confinement fusion. Dynamic compression experiments to probe high-pressure states often encounter rapid phase transitions that may cause the materials to behave in unexpected ways, and understanding the kinetics of these phase transitions remains an area of great interest. In this review, we examine experimental and theoretical/computational efforts to study the freezing kinetics of water to a high-pressure solid phase known as ice VII. We first present a detailed analysis of dynamic compression experiments in which water has been observed to freeze on sub-microsecond time scales to ice VII. This is followed by a discussion of the limitations of currently available molecular and continuum simulation methods in modeling these experiments. We then describe how our phase transition kinetics models, which are based on classical nucleation theory, provide a more physics-based framework that overcomes some of these limitations. Finally, we give suggestions on future experimental and modeling work on the liquid-ice VII transition, including an outline of the development of a predictive multiscale model in which molecular and continuum simulations are intimately coupled.

Simplification and analysis of models of calcium dynamics based on IP3-sensitive calcium channel kinetics.

PubMed

Tang, Y; Stephenson, J L; Othmer, H G

1996-01-01

We study the models for calcium (Ca) dynamics developed in earlier studies, in each of which the key component is the kinetics of intracellular inositol-1,4,5-trisphosphate-sensitive Ca channels. After rapidly equilibrating steps are eliminated, the channel kinetics in these models are represented by a single differential equation that is linear in the state of the channel. In the reduced kinetic model, the graph of the steady-state fraction of conducting channels as a function of log10(Ca) is a bell-shaped curve. Dynamically, a step increase in inositol-1,4,5-trisphosphate induces an incremental increase in the fraction of conducting channels, whereas a step increase in Ca can either potentiate or inhibit channel activation, depending on the Ca level before and after the increase. The relationships among these models are discussed, and experimental tests to distinguish between them are given. Under certain conditions the models for intracellular calcium dynamics are reduced to the singular perturbed form epsilon dx/d tau = f(x, y, p), dy/d tau = g(x, y, p). Phase-plane analysis is applied to a generic form of these simplified models to show how different types of Ca response, such as excitability, oscillations, and a sustained elevation of Ca, can arise. The generic model can also be used to study frequency encoding of hormonal stimuli, to determine the conditions for stable traveling Ca waves, and to understand the effect of channel properties on the wave speed.

Dynamically adjustable foot-ground contact model to estimate ground reaction force during walking and running.

PubMed

Jung, Yihwan; Jung, Moonki; Ryu, Jiseon; Yoon, Sukhoon; Park, Sang-Kyoon; Koo, Seungbum

2016-03-01

Human dynamic models have been used to estimate joint kinetics during various activities. Kinetics estimation is in demand in sports and clinical applications where data on external forces, such as the ground reaction force (GRF), are not available. The purpose of this study was to estimate the GRF during gait by utilizing distance- and velocity-dependent force models between the foot and ground in an inverse-dynamics-based optimization. Ten males were tested as they walked at four different speeds on a force plate-embedded treadmill system. The full-GRF model whose foot-ground reaction elements were dynamically adjusted according to vertical displacement and anterior-posterior speed between the foot and ground was implemented in a full-body skeletal model. The model estimated the vertical and shear forces of the GRF from body kinematics. The shear-GRF model with dynamically adjustable shear reaction elements according to the input vertical force was also implemented in the foot of a full-body skeletal model. Shear forces of the GRF were estimated from body kinematics, vertical GRF, and center of pressure. The estimated full GRF had the lowest root mean square (RMS) errors at the slow walking speed (1.0m/s) with 4.2, 1.3, and 5.7% BW for anterior-posterior, medial-lateral, and vertical forces, respectively. The estimated shear forces were not significantly different between the full-GRF and shear-GRF models, but the RMS errors of the estimated knee joint kinetics were significantly lower for the shear-GRF model. Providing COP and vertical GRF with sensors, such as an insole-type pressure mat, can help estimate shear forces of the GRF and increase accuracy for estimation of joint kinetics. Copyright © 2016 Elsevier B.V. All rights reserved.

Disorder and Chaos: Developing and Teaching an Interdisciplinary Course on Chemical Dynamics

ERIC Educational Resources Information Center

Desjardins, Steven G.

2008-01-01

In this paper we describe an interdisciplinary course on dynamics that is appropriate for nonscience majors. This course introduces ideas about mathematical modeling using examples based on pendulums, chemical kinetics, and population dynamics. The unique emphasis for a nonmajors course is on chemical reactions as dynamical systems that do more…

Spatio-temporal diffusion of dynamic PET images

NASA Astrophysics Data System (ADS)

Tauber, C.; Stute, S.; Chau, M.; Spiteri, P.; Chalon, S.; Guilloteau, D.; Buvat, I.

2011-10-01

Positron emission tomography (PET) images are corrupted by noise. This is especially true in dynamic PET imaging where short frames are required to capture the peak of activity concentration after the radiotracer injection. High noise results in a possible bias in quantification, as the compartmental models used to estimate the kinetic parameters are sensitive to noise. This paper describes a new post-reconstruction filter to increase the signal-to-noise ratio in dynamic PET imaging. It consists in a spatio-temporal robust diffusion of the 4D image based on the time activity curve (TAC) in each voxel. It reduces the noise in homogeneous areas while preserving the distinct kinetics in regions of interest corresponding to different underlying physiological processes. Neither anatomical priors nor the kinetic model are required. We propose an automatic selection of the scale parameter involved in the diffusion process based on a robust statistical analysis of the distances between TACs. The method is evaluated using Monte Carlo simulations of brain activity distributions. We demonstrate the usefulness of the method and its superior performance over two other post-reconstruction spatial and temporal filters. Our simulations suggest that the proposed method can be used to significantly increase the signal-to-noise ratio in dynamic PET imaging.

A physiologically based kinetic model for bacterial sulfide oxidation.

PubMed

Klok, Johannes B M; de Graaff, Marco; van den Bosch, Pim L F; Boelee, Nadine C; Keesman, Karel J; Janssen, Albert J H

2013-02-01

In the biotechnological process for hydrogen sulfide removal from gas streams, a variety of oxidation products can be formed. Under natron-alkaline conditions, sulfide is oxidized by haloalkaliphilic sulfide oxidizing bacteria via flavocytochrome c oxidoreductase. From previous studies, it was concluded that the oxidation-reduction state of cytochrome c is a direct measure for the bacterial end-product formation. Given this physiological feature, incorporation of the oxidation state of cytochrome c in a mathematical model for the bacterial oxidation kinetics will yield a physiologically based model structure. This paper presents a physiologically based model, describing the dynamic formation of the various end-products in the biodesulfurization process. It consists of three elements: 1) Michaelis-Menten kinetics combined with 2) a cytochrome c driven mechanism describing 3) the rate determining enzymes of the respiratory system of haloalkaliphilic sulfide oxidizing bacteria. The proposed model is successfully validated against independent data obtained from biological respiration tests and bench scale gas-lift reactor experiments. The results demonstrate that the model is a powerful tool to describe product formation for haloalkaliphilic biomass under dynamic conditions. The model predicts a maximum S⁰ formation of about 98 mol%. A future challenge is the optimization of this bioprocess by improving the dissolved oxygen control strategy and reactor design. Copyright © 2012 Elsevier Ltd. All rights reserved.

Automated chemical kinetic modeling via hybrid reactive molecular dynamics and quantum chemistry simulations.

PubMed

Döntgen, Malte; Schmalz, Felix; Kopp, Wassja A; Kröger, Leif C; Leonhard, Kai

2018-06-13

An automated scheme for obtaining chemical kinetic models from scratch using reactive molecular dynamics and quantum chemistry simulations is presented. This methodology combines the phase space sampling of reactive molecular dynamics with the thermochemistry and kinetics prediction capabilities of quantum mechanics. This scheme provides the NASA polynomial and modified Arrhenius equation parameters for all species and reactions that are observed during the simulation and supplies them in the ChemKin format. The ab initio level of theory for predictions is easily exchangeable and the presently used G3MP2 level of theory is found to reliably reproduce hydrogen and methane oxidation thermochemistry and kinetics data. Chemical kinetic models obtained with this approach are ready-to-use for, e.g., ignition delay time simulations, as shown for hydrogen combustion. The presented extension of the ChemTraYzer approach can be used as a basis for methodologically advancing chemical kinetic modeling schemes and as a black-box approach to generate chemical kinetic models.

Linear stability analysis of detonations via numerical computation and dynamic mode decomposition

NASA Astrophysics Data System (ADS)

Kabanov, Dmitry I.; Kasimov, Aslan R.

2018-03-01

We introduce a new method to investigate linear stability of gaseous detonations that is based on an accurate shock-fitting numerical integration of the linearized reactive Euler equations with a subsequent analysis of the computed solution via the dynamic mode decomposition. The method is applied to the detonation models based on both the standard one-step Arrhenius kinetics and two-step exothermic-endothermic reaction kinetics. Stability spectra for all cases are computed and analyzed. The new approach is shown to be a viable alternative to the traditional normal-mode analysis used in detonation theory.

HOW CAN BIOLOGICALLY-BASED MODELING OF ARSENIC KINETICS AND DYNAMICS INFORM THE RISK ASSESSMENT PROCESS?

EPA Science Inventory

Quantitative biologically-based models describing key events in the continuum from arsenic exposure to the development of adverse health effects provide a framework to integrate information obtained across diverse research areas. For example, genetic polymorphisms in arsenic met...

Modeling nitrous oxide production and reduction in soil through explicit representation of denitrification enzyme kinetics.

PubMed

Zheng, Jianqiu; Doskey, Paul V

2015-02-17

An enzyme-explicit denitrification model with representations for pre- and de novo synthesized enzymes was developed to improve predictions of nitrous oxide (N2O) accumulations in soil and emissions from the surface. The metabolic model of denitrification is based on dual-substrate utilization and Monod growth kinetics. Enzyme synthesis/activation was incorporated into each sequential reduction step of denitrification to regulate dynamics of the denitrifier population and the active enzyme pool, which controlled the rate function. Parameterizations were developed from observations of the dynamics of N2O production and reduction in soil incubation experiments. The model successfully reproduced the dynamics of N2O and N2 accumulation in the incubations and revealed an important regulatory effect of denitrification enzyme kinetics on the accumulation of denitrification products. Pre-synthesized denitrification enzymes contributed 20, 13, 43, and 62% of N2O that accumulated in 48 h incubations of soil collected from depths of 0-5, 5-10, 10-15, and 15-25 cm, respectively. An enzyme activity function (E) was defined to estimate the relative concentration of active enzymes and variation in response to environmental conditions. The value of E allows for activities of pre-synthesized denitrification enzymes to be differentiated from de novo synthesized enzymes. Incorporating explicit representations of denitrification enzyme kinetics into biogeochemical models is a promising approach for accurately simulating dynamics of the production and reduction of N2O in soils.

Comparison of the performance of tracer kinetic model-driven registration for dynamic contrast enhanced MRI using different models of contrast enhancement.

PubMed

Buonaccorsi, Giovanni A; Roberts, Caleb; Cheung, Sue; Watson, Yvonne; O'Connor, James P B; Davies, Karen; Jackson, Alan; Jayson, Gordon C; Parker, Geoff J M

2006-09-01

The quantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) data is subject to model fitting errors caused by motion during the time-series data acquisition. However, the time-varying features that occur as a result of contrast enhancement can confound motion correction techniques based on conventional registration similarity measures. We have therefore developed a heuristic, locally controlled tracer kinetic model-driven registration procedure, in which the model accounts for contrast enhancement, and applied it to the registration of abdominal DCE-MRI data at high temporal resolution. Using severely motion-corrupted data sets that had been excluded from analysis in a clinical trial of an antiangiogenic agent, we compared the results obtained when using different models to drive the tracer kinetic model-driven registration with those obtained when using a conventional registration against the time series mean image volume. Using tracer kinetic model-driven registration, it was possible to improve model fitting by reducing the sum of squared errors but the improvement was only realized when using a model that adequately described the features of the time series data. The registration against the time series mean significantly distorted the time series data, as did tracer kinetic model-driven registration using a simpler model of contrast enhancement. When an appropriate model is used, tracer kinetic model-driven registration influences motion-corrupted model fit parameter estimates and provides significant improvements in localization in three-dimensional parameter maps. This has positive implications for the use of quantitative DCE-MRI for example in clinical trials of antiangiogenic or antivascular agents.

Blind identification of the kinetic parameters in three-compartment models

NASA Astrophysics Data System (ADS)

Riabkov, Dmitri Y.; Di Bella, Edward V. R.

2004-03-01

Quantified knowledge of tissue kinetic parameters in the regions of the brain and other organs can offer information useful in clinical and research applications. Dynamic medical imaging with injection of radioactive or paramagnetic tracer can be used for this measurement. The kinetics of some widely used tracers such as [18F]2-fluoro-2-deoxy-D-glucose can be described by a three-compartment physiological model. The kinetic parameters of the tissue can be estimated from dynamically acquired images. Feasibility of estimation by blind identification, which does not require knowledge of the blood input, is considered analytically and numerically in this work for the three-compartment type of tissue response. The non-uniqueness of the two-region case for blind identification of kinetic parameters in three-compartment model is shown; at least three regions are needed for the blind identification to be unique. Numerical results for the accuracy of these blind identification methods in different conditions were considered. Both a separable variables least-squares (SLS) approach and an eigenvector-based algorithm for multichannel blind deconvolution approach were used. The latter showed poor accuracy. Modifications for non-uniform time sampling were also developed. Also, another method which uses a model for the blood input was compared. Results for the macroparameter K, which reflects the metabolic rate of glucose usage, using three regions with noise showed comparable accuracy for the separable variables least squares method and for the input model-based method, and slightly worse accuracy for SLS with the non-uniform sampling modification.

Stochastic kinetic mean field model

NASA Astrophysics Data System (ADS)

Erdélyi, Zoltán; Pasichnyy, Mykola; Bezpalchuk, Volodymyr; Tomán, János J.; Gajdics, Bence; Gusak, Andriy M.

2016-07-01

This paper introduces a new model for calculating the change in time of three-dimensional atomic configurations. The model is based on the kinetic mean field (KMF) approach, however we have transformed that model into a stochastic approach by introducing dynamic Langevin noise. The result is a stochastic kinetic mean field model (SKMF) which produces results similar to the lattice kinetic Monte Carlo (KMC). SKMF is, however, far more cost-effective and easier to implement the algorithm (open source program code is provided on http://skmf.eu website). We will show that the result of one SKMF run may correspond to the average of several KMC runs. The number of KMC runs is inversely proportional to the amplitude square of the noise in SKMF. This makes SKMF an ideal tool also for statistical purposes.

Accounting for Space—Quantification of Cell-To-Cell Transmission Kinetics Using Virus Dynamics Models.

PubMed

Kumberger, Peter; Durso-Cain, Karina; Uprichard, Susan L; Dahari, Harel; Graw, Frederik

2018-04-17

Mathematical models based on ordinary differential equations (ODE) that describe the population dynamics of viruses and infected cells have been an essential tool to characterize and quantify viral infection dynamics. Although an important aspect of viral infection is the dynamics of viral spread, which includes transmission by cell-free virions and direct cell-to-cell transmission, models used so far ignored cell-to-cell transmission completely, or accounted for this process by simple mass-action kinetics between infected and uninfected cells. In this study, we show that the simple mass-action approach falls short when describing viral spread in a spatially-defined environment. Using simulated data, we present a model extension that allows correct quantification of cell-to-cell transmission dynamics within a monolayer of cells. By considering the decreasing proportion of cells that can contribute to cell-to-cell spread with progressing infection, our extension accounts for the transmission dynamics on a single cell level while still remaining applicable to standard population-based experimental measurements. While the ability to infer the proportion of cells infected by either of the transmission modes depends on the viral diffusion rate, the improved estimates obtained using our novel approach emphasize the need to correctly account for spatial aspects when analyzing viral spread.

How Can Biologically-Based Modeling of Arsenic Kinetics and Dynamics Inform the Risk Assessment Process? -- ETD

EPA Science Inventory

Quantitative biologically-based models describing key events in the continuum from arsenic exposure to the development of adverse health effects provide a framework to integrate information obtained across diverse research areas. For example, genetic polymorphisms in arsenic me...

Kinetics of the chiral phase transition in a linear σ model

NASA Astrophysics Data System (ADS)

Wesp, Christian; van Hees, Hendrik; Meistrenko, Alex; Greiner, Carsten

2018-02-01

We study the dynamics of the chiral phase transition in a linear quark-meson σ model using a novel approach based on semiclassical wave-particle duality. The quarks are treated as test particles in a Monte Carlo simulation of elastic collisions and the coupling to the σ meson, which is treated as a classical field, via a kinetic approach motivated by wave-particle duality. The exchange of energy and momentum between particles and fields is described in terms of appropriate Gaussian wave packets. It has been demonstrated that energy-momentum conservation and the principle of detailed balance are fulfilled, and that the dynamics leads to the correct equilibrium limit. First schematic studies of the dynamics of matter produced in heavy-ion collisions are presented.

Inference of Gene Regulatory Networks Incorporating Multi-Source Biological Knowledge via a State Space Model with L1 Regularization

PubMed Central

Hasegawa, Takanori; Yamaguchi, Rui; Nagasaki, Masao; Miyano, Satoru; Imoto, Seiya

2014-01-01

Comprehensive understanding of gene regulatory networks (GRNs) is a major challenge in the field of systems biology. Currently, there are two main approaches in GRN analysis using time-course observation data, namely an ordinary differential equation (ODE)-based approach and a statistical model-based approach. The ODE-based approach can generate complex dynamics of GRNs according to biologically validated nonlinear models. However, it cannot be applied to ten or more genes to simultaneously estimate system dynamics and regulatory relationships due to the computational difficulties. The statistical model-based approach uses highly abstract models to simply describe biological systems and to infer relationships among several hundreds of genes from the data. However, the high abstraction generates false regulations that are not permitted biologically. Thus, when dealing with several tens of genes of which the relationships are partially known, a method that can infer regulatory relationships based on a model with low abstraction and that can emulate the dynamics of ODE-based models while incorporating prior knowledge is urgently required. To accomplish this, we propose a method for inference of GRNs using a state space representation of a vector auto-regressive (VAR) model with L1 regularization. This method can estimate the dynamic behavior of genes based on linear time-series modeling constructed from an ODE-based model and can infer the regulatory structure among several tens of genes maximizing prediction ability for the observational data. Furthermore, the method is capable of incorporating various types of existing biological knowledge, e.g., drug kinetics and literature-recorded pathways. The effectiveness of the proposed method is shown through a comparison of simulation studies with several previous methods. For an application example, we evaluated mRNA expression profiles over time upon corticosteroid stimulation in rats, thus incorporating corticosteroid kinetics/dynamics, literature-recorded pathways and transcription factor (TF) information. PMID:25162401

Multi-fluid CFD analysis in Process Engineering

NASA Astrophysics Data System (ADS)

Hjertager, B. H.

2017-12-01

An overview of modelling and simulation of flow processes in gas/particle and gas/liquid systems are presented. Particular emphasis is given to computational fluid dynamics (CFD) models that use the multi-dimensional multi-fluid techniques. Turbulence modelling strategies for gas/particle flows based on the kinetic theory for granular flows are given. Sub models for the interfacial transfer processes and chemical kinetics modelling are presented. Examples are shown for some gas/particle systems including flow and chemical reaction in risers as well as gas/liquid systems including bubble columns and stirred tanks.

Kinetics of Cation and Oxyanion Adsorption and Desorption on Ferrihydrite: Roles of Ferrihydrite Binding Sites and a Unified Model

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

Tian, Lei; Shi, Zhenqing; Lu, Yang

Understanding the kinetics of toxic ion reactions with ferrihydrite is crucial for predicting the dynamic behavior of contaminants in soil environments. In this study, the kinetics of As(V), Cr(VI), Cu, and Pb adsorption and desorption on ferrihydrite were investigated with a combination of laboratory macroscopic experiments, microscopic investigation and mechanistic modeling. The rates of As(V), Cr(VI), Cu, and Pb adsorption and desorption on ferrihydrite, as systematically studied using a stirred-flow method, was highly dependent on the reaction pH and metal concentrations and varied significantly among four metals. Spherical aberration-corrected scanning transmission electron microscopy (Cs-STEM) showed, at sub-nano scales, all fourmore » metals were distributed within the ferrihydrite particle aggregates homogeneously after adsorption reactions, with no evidence of surface diffusion-controlled processes. Based on experimental results, we developed a unifying kinetics model for both cation and oxyanion adsorption/desorption on ferrihydrite based on the mechanistic-based equilibrium model CD-MUSIC. Overall, the model described the kinetic results well, and we quantitatively demonstrated how the equilibrium properties of the cation and oxyanion binding to various ferrihydrite sites affected the adsorption and desorption rates. Our results provided a unifying quantitative modeling method for the kinetics of both cation and oxyanion adsorption/desorption on iron minerals.« less

Systematic Construction of Kinetic Models from Genome-Scale Metabolic Networks

PubMed Central

Smallbone, Kieran; Klipp, Edda; Mendes, Pedro; Liebermeister, Wolfram

2013-01-01

The quantitative effects of environmental and genetic perturbations on metabolism can be studied in silico using kinetic models. We present a strategy for large-scale model construction based on a logical layering of data such as reaction fluxes, metabolite concentrations, and kinetic constants. The resulting models contain realistic standard rate laws and plausible parameters, adhere to the laws of thermodynamics, and reproduce a predefined steady state. These features have not been simultaneously achieved by previous workflows. We demonstrate the advantages and limitations of the workflow by translating the yeast consensus metabolic network into a kinetic model. Despite crudely selected data, the model shows realistic control behaviour, a stable dynamic, and realistic response to perturbations in extracellular glucose concentrations. The paper concludes by outlining how new data can continuously be fed into the workflow and how iterative model building can assist in directing experiments. PMID:24324546

A new approach for describing glass transition kinetics.

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

Vasin, N. M.; Shchelkachev, M. G.; Vinokur, V. M.

2010-04-01

We use a functional integral technique generalizing the Keldysh diagram technique to describe glass transition kinetics. We show that the Keldysh functional approach takes the dynamical determinant arising in the glass dynamics into account exactly and generalizes the traditional approach based on using the supersymmetric dynamic generating functional method. In contrast to the supersymmetric method, this approach allows avoiding additional Grassmannian fields and tracking the violation of the fluctuation-dissipation theorem explicitly. We use this method to describe the dynamics of an Edwards-Anderson soft spin-glass-type model near the paramagnet-glass transition. We show that a Vogel-Fulcher-type dynamics arises in the fluctuation regionmore » only if the fluctuation-dissipation theorem is violated in the process of dynamical renormalization of the Keldysh action in the replica space.« less

On the biophysics and kinetics of toehold-mediated DNA strand displacement

PubMed Central

Srinivas, Niranjan; Ouldridge, Thomas E.; Šulc, Petr; Schaeffer, Joseph M.; Yurke, Bernard; Louis, Ard A.; Doye, Jonathan P. K.; Winfree, Erik

2013-01-01

Dynamic DNA nanotechnology often uses toehold-mediated strand displacement for controlling reaction kinetics. Although the dependence of strand displacement kinetics on toehold length has been experimentally characterized and phenomenologically modeled, detailed biophysical understanding has remained elusive. Here, we study strand displacement at multiple levels of detail, using an intuitive model of a random walk on a 1D energy landscape, a secondary structure kinetics model with single base-pair steps and a coarse-grained molecular model that incorporates 3D geometric and steric effects. Further, we experimentally investigate the thermodynamics of three-way branch migration. Two factors explain the dependence of strand displacement kinetics on toehold length: (i) the physical process by which a single step of branch migration occurs is significantly slower than the fraying of a single base pair and (ii) initiating branch migration incurs a thermodynamic penalty, not captured by state-of-the-art nearest neighbor models of DNA, due to the additional overhang it engenders at the junction. Our findings are consistent with previously measured or inferred rates for hybridization, fraying and branch migration, and they provide a biophysical explanation of strand displacement kinetics. Our work paves the way for accurate modeling of strand displacement cascades, which would facilitate the simulation and construction of more complex molecular systems. PMID:24019238

On the biophysics and kinetics of toehold-mediated DNA strand displacement.

PubMed

Srinivas, Niranjan; Ouldridge, Thomas E; Sulc, Petr; Schaeffer, Joseph M; Yurke, Bernard; Louis, Ard A; Doye, Jonathan P K; Winfree, Erik

2013-12-01

Dynamic DNA nanotechnology often uses toehold-mediated strand displacement for controlling reaction kinetics. Although the dependence of strand displacement kinetics on toehold length has been experimentally characterized and phenomenologically modeled, detailed biophysical understanding has remained elusive. Here, we study strand displacement at multiple levels of detail, using an intuitive model of a random walk on a 1D energy landscape, a secondary structure kinetics model with single base-pair steps and a coarse-grained molecular model that incorporates 3D geometric and steric effects. Further, we experimentally investigate the thermodynamics of three-way branch migration. Two factors explain the dependence of strand displacement kinetics on toehold length: (i) the physical process by which a single step of branch migration occurs is significantly slower than the fraying of a single base pair and (ii) initiating branch migration incurs a thermodynamic penalty, not captured by state-of-the-art nearest neighbor models of DNA, due to the additional overhang it engenders at the junction. Our findings are consistent with previously measured or inferred rates for hybridization, fraying and branch migration, and they provide a biophysical explanation of strand displacement kinetics. Our work paves the way for accurate modeling of strand displacement cascades, which would facilitate the simulation and construction of more complex molecular systems.

Mark R. Nimlos | NREL

Science.gov Websites

, reaction kinetics, computational modeling, photochemistry, and molecular spectroscopy. Nimlos has served as Chemical reaction energetics and kinetics Biomass pyrolysis and gasification Heterogeneous catalysis in zeolites Quantum modeling and kinetic modeling of reaction Molecular dynamics modeling

Relaxation processes in a low-order three-dimensional magnetohydrodynamics model

NASA Technical Reports Server (NTRS)

Stribling, Troy; Matthaeus, William H.

1991-01-01

The time asymptotic behavior of a Galerkin model of 3D magnetohydrodynamics (MHD) has been interpreted using the selective decay and dynamic alignment relaxation theories. A large number of simulations has been performed that scan a parameter space defined by the rugged ideal invariants, including energy, cross helicity, and magnetic helicity. It is concluded that time asymptotic state can be interpreted as a relaxation to minimum energy. A simple decay model, based on absolute equilibrium theory, is found to predict a mapping of initial onto time asymptotic states, and to accurately describe the long time behavior of the runs when magnetic helicity is present. Attention is also given to two processes, operating on time scales shorter than selective decay and dynamic alignment, in which the ratio of kinetic to magnetic energy relaxes to values 0(1). The faster of the two processes takes states initially dominant in magnetic energy to a state of near-equipartition between kinetic and magnetic energy through power law growth of kinetic energy. The other process takes states initially dominant in kinetic energy to the near-equipartitioned state through exponential growth of magnetic energy.

DISCRETE VOLUME-ELEMENT METHOD FOR NETWORK WATER- QUALITY MODELS

EPA Science Inventory

An explicit dynamic water-quality modeling algorithm is developed for tracking dissolved substances in water-distribution networks. The algorithm is based on a mass-balance relation within pipes that considers both advective transport and reaction kinetics. Complete mixing of m...

Understanding the kinetic mechanism of RNA single base pair formation

PubMed Central

Xu, Xiaojun; Yu, Tao; Chen, Shi-Jie

2016-01-01

RNA functions are intrinsically tied to folding kinetics. The most elementary step in RNA folding is the closing and opening of a base pair. Understanding this elementary rate process is the basis for RNA folding kinetics studies. Previous studies mostly focused on the unfolding of base pairs. Here, based on a hybrid approach, we investigate the folding process at level of single base pairing/stacking. The study, which integrates molecular dynamics simulation, kinetic Monte Carlo simulation, and master equation methods, uncovers two alternative dominant pathways: Starting from the unfolded state, the nucleotide backbone first folds to the native conformation, followed by subsequent adjustment of the base conformation. During the base conformational rearrangement, the backbone either retains the native conformation or switches to nonnative conformations in order to lower the kinetic barrier for base rearrangement. The method enables quantification of kinetic partitioning among the different pathways. Moreover, the simulation reveals several intriguing ion binding/dissociation signatures for the conformational changes. Our approach may be useful for developing a base pair opening/closing rate model. PMID:26699466

Potential-based dynamical reweighting for Markov state models of protein dynamics.

PubMed

Weber, Jeffrey K; Pande, Vijay S

2015-06-09

As simulators attempt to replicate the dynamics of large cellular components in silico, problems related to sampling slow, glassy degrees of freedom in molecular systems will be amplified manyfold. It is tempting to augment simulation techniques with external biases to overcome such barriers with ease; biased simulations, however, offer little utility unless equilibrium properties of interest (both kinetic and thermodynamic) can be recovered from the data generated. In this Article, we present a general scheme that harnesses the power of Markov state models (MSMs) to extract equilibrium kinetic properties from molecular dynamics trajectories collected on biased potential energy surfaces. We first validate our reweighting protocol on a simple two-well potential, and we proceed to test our method on potential-biased simulations of the Trp-cage miniprotein. In both cases, we find that equilibrium populations, time scales, and dynamical processes are reliably reproduced as compared to gold standard, unbiased data sets. We go on to discuss the limitations of our dynamical reweighting approach, and we suggest auspicious target systems for further application.

Kinetic damping in the spectra of the spherical impedance probe

NASA Astrophysics Data System (ADS)

Oberrath, J.

2018-04-01

The impedance probe is a measurement device to measure plasma parameters, such as electron density. It consists of one electrode connected to a network analyzer via a coaxial cable and is immersed into a plasma. A bias potential superposed with an alternating potential is applied to the electrode and the response of the plasma is measured. Its dynamical interaction with the plasma in an electrostatic, kinetic description can be modeled in an abstract notation based on functional analytic methods. These methods provide the opportunity to derive a general solution, which is given as the response function of the probe–plasma system. It is defined by the matrix elements of the resolvent of an appropriate dynamical operator. Based on the general solution, a residual damping for vanishing pressure can be predicted and can only be explained by kinetic effects. In this paper, an explicit response function of the spherical impedance probe is derived. Therefore, the resolvent is determined by its algebraic representation based on an expansion in orthogonal basis functions. This allows one to compute an approximated response function and its corresponding spectra. These spectra show additional damping due to kinetic effects and are in good agreement with former kinetically determined spectra.

Efficient use of single molecule time traces to resolve kinetic rates, models and uncertainties

NASA Astrophysics Data System (ADS)

Schmid, Sonja; Hugel, Thorsten

2018-03-01

Single molecule time traces reveal the time evolution of unsynchronized kinetic systems. Especially single molecule Förster resonance energy transfer (smFRET) provides access to enzymatically important time scales, combined with molecular distance resolution and minimal interference with the sample. Yet the kinetic analysis of smFRET time traces is complicated by experimental shortcomings—such as photo-bleaching and noise. Here we recapitulate the fundamental limits of single molecule fluorescence that render the classic, dwell-time based kinetic analysis unsuitable. In contrast, our Single Molecule Analysis of Complex Kinetic Sequences (SMACKS) considers every data point and combines the information of many short traces in one global kinetic rate model. We demonstrate the potential of SMACKS by resolving the small kinetic effects caused by different ionic strengths in the chaperone protein Hsp90. These results show an unexpected interrelation between conformational dynamics and ATPase activity in Hsp90.

The Nonlinear Magnetosphere: Expressions in MHD and in Kinetic Models

NASA Technical Reports Server (NTRS)

Hesse, Michael; Birn, Joachim

2011-01-01

Like most plasma systems, the magnetosphere of the Earth is governed by nonlinear dynamic evolution equations. The impact of nonlinearities ranges from large scales, where overall dynamics features are exhibiting nonlinear behavior, to small scale, kinetic, processes, where nonlinear behavior governs, among others, energy conversion and dissipation. In this talk we present a select set of examples of such behavior, with a specific emphasis on how nonlinear effects manifest themselves in MHD and in kinetic models of magnetospheric plasma dynamics.

Modeling initial contact dynamics during ambulation with dynamic simulation.

PubMed

Meyer, Andrew R; Wang, Mei; Smith, Peter A; Harris, Gerald F

2007-04-01

Ankle-foot orthoses are frequently used interventions to correct pathological gait. Their effects on the kinematics and kinetics of the proximal joints are of great interest when prescribing ankle-foot orthoses to specific patient groups. Mathematical Dynamic Model (MADYMO) is developed to simulate motor vehicle crash situations and analyze tissue injuries of the occupants based multibody dynamic theories. Joint kinetics output from an inverse model were perturbed and input to the forward model to examine the effects of changes in the internal sagittal ankle moment on knee and hip kinematics following heel strike. Increasing the internal ankle moment (augmentation, equivalent to gastroc-soleus contraction) produced less pronounced changes in kinematic results at the hip, knee and ankle than decreasing the moment (attenuation, equivalent to gastroc-soleus relaxation). Altering the internal ankle moment produced two distinctly different kinematic curve morphologies at the hip. Decreased internal ankle moments increased hip flexion, peaking at roughly 8% of the gait cycle. Increasing internal ankle moments decreased hip flexion to a lesser degree, and approached normal at the same point in the gait cycle. Increasing the internal ankle moment produced relatively small, well-behaved extension-biased kinematic results at the knee. Decreasing the internal ankle moment produced more substantial changes in knee kinematics towards flexion that increased with perturbation magnitude. Curve morphologies were similar to those at the hip. Immediately following heel strike, kinematic results at the ankle showed movement in the direction of the internal moment perturbation. Increased internal moments resulted in kinematic patterns that rapidly approach normal after initial differences. When the internal ankle moment was decreased, differences from normal were much greater and did not rapidly decrease. This study shows that MADYMO can be successfully applied to accomplish forward dynamic simulations, given kinetic inputs. Future applications include predicting muscle forces and decomposing external kinetics.

Evaluation of rate law approximations in bottom-up kinetic models of metabolism.

PubMed

Du, Bin; Zielinski, Daniel C; Kavvas, Erol S; Dräger, Andreas; Tan, Justin; Zhang, Zhen; Ruggiero, Kayla E; Arzumanyan, Garri A; Palsson, Bernhard O

2016-06-06

The mechanistic description of enzyme kinetics in a dynamic model of metabolism requires specifying the numerical values of a large number of kinetic parameters. The parameterization challenge is often addressed through the use of simplifying approximations to form reaction rate laws with reduced numbers of parameters. Whether such simplified models can reproduce dynamic characteristics of the full system is an important question. In this work, we compared the local transient response properties of dynamic models constructed using rate laws with varying levels of approximation. These approximate rate laws were: 1) a Michaelis-Menten rate law with measured enzyme parameters, 2) a Michaelis-Menten rate law with approximated parameters, using the convenience kinetics convention, 3) a thermodynamic rate law resulting from a metabolite saturation assumption, and 4) a pure chemical reaction mass action rate law that removes the role of the enzyme from the reaction kinetics. We utilized in vivo data for the human red blood cell to compare the effect of rate law choices against the backdrop of physiological flux and concentration differences. We found that the Michaelis-Menten rate law with measured enzyme parameters yields an excellent approximation of the full system dynamics, while other assumptions cause greater discrepancies in system dynamic behavior. However, iteratively replacing mechanistic rate laws with approximations resulted in a model that retains a high correlation with the true model behavior. Investigating this consistency, we determined that the order of magnitude differences among fluxes and concentrations in the network were greatly influential on the network dynamics. We further identified reaction features such as thermodynamic reversibility, high substrate concentration, and lack of allosteric regulation, which make certain reactions more suitable for rate law approximations. Overall, our work generally supports the use of approximate rate laws when building large scale kinetic models, due to the key role that physiologically meaningful flux and concentration ranges play in determining network dynamics. However, we also showed that detailed mechanistic models show a clear benefit in prediction accuracy when data is available. The work here should help to provide guidance to future kinetic modeling efforts on the choice of rate law and parameterization approaches.

Joint reconstruction of dynamic PET activity and kinetic parametric images using total variation constrained dictionary sparse coding

NASA Astrophysics Data System (ADS)

Yu, Haiqing; Chen, Shuhang; Chen, Yunmei; Liu, Huafeng

2017-05-01

Dynamic positron emission tomography (PET) is capable of providing both spatial and temporal information of radio tracers in vivo. In this paper, we present a novel joint estimation framework to reconstruct temporal sequences of dynamic PET images and the coefficients characterizing the system impulse response function, from which the associated parametric images of the system macro parameters for tracer kinetics can be estimated. The proposed algorithm, which combines statistical data measurement and tracer kinetic models, integrates a dictionary sparse coding (DSC) into a total variational minimization based algorithm for simultaneous reconstruction of the activity distribution and parametric map from measured emission sinograms. DSC, based on the compartmental theory, provides biologically meaningful regularization, and total variation regularization is incorporated to provide edge-preserving guidance. We rely on techniques from minimization algorithms (the alternating direction method of multipliers) to first generate the estimated activity distributions with sub-optimal kinetic parameter estimates, and then recover the parametric maps given these activity estimates. These coupled iterative steps are repeated as necessary until convergence. Experiments with synthetic, Monte Carlo generated data, and real patient data have been conducted, and the results are very promising.

Nonequilibrium Statistical Mechanics in One Dimension

NASA Astrophysics Data System (ADS)

Privman, Vladimir

2005-08-01

Part I. Reaction-Diffusion Systems and Models of Catalysis; 1. Scaling theories of diffusion-controlled and ballistically-controlled bimolecular reactions S. Redner; 2. The coalescence process, A+A->A, and the method of interparticle distribution functions D. ben-Avraham; 3. Critical phenomena at absorbing states R. Dickman; Part II. Kinetic Ising Models; 4. Kinetic ising models with competing dynamics: mappings, correlations, steady states, and phase transitions Z. Racz; 5. Glauber dynamics of the ising model N. Ito; 6. 1D Kinetic ising models at low temperatures - critical dynamics, domain growth, and freezing S. Cornell; Part III. Ordering, Coagulation, Phase Separation; 7. Phase-ordering dynamics in one dimension A. J. Bray; 8. Phase separation, cluster growth, and reaction kinetics in models with synchronous dynamics V. Privman; 9. Stochastic models of aggregation with injection H. Takayasu and M. Takayasu; Part IV. Random Sequential Adsorption and Relaxation Processes; 10. Random and cooperative sequential adsorption: exactly solvable problems on 1D lattices, continuum limits, and 2D extensions J. W. Evans; 11. Lattice models of irreversible adsorption and diffusion P. Nielaba; 12. Deposition-evaporation dynamics: jamming, conservation laws and dynamical diversity M. Barma; Part V. Fluctuations In Particle and Surface Systems; 13. Microscopic models of macroscopic shocks S. A. Janowsky and J. L. Lebowitz; 14. The asymmetric exclusion model: exact results through a matrix approach B. Derrida and M. R. Evans; 15. Nonequilibrium surface dynamics with volume conservation J. Krug; 16. Directed walks models of polymers and wetting J. Yeomans; Part VI. Diffusion and Transport In One Dimension; 17. Some recent exact solutions of the Fokker-Planck equation H. L. Frisch; 18. Random walks, resonance, and ratchets C. R. Doering and T. C. Elston; 19. One-dimensional random walks in random environment K. Ziegler; Part VII. Experimental Results; 20. Diffusion-limited exciton kinetics in one-dimensional systems R. Kroon and R. Sprik; 21. Experimental investigations of molecular and excitonic elementary reaction kinetics in one-dimensional systems R. Kopelman and A. L. Lin; 22. Luminescence quenching as a probe of particle distribution S. H. Bossmann and L. S. Schulman; Index.

Kinetic and dynamic probability-density-function descriptions of disperse turbulent two-phase flows

NASA Astrophysics Data System (ADS)

Minier, Jean-Pierre; Profeta, Christophe

2015-11-01

This article analyzes the status of two classical one-particle probability density function (PDF) descriptions of the dynamics of discrete particles dispersed in turbulent flows. The first PDF formulation considers only the process made up by particle position and velocity Zp=(xp,Up) and is represented by its PDF p (t ;yp,Vp) which is the solution of a kinetic PDF equation obtained through a flux closure based on the Furutsu-Novikov theorem. The second PDF formulation includes fluid variables into the particle state vector, for example, the fluid velocity seen by particles Zp=(xp,Up,Us) , and, consequently, handles an extended PDF p (t ;yp,Vp,Vs) which is the solution of a dynamic PDF equation. For high-Reynolds-number fluid flows, a typical formulation of the latter category relies on a Langevin model for the trajectories of the fluid seen or, conversely, on a Fokker-Planck equation for the extended PDF. In the present work, a new derivation of the kinetic PDF equation is worked out and new physical expressions of the dispersion tensors entering the kinetic PDF equation are obtained by starting from the extended PDF and integrating over the fluid seen. This demonstrates that, under the same assumption of a Gaussian colored noise and irrespective of the specific stochastic model chosen for the fluid seen, the kinetic PDF description is the marginal of a dynamic PDF one. However, a detailed analysis reveals that kinetic PDF models of particle dynamics in turbulent flows described by statistical correlations constitute incomplete stand-alone PDF descriptions and, moreover, that present kinetic-PDF equations are mathematically ill posed. This is shown to be the consequence of the non-Markovian characteristic of the stochastic process retained to describe the system and the use of an external colored noise. Furthermore, developments bring out that well-posed PDF descriptions are essentially due to a proper choice of the variables selected to describe physical systems and guidelines are formulated to emphasize the key role played by the notion of slow and fast variables.

Role of small oligomers on the amyloidogenic aggregation free-energy landscape.

PubMed

He, Xianglan; Giurleo, Jason T; Talaga, David S

2010-01-08

We combine atomic-force-microscopy particle-size-distribution measurements with earlier measurements on 1-anilino-8-naphthalene sulfonate, thioflavin T, and dynamic light scattering to develop a quantitative kinetic model for the aggregation of beta-lactoglobulin into amyloid. We directly compare our simulations to the population distributions provided by dynamic light scattering and atomic force microscopy. We combine species in the simulation according to structural type for comparison with fluorescence fingerprint results. The kinetic model of amyloidogenesis leads to an aggregation free-energy landscape. We define the roles of and propose a classification scheme for different oligomeric species based on their location in the aggregation free-energy landscape. We relate the different types of oligomers to the amyloid cascade hypothesis and the toxic oligomer hypothesis for amyloid-related diseases. We discuss existing kinetic mechanisms in terms of the different types of oligomers. We provide a possible resolution to the toxic oligomer-amyloid coincidence.

ITC Recommendations for Transporter Kinetic Parameter Estimation and Translational Modeling of Transport-Mediated PK and DDIs in Humans

PubMed Central

Zamek-Gliszczynski, MJ; Lee, CA; Poirier, A; Bentz, J; Chu, X; Ellens, H; Ishikawa, T; Jamei, M; Kalvass, JC; Nagar, S; Pang, KS; Korzekwa, K; Swaan, PW; Taub, ME; Zhao, P; Galetin, A

2013-01-01

This white paper provides a critical analysis of methods for estimating transporter kinetics and recommendations on proper parameter calculation in various experimental systems. Rational interpretation of transporter-knockout animal findings and application of static and dynamic physiologically based modeling approaches for prediction of human transporter-mediated pharmacokinetics and drug–drug interactions (DDIs) are presented. The objective is to provide appropriate guidance for the use of in vitro, in vivo, and modeling tools in translational transporter science. PMID:23588311

Chemical Kinetics, Heat Transfer, and Sensor Dynamics Revisited in a Simple Experiment

ERIC Educational Resources Information Center

Sad, Maria E.; Sad, Mario R.; Castro, Alberto A.; Garetto, Teresita F.

2008-01-01

A simple experiment about thermal effects in chemical reactors is described, which can be used to illustrate chemical reactor models, the determination and validation of their parameters, and some simple principles of heat transfer and sensor dynamics. It is based in the exothermic reaction between aqueous solutions of sodium thiosulfate and…

Programmable energy landscapes for kinetic control of DNA strand displacement.

PubMed

Machinek, Robert R F; Ouldridge, Thomas E; Haley, Natalie E C; Bath, Jonathan; Turberfield, Andrew J

2014-11-10

DNA is used to construct synthetic systems that sense, actuate, move and compute. The operation of many dynamic DNA devices depends on toehold-mediated strand displacement, by which one DNA strand displaces another from a duplex. Kinetic control of strand displacement is particularly important in autonomous molecular machinery and molecular computation, in which non-equilibrium systems are controlled through rates of competing processes. Here, we introduce a new method based on the creation of mismatched base pairs as kinetic barriers to strand displacement. Reaction rate constants can be tuned across three orders of magnitude by altering the position of such a defect without significantly changing the stabilities of reactants or products. By modelling reaction free-energy landscapes, we explore the mechanistic basis of this control mechanism. We also demonstrate that oxDNA, a coarse-grained model of DNA, is capable of accurately predicting and explaining the impact of mismatches on displacement kinetics.

Dynamic biogas upgrading based on the Sabatier process: thermodynamic and dynamic process simulation.

PubMed

Jürgensen, Lars; Ehimen, Ehiaze Augustine; Born, Jens; Holm-Nielsen, Jens Bo

2015-02-01

This study aimed to investigate the feasibility of substitute natural gas (SNG) generation using biogas from anaerobic digestion and hydrogen from renewable energy systems. Using thermodynamic equilibrium analysis, kinetic reactor modeling and transient simulation, an integrated approach for the operation of a biogas-based Sabatier process was put forward, which was then verified using a lab scale heterogenous methanation reactor. The process simulation using a kinetic reactor model demonstrated the feasibility of the production of SNG at gas grid standards using a single reactor setup. The Wobbe index, CO2 content and calorific value were found to be controllable by the H2/CO2 ratio fed the methanation reactor. An optimal H2/CO2 ratio of 3.45-3.7 was seen to result in a product gas with high calorific value and Wobbe index. The dynamic reactor simulation verified that the process start-up was feasible within several minutes to facilitate surplus electricity use from renewable energy systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

Kinetics of heavy metal adsorption and desorption in soil: Developing a unified model based on chemical speciation

NASA Astrophysics Data System (ADS)

Peng, Lanfang; Liu, Paiyu; Feng, Xionghan; Wang, Zimeng; Cheng, Tao; Liang, Yuzhen; Lin, Zhang; Shi, Zhenqing

2018-03-01

Predicting the kinetics of heavy metal adsorption and desorption in soil requires consideration of multiple heterogeneous soil binding sites and variations of reaction chemistry conditions. Although chemical speciation models have been developed for predicting the equilibrium of metal adsorption on soil organic matter (SOM) and important mineral phases (e.g. Fe and Al (hydr)oxides), there is still a lack of modeling tools for predicting the kinetics of metal adsorption and desorption reactions in soil. In this study, we developed a unified model for the kinetics of heavy metal adsorption and desorption in soil based on the equilibrium models WHAM 7 and CD-MUSIC, which specifically consider metal kinetic reactions with multiple binding sites of SOM and soil minerals simultaneously. For each specific binding site, metal adsorption and desorption rate coefficients were constrained by the local equilibrium partition coefficients predicted by WHAM 7 or CD-MUSIC, and, for each metal, the desorption rate coefficients of various binding sites were constrained by their metal binding constants with those sites. The model had only one fitting parameter for each soil binding phase, and all other parameters were derived from WHAM 7 and CD-MUSIC. A stirred-flow method was used to study the kinetics of Cd, Cu, Ni, Pb, and Zn adsorption and desorption in multiple soils under various pH and metal concentrations, and the model successfully reproduced most of the kinetic data. We quantitatively elucidated the significance of different soil components and important soil binding sites during the adsorption and desorption kinetic processes. Our model has provided a theoretical framework to predict metal adsorption and desorption kinetics, which can be further used to predict the dynamic behavior of heavy metals in soil under various natural conditions by coupling other important soil processes.

Integrating Kinetic Model of E. coli with Genome Scale Metabolic Fluxes Overcomes Its Open System Problem and Reveals Bistability in Central Metabolism

PubMed Central

Mannan, Ahmad A.; Toya, Yoshihiro; Shimizu, Kazuyuki; McFadden, Johnjoe; Kierzek, Andrzej M.; Rocco, Andrea

2015-01-01

An understanding of the dynamics of the metabolic profile of a bacterial cell is sought from a dynamical systems analysis of kinetic models. This modelling formalism relies on a deterministic mathematical description of enzyme kinetics and their metabolite regulation. However, it is severely impeded by the lack of available kinetic information, limiting the size of the system that can be modelled. Furthermore, the subsystem of the metabolic network whose dynamics can be modelled is faced with three problems: how to parameterize the model with mostly incomplete steady state data, how to close what is now an inherently open system, and how to account for the impact on growth. In this study we address these challenges of kinetic modelling by capitalizing on multi-‘omics’ steady state data and a genome-scale metabolic network model. We use these to generate parameters that integrate knowledge embedded in the genome-scale metabolic network model, into the most comprehensive kinetic model of the central carbon metabolism of E. coli realized to date. As an application, we performed a dynamical systems analysis of the resulting enriched model. This revealed bistability of the central carbon metabolism and thus its potential to express two distinct metabolic states. Furthermore, since our model-informing technique ensures both stable states are constrained by the same thermodynamically feasible steady state growth rate, the ensuing bistability represents a temporal coexistence of the two states, and by extension, reveals the emergence of a phenotypically heterogeneous population. PMID:26469081

Dynamic Modeling of Yield and Particle Size Distribution in Continuous Bayer Precipitation

NASA Astrophysics Data System (ADS)

Stephenson, Jerry L.; Kapraun, Chris

Process engineers at Alcoa's Point Comfort refinery are using a dynamic model of the Bayer precipitation area to evaluate options in operating strategies. The dynamic model, a joint development effort between Point Comfort and the Alcoa Technical Center, predicts process yields, particle size distributions and occluded soda levels for various flowsheet configurations of the precipitation and classification circuit. In addition to rigorous heat, material and particle population balances, the model includes mechanistic kinetic expressions for particle growth and agglomeration and semi-empirical kinetics for nucleation and attrition. The kinetic parameters have been tuned to Point Comfort's operating data, with excellent matches between the model results and plant data. The model is written for the ACSL dynamic simulation program with specifically developed input/output graphical user interfaces to provide a user-friendly tool. Features such as a seed charge controller enhance the model's usefulness for evaluating operating conditions and process control approaches.

Efficient chemoenzymatic dynamic kinetic resolution of 1-heteroaryl ethanols.

PubMed

Vallin, Karl S A; Wensbo Posaric, David; Hamersak, Zdenko; Svensson, Mats A; Minidis, Alexander B E

2009-12-18

The scope and limitation of the combined ruthenium-lipase induced dynamic kinetic resolution (DKR) through O-acetylation of racemic heteroaromatic secondary alcohols, i.e., 1-heteroaryl substituted ethanols, was investigated. After initial screening of reaction conditions, Candida antarctica lipase B (Novozyme 435, N435) together with 4-chloro-phenylacetate as acetyl-donor for kinetic resolution (KR), in conjunction with the ruthenium-based Shvo catalyst for substrate racemization in toluene at 80 degrees C, enabled DKR with high yields and stereoselectivity of various 1-heteroaryl ethanols, such as oxadiazoles, isoxazoles, 1H-pyrazole, or 1H-imidazole. In addition, DFT calculations based on a simplified catalyst complex model for the catalytic (de)hydrogenation step are in agreement with the previously reported outer sphere mechanism. These results support the further understanding of the mechanistic aspects behind the difference in reactivity of 1-heteroaryl substituted ethanols in comparison to reference substrates, as often referred to in the literature.

Kinetics from Replica Exchange Molecular Dynamics Simulations.

PubMed

Stelzl, Lukas S; Hummer, Gerhard

2017-08-08

Transitions between metastable states govern many fundamental processes in physics, chemistry and biology, from nucleation events in phase transitions to the folding of proteins. The free energy surfaces underlying these processes can be obtained from simulations using enhanced sampling methods. However, their altered dynamics makes kinetic and mechanistic information difficult or impossible to extract. Here, we show that, with replica exchange molecular dynamics (REMD), one can not only sample equilibrium properties but also extract kinetic information. For systems that strictly obey first-order kinetics, the procedure to extract rates is rigorous. For actual molecular systems whose long-time dynamics are captured by kinetic rate models, accurate rate coefficients can be determined from the statistics of the transitions between the metastable states at each replica temperature. We demonstrate the practical applicability of the procedure by constructing master equation (Markov state) models of peptide and RNA folding from REMD simulations.

Modeling of scale-dependent bacterial growth by chemical kinetics approach.

PubMed

Martínez, Haydee; Sánchez, Joaquín; Cruz, José-Manuel; Ayala, Guadalupe; Rivera, Marco; Buhse, Thomas

2014-01-01

We applied the so-called chemical kinetics approach to complex bacterial growth patterns that were dependent on the liquid-surface-area-to-volume ratio (SA/V) of the bacterial cultures. The kinetic modeling was based on current experimental knowledge in terms of autocatalytic bacterial growth, its inhibition by the metabolite CO2, and the relief of inhibition through the physical escape of the inhibitor. The model quantitatively reproduces kinetic data of SA/V-dependent bacterial growth and can discriminate between differences in the growth dynamics of enteropathogenic E. coli, E. coli JM83, and Salmonella typhimurium on one hand and Vibrio cholerae on the other hand. Furthermore, the data fitting procedures allowed predictions about the velocities of the involved key processes and the potential behavior in an open-flow bacterial chemostat, revealing an oscillatory approach to the stationary states.

Structural kinetic modeling of metabolic networks.

PubMed

Steuer, Ralf; Gross, Thilo; Selbig, Joachim; Blasius, Bernd

2006-08-08

To develop and investigate detailed mathematical models of metabolic processes is one of the primary challenges in systems biology. However, despite considerable advance in the topological analysis of metabolic networks, kinetic modeling is still often severely hampered by inadequate knowledge of the enzyme-kinetic rate laws and their associated parameter values. Here we propose a method that aims to give a quantitative account of the dynamical capabilities of a metabolic system, without requiring any explicit information about the functional form of the rate equations. Our approach is based on constructing a local linear model at each point in parameter space, such that each element of the model is either directly experimentally accessible or amenable to a straightforward biochemical interpretation. This ensemble of local linear models, encompassing all possible explicit kinetic models, then allows for a statistical exploration of the comprehensive parameter space. The method is exemplified on two paradigmatic metabolic systems: the glycolytic pathway of yeast and a realistic-scale representation of the photosynthetic Calvin cycle.

Assembly kinetics determine the architecture of α-actinin crosslinked F-actin networks.

PubMed

Falzone, Tobias T; Lenz, Martin; Kovar, David R; Gardel, Margaret L

2012-05-29

The actin cytoskeleton is organized into diverse meshworks and bundles that support many aspects of cell physiology. Understanding the self-assembly of these actin-based structures is essential for developing predictive models of cytoskeletal organization. Here we show that the competing kinetics of bundle formation with the onset of dynamic arrest arising from filament entanglements and crosslinking determine the architecture of reconstituted actin networks formed with α-actinin crosslinks. Crosslink-mediated bundle formation only occurs in dilute solutions of highly mobile actin filaments. As actin polymerization proceeds, filament mobility and bundle formation are arrested concomitantly. By controlling the onset of dynamic arrest, perturbations to actin assembly kinetics dramatically alter the architecture of biochemically identical samples. Thus, the morphology of reconstituted F-actin networks is a kinetically determined structure similar to those formed by physical gels and glasses. These results establish mechanisms controlling the structure and mechanics in diverse semiflexible biopolymer networks.

Optimal blood glucose level control using dynamic programming based on minimal Bergman model

NASA Astrophysics Data System (ADS)

Rettian Anggita Sari, Maria; Hartono

2018-03-01

The purpose of this article is to simulate the glucose dynamic and the insulin kinetic of diabetic patient. The model used in this research is a non-linear Minimal Bergman model. Optimal control theory is then applied to formulate the problem in order to determine the optimal dose of insulin in the treatment of diabetes mellitus such that the glucose level is in the normal range for some specific time range. The optimization problem is solved using dynamic programming. The result shows that dynamic programming is quite reliable to represent the interaction between glucose and insulin levels in diabetes mellitus patient.

Dynamic determination of kinetic parameters and computer simulation of growth of Clostridium perfringens in cooked beef

USDA-ARS?s Scientific Manuscript database

The objective of this research was to develop a new one-step methodology that uses a dynamic approach to directly construct a tertiary model for prediction of the growth of C. perfringens in cooked beef. This methodology was based on numerical analysis and optimization of both primary and secondary...

Kinetics of Cation and Oxyanion Adsorption and Desorption on Ferrihydrite: Roles of Ferrihydrite Binding Sites and a Unified Model.

PubMed

Tian, Lei; Shi, Zhenqing; Lu, Yang; Dohnalkova, Alice C; Lin, Zhang; Dang, Zhi

2017-09-19

Quantitative understanding the kinetics of toxic ion reactions with various heterogeneous ferrihydrite binding sites is crucial for accurately predicting the dynamic behavior of contaminants in environment. In this study, kinetics of As(V), Cr(VI), Cu(II), and Pb(II) adsorption and desorption on ferrihydrite was studied using a stirred-flow method, which showed that metal adsorption/desorption kinetics was highly dependent on the reaction conditions and varied significantly among four metals. High resolution scanning transmission electron microscopy coupled with energy-dispersive X-ray spectroscopy showed that all four metals were distributed within the ferrihydrite aggregates homogeneously after adsorption reactions. Based on the equilibrium model CD-MUSIC, we developed a novel unified kinetics model applicable for both cation and oxyanion adsorption and desorption on ferrihydrite, which is able to account for the heterogeneity of ferrihydrite binding sites, different binding properties of cations and oxyanions, and variations of solution chemistry. The model described the kinetic results well. We quantitatively elucidated how the equilibrium properties of the cation and oxyanion binding to various ferrihydrite sites and the formation of various surface complexes controlled the adsorption and desorption kinetics at different reaction conditions and time scales. Our study provided a unified modeling method for the kinetics of ion adsorption/desorption on ferrihydrite.

Exact solutions for kinetic models of macromolecular dynamics.

PubMed

Chemla, Yann R; Moffitt, Jeffrey R; Bustamante, Carlos

2008-05-15

Dynamic biological processes such as enzyme catalysis, molecular motor translocation, and protein and nucleic acid conformational dynamics are inherently stochastic processes. However, when such processes are studied on a nonsynchronized ensemble, the inherent fluctuations are lost, and only the average rate of the process can be measured. With the recent development of methods of single-molecule manipulation and detection, it is now possible to follow the progress of an individual molecule, measuring not just the average rate but the fluctuations in this rate as well. These fluctuations can provide a great deal of detail about the underlying kinetic cycle that governs the dynamical behavior of the system. However, extracting this information from experiments requires the ability to calculate the general properties of arbitrarily complex theoretical kinetic schemes. We present here a general technique that determines the exact analytical solution for the mean velocity and for measures of the fluctuations. We adopt a formalism based on the master equation and show how the probability density for the position of a molecular motor at a given time can be solved exactly in Fourier-Laplace space. With this analytic solution, we can then calculate the mean velocity and fluctuation-related parameters, such as the randomness parameter (a dimensionless ratio of the diffusion constant and the velocity) and the dwell time distributions, which fully characterize the fluctuations of the system, both commonly used kinetic parameters in single-molecule measurements. Furthermore, we show that this formalism allows calculation of these parameters for a much wider class of general kinetic models than demonstrated with previous methods.

Model-independent plot of dynamic PET data facilitates data interpretation and model selection.

PubMed

Munk, Ole Lajord

2012-02-21

When testing new PET radiotracers or new applications of existing tracers, the blood-tissue exchange and the metabolism need to be examined. However, conventional plots of measured time-activity curves from dynamic PET do not reveal the inherent kinetic information. A novel model-independent volume-influx plot (vi-plot) was developed and validated. The new vi-plot shows the time course of the instantaneous distribution volume and the instantaneous influx rate. The vi-plot visualises physiological information that facilitates model selection and it reveals when a quasi-steady state is reached, which is a prerequisite for the use of the graphical analyses by Logan and Gjedde-Patlak. Both axes of the vi-plot have direct physiological interpretation, and the plot shows kinetic parameter in close agreement with estimates obtained by non-linear kinetic modelling. The vi-plot is equally useful for analyses of PET data based on a plasma input function or a reference region input function. The vi-plot is a model-independent and informative plot for data exploration that facilitates the selection of an appropriate method for data analysis. Copyright © 2011 Elsevier Ltd. All rights reserved.

[Mass Transfer Kinetics Model of Ultrasonic Extraction of Pomegranate Peel Polyphenols].

PubMed

Wang, Zhan-yi; Zhang, Li-hua; Wang, Yu-hai; Zhang, Yuan-hu; Ma, Li; Zheng, Dan-dan

2015-05-01

The dynamic mathematical model of ultrasonic extraction of polyphenols from pomegranate peel was constructed with the Fick's second law as the theoretical basis. The spherical model was selected, with mass concentrations of pomegranate peel polyphenols as the index, 50% ethanol as the extraction solvent and ultrasonic extraction as the extraction method. In different test conditions including the liquid ratio, extraction temperature and extraction time, a series of kinetic parameters were solved, such as the extraction process (k), relative raffinate rate, surface diffusion coefficient(D(S)), half life (t½) and the apparent activation energy (E(a)). With the extraction temperature increasing, k and D(S) were gradually increased with t½ decreasing,which indicated that the elevated temperature was favorable to the extraction of pomegranate peel polyphenols. The exponential equation of relative raffinate rate showed that the established numerical dynamics model fitted the extraction of pomegranate peel polyphenols, and the relationship between the reaction conditions and pomegranate peel polyphenols concentration was well reflected by the model. Based on the experimental results, a feasible and reliable kinetic model for ultrasonic extraction of polyphenols from pomegranate peel is established, which can be used for the optimization control of engineering magnifying production.

Microkinetic modeling of the autoxidative curing of an alkyd and oil-based paint model system

NASA Astrophysics Data System (ADS)

Oakley, Lindsay H.; Casadio, Francesca; Shull, Kenneth R.; Broadbelt, Linda J.

2015-11-01

Elucidating the curing and aging mechanisms of alkyd and other oil-based paints is valuable for the fields of conservation and bio-based coatings. Recent research has demonstrated the limitations of artificial aging in predicting the actual properties of paints that are hundreds of years old. Kinetic modeling offers pathways to develop a realistic and dynamic description of the composition of these oil-based paint coatings and facilitates the exploration of the effects of various environmental conditions on their long-term chemical stability. This work presents the construction of a kinetic Monte Carlo framework from elementary steps for the cobalt-catalyzed autoxidative curing of an ethyl linoleate model system up to the formation of single cross-links. Kinetic correlations for reaction families of similar chemistry are employed to reduce the number of parameters required to calculate rate constants in Arrhenius form. The model, developed from mechanisms proposed in the literature, shows good agreement with experiment for the formation of primary products in the early stages of curing. The model has also revealed that the mechanisms proposed in the literature for the formation of secondary products, such as volatile aldehydes, are still not well established, and alternative routes are under evaluation.

Functional Enzyme-Based Approach for Linking Microbial Community Functions with Biogeochemical Process Kinetics

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

Li, Minjing; Qian, Wei-jun; Gao, Yuqian

The kinetics of biogeochemical processes in natural and engineered environmental systems are typically described using Monod-type or modified Monod-type models. These models rely on biomass as surrogates for functional enzymes in microbial community that catalyze biogeochemical reactions. A major challenge to apply such models is the difficulty to quantitatively measure functional biomass for constraining and validating the models. On the other hand, omics-based approaches have been increasingly used to characterize microbial community structure, functions, and metabolites. Here we proposed an enzyme-based model that can incorporate omics-data to link microbial community functions with biogeochemical process kinetics. The model treats enzymes asmore » time-variable catalysts for biogeochemical reactions and applies biogeochemical reaction network to incorporate intermediate metabolites. The sequences of genes and proteins from metagenomes, as well as those from the UniProt database, were used for targeted enzyme quantification and to provide insights into the dynamic linkage among functional genes, enzymes, and metabolites that are necessary to be incorporated in the model. The application of the model was demonstrated using denitrification as an example by comparing model-simulated with measured functional enzymes, genes, denitrification substrates and intermediates« less

An evaluation of Computational Fluid dynamics model for flood risk analysis

NASA Astrophysics Data System (ADS)

Di Francesco, Silvia; Biscarini, Chiara; Montesarchio, Valeria

2014-05-01

This work presents an analysis of the hydrological-hydraulic engineering requisites for Risk evaluation and efficient flood damage reduction plans. Most of the research efforts have been dedicated to the scientific and technical aspects of risk assessment, providing estimates of possible alternatives and of the risk associated. In the decision making process for mitigation plan, the contribute of scientist is crucial, due to the fact that Risk-Damage analysis is based on evaluation of flow field ,of Hydraulic Risk and on economical and societal considerations. The present paper will focus on the first part of process, the mathematical modelling of flood events which is the base for all further considerations. The evaluation of potential catastrophic damage consequent to a flood event and in particular to dam failure requires modelling of the flood with sufficient detail so to capture the spatial and temporal evolutions of the event, as well of the velocity field. Thus, the selection of an appropriate mathematical model to correctly simulate flood routing is an essential step. In this work we present the application of two 3D Computational fluid dynamics models to a synthetic and real case study in order to evaluate the correct evolution of flow field and the associated flood Risk . The first model is based on a opensource CFD platform called openFoam. Water flow is schematized with a classical continuum approach based on Navier-Stokes equation coupled with Volume of fluid (VOF) method to take in account the multiphase character of river bottom-water- air systems. The second model instead is based on the Lattice Boltzmann method, an innovative numerical fluid dynamics scheme based on Boltzmann's kinetic equation that represents the flow dynamics at the macroscopic level by incorporating a microscopic kinetic approach. Fluid is seen as composed by particles that can move and collide among them. Simulation results from both models are promising and congruent to experimental results available in literature, thought the LBM model requires less computational effort respect to the NS one.

A mixed fluid-kinetic solver for the Vlasov-Poisson equations

NASA Astrophysics Data System (ADS)

Cheng, Yongtao

Plasmas are ionized gases that appear in a wide range of applications including astrophysics and space physics, as well as in laboratory settings such as in magnetically confined fusion. There are two prevailing types of modeling strategies to describe a plasma system: kinetic models and fluid models. Kinetic models evolve particle probability density distributions (PDFs) in phase space, which are accurate but computationally expensive. Fluid models evolve a small number of moments of the distribution function and reduce the dimension of the solution. However, some approximation is necessary to close the system, and finding an accurate moment closure that correctly captures the dynamics away from thermodynamic equilibrium is a difficult and still open problem. The main contributions of the present work can be divided into two main parts: (1) a new class of moment closures, based on a modification of existing quadrature-based moment-closure methods, is developed using bi-B-spline and bi-bubble representations; and (2) a novel mixed solver that combines a fluid and a kinetic solver is proposed, which uses the new class of moment-closure methods described in the first part. For the newly developed quadrature-based moment-closure based on bi-B-spline and bi-bubble representation, the explicit form of flux terms and the moment-realizability conditions are given. It is shown that while the bi-delta system is weakly hyperbolic, the newly proposed fluid models are strongly hyperbolic. Using a high-order Runge-Kutta discontinuous Galerkin method together with Strang operator splitting, the resulting models are applied to the Vlasov-Poisson-Fokker-Planck system in the high field limit. In the second part of this work, results from kinetic solver are used to provide a corrected closure to the fluid model. This correction keeps the fluid model hyperbolic and gives fluid results that match the moments as computed from the kinetic solution. Furthermore, a prolongation operation based on the bi-bubble moment-closure is used to make the first few moments of the kinetic and fluid solvers match. This results in a kinetic solver that exactly conserves mass and total energy. This mixed fluid-kinetic solver is applied to standard test problems for the Vlasov-Poisson system, including two-stream-instability problem and Landau damping.

Spatial Stochastic Intracellular Kinetics: A Review of Modelling Approaches.

PubMed

Smith, Stephen; Grima, Ramon

2018-05-21

Models of chemical kinetics that incorporate both stochasticity and diffusion are an increasingly common tool for studying biology. The variety of competing models is vast, but two stand out by virtue of their popularity: the reaction-diffusion master equation and Brownian dynamics. In this review, we critically address a number of open questions surrounding these models: How can they be justified physically? How do they relate to each other? How do they fit into the wider landscape of chemical models, ranging from the rate equations to molecular dynamics? This review assumes no prior knowledge of modelling chemical kinetics and should be accessible to a wide range of readers.

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

Chen, Hang, E-mail: hangchen@mit.edu; Thill, Peter; Cao, Jianshu

In biochemical systems, intrinsic noise may drive the system switch from one stable state to another. We investigate how kinetic switching between stable states in a bistable network is influenced by dynamic disorder, i.e., fluctuations in the rate coefficients. Using the geometric minimum action method, we first investigate the optimal transition paths and the corresponding minimum actions based on a genetic toggle switch model in which reaction coefficients draw from a discrete probability distribution. For the continuous probability distribution of the rate coefficient, we then consider two models of dynamic disorder in which reaction coefficients undergo different stochastic processes withmore » the same stationary distribution. In one, the kinetic parameters follow a discrete Markov process and in the other they follow continuous Langevin dynamics. We find that regulation of the parameters modulating the dynamic disorder, as has been demonstrated to occur through allosteric control in bistable networks in the immune system, can be crucial in shaping the statistics of optimal transition paths, transition probabilities, and the stationary probability distribution of the network.« less

Direct Estimation of Kinetic Parametric Images for Dynamic PET

PubMed Central

Wang, Guobao; Qi, Jinyi

2013-01-01

Dynamic positron emission tomography (PET) can monitor spatiotemporal distribution of radiotracer in vivo. The spatiotemporal information can be used to estimate parametric images of radiotracer kinetics that are of physiological and biochemical interests. Direct estimation of parametric images from raw projection data allows accurate noise modeling and has been shown to offer better image quality than conventional indirect methods, which reconstruct a sequence of PET images first and then perform tracer kinetic modeling pixel-by-pixel. Direct reconstruction of parametric images has gained increasing interests with the advances in computing hardware. Many direct reconstruction algorithms have been developed for different kinetic models. In this paper we review the recent progress in the development of direct reconstruction algorithms for parametric image estimation. Algorithms for linear and nonlinear kinetic models are described and their properties are discussed. PMID:24396500

Modified kinetic-hydraulic UASB reactor model for treatment of wastewater containing biodegradable organic substrates.

PubMed

El-Seddik, Mostafa M; Galal, Mona M; Radwan, A G; Abdel-Halim, Hisham S

2016-01-01

This paper addresses a modified kinetic-hydraulic model for up-flow anaerobic sludge blanket (UASB) reactor aimed to treat wastewater of biodegradable organic substrates as acetic acid based on Van der Meer model incorporated with biological granules inclusion. This dynamic model illustrates the biomass kinetic reaction rate for both direct and indirect growth of microorganisms coupled with the amount of biogas produced by methanogenic bacteria in bed and blanket zones of reactor. Moreover, the pH value required for substrate degradation at the peak specific growth rate of bacteria is discussed for Andrews' kinetics. The sensitivity analyses of biomass concentration with respect to fraction of volume of reactor occupied by granules and up-flow velocity are also demonstrated. Furthermore, the modified mass balance equations of reactor are applied during steady state using Newton Raphson technique to obtain a suitable degree of freedom for the modified model matching with the measured results of UASB Sanhour wastewater treatment plant in Fayoum, Egypt.

From in vitro to in vivo: Integration of the virtual cell based assay with physiologically based kinetic modelling.

PubMed

Paini, Alicia; Sala Benito, Jose Vicente; Bessems, Jos; Worth, Andrew P

2017-12-01

Physiologically based kinetic (PBK) models and the virtual cell based assay can be linked to form so called physiologically based dynamic (PBD) models. This study illustrates the development and application of a PBK model for prediction of estragole-induced DNA adduct formation and hepatotoxicity in humans. To address the hepatotoxicity, HepaRG cells were used as a surrogate for liver cells, with cell viability being used as the in vitro toxicological endpoint. Information on DNA adduct formation was taken from the literature. Since estragole induced cell damage is not directly caused by the parent compound, but by a reactive metabolite, information on the metabolic pathway was incorporated into the model. In addition, a user-friendly tool was developed by implementing the PBK/D model into a KNIME workflow. This workflow can be used to perform in vitro to in vivo extrapolation and forward as backward dosimetry in support of chemical risk assessment. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Direct dynamic kinetic analysis and computer simulation of growth of Clostridium perfringens in cooked turkey during cooling

USDA-ARS?s Scientific Manuscript database

This research applied a new one-step methodology to directly construct a tertiary model for describing the growth of C. perfringens in cooked turkey meat under dynamically cooling conditions. The kinetic parameters of the growth models were determined by numerical analysis and optimization using mu...

Dynamic contact angle of water-based titanium oxide nanofluid

PubMed Central

2013-01-01

This paper presents an investigation into spreading dynamics and dynamic contact angle of TiO2-deionized water nanofluids. Two mechanisms of energy dissipation, (1) contact line friction and (2) wedge film viscosity, govern the dynamics of contact line motion. The primary stage of spreading has the contact line friction as the dominant dissipative mechanism. At the secondary stage of spreading, the wedge film viscosity is the dominant dissipative mechanism. A theoretical model based on combination of molecular kinetic theory and hydrodynamic theory which incorporates non-Newtonian viscosity of solutions is used. The model agreement with experimental data is reasonable. Complex interparticle interactions, local pinning of the contact line, and variations in solid–liquid interfacial tension are attributed to errors. PMID:23759071

Investigation of nucleation kinetics in H2SO4 vapor through modeling of gas phase kinetics coupled with particle dynamics

NASA Astrophysics Data System (ADS)

Carlsson, Philip T. M.; Zeuch, Thomas

2018-03-01

We have developed a new model utilizing our existing kinetic gas phase models to simulate experimental particle size distributions emerging in dry supersaturated H2SO4 vapor homogeneously produced by rapid oxidation of SO2 through stabilized Criegee-Intermediates from 2-butene ozonolysis. We use a sectional method for simulating the particle dynamics. The particle treatment in the model is based on first principles and takes into account the transition from the kinetic to the diffusion-limited regime. It captures the temporal evolution of size distributions at the end of the ozonolysis experiment well, noting a slight underrepresentation of coagulation effects for larger particle sizes. The model correctly predicts the shape and the modes of the experimentally observed particle size distributions. The predicted modes show an extremely high sensitivity to the H2SO4 evaporation rates of the initially formed H2SO4 clusters (dimer to pentamer), which were arbitrarily restricted to decrease exponentially with increasing cluster size. In future, the analysis presented in this work can be extended to allow a direct validation of quantum chemically predicted stabilities of small H2SO4 clusters, which are believed to initiate a significant fraction of atmospheric new particle formation events. We discuss the prospects and possible limitations of the here presented approach.

Global fully kinetic models of planetary magnetospheres with iPic3D

NASA Astrophysics Data System (ADS)

Gonzalez, D.; Sanna, L.; Amaya, J.; Zitz, A.; Lembege, B.; Markidis, S.; Schriver, D.; Walker, R. J.; Berchem, J.; Peng, I. B.; Travnicek, P. M.; Lapenta, G.

2016-12-01

We report on the latest developments of our approach to model planetary magnetospheres, mini magnetospheres and the Earth's magnetosphere with the fully kinetic, electromagnetic particle in cell code iPic3D. The code treats electrons and multiple species of ions as full kinetic particles. We review: 1) Why a fully kinetic model and in particular why kinetic electrons are needed for capturing some of the most important aspects of the physics processes of planetary magnetospheres. 2) Why the energy conserving implicit method (ECIM) in its newest implementation [1] is the right approach to reach this goal. We consider the different electron scales and study how the new IECIM can be tuned to resolve only the electron scales of interest while averaging over the unresolved scales preserving their contribution to the evolution. 3) How with modern computing planetary magnetospheres, mini magnetosphere and eventually Earth's magnetosphere can be modeled with fully kinetic electrons. The path from petascale to exascale for iPiC3D is outlined based on the DEEP-ER project [2], using dynamic allocation of different processor architectures (Xeon and Xeon Phi) and innovative I/O technologies.Specifically results from models of Mercury are presented and compared with MESSENGER observations and with previous hybrid (fluid electrons and kinetic ions) simulations. The plasma convection around the planets includes the development of hydrodynamic instabilities at the flanks, the presence of the collisionless shocks, the magnetosheath, the magnetopause, reconnection zones, the formation of the plasma sheet and the magnetotail, and the variation of ion/electron plasma flows when crossing these frontiers. Given the full kinetic nature of our approach we focus on detailed particle dynamics and distribution at locations that can be used for comparison with satellite data. [1] Lapenta, G. (2016). Exactly Energy Conserving Implicit Moment Particle in Cell Formulation. arXiv preprint arXiv:1602.06326.[2] www.deep-er.eu

Model free approach to kinetic analysis of real-time hyperpolarized 13C magnetic resonance spectroscopy data.

PubMed

Hill, Deborah K; Orton, Matthew R; Mariotti, Erika; Boult, Jessica K R; Panek, Rafal; Jafar, Maysam; Parkes, Harold G; Jamin, Yann; Miniotis, Maria Falck; Al-Saffar, Nada M S; Beloueche-Babari, Mounia; Robinson, Simon P; Leach, Martin O; Chung, Yuen-Li; Eykyn, Thomas R

2013-01-01

Real-time detection of the rates of metabolic flux, or exchange rates of endogenous enzymatic reactions, is now feasible in biological systems using Dynamic Nuclear Polarization Magnetic Resonance. Derivation of reaction rate kinetics from this technique typically requires multi-compartmental modeling of dynamic data, and results are therefore model-dependent and prone to misinterpretation. We present a model-free formulism based on the ratio of total areas under the curve (AUC) of the injected and product metabolite, for example pyruvate and lactate. A theoretical framework to support this novel analysis approach is described, and demonstrates that the AUC ratio is proportional to the forward rate constant k. We show that the model-free approach strongly correlates with k for whole cell in vitro experiments across a range of cancer cell lines, and detects response in cells treated with the pan-class I PI3K inhibitor GDC-0941 with comparable or greater sensitivity. The same result is seen in vivo with tumor xenograft-bearing mice, in control tumors and following drug treatment with dichloroacetate. An important finding is that the area under the curve is independent of both the input function and of any other metabolic pathways arising from the injected metabolite. This model-free approach provides a robust and clinically relevant alternative to kinetic model-based rate measurements in the clinical translation of hyperpolarized (13)C metabolic imaging in humans, where measurement of the input function can be problematic.

Model Free Approach to Kinetic Analysis of Real-Time Hyperpolarized 13C Magnetic Resonance Spectroscopy Data

PubMed Central

Mariotti, Erika; Boult, Jessica K. R.; Panek, Rafal; Jafar, Maysam; Parkes, Harold G.; Jamin, Yann; Miniotis, Maria Falck; Al-Saffar, Nada M. S.; Beloueche-Babari, Mounia; Robinson, Simon P.; Leach, Martin O.; Chung, Yuen-Li; Eykyn, Thomas R.

2013-01-01

Real-time detection of the rates of metabolic flux, or exchange rates of endogenous enzymatic reactions, is now feasible in biological systems using Dynamic Nuclear Polarization Magnetic Resonance. Derivation of reaction rate kinetics from this technique typically requires multi-compartmental modeling of dynamic data, and results are therefore model-dependent and prone to misinterpretation. We present a model-free formulism based on the ratio of total areas under the curve (AUC) of the injected and product metabolite, for example pyruvate and lactate. A theoretical framework to support this novel analysis approach is described, and demonstrates that the AUC ratio is proportional to the forward rate constant k. We show that the model-free approach strongly correlates with k for whole cell in vitro experiments across a range of cancer cell lines, and detects response in cells treated with the pan-class I PI3K inhibitor GDC-0941 with comparable or greater sensitivity. The same result is seen in vivo with tumor xenograft-bearing mice, in control tumors and following drug treatment with dichloroacetate. An important finding is that the area under the curve is independent of both the input function and of any other metabolic pathways arising from the injected metabolite. This model-free approach provides a robust and clinically relevant alternative to kinetic model-based rate measurements in the clinical translation of hyperpolarized 13C metabolic imaging in humans, where measurement of the input function can be problematic. PMID:24023724

Design Principles of DNA Enzyme-Based Walkers: Translocation Kinetics and Photoregulation.

PubMed

Cha, Tae-Gon; Pan, Jing; Chen, Haorong; Robinson, Heather N; Li, Xiang; Mao, Chengde; Choi, Jong Hyun

2015-07-29

Dynamic DNA enzyme-based walkers complete their stepwise movements along the prescribed track through a series of reactions, including hybridization, enzymatic cleavage, and strand displacement; however, their overall translocation kinetics is not well understood. Here, we perform mechanistic studies to elucidate several key parameters that govern the kinetics and processivity of DNA enzyme-based walkers. These parameters include DNA enzyme core type and structure, upper and lower recognition arm lengths, and divalent metal cation species and concentration. A theoretical model is developed within the framework of single-molecule kinetics to describe overall translocation kinetics as well as each reaction step. A better understanding of kinetics and design parameters enables us to demonstrate a walker movement near 5 μm at an average speed of ∼1 nm s(-1). We also show that the translocation kinetics of DNA walkers can be effectively controlled by external light stimuli using photoisomerizable azobenzene moieties. A 2-fold increase in the cleavage reaction is observed when the hairpin stems of enzyme catalytic cores are open under UV irradiation. This study provides general design guidelines to construct highly processive, autonomous DNA walker systems and to regulate their translocation kinetics, which would facilitate the development of functional DNA walkers.

The kinetics of polyurethane structural foam formation: Foaming and polymerization

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

Rao, Rekha R.; Mondy, Lisa A.; Long, Kevin N.

We are developing kinetic models to understand the manufacturing of polymeric foams, which evolve from low viscosity Newtonian liquids, to bubbly liquids, finally producing solid foam. Closed-form kinetics are formulated and parameterized for PMDI-10, a fast curing polyurethane, including polymerization and foaming. PMDI- 10 is chemically blown, where water and isocyanate react to form carbon dioxide. The isocyanate reacts with polyol in a competing reaction, producing polymer. Our approach is unique, though it builds on our previous work and the polymerization literature. This kinetic model follows a simplified mathematical formalism that decouples foaming and curing, including an evolving glass transitionmore » temperature to represent vitrification. This approach is based on IR, DSC, and volume evolution data, where we observed that the isocyanate is always in excess and does not affect the kinetics. Finally, the kinetics are suitable for implementation into a computational fluid dynamics framework, which will be explored in subsequent papers.« less

The kinetics of polyurethane structural foam formation: Foaming and polymerization

DOE PAGES

Rao, Rekha R.; Mondy, Lisa A.; Long, Kevin N.; ...

2017-02-15

We are developing kinetic models to understand the manufacturing of polymeric foams, which evolve from low viscosity Newtonian liquids, to bubbly liquids, finally producing solid foam. Closed-form kinetics are formulated and parameterized for PMDI-10, a fast curing polyurethane, including polymerization and foaming. PMDI- 10 is chemically blown, where water and isocyanate react to form carbon dioxide. The isocyanate reacts with polyol in a competing reaction, producing polymer. Our approach is unique, though it builds on our previous work and the polymerization literature. This kinetic model follows a simplified mathematical formalism that decouples foaming and curing, including an evolving glass transitionmore » temperature to represent vitrification. This approach is based on IR, DSC, and volume evolution data, where we observed that the isocyanate is always in excess and does not affect the kinetics. Finally, the kinetics are suitable for implementation into a computational fluid dynamics framework, which will be explored in subsequent papers.« less

A paradigm for modeling and computation of gas dynamics

NASA Astrophysics Data System (ADS)

Xu, Kun; Liu, Chang

2017-02-01

In the continuum flow regime, the Navier-Stokes (NS) equations are usually used for the description of gas dynamics. On the other hand, the Boltzmann equation is applied for the rarefied flow. These two equations are based on distinguishable modeling scales for flow physics. Fortunately, due to the scale separation, i.e., the hydrodynamic and kinetic ones, both the Navier-Stokes equations and the Boltzmann equation are applicable in their respective domains. However, in real science and engineering applications, they may not have such a distinctive scale separation. For example, around a hypersonic flying vehicle, the flow physics at different regions may correspond to different regimes, where the local Knudsen number can be changed significantly in several orders of magnitude. With a variation of flow physics, theoretically a continuous governing equation from the kinetic Boltzmann modeling to the hydrodynamic Navier-Stokes dynamics should be used for its efficient description. However, due to the difficulties of a direct modeling of flow physics in the scale between the kinetic and hydrodynamic ones, there is basically no reliable theory or valid governing equations to cover the whole transition regime, except resolving flow physics always down to the mean free path scale, such as the direct Boltzmann solver and the Direct Simulation Monte Carlo (DSMC) method. In fact, it is an unresolved problem about the exact scale for the validity of the NS equations, especially in the small Reynolds number cases. The computational fluid dynamics (CFD) is usually based on the numerical solution of partial differential equations (PDEs), and it targets on the recovering of the exact solution of the PDEs as mesh size and time step converging to zero. This methodology can be hardly applied to solve the multiple scale problem efficiently because there is no such a complete PDE for flow physics through a continuous variation of scales. For the non-equilibrium flow study, the direct modeling methods, such as DSMC, particle in cell, and smooth particle hydrodynamics, play a dominant role to incorporate the flow physics into the algorithm construction directly. It is fully legitimate to combine the modeling and computation together without going through the process of constructing PDEs. In other words, the CFD research is not only to obtain the numerical solution of governing equations but to model flow dynamics as well. This methodology leads to the unified gas-kinetic scheme (UGKS) for flow simulation in all flow regimes. Based on UGKS, the boundary for the validation of the Navier-Stokes equations can be quantitatively evaluated. The combination of modeling and computation provides a paradigm for the description of multiscale transport process.

Dynamic biological exposure indexes for n-hexane and 2,5-hexanedione, suggested by a physiologically based pharmacokinetic model

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

Perbellini, L.; Mozzo, P.; Olivato, D.

Biological exposure index (BEI) of n-hexane was studied for accuracy using a physiologically based pharmacokinetic (PB-PK) model. The kinetics of n-hexane in alveolar air, blood, urine, and other tissues were simulated for different values of alveolar ventilations and also for constant and variable exposures. The kinetics of 2,5-hexanedione, the toxic n-hexane metabolite, were also simulated. The ranges of n-hexane concentrations in biological media and the urinary concentrations of 2,5-hexanedione are discussed in connection with a mean n-hexane exposure of 180 mg/m3 (50 ppm) (threshold limit value (TLV) suggested by American Conference of Governmental Industrial Hygienists (ACGIH) for 1988-89). The experimentalmore » and field data as well as those predicted by simulation with the PB-PK model were comparable. The physiological-pharmacokinetic simulations are used to propose the dynamic BEIs of n-hexane and 2,5-hexanedione. The use of simulation with PB-PK models enables a better understanding of the limits, advantages, and issues associated with biological monitoring of exposures to industrial solvents.« less

Observations & modeling of solar-wind/magnetospheric interactions

NASA Astrophysics Data System (ADS)

Hoilijoki, Sanni; Von Alfthan, Sebastian; Pfau-Kempf, Yann; Palmroth, Minna; Ganse, Urs

2016-07-01

The majority of the global magnetospheric dynamics is driven by magnetic reconnection, indicating the need to understand and predict reconnection processes and their global consequences. So far, global magnetospheric dynamics has been simulated using mainly magnetohydrodynamic (MHD) models, which are approximate but fast enough to be executed in real time or near-real time. Due to their fast computation times, MHD models are currently the only possible frameworks for space weather predictions. However, in MHD models reconnection is not treated kinetically. In this presentation we will compare the results from global kinetic (hybrid-Vlasov) and global MHD simulations. Both simulations are compared with in-situ measurements. We will show that the kinetic processes at the bow shock, in the magnetosheath and at the magnetopause affect global dynamics even during steady solar wind conditions. Foreshock processes cause an asymmetry in the magnetosheath plasma, indicating that the plasma entering the magnetosphere is not symmetrical on different sides of the magnetosphere. Behind the bow shock in the magnetosheath kinetic wave modes appear. Some of these waves propagate to the magnetopause and have an effect on the magnetopause reconnection. Therefore we find that kinetic phenomena have a significant role in the interaction between the solar wind and the magnetosphere. While kinetic models cannot be executed in real time currently, they could be used to extract heuristics to be added in the faster MHD models.

Effects of Different PER Translational Kinetics on the Dynamics of a Core Circadian Clock Model

PubMed Central

Nieto, Paula S.; Revelli, Jorge A.; Garbarino-Pico, Eduardo; Condat, Carlos A.; Guido, Mario E.; Tamarit, Francisco A.

2015-01-01

Living beings display self-sustained daily rhythms in multiple biological processes, which persist in the absence of external cues since they are generated by endogenous circadian clocks. The period (per) gene is a central player within the core molecular mechanism for keeping circadian time in most animals. Recently, the modulation PER translation has been reported, both in mammals and flies, suggesting that translational regulation of clock components is important for the proper clock gene expression and molecular clock performance. Because translational regulation ultimately implies changes in the kinetics of translation and, therefore, in the circadian clock dynamics, we sought to study how and to what extent the molecular clock dynamics is affected by the kinetics of PER translation. With this objective, we used a minimal mathematical model of the molecular circadian clock to qualitatively characterize the dynamical changes derived from kinetically different PER translational mechanisms. We found that the emergence of self-sustained oscillations with characteristic period, amplitude, and phase lag (time delays) between per mRNA and protein expression depends on the kinetic parameters related to PER translation. Interestingly, under certain conditions, a PER translation mechanism with saturable kinetics introduces longer time delays than a mechanism ruled by a first-order kinetics. In addition, the kinetic laws of PER translation significantly changed the sensitivity of our model to parameters related to the synthesis and degradation of per mRNA and PER degradation. Lastly, we found a set of parameters, with realistic values, for which our model reproduces some experimental results reported recently for Drosophila melanogaster and we present some predictions derived from our analysis. PMID:25607544

Effects of different per translational kinetics on the dynamics of a core circadian clock model.

PubMed

Nieto, Paula S; Revelli, Jorge A; Garbarino-Pico, Eduardo; Condat, Carlos A; Guido, Mario E; Tamarit, Francisco A

2015-01-01

Living beings display self-sustained daily rhythms in multiple biological processes, which persist in the absence of external cues since they are generated by endogenous circadian clocks. The period (per) gene is a central player within the core molecular mechanism for keeping circadian time in most animals. Recently, the modulation PER translation has been reported, both in mammals and flies, suggesting that translational regulation of clock components is important for the proper clock gene expression and molecular clock performance. Because translational regulation ultimately implies changes in the kinetics of translation and, therefore, in the circadian clock dynamics, we sought to study how and to what extent the molecular clock dynamics is affected by the kinetics of PER translation. With this objective, we used a minimal mathematical model of the molecular circadian clock to qualitatively characterize the dynamical changes derived from kinetically different PER translational mechanisms. We found that the emergence of self-sustained oscillations with characteristic period, amplitude, and phase lag (time delays) between per mRNA and protein expression depends on the kinetic parameters related to PER translation. Interestingly, under certain conditions, a PER translation mechanism with saturable kinetics introduces longer time delays than a mechanism ruled by a first-order kinetics. In addition, the kinetic laws of PER translation significantly changed the sensitivity of our model to parameters related to the synthesis and degradation of per mRNA and PER degradation. Lastly, we found a set of parameters, with realistic values, for which our model reproduces some experimental results reported recently for Drosophila melanogaster and we present some predictions derived from our analysis.

An new MHD/kinetic model for exploring energetic particle production in macro-scale systems

NASA Astrophysics Data System (ADS)

Drake, J. F.; Swisdak, M.; Dahlin, J. T.

2017-12-01

A novel MHD/kinetic model is being developed to explore magneticreconnection and particle energization in macro-scale systems such asthe solar corona and the outer heliosphere. The model blends the MHDdescription with a macro-particle description. The rationale for thismodel is based on the recent discovery that energetic particleproduction during magnetic reconnection is controlled by Fermireflection and Betatron acceleration and not parallel electricfields. Since the former mechanisms are not dependent on kineticscales such as the Debye length and the electron and ion inertialscales, a model that sheds these scales is sufficient for describingparticle acceleration in macro-systems. Our MHD/kinetic model includesmacroparticles laid out on an MHD grid that are evolved with the MHDfields. Crucially, the feedback of the energetic component on the MHDfluid is included in the dynamics. Thus, energy of the total system,the MHD fluid plus the energetic component, is conserved. The systemhas no kinetic scales and therefore can be implemented to modelenergetic particle production in macro-systems with none of theconstraints associated with a PIC model. Tests of the new model insimple geometries will be presented and potential applications will bediscussed.

Dynamic metabolic modeling for a MAB bioprocess.

PubMed

Gao, Jianying; Gorenflo, Volker M; Scharer, Jeno M; Budman, Hector M

2007-01-01

Production of monoclonal antibodies (MAb) for diagnostic or therapeutic applications has become an important task in the pharmaceutical industry. The efficiency of high-density reactor systems can be potentially increased by model-based design and control strategies. Therefore, a reliable kinetic model for cell metabolism is required. A systematic procedure based on metabolic modeling is used to model nutrient uptake and key product formation in a MAb bioprocess during both the growth and post-growth phases. The approach combines the key advantages of stoichiometric and kinetic models into a complete metabolic network while integrating the regulation and control of cellular activity. This modeling procedure can be easily applied to any cell line during both the cell growth and post-growth phases. Quadratic programming (QP) has been identified as a suitable method to solve the underdetermined constrained problem related to model parameter identification. The approach is illustrated for the case of murine hybridoma cells cultivated in stirred spinners.

Modeling of adsorption dynamics at air-liquid interfaces using statistical rate theory (SRT).

PubMed

Biswas, M E; Chatzis, I; Ioannidis, M A; Chen, P

2005-06-01

A large number of natural and technological processes involve mass transfer at interfaces. Interfacial properties, e.g., adsorption, play a key role in such applications as wetting, foaming, coating, and stabilizing of liquid films. The mechanistic understanding of surface adsorption often assumes molecular diffusion in the bulk liquid and subsequent adsorption at the interface. Diffusion is well described by Fick's law, while adsorption kinetics is less understood and is commonly described using Langmuir-type empirical equations. In this study, a general theoretical model for adsorption kinetics/dynamics at the air-liquid interface is developed; in particular, a new kinetic equation based on the statistical rate theory (SRT) is derived. Similar to many reported kinetic equations, the new kinetic equation also involves a number of parameters, but all these parameters are theoretically obtainable. In the present model, the adsorption dynamics is governed by three dimensionless numbers: psi (ratio of adsorption thickness to diffusion length), lambda (ratio of square of the adsorption thickness to the ratio of adsorption to desorption rate constant), and Nk (ratio of the adsorption rate constant to the product of diffusion coefficient and bulk concentration). Numerical simulations for surface adsorption using the proposed model are carried out and verified. The difference in surface adsorption between the general and the diffusion controlled model is estimated and presented graphically as contours of deviation. Three different regions of adsorption dynamics are identified: diffusion controlled (deviation less than 10%), mixed diffusion and transfer controlled (deviation in the range of 10-90%), and transfer controlled (deviation more than 90%). These three different modes predominantly depend on the value of Nk. The corresponding ranges of Nk for the studied values of psi (10(-2)

Multijoint kinetic chain analysis of knee extension during the soccer instep kick.

PubMed

Naito, Kozo; Fukui, Yosuke; Maruyama, Takeo

2010-04-01

Although previous studies have shown that motion-dependent interactions between adjacent segments play an important role in producing knee extension during the soccer instep kick, detailed knowledge about the mechanisms underlying those interactions is lacking. The present study aimed to develop a 3-D dynamical model for the multijoint kinetic chain of the instep kick in order to quantify the contributions of the causal dynamical factors to the production of maximum angular velocity during knee extension. Nine collegiate soccer players volunteered to participate in the experiment and performed instep kicking movements while 3-D positional data and the ground reaction force were measured. A dynamical model was developed in the form of a linked system containing 8 segments and 18 joint rotations, and the knee extension/flexion motion was decomposed into causal factors related to muscular moment, gyroscopic moment, centrifugal force, Coriolis force, gravity, proximal endpoint linear acceleration, and external force-dependent terms. The rapid knee extension during instep kicking was found to result almost entirely from kicking leg centrifugal force, trunk rotation muscular moment, kicking leg Coriolis force, and trunk rotation gyroscopic-dependent components. Based on the finding that rapid knee extension during instep kicking stems from multiple dynamical factors, it is suggested that the multijoint kinetic chain analysis used in the present study is more useful for achieving a detailed understanding of the cause of rapid kicking leg movement than the previously used 2-D, two-segment kinetic chain model. The present results also indicated that the centrifugal effect due to the kicking hip flexion angular velocity contributed substantially to the generation of a rapid knee extension, suggesting that the adjustment between the kicking hip flexion angular velocity and the leg configuration (knee flexion angle) is more important for effective instep kicking than other joint kinematics.

Understanding the kinetics of ligand binding to globins with molecular dynamics simulations: the necessity of multiple state models.

PubMed

Estarellas Martin, Carolina; Seira Castan, Constantí; Luque Garriga, F Javier; Bidon-Chanal Badia, Axel

2015-10-01

Residue conformational changes and internal cavity migration processes play a key role in regulating the kinetics of ligand migration and binding events in globins. Molecular dynamics simulations have demonstrated their value in the study of these processes in different haemoglobins, but derivation of kinetic data demands the use of more complex techniques like enhanced sampling molecular dynamics methods. This review discusses the different methodologies that are currently applied to study the ligand migration process in globins and highlight those specially developed to derive kinetic data. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multi-scale modeling of irradiation effects in spallation neutron source materials

NASA Astrophysics Data System (ADS)

Yoshiie, T.; Ito, T.; Iwase, H.; Kaneko, Y.; Kawai, M.; Kishida, I.; Kunieda, S.; Sato, K.; Shimakawa, S.; Shimizu, F.; Hashimoto, S.; Hashimoto, N.; Fukahori, T.; Watanabe, Y.; Xu, Q.; Ishino, S.

2011-07-01

Changes in mechanical property of Ni under irradiation by 3 GeV protons were estimated by multi-scale modeling. The code consisted of four parts. The first part was based on the Particle and Heavy-Ion Transport code System (PHITS) code for nuclear reactions, and modeled the interactions between high energy protons and nuclei in the target. The second part covered atomic collisions by particles without nuclear reactions. Because the energy of the particles was high, subcascade analysis was employed. The direct formation of clusters and the number of mobile defects were estimated using molecular dynamics (MD) and kinetic Monte-Carlo (kMC) methods in each subcascade. The third part considered damage structural evolutions estimated by reaction kinetic analysis. The fourth part involved the estimation of mechanical property change using three-dimensional discrete dislocation dynamics (DDD). Using the above four part code, stress-strain curves for high energy proton irradiated Ni were obtained.

Simulations of moving effect of coastal vegetation on tsunami damping

NASA Astrophysics Data System (ADS)

Tsai, Ching-Piao; Chen, Ying-Chi; Octaviani Sihombing, Tri; Lin, Chang

2017-05-01

A coupled wave-vegetation simulation is presented for the moving effect of the coastal vegetation on tsunami wave height damping. The problem is idealized by solitary wave propagation on a group of emergent cylinders. The numerical model is based on general Reynolds-averaged Navier-Stokes equations with renormalization group turbulent closure model by using volume of fluid technique. The general moving object (GMO) model developed in computational fluid dynamics (CFD) code Flow-3D is applied to simulate the coupled motion of vegetation with wave dynamically. The damping of wave height and the turbulent kinetic energy along moving and stationary cylinders are discussed. The simulated results show that the damping of wave height and the turbulent kinetic energy by the moving cylinders are clearly less than by the stationary cylinders. The result implies that the wave decay by the coastal vegetation may be overestimated if the vegetation was represented as stationary state.

Mammalian cell culture process for monoclonal antibody production: nonlinear modelling and parameter estimation.

PubMed

Selişteanu, Dan; Șendrescu, Dorin; Georgeanu, Vlad; Roman, Monica

2015-01-01

Monoclonal antibodies (mAbs) are at present one of the fastest growing products of pharmaceutical industry, with widespread applications in biochemistry, biology, and medicine. The operation of mAbs production processes is predominantly based on empirical knowledge, the improvements being achieved by using trial-and-error experiments and precedent practices. The nonlinearity of these processes and the absence of suitable instrumentation require an enhanced modelling effort and modern kinetic parameter estimation strategies. The present work is dedicated to nonlinear dynamic modelling and parameter estimation for a mammalian cell culture process used for mAb production. By using a dynamical model of such kind of processes, an optimization-based technique for estimation of kinetic parameters in the model of mammalian cell culture process is developed. The estimation is achieved as a result of minimizing an error function by a particle swarm optimization (PSO) algorithm. The proposed estimation approach is analyzed in this work by using a particular model of mammalian cell culture, as a case study, but is generic for this class of bioprocesses. The presented case study shows that the proposed parameter estimation technique provides a more accurate simulation of the experimentally observed process behaviour than reported in previous studies.

Mammalian Cell Culture Process for Monoclonal Antibody Production: Nonlinear Modelling and Parameter Estimation

PubMed Central

Selişteanu, Dan; Șendrescu, Dorin; Georgeanu, Vlad

2015-01-01

Monoclonal antibodies (mAbs) are at present one of the fastest growing products of pharmaceutical industry, with widespread applications in biochemistry, biology, and medicine. The operation of mAbs production processes is predominantly based on empirical knowledge, the improvements being achieved by using trial-and-error experiments and precedent practices. The nonlinearity of these processes and the absence of suitable instrumentation require an enhanced modelling effort and modern kinetic parameter estimation strategies. The present work is dedicated to nonlinear dynamic modelling and parameter estimation for a mammalian cell culture process used for mAb production. By using a dynamical model of such kind of processes, an optimization-based technique for estimation of kinetic parameters in the model of mammalian cell culture process is developed. The estimation is achieved as a result of minimizing an error function by a particle swarm optimization (PSO) algorithm. The proposed estimation approach is analyzed in this work by using a particular model of mammalian cell culture, as a case study, but is generic for this class of bioprocesses. The presented case study shows that the proposed parameter estimation technique provides a more accurate simulation of the experimentally observed process behaviour than reported in previous studies. PMID:25685797

Nitrate denitrification with nitrite or nitrous oxide as intermediate products: Stoichiometry, kinetics and dynamics of stable isotope signatures.

PubMed

Vavilin, V A; Rytov, S V

2015-09-01

A kinetic analysis of nitrate denitrification by a single or two species of denitrifying bacteria with glucose or ethanol as a carbon source and nitrite or nitrous oxide as intermediate products was performed using experimental data published earlier (Menyailo and Hungate, 2006; Vidal-Gavilan et al., 2013). Modified Monod kinetics was used in the dynamic biological model. The special equations were added to the common dynamic biological model to describe how isotopic fractionation between N species changes. In contrast to the generally assumed first-order kinetics, in this paper, the traditional Rayleigh equation describing stable nitrogen and oxygen isotope fractionation in nitrate was derived from the dynamic isotopic equations for any type of kinetics. In accordance with the model, in Vidal-Gavilan's experiments, the maximum specific rate of nitrate reduction was proved to be less for ethanol compared to glucose. Conversely, the maximum specific rate of nitrite reduction was proved to be much less for glucose compared to ethanol. Thus, the intermediate nitrite concentration was negligible for the ethanol experiment, while it was significant for the glucose experiment. In Menyailo's and Hungate's experiments, the low value of maximum specific rate of nitrous oxide reduction gives high intermediate value of nitrous oxide concentration. The model showed that the dynamics of nitrogen and oxygen isotope signatures are responding to the biological dynamics. Two microbial species instead of single denitrifying bacteria are proved to be more adequate to describe the total process of nitrate denitrification to dinitrogen. Copyright © 2015 Elsevier Ltd. All rights reserved.

Predicting perturbation patterns from the topology of biological networks.

PubMed

Santolini, Marc; Barabási, Albert-László

2018-06-20

High-throughput technologies, offering an unprecedented wealth of quantitative data underlying the makeup of living systems, are changing biology. Notably, the systematic mapping of the relationships between biochemical entities has fueled the rapid development of network biology, offering a suitable framework to describe disease phenotypes and predict potential drug targets. However, our ability to develop accurate dynamical models remains limited, due in part to the limited knowledge of the kinetic parameters underlying these interactions. Here, we explore the degree to which we can make reasonably accurate predictions in the absence of the kinetic parameters. We find that simple dynamically agnostic models are sufficient to recover the strength and sign of the biochemical perturbation patterns observed in 87 biological models for which the underlying kinetics are known. Surprisingly, a simple distance-based model achieves 65% accuracy. We show that this predictive power is robust to topological and kinetic parameter perturbations, and we identify key network properties that can increase up to 80% the recovery rate of the true perturbation patterns. We validate our approach using experimental data on the chemotactic pathway in bacteria, finding that a network model of perturbation spreading predicts with ∼80% accuracy the directionality of gene expression and phenotype changes in knock-out and overproduction experiments. These findings show that the steady advances in mapping out the topology of biochemical interaction networks opens avenues for accurate perturbation spread modeling, with direct implications for medicine and drug development.

A dislocation-based crystal plasticity framework for dynamic ductile failure of single crystals

NASA Astrophysics Data System (ADS)

Nguyen, Thao; Luscher, D. J.; Wilkerson, J. W.

2017-11-01

A framework for dislocation-based viscoplasticity and dynamic ductile failure has been developed to model high strain rate deformation and damage in single crystals. The rate-dependence of the crystal plasticity formulation is based on the physics of relativistic dislocation kinetics suited for extremely high strain rates. The damage evolution is based on the dynamics of void growth, which are governed by both micro-inertia as well as dislocation kinetics and dislocation substructure evolution. An averaging scheme is proposed in order to approximate the evolution of the dislocation substructure in both the macroscale as well as its spatial distribution at the microscale. Additionally, a concept of a single equivalent dislocation density that effectively captures the collective influence of dislocation density on all active slip systems is proposed here. Together, these concepts and approximations enable the use of semi-analytic solutions for void growth dynamics developed in (Wilkerson and Ramesh, 2014), which greatly reduce the computational overhead that would otherwise be required. The resulting homogenized framework has been implemented into a commercially available finite element package, and a validation study against a suite of direct numerical simulations was carried out.

Predicting the F(ab)-mediated effect of monoclonal antibodies in vivo by combining cell-level kinetic and pharmacokinetic modelling.

PubMed

Krippendorff, Ben-Fillippo; Oyarzún, Diego A; Huisinga, Wilhelm

2012-04-01

Cell-level kinetic models for therapeutically relevant processes increasingly benefit the early stages of drug development. Later stages of the drug development processes, however, rely on pharmacokinetic compartment models while cell-level dynamics are typically neglected. We here present a systematic approach to integrate cell-level kinetic models and pharmacokinetic compartment models. Incorporating target dynamics into pharmacokinetic models is especially useful for the development of therapeutic antibodies because their effect and pharmacokinetics are inherently interdependent. The approach is illustrated by analysing the F(ab)-mediated inhibitory effect of therapeutic antibodies targeting the epidermal growth factor receptor. We build a multi-level model for anti-EGFR antibodies by combining a systems biology model with in vitro determined parameters and a pharmacokinetic model based on in vivo pharmacokinetic data. Using this model, we investigated in silico the impact of biochemical properties of anti-EGFR antibodies on their F(ab)-mediated inhibitory effect. The multi-level model suggests that the F(ab)-mediated inhibitory effect saturates with increasing drug-receptor affinity, thereby limiting the impact of increasing antibody affinity on improving the effect. This indicates that observed differences in the therapeutic effects of high affinity antibodies in the market and in clinical development may result mainly from Fc-mediated indirect mechanisms such as antibody-dependent cell cytotoxicity.

Direct parametric reconstruction in dynamic PET myocardial perfusion imaging: in vivo studies.

PubMed

Petibon, Yoann; Rakvongthai, Yothin; El Fakhri, Georges; Ouyang, Jinsong

2017-05-07

Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves-TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. The aim of this study was to extend and evaluate the performance of a direct parametric reconstruction method using in vivo dynamic PET MPI data for the purpose of quantifying MBF. Dynamic PET MPI studies were performed on two healthy pigs using a Siemens Biograph mMR scanner. List-mode PET data for each animal were acquired following a bolus injection of ~7-8 mCi of 18 F-flurpiridaz, a myocardial perfusion agent. Fully-3D dynamic PET sinograms were obtained by sorting the coincidence events into 16 temporal frames covering ~5 min after radiotracer administration. Additionally, eight independent noise realizations of both scans-each containing 1/8th of the total number of events-were generated from the original list-mode data. Dynamic sinograms were then used to compute parametric maps using the conventional indirect method and the proposed direct method. For both methods, a one-tissue compartment model accounting for spillover from the left and right ventricle blood-pools was used to describe the kinetics of 18 F-flurpiridaz. An image-derived arterial input function obtained from a TAC taken in the left ventricle cavity was used for tracer kinetic analysis. For the indirect method, frame-by-frame images were estimated using two fully-3D reconstruction techniques: the standard ordered subset expectation maximization (OSEM) reconstruction algorithm on one side, and the one-step late maximum a posteriori (OSL-MAP) algorithm on the other side, which incorporates a quadratic penalty function. The parametric images were then calculated using voxel-wise weighted least-square fitting of the reconstructed myocardial PET TACs. For the direct method, parametric images were estimated directly from the dynamic PET sinograms using a maximum a posteriori (MAP) parametric reconstruction algorithm which optimizes an objective function comprised of the Poisson log-likelihood term, the kinetic model and a quadratic penalty function. Maximization of the objective function with respect to each set of parameters was achieved using a preconditioned conjugate gradient algorithm with a specifically developed pre-conditioner. The performance of the direct method was evaluated by comparing voxel- and segment-wise estimates of [Formula: see text], the tracer transport rate (ml · min -1 · ml -1 ), to those obtained using the indirect method applied to both OSEM and OSL-MAP dynamic reconstructions. The proposed direct reconstruction method produced [Formula: see text] maps with visibly lower noise than the indirect method based on OSEM and OSL-MAP reconstructions. At normal count levels, the direct method was shown to outperform the indirect method based on OSL-MAP in the sense that at matched level of bias, reduced regional noise levels were obtained. At lower count levels, the direct method produced [Formula: see text] estimates with significantly lower standard deviation across noise realizations than the indirect method based on OSL-MAP at matched bias level. In all cases, the direct method yielded lower noise and standard deviation than the indirect method based on OSEM. Overall, the proposed direct reconstruction offered a better bias-variance tradeoff than the indirect method applied to either OSEM and OSL-MAP. Direct parametric reconstruction as applied to in vivo dynamic PET MPI data is therefore a promising method for producing MBF maps with lower variance.

Direct parametric reconstruction in dynamic PET myocardial perfusion imaging: in-vivo studies

PubMed Central

Petibon, Yoann; Rakvongthai, Yothin; Fakhri, Georges El; Ouyang, Jinsong

2017-01-01

Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves -TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. The aim of this study was to extend and evaluate the performance of a direct parametric reconstruction method using in-vivo dynamic PET MPI data for the purpose of quantifying MBF. Dynamic PET MPI studies were performed on two healthy pigs using a Siemens Biograph mMR scanner. List-mode PET data for each animal were acquired following a bolus injection of ~7-8 mCi of 18F-flurpiridaz, a myocardial perfusion agent. Fully-3D dynamic PET sinograms were obtained by sorting the coincidence events into 16 temporal frames covering ~5 min after radiotracer administration. Additionally, eight independent noise realizations of both scans - each containing 1/8th of the total number of events - were generated from the original list-mode data. Dynamic sinograms were then used to compute parametric maps using the conventional indirect method and the proposed direct method. For both methods, a one-tissue compartment model accounting for spillover from the left and right ventricle blood-pools was used to describe the kinetics of 18F-flurpiridaz. An image-derived arterial input function obtained from a TAC taken in the left ventricle cavity was used for tracer kinetic analysis. For the indirect method, frame-by-frame images were estimated using two fully-3D reconstruction techniques: the standard Ordered Subset Expectation Maximization (OSEM) reconstruction algorithm on one side, and the One-Step Late Maximum a Posteriori (OSL-MAP) algorithm on the other side, which incorporates a quadratic penalty function. The parametric images were then calculated using voxel-wise weighted least-square fitting of the reconstructed myocardial PET TACs. For the direct method, parametric images were estimated directly from the dynamic PET sinograms using a maximum a posteriori (MAP) parametric reconstruction algorithm which optimizes an objective function comprised of the Poisson log-likelihood term, the kinetic model and a quadratic penalty function. Maximization of the objective function with respect to each set of parameters was achieved using a preconditioned conjugate gradient algorithm with a specifically developed pre-conditioner. The performance of the direct method was evaluated by comparing voxel- and segment-wise estimates of K1, the tracer transport rate (mL.min−1.mL−1), to those obtained using the indirect method applied to both OSEM and OSL-MAP dynamic reconstructions. The proposed direct reconstruction method produced K1 maps with visibly lower noise than the indirect method based on OSEM and OSL-MAP reconstructions. At normal count levels, the direct method was shown to outperform the indirect method based on OSL-MAP in the sense that at matched level of bias, reduced regional noise levels were obtained. At lower count levels, the direct method produced K1 estimates with significantly lower standard deviation across noise realizations than the indirect method based on OSL-MAP at matched bias level. In all cases, the direct method yielded lower noise and standard deviation than the indirect method based on OSEM. Overall, the proposed direct reconstruction offered a better bias-variance tradeoff than the indirect method applied to either OSEM and OSL-MAP. Direct parametric reconstruction as applied to in-vivo dynamic PET MPI data is therefore a promising method for producing MBF maps with lower variance. PMID:28379843

Direct parametric reconstruction in dynamic PET myocardial perfusion imaging: in vivo studies

NASA Astrophysics Data System (ADS)

Petibon, Yoann; Rakvongthai, Yothin; El Fakhri, Georges; Ouyang, Jinsong

2017-05-01

Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves-TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. The aim of this study was to extend and evaluate the performance of a direct parametric reconstruction method using in vivo dynamic PET MPI data for the purpose of quantifying MBF. Dynamic PET MPI studies were performed on two healthy pigs using a Siemens Biograph mMR scanner. List-mode PET data for each animal were acquired following a bolus injection of ~7-8 mCi of 18F-flurpiridaz, a myocardial perfusion agent. Fully-3D dynamic PET sinograms were obtained by sorting the coincidence events into 16 temporal frames covering ~5 min after radiotracer administration. Additionally, eight independent noise realizations of both scans—each containing 1/8th of the total number of events—were generated from the original list-mode data. Dynamic sinograms were then used to compute parametric maps using the conventional indirect method and the proposed direct method. For both methods, a one-tissue compartment model accounting for spillover from the left and right ventricle blood-pools was used to describe the kinetics of 18F-flurpiridaz. An image-derived arterial input function obtained from a TAC taken in the left ventricle cavity was used for tracer kinetic analysis. For the indirect method, frame-by-frame images were estimated using two fully-3D reconstruction techniques: the standard ordered subset expectation maximization (OSEM) reconstruction algorithm on one side, and the one-step late maximum a posteriori (OSL-MAP) algorithm on the other side, which incorporates a quadratic penalty function. The parametric images were then calculated using voxel-wise weighted least-square fitting of the reconstructed myocardial PET TACs. For the direct method, parametric images were estimated directly from the dynamic PET sinograms using a maximum a posteriori (MAP) parametric reconstruction algorithm which optimizes an objective function comprised of the Poisson log-likelihood term, the kinetic model and a quadratic penalty function. Maximization of the objective function with respect to each set of parameters was achieved using a preconditioned conjugate gradient algorithm with a specifically developed pre-conditioner. The performance of the direct method was evaluated by comparing voxel- and segment-wise estimates of {{K}1} , the tracer transport rate (ml · min-1 · ml-1), to those obtained using the indirect method applied to both OSEM and OSL-MAP dynamic reconstructions. The proposed direct reconstruction method produced {{K}1} maps with visibly lower noise than the indirect method based on OSEM and OSL-MAP reconstructions. At normal count levels, the direct method was shown to outperform the indirect method based on OSL-MAP in the sense that at matched level of bias, reduced regional noise levels were obtained. At lower count levels, the direct method produced {{K}1} estimates with significantly lower standard deviation across noise realizations than the indirect method based on OSL-MAP at matched bias level. In all cases, the direct method yielded lower noise and standard deviation than the indirect method based on OSEM. Overall, the proposed direct reconstruction offered a better bias-variance tradeoff than the indirect method applied to either OSEM and OSL-MAP. Direct parametric reconstruction as applied to in vivo dynamic PET MPI data is therefore a promising method for producing MBF maps with lower variance.

Biophysical Neural Spiking, Bursting, and Excitability Dynamics in Reconfigurable Analog VLSI.

PubMed

Yu, T; Sejnowski, T J; Cauwenberghs, G

2011-10-01

We study a range of neural dynamics under variations in biophysical parameters underlying extended Morris-Lecar and Hodgkin-Huxley models in three gating variables. The extended models are implemented in NeuroDyn, a four neuron, twelve synapse continuous-time analog VLSI programmable neural emulation platform with generalized channel kinetics and biophysical membrane dynamics. The dynamics exhibit a wide range of time scales extending beyond 100 ms neglected in typical silicon models of tonic spiking neurons. Circuit simulations and measurements show transition from tonic spiking to tonic bursting dynamics through variation of a single conductance parameter governing calcium recovery. We similarly demonstrate transition from graded to all-or-none neural excitability in the onset of spiking dynamics through the variation of channel kinetic parameters governing the speed of potassium activation. Other combinations of variations in conductance and channel kinetic parameters give rise to phasic spiking and spike frequency adaptation dynamics. The NeuroDyn chip consumes 1.29 mW and occupies 3 mm × 3 mm in 0.5 μm CMOS, supporting emerging developments in neuromorphic silicon-neuron interfaces.

Kinetics and mechanical stability of the fibril state control fibril formation time of polypeptide chains: A computational study

NASA Astrophysics Data System (ADS)

Kouza, Maksim; Co, Nguyen Truong; Li, Mai Suan; Kmiecik, Sebastian; Kolinski, Andrzej; Kloczkowski, Andrzej; Buhimschi, Irina Alexandra

2018-06-01

Fibril formation resulting from protein misfolding and aggregation is a hallmark of several neurodegenerative diseases such as Alzheimer's and Parkinson's diseases. Despite much progress in the understanding of the protein aggregation process, the factors governing fibril formation rates and fibril stability have not been fully understood. Using lattice models, we have shown that the fibril formation time is controlled by the kinetic stability of the fibril state but not by its energy. Having performed all-atom explicit solvent molecular dynamics simulations with the GROMOS43a1 force field for full-length amyloid beta peptides Aβ40 and Aβ42 and truncated peptides, we demonstrated that kinetic stability can be accessed via mechanical stability in such a way that the higher the mechanical stability or the kinetic stability, the faster the fibril formation. This result opens up a new way for predicting fibril formation rates based on mechanical stability that may be easily estimated by steered molecular dynamics.

Assembly Kinetics Determine the Architecture of α-actinin Crosslinked F-actin Networks

PubMed Central

Falzone, Tobias T.; Lenz, Martin; Kovar, David R.; Gardel, Margaret L.

2013-01-01

The actin cytoskeleton is organized into diverse meshworks and bundles that support many aspects of cell physiology. Understanding the self-assembly of these actin-based structures is essential for developing predictive models of cytoskeletal organization. Here we show that the competing kinetics of bundle formation with the onset of dynamic arrest arising from filament entanglements and cross-linking determine the architecture of reconstituted actin networks formed with α-actinin cross-links. Cross-link mediated bundle formation only occurs in dilute solutions of highly mobile actin filaments. As actin polymerization proceeds, filament mobility and bundle formation are arrested concomitantly. By controlling the onset of dynamic arrest, perturbations to actin assembly kinetics dramatically alter the architecture of biochemically identical samples. Thus, the morphology of reconstituted F-actin networks is a kinetically determined structure similar to those formed by physical gels and glasses. These results establish mechanisms controlling the structure and mechanics in diverse semi-flexible biopolymer networks. PMID:22643888

A new class of enhanced kinetic sampling methods for building Markov state models

NASA Astrophysics Data System (ADS)

Bhoutekar, Arti; Ghosh, Susmita; Bhattacharya, Swati; Chatterjee, Abhijit

2017-10-01

Markov state models (MSMs) and other related kinetic network models are frequently used to study the long-timescale dynamical behavior of biomolecular and materials systems. MSMs are often constructed bottom-up using brute-force molecular dynamics (MD) simulations when the model contains a large number of states and kinetic pathways that are not known a priori. However, the resulting network generally encompasses only parts of the configurational space, and regardless of any additional MD performed, several states and pathways will still remain missing. This implies that the duration for which the MSM can faithfully capture the true dynamics, which we term as the validity time for the MSM, is always finite and unfortunately much shorter than the MD time invested to construct the model. A general framework that relates the kinetic uncertainty in the model to the validity time, missing states and pathways, network topology, and statistical sampling is presented. Performing additional calculations for frequently-sampled states/pathways may not alter the MSM validity time. A new class of enhanced kinetic sampling techniques is introduced that aims at targeting rare states/pathways that contribute most to the uncertainty so that the validity time is boosted in an effective manner. Examples including straightforward 1D energy landscapes, lattice models, and biomolecular systems are provided to illustrate the application of the method. Developments presented here will be of interest to the kinetic Monte Carlo community as well.

Modeling biological pathway dynamics with timed automata.

PubMed

Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N

2014-05-01

Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.

Influence of kinetic effects on the resonance behavior of the Multipole Resonance Probe

NASA Astrophysics Data System (ADS)

Oberrath, Jens; Mussenbrock, Thomas; Brinkmann, Ralf Peter

2012-10-01

Active plasma resonance spectroscopy is a well known diagnostic method. Many concepts of this method are theoretically investigated and realized as a diagnostic tool. One of these tools is the multipole resonance probe (MRP) [1]. The application of such a probe in plasmas with pressures of only a few Pa raises the question whether kinetic effects have to be taken into account or not. To address this question a kinetic model is necessary. A general kinetic model for an electrostatic concept of active plasma resonance spectroscopy has already been presented by the authors [2]. This model can be used to describe the dynamical behavior of the MRP, which is interpretable as a special case of the general model. Neglecting electron-neutral collisions, this model can be solved analytically. Based on this solution we derive an approximated expression for the admittance of the system to investigate the influence of kinetic effects on the resonance behavior of the MRP. [4pt] [1] M. Lapke et al., Plasma Sources Sci. Technol. 20, 2011, 042001[0pt] [2] J. Oberrath et al., Proceedings of the 30th International Conference on Phenomena in Ionized Gases, 28th August - 2nd September, 2011

Direct modeling for computational fluid dynamics

NASA Astrophysics Data System (ADS)

Xu, Kun

2015-06-01

All fluid dynamic equations are valid under their modeling scales, such as the particle mean free path and mean collision time scale of the Boltzmann equation and the hydrodynamic scale of the Navier-Stokes (NS) equations. The current computational fluid dynamics (CFD) focuses on the numerical solution of partial differential equations (PDEs), and its aim is to get the accurate solution of these governing equations. Under such a CFD practice, it is hard to develop a unified scheme that covers flow physics from kinetic to hydrodynamic scales continuously because there is no such governing equation which could make a smooth transition from the Boltzmann to the NS modeling. The study of fluid dynamics needs to go beyond the traditional numerical partial differential equations. The emerging engineering applications, such as air-vehicle design for near-space flight and flow and heat transfer in micro-devices, do require further expansion of the concept of gas dynamics to a larger domain of physical reality, rather than the traditional distinguishable governing equations. At the current stage, the non-equilibrium flow physics has not yet been well explored or clearly understood due to the lack of appropriate tools. Unfortunately, under the current numerical PDE approach, it is hard to develop such a meaningful tool due to the absence of valid PDEs. In order to construct multiscale and multiphysics simulation methods similar to the modeling process of constructing the Boltzmann or the NS governing equations, the development of a numerical algorithm should be based on the first principle of physical modeling. In this paper, instead of following the traditional numerical PDE path, we introduce direct modeling as a principle for CFD algorithm development. Since all computations are conducted in a discretized space with limited cell resolution, the flow physics to be modeled has to be done in the mesh size and time step scales. Here, the CFD is more or less a direct construction of discrete numerical evolution equations, where the mesh size and time step will play dynamic roles in the modeling process. With the variation of the ratio between mesh size and local particle mean free path, the scheme will capture flow physics from the kinetic particle transport and collision to the hydrodynamic wave propagation. Based on the direct modeling, a continuous dynamics of flow motion will be captured in the unified gas-kinetic scheme. This scheme can be faithfully used to study the unexplored non-equilibrium flow physics in the transition regime.

Development and validation of a comprehensive model for map of fruits based on enzyme kinetics theory and arrhenius relation.

PubMed

Mangaraj, S; K Goswami, T; Mahajan, P V

2015-07-01

MAP is a dynamic system where respiration of the packaged product and gas permeation through the packaging film takes place simultaneously. The desired level of O2 and CO2 in a package is achieved by matching film permeation rates for O2 and CO2 with respiration rate of the packaged product. A mathematical model for MAP of fresh fruits applying enzyme kinetics based respiration equation coupled with the Arrhenious type model was developed. The model was solved numerically using MATLAB programme. The model was used to determine the time to reach to the equilibrium concentration inside the MA package and the level of O2 and CO2 concentration at equilibrium state. The developed model for prediction of equilibrium O2 and CO2 concentration was validated using experimental data for MA packaging of apple, guava and litchi.

A Hierarchy of Heuristic-Based Models of Crowd Dynamics

NASA Astrophysics Data System (ADS)

Degond, P.; Appert-Rolland, C.; Moussaïd, M.; Pettré, J.; Theraulaz, G.

2013-09-01

We derive a hierarchy of kinetic and macroscopic models from a noisy variant of the heuristic behavioral Individual-Based Model of Ngai et al. (Disaster Med. Public Health Prep. 3:191-195, 2009) where pedestrians are supposed to have constant speeds. This IBM supposes that pedestrians seek the best compromise between navigation towards their target and collisions avoidance. We first propose a kinetic model for the probability distribution function of pedestrians. Then, we derive fluid models and propose three different closure relations. The first two closures assume that the velocity distribution function is either a Dirac delta or a von Mises-Fisher distribution respectively. The third closure results from a hydrodynamic limit associated to a Local Thermodynamical Equilibrium. We develop an analogy between this equilibrium and Nash equilibria in a game theoretic framework. In each case, we discuss the features of the models and their suitability for practical use.

Thermodynamics of information processing based on enzyme kinetics: An exactly solvable model of an information pump.

PubMed

Cao, Yuansheng; Gong, Zongping; Quan, H T

2015-06-01

Motivated by the recent proposed models of the information engine [Proc. Natl. Acad. Sci. USA 109, 11641 (2012)] and the information refrigerator [Phys. Rev. Lett. 111, 030602 (2013)], we propose a minimal model of the information pump and the information eraser based on enzyme kinetics. This device can either pump molecules against the chemical potential gradient by consuming the information to be encoded in the bit stream or (partially) erase the information initially encoded in the bit stream by consuming the Gibbs free energy. The dynamics of this model is solved exactly, and the "phase diagram" of the operation regimes is determined. The efficiency and the power of the information machine is analyzed. The validity of the second law of thermodynamics within our model is clarified. Our model offers a simple paradigm for the investigating of the thermodynamics of information processing involving the chemical potential in small systems.

KINETIC AND DYNAMIC ASPECTS OF ARSENIC TOXICITY

EPA Science Inventory

This project integrates research on aspects of the kinetic and dynamic behavior of arsenic. A PBPK model for arsenic will be developed using metabolism and disposition data from studies in mice. Retention of arsenic in the tissues following exposure to arsenic will be investigate...

Dynamical approach to the cosmological constant.

PubMed

Mukohyama, Shinji; Randall, Lisa

2004-05-28

We consider a dynamical approach to the cosmological constant. There is a scalar field with a potential whose minimum occurs at a generic, but negative, value for the vacuum energy, and it has a nonstandard kinetic term whose coefficient diverges at zero curvature as well as the standard kinetic term. Because of the divergent coefficient of the kinetic term, the lowest energy state is never achieved. Instead, the cosmological constant automatically stalls at or near zero. The merit of this model is that it is stable under radiative corrections and leads to stable dynamics, despite the singular kinetic term. The model is not complete, however, in that some reheating is required. Nonetheless, our approach can at the very least reduce fine-tuning by 60 orders of magnitude or provide a new mechanism for sampling possible cosmological constants and implementing the anthropic principle.

Comparison between different adsorption-desorption kinetics schemes in two dimensional lattice gas

NASA Astrophysics Data System (ADS)

Huespe, V. J.; Belardinelli, R. E.; Pereyra, V. D.; Manzi, S. J.

2017-12-01

Monte Carlo simulation is used to study the adsorption-desorption kinetics in the framework of the kinetic lattice-gas model. Three schemes of the so-called hard dynamics and five schemes of the so called soft dynamics were used for this purpose. It is observed that for the hard dynamic schemes, the equilibrium and non-equilibrium observable, such as adsorption isotherms, sticking coefficients, and thermal desorption spectra, have a normal or physical sustainable behavior. While for the soft dynamics schemes, with the exception of the transition state theory, the equilibrium and non-equilibrium observables have several problems.

High-order continuum kinetic method for modeling plasma dynamics in phase space

DOE PAGES

Vogman, G. V.; Colella, P.; Shumlak, U.

2014-12-15

Continuum methods offer a high-fidelity means of simulating plasma kinetics. While computationally intensive, these methods are advantageous because they can be cast in conservation-law form, are not susceptible to noise, and can be implemented using high-order numerical methods. Advances in continuum method capabilities for modeling kinetic phenomena in plasmas require the development of validation tools in higher dimensional phase space and an ability to handle non-cartesian geometries. To that end, a new benchmark for validating Vlasov-Poisson simulations in 3D (x,v x,v y) is presented. The benchmark is based on the Dory-Guest-Harris instability and is successfully used to validate a continuummore » finite volume algorithm. To address challenges associated with non-cartesian geometries, unique features of cylindrical phase space coordinates are described. Preliminary results of continuum kinetic simulations in 4D (r,z,v r,v z) phase space are presented.« less

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

Alvarez-Ramirez, J.; Aguilar, R.; Lopez-Isunza, F.

FCC processes involve complex interactive dynamics which are difficult to operate and control as well as poorly known reaction kinetics. This work concerns the synthesis of temperature controllers for FCC units. The problem is addressed first for the case where perfect knowledge of the reaction kinetics is assumed, leading to an input-output linearizing state feedback. However, in most industrial FCC units, perfect knowledge of reaction kinetics and composition measurements is not available. To address the problem of robustness against uncertainties in the reaction kinetics, an adaptive model-based nonlinear controller with simplified reaction models is presented. The adaptive strategy makes usemore » of estimates of uncertainties derived from calorimetric (energy) balances. The resulting controller is similar in form to standard input-output linearizing controllers and can be tuned analogously. Alternatively, the controller can be tuned using a single gain parameter and is computationally efficient. The performance of the closed-loop system and the controller design procedure are shown with simulations.« less

Conformational Dynamics of Insulin

PubMed Central

Hua, Qing-Xin; Jia, Wenhua; Weiss, Michael A.

2011-01-01

We have exploited a prandial insulin analog to elucidate the underlying structure and dynamics of insulin as a monomer in solution. A model was provided by insulin lispro (the active component of Humalog®; Eli Lilly and Co.). Whereas NMR-based modeling recapitulated structural relationships of insulin crystals (T-state protomers), dynamic anomalies were revealed by amide-proton exchange kinetics in D2O. Surprisingly, the majority of hydrogen bonds observed in crystal structures are only transiently maintained in solution, including key T-state-specific inter-chain contacts. Long-lived hydrogen bonds (as defined by global exchange kinetics) exist only at a subset of four α-helical sites (two per chain) flanking an internal disulfide bridge (cystine A20–B19); these sites map within the proposed folding nucleus of proinsulin. The anomalous flexibility of insulin otherwise spans its active surface and may facilitate receptor binding. Because conformational fluctuations promote the degradation of pharmaceutical formulations, we envisage that “dynamic re-engineering” of insulin may enable design of ultra-stable formulations for humanitarian use in the developing world. PMID:22649374

Modeling Dynamic Contrast-Enhanced MRI Data with a Constrained Local AIF.

PubMed

Duan, Chong; Kallehauge, Jesper F; Pérez-Torres, Carlos J; Bretthorst, G Larry; Beeman, Scott C; Tanderup, Kari; Ackerman, Joseph J H; Garbow, Joel R

2018-02-01

This study aims to develop a constrained local arterial input function (cL-AIF) to improve quantitative analysis of dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) data by accounting for the contrast-agent bolus amplitude error in the voxel-specific AIF. Bayesian probability theory-based parameter estimation and model selection were used to compare tracer kinetic modeling employing either the measured remote-AIF (R-AIF, i.e., the traditional approach) or an inferred cL-AIF against both in silico DCE-MRI data and clinical, cervical cancer DCE-MRI data. When the data model included the cL-AIF, tracer kinetic parameters were correctly estimated from in silico data under contrast-to-noise conditions typical of clinical DCE-MRI experiments. Considering the clinical cervical cancer data, Bayesian model selection was performed for all tumor voxels of the 16 patients (35,602 voxels in total). Among those voxels, a tracer kinetic model that employed the voxel-specific cL-AIF was preferred (i.e., had a higher posterior probability) in 80 % of the voxels compared to the direct use of a single R-AIF. Maps of spatial variation in voxel-specific AIF bolus amplitude and arrival time for heterogeneous tissues, such as cervical cancer, are accessible with the cL-AIF approach. The cL-AIF method, which estimates unique local-AIF amplitude and arrival time for each voxel within the tissue of interest, provides better modeling of DCE-MRI data than the use of a single, measured R-AIF. The Bayesian-based data analysis described herein affords estimates of uncertainties for each model parameter, via posterior probability density functions, and voxel-wise comparison across methods/models, via model selection in data modeling.

A minimal model for kinetochore-microtubule dynamics

NASA Astrophysics Data System (ADS)

Liu, Andrea

2014-03-01

During mitosis, chromosome pairs align at the center of a bipolar microtubule (MT) spindle and oscillate as MTs attaching them to the cell poles polymerize and depolymerize. The cell fixes misaligned pairs by a tension-sensing mechanism. Pairs later separate as shrinking MTs pull each chromosome toward its respective cell pole. We present a minimal model for these processes based on properties of MT kinetics. We apply the measured tension-dependence of single MT kinetics to a stochastic many MT model, which we solve numerically and with master equations. We find that the force-velocity curve for the single chromosome system is bistable and hysteretic. Above some threshold load, tension fluctuations induce MTs to spontaneously switch from a pulling state into a growing, pushing state. To recover pulling from the pushing state, the load must be reduced far below the threshold. This leads to oscillations in the two-chromosome system. Our minimal model quantitatively captures several aspects of kinetochore dynamics observed experimentally. This work was supported by NSF-DMR-1104637.

Detonation initiation in a model of explosive: Comparative atomistic and hydrodynamics simulations

NASA Astrophysics Data System (ADS)

Murzov, S. A.; Sergeev, O. V.; Dyachkov, S. A.; Egorova, M. S.; Parshikov, A. N.; Zhakhovsky, V. V.

2016-11-01

Here we extend consistent simulations to reactive materials by the example of AB model explosive. The kinetic model of chemical reactions observed in a molecular dynamics (MD) simulation of self-sustained detonation wave can be used in hydrodynamic simulation of detonation initiation. Kinetic coefficients are obtained by minimization of difference between profiles of species calculated from the kinetic model and observed in MD simulations of isochoric thermal decomposition with a help of downhill simplex method combined with random walk in multidimensional space of fitting kinetic model parameters.

Intelligent processing for thick composites

NASA Astrophysics Data System (ADS)

Shin, Daniel Dong-Ok

2000-10-01

Manufacturing thick composite parts are associated with adverse curing conditions such as large in-plane temperature gradient and exotherms. The condition is further aggravated because the manufacturer's cycle and the existing cure control systems do not adequately counter such affects. In response, the forecast-based thermal control system is developed to have better cure control for thick composites. Accurate cure kinetic model is crucial for correctly identifying the amount of heat generated for composite process simulation. A new technique for identifying cure parameters for Hercules AS4/3502 prepreg is presented by normalizing the DSC data. The cure kinetics is based on an autocatalytic model for the proposed method, which uses dynamic and isothermal DSC data to determine its parameters. Existing models are also used to determine kinetic parameters but rendered inadequate because of the material's temperature dependent final degree of cure. The model predictions determined from the new technique showed good agreement to both isothermal and dynamic DSC data. The final degree of cure was also in good agreement with experimental data. A realistic cure simulation model including bleeder ply analysis and compaction is validated with Hercules AS4/3501-6 based laminates. The nonsymmetrical temperature distribution resulting from the presence of bleeder plies agreed well to the model prediction. Some of the discrepancies in the predicted compaction behavior were attributed to inaccurate viscosity and permeability models. The temperature prediction was quite good for the 3cm laminate. The validated process simulation model along with cure kinetics model for AS4/3502 prepreg were integrated into the thermal control system. The 3cm Hercules AS4/3501-6 and AS4/3502 laminate were fabricated. The resulting cure cycles satisfied all imposed requirements by minimizing exotherms and temperature gradient. Although the duration of the cure cycles increased, such phenomena was inevitable since longer time was required to maintain acceptable temperature gradient. The derived cure cycles were slightly different than what was anticipated by the offline simulation. Nevertheless, the system adapted to unanticipated events to satisfy the cure requirements.

Discrete dynamic modeling of cellular signaling networks.

PubMed

Albert, Réka; Wang, Rui-Sheng

2009-01-01

Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

Dynamic modeling of parallel robots for computed-torque control implementation

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

Codourey, A.

1998-12-01

In recent years, increased interest in parallel robots has been observed. Their control with modern theory, such as the computed-torque method, has, however, been restrained, essentially due to the difficulty in establishing a simple dynamic model that can be calculated in real time. In this paper, a simple method based on the virtual work principle is proposed for modeling parallel robots. The mass matrix of the robot, needed for decoupling control strategies, does not explicitly appear in the formulation; however, it can be computed separately, based on kinetic energy considerations. The method is applied to the DELTA parallel robot, leadingmore » to a very efficient model that has been implemented in a real-time computed-torque control algorithm.« less

Kinetic modeling of active plasma resonance spectroscopy

NASA Astrophysics Data System (ADS)

Oberrath, Jens

2016-09-01

The term ``active plasma resonance spectroscopy'' (APRS) refers to a plasma diagnostic method which employs the natural ability of plasmas to resonate close to the plasma frequency. Essential for this method is an appropriate model to determine the relation between the resonance parameters and demanded plasma parameters. Measurements with these probes in plasmas of a few Pa typically show a broadening of the spectrum that cannot be predicted by a fluid model. Thus, a kinetic model is necessary. A general kinetic model of APRS probes, which can be described in electorstatic approximation, valid for all pressures has been presented. This model is used to analyze the dynamic behavior of such probes by means of functional analytic methods. One of the main results is, that the system response function Y (ω) is given in terms of the matrix elements of the resolvent of the dynamic operator evaluated for values on the imaginary axis. The spectrum of this operator is continuous which implies a new phenomenon related to anomalous or non-collisional dissipation. Based on the scalar product, which is motivated by the kinetic free energy, the non-collisional damping can be interpreted: In a periodic state, the probe constantly emits plasma waves which propagate to ``infinity''. The free energy simply leaves the ``observation range'' of the probe which is recorded as damping. The kinetic damping, which depends on the mean kinetic energy of the electrons, is responsible for the broadening of a resonance peak in the measured spectrum of APRS probes. The ultimate goal is to determine explicit formulas for the relation between the broadening of the resonance peak and the ``equivalent electron temperature'', especially in the case of the spherical Impedance Probe and the Multipole Resonance Probe. Gratitude is expressed to the internal funding of Leuphana University, the BMBF via PluTO+, the DFG via Collaborative Research Center TR 87, and the Ruhr University Research School.

There is more than one way to model an elephant. Experiment-driven modeling of the actin cytoskeleton.

PubMed

Ditlev, Jonathon A; Mayer, Bruce J; Loew, Leslie M

2013-02-05

Mathematical modeling has established its value for investigating the interplay of biochemical and mechanical mechanisms underlying actin-based motility. Because of the complex nature of actin dynamics and its regulation, many of these models are phenomenological or conceptual, providing a general understanding of the physics at play. But the wealth of carefully measured kinetic data on the interactions of many of the players in actin biochemistry cries out for the creation of more detailed and accurate models that could permit investigators to dissect interdependent roles of individual molecular components. Moreover, no human mind can assimilate all of the mechanisms underlying complex protein networks; so an additional benefit of a detailed kinetic model is that the numerous binding proteins, signaling mechanisms, and biochemical reactions can be computationally organized in a fully explicit, accessible, visualizable, and reusable structure. In this review, we will focus on how comprehensive and adaptable modeling allows investigators to explain experimental observations and develop testable hypotheses on the intracellular dynamics of the actin cytoskeleton. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

There is More Than One Way to Model an Elephant. Experiment-Driven Modeling of the Actin Cytoskeleton

PubMed Central

Ditlev, Jonathon A.; Mayer, Bruce J.; Loew, Leslie M.

2013-01-01

Mathematical modeling has established its value for investigating the interplay of biochemical and mechanical mechanisms underlying actin-based motility. Because of the complex nature of actin dynamics and its regulation, many of these models are phenomenological or conceptual, providing a general understanding of the physics at play. But the wealth of carefully measured kinetic data on the interactions of many of the players in actin biochemistry cries out for the creation of more detailed and accurate models that could permit investigators to dissect interdependent roles of individual molecular components. Moreover, no human mind can assimilate all of the mechanisms underlying complex protein networks; so an additional benefit of a detailed kinetic model is that the numerous binding proteins, signaling mechanisms, and biochemical reactions can be computationally organized in a fully explicit, accessible, visualizable, and reusable structure. In this review, we will focus on how comprehensive and adaptable modeling allows investigators to explain experimental observations and develop testable hypotheses on the intracellular dynamics of the actin cytoskeleton. PMID:23442903

Predicting the kinetics of Listeria monocytogenes and Yersinia enterocolitica under dynamic growth/death-inducing conditions, in Italian style fresh sausage.

PubMed

Iannetti, Luigi; Salini, Romolo; Sperandii, Anna Franca; Santarelli, Gino Angelo; Neri, Diana; Di Marzio, Violeta; Romantini, Romina; Migliorati, Giacomo; Baranyi, József

2017-01-02

Traditional Italian pork products can be consumed after variable drying periods, where the temporal decrease of water activity spans from optimal to inactivating values. This makes it necessary to A) consider the bias factor when applying culture-medium-based predictive models to sausage; B) apply the dynamic version (described by differential equations) of those models; C) combine growth and death models in a continuous way, including the highly uncertain growth/no growth range separating the two regions. This paper tests the applicability of published predictive models on the responses of Listeria monocytogenes and Yersinia enterocolitica to dynamic conditions in traditional Italian pork sausage, where the environment changes from growth-supporting to inhibitory conditions, so the growth and death models need to be combined. The effect of indigenous lactic acid bacteria was also taken into account in the predictions. Challenge tests were carried out using such sausages, inoculated separately with L. monocytogenes and Y. enterocolitica, stored for 480h at 8, 12, 18 and 20°C. The pH was fairly constant, while the water activity changed dynamically. The effects of the environment on the specific growth and death rate of the studied organisms were predicted using previously published predictive models and parameters. Microbial kinetics in many products with a long shelf-life and dynamic internal environment, could result in both growth and inactivation, making it difficult to estimate the bacterial concentration at the time of consumption by means of commonly available predictive software tools. Our prediction of the effect of the storage environment, where the water activity gradually decreases during a drying period, is designed to overcome these difficulties. The methodology can be used generally to predict and visualise bacterial kinetics under temporal variation of environments, which is vital when assessing the safety of many similar products. Copyright © 2016 Elsevier B.V. All rights reserved.

Modeling the degradation kinetics of ascorbic acid.

PubMed

Peleg, Micha; Normand, Mark D; Dixon, William R; Goulette, Timothy R

2018-06-13

Most published reports on ascorbic acid (AA) degradation during food storage and heat preservation suggest that it follows first-order kinetics. Deviations from this pattern include Weibullian decay, and exponential drop approaching finite nonzero retention. Almost invariably, the degradation rate constant's temperature-dependence followed the Arrhenius equation, and hence the simpler exponential model too. A formula and freely downloadable interactive Wolfram Demonstration to convert the Arrhenius model's energy of activation, E a , to the exponential model's c parameter, or vice versa, are provided. The AA's isothermal and non-isothermal degradation can be simulated with freely downloadable interactive Wolfram Demonstrations in which the model's parameters can be entered and modified by moving sliders on the screen. Where the degradation is known a priori to follow first or other fixed order kinetics, one can use the endpoints method, and in principle the successive points method too, to estimate the reaction's kinetic parameters from considerably fewer AA concentration determinations than in the traditional manner. Freeware to do the calculations by either method has been recently made available on the Internet. Once obtained in this way, the kinetic parameters can be used to reconstruct the entire degradation curves and predict those at different temperature profiles, isothermal or dynamic. Comparison of the predicted concentration ratios with experimental ones offers a way to validate or refute the kinetic model and the assumptions on which it is based.

Recent Advances in Dynamic Kinetic Resolution by Chiral Bifunctional (Thio)urea- and Squaramide-Based Organocatalysts.

PubMed

Li, Pan; Hu, Xinquan; Dong, Xiu-Qin; Zhang, Xumu

2016-10-14

The organocatalysis-based dynamic kinetic resolution (DKR) process has proved to be a powerful strategy for the construction of chiral compounds. In this feature review, we summarized recent progress on the DKR process, which was promoted by chiral bifunctional (thio)urea and squaramide catalysis via hydrogen-bonding interactions between substrates and catalysts. A wide range of asymmetric reactions involving DKR, such as asymmetric alcoholysis of azlactones, asymmetric Michael-Michael cascade reaction, and enantioselective selenocyclization, are reviewed and demonstrate the efficiency of this strategy. The (thio)urea and squaramide catalysts with dual activation would be efficient for more unmet challenges in dynamic kinetic resolution.

Poster — Thur Eve — 44: Linearization of Compartmental Models for More Robust Estimates of Regional Hemodynamic, Metabolic and Functional Parameters using DCE-CT/PET Imaging

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

Blais, AR; Dekaban, M; Lee, T-Y

2014-08-15

Quantitative analysis of dynamic positron emission tomography (PET) data usually involves minimizing a cost function with nonlinear regression, wherein the choice of starting parameter values and the presence of local minima affect the bias and variability of the estimated kinetic parameters. These nonlinear methods can also require lengthy computation time, making them unsuitable for use in clinical settings. Kinetic modeling of PET aims to estimate the rate parameter k{sub 3}, which is the binding affinity of the tracer to a biological process of interest and is highly susceptible to noise inherent in PET image acquisition. We have developed linearized kineticmore » models for kinetic analysis of dynamic contrast enhanced computed tomography (DCE-CT)/PET imaging, including a 2-compartment model for DCE-CT and a 3-compartment model for PET. Use of kinetic parameters estimated from DCE-CT can stabilize the kinetic analysis of dynamic PET data, allowing for more robust estimation of k{sub 3}. Furthermore, these linearized models are solved with a non-negative least squares algorithm and together they provide other advantages including: 1) only one possible solution and they do not require a choice of starting parameter values, 2) parameter estimates are comparable in accuracy to those from nonlinear models, 3) significantly reduced computational time. Our simulated data show that when blood volume and permeability are estimated with DCE-CT, the bias of k{sub 3} estimation with our linearized model is 1.97 ± 38.5% for 1,000 runs with a signal-to-noise ratio of 10. In summary, we have developed a computationally efficient technique for accurate estimation of k{sub 3} from noisy dynamic PET data.« less

Automated workflows for modelling chemical fate, kinetics and toxicity.

PubMed

Sala Benito, J V; Paini, Alicia; Richarz, Andrea-Nicole; Meinl, Thorsten; Berthold, Michael R; Cronin, Mark T D; Worth, Andrew P

2017-12-01

Automation is universal in today's society, from operating equipment such as machinery, in factory processes, to self-parking automobile systems. While these examples show the efficiency and effectiveness of automated mechanical processes, automated procedures that support the chemical risk assessment process are still in their infancy. Future human safety assessments will rely increasingly on the use of automated models, such as physiologically based kinetic (PBK) and dynamic models and the virtual cell based assay (VCBA). These biologically-based models will be coupled with chemistry-based prediction models that also automate the generation of key input parameters such as physicochemical properties. The development of automated software tools is an important step in harmonising and expediting the chemical safety assessment process. In this study, we illustrate how the KNIME Analytics Platform can be used to provide a user-friendly graphical interface for these biokinetic models, such as PBK models and VCBA, which simulates the fate of chemicals in vivo within the body and in vitro test systems respectively. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Kinetic modelling of starch and lipid formation during mixotrophic, nutrient-limited microalgal growth.

PubMed

Figueroa-Torres, Gonzalo M; Pittman, Jon K; Theodoropoulos, Constantinos

2017-10-01

Microalgal starch and lipids, carbon-based storage molecules, are useful as potential biofuel feedstocks. In this work, cultivation strategies maximising starch and lipid formation were established by developing a multi-parameter kinetic model describing microalgal growth as well as starch and lipid formation, in conjunction with laboratory-scale experiments. Growth dynamics are driven by nitrogen-limited mixotrophic conditions, known to increase cellular starch and lipid contents whilst enhancing biomass growth. Model parameters were computed by fitting model outputs to a range of experimental datasets from batch cultures of Chlamydomonas reinhardtii. Predictive capabilities of the model were established against different experimental data. The model was subsequently used to compute optimal nutrient-based cultivation strategies in terms of initial nitrogen and carbon concentrations. Model-based optimal strategies yielded a significant increase of 261% for starch (0.065gCL -1 ) and 66% for lipid (0.08gCL -1 ) production compared to base-case conditions (0.018gCL -1 starch, 0.048gCL -1 lipids). Copyright © 2017 Elsevier Ltd. All rights reserved.

Dynamic analysis of the deployment for mesh reflector deployable antennas with the cable-net structure

NASA Astrophysics Data System (ADS)

Zhang, Yiqun; Li, Na; Yang, Guigeng; Ru, Wenrui

2017-02-01

This paper presents a dynamic analysis approach for the composite structure of a deployable truss and cable-net system. An Elastic Catenary Element is adopted to model the slack/tensioned cables. Then, from the energy standpoint, the kinetic energy, elasticity-potential energy and geopotential energy of the cable-net structure and deployable truss are derived. Thus, the flexible multi-body dynamic model of the deployable antenna is built based on the Lagrange equation. The effect of the cable-net tension on the antenna truss is discussed and compared with previous publications and a dynamic deployment analysis is performed. Both the simulation and experimental results verify the validity of the method presented.

Kinetic modeling in PET imaging of hypoxia

PubMed Central

Li, Fan; Joergensen, Jesper T; Hansen, Anders E; Kjaer, Andreas

2014-01-01

Tumor hypoxia is associated with increased therapeutic resistance leading to poor treatment outcome. Therefore the ability to detect and quantify intratumoral oxygenation could play an important role in future individual personalized treatment strategies. Positron Emission Tomography (PET) can be used for non-invasive mapping of tissue oxygenation in vivo and several hypoxia specific PET tracers have been developed. Evaluation of PET data in the clinic is commonly based on visual assessment together with semiquantitative measurements e.g. standard uptake value (SUV). However, dynamic PET contains additional valuable information on the temporal changes in tracer distribution. Kinetic modeling can be used to extract relevant pharmacokinetic parameters of tracer behavior in vivo that reflects relevant physiological processes. In this paper, we review the potential contribution of kinetic analysis for PET imaging of hypoxia. PMID:25250200

High resolution approach to the native state ensemble kinetics and thermodynamics.

PubMed

Wu, Sangwook; Zhuravlev, Pavel I; Papoian, Garegin A

2008-12-15

Many biologically interesting functions such as allosteric switching or protein-ligand binding are determined by the kinetics and mechanisms of transitions between various conformational substates of the native basin of globular proteins. To advance our understanding of these processes, we constructed a two-dimensional free energy surface (FES) of the native basin of a small globular protein, Trp-cage. The corresponding order parameters were defined using two native substructures of Trp-cage. These calculations were based on extensive explicit water all-atom molecular dynamics simulations. Using the obtained two-dimensional FES, we studied the transition kinetics between two Trp-cage conformations, finding that switching process shows a borderline behavior between diffusive and weakly-activated dynamics. The transition is well-characterized kinetically as a biexponential process. We also introduced a new one-dimensional reaction coordinate for the conformational transition, finding reasonable qualitative agreement with the two-dimensional kinetics results. We investigated the distribution of all the 38 native nuclear magnetic resonance structures on the obtained FES, analyzing interactions that stabilize specific low-energy conformations. Finally, we constructed a FES for the same system but with simple dielectric model of water instead of explicit water, finding that the results were surprisingly similar in a small region centered on the native conformations. The dissimilarities between the explicit and implicit model on the larger-scale point to the important role of water in mediating interactions between amino acid residues.

Ion-Pairing Contribution to the Liposomal Transport of Topotecan as Revealed by Mechanistic Modeling.

PubMed

Fugit, Kyle D; Anderson, Bradley D

2017-04-01

Actively loaded liposomal formulations of anticancer agents have been widely explored due to their high drug encapsulation efficiencies and prolonged drug retention. Mathematical models to predict and optimize drug loading and release kinetics from these nanoparticle formulations would be useful in their development and may allow researchers to tune release profiles. Such models must account for the driving forces as influenced by the physicochemical properties of the drug and the microenvironment, and the liposomal barrier properties. This study employed mechanistic modeling to describe the active liposomal loading and release kinetics of the anticancer agent topotecan (TPT). The model incorporates ammonia transport resulting in generation of a pH gradient, TPT dimerization, TPT lactone ring-opening and -closing interconversion kinetics, chloride transport, and transport of TPT-chloride ion-pairs to describe the active loading and release kinetics of TPT in the presence of varying chloride concentrations. Model-based predictions of the kinetics of active loading at varying loading concentrations of TPT and release under dynamic dialysis conditions were in reasonable agreement with experiments. These findings identify key attributes to consider in optimizing and predicting loading and release of liposomal TPT that may also be applicable to liposomal formulations of other weakly basic pharmaceuticals. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Integrated analysis of dynamic FET PET/CT parameters, histology, and methylation profiling of 44 gliomas.

PubMed

Röhrich, Manuel; Huang, Kristin; Schrimpf, Daniel; Albert, Nathalie L; Hielscher, Thomas; von Deimling, Andreas; Schüller, Ulrich; Dimitrakopoulou-Strauss, Antonia; Haberkorn, Uwe

2018-05-07

Dynamic 18 F-FET PET/CT is a powerful tool for the diagnosis of gliomas. 18 F-FET PET time-activity curves (TAC) allow differentiation between histological low-grade gliomas (LGG) and high-grade gliomas (HGG). Molecular methods such as epigenetic profiling are of rising importance for glioma grading and subclassification. Here, we analysed dynamic 18 F-FET PET data, and the histological and epigenetic features of 44 gliomas. Dynamic 18 F-FET PET was performed in 44 patients with newly diagnosed, untreated glioma: 10 WHO grade II glioma, 13 WHO grade III glioma and 21 glioblastoma (GBM). All patients underwent stereotactic biopsy or tumour resection after 18 F-FET PET imaging. As well as histological analysis of tissue samples, DNA was subjected to epigenetic analysis using the Illumina 850 K methylation array. TACs, standardized uptake values corrected for background uptake in healthy tissue (SUVmax/BG), time to peak (TTP) and kinetic modelling parameters were correlated with histological diagnoses and with epigenetic signatures. Multivariate analyses were performed to evaluate the diagnostic accuracy of 18 F-FET PET in relation to the tumour groups identified by histological and methylation-based analysis. Epigenetic profiling led to substantial tumour reclassification, with six grade II/III gliomas reclassified as GBM. Overlap of HGG-typical TACs and LGG-typical TACs was dramatically reduced when tumours were clustered on the basis of their methylation profile. SUVmax/BG values of GBM were higher than those of LGGs following both histological diagnosis and methylation-based diagnosis. The differences in TTP between GBMs and grade II/III gliomas were greater following methylation-based diagnosis than following histological diagnosis. Kinetic modeling showed that relative K1 and fractal dimension (FD) values significantly differed in histology- and methylation-based GBM and grade II/III glioma between those diagnosed histologically and those diagnosed by methylation analysis. Multivariate analysis revealed slightly greater diagnostic accuracy with methylation-based diagnosis. IDH-mutant gliomas and GBM subgroups tended to differ in their 18 F-FET PET kinetics. The status of dynamic 18 F-FET PET as a biologically and clinically relevant imaging modality is confirmed in the context of molecular glioma diagnosis.

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

PubMed Central

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

2009-01-01

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

A Kinetic Model for Calcium Dynamics in RAW 264.7 Cells: 1. Mechanisms, Parameters, and Subpopulational Variability

PubMed Central

Maurya, Mano Ram; Subramaniam, Shankar

2007-01-01

Calcium (Ca2+) is an important second messenger and has been the subject of numerous experimental measurements and mechanistic studies in intracellular signaling. Calcium profile can also serve as a useful cellular phenotype. Kinetic models of calcium dynamics provide quantitative insights into the calcium signaling networks. We report here the development of a complex kinetic model for calcium dynamics in RAW 264.7 cells stimulated by the C5a ligand. The model is developed using the vast number of measurements of in vivo calcium dynamics carried out in the Alliance for Cellular Signaling (AfCS) Laboratories. Ligand binding, phospholipase C-β (PLC-β) activation, inositol 1,4,5-trisphosphate (IP3) receptor (IP3R) dynamics, and calcium exchange with mitochondria and extracellular matrix have all been incorporated into the model. The experimental data include data from both native and knockdown cell lines. Subpopulational variability in measurements is addressed by allowing nonkinetic parameters to vary across datasets. The model predicts temporal response of Ca2+ concentration for various doses of C5a under different initial conditions. The optimized parameters for IP3R dynamics are in agreement with the legacy data. Further, the half-maximal effect concentration of C5a and the predicted dose response are comparable to those seen in AfCS measurements. Sensitivity analysis shows that the model is robust to parametric perturbations. PMID:17483174

Canonical formalism for modelling and control of rigid body dynamics.

PubMed

Gurfil, P

2005-12-01

This paper develops a new paradigm for stabilization of rigid-body dynamics. The state-space model is formulated using canonical elements, known as the Serret-Andoyer (SA) variables, thus far scarcely used for engineering applications. The main feature of the SA formalism is the reduction of the dynamics via the underlying symmetry stemming from conservation of angular momentum and rotational kinetic energy. The controllability of the system model is examined using the notion of accessibility, and is shown to be accessible from all points. Based on the accessibility proof, two nonlinear asymptotic feedback stabilizers are developed: a damping feedback is designed based on the Jurdjevic-Quinn method, and a Hamiltonian controller is derived by using the Hamiltonian as a natural Lyapunov function for the closed-loop dynamics. It is shown that the Hamiltonian control is both passive and inverse optimal with respect to a meaningful performance index. The performance of the new controllers is examined and compared using simulations of realistic scenarios from the satellite attitude dynamics field.

New insights into the complex regulation of the glycolytic pathway in Lactococcus lactis. I. Construction and diagnosis of a comprehensive dynamic model.

PubMed

Dolatshahi, Sepideh; Fonseca, Luis L; Voit, Eberhard O

2016-01-01

This article and the companion paper use computational systems modeling to decipher the complex coordination of regulatory signals controlling the glycolytic pathway in the dairy bacterium Lactococcus lactis. In this first article, the development of a comprehensive kinetic dynamic model is described. The model is based on in vivo NMR data that consist of concentration trends in key glycolytic metabolites and cofactors. The model structure and parameter values are identified with a customized optimization strategy that uses as its core the method of dynamic flux estimation. For the first time, a dynamic model with a single parameter set fits all available glycolytic time course data under anaerobic operation. The model captures observations that had not been addressed so far and suggests the existence of regulatory effects that had been observed in other species, but not in L. lactis. The companion paper uses this model to analyze details of the dynamic control of glycolysis under aerobic and anaerobic conditions.

A dynamical model of plasma turbulence in the solar wind

PubMed Central

Howes, G. G.

2015-01-01

A dynamical approach, rather than the usual statistical approach, is taken to explore the physical mechanisms underlying the nonlinear transfer of energy, the damping of the turbulent fluctuations, and the development of coherent structures in kinetic plasma turbulence. It is argued that the linear and nonlinear dynamics of Alfvén waves are responsible, at a very fundamental level, for some of the key qualitative features of plasma turbulence that distinguish it from hydrodynamic turbulence, including the anisotropic cascade of energy and the development of current sheets at small scales. The first dynamical model of kinetic turbulence in the weakly collisional solar wind plasma that combines self-consistently the physics of Alfvén waves with the development of small-scale current sheets is presented and its physical implications are discussed. This model leads to a simplified perspective on the nature of turbulence in a weakly collisional plasma: the nonlinear interactions responsible for the turbulent cascade of energy and the formation of current sheets are essentially fluid in nature, while the collisionless damping of the turbulent fluctuations and the energy injection by kinetic instabilities are essentially kinetic in nature. PMID:25848075

Modeling of Tracer Transport Delays for Improved Quantification of Regional Pulmonary 18F-FDG Kinetics, Vascular Transit Times, and Perfusion

PubMed Central

Wellman, Tyler J.; Winkler, Tilo; Vidal Melo, Marcos F.

2015-01-01

18F-FDG-PET is increasingly used to assess pulmonary inflammatory cell activity. However, current models of pulmonary 18F-FDG kinetics do not account for delays in 18F-FDG transport between the plasma sampling site and the lungs. We developed a three-compartment model of 18F-FDG kinetics that includes a delay between the right heart and the local capillary blood pool, and used this model to estimate regional pulmonary perfusion. We acquired dynamic 18F-FDG scans in 12 mechanically ventilated sheep divided into control and lung injury groups (n=6 each). The model was fit to tracer kinetics in three isogravitational regions-of-interest to estimate regional lung transport delays and regional perfusion. 13NN bolus infusion scans were acquired during a period of apnea to measure regional perfusion using an established reference method. The delayed input function model improved description of 18F-FDG kinetics (lower Akaike Information Criterion) in 98% of studied regions. Local transport delays ranged from 2.0–13.6s, averaging 6.4±2.9s, and were highest in non-dependent regions. Estimates of regional perfusion derived from model parameters were highly correlated with perfusion measurements based on 13NN-PET (R2=0.92, p<0.001). By incorporating local vascular transports delays, this model of pulmonary 18F-FDG kinetics allows for simultaneous assessment of regional lung perfusion, transit times, and inflammation. PMID:25940652

MR-guided dynamic PET reconstruction with the kernel method and spectral temporal basis functions

NASA Astrophysics Data System (ADS)

Novosad, Philip; Reader, Andrew J.

2016-06-01

Recent advances in dynamic positron emission tomography (PET) reconstruction have demonstrated that it is possible to achieve markedly improved end-point kinetic parameter maps by incorporating a temporal model of the radiotracer directly into the reconstruction algorithm. In this work we have developed a highly constrained, fully dynamic PET reconstruction algorithm incorporating both spectral analysis temporal basis functions and spatial basis functions derived from the kernel method applied to a co-registered T1-weighted magnetic resonance (MR) image. The dynamic PET image is modelled as a linear combination of spatial and temporal basis functions, and a maximum likelihood estimate for the coefficients can be found using the expectation-maximization (EM) algorithm. Following reconstruction, kinetic fitting using any temporal model of interest can be applied. Based on a BrainWeb T1-weighted MR phantom, we performed a realistic dynamic [18F]FDG simulation study with two noise levels, and investigated the quantitative performance of the proposed reconstruction algorithm, comparing it with reconstructions incorporating either spectral analysis temporal basis functions alone or kernel spatial basis functions alone, as well as with conventional frame-independent reconstruction. Compared to the other reconstruction algorithms, the proposed algorithm achieved superior performance, offering a decrease in spatially averaged pixel-level root-mean-square-error on post-reconstruction kinetic parametric maps in the grey/white matter, as well as in the tumours when they were present on the co-registered MR image. When the tumours were not visible in the MR image, reconstruction with the proposed algorithm performed similarly to reconstruction with spectral temporal basis functions and was superior to both conventional frame-independent reconstruction and frame-independent reconstruction with kernel spatial basis functions. Furthermore, we demonstrate that a joint spectral/kernel model can also be used for effective post-reconstruction denoising, through the use of an EM-like image-space algorithm. Finally, we applied the proposed algorithm to reconstruction of real high-resolution dynamic [11C]SCH23390 data, showing promising results.

MR-guided dynamic PET reconstruction with the kernel method and spectral temporal basis functions.

PubMed

Novosad, Philip; Reader, Andrew J

2016-06-21

Recent advances in dynamic positron emission tomography (PET) reconstruction have demonstrated that it is possible to achieve markedly improved end-point kinetic parameter maps by incorporating a temporal model of the radiotracer directly into the reconstruction algorithm. In this work we have developed a highly constrained, fully dynamic PET reconstruction algorithm incorporating both spectral analysis temporal basis functions and spatial basis functions derived from the kernel method applied to a co-registered T1-weighted magnetic resonance (MR) image. The dynamic PET image is modelled as a linear combination of spatial and temporal basis functions, and a maximum likelihood estimate for the coefficients can be found using the expectation-maximization (EM) algorithm. Following reconstruction, kinetic fitting using any temporal model of interest can be applied. Based on a BrainWeb T1-weighted MR phantom, we performed a realistic dynamic [(18)F]FDG simulation study with two noise levels, and investigated the quantitative performance of the proposed reconstruction algorithm, comparing it with reconstructions incorporating either spectral analysis temporal basis functions alone or kernel spatial basis functions alone, as well as with conventional frame-independent reconstruction. Compared to the other reconstruction algorithms, the proposed algorithm achieved superior performance, offering a decrease in spatially averaged pixel-level root-mean-square-error on post-reconstruction kinetic parametric maps in the grey/white matter, as well as in the tumours when they were present on the co-registered MR image. When the tumours were not visible in the MR image, reconstruction with the proposed algorithm performed similarly to reconstruction with spectral temporal basis functions and was superior to both conventional frame-independent reconstruction and frame-independent reconstruction with kernel spatial basis functions. Furthermore, we demonstrate that a joint spectral/kernel model can also be used for effective post-reconstruction denoising, through the use of an EM-like image-space algorithm. Finally, we applied the proposed algorithm to reconstruction of real high-resolution dynamic [(11)C]SCH23390 data, showing promising results.

Modeling dynamic beta-gamma polymorphic transition in Tin

NASA Astrophysics Data System (ADS)

Chauvin, Camille; Montheillet, Frank; Petit, Jacques; CEA Gramat Collaboration; EMSE Collaboration

2015-06-01

Solid-solid phase transitions in metals have been studied by shock waves techniques for many decades. Recent experiments have investigated the transition during isentropic compression experiments and shock-wave compression and have highlighted the strong influence of the loading rate on the transition. Complementary data obtained with velocity and temperature measurements around the polymorphic transition beta-gamma of Tin on gas gun experiments have displayed the importance of the kinetics of the transition. But, even though this phenomenon is known, modeling the kinetic remains complex and based on empirical formulations. A multiphase EOS is available in our 1D Lagrangian code Unidim. We propose to present the influence of various kinetic laws (either empirical or involving nucleation and growth mechanisms) and their parameters (Gibbs free energy, temperature, pressure) on the transformation rate. We compare experimental and calculated velocities and temperature profiles and we underline the effects of the empirical parameters of these models.

Analytical solution of Luedeking-Piret equation for a batch fermentation obeying Monod growth kinetics.

PubMed

Garnier, Alain; Gaillet, Bruno

2015-12-01

Not so many fermentation mathematical models allow analytical solutions of batch process dynamics. The most widely used is the combination of the logistic microbial growth kinetics with Luedeking-Piret bioproduct synthesis relation. However, the logistic equation is principally based on formalistic similarities and only fits a limited range of fermentation types. In this article, we have developed an analytical solution for the combination of Monod growth kinetics with Luedeking-Piret relation, which can be identified by linear regression and used to simulate batch fermentation evolution. Two classical examples are used to show the quality of fit and the simplicity of the method proposed. A solution for the combination of Haldane substrate-limited growth model combined with Luedeking-Piret relation is also provided. These models could prove useful for the analysis of fermentation data in industry as well as academia. © 2015 Wiley Periodicals, Inc.

A Model-based B2B (Batch to Batch) Control for An Industrial Batch Polymerization Process

NASA Astrophysics Data System (ADS)

Ogawa, Morimasa

This paper describes overview of a model-based B2B (batch to batch) control for an industrial batch polymerization process. In order to control the reaction temperature precisely, several methods based on the rigorous process dynamics model are employed at all design stage of the B2B control, such as modeling and parameter estimation of the reaction kinetics which is one of the important part of the process dynamics model. The designed B2B control consists of the gain scheduled I-PD/II2-PD control (I-PD with double integral control), the feed-forward compensation at the batch start time, and the model adaptation utilizing the results of the last batch operation. Throughout the actual batch operations, the B2B control provides superior control performance compared with that of conventional control methods.

Teaching Thermodynamics with Physlets[R] in Introductory Physics

ERIC Educational Resources Information Center

Cox, Anne J.; Belloni, Mario; Dancy, Melissa; Christian, Wolfgang

2003-01-01

This paper describes the use of interactive, Physlet[R]-based curricular material designed to help students learn concepts of thermodynamics with a particular focus on the use of kinetic theory models. These exercises help students visualize ideal gas particle dynamics and engine cycles, make concrete connections between mechanics and…

Dynamic Modeling of Cell-Free Biochemical Networks Using Effective Kinetic Models

DTIC Science & Technology

2015-03-16

sensitivity value was the maximum uncertainty in that value estimated by the Sobol method. 2.4. Global Sensitivity Analysis of the Reduced Order Coagulation...sensitivity analysis, using the variance-based method of Sobol , to estimate which parameters controlled the performance of the reduced order model [69]. We...Environment. Comput. Sci. Eng. 2007, 9, 90–95. 69. Sobol , I. Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates

Freezing in stripe states for kinetic Ising models: a comparative study of three dynamics

NASA Astrophysics Data System (ADS)

Godrèche, Claude; Pleimling, Michel

2018-04-01

We present a comparative study of the fate of an Ising ferromagnet on the square lattice with periodic boundary conditions evolving under three different zero-temperature dynamics. The first one is Glauber dynamics, the two other dynamics correspond to two limits of the directed Ising model, defined by rules that break the full symmetry of the former, yet sharing the same Boltzmann-Gibbs distribution at stationarity. In one of these limits the directed Ising model is reversible, in the other one it is irreversible. For the kinetic Ising-Glauber model, several recent studies have demonstrated the role of critical percolation to predict the probabilities for the system to reach the ground state or to fall in a metastable state. We investigate to what extent the predictions coming from critical percolation still apply to the two other dynamics.

A hybrid model describing ion induced kinetic electron emission

NASA Astrophysics Data System (ADS)

Hanke, S.; Duvenbeck, A.; Heuser, C.; Weidtmann, B.; Wucher, A.

2015-06-01

We present a model to describe the kinetic internal and external electron emission from an ion bombarded metal target. The model is based upon a molecular dynamics treatment of the nuclear degree of freedom, the electronic system is assumed as a quasi-free electron gas characterized by its Fermi energy, electron temperature and a characteristic attenuation length. In a series of previous works we have employed this model, which includes the local kinetic excitation as well as the rapid spread of the generated excitation energy, in order to calculate internal and external electron emission yields within the framework of a Richardson-Dushman-like thermionic emission model. However, this kind of treatment turned out to fail in the realistic prediction of experimentally measured internal electron yields mainly due to the restriction of the treatment of electronic transport to a diffusive manner. Here, we propose a slightly modified approach additionally incorporating the contribution of hot electrons which are generated in the bulk material and undergo ballistic transport towards the emitting interface.

Nonlinear saturation of the slab ITG instability and zonal flow generation with fully kinetic ions

NASA Astrophysics Data System (ADS)

Miecnikowski, Matthew T.; Sturdevant, Benjamin J.; Chen, Yang; Parker, Scott E.

2018-05-01

Fully kinetic turbulence models are of interest for their potential to validate or replace gyrokinetic models in plasma regimes where the gyrokinetic expansion parameters are marginal. Here, we demonstrate fully kinetic ion capability by simulating the growth and nonlinear saturation of the ion-temperature-gradient instability in shearless slab geometry assuming adiabatic electrons and including zonal flow dynamics. The ion trajectories are integrated using the Lorentz force, and the cyclotron motion is fully resolved. Linear growth and nonlinear saturation characteristics show excellent agreement with analogous gyrokinetic simulations across a wide range of parameters. The fully kinetic simulation accurately reproduces the nonlinearly generated zonal flow. This work demonstrates nonlinear capability, resolution of weak gradient drive, and zonal flow physics, which are critical aspects of modeling plasma turbulence with full ion dynamics.

A possible mechanism of metabolic regulation in Gibberella fujikuroi using a mixed carbon source of glucose and corn oil inferred from analysis of the kinetics data obtained in a stirrer tank bioreactor.

PubMed

Rios-Iribe, Erika Y; Hernández-Calderón, Oscar M; Reyes-Moreno, C; Contreras-Andrade, I; Flores-Cotera, Luis B; Escamilla-Silva, Eleazar M

2013-01-01

A nonstructured model was used to study the dynamics of gibberellic acid production in a stirred tank bioreactor. Experimental data were obtained from submerged batch cultures of Gibberella fujikuroi (CDBB H-984) grown in varying ratios of glucose-corn oil as the carbon source. The nitrogen depletion effect was included in mathematical model by considering the specific kinetic constants as a linear function of the normalized nitrogen consumption rate. The kinetics of biomass growth and consumption of phosphate and nitrogen were based on the logistic model. The traditional first-order kinetic model was used to describe the specific consumption of glucose and corn oil. The nitrogen effect was solely included in the phosphate and corn oil consumption and biomass growth. The model fit was satisfactory, revealing the dependence of the kinetics with respect to the nitrogen assimilation rate. Through simulations, it was possible to make diagrams of specific growth rate and specific rate of substrate consumptions, which was a powerful tool for understanding the metabolic interactions that occurred during the various stages of fermentation process. This kinetic analysis provided the proposal of a possible mechanism of regulation on growth, substrate consumptions, and production of gibberellic acid (GA3 ) in G. fujikuroi. © 2013 American Institute of Chemical Engineers.

Dynamic contrast-enhanced CT of head and neck tumors: perfusion measurements using a distributed-parameter tracer kinetic model. Initial results and comparison with deconvolution-based analysis

NASA Astrophysics Data System (ADS)

Bisdas, Sotirios; Konstantinou, George N.; Sherng Lee, Puor; Thng, Choon Hua; Wagenblast, Jens; Baghi, Mehran; San Koh, Tong

2007-10-01

The objective of this work was to evaluate the feasibility of a two-compartment distributed-parameter (DP) tracer kinetic model to generate functional images of several physiologic parameters from dynamic contrast-enhanced CT data obtained of patients with extracranial head and neck tumors and to compare the DP functional images to those obtained by deconvolution-based DCE-CT data analysis. We performed post-processing of DCE-CT studies, obtained from 15 patients with benign and malignant head and neck cancer. We introduced a DP model of the impulse residue function for a capillary-tissue exchange unit, which accounts for the processes of convective transport and capillary-tissue exchange. The calculated parametric maps represented blood flow (F), intravascular blood volume (v1), extravascular extracellular blood volume (v2), vascular transit time (t1), permeability-surface area product (PS), transfer ratios k12 and k21, and the fraction of extracted tracer (E). Based on the same regions of interest (ROI) analysis, we calculated the tumor blood flow (BF), blood volume (BV) and mean transit time (MTT) by using a modified deconvolution-based analysis taking into account the extravasation of the contrast agent for PS imaging. We compared the corresponding values by using Bland-Altman plot analysis. We outlined 73 ROIs including tumor sites, lymph nodes and normal tissue. The Bland-Altman plot analysis revealed that the two methods showed an accepted degree of agreement for blood flow, and, thus, can be used interchangeably for measuring this parameter. Slightly worse agreement was observed between v1 in the DP model and BV but even here the two tracer kinetic analyses can be used interchangeably. Under consideration of whether both techniques may be used interchangeably was the case of t1 and MTT, as well as for measurements of the PS values. The application of the proposed DP model is feasible in the clinical routine and it can be used interchangeably for measuring blood flow and vascular volume with the commercially available reference standard of the deconvolution-based approach. The lack of substantial agreement between the measurements of vascular transit time and permeability-surface area product may be attributed to the different tracer kinetic principles employed by both models and the detailed capillary tissue exchange physiological modeling of the DP technique.

How to Run FAST Simulations.

PubMed

Zimmerman, M I; Bowman, G R

2016-01-01

Molecular dynamics (MD) simulations are a powerful tool for understanding enzymes' structures and functions with full atomistic detail. These physics-based simulations model the dynamics of a protein in solution and store snapshots of its atomic coordinates at discrete time intervals. Analysis of the snapshots from these trajectories provides thermodynamic and kinetic properties such as conformational free energies, binding free energies, and transition times. Unfortunately, simulating biologically relevant timescales with brute force MD simulations requires enormous computing resources. In this chapter we detail a goal-oriented sampling algorithm, called fluctuation amplification of specific traits, that quickly generates pertinent thermodynamic and kinetic information by using an iterative series of short MD simulations to explore the vast depths of conformational space. © 2016 Elsevier Inc. All rights reserved.

Systems biology from micro-organisms to human metabolic diseases: the role of detailed kinetic models.

PubMed

Bakker, Barbara M; van Eunen, Karen; Jeneson, Jeroen A L; van Riel, Natal A W; Bruggeman, Frank J; Teusink, Bas

2010-10-01

Human metabolic diseases are typically network diseases. This holds not only for multifactorial diseases, such as metabolic syndrome or Type 2 diabetes, but even when a single gene defect is the primary cause, where the adaptive response of the entire network determines the severity of disease. The latter may differ between individuals carrying the same mutation. Understanding the adaptive responses of human metabolism naturally requires a systems biology approach. Modelling of metabolic pathways in micro-organisms and some mammalian tissues has yielded many insights, qualitative as well as quantitative, into their control and regulation. Yet, even for a well-known pathway such as glycolysis, precise predictions of metabolite dynamics from experimentally determined enzyme kinetics have been only moderately successful. In the present review, we compare kinetic models of glycolysis in three cell types (African trypanosomes, yeast and skeletal muscle), evaluate their predictive power and identify limitations in our understanding. Although each of these models has its own merits and shortcomings, they also share common features. For example, in each case independently measured enzyme kinetic parameters were used as input. Based on these 'lessons from glycolysis', we will discuss how to make best use of kinetic computer models to advance our understanding of human metabolic diseases.

Monte-Carlo Modeling of the Central Carbon Metabolism of Lactococcus lactis: Insights into Metabolic Regulation

PubMed Central

Murabito, Ettore; Verma, Malkhey; Bekker, Martijn; Bellomo, Domenico; Westerhoff, Hans V.; Teusink, Bas; Steuer, Ralf

2014-01-01

Metabolic pathways are complex dynamic systems whose response to perturbations and environmental challenges are governed by multiple interdependencies between enzyme properties, reactions rates, and substrate levels. Understanding the dynamics arising from such a network can be greatly enhanced by the construction of a computational model that embodies the properties of the respective system. Such models aim to incorporate mechanistic details of cellular interactions to mimic the temporal behavior of the biochemical reaction system and usually require substantial knowledge of kinetic parameters to allow meaningful conclusions. Several approaches have been suggested to overcome the severe data requirements of kinetic modeling, including the use of approximative kinetics and Monte-Carlo sampling of reaction parameters. In this work, we employ a probabilistic approach to study the response of a complex metabolic system, the central metabolism of the lactic acid bacterium Lactococcus lactis, subject to perturbations and brief periods of starvation. Supplementing existing methodologies, we show that it is possible to acquire a detailed understanding of the control properties of a corresponding metabolic pathway model that is directly based on experimental observations. In particular, we delineate the role of enzymatic regulation to maintain metabolic stability and metabolic recovery after periods of starvation. It is shown that the feedforward activation of the pyruvate kinase by fructose-1,6-bisphosphate qualitatively alters the bifurcation structure of the corresponding pathway model, indicating a crucial role of enzymatic regulation to prevent metabolic collapse for low external concentrations of glucose. We argue that similar probabilistic methodologies will help our understanding of dynamic properties of small-, medium- and large-scale metabolic networks models. PMID:25268481

Quantifying heterogeneity of lesion uptake in dynamic contrast enhanced MRI for breast cancer diagnosis

NASA Astrophysics Data System (ADS)

Karahaliou, A.; Vassiou, K.; Skiadopoulos, S.; Kanavou, T.; Yiakoumelos, A.; Costaridou, L.

2009-07-01

The current study investigates whether texture features extracted from lesion kinetics feature maps can be used for breast cancer diagnosis. Fifty five women with 57 breast lesions (27 benign, 30 malignant) were subjected to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) on 1.5T system. A linear-slope model was fitted pixel-wise to a representative lesion slice time series and fitted parameters were used to create three kinetic maps (wash out, time to peak enhancement and peak enhancement). 28 grey level co-occurrence matrices features were extracted from each lesion kinetic map. The ability of texture features per map in discriminating malignant from benign lesions was investigated using a Probabilistic Neural Network classifier. Additional classification was performed by combining classification outputs of most discriminating feature subsets from the three maps, via majority voting. The combined scheme outperformed classification based on individual maps achieving area under Receiver Operating Characteristics curve 0.960±0.029. Results suggest that heterogeneity of breast lesion kinetics, as quantified by texture analysis, may contribute to computer assisted tissue characterization in DCE-MRI.

Programming chemical kinetics: engineering dynamic reaction networks with DNA strand displacement

NASA Astrophysics Data System (ADS)

Srinivas, Niranjan

Over the last century, the silicon revolution has enabled us to build faster, smaller and more sophisticated computers. Today, these computers control phones, cars, satellites, assembly lines, and other electromechanical devices. Just as electrical wiring controls electromechanical devices, living organisms employ "chemical wiring" to make decisions about their environment and control physical processes. Currently, the big difference between these two substrates is that while we have the abstractions, design principles, verification and fabrication techniques in place for programming with silicon, we have no comparable understanding or expertise for programming chemistry. In this thesis we take a small step towards the goal of learning how to systematically engineer prescribed non-equilibrium dynamical behaviors in chemical systems. We use the formalism of chemical reaction networks (CRNs), combined with mass-action kinetics, as our programming language for specifying dynamical behaviors. Leveraging the tools of nucleic acid nanotechnology (introduced in Chapter 1), we employ synthetic DNA molecules as our molecular architecture and toehold-mediated DNA strand displacement as our reaction primitive. Abstraction, modular design and systematic fabrication can work only with well-understood and quantitatively characterized tools. Therefore, we embark on a detailed study of the "device physics" of DNA strand displacement (Chapter 2). We present a unified view of strand displacement biophysics and kinetics by studying the process at multiple levels of detail, using an intuitive model of a random walk on a 1-dimensional energy landscape, a secondary structure kinetics model with single base-pair steps, and a coarse-grained molecular model that incorporates three-dimensional geometric and steric effects. Further, we experimentally investigate the thermodynamics of three-way branch migration. Our findings are consistent with previously measured or inferred rates for hybridization, fraying, and branch migration, and provide a biophysical explanation of strand displacement kinetics. Our work paves the way for accurate modeling of strand displacement cascades, which would facilitate the simulation and construction of more complex molecular systems. In Chapters 3 and 4, we identify and overcome the crucial experimental challenges involved in using our general DNA-based technology for engineering dynamical behaviors in the test tube. In this process, we identify important design rules that inform our choice of molecular motifs and our algorithms for designing and verifying DNA sequences for our molecular implementation. We also develop flexible molecular strategies for "tuning" our reaction rates and stoichiometries in order to compensate for unavoidable non-idealities in the molecular implementation, such as imperfectly synthesized molecules and spurious "leak" pathways that compete with desired pathways. We successfully implement three distinct autocatalytic reactions, which we then combine into a de novo chemical oscillator. Unlike biological networks, which use sophisticated evolved molecules (like proteins) to realize such behavior, our test tube realization is the first to demonstrate that Watson-Crick base pairing interactions alone suffice for oscillatory dynamics. Since our design pipeline is general and applicable to any CRN, our experimental demonstration of a de novo chemical oscillator could enable the systematic construction of CRNs with other dynamic behaviors.

AdapChem

NASA Technical Reports Server (NTRS)

Oluwole, Oluwayemisi O.; Wong, Hsi-Wu; Green, William

2012-01-01

AdapChem software enables high efficiency, low computational cost, and enhanced accuracy on computational fluid dynamics (CFD) numerical simulations used for combustion studies. The software dynamically allocates smaller, reduced chemical models instead of the larger, full chemistry models to evolve the calculation while ensuring the same accuracy to be obtained for steady-state CFD reacting flow simulations. The software enables detailed chemical kinetic modeling in combustion CFD simulations. AdapChem adapts the reaction mechanism used in the CFD to the local reaction conditions. Instead of a single, comprehensive reaction mechanism throughout the computation, a dynamic distribution of smaller, reduced models is used to capture accurately the chemical kinetics at a fraction of the cost of the traditional single-mechanism approach.

A Thermodynamically-consistent FBA-based Approach to Biogeochemical Reaction Modeling

NASA Astrophysics Data System (ADS)

Shapiro, B.; Jin, Q.

2015-12-01

Microbial rates are critical to understanding biogeochemical processes in natural environments. Recently, flux balance analysis (FBA) has been applied to predict microbial rates in aquifers and other settings. FBA is a genome-scale constraint-based modeling approach that computes metabolic rates and other phenotypes of microorganisms. This approach requires a prior knowledge of substrate uptake rates, which is not available for most natural microbes. Here we propose to constrain substrate uptake rates on the basis of microbial kinetics. Specifically, we calculate rates of respiration (and fermentation) using a revised Monod equation; this equation accounts for both the kinetics and thermodynamics of microbial catabolism. Substrate uptake rates are then computed from the rates of respiration, and applied to FBA to predict rates of microbial growth. We implemented this method by linking two software tools, PHREEQC and COBRA Toolbox. We applied this method to acetotrophic methanogenesis by Methanosarcina barkeri, and compared the simulation results to previous laboratory observations. The new method constrains acetate uptake by accounting for the kinetics and thermodynamics of methanogenesis, and predicted well the observations of previous experiments. In comparison, traditional methods of dynamic-FBA constrain acetate uptake on the basis of enzyme kinetics, and failed to reproduce the experimental results. These results show that microbial rate laws may provide a better constraint than enzyme kinetics for applying FBA to biogeochemical reaction modeling.

Model colloid system for interfacial sorption kinetics

NASA Astrophysics Data System (ADS)

Salipante, Paul; Hudson, Steven

2014-11-01

Adsorption kinetics of nanometer scale molecules, such as proteins at interfaces, is usually determined through measurements of surface coverage. Their small size limits the ability to directly observe individual molecule behavior. To better understand the behavior of nanometer size molecules and the effect on interfacial kinetics, we use micron size colloids with a weak interfacial interaction potential as a model system. Thus, the interaction strength is comparable to many nanoscale systems (less than 10 kBT). The colloid-interface interaction potential is tuned using a combination of depletion, electrostatic, and gravitational forces. The colloids transition between an entropically trapped adsorbed state and a desorbed state through Brownian motion. Observations are made using an LED-based Total Internal Reflection Microscopy (TIRM) setup. The observed adsorption and desorption rates are compared theoretical predictions based on the measured interaction potential and near wall particle diffusivity. This experimental system also allows for the study of more complex dynamics such as nonspherical colloids and collective effects at higher concentrations.

Constructive methods of invariant manifolds for kinetic problems

NASA Astrophysics Data System (ADS)

Gorban, Alexander N.; Karlin, Iliya V.; Zinovyev, Andrei Yu.

2004-06-01

The concept of the slow invariant manifold is recognized as the central idea underpinning a transition from micro to macro and model reduction in kinetic theories. We present the Constructive Methods of Invariant Manifolds for model reduction in physical and chemical kinetics, developed during last two decades. The physical problem of reduced description is studied in the most general form as a problem of constructing the slow invariant manifold. The invariance conditions are formulated as the differential equation for a manifold immersed in the phase space ( the invariance equation). The equation of motion for immersed manifolds is obtained ( the film extension of the dynamics). Invariant manifolds are fixed points for this equation, and slow invariant manifolds are Lyapunov stable fixed points, thus slowness is presented as stability. A collection of methods to derive analytically and to compute numerically the slow invariant manifolds is presented. Among them, iteration methods based on incomplete linearization, relaxation method and the method of invariant grids are developed. The systematic use of thermodynamics structures and of the quasi-chemical representation allow to construct approximations which are in concordance with physical restrictions. The following examples of applications are presented: nonperturbative deviation of physically consistent hydrodynamics from the Boltzmann equation and from the reversible dynamics, for Knudsen numbers Kn∼1; construction of the moment equations for nonequilibrium media and their dynamical correction (instead of extension of list of variables) to gain more accuracy in description of highly nonequilibrium flows; determination of molecules dimension (as diameters of equivalent hard spheres) from experimental viscosity data; model reduction in chemical kinetics; derivation and numerical implementation of constitutive equations for polymeric fluids; the limits of macroscopic description for polymer molecules, etc.

Role of wave packet width in quantum molecular dynamics in fusion reactions near barrier

NASA Astrophysics Data System (ADS)

Cao, X. G.; Ma, Y. G.; Zhang, G. Q.; Wang, H. W.; Anastasi, A.; Curciarello, F.; De Leo, V.

2014-05-01

The dynamical fusion process of 48Ca + 144Sm with different impact parameters near barrier is studied by an extended quantum molecular dynamics (EQMD) model, where width of wavepacket is dynamically treated based on variational principle. The time evolution of different energy components such as potential energy, kinetic energy, Coulomb energy and Pauli potential are analyzed when dynamical or fixed width is assumed in calculation. It is found that the dynamical wavepacket width can enhance the dissipation of incident energy and the fluctuations, which are important to form compound nuclei. Moreover, we compare the fusion barrier dependence on the incident energy when it is determined by both dynamical and fixed wavepacket width.

Kinetic energy spectra, vertical resolution and dissipation in high-resolution atmospheric simulations.

NASA Astrophysics Data System (ADS)

Skamarock, W. C.

2017-12-01

We have performed week-long full-physics simulations with the MPAS global model at 15 km cell spacing using vertical mesh spacings of 800, 400, 200 and 100 meters in the mid-troposphere through the mid-stratosphere. We find that the horizontal kinetic energy spectra in the upper troposphere and stratosphere does not converge with increasing vertical resolution until we reach 200 meter level spacing. Examination of the solutions indicates that significant inertia-gravity waves are not vertically resolved at the lower vertical resolutions. Diagnostics from the simulations indicate that the primary kinetic energy dissipation results from the vertical mixing within the PBL parameterization and from the gravity-wave drag parameterization, with smaller but significant contributions from damping in the vertical transport scheme and from the horizontal filters in the dynamical core. Most of the kinetic energy dissipation in the free atmosphere occurs within breaking mid-latitude baroclinic waves. We will briefly review these results and their implications for atmospheric model configuration and for atmospheric dynamics, specifically that related to the dynamics associated with the mesoscale kinetic energy spectrum.

Multiensemble Markov models of molecular thermodynamics and kinetics.

PubMed

Wu, Hao; Paul, Fabian; Wehmeyer, Christoph; Noé, Frank

2016-06-07

We introduce the general transition-based reweighting analysis method (TRAM), a statistically optimal approach to integrate both unbiased and biased molecular dynamics simulations, such as umbrella sampling or replica exchange. TRAM estimates a multiensemble Markov model (MEMM) with full thermodynamic and kinetic information at all ensembles. The approach combines the benefits of Markov state models-clustering of high-dimensional spaces and modeling of complex many-state systems-with those of the multistate Bennett acceptance ratio of exploiting biased or high-temperature ensembles to accelerate rare-event sampling. TRAM does not depend on any rate model in addition to the widely used Markov state model approximation, but uses only fundamental relations such as detailed balance and binless reweighting of configurations between ensembles. Previous methods, including the multistate Bennett acceptance ratio, discrete TRAM, and Markov state models are special cases and can be derived from the TRAM equations. TRAM is demonstrated by efficiently computing MEMMs in cases where other estimators break down, including the full thermodynamics and rare-event kinetics from high-dimensional simulation data of an all-atom protein-ligand binding model.

DSC and curing kinetics study of epoxy grouting diluted with furfural -acetone slurry

NASA Astrophysics Data System (ADS)

Yin, H.; Sun, D. W.; Li, B.; Liu, Y. T.; Ran, Q. P.; Liu, J. P.

2016-07-01

The use of furfural-acetone slurry as active diluents of Bisphenol-A epoxy resin (DGEBA) groutings has been studied by dynamic and non-isothermal DSC for the first time. Curing kinetics study was investigated by non-isothermal differential scanning calorimetries at different heating rates. Activation enery (Ea) was calculated based on Kissinger and Ozawa Methods, and the results showed that Ea increased from 58.87 to 71.13KJ/mol after the diluents were added. The furfural-acetone epoxy matrix could cure completely at the theoretical curing temperature of 365.8K and the curing time of 139mins, which were determined by the kinetic model parameters.

Fluctuating bottleneck model studies on kinetics of DNA escape from α-hemolysin nanopores

NASA Astrophysics Data System (ADS)

Bian, Yukun; Wang, Zilin; Chen, Anpu; Zhao, Nanrong

2015-11-01

We have proposed a fluctuation bottleneck (FB) model to investigate the non-exponential kinetics of DNA escape from nanometer-scale pores. The basic idea is that the escape rate is proportional to the fluctuating cross-sectional area of DNA escape channel, the radius r of which undergoes a subdiffusion dynamics subjected to fractional Gaussian noise with power-law memory kernel. Such a FB model facilitates us to obtain the analytical result of the averaged survival probability as a function of time, which can be directly compared to experimental results. Particularly, we have applied our theory to address the escape kinetics of DNA through α-hemolysin nanopores. We find that our theoretical framework can reproduce the experimental results very well in the whole time range with quite reasonable estimation for the intrinsic parameters of the kinetics processes. We believe that FB model has caught some key features regarding the long time kinetics of DNA escape through a nanopore and it might provide a sound starting point to study much wider problems involving anomalous dynamics in confined fluctuating channels.

Thermodynamics of information processing based on enzyme kinetics: An exactly solvable model of an information pump

NASA Astrophysics Data System (ADS)

Cao, Yuansheng; Gong, Zongping; Quan, H. T.

2015-06-01

Motivated by the recent proposed models of the information engine [Proc. Natl. Acad. Sci. USA 109, 11641 (2012), 10.1073/pnas.1204263109] and the information refrigerator [Phys. Rev. Lett. 111, 030602 (2013), 10.1103/PhysRevLett.111.030602], we propose a minimal model of the information pump and the information eraser based on enzyme kinetics. This device can either pump molecules against the chemical potential gradient by consuming the information to be encoded in the bit stream or (partially) erase the information initially encoded in the bit stream by consuming the Gibbs free energy. The dynamics of this model is solved exactly, and the "phase diagram" of the operation regimes is determined. The efficiency and the power of the information machine is analyzed. The validity of the second law of thermodynamics within our model is clarified. Our model offers a simple paradigm for the investigating of the thermodynamics of information processing involving the chemical potential in small systems.

Water Dynamics in Egg White Peptide, Asp-His-Thr-Lys-Glu, Powder Monitored by Dynamic Vapor Sorption and LF-NMR.

PubMed

Yang, Shuailing; Liu, Xuye; Jin, Yan; Li, Xingfang; Chen, Feng; Zhang, Mingdi; Lin, Songyi

2016-03-16

Water absorbed into the bulk amorphous structure of peptides can have profound effects on their properties. Here, we elucidated water dynamics in Asp-His-Thr-Lys-Glu (DHTKE), an antioxidant peptide derived from egg white ovalbumin, using water dynamic vapor sorption (DVS) and low-field nuclear magnetic resonance (LF-NMR). The DVS results indicated that parallel exponential kinetics model fitted well to the data of sorption kinetics behavior of DHTKE. Four different proton fractions with different mobilities were identified based on the degree of interaction between peptide and water. The water could significantly change the proton distribution and structure of the sample. The different phases of moisture absorption were reflected in the T2 parameters. In addition, the combined water content was dominant in the hygroscopicity of DHTKE. This study provides an effective real-time monitoring method for water mobility and distribution in synthetic peptides, and this method may have applications in promoting peptide quality assurance.

Three-dimensional simulation of beam propagation and heat transfer in static gas Cs DPALs using wave optics and fluid dynamics models

NASA Astrophysics Data System (ADS)

Waichman, Karol; Barmashenko, Boris D.; Rosenwaks, Salman

2017-10-01

Analysis of beam propagation, kinetic and fluid dynamic processes in Cs diode pumped alkali lasers (DPALs), using wave optics model and gasdynamic code, is reported. The analysis is based on a three-dimensional, time-dependent computational fluid dynamics (3D CFD) model. The Navier-Stokes equations for momentum, heat and mass transfer are solved by a commercial Ansys FLUENT solver based on the finite volume discretization technique. The CFD code which solves the gas conservation equations includes effects of natural convection and temperature diffusion of the species in the DPAL mixture. The DPAL kinetic processes in the Cs/He/C2H6 gas mixture dealt with in this paper involve the three lowest energy levels of Cs, (1) 62S1/2, (2) 62P1/2 and (3) 62P3/2. The kinetic processes include absorption due to the 1->3 D2 transition followed by relaxation the 3 to 2 fine structure levels and stimulated emission due to the 2->1 D1 transition. Collisional quenching of levels 2 and 3 and spontaneous emission from these levels are also considered. The gas flow conservation equations are coupled to fast-Fourier-transform algorithm for transverse mode propagation to obtain a solution of the scalar paraxial propagation equation for the laser beam. The wave propagation equation is solved by the split-step beam propagation method where the gain and refractive index in the DPAL medium affect the wave amplitude and phase. Using the CFD and beam propagation models, the gas flow pattern and spatial distributions of the pump and laser intensities in the resonator were calculated for end-pumped Cs DPAL. The laser power, DPAL medium temperature and the laser beam quality were calculated as a function of pump power. The results of the theoretical model for laser power were compared to experimental results of Cs DPAL.

Real-time inverse kinematics and inverse dynamics for lower limb applications using OpenSim

PubMed Central

Modenese, L.; Lloyd, D.G.

2017-01-01

Real-time estimation of joint angles and moments can be used for rapid evaluation in clinical, sport, and rehabilitation contexts. However, real-time calculation of kinematics and kinetics is currently based on approximate solutions or generic anatomical models. We present a real-time system based on OpenSim solving inverse kinematics and dynamics without simplifications at 2000 frame per seconds with less than 31.5ms of delay. We describe the software architecture, sensitivity analyses to minimise delays and errors, and compare offline and real-time results. This system has the potential to strongly impact current rehabilitation practices enabling the use of personalised musculoskeletal models in real-time. PMID:27723992

Real-time inverse kinematics and inverse dynamics for lower limb applications using OpenSim.

PubMed

Pizzolato, C; Reggiani, M; Modenese, L; Lloyd, D G

2017-03-01

Real-time estimation of joint angles and moments can be used for rapid evaluation in clinical, sport, and rehabilitation contexts. However, real-time calculation of kinematics and kinetics is currently based on approximate solutions or generic anatomical models. We present a real-time system based on OpenSim solving inverse kinematics and dynamics without simplifications at 2000 frame per seconds with less than 31.5 ms of delay. We describe the software architecture, sensitivity analyses to minimise delays and errors, and compare offline and real-time results. This system has the potential to strongly impact current rehabilitation practices enabling the use of personalised musculoskeletal models in real-time.

Anomalous diffusion with linear reaction dynamics: from continuous time random walks to fractional reaction-diffusion equations.

PubMed

Henry, B I; Langlands, T A M; Wearne, S L

2006-09-01

We have revisited the problem of anomalously diffusing species, modeled at the mesoscopic level using continuous time random walks, to include linear reaction dynamics. If a constant proportion of walkers are added or removed instantaneously at the start of each step then the long time asymptotic limit yields a fractional reaction-diffusion equation with a fractional order temporal derivative operating on both the standard diffusion term and a linear reaction kinetics term. If the walkers are added or removed at a constant per capita rate during the waiting time between steps then the long time asymptotic limit has a standard linear reaction kinetics term but a fractional order temporal derivative operating on a nonstandard diffusion term. Results from the above two models are compared with a phenomenological model with standard linear reaction kinetics and a fractional order temporal derivative operating on a standard diffusion term. We have also developed further extensions of the CTRW model to include more general reaction dynamics.

Three-dimensional kinetic and fluid dynamic modeling and three iterative algorithms for side-pumped alkali vapor lasers

NASA Astrophysics Data System (ADS)

Shen, Binglin; Xu, Xingqi; Xia, Chunsheng; Pan, Bailiang

2017-11-01

Combining the kinetic and fluid dynamic processes in static and flowing-gas diode-pumped alkali vapor lasers, a comprehensive physical model with three cyclically iterative algorithms for simulating the three-dimensional pump and laser intensities as well as temperature distribution in the vapor cell of side-pumped alkali vapor lasers is established. Comparison with measurement of a static side-pumped cesium vapor laser with a diffuse type hollow cylinder cavity, and with classical and modified models is made. Influences of flowed velocity and pump power on laser power are calculated and analyzed. The results have demonstrated that for high-power side-pumped alkali vapor lasers, it is necessary to take into account the three-dimensional distributions of pump energy, laser energy and temperature in the cell to simultaneously obtain the thermal features and output characteristics. Therefore, the model can deepen the understanding of the complete kinetic and fluid dynamic mechanisms of a side-pumped alkali vapor laser, and help with its further experimental design.

Wave kinetics of random fibre lasers

PubMed Central

Churkin, D V.; Kolokolov, I V.; Podivilov, E V.; Vatnik, I D.; Nikulin, M A.; Vergeles, S S.; Terekhov, I S.; Lebedev, V V.; Falkovich, G.; Babin, S A.; Turitsyn, S K.

2015-01-01

Traditional wave kinetics describes the slow evolution of systems with many degrees of freedom to equilibrium via numerous weak non-linear interactions and fails for very important class of dissipative (active) optical systems with cyclic gain and losses, such as lasers with non-linear intracavity dynamics. Here we introduce a conceptually new class of cyclic wave systems, characterized by non-uniform double-scale dynamics with strong periodic changes of the energy spectrum and slow evolution from cycle to cycle to a statistically steady state. Taking a practically important example—random fibre laser—we show that a model describing such a system is close to integrable non-linear Schrödinger equation and needs a new formalism of wave kinetics, developed here. We derive a non-linear kinetic theory of the laser spectrum, generalizing the seminal linear model of Schawlow and Townes. Experimental results agree with our theory. The work has implications for describing kinetics of cyclical systems beyond photonics. PMID:25645177

Dynamic and Thermal Turbulent Time Scale Modelling for Homogeneous Shear Flows

NASA Technical Reports Server (NTRS)

Schwab, John R.; Lakshminarayana, Budugur

1994-01-01

A new turbulence model, based upon dynamic and thermal turbulent time scale transport equations, is developed and applied to homogeneous shear flows with constant velocity and temperature gradients. The new model comprises transport equations for k, the turbulent kinetic energy; tau, the dynamic time scale; k(sub theta), the fluctuating temperature variance; and tau(sub theta), the thermal time scale. It offers conceptually parallel modeling of the dynamic and thermal turbulence at the two equation level, and eliminates the customary prescription of an empirical turbulent Prandtl number, Pr(sub t), thus permitting a more generalized prediction capability for turbulent heat transfer in complex flows and geometries. The new model also incorporates constitutive relations, based upon invariant theory, that allow the effects of nonequilibrium to modify the primary coefficients for the turbulent shear stress and heat flux. Predictions of the new model, along with those from two other similar models, are compared with experimental data for decaying homogeneous dynamic and thermal turbulence, homogeneous turbulence with constant temperature gradient, and homogeneous turbulence with constant temperature gradient and constant velocity gradient. The new model offers improvement in agreement with the data for most cases considered in this work, although it was no better than the other models for several cases where all the models performed poorly.

Aromatic sulfonation with sulfur trioxide: mechanism and kinetic model.

PubMed

Moors, Samuel L C; Deraet, Xavier; Van Assche, Guy; Geerlings, Paul; De Proft, Frank

2017-01-01

Electrophilic aromatic sulfonation of benzene with sulfur trioxide is studied with ab initio molecular dynamics simulations in gas phase, and in explicit noncomplexing (CCl 3 F) and complexing (CH 3 NO 2 ) solvent models. We investigate different possible reaction pathways, the number of SO 3 molecules participating in the reaction, and the influence of the solvent. Our simulations confirm the existence of a low-energy concerted pathway with formation of a cyclic transition state with two SO 3 molecules. Based on the simulation results, we propose a sequence of elementary reaction steps and a kinetic model compatible with experimental data. Furthermore, a new alternative reaction pathway is proposed in complexing solvent, involving two SO 3 and one CH 3 NO 2 .

Hybrid plasma modeling.

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

Hopkins, Matthew Morgan; DeChant, Lawrence Justin.; Piekos, Edward Stanley

2009-02-01

This report summarizes the work completed during FY2007 and FY2008 for the LDRD project ''Hybrid Plasma Modeling''. The goal of this project was to develop hybrid methods to model plasmas across the non-continuum-to-continuum collisionality spectrum. The primary methodology to span these regimes was to couple a kinetic method (e.g., Particle-In-Cell) in the non-continuum regions to a continuum PDE-based method (e.g., finite differences) in continuum regions. The interface between the two would be adjusted dynamically ased on statistical sampling of the kinetic results. Although originally a three-year project, it became clear during the second year (FY2008) that there were not sufficientmore » resources to complete the project and it was terminated mid-year.« less

Computation of restoration of ligand response in the random kinetics of a prostate cancer cell signaling pathway.

PubMed

Dana, Saswati; Nakakuki, Takashi; Hatakeyama, Mariko; Kimura, Shuhei; Raha, Soumyendu

2011-01-01

Mutation and/or dysfunction of signaling proteins in the mitogen activated protein kinase (MAPK) signal transduction pathway are frequently observed in various kinds of human cancer. Consistent with this fact, in the present study, we experimentally observe that the epidermal growth factor (EGF) induced activation profile of MAP kinase signaling is not straightforward dose-dependent in the PC3 prostate cancer cells. To find out what parameters and reactions in the pathway are involved in this departure from the normal dose-dependency, a model-based pathway analysis is performed. The pathway is mathematically modeled with 28 rate equations yielding those many ordinary differential equations (ODE) with kinetic rate constants that have been reported to take random values in the existing literature. This has led to us treating the ODE model of the pathways kinetics as a random differential equations (RDE) system in which the parameters are random variables. We show that our RDE model captures the uncertainty in the kinetic rate constants as seen in the behavior of the experimental data and more importantly, upon simulation, exhibits the abnormal EGF dose-dependency of the activation profile of MAP kinase signaling in PC3 prostate cancer cells. The most likely set of values of the kinetic rate constants obtained from fitting the RDE model into the experimental data is then used in a direct transcription based dynamic optimization method for computing the changes needed in these kinetic rate constant values for the restoration of the normal EGF dose response. The last computation identifies the parameters, i.e., the kinetic rate constants in the RDE model, that are the most sensitive to the change in the EGF dose response behavior in the PC3 prostate cancer cells. The reactions in which these most sensitive parameters participate emerge as candidate drug targets on the signaling pathway. 2011 Elsevier Ireland Ltd. All rights reserved.

Multiensemble Markov models of molecular thermodynamics and kinetics

PubMed Central

Wu, Hao; Paul, Fabian; Noé, Frank

2016-01-01

We introduce the general transition-based reweighting analysis method (TRAM), a statistically optimal approach to integrate both unbiased and biased molecular dynamics simulations, such as umbrella sampling or replica exchange. TRAM estimates a multiensemble Markov model (MEMM) with full thermodynamic and kinetic information at all ensembles. The approach combines the benefits of Markov state models—clustering of high-dimensional spaces and modeling of complex many-state systems—with those of the multistate Bennett acceptance ratio of exploiting biased or high-temperature ensembles to accelerate rare-event sampling. TRAM does not depend on any rate model in addition to the widely used Markov state model approximation, but uses only fundamental relations such as detailed balance and binless reweighting of configurations between ensembles. Previous methods, including the multistate Bennett acceptance ratio, discrete TRAM, and Markov state models are special cases and can be derived from the TRAM equations. TRAM is demonstrated by efficiently computing MEMMs in cases where other estimators break down, including the full thermodynamics and rare-event kinetics from high-dimensional simulation data of an all-atom protein–ligand binding model. PMID:27226302

Methodology for extracting local constants from petroleum cracking flows

DOEpatents

Chang, Shen-Lin; Lottes, Steven A.; Zhou, Chenn Q.

2000-01-01

A methodology provides for the extraction of local chemical kinetic model constants for use in a reacting flow computational fluid dynamics (CFD) computer code with chemical kinetic computations to optimize the operating conditions or design of the system, including retrofit design improvements to existing systems. The coupled CFD and kinetic computer code are used in combination with data obtained from a matrix of experimental tests to extract the kinetic constants. Local fluid dynamic effects are implicitly included in the extracted local kinetic constants for each particular application system to which the methodology is applied. The extracted local kinetic model constants work well over a fairly broad range of operating conditions for specific and complex reaction sets in specific and complex reactor systems. While disclosed in terms of use in a Fluid Catalytic Cracking (FCC) riser, the inventive methodology has application in virtually any reaction set to extract constants for any particular application and reaction set formulation. The methodology includes the step of: (1) selecting the test data sets for various conditions; (2) establishing the general trend of the parametric effect on the measured product yields; (3) calculating product yields for the selected test conditions using coupled computational fluid dynamics and chemical kinetics; (4) adjusting the local kinetic constants to match calculated product yields with experimental data; and (5) validating the determined set of local kinetic constants by comparing the calculated results with experimental data from additional test runs at different operating conditions.

Dynamic wake model with coordinated pitch and torque control of wind farms for power tracking

NASA Astrophysics Data System (ADS)

Shapiro, Carl; Meyers, Johan; Meneveau, Charles; Gayme, Dennice

2017-11-01

Control of wind farm power production, where wind turbines within a wind farm coordinate to follow a time-varying power set point, is vital for increasing renewable energy participation in the power grid. Previous work developed a one-dimensional convection-diffusion equation describing the advection of the velocity deficit behind each turbine (wake) as well the turbulent mixing of the wake with the surrounding fluid. Proof-of-concept simulations demonstrated that a receding horizon controller built around this time-dependent model can effectively provide power tracking services by modulating the thrust coefficients of individual wind turbines. In this work, we extend this model-based controller to include pitch angle and generator torque control and the first-order dynamics of the drive train. Including these dynamics allows us to investigate control strategies for providing kinetic energy reserves to the grid, i.e. storing kinetic energy from the wind in the rotating mass of the wind turbine rotor for later use. CS, CM, and DG are supported by NSF (ECCS-1230788, CMMI 1635430, and OISE-1243482, the WINDINSPIRE project). JM is supported by ERC (ActiveWindFarms, 306471). This research was conducted using computational resources at MARCC.

Multilayer Insulation Ascent Venting Model

NASA Technical Reports Server (NTRS)

Tramel, R. W.; Sutherlin, S. G.; Johnson, W. L.

2017-01-01

The thermal and venting transient experienced by tank-applied multilayer insulation (MLI) in the Earth-to-orbit environment is very dynamic and not well characterized. This new predictive code is a first principles-based engineering model which tracks the time history of the mass and temperature (internal energy) of the gas in each MLI layer. A continuum-based model is used for early portions of the trajectory while a kinetic theory-based model is used for the later portions of the trajectory, and the models are blended based on a reference mean free path. This new capability should improve understanding of the Earth-to-orbit transient and enable better insulation system designs for in-space cryogenic propellant systems.

Water age and stream solute dynamics at the Hubbard Brook Experimental Forest (US)

NASA Astrophysics Data System (ADS)

Botter, Gianluca; Benettin, Paolo; McGuire, Kevin; Rinaldo, Andrea

2016-04-01

The contribution discusses experimental and modeling results from a headwater catchment at the Hubbard Brook Experimental Forest (New Hampshire, USA) to explore the link between stream solute dynamics and water age. A theoretical framework based on water age dynamics, which represents a general basis for characterizing solute transport at the catchment scale, is used to model both conservative and weathering-derived solutes. Based on the available information about the hydrology of the site, an integrated transport model was developed and used to estimate the relevant hydrochemical fluxes. The model was designed to reproduce the deuterium content of streamflow and allowed for the estimate of catchment water storage and dynamic travel time distributions (TTDs). Within this framework, dissolved silicon and sodium concentration in streamflow were simulated by implementing first-order chemical kinetics based explicitly on dynamic TTD, thus upscaling local geochemical processes to catchment scale. Our results highlight the key role of water stored within the subsoil glacial material in both the short-term and long-term solute circulation at Hubbard Brook. The analysis of the results provided by the calibrated model allowed a robust estimate of the emerging concentration-discharge relationship, streamflow age distributions (including the fraction of event water) and storage size, and their evolution in time due to hydrologic variability.

Kinetic models for space plasmas: Recent progress for the solar wind and the Earth's magnetosphere

NASA Astrophysics Data System (ADS)

Pierrard, V.; Moschou, S. P.; Lazar, M.; Borremans, K.; Rosson, G. Lopez

2016-11-01

Recent models for the solar wind and the inner magnetosphere have been developed using the kinetic approach. The solution of the evolution equation is used to determine the velocity distribution function of the particles and their moments. The solutions depend on the approximations and assumptions made in the development of the models. Effects of suprathermal particles often observed in space plasmas are taken into account to show their influence on the characteristics of the plasma, with specific applications for coronal heating and solar wind acceleration. We describe in particular the results obtained with the collisionless exospheric approximation based on the Lorentzian velocity distribution function for the electrons and its recent progress in three dimensions. The effects of Coulomb collisions obtained by using a Fokker-Planck term in the evolution equation were also investigated, as well as effects of the whistler wave turbulence at electron scale and the kinetic Alfven waves at the proton scale. For solar wind especially, modelling efforts with both magnetohydrodynamic and kinetic treatments have been compared and combined in order to improve the predictions in the vicinity of the Earth. Photospheric magnetograms serve as observational input in semi-empirical coronal models used for estimating the plasma characteristics up to coronal heliocentric distances taken as boundary conditions in solar wind models. The solar wind fluctuations may influence the dynamics of the space environment of the Earth and generate geomagnetic storms. In the magnetosphere of the Earth, the trajectories of the particles are simulated to study the plasmasphere, the extension of the ionosphere along closed magnetic field lines and to better understand the physical mechanisms involved in the radiation belts dynamics.

Non-linear dynamics of stable carbon and hydrogen isotope signatures based on a biological kinetic model of aerobic enzymatic methane oxidation.

PubMed

Vavilin, Vasily A; Rytov, Sergey V; Shim, Natalia; Vogt, Carsten

2016-06-01

The non-linear dynamics of stable carbon and hydrogen isotope signatures during methane oxidation by the methanotrophic bacteria Methylosinus sporium strain 5 (NCIMB 11126) and Methylocaldum gracile strain 14 L (NCIMB 11912) under copper-rich (8.9 µM Cu(2+)), copper-limited (0.3 µM Cu(2+)) or copper-regular (1.1 µM Cu(2+)) conditions has been described mathematically. The model was calibrated by experimental data of methane quantities and carbon and hydrogen isotope signatures of methane measured previously in laboratory microcosms reported by Feisthauer et al. [ 1 ] M. gracile initially oxidizes methane by a particulate methane monooxygenase and assimilates formaldehyde via the ribulose monophosphate pathway, whereas M. sporium expresses a soluble methane monooxygenase under copper-limited conditions and uses the serine pathway for carbon assimilation. The model shows that during methane solubilization dominant carbon and hydrogen isotope fractionation occurs. An increase of biomass due to growth of methanotrophs causes an increase of particulate or soluble monooxygenase that, in turn, decreases soluble methane concentration intensifying methane solubilization. The specific maximum rate of methane oxidation υm was proved to be equal to 4.0 and 1.3 mM mM(-1) h(-1) for M. sporium under copper-rich and copper-limited conditions, respectively, and 0.5 mM mM(-1) h(-1) for M. gracile. The model shows that methane oxidation cannot be described by traditional first-order kinetics. The kinetic isotope fractionation ceases when methane concentrations decrease close to the threshold value. Applicability of the non-linear model was confirmed by dynamics of carbon isotope signature for carbon dioxide that was depleted and later enriched in (13)C. Contrasting to the common Rayleigh linear graph, the dynamic curves allow identifying inappropriate isotope data due to inaccurate substrate concentration analyses. The non-linear model pretty adequately described experimental data presented in the two-dimensional plot of hydrogen versus carbon stable isotope signatures.

Modeling of Tracer Transport Delays for Improved Quantification of Regional Pulmonary ¹⁸F-FDG Kinetics, Vascular Transit Times, and Perfusion.

PubMed

Wellman, Tyler J; Winkler, Tilo; Vidal Melo, Marcos F

2015-11-01

¹⁸F-FDG-PET is increasingly used to assess pulmonary inflammatory cell activity. However, current models of pulmonary ¹⁸F-FDG kinetics do not account for delays in ¹⁸F-FDG transport between the plasma sampling site and the lungs. We developed a three-compartment model of ¹⁸F-FDG kinetics that includes a delay between the right heart and the local capillary blood pool, and used this model to estimate regional pulmonary perfusion. We acquired dynamic ¹⁸F-FDG scans in 12 mechanically ventilated sheep divided into control and lung injury groups (n = 6 each). The model was fit to tracer kinetics in three isogravitational regions-of-interest to estimate regional lung transport delays and regional perfusion. ¹³NN bolus infusion scans were acquired during a period of apnea to measure regional perfusion using an established reference method. The delayed input function model improved description of ¹⁸F-FDG kinetics (lower Akaike Information Criterion) in 98% of studied regions. Local transport delays ranged from 2.0 to 13.6 s, averaging 6.4 ± 2.9 s, and were highest in non-dependent regions. Estimates of regional perfusion derived from model parameters were highly correlated with perfusion measurements based on ¹³NN-PET (R² = 0.92, p < 0.001). By incorporating local vascular transports delays, this model of pulmonary ¹⁸F-FDG kinetics allows for simultaneous assessment of regional lung perfusion, transit times, and inflammation.

Dynamics of solid thin-film dewetting in the silicon-on-insulator system

NASA Astrophysics Data System (ADS)

Bussmann, E.; Cheynis, F.; Leroy, F.; Müller, P.; Pierre-Louis, O.

2011-04-01

Using low-energy electron microscopy movies, we have measured the dewetting dynamics of single-crystal Si(001) thin films on SiO2 substrates. During annealing (T>700 °C), voids open in the Si, exposing the oxide. The voids grow, evolving Si fingers that subsequently break apart into self-organized three-dimensional (3D) Si nanocrystals. A kinetic Monte Carlo model incorporating surface and interfacial free energies reproduces all the salient features of the morphological evolution. The dewetting dynamics is described using an analytic surface-diffusion-based model. We demonstrate quantitatively that Si dewetting from SiO2 is mediated by surface-diffusion driven by surface free-energy minimization.

Kinetic theory of situated agents applied to pedestrian flow in a corridor

NASA Astrophysics Data System (ADS)

Rangel-Huerta, A.; Muñoz-Meléndez, A.

2010-03-01

A situated agent-based model for simulation of pedestrian flow in a corridor is presented. In this model, pedestrians choose their paths freely and make decisions based on local criteria for solving collision conflicts. The crowd consists of multiple walking agents equipped with a function of perception as well as a competitive rule-based strategy that enables pedestrians to reach free access areas. Pedestrians in our model are autonomous entities capable of perceiving and making decisions. They apply socially accepted conventions, such as avoidance rules, as well as individual preferences such as the use of specific exit points, or the execution of eventual comfort turns resulting in spontaneous changes of walking speed. Periodic boundary conditions were considered in order to determine the density-average walking speed, and the density-average activity with respect to specific parameters: comfort angle turn and frequency of angle turn of walking agents. The main contribution of this work is an agent-based model where each pedestrian is represented as an autonomous agent. At the same time the pedestrian crowd dynamics is framed by the kinetic theory of biological systems.

Dynamic model for predicting growth of salmonella spp. in ground sterile pork

USDA-ARS?s Scientific Manuscript database

Predictive model for Salmonella spp. growth in ground pork was developed and validated using kinetic growth data. Salmonella spp. kinetic growth data in ground pork was collected at several isothermal conditions (between 10 and 45C) and Baranyi model was fitted to describe the growth at each temper...

Multiple Ion Binding Equilibria, Reaction Kinetics, and Thermodynamics in Dynamic Models of Biochemical Pathways

PubMed Central

Vinnakota, Kalyan C.; Wu, Fan; Kushmerick, Martin J.; Beard, Daniel A.

2009-01-01

The operation of biochemical systems in vivo and in vitro is strongly influenced by complex interactions between biochemical reactants and ions such as H+, Mg2+, K+, and Ca2+. These are important second messengers in metabolic and signaling pathways that directly influence the kinetics and thermodynamics of biochemical systems. Herein we describe the biophysical theory and computational methods to account for multiple ion binding to biochemical reactants and demonstrate the crucial effects of ion binding on biochemical reaction kinetics and thermodynamics. In simulations of realistic systems, the concentrations of these ions change with time due to dynamic buffering and competitive binding. In turn, the effective thermodynamic properties vary as functions of cation concentrations and important environmental variables such as temperature and overall ionic strength. Physically realistic simulations of biochemical systems require incorporating all of these phenomena into a coherent mathematical description. Several applications to physiological systems are demonstrated based on this coherent simulation framework. PMID:19216922

Time-Resolved Kinetic Chirped-Pulse Rotational Spectroscopy in a Room-Temperature Flow Reactor

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

Zaleski, Daniel P.; Harding, Lawrence B.; Klippenstein, Stephen J.

Chirped-pulse Fourier transform millimeter-wave spectroscopy is a potentially powerful tool for studying chemical reaction dynamics and kinetics. Branching ratios of multiple reaction products and intermediates can be measured with unprecedented chemical specificity; molecular isomers, conformers, and vibrational states have distinct rotational spectra. Here we demonstrate chirped-pulse spectroscopy of vinyl cyanide photoproducts in a flow tube reactor at ambient temperature of 295 K and pressures of 1-10 mu bar. This in situ and time-resolved experiment illustrates the utility of this novel approach to investigating chemical reaction dynamics and kinetics. Following 193 nm photodissociation of CH2CHCN, we observe rotational relaxation of energizedmore » HCN, HNC, and HCCCN photoproducts with 10 mu s time resolution and sample the vibrational population distribution of HCCCN. The experimental branching ratio HCN/HCCCN is compared with a model based on RRKM theory using high-level ab initio calculations, which were in turn validated by comparisons to Active Thermochemical Tables enthalpies.« less

Time-Resolved Kinetic Chirped-Pulse Rotational Spectroscopy in a Room-Temperature Flow Reactor

DOE PAGES

Zaleski, Daniel P.; Harding, Lawrence B.; Klippenstein, Stephen J.; ...

2017-12-01

Chirped-pulse Fourier transform millimeter-wave spectroscopy is a potentially powerful tool for studying chemical reaction dynamics and kinetics. Branching ratios of multiple reaction products and intermediates can be measured with unprecedented chemical specificity; molecular isomers, conformers, and vibrational states have distinct rotational spectra. Here we demonstrate chirped-pulse spectroscopy of vinyl cyanide photoproducts in a flow tube reactor at ambient temperature of 295 K and pressures of 1-10 mu bar. This in situ and time-resolved experiment illustrates the utility of this novel approach to investigating chemical reaction dynamics and kinetics. Following 193 nm photodissociation of CH2CHCN, we observe rotational relaxation of energizedmore » HCN, HNC, and HCCCN photoproducts with 10 mu s time resolution and sample the vibrational population distribution of HCCCN. The experimental branching ratio HCN/HCCCN is compared with a model based on RRKM theory using high-level ab initio calculations, which were in turn validated by comparisons to Active Thermochemical Tables enthalpies.« less

Grain scale observations of stick-slip dynamics in fluid saturated granular fault gouge

NASA Astrophysics Data System (ADS)

Johnson, P. A.; Dorostkar, O.; Guyer, R. A.; Marone, C.; Carmeliet, J.

2017-12-01

We are studying granular mechanics during slip. In the present work, we conduct coupled computational fluid dynamics (CFD) and discrete element method (DEM) simulations to study grain scale characteristics of slip instabilities in fluid saturated granular fault gouge. The granular sample is confined with constant normal load (10 MPa), and sheared with constant velocity (0.6 mm/s). This loading configuration is chosen to promote stick-slip dynamics, based on a phase-space study. Fluid is introduced in the beginning of stick phase and characteristics of slip events i.e. macroscopic friction coefficient, kinetic energy and layer thickness are monitored. At the grain scale, we monitor particle coordination number, fluid-particle interaction forces as well as particle and fluid kinetic energy. Our observations show that presence of fluids in a drained granular fault gouge stabilizes the layer in the stick phase and increases the recurrence time. In saturated model, we observe that average particle coordination number reaches higher values compared to dry granular gouge. Upon slip, we observe that a larger portion of the granular sample is mobilized in saturated gouge compared to dry system. We also observe that regions with high particle kinetic energy are correlated with zones of high fluid motion. Our observations highlight that spatiotemporal profile of fluid dynamic pressure affects the characteristics of slip instabilities, increasing macroscopic friction coefficient drop, kinetic energy release and granular layer compaction. We show that numerical simulations help characterize the micromechanics of fault mechanics.

Local rules simulation of the kinetics of virus capsid self-assembly.

PubMed

Schwartz, R; Shor, P W; Prevelige, P E; Berger, B

1998-12-01

A computer model is described for studying the kinetics of the self-assembly of icosahedral viral capsids. Solution of this problem is crucial to an understanding of the viral life cycle, which currently cannot be adequately addressed through laboratory techniques. The abstract simulation model employed to address this is based on the local rules theory of. Proc. Natl. Acad. Sci. USA. 91:7732-7736). It is shown that the principle of local rules, generalized with a model of kinetics and other extensions, can be used to simulate complicated problems in self-assembly. This approach allows for a computationally tractable molecular dynamics-like simulation of coat protein interactions while retaining many relevant features of capsid self-assembly. Three simple simulation experiments are presented to illustrate the use of this model. These show the dependence of growth and malformation rates on the energetics of binding interactions, the tolerance of errors in binding positions, and the concentration of subunits in the examples. These experiments demonstrate a tradeoff within the model between growth rate and fidelity of assembly for the three parameters. A detailed discussion of the computational model is also provided.

Importance of interactions between food quality, quantity, and gut transit time on consumer feeding, growth, and trophic dynamics.

PubMed

Mitra, Aditee; Flynn, Kevin J

2007-05-01

Ingestion kinetics of animals are controlled by both external food availability and feedback from the quantity of material already within the gut. The latter varies with gut transit time (GTT) and digestion of the food. Ingestion, assimilation efficiency, and thus, growth dynamics are not related in a simple fashion. For the first time, the important linkage between these processes and GTT is demonstrated; this is achieved using a biomass-based, mechanistic multinutrient model fitted to experimental data for zooplankton growth dynamics when presented with food items of varying quality (stoichiometric composition) or quantity. The results show that trophic transfer dynamics will vary greatly between the extremes of feeding on low-quantity/high-quality versus high-quantity/low-quality food; these conditions are likely to occur in nature. Descriptions of consumer behavior that assume a constant relationship between the kinetics of grazing and growth irrespective of food quality and/or quantity, with little or no recognition of the combined importance of these factors on consumer behavior, may seriously misrepresent consumer activity in dynamic situations.

Variational Koopman models: Slow collective variables and molecular kinetics from short off-equilibrium simulations

NASA Astrophysics Data System (ADS)

Wu, Hao; Nüske, Feliks; Paul, Fabian; Klus, Stefan; Koltai, Péter; Noé, Frank

2017-04-01

Markov state models (MSMs) and master equation models are popular approaches to approximate molecular kinetics, equilibria, metastable states, and reaction coordinates in terms of a state space discretization usually obtained by clustering. Recently, a powerful generalization of MSMs has been introduced, the variational approach conformation dynamics/molecular kinetics (VAC) and its special case the time-lagged independent component analysis (TICA), which allow us to approximate slow collective variables and molecular kinetics by linear combinations of smooth basis functions or order parameters. While it is known how to estimate MSMs from trajectories whose starting points are not sampled from an equilibrium ensemble, this has not yet been the case for TICA and the VAC. Previous estimates from short trajectories have been strongly biased and thus not variationally optimal. Here, we employ the Koopman operator theory and the ideas from dynamic mode decomposition to extend the VAC and TICA to non-equilibrium data. The main insight is that the VAC and TICA provide a coefficient matrix that we call Koopman model, as it approximates the underlying dynamical (Koopman) operator in conjunction with the basis set used. This Koopman model can be used to compute a stationary vector to reweight the data to equilibrium. From such a Koopman-reweighted sample, equilibrium expectation values and variationally optimal reversible Koopman models can be constructed even with short simulations. The Koopman model can be used to propagate densities, and its eigenvalue decomposition provides estimates of relaxation time scales and slow collective variables for dimension reduction. Koopman models are generalizations of Markov state models, TICA, and the linear VAC and allow molecular kinetics to be described without a cluster discretization.

Block matrix based LU decomposition to analyze kinetic damping in active plasma resonance spectroscopy

NASA Astrophysics Data System (ADS)

Roehl, Jan Hendrik; Oberrath, Jens

2016-09-01

``Active plasma resonance spectroscopy'' (APRS) is a widely used diagnostic method to measure plasma parameter like electron density. Measurements with APRS probes in plasmas of a few Pa typically show a broadening of the spectrum due to kinetic effects. To analyze the broadening a general kinetic model in electrostatic approximation based on functional analytic methods has been presented [ 1 ] . One of the main results is, that the system response function Y(ω) is given in terms of the matrix elements of the resolvent of the dynamic operator evaluated for values on the imaginary axis. To determine the response function of a specific probe the resolvent has to be approximated by a huge matrix which is given by a banded block structure. Due to this structure a block based LU decomposition can be implemented. It leads to a solution of Y(ω) which is given only by products of matrices of the inner block size. This LU decomposition allows to analyze the influence of kinetic effects on the broadening and saves memory and calculation time. Gratitude is expressed to the internal funding of Leuphana University.

Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems

PubMed Central

Chylek, Lily A.; Harris, Leonard A.; Tung, Chang-Shung; Faeder, James R.; Lopez, Carlos F.

2013-01-01

Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and post-translational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). PMID:24123887

Kinetic modeling of particle dynamics in H- negative ion sources (invited)

NASA Astrophysics Data System (ADS)

Hatayama, A.; Shibata, T.; Nishioka, S.; Ohta, M.; Yasumoto, M.; Nishida, K.; Yamamoto, T.; Miyamoto, K.; Fukano, A.; Mizuno, T.

2014-02-01

Progress in the kinetic modeling of particle dynamics in H- negative ion source plasmas and their comparisons with experiments are reviewed, and discussed with some new results. Main focus is placed on the following two topics, which are important for the research and development of large negative ion sources and high power H- ion beams: (i) Effects of non-equilibrium features of EEDF (electron energy distribution function) on H- production, and (ii) extraction physics of H- ions and beam optics.

Steady-state kinetic modeling constrains cellular resting states and dynamic behavior.

PubMed

Purvis, Jeremy E; Radhakrishnan, Ravi; Diamond, Scott L

2009-03-01

A defining characteristic of living cells is the ability to respond dynamically to external stimuli while maintaining homeostasis under resting conditions. Capturing both of these features in a single kinetic model is difficult because the model must be able to reproduce both behaviors using the same set of molecular components. Here, we show how combining small, well-defined steady-state networks provides an efficient means of constructing large-scale kinetic models that exhibit realistic resting and dynamic behaviors. By requiring each kinetic module to be homeostatic (at steady state under resting conditions), the method proceeds by (i) computing steady-state solutions to a system of ordinary differential equations for each module, (ii) applying principal component analysis to each set of solutions to capture the steady-state solution space of each module network, and (iii) combining optimal search directions from all modules to form a global steady-state space that is searched for accurate simulation of the time-dependent behavior of the whole system upon perturbation. Importantly, this stepwise approach retains the nonlinear rate expressions that govern each reaction in the system and enforces constraints on the range of allowable concentration states for the full-scale model. These constraints not only reduce the computational cost of fitting experimental time-series data but can also provide insight into limitations on system concentrations and architecture. To demonstrate application of the method, we show how small kinetic perturbations in a modular model of platelet P2Y(1) signaling can cause widespread compensatory effects on cellular resting states.

Cell Population Kinetics of Collagen Scaffolds in Ex Vivo Oral Wound Repair

PubMed Central

Agis, Hermann; Collins, Amy; Taut, Andrei D.; Jin, Qiming; Kruger, Laura; Görlach, Christoph; Giannobile, William V.

2014-01-01

Biodegradable collagen scaffolds are used clinically for oral soft tissue augmentation to support wound healing. This study sought to provide a novel ex vivo model for analyzing healing kinetics and gene expression of primary human gingival fibroblasts (hGF) within collagen scaffolds. Sponge type and gel type scaffolds with and without platelet-derived growth factor-BB (PDGF) were assessed in an hGF containing matrix. Morphology was evaluated with scanning electron microscopy, and hGF metabolic activity using MTT. We quantitated the population kinetics within the scaffolds based on cell density and distance from the scaffold border of DiI-labled hGFs over a two-week observation period. Gene expression was evaluated with gene array and qPCR. The sponge type scaffolds showed a porous morphology. Absolute cell number and distance was higher in sponge type scaffolds when compared to gel type scaffolds, in particular during the first week of observation. PDGF incorporated scaffolds increased cell numbers, distance, and formazan formation in the MTT assay. Gene expression dynamics revealed the induction of key genes associated with the generation of oral tissue. DKK1, CYR61, CTGF, TGFBR1 levels were increased and integrin ITGA2 levels were decreased in the sponge type scaffolds compared to the gel type scaffold. The results suggest that this novel model of oral wound healing provides insights into population kinetics and gene expression dynamics of biodegradable scaffolds. PMID:25397671

Electron-phonon thermalization in a scalable method for real-time quantum dynamics

NASA Astrophysics Data System (ADS)

Rizzi, Valerio; Todorov, Tchavdar N.; Kohanoff, Jorge J.; Correa, Alfredo A.

2016-01-01

We present a quantum simulation method that follows the dynamics of out-of-equilibrium many-body systems of electrons and oscillators in real time. Its cost is linear in the number of oscillators and it can probe time scales from attoseconds to hundreds of picoseconds. Contrary to Ehrenfest dynamics, it can thermalize starting from a variety of initial conditions, including electronic population inversion. While an electronic temperature can be defined in terms of a nonequilibrium entropy, a Fermi-Dirac distribution in general emerges only after thermalization. These results can be used to construct a kinetic model of electron-phonon equilibration based on the explicit quantum dynamics.

Numerical modelling in biosciences using delay differential equations

NASA Astrophysics Data System (ADS)

Bocharov, Gennadii A.; Rihan, Fathalla A.

2000-12-01

Our principal purposes here are (i) to consider, from the perspective of applied mathematics, models of phenomena in the biosciences that are based on delay differential equations and for which numerical approaches are a major tool in understanding their dynamics, (ii) to review the application of numerical techniques to investigate these models. We show that there are prima facie reasons for using such models: (i) they have a richer mathematical framework (compared with ordinary differential equations) for the analysis of biosystem dynamics, (ii) they display better consistency with the nature of certain biological processes and predictive results. We analyze both the qualitative and quantitative role that delays play in basic time-lag models proposed in population dynamics, epidemiology, physiology, immunology, neural networks and cell kinetics. We then indicate suitable computational techniques for the numerical treatment of mathematical problems emerging in the biosciences, comparing them with those implemented by the bio-modellers.

Wavelet-based surrogate time series for multiscale simulation of heterogeneous catalysis

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

Savara, Aditya Ashi; Daw, C. Stuart; Xiong, Qingang

We propose a wavelet-based scheme that encodes the essential dynamics of discrete microscale surface reactions in a form that can be coupled with continuum macroscale flow simulations with high computational efficiency. This makes it possible to simulate the dynamic behavior of reactor-scale heterogeneous catalysis without requiring detailed concurrent simulations at both the surface and continuum scales using different models. Our scheme is based on the application of wavelet-based surrogate time series that encodes the essential temporal and/or spatial fine-scale dynamics at the catalyst surface. The encoded dynamics are then used to generate statistically equivalent, randomized surrogate time series, which canmore » be linked to the continuum scale simulation. As a result, we illustrate an application of this approach using two different kinetic Monte Carlo simulations with different characteristic behaviors typical for heterogeneous chemical reactions.« less

Wavelet-based surrogate time series for multiscale simulation of heterogeneous catalysis

DOE PAGES

Savara, Aditya Ashi; Daw, C. Stuart; Xiong, Qingang; ...

2016-01-28

We propose a wavelet-based scheme that encodes the essential dynamics of discrete microscale surface reactions in a form that can be coupled with continuum macroscale flow simulations with high computational efficiency. This makes it possible to simulate the dynamic behavior of reactor-scale heterogeneous catalysis without requiring detailed concurrent simulations at both the surface and continuum scales using different models. Our scheme is based on the application of wavelet-based surrogate time series that encodes the essential temporal and/or spatial fine-scale dynamics at the catalyst surface. The encoded dynamics are then used to generate statistically equivalent, randomized surrogate time series, which canmore » be linked to the continuum scale simulation. As a result, we illustrate an application of this approach using two different kinetic Monte Carlo simulations with different characteristic behaviors typical for heterogeneous chemical reactions.« less

Improved kinetic model of Escherichia coli central carbon metabolism in batch and continuous cultures.

PubMed

Kurata, Hiroyuki; Sugimoto, Yurie

2018-02-01

Many kinetic models of Escherichia coli central metabolism have been built, but few models accurately reproduced the dynamic behaviors of wild type and multiple genetic mutants. In 2016, our latest kinetic model improved problems of existing models to reproduce the cell growth and glucose uptake of wild type, ΔpykA:pykF and Δpgi in a batch culture, while it overestimated the glucose uptake and cell growth rates of Δppc and hardly captured the typical characteristics of the glyoxylate and TCA cycle fluxes for Δpgi and Δppc. Such discrepancies between the simulated and experimental data suggested biological complexity. In this study, we overcame these problems by assuming critical mechanisms regarding the OAA-regulated isocitrate dehydrogenase activity, aceBAK gene regulation and growth suppression. The present model accurately predicts the extracellular and intracellular dynamics of wild type and many gene knockout mutants in batch and continuous cultures. It is now the most accurate, detailed kinetic model of E. coli central carbon metabolism and will contribute to advances in mathematical modeling of cell factories. Copyright © 2017 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

iSCHRUNK--In Silico Approach to Characterization and Reduction of Uncertainty in the Kinetic Models of Genome-scale Metabolic Networks.

PubMed

Andreozzi, Stefano; Miskovic, Ljubisa; Hatzimanikatis, Vassily

2016-01-01

Accurate determination of physiological states of cellular metabolism requires detailed information about metabolic fluxes, metabolite concentrations and distribution of enzyme states. Integration of fluxomics and metabolomics data, and thermodynamics-based metabolic flux analysis contribute to improved understanding of steady-state properties of metabolism. However, knowledge about kinetics and enzyme activities though essential for quantitative understanding of metabolic dynamics remains scarce and involves uncertainty. Here, we present a computational methodology that allow us to determine and quantify the kinetic parameters that correspond to a certain physiology as it is described by a given metabolic flux profile and a given metabolite concentration vector. Though we initially determine kinetic parameters that involve a high degree of uncertainty, through the use of kinetic modeling and machine learning principles we are able to obtain more accurate ranges of kinetic parameters, and hence we are able to reduce the uncertainty in the model analysis. We computed the distribution of kinetic parameters for glucose-fed E. coli producing 1,4-butanediol and we discovered that the observed physiological state corresponds to a narrow range of kinetic parameters of only a few enzymes, whereas the kinetic parameters of other enzymes can vary widely. Furthermore, this analysis suggests which are the enzymes that should be manipulated in order to engineer the reference state of the cell in a desired way. The proposed approach also sets up the foundations of a novel type of approaches for efficient, non-asymptotic, uniform sampling of solution spaces. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

The (kinetic) theory of active particles applied to learning dynamics. Comment on "Collective learning modeling based on the kinetic theory of active particles" by D. Burini et al.

NASA Astrophysics Data System (ADS)

Nieto, J.

2016-03-01

The learning phenomena, their complexity, concepts, structure, suitable theories and models, have been extensively treated in the mathematical literature in the last century, and [4] contains a very good introduction to the literature describing the many approaches and lines of research developed about them. Two main schools have to be pointed out [5] in order to understand the two -not exclusive- kinds of existing models: the stimulus sampling models and the stochastic learning models. Also [6] should be mentioned as a survey where two methods of learning are pointed out, the cognitive and the social, and where the knowledge looks like a mathematical unknown. Finally, as the authors do, we refer to the works [9,10], where the concept of population thinking was introduced and which motivate the game theory rules as a tool (both included in [4] to develop their theory) and [7], where the ideas of developing a mathematical kinetic theory of perception and learning were proposed.

Parameterization of the Van Hove dynamic self-scattering law Ss(Q,omega)

NASA Astrophysics Data System (ADS)

Zetterstrom, P.

In this paper we present a model of the Van Hove dynamic scattering law SME(Q, omega) based on the maximum entropy principle which is developed for the first time. The model is aimed to be used in the calculation of inelastic corrections to neutron diffraction data. The model is constrained by the first and second frequency moments and detailed balance, but can be expanded to an arbitrary number of frequency moments. The second moment can be varied by an effective temperature to account for the kinetic energy of the atoms. The results are compared with a diffusion model of the scattering law. Finally some calculations of the inelastic self-scattering for a time-of-flight diffractometer are presented. From this we show that the inelastic self-scattering is very sensitive to the details of the dynamic scattering law.

A KINETIC MODEL FOR H2O2/UV PROCESS IN A COMPLETELY MIXED BATCH REACTOR. (R825370C076)

EPA Science Inventory

A dynamic kinetic model for the advanced oxidation process (AOP) using hydrogen peroxide and ultraviolet irradiation (H₂O₂/UV) in a completely mixed batch reactor (CMBR) is developed. The model includes the known elementary chemical and photochemical reac...

Interfacial mixing in high energy-density matter with a multiphysics kinetic model

NASA Astrophysics Data System (ADS)

Haack, Jeff; Hauck, Cory; Murillo, Michael

2017-10-01

We have extended a recently-developed multispecies, multitemperature BGK model to include multiphysics capability that allows modeling of a wider range of plasma conditions. In particular, we have extended the model to describe one spatial dimension, and included a multispecies atomic ionization model, accurate collision physics across coupling regimes, self-consistent electric fields, and degeneracy in the electronic screening. We apply the new model to a warm dense matter scenario in which the ablator-fuel interface of an inertial confinement fusion target is heated, similar to a recent molecular dynamics study, but for larger length and time scales and for much higher temperatures. From our numerical results we are able to explore a variety of phenomena, including hydrogen jetting, kinetic effects (non-Maxwellian and anisotropic distributions), plasma physics (size, persistence and role of electric fields) and transport (relative sizes of Fickean diffision, electrodiffusion and barodiffusion). As compared with the recent molecular dynamics work the kinetic model greatly extends the accessible physical domains we are able to model.

Is cancer a pure growth curve or does it follow a kinetics of dynamical structural transformation?

PubMed

González, Maraelys Morales; Joa, Javier Antonio González; Cabrales, Luis Enrique Bergues; Pupo, Ana Elisa Bergues; Schneider, Baruch; Kondakci, Suleyman; Ciria, Héctor Manuel Camué; Reyes, Juan Bory; Jarque, Manuel Verdecia; Mateus, Miguel Angel O'Farril; González, Tamara Rubio; Brooks, Soraida Candida Acosta; Cáceres, José Luis Hernández; González, Gustavo Victoriano Sierra

2017-03-07

Unperturbed tumor growth kinetics is one of the more studied cancer topics; however, it is poorly understood. Mathematical modeling is a useful tool to elucidate new mechanisms involved in tumor growth kinetics, which can be relevant to understand cancer genesis and select the most suitable treatment. The classical Kolmogorov-Johnson-Mehl-Avrami as well as the modified Kolmogorov-Johnson-Mehl-Avrami models to describe unperturbed fibrosarcoma Sa-37 tumor growth are used and compared with the Gompertz modified and Logistic models. Viable tumor cells (1×10 5 ) are inoculated to 28 BALB/c male mice. Modified Gompertz, Logistic, Kolmogorov-Johnson-Mehl-Avrami classical and modified Kolmogorov-Johnson-Mehl-Avrami models fit well to the experimental data and agree with one another. A jump in the time behaviors of the instantaneous slopes of classical and modified Kolmogorov-Johnson-Mehl-Avrami models and high values of these instantaneous slopes at very early stages of tumor growth kinetics are observed. The modified Kolmogorov-Johnson-Mehl-Avrami equation can be used to describe unperturbed fibrosarcoma Sa-37 tumor growth. It reveals that diffusion-controlled nucleation/growth and impingement mechanisms are involved in tumor growth kinetics. On the other hand, tumor development kinetics reveals dynamical structural transformations rather than a pure growth curve. Tumor fractal property prevails during entire TGK.

C. botulinum inactivation kinetics implemented in a computational model of a high-pressure sterilization process.

PubMed

Juliano, Pablo; Knoerzer, Kai; Fryer, Peter J; Versteeg, Cornelis

2009-01-01

High-pressure, high-temperature (HPHT) processing is effective for microbial spore inactivation using mild preheating, followed by rapid volumetric compression heating and cooling on pressure release, enabling much shorter processing times than conventional thermal processing for many food products. A computational thermal fluid dynamic (CTFD) model has been developed to model all processing steps, including the vertical pressure vessel, an internal polymeric carrier, and food packages in an axis-symmetric geometry. Heat transfer and fluid dynamic equations were coupled to four selected kinetic models for the inactivation of C. botulinum; the traditional first-order kinetic model, the Weibull model, an nth-order model, and a combined discrete log-linear nth-order model. The models were solved to compare the resulting microbial inactivation distributions. The initial temperature of the system was set to 90 degrees C and pressure was selected at 600 MPa, holding for 220 s, with a target temperature of 121 degrees C. A representation of the extent of microbial inactivation throughout all processing steps was obtained for each microbial model. Comparison of the models showed that the conventional thermal processing kinetics (not accounting for pressure) required shorter holding times to achieve a 12D reduction of C. botulinum spores than the other models. The temperature distribution inside the vessel resulted in a more uniform inactivation distribution when using a Weibull or an nth-order kinetics model than when using log-linear kinetics. The CTFD platform could illustrate the inactivation extent and uniformity provided by the microbial models. The platform is expected to be useful to evaluate models fitted into new C. botulinum inactivation data at varying conditions of pressure and temperature, as an aid for regulatory filing of the technology as well as in process and equipment design.

A unified theory for ice vapor growth suitable for cloud models: Testing and implications for cold cloud evolution

NASA Astrophysics Data System (ADS)

Zhang, Chengzhu

A new microphysical model for the vapor growth and aspect ratio evolution of atmospheric ice crystals is presented. The method is based on the adaptive habit model of Chen and Lamb (1994), but is modified to include surface kinetic processes for crystal growth. Inclusion of surface kinetic effects is accomplished with a new theory that accounts for axis dependent growth. Deposition coefficients (growth efficiencies) are predicted for two axis directions based on laboratory-determined parameters for growth initiation (critical supersaturations) on each face. In essence, the new theory extends the adaptive habit approach of Chen and Lamb (1994) to ice saturation states below that of liquid saturation, where Chen and Lamb (1994) is likely most valid. The new model is used to simulate changes in crystal primary habit as a function of temperature and ice supersaturation. Predictions are compared with a detailed hexagonal growth model both in a single particle framework and in a Lagrangian parcel model to indicate the accuracy of the new method. Moreover, predictions of the ratio of the axis deposition coefficients match laboratory-generated data. A parameterization for predicting deposition coefficients is developed for the bulk microphysics frame work in Regional Atmospheric Modeling System (RAMS). Initial eddy-resolving model simulation is conducted to study the effect of surface kinetics on microphysical and dynamical processes in cold cloud development.

Mechanistic analysis of multi-omics datasets to generate kinetic parameters for constraint-based metabolic models.

PubMed

Cotten, Cameron; Reed, Jennifer L

2013-01-30

Constraint-based modeling uses mass balances, flux capacity, and reaction directionality constraints to predict fluxes through metabolism. Although transcriptional regulation and thermodynamic constraints have been integrated into constraint-based modeling, kinetic rate laws have not been extensively used. In this study, an in vivo kinetic parameter estimation problem was formulated and solved using multi-omic data sets for Escherichia coli. To narrow the confidence intervals for kinetic parameters, a series of kinetic model simplifications were made, resulting in fewer kinetic parameters than the full kinetic model. These new parameter values are able to account for flux and concentration data from 20 different experimental conditions used in our training dataset. Concentration estimates from the simplified kinetic model were within one standard deviation for 92.7% of the 790 experimental measurements in the training set. Gibbs free energy changes of reaction were calculated to identify reactions that were often operating close to or far from equilibrium. In addition, enzymes whose activities were positively or negatively influenced by metabolite concentrations were also identified. The kinetic model was then used to calculate the maximum and minimum possible flux values for individual reactions from independent metabolite and enzyme concentration data that were not used to estimate parameter values. Incorporating these kinetically-derived flux limits into the constraint-based metabolic model improved predictions for uptake and secretion rates and intracellular fluxes in constraint-based models of central metabolism. This study has produced a method for in vivo kinetic parameter estimation and identified strategies and outcomes of kinetic model simplification. We also have illustrated how kinetic constraints can be used to improve constraint-based model predictions for intracellular fluxes and biomass yield and identify potential metabolic limitations through the integrated analysis of multi-omics datasets.

Mechanistic analysis of multi-omics datasets to generate kinetic parameters for constraint-based metabolic models

PubMed Central

2013-01-01

Background Constraint-based modeling uses mass balances, flux capacity, and reaction directionality constraints to predict fluxes through metabolism. Although transcriptional regulation and thermodynamic constraints have been integrated into constraint-based modeling, kinetic rate laws have not been extensively used. Results In this study, an in vivo kinetic parameter estimation problem was formulated and solved using multi-omic data sets for Escherichia coli. To narrow the confidence intervals for kinetic parameters, a series of kinetic model simplifications were made, resulting in fewer kinetic parameters than the full kinetic model. These new parameter values are able to account for flux and concentration data from 20 different experimental conditions used in our training dataset. Concentration estimates from the simplified kinetic model were within one standard deviation for 92.7% of the 790 experimental measurements in the training set. Gibbs free energy changes of reaction were calculated to identify reactions that were often operating close to or far from equilibrium. In addition, enzymes whose activities were positively or negatively influenced by metabolite concentrations were also identified. The kinetic model was then used to calculate the maximum and minimum possible flux values for individual reactions from independent metabolite and enzyme concentration data that were not used to estimate parameter values. Incorporating these kinetically-derived flux limits into the constraint-based metabolic model improved predictions for uptake and secretion rates and intracellular fluxes in constraint-based models of central metabolism. Conclusions This study has produced a method for in vivo kinetic parameter estimation and identified strategies and outcomes of kinetic model simplification. We also have illustrated how kinetic constraints can be used to improve constraint-based model predictions for intracellular fluxes and biomass yield and identify potential metabolic limitations through the integrated analysis of multi-omics datasets. PMID:23360254

The nearest neighbor and next nearest neighbor effects on the thermodynamic and kinetic properties of RNA base pair

NASA Astrophysics Data System (ADS)

Wang, Yujie; Wang, Zhen; Wang, Yanli; Liu, Taigang; Zhang, Wenbing

2018-01-01

The thermodynamic and kinetic parameters of an RNA base pair with different nearest and next nearest neighbors were obtained through long-time molecular dynamics simulation of the opening-closing switch process of the base pair near its melting temperature. The results indicate that thermodynamic parameters of GC base pair are dependent on the nearest neighbor base pair, and the next nearest neighbor base pair has little effect, which validated the nearest-neighbor model. The closing and opening rates of the GC base pair also showed nearest neighbor dependences. At certain temperature, the closing and opening rates of the GC pair with nearest neighbor AU is larger than that with the nearest neighbor GC, and the next nearest neighbor plays little role. The free energy landscape of the GC base pair with the nearest neighbor GC is rougher than that with nearest neighbor AU.

Using gamma distribution to determine half-life of rotenone, applied in freshwater.

PubMed

Rohan, Maheswaran; Fairweather, Alastair; Grainger, Natasha

2015-09-15

Following the use of rotenone to eradicate invasive pest fish, a dynamic first-order kinetic model is usually used to determine the half-life and rate at which rotenone dissipated from the treated waterbody. In this study, we investigate the use of a stochastic gamma model for determining the half-life and rate at which rotenone dissipates from waterbodies. The first-order kinetic and gamma models produced similar values for the half-life (4.45 days and 5.33 days respectively) and days to complete dissipation (51.2 days and 52.48 days respectively). However, the gamma model fitted the data better and was more flexible than the first-order kinetic model, allowing us to use covariates and to predict a possible range for the half-life of rotenone. These benefits are particularly important when examining the influence that different environmental factors have on rotenone dissipation and when trying to predict the rate at which rotenone will dissipate during future operations. We therefore recommend that in future the gamma distribution model is used when calculating the half-life of rotenone in preference to the dynamic first-order kinetics model. Copyright © 2015 Elsevier B.V. All rights reserved.

Mechanisms of kinetic stabilization by the drugs paclitaxel and vinblastine

PubMed Central

Castle, Brian T.; McCubbin, Seth; Prahl, Louis S.; Bernens, Jordan N.; Sept, David; Odde, David J.

2017-01-01

Microtubule-targeting agents (MTAs), widely used as biological probes and chemotherapeutic drugs, bind directly to tubulin subunits and “kinetically stabilize” microtubules, suppressing the characteristic self-assembly process of dynamic instability. However, the molecular-level mechanisms of kinetic stabilization are unclear, and the fundamental thermodynamic and kinetic requirements for dynamic instability and its elimination by MTAs have yet to be defined. Here we integrate a computational model for microtubule assembly with nanometer-scale fluorescence microscopy measurements to identify the kinetic and thermodynamic basis of kinetic stabilization by the MTAs paclitaxel, an assembly promoter, and vinblastine, a disassembly promoter. We identify two distinct modes of kinetic stabilization in live cells, one that truly suppresses on-off kinetics, characteristic of vinblastine, and the other a “pseudo” kinetic stabilization, characteristic of paclitaxel, that nearly eliminates the energy difference between the GTP- and GDP-tubulin thermodynamic states. By either mechanism, the main effect of both MTAs is to effectively stabilize the microtubule against disassembly in the absence of a robust GTP cap. PMID:28298489

Kinetic Monte Carlo simulation of nanoparticle film formation via nanocolloid drying

NASA Astrophysics Data System (ADS)

Kameya, Yuki

2017-06-01

A kinetic Monte Carlo simulation of nanoparticle film formation via nanocolloid drying is presented. The proposed two-dimensional model addresses the dynamics of nanoparticles in the vertical plane of a drying nanocolloid film. The gas-liquid interface movement due to solvent evaporation was controlled by a time-dependent chemical potential, and the resultant particle dynamics including Brownian diffusion and aggregate growth were calculated. Simulations were performed at various Peclet numbers defined based on the rate ratio of solvent evaporation and nanoparticle diffusion. At high Peclet numbers, nanoparticles accumulated at the top layer of the liquid film and eventually formed a skin layer, causing the formation of a particulate film with a densely packed structure. At low Peclet numbers, enhanced particle diffusion led to significant particle aggregation in the bulk colloid, and the resulting film structure became highly porous. The simulated results showed some typical characteristics of a drying nanocolloid that had been reported experimentally. Finally, the potential of the model as well as the remaining challenges are discussed.

Modeling and Classification of Kinetic Patterns of Dynamic Metabolic Biomarkers in Physical Activity

PubMed Central

Breit, Marc; Netzer, Michael

2015-01-01

The objectives of this work were the classification of dynamic metabolic biomarker candidates and the modeling and characterization of kinetic regulatory mechanisms in human metabolism with response to external perturbations by physical activity. Longitudinal metabolic concentration data of 47 individuals from 4 different groups were examined, obtained from a cycle ergometry cohort study. In total, 110 metabolites (within the classes of acylcarnitines, amino acids, and sugars) were measured through a targeted metabolomics approach, combining tandem mass spectrometry (MS/MS) with the concept of stable isotope dilution (SID) for metabolite quantitation. Biomarker candidates were selected by combined analysis of maximum fold changes (MFCs) in concentrations and P-values resulting from statistical hypothesis testing. Characteristic kinetic signatures were identified through a mathematical modeling approach utilizing polynomial fitting. Modeled kinetic signatures were analyzed for groups with similar behavior by applying hierarchical cluster analysis. Kinetic shape templates were characterized, defining different forms of basic kinetic response patterns, such as sustained, early, late, and other forms, that can be used for metabolite classification. Acetylcarnitine (C2), showing a late response pattern and having the highest values in MFC and statistical significance, was classified as late marker and ranked as strong predictor (MFC = 1.97, P < 0.001). In the class of amino acids, highest values were shown for alanine (MFC = 1.42, P < 0.001), classified as late marker and strong predictor. Glucose yields a delayed response pattern, similar to a hockey stick function, being classified as delayed marker and ranked as moderate predictor (MFC = 1.32, P < 0.001). These findings coincide with existing knowledge on central metabolic pathways affected in exercise physiology, such as β-oxidation of fatty acids, glycolysis, and glycogenolysis. The presented modeling approach demonstrates high potential for dynamic biomarker identification and the investigation of kinetic mechanisms in disease or pharmacodynamics studies using MS data from longitudinal cohort studies. PMID:26317529

Minimal models of electric potential oscillations in non-excitable membranes.

PubMed

Perdomo, Guillermo; Hernández, Julio A

2010-01-01

Sustained oscillations in the membrane potential have been observed in a variety of cellular and subcellular systems, including several types of non-excitable cells and mitochondria. For the plasma membrane, these electrical oscillations have frequently been related to oscillations in intracellular calcium. For the inner mitochondrial membrane, in several cases the electrical oscillations have been attributed to modifications in calcium dynamics. As an alternative, some authors have suggested that the sustained oscillations in the mitochondrial membrane potential induced by some metabolic intermediates depends on the direct effect of internal protons on proton conductance. Most theoretical models developed to interpret oscillations in the membrane potential integrate several transport and biochemical processes. Here we evaluate whether three simple dynamic models may constitute plausible representations of electric oscillations in non-excitable membranes. The basic mechanism considered in the derivation of the models is based upon evidence obtained by Hattori et al. for mitochondria and assumes that an ionic species (i.e., the proton) is transported via passive and active transport systems between an external and an internal compartment and that the ion affects the kinetic properties of transport by feedback regulation. The membrane potential is incorporated via its effects on kinetic properties. The dynamic properties of two of the models enable us to conclude that they may represent alternatives enabling description of the generation of electrical oscillations in membranes that depend on the transport of a single ionic species.

A preliminary model of the coma of 2060 Chiron

NASA Technical Reports Server (NTRS)

Boice, Daniel C.; Konno, I.; Stern, S. Alan; Huebner, Walter F.

1992-01-01

We have included gravity in our fluid dynamic model with chemical kinetics of dusty comet comae and applied it with two dust sizes to 2060 Chiron. A progress report on the model and preliminary results concerning gas/dust dynamics and chemistry is given.

Verification of kinetic schemes of hydrogen ignition and combustion in air

NASA Astrophysics Data System (ADS)

Fedorov, A. V.; Fedorova, N. N.; Vankova, O. S.; Tropin, D. A.

2018-03-01

Three chemical kinetic models for hydrogen combustion in oxygen and three gas-dynamic models for reactive mixture flow behind the initiating SW front were analyzed. The calculated results were compared with experimental data on the dependences of the ignition delay on the temperature and the dilution of the mixture with argon or nitrogen. Based on detailed kinetic mechanisms of nonequilibrium chemical transformations, a mathematical technique for describing the ignition and combustion of hydrogen in air was developed using the ANSYS Fluent code. The problem of ignition of a hydrogen jet fed coaxially into supersonic flow was solved numerically. The calculations were carried out using the Favre-averaged Navier-Stokes equations for a multi-species gas taking into account chemical reactions combined with the k-ω SST turbulence model. The problem was solved in several steps. In the first step, verification of the calculated and experimental data for the three kinetic schemes was performed without considering the conicity of the flow. In the second step, parametric calculations were performed to determine the influence of the conicity of the flow on the mixing and ignition of hydrogen in air using a kinetic scheme consisting of 38 reactions. Three conical supersonic nozzles for a Mach number M = 2 with different expansion angles β = 4°, 4.5°, and 5° were considered.

The kinetic regime of the Vicsek model

NASA Astrophysics Data System (ADS)

Chepizhko, A. A.; Kulinskii, V. L.

2009-12-01

We consider the dynamics of the system of self-propelling particles modeled via the Vicsek algorithm in continuum time limit. It is shown that the alignment process for the velocities can be subdivided into two regimes: "fast" kinetic and "slow" hydrodynamic ones. In fast kinetic regime the alignment of the particle velocity to the local neighborhood takes place with characteristic relaxation time. So, that the bigger regions arise with the velocity alignment. These regions align their velocities thus giving rise to hydrodynamic regime of the dynamics. We propose the mean-field-like approach in which we take into account the correlations between density and velocity. The comparison of the theoretical predictions with the numerical simulations is given. The relation between Vicsek model in the zero velocity limit and the Kuramoto model is stated. The mean-field approach accounting for the dynamic change of the neighborhood is proposed. The nature of the discontinuity of the dependence of the order parameter in case of vectorial noise revealed in Gregorie and Chaite, Phys. Rev. Lett., 92, 025702 (2004) is discussed and the explanation of it is proposed.

Effects of Kinetic Processes in Shaping Io's Global Plasma Environment: A 3D Hybrid Model

NASA Technical Reports Server (NTRS)

Lipatov, Alexander S.; Combi, Michael R.

2004-01-01

The global dynamics of the ionized and neutral components in the environment of Io plays an important role in the interaction of Jupiter's corotating magnetospheric plasma with Io. The stationary simulation of this problem was done in the MHD and the electrodynamics approaches. One of the main significant results from the simplified two-fluid model simulations was a production of the structure of the double-peak in the magnetic field signature of the I0 flyby that could not be explained by standard MHD models. In this paper, we develop a method of kinetic ion simulation. This method employs the fluid description for electrons and neutrals whereas for ions multilevel, drift-kinetic and particle, approaches are used. We also take into account charge-exchange and photoionization processes. Our model provides much more accurate description for ion dynamics and allows us to take into account the realistic anisotropic ion distribution that cannot be done in fluid simulations. The first results of such simulation of the dynamics of ions in the Io's environment are discussed in this paper.

Dynamic Modeling of the Human Coagulation Cascade Using Reduced Order Effective Kinetic Models (Open Access)

DTIC Science & Technology

2015-03-16

shaded region around each total sensitivity value was the maximum uncertainty in that value estimated by the Sobol method. 2.4. Global Sensitivity...Performance We conducted a global sensitivity analysis, using the variance-based method of Sobol , to estimate which parameters controlled the...Hunter, J.D. Matplotlib: A 2D Graphics Environment. Comput. Sci. Eng. 2007, 9, 90–95. 69. Sobol , I. Global sensitivity indices for nonlinear

New types of experimental data shape the use of enzyme kinetics for dynamic network modeling.

PubMed

Tummler, Katja; Lubitz, Timo; Schelker, Max; Klipp, Edda

2014-01-01

Since the publication of Leonor Michaelis and Maude Menten's paper on the reaction kinetics of the enzyme invertase in 1913, molecular biology has evolved tremendously. New measurement techniques allow in vivo characterization of the whole genome, proteome or transcriptome of cells, whereas the classical enzyme essay only allows determination of the two Michaelis-Menten parameters V and K(m). Nevertheless, Michaelis-Menten kinetics are still commonly used, not only in the in vitro context of enzyme characterization but also as a rate law for enzymatic reactions in larger biochemical reaction networks. In this review, we give an overview of the historical development of kinetic rate laws originating from Michaelis-Menten kinetics over the past 100 years. Furthermore, we briefly summarize the experimental techniques used for the characterization of enzymes, and discuss web resources that systematically store kinetic parameters and related information. Finally, describe the novel opportunities that arise from using these data in dynamic mathematical modeling. In this framework, traditional in vitro approaches may be combined with modern genome-scale measurements to foster thorough understanding of the underlying complex mechanisms. © 2013 FEBS.

Structural analysis as an alternative to identify and determine mode of action of antimicrobial peptides: proposition of a kinetic model based on molecular dynamics studies.

PubMed

Robles-Gomez, Edson Edinho; Flores-Villegas, Mirelle Citlali; Gonzalez-Manjarrez, Alicia; Soriano-Garcia, Manuel

2013-05-01

Antimicrobial peptides (AMPs) constitute an important alternative in the search for new treatments against pathogens. We analyzed the sequence variability in cytokine and chemokine proteins to investigate whether these molecules contain a sequence useful in the development of new AMPs. Cluster analysis allowed the identification of tracts, grouped in five categories showing structure and sequence homology. The structure and function relationship among these groups, was analyzed using physicochemical parameters such as length, sequence, charge, hydrophobicity and helicity, which allowed the selection of a candidate that could constitute an AMP. This peptide comprises the C-terminal alpha-helix of chemokines CXCL4/PF-457-70. Far-UV CD spectroscopy showed that this molecule adopts a random conformation in aqueous solution and the addition of 2, 2, 2 trifluoroethanol (TFE) is required to induce a helical secondary structure. The CXCL4/PF-457-70 peptide was found to have antimicrobial activity and very limited hemolytic activity. The mechanism of action was analyzed using model kinetics and molecular dynamics. The kinetic model led to a reasonable assumption about a rate constant and regulatory step on its mechanism of action. Using molecular dynamics simulations, the structural properties the CXCL4/PF-457-70 have been examined in a membrane environment. Our results show that this peptide has a strong preference for binding to the lipid head groups, consequently, increasing the surface density and decreasing the lateral mobility of the lipids alters its functionality.

Viral kinetic modeling: state of the art

DOE PAGES

Canini, Laetitia; Perelson, Alan S.

2014-06-25

Viral kinetic modeling has led to increased understanding of the within host dynamics of viral infections and the effects of therapy. Here we review recent developments in the modeling of viral infection kinetics with emphasis on two infectious diseases: hepatitis C and influenza. We review how viral kinetic modeling has evolved from simple models of viral infections treated with a drug or drug cocktail with an assumed constant effectiveness to models that incorporate drug pharmacokinetics and pharmacodynamics, as well as phenomenological models that simply assume drugs have time varying-effectiveness. We also discuss multiscale models that include intracellular events in viralmore » replication, models of drug-resistance, models that include innate and adaptive immune responses and models that incorporate cell-to-cell spread of infection. Overall, viral kinetic modeling has provided new insights into the understanding of the disease progression and the modes of action of several drugs. In conclusion, we expect that viral kinetic modeling will be increasingly used in the coming years to optimize drug regimens in order to improve therapeutic outcomes and treatment tolerability for infectious diseases.« less

Kinetic exchange models: From molecular physics to social science

NASA Astrophysics Data System (ADS)

Patriarca, Marco; Chakraborti, Anirban

2013-08-01

We discuss several multi-agent models that have their origin in the kinetic exchange theory of statistical mechanics and have been recently applied to a variety of problems in the social sciences. This class of models can be easily adapted for simulations in areas other than physics, such as the modeling of income and wealth distributions in economics and opinion dynamics in sociology.

Emergent kinetic constraints, ergodicity breaking, and cooperative dynamics in noisy quantum systems

NASA Astrophysics Data System (ADS)

Everest, B.; Marcuzzi, M.; Garrahan, J. P.; Lesanovsky, I.

2016-11-01

Kinetically constrained spin systems play an important role in understanding key properties of the dynamics of slowly relaxing materials, such as glasses. Recent experimental studies have revealed that manifest kinetic constraints govern the evolution of strongly interacting gases of highly excited atoms in a noisy environment. Motivated by this development we explore which types of kinetically constrained dynamics can generally emerge in quantum spin systems subject to strong noise and show how, in this framework, constraints are accompanied by conservation laws. We discuss an experimentally realizable case of a lattice gas, where the interplay between those and the geometry of the lattice leads to collective behavior and time-scale separation even at infinite temperature. This is in contrast to models of glass-forming substances which typically rely on low temperatures and the consequent suppression of thermal activation.

Complete protein-protein association kinetics in atomic detail revealed by molecular dynamics simulations and Markov modelling

NASA Astrophysics Data System (ADS)

Plattner, Nuria; Doerr, Stefan; de Fabritiis, Gianni; Noé, Frank

2017-10-01

Protein-protein association is fundamental to many life processes. However, a microscopic model describing the structures and kinetics during association and dissociation is lacking on account of the long lifetimes of associated states, which have prevented efficient sampling by direct molecular dynamics (MD) simulations. Here we demonstrate protein-protein association and dissociation in atomistic resolution for the ribonuclease barnase and its inhibitor barstar by combining adaptive high-throughput MD simulations and hidden Markov modelling. The model reveals experimentally consistent intermediate structures, energetics and kinetics on timescales from microseconds to hours. A variety of flexibly attached intermediates and misbound states funnel down to a transition state and a native basin consisting of the loosely bound near-native state and the tightly bound crystallographic state. These results offer a deeper level of insight into macromolecular recognition and our approach opens the door for understanding and manipulating a wide range of macromolecular association processes.

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

Wang, Yujie; Gong, Sha; Wang, Zhen

The thermodynamic and kinetic parameters of an RNA base pair were obtained through a long-time molecular dynamics simulation of the opening-closing switch process of the base pair near its melting temperature. The thermodynamic parameters were in good agreement with the nearest-neighbor model. The opening rates showed strong temperature dependence, however, the closing rates showed only weak temperature dependence. The transition path time was weakly temperature dependent and was insensitive to the energy barrier. The diffusion constant exhibited super-Arrhenius behavior. The free energy barrier of breaking a single base stack results from the enthalpy increase, ΔH, caused by the disruption ofmore » hydrogen bonding and base-stacking interactions. The free energy barrier of base pair closing comes from the unfavorable entropy loss, ΔS, caused by the restriction of torsional angles. These results suggest that a one-dimensional free energy surface is sufficient to accurately describe the dynamics of base pair opening and closing, and the dynamics are Brownian.« less

WAKES: Wavelet Adaptive Kinetic Evolution Solvers

NASA Astrophysics Data System (ADS)

Mardirian, Marine; Afeyan, Bedros; Larson, David

2016-10-01

We are developing a general capability to adaptively solve phase space evolution equations mixing particle and continuum techniques in an adaptive manner. The multi-scale approach is achieved using wavelet decompositions which allow phase space density estimation to occur with scale dependent increased accuracy and variable time stepping. Possible improvements on the SFK method of Larson are discussed, including the use of multiresolution analysis based Richardson-Lucy Iteration, adaptive step size control in explicit vs implicit approaches. Examples will be shown with KEEN waves and KEEPN (Kinetic Electrostatic Electron Positron Nonlinear) waves, which are the pair plasma generalization of the former, and have a much richer span of dynamical behavior. WAKES techniques are well suited for the study of driven and released nonlinear, non-stationary, self-organized structures in phase space which have no fluid, limit nor a linear limit, and yet remain undamped and coherent well past the drive period. The work reported here is based on the Vlasov-Poisson model of plasma dynamics. Work supported by a Grant from the AFOSR.

In situ dynamic observations of perovskite crystallisation and microstructure evolution intermediated from [PbI6]4- cage nanoparticles

NASA Astrophysics Data System (ADS)

Hu, Qin; Zhao, Lichen; Wu, Jiang; Gao, Ke; Luo, Deying; Jiang, Yufeng; Zhang, Ziyi; Zhu, Chenhui; Schaible, Eric; Hexemer, Alexander; Wang, Cheng; Liu, Yi; Zhang, Wei; Grätzel, Michael; Liu, Feng; Russell, Thomas P.; Zhu, Rui; Gong, Qihuang

2017-06-01

Hybrid lead halide perovskites have emerged as high-performance photovoltaic materials with their extraordinary optoelectronic properties. In particular, the remarkable device efficiency is strongly influenced by the perovskite crystallinity and the film morphology. Here, we investigate the perovskites crystallisation kinetics and growth mechanism in real time from liquid precursor continually to the final uniform film. We utilize some advanced in situ characterisation techniques including synchrotron-based grazing incident X-ray diffraction to observe crystal structure and chemical transition of perovskites. The nano-assemble model from perovskite intermediated [PbI6]4- cage nanoparticles to bulk polycrystals is proposed to understand perovskites formation at a molecular- or nano-level. A crystallisation-depletion mechanism is developed to elucidate the periodic crystallisation and the kinetically trapped morphology at a mesoscopic level. Based on these in situ dynamics studies, the whole process of the perovskites formation and transformation from the molecular to the microstructure over relevant temperature and time scales is successfully demonstrated.

In situ dynamic observations of perovskite crystallisation and microstructure evolution intermediated from [PbI6]4− cage nanoparticles

PubMed Central

Hu, Qin; Zhao, Lichen; Wu, Jiang; Gao, Ke; Luo, Deying; Jiang, Yufeng; Zhang, Ziyi; Zhu, Chenhui; Schaible, Eric; Hexemer, Alexander; Wang, Cheng; Liu, Yi; Zhang, Wei; Grätzel, Michael; Liu, Feng; Russell, Thomas P.; Zhu, Rui; Gong, Qihuang

2017-01-01

Hybrid lead halide perovskites have emerged as high-performance photovoltaic materials with their extraordinary optoelectronic properties. In particular, the remarkable device efficiency is strongly influenced by the perovskite crystallinity and the film morphology. Here, we investigate the perovskites crystallisation kinetics and growth mechanism in real time from liquid precursor continually to the final uniform film. We utilize some advanced in situ characterisation techniques including synchrotron-based grazing incident X-ray diffraction to observe crystal structure and chemical transition of perovskites. The nano-assemble model from perovskite intermediated [PbI6]4− cage nanoparticles to bulk polycrystals is proposed to understand perovskites formation at a molecular- or nano-level. A crystallisation-depletion mechanism is developed to elucidate the periodic crystallisation and the kinetically trapped morphology at a mesoscopic level. Based on these in situ dynamics studies, the whole process of the perovskites formation and transformation from the molecular to the microstructure over relevant temperature and time scales is successfully demonstrated. PMID:28635947

Analytical structure, dynamics, and coarse graining of a kinetic model of an active fluid

NASA Astrophysics Data System (ADS)

Gao, Tong; Betterton, Meredith D.; Jhang, An-Sheng; Shelley, Michael J.

2017-09-01

We analyze one of the simplest active suspensions with complex dynamics: a suspension of immotile "extensor" particles that exert active extensile dipolar stresses on the fluid in which they are immersed. This is relevant to several experimental systems, such as recently studied tripartite rods that create extensile flows by consuming a chemical fuel. We first describe the system through a Doi-Onsager kinetic theory based on microscopic modeling. This theory captures the active stresses produced by the particles that can drive hydrodynamic instabilities, as well as the steric interactions of rodlike particles that lead to nematic alignment. This active nematic system yields complex flows and disclination defect dynamics very similar to phenomenological Landau-deGennes Q -tensor theories for active nematic fluids, as well as by more complex Doi-Onsager theories for polar microtubule-motor-protein systems. We apply the quasiequilibrium Bingham closure, used to study suspensions of passive microscopic rods, to develop a nonstandard Q -tensor theory. We demonstrate through simulation that this B Q -tensor theory gives an excellent analytical and statistical accounting of the suspension's complex dynamics, at a far reduced computational cost. Finally, we apply the B Q -tensor model to study the dynamics of extensor suspensions in circular and biconcave domains. In circular domains, we reproduce previous results for systems with weak nematic alignment, but for strong alignment we find unusual dynamics with activity-controlled defect production and absorption at the boundaries of the domain. In biconcave domains, a Fredericks-like transition occurs as the width of the neck connecting the two disks is varied.

Colored Petri net modeling and simulation of signal transduction pathways.

PubMed

Lee, Dong-Yup; Zimmer, Ralf; Lee, Sang Yup; Park, Sunwon

2006-03-01

Presented herein is a methodology for quantitatively analyzing the complex signaling network by resorting to colored Petri nets (CPN). The mathematical as well as Petri net models for two basic reaction types were established, followed by the extension to a large signal transduction system stimulated by epidermal growth factor (EGF) in an application study. The CPN models based on the Petri net representation and the conservation and kinetic equations were used to examine the dynamic behavior of the EGF signaling pathway. The usefulness of Petri nets is demonstrated for the quantitative analysis of the signal transduction pathway. Moreover, the trade-offs between modeling capability and simulation efficiency of this pathway are explored, suggesting that the Petri net model can be invaluable in the initial stage of building a dynamic model.

Kinetic Study of Acetone-Butanol-Ethanol Fermentation in Continuous Culture

PubMed Central

Buehler, Edward A.; Mesbah, Ali

2016-01-01

Acetone-butanol-ethanol (ABE) fermentation by clostridia has shown promise for industrial-scale production of biobutanol. However, the continuous ABE fermentation suffers from low product yield, titer, and productivity. Systems analysis of the continuous ABE fermentation will offer insights into its metabolic pathway as well as into optimal fermentation design and operation. For the ABE fermentation in continuous Clostridium acetobutylicum culture, this paper presents a kinetic model that includes the effects of key metabolic intermediates and enzymes as well as culture pH, product inhibition, and glucose inhibition. The kinetic model is used for elucidating the behavior of the ABE fermentation under the conditions that are most relevant to continuous cultures. To this end, dynamic sensitivity analysis is performed to systematically investigate the effects of culture conditions, reaction kinetics, and enzymes on the dynamics of the ABE production pathway. The analysis provides guidance for future metabolic engineering and fermentation optimization studies. PMID:27486663

Carbonic Anhydrase, Calcification Dynamics and Stable Isotope Vital Effects: Deep Sea Corals and Beyond

NASA Astrophysics Data System (ADS)

Chen, S.; Gagnon, A. C.; Adkins, J. F.

2017-12-01

The stable isotope compositions of biogenic carbonates have been used for paleoceanographic and paleoclimatic reconstructions for decades, and produced some of the most iconic records in the field. However, we still lack a fully mechanistic understanding of the stable isotope proxies, especially the biological overprint on the environmental signals termed "vital effects". A ubiquitous feature of stable isotope vital effects in marine calcifying organisms is a strong correlation between δ18O and δ13C in a range of values that are depleted from equilibrium. Two mechanisms have been proposed to explain this correlation, one based on kinetic isotope effects during CO2(aq)-HCO3- inter-conversion, the other based on equilibrium isotope exchange during pH dependent speciation of the dissolved inorganic carbon pool. Neither mechanism explains all the stable isotope features observed in biogenic carbonates. Here we present a fully kinetic model of biomineralization and its isotope effects using deep sea corals as a test organism. A key component of our model is the consideration of the enzyme carbonic anhydrase in catalyzing the CO2(aq)-HCO3- inter-conversion reactions in the extracellular calcifying fluid (ECF). We find that the amount of carbonic anhydrase not only modulates the carbonate chemistry of the calcifying fluid, but also helps explain the slope of the δ18O-δ13C correlation. With this model, we are not only able to fit deep sea coral data, but also explain the stable isotope vital effects of other calcifying organisms. This fully kinetic model of stable isotope vital effects and the underlying calcification dynamics may also help us better understand mechanisms of other paleoceanographic tracers in biogenic carbonates, including boron isotopes and trace metal proxies.

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

Marinov, N.M.; Westbrook, C.K.; Cloutman, L.D.

Work being carried out at LLNL has concentrated on studies of the role of chemical kinetics in a variety of problems related to hydrogen combustion in practical combustion systems, with an emphasis on vehicle propulsion. Use of hydrogen offers significant advantages over fossil fuels, and computer modeling provides advantages when used in concert with experimental studies. Many numerical {open_quotes}experiments{close_quotes} can be carried out quickly and efficiently, reducing the cost and time of system development, and many new and speculative concepts can be screened to identify those with sufficient promise to pursue experimentally. This project uses chemical kinetic and fluid dynamicmore » computational modeling to examine the combustion characteristics of systems burning hydrogen, either as the only fuel or mixed with natural gas. Oxidation kinetics are combined with pollutant formation kinetics, including formation of oxides of nitrogen but also including air toxics in natural gas combustion. We have refined many of the elementary kinetic reaction steps in the detailed reaction mechanism for hydrogen oxidation. To extend the model to pressures characteristic of internal combustion engines, it was necessary to apply theoretical pressure falloff formalisms for several key steps in the reaction mechanism. We have continued development of simplified reaction mechanisms for hydrogen oxidation, we have implemented those mechanisms into multidimensional computational fluid dynamics models, and we have used models of chemistry and fluid dynamics to address selected application problems. At the present time, we are using computed high pressure flame, and auto-ignition data to further refine the simplified kinetics models that are then to be used in multidimensional fluid mechanics models. Detailed kinetics studies have investigated hydrogen flames and ignition of hydrogen behind shock waves, intended to refine the detailed reactions mechanisms.« less

A simple hydrodynamic model of tornado-like vortices

NASA Astrophysics Data System (ADS)

Kurgansky, M. V.

2015-05-01

Based on similarity arguments, a simple fluid dynamic model of tornado-like vortices is offered that, with account for "vortex breakdown" at a certain height above the ground, relates the maximal azimuthal velocity in the vortex, reachable near the ground surface, to the convective available potential energy (CAPE) stored in the environmental atmosphere under pre-tornado conditions. The relative proportion of the helicity (kinetic energy) destruction (dissipation) in the "vortex breakdown" zone and, accordingly, within the surface boundary layer beneath the vortex is evaluated. These considerations form the basis of the dynamic-statistical analysis of the relationship between the tornado intensity and the CAPE budget in the surrounding atmosphere.

Dye adsorption mechanisms in TiO2 films, and their effects on the photodynamic and photovoltaic properties in dye-sensitized solar cells.

PubMed

Hwang, Kyung-Jun; Shim, Wang-Geun; Kim, Youngjin; Kim, Gunwoo; Choi, Chulmin; Kang, Sang Ook; Cho, Dae Won

2015-09-14

The adsorption mechanism for the N719 dye on a TiO2 electrode was examined by the kinetic and diffusion models (pseudo-first order, pseudo-second order, and intra-particle diffusion models). Among these methods, the observed adsorption kinetics are well-described using the pseudo-second order model. Moreover, the film diffusion process was the main controlling step of adsorption, which was analysed using a diffusion-based model. The photodynamic properties in dye-sensitized solar cells (DSSCs) were investigated using time-resolved transient absorption techniques. The photodynamics of the oxidized N719 species were shown to be dependent on the adsorption time, and also the adsorbed concentration of N719. The photovoltaic parameters (Jsc, Voc, FF and η) of this DSSC were determined in terms of the dye adsorption amounts. The solar cell performance correlates significantly with charge recombination and dye regeneration dynamics, which are also affected by the dye adsorption amounts. Therefore, the photovoltaic performance of this DSSC can be interpreted in terms of the adsorption kinetics and the photodynamics of oxidized N719.

Thermal contact through a two-temperature kinetic Ising chain

NASA Astrophysics Data System (ADS)

Bauer, M.; Cornu, F.

2018-05-01

We consider a model for thermal contact through a diathermal interface between two macroscopic bodies at different temperatures: an Ising spin chain with nearest neighbor interactions is endowed with a Glauber dynamics with different temperatures and kinetic parameters on alternating sites. The inhomogeneity of the kinetic parameter is a novelty with respect to the model of Racz and Zia (1994 Phys. Rev. E 49 139), and we exhibit its influence upon the stationary non equilibrium values of the two-spin correlations at any distance. By mapping to the dynamics of spin domain walls and using free fermion techniques, we determine the scaled generating function for the cumulants of the exchanged heat amounts per unit of time in the long time limit.

Dynamics of bulk electron heating and ionization in solid density plasmas driven by ultra-short relativistic laser pulses

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

Huang, L. G., E-mail: lingen.huang@hzdr.de; Kluge, T.; Cowan, T. E.

The dynamics of bulk heating and ionization is investigated both in simulations and theory, which determines the crucial plasma parameters such as plasma temperature and density in ultra-short relativistic laser-solid target interactions. During laser-plasma interactions, the solid density plasma absorbs a fraction of laser energy and converts it into kinetic energy of electrons. A portion of the electrons with relativistic kinetic energy goes through the solid density plasma and transfers energy into the bulk electrons, which results in bulk electron heating. The bulk electron heating is finally translated into the processes of bulk collisional ionization inside the solid target. Amore » simple model based on the Ohmic heating mechanism indicates that the local and temporal profile of bulk return current is essential to determine the temporal evolution of bulk electron temperature. A series of particle-in-cell simulations showing the local heating model is robust in the cases of target with a preplasma and without a preplasma. Predicting the bulk electron heating is then benefit for understanding the collisional ionization dynamics inside the solid targets. The connection of the heating and ionization inside the solid target is further studied using Thomas-Fermi model.« less

Inference of the sparse kinetic Ising model using the decimation method

NASA Astrophysics Data System (ADS)

Decelle, Aurélien; Zhang, Pan

2015-05-01

In this paper we study the inference of the kinetic Ising model on sparse graphs by the decimation method. The decimation method, which was first proposed in Decelle and Ricci-Tersenghi [Phys. Rev. Lett. 112, 070603 (2014), 10.1103/PhysRevLett.112.070603] for the static inverse Ising problem, tries to recover the topology of the inferred system by setting the weakest couplings to zero iteratively. During the decimation process the likelihood function is maximized over the remaining couplings. Unlike the ℓ1-optimization-based methods, the decimation method does not use the Laplace distribution as a heuristic choice of prior to select a sparse solution. In our case, the whole process can be done auto-matically without fixing any parameters by hand. We show that in the dynamical inference problem, where the task is to reconstruct the couplings of an Ising model given the data, the decimation process can be applied naturally into a maximum-likelihood optimization algorithm, as opposed to the static case where pseudolikelihood method needs to be adopted. We also use extensive numerical studies to validate the accuracy of our methods in dynamical inference problems. Our results illustrate that, on various topologies and with different distribution of couplings, the decimation method outperforms the widely used ℓ1-optimization-based methods.

Ultrasensitive dual phosphorylation dephosphorylation cycle kinetics exhibits canonical competition behavior

NASA Astrophysics Data System (ADS)

Huang, Qingdao; Qian, Hong

2009-09-01

We establish a mathematical model for a cellular biochemical signaling module in terms of a planar differential equation system. The signaling process is carried out by two phosphorylation-dephosphorylation reaction steps that share common kinase and phosphatase with saturated enzyme kinetics. The pair of equations is particularly simple in the present mathematical formulation, but they are singular. A complete mathematical analysis is developed based on an elementary perturbation theory. The dynamics exhibits the canonical competition behavior in addition to bistability. Although widely understood in ecological context, we are not aware of a full range of biochemical competition in a simple signaling network. The competition dynamics has broad implications to cellular processes such as cell differentiation and cancer immunoediting. The concepts of homogeneous and heterogeneous multisite phosphorylation are introduced and their corresponding dynamics are compared: there is no bistability in a heterogeneous dual phosphorylation system. A stochastic interpretation is also provided that further gives intuitive understanding of the bistable behavior inside the cells.

Derivation of the Boltzmann Equation for Financial Brownian Motion: Direct Observation of the Collective Motion of High-Frequency Traders.

PubMed

Kanazawa, Kiyoshi; Sueshige, Takumi; Takayasu, Hideki; Takayasu, Misako

2018-03-30

A microscopic model is established for financial Brownian motion from the direct observation of the dynamics of high-frequency traders (HFTs) in a foreign exchange market. Furthermore, a theoretical framework parallel to molecular kinetic theory is developed for the systematic description of the financial market from microscopic dynamics of HFTs. We report first on a microscopic empirical law of traders' trend-following behavior by tracking the trajectories of all individuals, which quantifies the collective motion of HFTs but has not been captured in conventional order-book models. We next introduce the corresponding microscopic model of HFTs and present its theoretical solution paralleling molecular kinetic theory: Boltzmann-like and Langevin-like equations are derived from the microscopic dynamics via the Bogoliubov-Born-Green-Kirkwood-Yvon hierarchy. Our model is the first microscopic model that has been directly validated through data analysis of the microscopic dynamics, exhibiting quantitative agreements with mesoscopic and macroscopic empirical results.

Building a kinetic Monte Carlo model with a chosen accuracy.

PubMed

Bhute, Vijesh J; Chatterjee, Abhijit

2013-06-28

The kinetic Monte Carlo (KMC) method is a popular modeling approach for reaching large materials length and time scales. The KMC dynamics is erroneous when atomic processes that are relevant to the dynamics are missing from the KMC model. Recently, we had developed for the first time an error measure for KMC in Bhute and Chatterjee [J. Chem. Phys. 138, 084103 (2013)]. The error measure, which is given in terms of the probability that a missing process will be selected in the correct dynamics, requires estimation of the missing rate. In this work, we present an improved procedure for estimating the missing rate. The estimate found using the new procedure is within an order of magnitude of the correct missing rate, unlike our previous approach where the estimate was larger by orders of magnitude. This enables one to find the error in the KMC model more accurately. In addition, we find the time for which the KMC model can be used before a maximum error in the dynamics has been reached.

Derivation of the Boltzmann Equation for Financial Brownian Motion: Direct Observation of the Collective Motion of High-Frequency Traders

NASA Astrophysics Data System (ADS)

Kanazawa, Kiyoshi; Sueshige, Takumi; Takayasu, Hideki; Takayasu, Misako

2018-03-01

A microscopic model is established for financial Brownian motion from the direct observation of the dynamics of high-frequency traders (HFTs) in a foreign exchange market. Furthermore, a theoretical framework parallel to molecular kinetic theory is developed for the systematic description of the financial market from microscopic dynamics of HFTs. We report first on a microscopic empirical law of traders' trend-following behavior by tracking the trajectories of all individuals, which quantifies the collective motion of HFTs but has not been captured in conventional order-book models. We next introduce the corresponding microscopic model of HFTs and present its theoretical solution paralleling molecular kinetic theory: Boltzmann-like and Langevin-like equations are derived from the microscopic dynamics via the Bogoliubov-Born-Green-Kirkwood-Yvon hierarchy. Our model is the first microscopic model that has been directly validated through data analysis of the microscopic dynamics, exhibiting quantitative agreements with mesoscopic and macroscopic empirical results.

Modelling of Batch Lactic Acid Fermentation in
the Presence of Anionic Clay

PubMed Central

Jinescu, Cosmin; Aruş, Vasilica Alisa; Nistor, Ileana Denisa

2014-01-01

Summary Batch fermentation of milk inoculated with lactic acid bacteria was conducted in the presence of hydrotalcite-type anionic clay under static and ultrasonic conditions. An experimental study of the effect of fermentation temperature (t=38–43 °C), clay/milk ratio (R=1–7.5 g/L) and ultrasonic field (ν=0 and 35 kHz) on process dynamics was performed. A mathematical model was selected to describe the fermentation process kinetics and its parameters were estimated based on experimental data. A good agreement between the experimental and simulated results was achieved. Consequently, the model can be employed to predict the dynamics of batch lactic acid fermentation with values of process variables in the studied ranges. A statistical analysis of the data based on a 23 factorial experiment was performed in order to express experimental and model-regressed process responses depending on t, R and ν factors. PMID:27904318

Thoracolumbar spine model with articulated ribcage for the prediction of dynamic spinal loading.

PubMed

Ignasiak, Dominika; Dendorfer, Sebastian; Ferguson, Stephen J

2016-04-11

Musculoskeletal modeling offers an invaluable insight into the spine biomechanics. A better understanding of thoracic spine kinetics is essential for understanding disease processes and developing new prevention and treatment methods. Current models of the thoracic region are not designed for segmental load estimation, or do not include the complex construct of the ribcage, despite its potentially important role in load transmission. In this paper, we describe a numerical musculoskeletal model of the thoracolumbar spine with articulated ribcage, modeled as a system of individual vertebral segments, elastic elements and thoracic muscles, based on a previously established lumbar spine model and data from the literature. The inverse dynamics simulations of the model allow the prediction of spinal loading as well as costal joints kinetics and kinematics. The intradiscal pressure predicted by the model correlated well (R(2)=0.89) with reported intradiscal pressure measurements, providing a first validation of the model. The inclusion of the ribcage did not affect segmental force predictions when the thoracic spine did not perform motion. During thoracic motion tasks, the ribcage had an important influence on the predicted compressive forces and muscle activation patterns. The compressive forces were reduced by up to 32%, or distributed more evenly between thoracic vertebrae, when compared to the predictions of the model without ribcage, for mild thoracic flexion and hyperextension tasks, respectively. The presented musculoskeletal model provides a tool for investigating thoracic spine loading and load sharing between vertebral column and ribcage during dynamic activities. Further validation for specific applications is still necessary. Copyright © 2015 Elsevier Ltd. All rights reserved.

Foundations of modelling of nonequilibrium low-temperature plasmas

NASA Astrophysics Data System (ADS)

Alves, L. L.; Bogaerts, A.; Guerra, V.; Turner, M. M.

2018-02-01

This work explains the need for plasma models, introduces arguments for choosing the type of model that better fits the purpose of each study, and presents the basics of the most common nonequilibrium low-temperature plasma models and the information available from each one, along with an extensive list of references for complementary in-depth reading. The paper presents the following models, organised according to the level of multi-dimensional description of the plasma: kinetic models, based on either a statistical particle-in-cell/Monte-Carlo approach or the solution to the Boltzmann equation (in the latter case, special focus is given to the description of the electron kinetics); multi-fluid models, based on the solution to the hydrodynamic equations; global (spatially-average) models, based on the solution to the particle and energy rate-balance equations for the main plasma species, usually including a very complete reaction chemistry; mesoscopic models for plasma-surface interaction, adopting either a deterministic approach or a stochastic dynamical Monte-Carlo approach. For each plasma model, the paper puts forward the physics context, introduces the fundamental equations, presents advantages and limitations, also from a numerical perspective, and illustrates its application with some examples. Whenever pertinent, the interconnection between models is also discussed, in view of multi-scale hybrid approaches.

A three-state kinetic agent-based model to analyze tax evasion dynamics

NASA Astrophysics Data System (ADS)

Crokidakis, Nuno

2014-11-01

In this work we study the problem of tax evasion on a fully-connected population. For this purpose, we consider that the agents may be in three different states, namely honest tax payers, tax evaders and undecided, that are individuals in an intermediate class among honests and evaders. Every individual can change his/her state following a kinetic exchange opinion dynamics, where the agents interact by pairs with competitive negative (with probability q) and positive (with probability 1-q) couplings, representing agreement/disagreement between pairs of agents. In addition, we consider the punishment rules of the Zaklan econophysics model, for which there is a probability pa of an audit each agent is subject to in every period and a length of time k detected tax evaders remain honest. Our results suggest that below the critical point qc=1/4 of the opinion dynamics the compliance is high, and the punishment rules have a small effect in the population. On the other hand, for q>qc the tax evasion can be considerably reduced by the enforcement mechanism. We also discuss the impact of the presence of the undecided agents in the evolution of the system.

Stopping dynamics of ions passing through correlated honeycomb clusters

NASA Astrophysics Data System (ADS)

Balzer, Karsten; Schlünzen, Niclas; Bonitz, Michael

2016-12-01

A combined nonequilibrium Green functions-Ehrenfest dynamics approach is developed that allows for a time-dependent study of the energy loss of a charged particle penetrating a strongly correlated system at zero and finite temperatures. Numerical results are presented for finite inhomogeneous two-dimensional Fermi-Hubbard models, where the many-electron dynamics in the target are treated fully quantum mechanically and the motion of the projectile is treated classically. The simulations are based on the solution of the two-time Dyson (Keldysh-Kadanoff-Baym) equations using the second-order Born, third-order, and T -matrix approximations of the self-energy. As application, we consider protons and helium nuclei with a kinetic energy between 1 and 500 keV/u passing through planar fragments of the two-dimensional honeycomb lattice and, in particular, examine the influence of electron-electron correlations on the energy exchange between projectile and electron system. We investigate the time dependence of the projectile's kinetic energy (stopping power), the electron density, the double occupancy, and the photoemission spectrum. Finally, we show that, for a suitable choice of the Hubbard model parameters, the results for the stopping power are in fair agreement with ab initio simulations for particle irradiation of single-layer graphene.

A rabbit ventricular action potential model replicating cardiac dynamics at rapid heart rates.

PubMed

Mahajan, Aman; Shiferaw, Yohannes; Sato, Daisuke; Baher, Ali; Olcese, Riccardo; Xie, Lai-Hua; Yang, Ming-Jim; Chen, Peng-Sheng; Restrepo, Juan G; Karma, Alain; Garfinkel, Alan; Qu, Zhilin; Weiss, James N

2008-01-15

Mathematical modeling of the cardiac action potential has proven to be a powerful tool for illuminating various aspects of cardiac function, including cardiac arrhythmias. However, no currently available detailed action potential model accurately reproduces the dynamics of the cardiac action potential and intracellular calcium (Ca(i)) cycling at rapid heart rates relevant to ventricular tachycardia and fibrillation. The aim of this study was to develop such a model. Using an existing rabbit ventricular action potential model, we modified the L-type calcium (Ca) current (I(Ca,L)) and Ca(i) cycling formulations based on new experimental patch-clamp data obtained in isolated rabbit ventricular myocytes, using the perforated patch configuration at 35-37 degrees C. Incorporating a minimal seven-state Markovian model of I(Ca,L) that reproduced Ca- and voltage-dependent kinetics in combination with our previously published dynamic Ca(i) cycling model, the new model replicates experimentally observed action potential duration and Ca(i) transient alternans at rapid heart rates, and accurately reproduces experimental action potential duration restitution curves obtained by either dynamic or S1S2 pacing.

Customized Steady-State Constraints for Parameter Estimation in Non-Linear Ordinary Differential Equation Models

PubMed Central

Rosenblatt, Marcus; Timmer, Jens; Kaschek, Daniel

2016-01-01

Ordinary differential equation models have become a wide-spread approach to analyze dynamical systems and understand underlying mechanisms. Model parameters are often unknown and have to be estimated from experimental data, e.g., by maximum-likelihood estimation. In particular, models of biological systems contain a large number of parameters. To reduce the dimensionality of the parameter space, steady-state information is incorporated in the parameter estimation process. For non-linear models, analytical steady-state calculation typically leads to higher-order polynomial equations for which no closed-form solutions can be obtained. This can be circumvented by solving the steady-state equations for kinetic parameters, which results in a linear equation system with comparatively simple solutions. At the same time multiplicity of steady-state solutions is avoided, which otherwise is problematic for optimization. When solved for kinetic parameters, however, steady-state constraints tend to become negative for particular model specifications, thus, generating new types of optimization problems. Here, we present an algorithm based on graph theory that derives non-negative, analytical steady-state expressions by stepwise removal of cyclic dependencies between dynamical variables. The algorithm avoids multiple steady-state solutions by construction. We show that our method is applicable to most common classes of biochemical reaction networks containing inhibition terms, mass-action and Hill-type kinetic equations. Comparing the performance of parameter estimation for different analytical and numerical methods of incorporating steady-state information, we show that our approach is especially well-tailored to guarantee a high success rate of optimization. PMID:27243005

Customized Steady-State Constraints for Parameter Estimation in Non-Linear Ordinary Differential Equation Models.

PubMed

Rosenblatt, Marcus; Timmer, Jens; Kaschek, Daniel

2016-01-01

Ordinary differential equation models have become a wide-spread approach to analyze dynamical systems and understand underlying mechanisms. Model parameters are often unknown and have to be estimated from experimental data, e.g., by maximum-likelihood estimation. In particular, models of biological systems contain a large number of parameters. To reduce the dimensionality of the parameter space, steady-state information is incorporated in the parameter estimation process. For non-linear models, analytical steady-state calculation typically leads to higher-order polynomial equations for which no closed-form solutions can be obtained. This can be circumvented by solving the steady-state equations for kinetic parameters, which results in a linear equation system with comparatively simple solutions. At the same time multiplicity of steady-state solutions is avoided, which otherwise is problematic for optimization. When solved for kinetic parameters, however, steady-state constraints tend to become negative for particular model specifications, thus, generating new types of optimization problems. Here, we present an algorithm based on graph theory that derives non-negative, analytical steady-state expressions by stepwise removal of cyclic dependencies between dynamical variables. The algorithm avoids multiple steady-state solutions by construction. We show that our method is applicable to most common classes of biochemical reaction networks containing inhibition terms, mass-action and Hill-type kinetic equations. Comparing the performance of parameter estimation for different analytical and numerical methods of incorporating steady-state information, we show that our approach is especially well-tailored to guarantee a high success rate of optimization.

Electron-phonon thermalization in a scalable method for real-time quantum dynamics

DOE PAGES

Rizzi, Valerio; Todorov, Tchavdar N.; Kohanoff, Jorge J.; ...

2016-01-27

Here, we present a quantum simulation method that follows the dynamics of out-of-equilibrium many-body systems of electrons and oscillators in real time. Its cost is linear in the number of oscillators and it can probe time scales from attoseconds to hundreds of picoseconds. Contrary to Ehrenfest dynamics, it can thermalize starting from a variety of initial conditions, including electronic population inversion. While an electronic temperature can be defined in terms of a nonequilibrium entropy, a Fermi-Dirac distribution in general emerges only after thermalization. These results can be used to construct a kinetic model of electron-phonon equilibration based on the explicitmore » quantum dynamics.« less

Conformation-controlled binding kinetics of antibodies

NASA Astrophysics Data System (ADS)

Galanti, Marta; Fanelli, Duccio; Piazza, Francesco

2016-01-01

Antibodies are large, extremely flexible molecules, whose internal dynamics is certainly key to their astounding ability to bind antigens of all sizes, from small hormones to giant viruses. In this paper, we build a shape-based coarse-grained model of IgG molecules and show that it can be used to generate 3D conformations in agreement with single-molecule Cryo-Electron Tomography data. Furthermore, we elaborate a theoretical model that can be solved exactly to compute the binding rate constant of a small antigen to an IgG in a prescribed 3D conformation. Our model shows that the antigen binding process is tightly related to the internal dynamics of the IgG. Our findings pave the way for further investigation of the subtle connection between the dynamics and the function of large, flexible multi-valent molecular machines.

Modeling of Non-Isothermal Cryogenic Fluid Sloshing

NASA Technical Reports Server (NTRS)

Agui, Juan H.; Moder, Jeffrey P.

2015-01-01

A computational fluid dynamic model was used to simulate the thermal destratification in an upright self-pressurized cryostat approximately half-filled with liquid nitrogen and subjected to forced sinusoidal lateral shaking. A full three-dimensional computational grid was used to model the tank dynamics, fluid flow and thermodynamics using the ANSYS Fluent code. A non-inertial grid was used which required the addition of momentum and energy source terms to account for the inertial forces, energy transfer and wall reaction forces produced by the shaken tank. The kinetics-based Schrage mass transfer model provided the interfacial mass transfer due to evaporation and condensation at the sloshing interface. The dynamic behavior of the sloshing interface, its amplitude and transition to different wave modes, provided insight into the fluid process at the interface. The tank pressure evolution and temperature profiles compared relatively well with the shaken cryostat experimental test data provided by the Centre National D'Etudes Spatiales.

Rational Design of Glucose-Responsive Insulin Using Pharmacokinetic Modeling.

PubMed

Bakh, Naveed A; Bisker, Gili; Lee, Michael A; Gong, Xun; Strano, Michael S

2017-11-01

A glucose responsive insulin (GRI) is a therapeutic that modulates its potency, concentration, or dosing of insulin in relation to a patient's dynamic glucose concentration, thereby approximating aspects of a normally functioning pancreas. Current GRI design lacks a theoretical basis on which to base fundamental design parameters such as glucose reactivity, dissociation constant or potency, and in vivo efficacy. In this work, an approach to mathematically model the relevant parameter space for effective GRIs is induced, and design rules for linking GRI performance to therapeutic benefit are developed. Well-developed pharmacokinetic models of human glucose and insulin metabolism coupled to a kinetic model representation of a freely circulating GRI are used to determine the desired kinetic parameters and dosing for optimal glycemic control. The model examines a subcutaneous dose of GRI with kinetic parameters in an optimal range that results in successful glycemic control within prescribed constraints over a 24 h period. Additionally, it is demonstrated that the modeling approach can find GRI parameters that enable stable glucose levels that persist through a skipped meal. The results provide a framework for exploring the parameter space of GRIs, potentially without extensive, iterative in vivo animal testing. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Acceleration of the chemistry solver for modeling DI engine combustion using dynamic adaptive chemistry (DAC) schemes

NASA Astrophysics Data System (ADS)

Shi, Yu; Liang, Long; Ge, Hai-Wen; Reitz, Rolf D.

2010-03-01

Acceleration of the chemistry solver for engine combustion is of much interest due to the fact that in practical engine simulations extensive computational time is spent solving the fuel oxidation and emission formation chemistry. A dynamic adaptive chemistry (DAC) scheme based on a directed relation graph error propagation (DRGEP) method has been applied to study homogeneous charge compression ignition (HCCI) engine combustion with detailed chemistry (over 500 species) previously using an R-value-based breadth-first search (RBFS) algorithm, which significantly reduced computational times (by as much as 30-fold). The present paper extends the use of this on-the-fly kinetic mechanism reduction scheme to model combustion in direct-injection (DI) engines. It was found that the DAC scheme becomes less efficient when applied to DI engine simulations using a kinetic mechanism of relatively small size and the accuracy of the original DAC scheme decreases for conventional non-premixed combustion engine. The present study also focuses on determination of search-initiating species, involvement of the NOx chemistry, selection of a proper error tolerance, as well as treatment of the interaction of chemical heat release and the fuel spray. Both the DAC schemes were integrated into the ERC KIVA-3v2 code, and simulations were conducted to compare the two schemes. In general, the present DAC scheme has better efficiency and similar accuracy compared to the previous DAC scheme. The efficiency depends on the size of the chemical kinetics mechanism used and the engine operating conditions. For cases using a small n-heptane kinetic mechanism of 34 species, 30% of the computational time is saved, and 50% for a larger n-heptane kinetic mechanism of 61 species. The paper also demonstrates that by combining the present DAC scheme with an adaptive multi-grid chemistry (AMC) solver, it is feasible to simulate a direct-injection engine using a detailed n-heptane mechanism with 543 species with practical computer time.

An investigation into the crystallization tendency/kinetics of amorphous active pharmaceutical ingredients: A case study with dipyridamole and cinnarizine.

PubMed

Baghel, Shrawan; Cathcart, Helen; Redington, Wynette; O'Reilly, Niall J

2016-07-01

Amorphous drug formulations have great potential to enhance solubility and thus bioavailability of BCS class II drugs. However, the higher free energy and molecular mobility of the amorphous form drive them towards the crystalline state which makes them unstable. Accurate determination of the crystallization tendency/kinetics is the key to the successful design and development of such systems. In this study, dipyridamole (DPM) and cinnarizine (CNZ) have been selected as model compounds. Thermodynamic fragility (mT) was measured from the heat capacity change at the glass transition temperature (Tg) whereas dynamic fragility (mD) was evaluated using methods based on extrapolation of configurational entropy to zero [Formula: see text] , and heating rate dependence of Tg [Formula: see text] . The mean relaxation time of amorphous drugs was calculated from the Vogel-Tammann-Fulcher (VTF) equation. Furthermore, the correlation between fragility and glass forming ability (GFA) of the model drugs has been established and the relevance of these parameters to crystallization of amorphous drugs is also assessed. Moreover, the crystallization kinetics of model drugs under isothermal conditions has been studied using Johnson-Mehl-Avrami (JMA) approach to determine the Avrami constant 'n' which provides an insight into the mechanism of crystallization. To further probe into the crystallization mechanism, the non-isothermal crystallization kinetics of model systems were also analysed by statistically fitting the crystallization data to 15 different kinetic models and the relevance of model-free kinetic approach has been established. The crystallization mechanism for DPM and CNZ at each extent of transformation has been predicted. The calculated fragility, glass forming ability (GFA) and crystallization kinetics are found to be in good correlation with the stability prediction of amorphous solid dispersions. Thus, this research work involves a multidisciplinary approach to establish fragility, GFA and crystallization kinetics as stability predictors for amorphous drug formulations. Copyright © 2016 Elsevier B.V. All rights reserved.

NASA upper atmosphere research program: Research summaries, 1990 - 1991. Report to the Congress and the Environmental Protection Agency

NASA Technical Reports Server (NTRS)

1992-01-01

The objectives, status, and accomplishments of the research tasks supported under the NASA Upper Atmosphere Research Program (UARP) are presented. The topics covered include the following: balloon-borne in situ measurements; balloon-borne remote measurements; ground-based measurements; aircraft-borne measurements; rocket-borne measurements; instrument development; reaction kinetics and photochemistry; spectroscopy; stratospheric dynamics and related analysis; stratospheric chemistry, analysis, and related modeling; and global chemical modeling.

Mathematical modeling and computational prediction of cancer drug resistance.

PubMed

Sun, Xiaoqiang; Hu, Bin

2017-06-23

Diverse forms of resistance to anticancer drugs can lead to the failure of chemotherapy. Drug resistance is one of the most intractable issues for successfully treating cancer in current clinical practice. Effective clinical approaches that could counter drug resistance by restoring the sensitivity of tumors to the targeted agents are urgently needed. As numerous experimental results on resistance mechanisms have been obtained and a mass of high-throughput data has been accumulated, mathematical modeling and computational predictions using systematic and quantitative approaches have become increasingly important, as they can potentially provide deeper insights into resistance mechanisms, generate novel hypotheses or suggest promising treatment strategies for future testing. In this review, we first briefly summarize the current progress of experimentally revealed resistance mechanisms of targeted therapy, including genetic mechanisms, epigenetic mechanisms, posttranslational mechanisms, cellular mechanisms, microenvironmental mechanisms and pharmacokinetic mechanisms. Subsequently, we list several currently available databases and Web-based tools related to drug sensitivity and resistance. Then, we focus primarily on introducing some state-of-the-art computational methods used in drug resistance studies, including mechanism-based mathematical modeling approaches (e.g. molecular dynamics simulation, kinetic model of molecular networks, ordinary differential equation model of cellular dynamics, stochastic model, partial differential equation model, agent-based model, pharmacokinetic-pharmacodynamic model, etc.) and data-driven prediction methods (e.g. omics data-based conventional screening approach for node biomarkers, static network approach for edge biomarkers and module biomarkers, dynamic network approach for dynamic network biomarkers and dynamic module network biomarkers, etc.). Finally, we discuss several further questions and future directions for the use of computational methods for studying drug resistance, including inferring drug-induced signaling networks, multiscale modeling, drug combinations and precision medicine. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Combination of Markov state models and kinetic networks for the analysis of molecular dynamics simulations of peptide folding.

PubMed

Radford, Isolde H; Fersht, Alan R; Settanni, Giovanni

2011-06-09

Atomistic molecular dynamics simulations of the TZ1 beta-hairpin peptide have been carried out using an implicit model for the solvent. The trajectories have been analyzed using a Markov state model defined on the projections along two significant observables and a kinetic network approach. The Markov state model allowed for an unbiased identification of the metastable states of the system, and provided the basis for commitment probability calculations performed on the kinetic network. The kinetic network analysis served to extract the main transition state for folding of the peptide and to validate the results from the Markov state analysis. The combination of the two techniques allowed for a consistent and concise characterization of the dynamics of the peptide. The slowest relaxation process identified is the exchange between variably folded and denatured species, and the second slowest process is the exchange between two different subsets of the denatured state which could not be otherwise identified by simple inspection of the projected trajectory. The third slowest process is the exchange between a fully native and a partially folded intermediate state characterized by a native turn with a proximal backbone H-bond, and frayed side-chain packing and termini. The transition state for the main folding reaction is similar to the intermediate state, although a more native like side-chain packing is observed.

Dynamics and Self-consistent Chaos in a Mean Field Hamiltonian Model

NASA Astrophysics Data System (ADS)

del-Castillo-Negrete, Diego

We study a mean field Hamiltonian model that describes the collective dynamics of marginally stable fluids and plasmas in the finite N and N-> infty kinetic limit (where N is the number of particles). The linear stability of equilibria in the kinetic model is studied as well as the initial value problem including Landau damping . Numerical simulations show the existence of coherent, rotating dipole states. We approximate the dipole as two macroparticles and show that the N=2 limit has a family of rotating integrable solutions that provide an accurate description of the dynamics. We discuss the role of self-consistent Hamiltonian chaos in the formation of coherent structures, and discuss a mechanism of "violent" mixing caused by a self-consistent elliptic-hyperbolic bifurcation in phase space.

Kinetic Measurements Reveal Enhanced Protein-Protein Interactions at Intercellular Junctions

PubMed Central

Shashikanth, Nitesh; Kisting, Meridith A.; Leckband, Deborah E.

2016-01-01

The binding properties of adhesion proteins are typically quantified from measurements with soluble fragments, under conditions that differ radically from the confined microenvironment of membrane bound proteins in adhesion zones. Using classical cadherin as a model adhesion protein, we tested the postulate that confinement within quasi two-dimensional intercellular gaps exposes weak protein interactions that are not detected in solution binding assays. Micropipette-based measurements of cadherin-mediated, cell-cell binding kinetics identified a unique kinetic signature that reflects both adhesive (trans) bonds between cadherins on opposing cells and lateral (cis) interactions between cadherins on the same cell. In solution, proposed lateral interactions were not detected, even at high cadherin concentrations. Mutations postulated to disrupt lateral cadherin association altered the kinetic signatures, but did not affect the adhesive (trans) binding affinity. Perturbed kinetics further coincided with altered cadherin distributions at junctions, wound healing dynamics, and paracellular permeability. Intercellular binding kinetics thus revealed cadherin interactions that occur within confined, intermembrane gaps but not in solution. Findings further demonstrate the impact of these revealed interactions on the organization and function of intercellular junctions. PMID:27009566

Satellite recovery - Attitude dynamics of the targets

NASA Technical Reports Server (NTRS)

Cochran, J. E., Jr.; Lahr, B. S.

1986-01-01

The problems of categorizing and modeling the attitude dynamics of uncontrolled artificial earth satellites which may be targets in recovery attempts are addressed. Methods of classification presented are based on satellite rotational kinetic energy, rotational angular momentum and orbit and on the type of control present prior to the benign failure of the control system. The use of approximate analytical solutions and 'exact' numerical solutions to the equations governing satellite attitude motions to predict uncontrolled attitude motion is considered. Analytical and numerical results are presented for the evolution of satellite attitude motions after active control termination.

Dynamic dual-tracer PET reconstruction.

PubMed

Gao, Fei; Liu, Huafeng; Jian, Yiqiang; Shi, Pengcheng

2009-01-01

Although of important medical implications, simultaneous dual-tracer positron emission tomography reconstruction remains a challenging problem, primarily because the photon measurements from dual tracers are overlapped. In this paper, we propose a simultaneous dynamic dual-tracer reconstruction of tissue activity maps based on guidance from tracer kinetics. The dual-tracer reconstruction problem is formulated in a state-space representation, where parallel compartment models serve as continuous-time system equation describing the tracer kinetic processes of dual tracers, and the imaging data is expressed as discrete sampling of the system states in measurement equation. The image reconstruction problem has therefore become a state estimation problem in a continuous-discrete hybrid paradigm, and H infinity filtering is adopted as the estimation strategy. As H infinity filtering makes no assumptions on the system and measurement statistics, robust reconstruction results can be obtained for the dual-tracer PET imaging system where the statistical properties of measurement data and system uncertainty are not available a priori, even when there are disturbances in the kinetic parameters. Experimental results on digital phantoms, Monte Carlo simulations and physical phantoms have demonstrated the superior performance.

SVD-aided pseudo principal-component analysis: A new method to speed up and improve determination of the optimum kinetic model from time-resolved data

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

Oang, Key Young; Yang, Cheolhee; Muniyappan, Srinivasan

Determination of the optimum kinetic model is an essential prerequisite for characterizing dynamics and mechanism of a reaction. Here, we propose a simple method, termed as singular value decomposition-aided pseudo principal-component analysis (SAPPA), to facilitate determination of the optimum kinetic model from time-resolved data by bypassing any need to examine candidate kinetic models. We demonstrate the wide applicability of SAPPA by examining three different sets of experimental time-resolved data and show that SAPPA can efficiently determine the optimum kinetic model. In addition, the results of SAPPA for both time-resolved X-ray solution scattering (TRXSS) and transient absorption (TA) data of themore » same protein reveal that global structural changes of protein, which is probed by TRXSS, may occur more slowly than local structural changes around the chromophore, which is probed by TA spectroscopy.« less

Ionic solubility and solutal advection governed augmented evaporation kinetics of salt solution pendant droplets

NASA Astrophysics Data System (ADS)

Jaiswal, Vivek; Harikrishnan, A. R.; Khurana, Gargi; Dhar, Purbarun

2018-01-01

The presence of dispersed inclusions is known to modify the interfacial characteristics in liquids by adsorption-desorption of the ions at interfaces. The present article reports the influencing role of dissolved ions in a polar fluid on its evaporation dynamics. The evaporation dynamics of pendant droplets of aqueous solutions of variant simple salts and concentrations have been experimentally studied. The presence of salts is observed to enhance the evaporation rate (obeying the classical D2 law), and the enhancement has been found to hold a direct proportionality to the concentration of the dissolved salt. Furthermore, it is observed that the degree of enhancement in the evaporation rate is also directly proportional to the solubility of the salt in question. The phenomenon is explained based on the chemical kinetics and thermodynamics of hydration of the ionic species in the polar fluid. The classical evaporation rate constant formulation is found to be inadequate in modeling the enhanced species transport. Additional probing via particle image velocimetry reveals augmented internal circulation within the evaporating salt based drops compared to pure water. Mapping the dynamic surface tension reveals that a salt concentration gradient is generated between the bulk and periphery of the droplet and it could be responsible for the internal advection cells visualized. A thermo-solutal Marangoni and Rayleigh convection based mathematical formulation has been put forward, and it is shown that the enhanced solute-thermal convection could play a major role in enhanced evaporation. The internal circulation mapped from experiments is found to be in good quantitative agreement with the model predictions. Scaling analysis further reveals that the stability of the solutal Marangoni convection surpasses the thermal counterpart with higher salt concentration and solubility. The present article sheds insight into the possible domineering role of conjugate thermohydraulic and mass transport phenomena on the evaporation kinetics aqueous droplets with ionic inclusions.

Deposition and transport of Pseudomonas aeruginosa in porous media: lab-scale experiments and model analysis.

PubMed

Kwon, Kyu-Sang; Kim, Song-Bae; Choi, Nag-Choul; Kim, Dong-Ju; Lee, Soonjae; Lee, Sang-Hyup; Choi, Jae-Woo

2013-01-01

In this study, the deposition and transport of Pseudomonas aeruginosa on sandy porous materials have been investigated under static and dynamic flow conditions. For the static experiments, both equilibrium and kinetic batch tests were performed at a 1:3 and 3:1 soil:solution ratio. The batch data were analysed to quantify the deposition parameters under static conditions. Column tests were performed for dynamic flow experiments with KCl solution and bacteria suspended in (1) deionized water, (2) mineral salt medium (MSM) and (3) surfactant + MSM. The equilibrium distribution coefficient (K(d)) was larger at a 1:3 (2.43 mL g(-1)) than that at a 3:1 (0.28 mL g(-1)) soil:solution ratio. Kinetic batch experiments showed that the reversible deposition rate coefficient (k(att)) and the release rate coefficient (k(det)) at a soil:solution ratio of 3:1 were larger than those at a 1:3 ratio. Column experiments showed that an increase in ionic strength resulted in a decrease in peak concentration of bacteria, mass recovery and tailing of the bacterial breakthrough curve (BTC) and that the presence of surfactant enhanced the movement of bacteria through quartz sand, giving increased mass recovery and tailing. Deposition parameters under dynamic condition were determined by fitting BTCs to four different transport models, (1) kinetic reversible, (2) two-site, (3) kinetic irreversible and (4) kinetic reversible and irreversible models. Among these models, Model 4 was more suitable than the others since it includes the irreversible sorption term directly related to the mass loss of bacteria observed in the column experiment. Applicability of the parameters obtained from the batch experiments to simulate the column breakthrough data is evaluated.

Kinetic model for the collisionless sheath of a collisional plasma

DOE PAGES

Tang, Xian-Zhu; Guo, Zehua

2016-08-04

Collisional plasmas typically have mean-free-path still much greater than the Debye length, so the sheath is mostly collisionless. Once the plasma density, temperature, and flow are specified at the sheath entrance, the profile variation of electron and ion density, temperature, flow speed, and conductive heat fluxes inside the sheath is set by collisionless dynamics, and can be predicted by an analytical kinetic model distribution. Finally, these predictions are contrasted in this paper with direct kinetic simulations, showing good agreement.

A kinetic theory for age-structured stochastic birth-death processes

NASA Astrophysics Data System (ADS)

Chou, Tom; Greenman, Chris

Classical age-structured mass-action models such as the McKendrick-von Foerster equation have been extensively studied but they are structurally unable to describe stochastic fluctuations or population-size-dependent birth and death rates. Conversely, current theories that include size-dependent population dynamics (e.g., carrying capacity) cannot be easily extended to take into account age-dependent birth and death rates. In this paper, we present a systematic derivation of a new fully stochastic kinetic theory for interacting age-structured populations. By defining multiparticle probability density functions, we derive a hierarchy of kinetic equations for the stochastic evolution of an aging population undergoing birth and death. We show that the fully stochastic age-dependent birth-death process precludes factorization of the corresponding probability densities, which then must be solved by using a BBGKY-like hierarchy. Our results generalize both deterministic models and existing master equation approaches by providing an intuitive and efficient way to simultaneously model age- and population-dependent stochastic dynamics applicable to the study of demography, stem cell dynamics, and disease evolution. NSF.

Photocatalytic mineralization of commercial herbicides in a pilot-scale solar CPC reactor: photoreactor modeling and reaction kinetics constants independent of radiation field.

PubMed

Colina-Márquez, Jose; Machuca-Martínez, Fiderman; Li Puma, Gianluca

2009-12-01

The six-flux absorption-scattering model (SFM) of the radiation field in the photoreactor, combined with reaction kinetics and fluid-dynamic models, has proved to be suitable to describe the degradation of water pollutants in heterogeneous photocatalytic reactors, combining simplicity and accuracy. In this study, the above approach was extended to model the photocatalytic mineralization of a commercial herbicides mixture (2,4-D, diuron, and ametryne used in Colombian sugar cane crops) in a solar, pilot-scale, compound parabolic collector (CPC) photoreactor using a slurry suspension of TiO(2). The ray-tracing technique was used jointly with the SFM to determine the direction of both the direct and diffuse solar photon fluxes and the spatial profile of the local volumetric rate of photon absorption (LVRPA) in the CPC reactor. Herbicides mineralization kinetics with explicit photon absorption effects were utilized to remove the dependence of the observed rate constants from the reactor geometry and radiation field in the photoreactor. The results showed that the overall model fitted the experimental data of herbicides mineralization in the solar CPC reactor satisfactorily for both cloudy and sunny days. Using the above approach kinetic parameters independent of the radiation field in the reactor can be estimated directly from the results of experiments carried out in a solar CPC reactor. The SFM combined with reaction kinetics and fluid-dynamic models proved to be a simple, but reliable model, for solar photocatalytic applications.

Systematic optimization of fed-batch simultaneous saccharification and fermentation at high-solid loading based on enzymatic hydrolysis and dynamic metabolic modeling of Saccharomyces cerevisiae.

PubMed

Unrean, Pornkamol; Khajeeram, Sutamat; Laoteng, Kobkul

2016-03-01

An integrative simultaneous saccharification and fermentation (SSF) modeling is a useful guiding tool for rapid process optimization to meet the techno-economic requirement of industrial-scale lignocellulosic ethanol production. In this work, we have developed the SSF model composing of a metabolic network of a Saccharomyces cerevisiae cell associated with fermentation kinetics and enzyme hydrolysis model to quantitatively capture dynamic responses of yeast cell growth and fermentation during SSF. By using model-based design of feeding profiles for substrate and yeast cell in the fed-batch SSF process, an efficient ethanol production with high titer of up to 65 g/L and high yield of 85 % of theoretical yield was accomplished. The ethanol titer and productivity was increased by 47 and 41 %, correspondingly, in optimized fed-batch SSF as compared to batch process. The developed integrative SSF model is, therefore, considered as a promising approach for systematic design of economical and sustainable SSF bioprocessing of lignocellulose.

Comparison among Reconstruction Algorithms for Quantitative Analysis of 11C-Acetate Cardiac PET Imaging.

PubMed

Shi, Ximin; Li, Nan; Ding, Haiyan; Dang, Yonghong; Hu, Guilan; Liu, Shuai; Cui, Jie; Zhang, Yue; Li, Fang; Zhang, Hui; Huo, Li

2018-01-01

Kinetic modeling of dynamic 11 C-acetate PET imaging provides quantitative information for myocardium assessment. The quality and quantitation of PET images are known to be dependent on PET reconstruction methods. This study aims to investigate the impacts of reconstruction algorithms on the quantitative analysis of dynamic 11 C-acetate cardiac PET imaging. Suspected alcoholic cardiomyopathy patients ( N = 24) underwent 11 C-acetate dynamic PET imaging after low dose CT scan. PET images were reconstructed using four algorithms: filtered backprojection (FBP), ordered subsets expectation maximization (OSEM), OSEM with time-of-flight (TOF), and OSEM with both time-of-flight and point-spread-function (TPSF). Standardized uptake values (SUVs) at different time points were compared among images reconstructed using the four algorithms. Time-activity curves (TACs) in myocardium and blood pools of ventricles were generated from the dynamic image series. Kinetic parameters K 1 and k 2 were derived using a 1-tissue-compartment model for kinetic modeling of cardiac flow from 11 C-acetate PET images. Significant image quality improvement was found in the images reconstructed using iterative OSEM-type algorithms (OSME, TOF, and TPSF) compared with FBP. However, no statistical differences in SUVs were observed among the four reconstruction methods at the selected time points. Kinetic parameters K 1 and k 2 also exhibited no statistical difference among the four reconstruction algorithms in terms of mean value and standard deviation. However, for the correlation analysis, OSEM reconstruction presented relatively higher residual in correlation with FBP reconstruction compared with TOF and TPSF reconstruction, and TOF and TPSF reconstruction were highly correlated with each other. All the tested reconstruction algorithms performed similarly for quantitative analysis of 11 C-acetate cardiac PET imaging. TOF and TPSF yielded highly consistent kinetic parameter results with superior image quality compared with FBP. OSEM was relatively less reliable. Both TOF and TPSF were recommended for cardiac 11 C-acetate kinetic analysis.

Formulation and closure of compressible turbulence equations in the light of kinetic theory

NASA Technical Reports Server (NTRS)

Tsuge, S.; Sagara, K.

1976-01-01

Fluid-dynamic moment equations, based on a kinetic hierarchy system, are derived governing the interaction between turbulent and thermal fluctuations. The kinetic theory is shown to reduce the inherent complexity of the conventional formalism of compressible turbulence theory and to minimize arbitrariness in formulating the closure condition.

Gas-kinetic unified algorithm for hypersonic flows covering various flow regimes solving Boltzmann model equation in nonequilibrium effect

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

Li, Zhihui; Ma, Qiang; Wu, Junlin

2014-12-09

Based on the Gas-Kinetic Unified Algorithm (GKUA) directly solving the Boltzmann model equation, the effect of rotational non-equilibrium is investigated recurring to the kinetic Rykov model with relaxation property of rotational degrees of freedom. The spin movement of diatomic molecule is described by moment of inertia, and the conservation of total angle momentum is taken as a new Boltzmann collision invariant. The molecular velocity distribution function is integrated by the weight factor on the internal energy, and the closed system of two kinetic controlling equations is obtained with inelastic and elastic collisions. The optimization selection technique of discrete velocity ordinatemore » points and numerical quadrature rules for macroscopic flow variables with dynamic updating evolvement are developed to simulate hypersonic flows, and the gas-kinetic numerical scheme is constructed to capture the time evolution of the discretized velocity distribution functions. The gas-kinetic boundary conditions in thermodynamic non-equilibrium and numerical procedures are studied and implemented by directly acting on the velocity distribution function, and then the unified algorithm of Boltzmann model equation involving non-equilibrium effect is presented for the whole range of flow regimes. The hypersonic flows involving non-equilibrium effect are numerically simulated including the inner flows of shock wave structures in nitrogen with different Mach numbers of 1.5-Ma-25, the planar ramp flow with the whole range of Knudsen numbers of 0.0009-Kn-10 and the three-dimensional re-entering flows around tine double-cone body.« less

A physiology-based parametric imaging method for FDG-PET data

NASA Astrophysics Data System (ADS)

Scussolini, Mara; Garbarino, Sara; Sambuceti, Gianmario; Caviglia, Giacomo; Piana, Michele

2017-12-01

Parametric imaging is a compartmental approach that processes nuclear imaging data to estimate the spatial distribution of the kinetic parameters governing tracer flow. The present paper proposes a novel and efficient computational method for parametric imaging which is potentially applicable to several compartmental models of diverse complexity and which is effective in the determination of the parametric maps of all kinetic coefficients. We consider applications to [18 F]-fluorodeoxyglucose positron emission tomography (FDG-PET) data and analyze the two-compartment catenary model describing the standard FDG metabolization by an homogeneous tissue and the three-compartment non-catenary model representing the renal physiology. We show uniqueness theorems for both models. The proposed imaging method starts from the reconstructed FDG-PET images of tracer concentration and preliminarily applies image processing algorithms for noise reduction and image segmentation. The optimization procedure solves pixel-wise the non-linear inverse problem of determining the kinetic parameters from dynamic concentration data through a regularized Gauss-Newton iterative algorithm. The reliability of the method is validated against synthetic data, for the two-compartment system, and experimental real data of murine models, for the renal three-compartment system.

Quantum Tunneling in Testosterone 6β-Hydroxylation by Cytochrome P450: Reaction Dynamics Calculations Employing Multiconfiguration Molecular-Mechanical Potential Energy Surfaces

NASA Astrophysics Data System (ADS)

Zhang, Yan; Lin, Hai

2009-05-01

Testosterone hydroxylation is a prototypical reaction of human cytochrome P450 3A4, which metabolizes about 50% of oral drugs on the market. Reaction dynamics calculations were carried out for the testosterone 6β-hydrogen abstraction and the 6β-d1-testosterone 6β-duterium abstraction employing a model that consists of the substrate and the active oxidant compound I. The calculations were performed at the level of canonical variational transition state theory with multidimensional tunneling and were based on a semiglobal full-dimensional potential energy surface generated by the multiconfiguration molecular mechanics technique. The tunneling coefficients were found to be around 3, indicating substantial contributions by quantum tunneling. However, the tunneling made only modest contributions to the kinetic isotope effects. The kinetic isotope effects were computed to be about 2 in the doublet spin state and about 5 in the quartet spin state.

Tumor characterization in small animals using magnetic resonance-guided dynamic contrast enhanced diffuse optical tomography

NASA Astrophysics Data System (ADS)

Lin, Yuting; Thayer, Dave; Nalcioglu, Orhan; Gulsen, Gultekin

2011-10-01

We present a magnetic resonance (MR)-guided near-infrared dynamic contrast enhanced diffuse optical tomography (DCE-DOT) system for characterization of tumors using an optical contrast agent (ICG) and a MR contrast agent [Gd-diethylenetriaminepentaacetic acid (DTPA)] in a rat model. Both ICG and Gd-DTPA are injected and monitored simultaneously using a combined MRI-DOT system, resulting in accurate co-registration between two imaging modalities. Fisher rats bearing R3230 breast tumor are imaged using this hybrid system. For the first time, enhancement kinetics of the exogenous contrast ICG is recovered from the DCE-DOT data using MR anatomical a priori information. As tumors grow, they undergo necrosis and the tissue transforms from viable to necrotic. The results show that the physiological changes between viable and necrotic tissue can be differentiated more accurately based on the ICG enhancement kinetics when MR anatomical information is utilized.

Melt infiltration of silicon carbide compacts. I - Study of infiltration dynamics

NASA Technical Reports Server (NTRS)

Asthana, Rajiv; Rohatgi, Pradeep K.

1992-01-01

Countergravity, pressure-assisted infiltration with a 2014 Al alloy of suitably tamped porous compacts of platelet shaped single crystals of alpha (hexagonal) silicon carbide was used to measure particulate wettability and infiltration kinetics under dynamic conditions relevant to pressure casting of composites. A threshold pressure P(th) for ingression of the infiltrant was identified based on the experimental penetration length versus pressure profiles for a range of experimental variables which included infiltration pressure, infiltration time, SiC size and SiC surface chemistry. The results showed that P(th) decreased whereas the penetration length increased with increasing SiC size and infiltration time. Cu-coated SiC led to lower P(th) and larger penetration lengths compared to uncoated SiC under identical conditions. These observations have been discussed in the light of theoretical models of infiltration and the kinetics of wetting.

A Proposal for a Subcritical Reactivity Meter based on Gandini and Salvatores' point kinetics equations for Multiplying Subcritical Systems

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

Pinto, Leticia N.; Dos Santos, Adimir

2015-07-01

Multiplying Subcritical Systems were for a long time poorly studied and its theoretical description remains with plenty open questions. Great interest on such systems arose partly due to the improvement of hybrid concepts, such as the Accelerator-Driven Systems (ADS). Along with the need for new technologies to be developed, further study and understanding of subcritical systems are essential also in more practical situations, such as in the case of a PWR criticalization in their physical startup tests. Point kinetics equations are fundamental to continuously monitor the reactivity behavior to a possible variation of external sources intensity. In this case, quicklymore » and accurately predicting power transients and reactivity becomes crucial. It is known that conventional Reactivity Meters cannot operate in subcritical levels nor describe the dynamics of multiplying systems in these conditions, by the very structure of the classical kinetic equations. Several theoretical models have been proposed to characterize the kinetics of such systems with special regard to the reactivity, as the one developed by Gandini and Salvatores among others. This work presents a discussion about the derivation of point kinetics equations for subcritical systems and the importance of considering the external source. From the point of view of the Gandini and Salvatores' point kinetics model and based on the experimental results provided by Lee and dos Santos, it was possible to develop an innovative approach. This article proposes an algorithm that describes the subcritical reactivity with external source, contributing to the advancement of studies in the field. (authors)« less

Dynamic PET image reconstruction integrating temporal regularization associated with respiratory motion correction for applications in oncology

NASA Astrophysics Data System (ADS)

Merlin, Thibaut; Visvikis, Dimitris; Fernandez, Philippe; Lamare, Frédéric

2018-02-01

Respiratory motion reduces both the qualitative and quantitative accuracy of PET images in oncology. This impact is more significant for quantitative applications based on kinetic modeling, where dynamic acquisitions are associated with limited statistics due to the necessity of enhanced temporal resolution. The aim of this study is to address these drawbacks, by combining a respiratory motion correction approach with temporal regularization in a unique reconstruction algorithm for dynamic PET imaging. Elastic transformation parameters for the motion correction are estimated from the non-attenuation-corrected PET images. The derived displacement matrices are subsequently used in a list-mode based OSEM reconstruction algorithm integrating a temporal regularization between the 3D dynamic PET frames, based on temporal basis functions. These functions are simultaneously estimated at each iteration, along with their relative coefficients for each image voxel. Quantitative evaluation has been performed using dynamic FDG PET/CT acquisitions of lung cancer patients acquired on a GE DRX system. The performance of the proposed method is compared with that of a standard multi-frame OSEM reconstruction algorithm. The proposed method achieved substantial improvements in terms of noise reduction while accounting for loss of contrast due to respiratory motion. Results on simulated data showed that the proposed 4D algorithms led to bias reduction values up to 40% in both tumor and blood regions for similar standard deviation levels, in comparison with a standard 3D reconstruction. Patlak parameter estimations on reconstructed images with the proposed reconstruction methods resulted in 30% and 40% bias reduction in the tumor and lung region respectively for the Patlak slope, and a 30% bias reduction for the intercept in the tumor region (a similar Patlak intercept was achieved in the lung area). Incorporation of the respiratory motion correction using an elastic model along with a temporal regularization in the reconstruction process of the PET dynamic series led to substantial quantitative improvements and motion artifact reduction. Future work will include the integration of a linear FDG kinetic model, in order to directly reconstruct parametric images.

Dynamic PET image reconstruction integrating temporal regularization associated with respiratory motion correction for applications in oncology.

PubMed

Merlin, Thibaut; Visvikis, Dimitris; Fernandez, Philippe; Lamare, Frédéric

2018-02-13

Respiratory motion reduces both the qualitative and quantitative accuracy of PET images in oncology. This impact is more significant for quantitative applications based on kinetic modeling, where dynamic acquisitions are associated with limited statistics due to the necessity of enhanced temporal resolution. The aim of this study is to address these drawbacks, by combining a respiratory motion correction approach with temporal regularization in a unique reconstruction algorithm for dynamic PET imaging. Elastic transformation parameters for the motion correction are estimated from the non-attenuation-corrected PET images. The derived displacement matrices are subsequently used in a list-mode based OSEM reconstruction algorithm integrating a temporal regularization between the 3D dynamic PET frames, based on temporal basis functions. These functions are simultaneously estimated at each iteration, along with their relative coefficients for each image voxel. Quantitative evaluation has been performed using dynamic FDG PET/CT acquisitions of lung cancer patients acquired on a GE DRX system. The performance of the proposed method is compared with that of a standard multi-frame OSEM reconstruction algorithm. The proposed method achieved substantial improvements in terms of noise reduction while accounting for loss of contrast due to respiratory motion. Results on simulated data showed that the proposed 4D algorithms led to bias reduction values up to 40% in both tumor and blood regions for similar standard deviation levels, in comparison with a standard 3D reconstruction. Patlak parameter estimations on reconstructed images with the proposed reconstruction methods resulted in 30% and 40% bias reduction in the tumor and lung region respectively for the Patlak slope, and a 30% bias reduction for the intercept in the tumor region (a similar Patlak intercept was achieved in the lung area). Incorporation of the respiratory motion correction using an elastic model along with a temporal regularization in the reconstruction process of the PET dynamic series led to substantial quantitative improvements and motion artifact reduction. Future work will include the integration of a linear FDG kinetic model, in order to directly reconstruct parametric images.

Emergence of dynamic cooperativity in the stochastic kinetics of fluctuating enzymes

NASA Astrophysics Data System (ADS)

Kumar, Ashutosh; Chatterjee, Sambarta; Nandi, Mintu; Dua, Arti

2016-08-01

Dynamic co-operativity in monomeric enzymes is characterized in terms of a non-Michaelis-Menten kinetic behaviour. The latter is believed to be associated with mechanisms that include multiple reaction pathways due to enzymatic conformational fluctuations. Recent advances in single-molecule fluorescence spectroscopy have provided new fundamental insights on the possible mechanisms underlying reactions catalyzed by fluctuating enzymes. Here, we present a bottom-up approach to understand enzyme turnover kinetics at physiologically relevant mesoscopic concentrations informed by mechanisms extracted from single-molecule stochastic trajectories. The stochastic approach, presented here, shows the emergence of dynamic co-operativity in terms of a slowing down of the Michaelis-Menten (MM) kinetics resulting in negative co-operativity. For fewer enzymes, dynamic co-operativity emerges due to the combined effects of enzymatic conformational fluctuations and molecular discreteness. The increase in the number of enzymes, however, suppresses the effect of enzymatic conformational fluctuations such that dynamic co-operativity emerges solely due to the discrete changes in the number of reacting species. These results confirm that the turnover kinetics of fluctuating enzyme based on the parallel-pathway MM mechanism switches over to the single-pathway MM mechanism with the increase in the number of enzymes. For large enzyme numbers, convergence to the exact MM equation occurs in the limit of very high substrate concentration as the stochastic kinetics approaches the deterministic behaviour.

Emergence of dynamic cooperativity in the stochastic kinetics of fluctuating enzymes.

PubMed

Kumar, Ashutosh; Chatterjee, Sambarta; Nandi, Mintu; Dua, Arti

2016-08-28

Dynamic co-operativity in monomeric enzymes is characterized in terms of a non-Michaelis-Menten kinetic behaviour. The latter is believed to be associated with mechanisms that include multiple reaction pathways due to enzymatic conformational fluctuations. Recent advances in single-molecule fluorescence spectroscopy have provided new fundamental insights on the possible mechanisms underlying reactions catalyzed by fluctuating enzymes. Here, we present a bottom-up approach to understand enzyme turnover kinetics at physiologically relevant mesoscopic concentrations informed by mechanisms extracted from single-molecule stochastic trajectories. The stochastic approach, presented here, shows the emergence of dynamic co-operativity in terms of a slowing down of the Michaelis-Menten (MM) kinetics resulting in negative co-operativity. For fewer enzymes, dynamic co-operativity emerges due to the combined effects of enzymatic conformational fluctuations and molecular discreteness. The increase in the number of enzymes, however, suppresses the effect of enzymatic conformational fluctuations such that dynamic co-operativity emerges solely due to the discrete changes in the number of reacting species. These results confirm that the turnover kinetics of fluctuating enzyme based on the parallel-pathway MM mechanism switches over to the single-pathway MM mechanism with the increase in the number of enzymes. For large enzyme numbers, convergence to the exact MM equation occurs in the limit of very high substrate concentration as the stochastic kinetics approaches the deterministic behaviour.

Cure Kinetics of Benzoxazine/Cycloaliphatic Epoxy Resin by Differential Scanning Calorimetry

NASA Astrophysics Data System (ADS)

Gouni, Sreeja Reddy

Understanding the curing kinetics of a thermoset resin has a significant importance in developing and optimizing curing cycles in various industrial manufacturing processes. This can assist in improving the quality of final product and minimizing the manufacturing-associated costs. One approach towards developing such an understanding is to formulate kinetic models that can be used to optimize curing time and temperature to reach a full cure state or to determine time to apply pressure in an autoclave process. Various phenomenological reaction models have been used in the literature to successfully predict the kinetic behavior of a thermoset system. The current research work was designed to investigate the cure kinetics of Bisphenol-A based Benzoxazine (BZ-a) and Cycloaliphatic epoxy resin (CER) system under isothermal and nonisothermal conditions by Differential Scanning Calorimetry (DSC). The cure characteristics of BZ-a/CER copolymer systems with 75/25 wt% and 50/50 wt% have been studied and compared to that of pure benzoxazine under nonisothermal conditions. The DSC thermograms exhibited by these BZ-a/CER copolymer systems showed a single exothermic peak, indicating that the reactions between benzoxazine-benzoxazine monomers and benzoxazine-cycloaliphatic epoxy resin were interactive and occurred simultaneously. The Kissinger method and isoconversional methods including Ozawa-Flynn-Wall and Freidman were employed to obtain the activation energy values and determine the nature of the reaction. The cure behavior and the kinetic parameters were determined by adopting a single step autocatalytic model based on Kamal and Sourour phenomenological reaction model. The model was found to suitably describe the cure kinetics of copolymer system prior to the diffusion-control reaction. Analyzing and understanding the thermoset resin system under isothermal conditions is also important since it is the most common practice in the industry. The BZ-a/CER copolymer system with 75/25 wt% ratio which exhibited high glass transition temperature compared to polybenzoxazine was investigated under isothermal conditions. The copolymer system exhibited the maximum reaction rate at an intermediate degree of cure (20 to 40%), indicating that the reaction was autocatalytic. Similar to the nonisothermal cure kinetics, Kamal and Sourour phenomenological reaction model was adopted to determine the kinetic behavior of the system. The theoretical values based on the developed model showed a deviation from the obtained experimental values, which indicated the change in kinetics from a reaction-controlled mechanism to a diffusion-controlled mechanism with increasing reaction conversion. To substantiate the hypothesis, Fournier et al's diffusion factor was introduced into the model, resulting in an agreement between the theoretical and experimental values. The changes in cross-linking density and the glass transition temperature (Tg) with increasing epoxy concentration were investigated under Dynamic Mechanical Analyzer (DMA). The BZ-a/CER copolymer system with the epoxy content of less than 40 wt% exhibited the greatest Tg and cross-linking density compared to benzoxazine homopolymer and other ratios.

Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics.

PubMed

Yang, Qian; Sing-Long, Carlos A; Reed, Evan J

2017-08-01

We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. In contrast, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our method on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. The framework described in this work paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates.

Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics

PubMed Central

Sing-Long, Carlos A.

2017-01-01

We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. In contrast, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our method on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. The framework described in this work paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates. PMID:28989618

Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics

DOE PAGES

Yang, Qian; Sing-Long, Carlos A.; Reed, Evan J.

2017-06-19

Here, we propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. Conversely, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our methodmore » on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. Furthermore, we describe a framework in this work that paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates.« less

Quasispecies in population of compositional assemblies.

PubMed

Gross, Renan; Fouxon, Itzhak; Lancet, Doron; Markovitch, Omer

2014-12-30

The quasispecies model refers to information carriers that undergo self-replication with errors. A quasispecies is a steady-state population of biopolymer sequence variants generated by mutations from a master sequence. A quasispecies error threshold is a minimal replication accuracy below which the population structure breaks down. Theory and experimentation of this model often refer to biopolymers, e.g. RNA molecules or viral genomes, while its prebiotic context is often associated with an RNA world scenario. Here, we study the possibility that compositional entities which code for compositional information, intrinsically different from biopolymers coding for sequential information, could show quasispecies dynamics. We employed a chemistry-based model, graded autocatalysis replication domain (GARD), which simulates the network dynamics within compositional molecular assemblies. In GARD, a compotype represents a population of similar assemblies that constitute a quasi-stationary state in compositional space. A compotype's center-of-mass is found to be analogous to a master sequence for a sequential quasispecies. Using single-cycle GARD dynamics, we measured the quasispecies transition matrix (Q) for the probabilities of transition from one center-of-mass Euclidean distance to another. Similarly, the quasispecies' growth rate vector (A) was obtained. This allowed computing a steady state distribution of distances to the center of mass, as derived from the quasispecies equation. In parallel, a steady state distribution was obtained via the GARD equation kinetics. Rewardingly, a significant correlation was observed between the distributions obtained by these two methods. This was only seen for distances to the compotype center-of-mass, and not to randomly selected compositions. A similar correspondence was found when comparing the quasispecies time dependent dynamics towards steady state. Further, changing the error rate by modifying basal assembly joining rate of GARD kinetics was found to display an error catastrophe, similar to the standard quasispecies model. Additional augmentation of compositional mutations leads to the complete disappearance of the master-like composition. Our results show that compositional assemblies, as simulated by the GARD formalism, portray significant attributes of quasispecies dynamics. This expands the applicability of the quasispecies model beyond sequence-based entities, and potentially enhances validity of GARD as a model for prebiotic evolution.

Advances in Stereoconvergent Catalysis from 2005–2015: Transition-Metal-Mediated Stereoablative Reactions, Dynamic Kinetic Resolutions, and Dynamic Kinetic Asymmetric Transformations

PubMed Central

Bhat, Vikram; Welin, Eric R.; Guo, Xuelei; Stoltz, Brian M.

2017-01-01

An important subset of asymmetric synthesis is dynamic kinetic resolution, dynamic kinetic asymmetric processes and stereoablative transformations. Initially, only enzymes were known to catalyze dynamic kinetic processes but recently various synthetic catalysts have been developed. This review summarizes major advances in non-enzymatic, transition metal promoted dynamic asymmetric transformations reported between 2005 and 2015. PMID:28164696

Simulation and analysis of a model dinoflagellate predator-prey system

NASA Astrophysics Data System (ADS)

Mazzoleni, M. J.; Antonelli, T.; Coyne, K. J.; Rossi, L. F.

2015-12-01

This paper analyzes the dynamics of a model dinoflagellate predator-prey system and uses simulations to validate theoretical and experimental studies. A simple model for predator-prey interactions is derived by drawing upon analogies from chemical kinetics. This model is then modified to account for inefficiencies in predation. Simulation results are shown to closely match the model predictions. Additional simulations are then run which are based on experimental observations of predatory dinoflagellate behavior, and this study specifically investigates how the predatory dinoflagellate Karlodinium veneficum uses toxins to immobilize its prey and increase its feeding rate. These simulations account for complex dynamics that were not included in the basic models, and the results from these computational simulations closely match the experimentally observed predatory behavior of K. veneficum and reinforce the notion that predatory dinoflagellates utilize toxins to increase their feeding rate.

Kinetics of molecular transitions with dynamic disorder in single-molecule pulling experiments

NASA Astrophysics Data System (ADS)

Zheng, Yue; Li, Ping; Zhao, Nanrong; Hou, Zhonghuai

2013-05-01

Macromolecular transitions are subject to large fluctuations of rate constant, termed as dynamic disorder. The individual or intrinsic transition rates and activation free energies can be extracted from single-molecule pulling experiments. Here we present a theoretical framework based on a generalized Langevin equation with fractional Gaussian noise and power-law memory kernel to study the kinetics of macromolecular transitions to address the effects of dynamic disorder on barrier-crossing kinetics under external pulling force. By using the Kramers' rate theory, we have calculated the fluctuating rate constant of molecular transition, as well as the experimentally accessible quantities such as the force-dependent mean lifetime, the rupture force distribution, and the speed-dependent mean rupture force. Particular attention is paid to the discrepancies between the kinetics with and without dynamic disorder. We demonstrate that these discrepancies show strong and nontrivial dependence on the external force or the pulling speed, as well as the barrier height of the potential of mean force. Our results suggest that dynamic disorder is an important factor that should be taken into account properly in accurate interpretations of single-molecule pulling experiments.

Driven fragmentation of granular gases.

PubMed

Cruz Hidalgo, Raúl; Pagonabarraga, Ignacio

2008-06-01

The dynamics of homogeneously heated granular gases which fragment due to particle collisions is analyzed. We introduce a kinetic model which accounts for correlations induced at the grain collisions and analyze both the kinetics and relevant distribution functions these systems develop. The work combines analytical and numerical studies based on direct simulation Monte Carlo calculations. A broad family of fragmentation probabilities is considered, and its implications for the system kinetics are discussed. We show that generically these driven materials evolve asymptotically into a dynamical scaling regime. If the fragmentation probability tends to a constant, the grain number diverges at a finite time, leading to a shattering singularity. If the fragmentation probability vanishes, then the number of grains grows monotonously as a power law. We consider different homogeneous thermostats and show that the kinetics of these systems depends weakly on both the grain inelasticity and driving. We observe that fragmentation plays a relevant role in the shape of the velocity distribution of the particles. When the fragmentation is driven by local stochastic events, the long velocity tail is essentially exponential independently of the heating frequency and the breaking rule. However, for a Lowe-Andersen thermostat, numerical evidence strongly supports the conjecture that the scaled velocity distribution follows a generalized exponential behavior f(c) approximately exp(-cn) , with n approximately 1.2 , regarding less the fragmentation mechanisms.

Contagion Shocks in One Dimension

NASA Astrophysics Data System (ADS)

Bertozzi, Andrea L.; Rosado, Jesus; Short, Martin B.; Wang, Li

2015-02-01

We consider an agent-based model of emotional contagion coupled with motion in one dimension that has recently been studied in the computer science community. The model involves movement with a speed proportional to a "fear" variable that undergoes a temporal consensus averaging based on distance to other agents. We study the effect of Riemann initial data for this problem, leading to shock dynamics that are studied both within the agent-based model as well as in a continuum limit. We examine the behavior of the model under distinguished limits as the characteristic contagion interaction distance and the interaction timescale both approach zero. The limiting behavior is related to a classical model for pressureless gas dynamics with "sticky" particles. In comparison, we observe a threshold for the interaction distance vs. interaction timescale that produce qualitatively different behavior for the system - in one case particle paths do not cross and there is a natural Eulerian limit involving nonlocal interactions and in the other case particle paths can cross and one may consider only a kinetic model in the continuum limit.

Nonlinear Fluid Model Of 3-D Field Effects In Tokamak Plasmas

NASA Astrophysics Data System (ADS)

Callen, J. D.; Hegna, C. C.; Beidler, M. T.

2017-10-01

Extended MHD codes (e.g., NIMROD, M3D-C1) are beginning to explore nonlinear effects of small 3-D magnetic fields on tokamak plasmas. To facilitate development of analogous physically understandable reduced models, a fluid-based dynamic nonlinear model of these added 3-D field effects in the base axisymmetric tokamak magnetic field geometry is being developed. The model incorporates kinetic-based closures within an extended MHD framework. Key 3-D field effects models that have been developed include: 1) a comprehensive modified Rutherford equation for the growth of a magnetic island that includes the classical tearing and NTM perturbed bootstrap current drives, externally applied magnetic field and current drives, and classical and neoclassical polarization current effects, and 2) dynamic nonlinear evolution of the plasma toroidal flow (radial electric field) in response to the 3-D fields. An application of this model to RMP ELM suppression precipitated by an ELM crash will be discussed. Supported by Office of Fusion Energy Sciences, Office of Science, Dept. of Energy Grants DE-FG02-86ER53218 and DE-FG02-92ER54139.

Ejecta cloud from the AIDA space project kinetic impact on the secondary of a binary asteroid: I. mechanical environment and dynamical model

NASA Astrophysics Data System (ADS)

Yu, Yang; Michel, Patrick; Schwartz, Stephen R.; Naidu, Shantanu P.; Benner, Lance A. M.

2017-01-01

An understanding of the post-impact dynamics of ejecta clouds are crucial to the planning of a kinetic impact mission to an asteroid, and also has great implications for the history of planetary formation. The purpose of this article is to track the evolution of ejecta produced by AIDA mission, which targets for kinetic impact the secondary of near-Earth binary asteroid (65803) Didymos on 2022, and to feedback essential informations to AIDA's ongoing phase-A study. We present a detailed dynamic model for the simulation of an ejecta cloud from a binary asteroid that synthesizes all relevant forces based on a previous analysis of the mechanical environment. We apply our method to gain insight into the expected response of Didymos to the AIDA impact, including the subsequent evolution of debris and dust. The crater scaling relations from laboratory experiments are employed to approximate the distributions of ejecta mass and launching speed. The size distribution of fragments is modeled with a power law fitted from observations of real asteroid surface. A full-scale demonstration is simulated using parameters specified by the mission. We report the results of the simulation, which include the computed spread of the ejecta cloud and the recorded history of ejecta accretion and escape. The violent period of the ejecta evolution is found to be short, and is followed by a stage where the remaining ejecta is gradually cleared. Solar radiation pressure proves to be efficient in cleaning dust-size ejecta, and the simulation results after two weeks shows that large debris on polar orbits (perpendicular to the binary orbital plane) has a survival advantage over smaller ejecta and ejecta that keeps to low latitudes.

Analyses of kinetic glass transition in short-range attractive colloids based on time-convolutionless mode-coupling theory.

PubMed

Narumi, Takayuki; Tokuyama, Michio

2017-03-01

For short-range attractive colloids, the phase diagram of the kinetic glass transition is studied by time-convolutionless mode-coupling theory (TMCT). Using numerical calculations, TMCT is shown to recover all the remarkable features predicted by the mode-coupling theory for attractive colloids: the glass-liquid-glass reentrant, the glass-glass transition, and the higher-order singularities. It is also demonstrated through the comparisons with the results of molecular dynamics for the binary attractive colloids that TMCT improves the critical values of the volume fraction. In addition, a schematic model of three control parameters is investigated analytically. It is thus confirmed that TMCT can describe the glass-glass transition and higher-order singularities even in such a schematic model.

Unfolding and melting of DNA (RNA) hairpins: the concept of structure-specific 2D dynamic landscapes.

PubMed

Lin, Milo M; Meinhold, Lars; Shorokhov, Dmitry; Zewail, Ahmed H

2008-08-07

A 2D free-energy landscape model is presented to describe the (un)folding transition of DNA/RNA hairpins, together with molecular dynamics simulations and experimental findings. The dependence of the (un)folding transition on the stem sequence and the loop length is shown in the enthalpic and entropic contributions to the free energy. Intermediate structures are well defined by the two coordinates of the landscape during (un)zipping. Both the free-energy landscape model and the extensive molecular dynamics simulations totaling over 10 mus predict the existence of temperature-dependent kinetic intermediate states during hairpin (un)zipping and provide the theoretical description of recent ultrafast temperature-jump studies which indicate that hairpin (un)zipping is, in general, not a two-state process. The model allows for lucid prediction of the collapsed state(s) in simple 2D space and we term it the kinetic intermediate structure (KIS) model.

Molecular Dynamics Simulations and Kinetic Measurements to Estimate and Predict Protein-Ligand Residence Times.

PubMed

Mollica, Luca; Theret, Isabelle; Antoine, Mathias; Perron-Sierra, Françoise; Charton, Yves; Fourquez, Jean-Marie; Wierzbicki, Michel; Boutin, Jean A; Ferry, Gilles; Decherchi, Sergio; Bottegoni, Giovanni; Ducrot, Pierre; Cavalli, Andrea

2016-08-11

Ligand-target residence time is emerging as a key drug discovery parameter because it can reliably predict drug efficacy in vivo. Experimental approaches to binding and unbinding kinetics are nowadays available, but we still lack reliable computational tools for predicting kinetics and residence time. Most attempts have been based on brute-force molecular dynamics (MD) simulations, which are CPU-demanding and not yet particularly accurate. We recently reported a new scaled-MD-based protocol, which showed potential for residence time prediction in drug discovery. Here, we further challenged our procedure's predictive ability by applying our methodology to a series of glucokinase activators that could be useful for treating type 2 diabetes mellitus. We combined scaled MD with experimental kinetics measurements and X-ray crystallography, promptly checking the protocol's reliability by directly comparing computational predictions and experimental measures. The good agreement highlights the potential of our scaled-MD-based approach as an innovative method for computationally estimating and predicting drug residence times.

Kinetic studies of divertor heat fluxes in Alcator C-Mod

NASA Astrophysics Data System (ADS)

Pankin, A. Y.; Bateman, G.; Kritz, A. H.; Rafiq, T.; Park, G. Y.; Chang, C. S.; Brunner, D.; Hughes, J. W.; Labombard, B.; Terry, J.

2010-11-01

The kinetic XGC0 code [C.S. Chang et al, Phys. Plasmas 11 (2004) 2649] is used to model the H- mode pedestal and SOL regions in Alcator C-Mod discharges. The self-consistent simulations in this study include kinetic neoclassical physics and anomalous transport models along with the ExB flow shear effects. The heat fluxes on the divertor plates are computed and the fluxes to the outer plate are compared with experimental observations. The dynamics of the radial electric field near the separatrix and in the SOL region are computed with the XGC0 code, and the effect of the anomalous transport on the heat fluxes in the SOL region is investigated. In particular, the particle and thermal diffusivities obtained in the analysis mode are compared with predictions from the theory-based anomalous transport models such as MMM95 [G. Bateman et al, Phys. Plasmas 5 (1998) 1793] and DRIBM [T. Rafiq et al, to appear in Phys. Plasmas (2010)]. It is found that there is a notable pinch effect in the inner separatrix region. Possible physical mechanisms for the particle and thermal pinches are discussed.

Refined BCF-type boundary conditions for mesoscale surface step dynamics

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

Zhao, Renjie; Ackerman, David M.; Evans, James W.

Deposition on a vicinal surface with alternating rough and smooth steps is described by a solid-on-solid model with anisotropic interactions. Kinetic Monte Carlo (KMC) simulations of the model reveal step pairing in the absence of any additional step attachment barriers. We explore the description of this behavior within an analytic Burton-Cabrera-Frank (BCF)-type step dynamics treatment. Without attachment barriers, conventional kinetic coefficients for the rough and smooth steps are identical, as are the predicted step velocities for a vicinal surface with equal terrace widths. However, we determine refined kinetic coefficients from a two-dimensional discrete deposition-diffusion equation formalism which accounts for stepmore » structure. These coefficients are generally higher for rough steps than for smooth steps, reflecting a higher propensity for capture of diffusing terrace adatoms due to a higher kink density. Such refined coefficients also depend on the local environment of the step and can even become negative (corresponding to net detachment despite an excess adatom density) for a smooth step in close proximity to a rough step. Incorporation of these refined kinetic coefficients into a BCF-type step dynamics treatment recovers quantitatively the mesoscale step-pairing behavior observed in the KMC simulations.« less

Refined BCF-type boundary conditions for mesoscale surface step dynamics

DOE PAGES

Zhao, Renjie; Ackerman, David M.; Evans, James W.

2015-06-24

Deposition on a vicinal surface with alternating rough and smooth steps is described by a solid-on-solid model with anisotropic interactions. Kinetic Monte Carlo (KMC) simulations of the model reveal step pairing in the absence of any additional step attachment barriers. We explore the description of this behavior within an analytic Burton-Cabrera-Frank (BCF)-type step dynamics treatment. Without attachment barriers, conventional kinetic coefficients for the rough and smooth steps are identical, as are the predicted step velocities for a vicinal surface with equal terrace widths. However, we determine refined kinetic coefficients from a two-dimensional discrete deposition-diffusion equation formalism which accounts for stepmore » structure. These coefficients are generally higher for rough steps than for smooth steps, reflecting a higher propensity for capture of diffusing terrace adatoms due to a higher kink density. Such refined coefficients also depend on the local environment of the step and can even become negative (corresponding to net detachment despite an excess adatom density) for a smooth step in close proximity to a rough step. Incorporation of these refined kinetic coefficients into a BCF-type step dynamics treatment recovers quantitatively the mesoscale step-pairing behavior observed in the KMC simulations.« less

A computational kinetic model of diffusion for molecular systems.

PubMed

Teo, Ivan; Schulten, Klaus

2013-09-28

Regulation of biomolecular transport in cells involves intra-protein steps like gating and passage through channels, but these steps are preceded by extra-protein steps, namely, diffusive approach and admittance of solutes. The extra-protein steps develop over a 10-100 nm length scale typically in a highly particular environment, characterized through the protein's geometry, surrounding electrostatic field, and location. In order to account for solute energetics and mobility of solutes in this environment at a relevant resolution, we propose a particle-based kinetic model of diffusion based on a Markov State Model framework. Prerequisite input data consist of diffusion coefficient and potential of mean force maps generated from extensive molecular dynamics simulations of proteins and their environment that sample multi-nanosecond durations. The suggested diffusion model can describe transport processes beyond microsecond duration, relevant for biological function and beyond the realm of molecular dynamics simulation. For this purpose the systems are represented by a discrete set of states specified by the positions, volumes, and surface elements of Voronoi grid cells distributed according to a density function resolving the often intricate relevant diffusion space. Validation tests carried out for generic diffusion spaces show that the model and the associated Brownian motion algorithm are viable over a large range of parameter values such as time step, diffusion coefficient, and grid density. A concrete application of the method is demonstrated for ion diffusion around and through the Eschericia coli mechanosensitive channel of small conductance ecMscS.

ESTIMATION OF CONSTANT AND TIME-VARYING DYNAMIC PARAMETERS OF HIV INFECTION IN A NONLINEAR DIFFERENTIAL EQUATION MODEL.

PubMed

Liang, Hua; Miao, Hongyu; Wu, Hulin

2010-03-01

Modeling viral dynamics in HIV/AIDS studies has resulted in deep understanding of pathogenesis of HIV infection from which novel antiviral treatment guidance and strategies have been derived. Viral dynamics models based on nonlinear differential equations have been proposed and well developed over the past few decades. However, it is quite challenging to use experimental or clinical data to estimate the unknown parameters (both constant and time-varying parameters) in complex nonlinear differential equation models. Therefore, investigators usually fix some parameter values, from the literature or by experience, to obtain only parameter estimates of interest from clinical or experimental data. However, when such prior information is not available, it is desirable to determine all the parameter estimates from data. In this paper, we intend to combine the newly developed approaches, a multi-stage smoothing-based (MSSB) method and the spline-enhanced nonlinear least squares (SNLS) approach, to estimate all HIV viral dynamic parameters in a nonlinear differential equation model. In particular, to the best of our knowledge, this is the first attempt to propose a comparatively thorough procedure, accounting for both efficiency and accuracy, to rigorously estimate all key kinetic parameters in a nonlinear differential equation model of HIV dynamics from clinical data. These parameters include the proliferation rate and death rate of uninfected HIV-targeted cells, the average number of virions produced by an infected cell, and the infection rate which is related to the antiviral treatment effect and is time-varying. To validate the estimation methods, we verified the identifiability of the HIV viral dynamic model and performed simulation studies. We applied the proposed techniques to estimate the key HIV viral dynamic parameters for two individual AIDS patients treated with antiretroviral therapies. We demonstrate that HIV viral dynamics can be well characterized and quantified for individual patients. As a result, personalized treatment decision based on viral dynamic models is possible.

Ab initio molecular dynamics with enhanced sampling for surface reaction kinetics at finite temperatures: CH2 ⇌ CH + H on Ni(111) as a case study

NASA Astrophysics Data System (ADS)

Sun, Geng; Jiang, Hong

2015-12-01

A comprehensive understanding of surface thermodynamics and kinetics based on first-principles approaches is crucial for rational design of novel heterogeneous catalysts, and requires combining accurate electronic structure theory and statistical mechanics modeling. In this work, ab initio molecular dynamics (AIMD) combined with the integrated tempering sampling (ITS) method has been explored to study thermodynamic and kinetic properties of elementary processes on surfaces, using a simple reaction CH 2 ⇌ CH + H on the Ni(111) surface as an example. By a careful comparison between the results from ITS-AIMD simulation and those evaluated in terms of the harmonic oscillator (HO) approximation, it is found that the reaction free energy and entropy from the HO approximation are qualitatively consistent with the results from ITS-AIMD simulation, but there are also quantitatively significant discrepancies. In particular, the HO model misses the entropy effects related to the existence of multiple adsorption configurations arising from the frustrated translation and rotation motion of adsorbed species, which are different in the reactant and product states. The rate constants are evaluated from two ITS-enhanced approaches, one using the transition state theory (TST) formulated in terms of the potential of mean force (PMF) and the other one combining ITS with the transition path sampling (TPS) technique, and are further compared to those based on harmonic TST. It is found that the rate constants from the PMF-based TST are significantly smaller than those from the harmonic TST, and that the results from PMF-TST and ITS-TPS are in a surprisingly good agreement. These findings indicate that the basic assumptions of transition state theory are valid in such elementary surface reactions, but the consideration of statistical averaging of all important adsorption configurations and reaction pathways, which are missing in the harmonic TST, are critical for accurate description of thermodynamic and kinetic properties of surface processes. This work clearly demonstrates the importance of considering temperature effects beyond the HO model, for which the AIMD simulation in combination with enhanced sampling techniques like ITS provides a feasible and general approach.

Physiologically-Based Pharmacokinetic/Toxicokinetic Modeling in Risk Assessment

DTIC Science & Technology

2005-03-01

between what is considered as "kinetic" and what is "dynamic". Many models seamlessly cover both areas in order to describe the biology as a whole. In...means of Monte-Carlo analysis (Clewell and Andersen, 1989). What cannot be so easily estimated is the possible error or uncertainty introduced by the...formulated, furnished, or in any way supplied the said drawings, specifications, or other data is not to be regarded by implication or otherwise, as in any

Modeling time-coincident ultrafast electron transfer and solvation processes at molecule-semiconductor interfaces

NASA Astrophysics Data System (ADS)

Li, Lesheng; Giokas, Paul G.; Kanai, Yosuke; Moran, Andrew M.

2014-06-01

Kinetic models based on Fermi's Golden Rule are commonly employed to understand photoinduced electron transfer dynamics at molecule-semiconductor interfaces. Implicit in such second-order perturbative descriptions is the assumption that nuclear relaxation of the photoexcited electron donor is fast compared to electron injection into the semiconductor. This approximation breaks down in systems where electron transfer transitions occur on 100-fs time scale. Here, we present a fourth-order perturbative model that captures the interplay between time-coincident electron transfer and nuclear relaxation processes initiated by light absorption. The model consists of a fairly small number of parameters, which can be derived from standard spectroscopic measurements (e.g., linear absorbance, fluorescence) and/or first-principles electronic structure calculations. Insights provided by the model are illustrated for a two-level donor molecule coupled to both (i) a single acceptor level and (ii) a density of states (DOS) calculated for TiO2 using a first-principles electronic structure theory. These numerical calculations show that second-order kinetic theories fail to capture basic physical effects when the DOS exhibits narrow maxima near the energy of the molecular excited state. Overall, we conclude that the present fourth-order rate formula constitutes a rigorous and intuitive framework for understanding photoinduced electron transfer dynamics that occur on the 100-fs time scale.

Simulations of anti-parallel reconnection using a nonlocal heat flux closure

DOE PAGES

Ng, Jonathan; Hakim, Ammar; Bhattacharjee, A.; ...

2017-08-08

The integration of kinetic effects in fluid models is important for global simulations of the Earth's magnetosphere. In particular, it has been shown that ion kinetics play a crucial role in the dynamics of large reconnecting systems, and that higher-order fluid moment models can account for some of these effects. Here, we use a ten-moment model for electrons and ions, which includes the off diagonal elements of the pressure tensor that are important for magnetic reconnection. Kinetic effects are recovered by using a nonlocal heat flux closure, which approximates linear Landau damping in the fluid framework. Moreover, the closure ismore » tested using the island coalescence problem, which is sensitive to ion dynamics. We also demonstrate that the nonlocal closure is able to self-consistently reproduce the structure of the ion diffusion region, pressure tensor, and ion velocity without the need for fine-tuning of relaxation coefficients present in earlier models.« less

Communication: Energy transfer and reaction dynamics for DCl scattering on Au(111): An ab initio molecular dynamics study.

PubMed

Kolb, Brian; Guo, Hua

2016-07-07

Scattering and dissociative chemisorption of DCl on Au(111) are investigated using ab initio molecular dynamics with a slab model, in which the top two layers of Au are mobile. Substantial kinetic energy loss in the scattered DCl is found, but the amount of energy transfer is notably smaller than that observed in the experiment. On the other hand, the dissociative chemisorption probability reproduces the experimental trend with respect to the initial kinetic energy, but is about one order of magnitude larger than the reported initial sticking probability. While the theory-experiment agreement is significantly improved from the previous rigid surface model, the remaining discrepancies are still substantial, calling for further scrutiny in both theory and experiment.

Dynamic PET and Optical Imaging and Compartment Modeling using a Dual-labeled Cyclic RGD Peptide Probe

PubMed Central

Zhu, Lei; Guo, Ning; Li, Quanzheng; Ma, Ying; Jacboson, Orit; Lee, Seulki; Choi, Hak Soo; Mansfield, James R.; Niu, Gang; Chen, Xiaoyuan

2012-01-01

Purpose: The aim of this study is to determine if dynamic optical imaging could provide comparable kinetic parameters to that of dynamic PET imaging by a near-infrared dye/64Cu dual-labeled cyclic RGD peptide. Methods: The integrin αvβ3 binding RGD peptide was conjugated with a macrocyclic chelator 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) for copper labeling and PET imaging and a near-infrared dye ZW-1 for optical imaging. The in vitro biological activity of RGD-C(DOTA)-ZW-1 was characterized by cell staining and receptor binding assay. Sixty-min dynamic PET and optical imaging were acquired on a MDA-MB-435 tumor model. Singular value decomposition (SVD) method was applied to compute the dynamic optical signal from the two-dimensional optical projection images. Compartment models were used to quantitatively analyze and compare the dynamic optical and PET data. Results: The dual-labeled probe 64Cu-RGD-C(DOTA)-ZW-1 showed integrin specific binding in vitro and in vivo. The binding potential (Bp) derived from dynamic optical imaging (1.762 ± 0.020) is comparable to that from dynamic PET (1.752 ± 0.026). Conclusion: The signal un-mixing process using SVD improved the accuracy of kinetic modeling of 2D dynamic optical data. Our results demonstrate that 2D dynamic optical imaging with SVD analysis could achieve comparable quantitative results as dynamic PET imaging in preclinical xenograft models. PMID:22916074

Dynamic PET and Optical Imaging and Compartment Modeling using a Dual-labeled Cyclic RGD Peptide Probe.

PubMed

Zhu, Lei; Guo, Ning; Li, Quanzheng; Ma, Ying; Jacboson, Orit; Lee, Seulki; Choi, Hak Soo; Mansfield, James R; Niu, Gang; Chen, Xiaoyuan

2012-01-01

The aim of this study is to determine if dynamic optical imaging could provide comparable kinetic parameters to that of dynamic PET imaging by a near-infrared dye/(64)Cu dual-labeled cyclic RGD peptide. The integrin α(v)β(3) binding RGD peptide was conjugated with a macrocyclic chelator 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) for copper labeling and PET imaging and a near-infrared dye ZW-1 for optical imaging. The in vitro biological activity of RGD-C(DOTA)-ZW-1 was characterized by cell staining and receptor binding assay. Sixty-min dynamic PET and optical imaging were acquired on a MDA-MB-435 tumor model. Singular value decomposition (SVD) method was applied to compute the dynamic optical signal from the two-dimensional optical projection images. Compartment models were used to quantitatively analyze and compare the dynamic optical and PET data. The dual-labeled probe (64)Cu-RGD-C(DOTA)-ZW-1 showed integrin specific binding in vitro and in vivo. The binding potential (Bp) derived from dynamic optical imaging (1.762 ± 0.020) is comparable to that from dynamic PET (1.752 ± 0.026). The signal un-mixing process using SVD improved the accuracy of kinetic modeling of 2D dynamic optical data. Our results demonstrate that 2D dynamic optical imaging with SVD analysis could achieve comparable quantitative results as dynamic PET imaging in preclinical xenograft models.

Critical evaluation of Jet-A spray combustion using propane chemical kinetics in gas turbine combustion simulated by KIVA-2

NASA Technical Reports Server (NTRS)

Nguyen, H. L.; Ying, S.-J.

1990-01-01

Jet-A spray combustion has been evaluated in gas turbine combustion with the use of propane chemical kinetics as the first approximation for the chemical reactions. Here, the numerical solutions are obtained by using the KIVA-2 computer code. The KIVA-2 code is the most developed of the available multidimensional combustion computer programs for application of the in-cylinder combustion dynamics of internal combustion engines. The released version of KIVA-2 assumes that 12 chemical species are present; the code uses an Arrhenius kinetic-controlled combustion model governed by a four-step global chemical reaction and six equilibrium reactions. Researchers efforts involve the addition of Jet-A thermophysical properties and the implementation of detailed reaction mechanisms for propane oxidation. Three different detailed reaction mechanism models are considered. The first model consists of 131 reactions and 45 species. This is considered as the full mechanism which is developed through the study of chemical kinetics of propane combustion in an enclosed chamber. The full mechanism is evaluated by comparing calculated ignition delay times with available shock tube data. However, these detailed reactions occupy too much computer memory and CPU time for the computation. Therefore, it only serves as a benchmark case by which to evaluate other simplified models. Two possible simplified models were tested in the existing computer code KIVA-2 for the same conditions as used with the full mechanism. One model is obtained through a sensitivity analysis using LSENS, the general kinetics and sensitivity analysis program code of D. A. Bittker and K. Radhakrishnan. This model consists of 45 chemical reactions and 27 species. The other model is based on the work published by C. K. Westbrook and F. L. Dryer.

Stress drop with constant, scale independent seismic efficiency and overshoot

USGS Publications Warehouse

Beeler, N.M.

2001-01-01

To model dissipated and radiated energy during earthquake stress drop, I calculate dynamic fault slip using a single degree of freedom spring-slider block and a laboratory-based static/kinetic fault strength relation with a dynamic stress drop proportional to effective normal stress. The model is scaled to earthquake size assuming a circular rupture; stiffness varies inversely with rupture radius, and rupture duration is proportional to radius. Calculated seismic efficiency, the ratio of radiated to total energy expended during stress drop, is in good agreement with laboratory and field observations. Predicted overshoot, a measure of how much the static stress drop exceeds the dynamic stress drop, is higher than previously published laboratory and seismic observations and fully elasto-dynamic calculations. Seismic efficiency and overshoot are constant, independent of normal stress and scale. Calculated variation of apparent stress with seismic moment resembles the observational constraints of McGarr [1999].

Correlation between Gini index and mobility in a stochastic kinetic model of economic exchange

NASA Astrophysics Data System (ADS)

Bertotti, Maria Letizia; Chattopadhyay, Amit K.; Modanese, Giovanni

Starting from a class of stochastically driven kinetic models of economic exchange, here we present results highlighting the correlation of the Gini inequality index with the social mobility rate, close to dynamical equilibrium. Except for the "canonical-additive case", our numerical results consistently indicate negative values of the correlation coefficient, in agreement with empirical evidence. This confirms that growing inequality is not conducive to social mobility which then requires an "external source" to sustain its dynamics. On the other hand, the sign of the correlation between inequality and total income in the canonical ensemble depends on the way wealth enters or leaves the system. At a technical level, the approach involves a generalization of a stochastic dynamical system formulation, that further paves the way for a probabilistic formulation of perturbed economic exchange models.

Improved accuracy and precision of tracer kinetic parameters by joint fitting to variable flip angle and dynamic contrast enhanced MRI data.

PubMed

Dickie, Ben R; Banerji, Anita; Kershaw, Lucy E; McPartlin, Andrew; Choudhury, Ananya; West, Catharine M; Rose, Chris J

2016-10-01

To improve the accuracy and precision of tracer kinetic model parameter estimates for use in dynamic contrast enhanced (DCE) MRI studies of solid tumors. Quantitative DCE-MRI requires an estimate of precontrast T1 , which is obtained prior to fitting a tracer kinetic model. As T1 mapping and tracer kinetic signal models are both a function of precontrast T1 it was hypothesized that its joint estimation would improve the accuracy and precision of both precontrast T1 and tracer kinetic model parameters. Accuracy and/or precision of two-compartment exchange model (2CXM) parameters were evaluated for standard and joint fitting methods in well-controlled synthetic data and for 36 bladder cancer patients. Methods were compared under a number of experimental conditions. In synthetic data, joint estimation led to statistically significant improvements in the accuracy of estimated parameters in 30 of 42 conditions (improvements between 1.8% and 49%). Reduced accuracy was observed in 7 of the remaining 12 conditions. Significant improvements in precision were observed in 35 of 42 conditions (between 4.7% and 50%). In clinical data, significant improvements in precision were observed in 18 of 21 conditions (between 4.6% and 38%). Accuracy and precision of DCE-MRI parameter estimates are improved when signal models are fit jointly rather than sequentially. Magn Reson Med 76:1270-1281, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

A systematic approach for finding the objective function and active constraints for dynamic flux balance analysis.

PubMed

Nikdel, Ali; Braatz, Richard D; Budman, Hector M

2018-05-01

Dynamic flux balance analysis (DFBA) has become an instrumental modeling tool for describing the dynamic behavior of bioprocesses. DFBA involves the maximization of a biologically meaningful objective subject to kinetic constraints on the rate of consumption/production of metabolites. In this paper, we propose a systematic data-based approach for finding both the biological objective function and a minimum set of active constraints necessary for matching the model predictions to the experimental data. The proposed algorithm accounts for the errors in the experiments and eliminates the need for ad hoc choices of objective function and constraints as done in previous studies. The method is illustrated for two cases: (1) for in silico (simulated) data generated by a mathematical model for Escherichia coli and (2) for actual experimental data collected from the batch fermentation of Bordetella Pertussis (whooping cough).

Temperature dependence of the kinetic energy in the Zr40Be60 amorphous alloy

NASA Astrophysics Data System (ADS)

Syrykh, G. F.; Stolyarov, A. A.; Krzystyniak, M.; Romanelli, G.; Sadykov, R. A.

2017-05-01

The average kinetic energy < E(T)> of the atomic nucleus for each element of the amorphous alloy Zr40Be60 in the temperature range 10-300 K has been measured for the first time using VESUVIO spectrometer (ISIS). The experimental values of < E(T)> have been compared to the partial ZrBe spectra refined by a recursion method based on the data obtained with thermal neutron scattering. The satisfactory agreement has been reached with the calculations using partial spectra based on thermal neutron spectra obtained with recursion method. In addition, the experimental data have been compared to the Debye model. The measurements at different temperatures (10, 200, and 300 K) will provide an opportunity to evaluate the significance of anharmonicity in the dynamics of metallic glasses.

Structure, Kinetics, and Thermodynamics of the Aqueous Uranyl(VI) Cation

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

Kerisit, Sebastien N.; Liu, Chongxuan

2013-08-20

Molecular simulation techniques are employed to gain insights into the structural, kinetic, and thermodynamic properties of the uranyl(VI) cation (UO22+) in aqueous solution. The simulations make use of an atomistic potential model (force field) derived in this work and based on the model of Guilbaud and Wipff (Guilbaud, P.; Wipff, G. J. Mol. Struct. (THEOCHEM) 1996, 366, 55-63). Reactive flux and thermodynamic integration calculations show that the derived potential model yields predictions for the water exchange rate and free energy of hydration, respectively, that are in agreement with experimental data. The water binding energies, hydration shell structure, and self-diffusion coefficientmore » are also calculated and discussed. Finally, a combination of metadynamics and transition path sampling simulations is employed to probe the mechanisms of water exchange reactions in the first hydration shell of the uranyl ion. These atomistic simulations indicate, based on two-dimensional free energy surfaces, that water exchanges follow an associative interchange mechanism. The nature and structure of the water exchange transition states are also determined. The improved potential model is expected to lead to more accurate predictions of uranyl adsorption energies at mineral surfaces using potential-based molecular dynamics simulations.« less

A thermostatted kinetic theory model for event-driven pedestrian dynamics

NASA Astrophysics Data System (ADS)

Bianca, Carlo; Mogno, Caterina

2018-06-01

This paper is devoted to the modeling of the pedestrian dynamics by means of the thermostatted kinetic theory. Specifically the microscopic interactions among pedestrians and an external force field are modeled for simulating the evacuation of pedestrians from a metro station. The fundamentals of the stochastic game theory and the thermostatted kinetic theory are coupled for the derivation of a specific mathematical model which depicts the time evolution of the distribution of pedestrians at different exits of a metro station. The perturbation theory is employed in order to establish the stability analysis of the nonequilibrium stationary states in the case of a metro station consisting of two exits. A general sensitivity analysis on the initial conditions, the magnitude of the external force field and the number of exits is presented by means of numerical simulations which, in particular, show how the asymptotic distribution and the convergence time are affected by the presence of an external force field. The results show how, in evacuation conditions, the interaction dynamics among pedestrians can be negligible with respect to the external force. The important role of the thermostat term in allowing the reaching of the nonequilibrium stationary state is stressed out. Research perspectives are underlined at the end of paper, in particular for what concerns the derivation of frameworks that take into account the definition of local external actions and the introduction of the space and velocity dynamics.

Kinetic Classroom: Acid-Base and Redox Demonstrations with Student Movement.

ERIC Educational Resources Information Center

Lomax, Joseph F.

1994-01-01

Describes classroom activities that involve student movement to demonstrate principles of kinetics. This classroom method can be used for any topic related to dynamic processes. The method used in this activity illustrates Brxnsted-Lowry acid-base theory and redox reactions. Takes advantage of analogies between proton and electron transfers. Use…

Kinetic modeling of sporulation and product formation in stationary phase by Bacillus coagulans RK-02 vis-à-vis other Bacilli.

PubMed

Das, Subhasish; Sen, Ramkrishna

2011-10-01

A logistic kinetic model was derived and validated to characterize the dynamics of a sporogenous bacterium in stationary phase with respect to sporulation and product formation. The kinetic constants as determined using this model are particularly important for describing intrinsic properties of a sporogenous bacterial culture in stationary phase. Non-linear curve fitting of the experimental data into the mathematical model showed very good correlation with the predicted values for sporulation and lipase production by Bacillus coagulans RK-02 culture in minimal media. Model fitting of literature data of sporulation and product (protease and amylase) formation in the stationary phase by some other Bacilli and comparison of the results of model fitting with those of Bacillus coagulans helped validate the significance and robustness of the developed kinetic model. Copyright © 2011 Elsevier Ltd. All rights reserved.

Parameterizing Coefficients of a POD-Based Dynamical System

NASA Technical Reports Server (NTRS)

Kalb, Virginia L.

2010-01-01

A method of parameterizing the coefficients of a dynamical system based of a proper orthogonal decomposition (POD) representing the flow dynamics of a viscous fluid has been introduced. (A brief description of POD is presented in the immediately preceding article.) The present parameterization method is intended to enable construction of the dynamical system to accurately represent the temporal evolution of the flow dynamics over a range of Reynolds numbers. The need for this or a similar method arises as follows: A procedure that includes direct numerical simulation followed by POD, followed by Galerkin projection to a dynamical system has been proven to enable representation of flow dynamics by a low-dimensional model at the Reynolds number of the simulation. However, a more difficult task is to obtain models that are valid over a range of Reynolds numbers. Extrapolation of low-dimensional models by use of straightforward Reynolds-number-based parameter continuation has proven to be inadequate for successful prediction of flows. A key part of the problem of constructing a dynamical system to accurately represent the temporal evolution of the flow dynamics over a range of Reynolds numbers is the problem of understanding and providing for the variation of the coefficients of the dynamical system with the Reynolds number. Prior methods do not enable capture of temporal dynamics over ranges of Reynolds numbers in low-dimensional models, and are not even satisfactory when large numbers of modes are used. The basic idea of the present method is to solve the problem through a suitable parameterization of the coefficients of the dynamical system. The parameterization computations involve utilization of the transfer of kinetic energy between modes as a function of Reynolds number. The thus-parameterized dynamical system accurately predicts the flow dynamics and is applicable to a range of flow problems in the dynamical regime around the Hopf bifurcation. Parameter-continuation software can be used on the parameterized dynamical system to derive a bifurcation diagram that accurately predicts the temporal flow behavior.

Mesoscopic modeling for nucleic acid chain dynamics

PubMed Central

Sales-Pardo, M.; Guimerà, R.; Moreira, A. A.; Widom, J.; Amaral, L. A. N.

2007-01-01

To gain a deeper insight into cellular processes such as transcription and translation, one needs to uncover the mechanisms controlling the configurational changes of nucleic acids. As a step toward this aim, we present here a mesoscopic-level computational model that provides a new window into nucleic acid dynamics. We model a single-stranded nucleic as a polymer chain whose monomers are the nucleosides. Each monomer comprises a bead representing the sugar molecule and a pin representing the base. The bead-pin complex can rotate about the backbone of the chain. We consider pairwise stacking and hydrogen-bonding interactions. We use a modified Monte Carlo dynamics that splits the dynamics into translational bead motion and rotational pin motion. By performing a number of tests, we first show that our model is physically sound. We then focus on a study of the kinetics of a DNA hairpin—a single-stranded molecule comprising two complementary segments joined by a noncomplementary loop—studied experimentally. We find that results from our simulations agree with experimental observations, demonstrating that our model is a suitable tool for the investigation of the hybridization of single strands. PMID:16089566

Assimilation of Biophysical Neuronal Dynamics in Neuromorphic VLSI.

PubMed

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

2017-12-01

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

A quasilinear kinetic model for solar wind electrons and protons instabilities

NASA Astrophysics Data System (ADS)

Sarfraz, M.; Yoon, P. H.

2017-12-01

In situ measurements confirm the anisotropic behavior in temperatures of solar wind species. These anisotropies associated with charge particles are observed to be relaxed. In collionless limit, kinetic instabilities play a significant role to reshape particles distribution. The linear analysis results are encapsulated in inverse relationship between anisotropy and plasma beta based observations fittings techniques, simulations methods, or solution of linearized Vlasov equation. Here amacroscopic quasilinear technique is adopted to confirm inverse relationship through solutions of set of self-consistent kinetic equations. Firstly, for a homogeneous and non-collisional medium, quasilinear kinetic model is employed to display asymptotic variations of core and halo electrons temperatures and saturations of wave energy densities for electromagnetic electron cyclotron (EMEC) instability sourced by, T⊥}>T{∥ . It is shown that, in (β ∥ , T⊥}/T{∥ ) phase space, the saturations stages of anisotropies associated with core and halo electrons lined up on their respective marginal stability curves. Secondly, for case of electrons firehose instability ignited by excessive parallel temperature i.e T⊥}>T{∥ , both electrons and protons are allowed to dynamically evolve in time. It is also observed that, the trajectories of protons and electrons at saturation stages in phase space of anisotropy and plasma beta correspond to proton cyclotron and firehose marginal stability curves, respectively. Next, the outstanding issue that most of observed proton data resides in nearly isotropic state in phase space is interpreted. Here, in quasilinear frame-work of inhomogeneous solar wind system, a set of self-consistent quasilinear equations is formulated to show a dynamical variations of temperatures with spatial distributions. On choice of different initial parameters, it is shown that, interplay of electron and proton instabilities provides an counter-balancing force to slow down the protons away from marginal stability states. As we are dealing both, protons and electrons for radially expanding solar wind plasma, our present approach may eventually be incorporated in global-kinetic models of the solar wind species.

Direct estimation of tracer-kinetic parameter maps from highly undersampled brain dynamic contrast enhanced MRI.

PubMed

Guo, Yi; Lingala, Sajan Goud; Zhu, Yinghua; Lebel, R Marc; Nayak, Krishna S

2017-10-01

The purpose of this work was to develop and evaluate a T 1 -weighted dynamic contrast enhanced (DCE) MRI methodology where tracer-kinetic (TK) parameter maps are directly estimated from undersampled (k,t)-space data. The proposed reconstruction involves solving a nonlinear least squares optimization problem that includes explicit use of a full forward model to convert parameter maps to (k,t)-space, utilizing the Patlak TK model. The proposed scheme is compared against an indirect method that creates intermediate images by parallel imaging and compressed sensing before to TK modeling. Thirteen fully sampled brain tumor DCE-MRI scans with 5-second temporal resolution are retrospectively undersampled at rates R = 20, 40, 60, 80, and 100 for each dynamic frame. TK maps are quantitatively compared based on root mean-squared-error (rMSE) and Bland-Altman analysis. The approach is also applied to four prospectively R = 30 undersampled whole-brain DCE-MRI data sets. In the retrospective study, the proposed method performed statistically better than indirect method at R ≥ 80 for all 13 cases. This approach provided restoration of TK parameter values with less errors in tumor regions of interest, an improvement compared to a state-of-the-art indirect method. Applied prospectively, the proposed method provided whole-brain, high-resolution TK maps with good image quality. Model-based direct estimation of TK maps from k,t-space DCE-MRI data is feasible and is compatible up to 100-fold undersampling. Magn Reson Med 78:1566-1578, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Impact of the glass transition on exciton dynamics in polymer thin films

NASA Astrophysics Data System (ADS)

Ehrenreich, Philipp; Proepper, Daniel; Graf, Alexander; Jores, Stefan; Boris, Alexander V.; Schmidt-Mende, Lukas

2017-11-01

In the development of organic electronics, unlimited design possibilities of conjugated polymers offer a wide variety of mechanical and electronic properties. Thereby, it is crucially important to reveal universal physical characteristics that allow efficient and forward developments of new chemical compounds. In particular for organic solar cells, a deeper understanding of exciton dynamics in polymer films can help to improve the charge generation process further. For this purpose, poly(3-hexylthiophene) (P3HT) is commonly used as a model system, although exciton decay kinetics have found different interpretations. Using temperature-dependent time-resolved photoluminescence spectroscopy in combination with low-temperature spectroscopic ellipsometry, we can show that P3HT is indeed a model system in which excitons follow a simple diffusion/hopping model. Based on our results we can exclude the relevance of hot-exciton emission as well as a dynamic torsional relaxation upon photoexcitation on a ps time scale. Instead, we depict the glass transition temperature of polymers to strongly affect exciton dynamics.

Quantification of in vivo metabolic kinetics of hyperpolarized pyruvate in rat kidneys using dynamic 13C MRSI.

PubMed

Xu, Tao; Mayer, Dirk; Gu, Meng; Yen, Yi-Fen; Josan, Sonal; Tropp, James; Pfefferbaum, Adolf; Hurd, Ralph; Spielman, Daniel

2011-10-01

With signal-to-noise ratio enhancements on the order of 10,000-fold, hyperpolarized MRSI of metabolically active substrates allows the study of both the injected substrate and downstream metabolic products in vivo. Although hyperpolarized [1-(13)C]pyruvate, in particular, has been used to demonstrate metabolic activities in various animal models, robust quantification and metabolic modeling remain important areas of investigation. Enzyme saturation effects are routinely seen with commonly used doses of hyperpolarized [1-(13)C]pyruvate; however, most metrics proposed to date, including metabolite ratios, time-to-peak of metabolic products and single exchange rate constants, fail to capture these saturation effects. In addition, the widely used small-flip-angle excitation approach does not correctly model the inflow of fresh downstream metabolites generated proximal to the target slice, which is often a significant factor in vivo. In this work, we developed an efficient quantification framework employing a spiral-based dynamic spectroscopic imaging approach. The approach overcomes the aforementioned limitations and demonstrates that the in vivo (13)C labeling of lactate and alanine after a bolus injection of [1-(13)C]pyruvate is well approximated by saturatable kinetics, which can be mathematically modeled using a Michaelis-Menten-like formulation, with the resulting estimated apparent maximal reaction velocity V(max) and apparent Michaelis constant K(M) being unbiased with respect to critical experimental parameters, including the substrate dose, bolus shape and duration. Although the proposed saturatable model has a similar mathematical formulation to the original Michaelis-Menten kinetics, it is conceptually different. In this study, we focus on the (13)C labeling of lactate and alanine and do not differentiate the labeling mechanism (net flux or isotopic exchange) or the respective contribution of various factors (organ perfusion rate, substrate transport kinetics, enzyme activities and the size of the unlabeled lactate and alanine pools) to the labeling process. Copyright © 2011 John Wiley & Sons, Ltd.

Neurobiologically Inspired Approaches to Nonlinear Process Control and Modeling

DTIC Science & Technology

1999-12-31

incorporates second messenger reaction kinetics and calcium dynamics to represent the nonlinear dynamics and the crucial role of neuromodulation in local...reflex). The dynamic neuromodulation as a mechanism for the nonlinear attenuation is the novel result of this study. Ear- lier simulations have shown

An experimental model of COD abatement in MBBR based on biofilm growth dynamic and on substrates' removal kinetics.

PubMed

Siciliano, Alessio; De Rosa, Salvatore

2016-08-01

In this study, the performance of a lab-scale Moving Bed Biofilm Reactor (MBBR) under different operating conditions was analysed. Moreover, the dependence of the reaction rates both from the concentration and biodegradability of substrates and from the biofilm surface density, by means of several batch kinetic tests, was investigated. The reactor controls exhibited an increasing COD (Chemical Oxygen Demand) removal, reaching maximum yields (close to 90%) for influent loadings of up to12.5 gCOD/m(2)d. From this value, the pilot plant performance decreased to yields of only about 55% for influent loadings greater than 16 gCOD/m(2)d. In response to the influent loading increase, the biofilm surface density exhibited a logistic growing trend until reaching a maximum amount of total attached solids of about 9.5 g/m(2). The kinetic test results indicated that the COD removal rates for rapidly biodegradable, rapidly hydrolysable and slowly biodegradable substrates were not affected by the organic matter concentrations. Instead, first-order kinetics were detected with respect to biofilm surface density. The experimental results permitted the formulation of a mathematical model to predict the MBBR organic matter removal efficiency. The validity of the model was successfully tested in the lab-scale plant.

Dynamic PET Image reconstruction for parametric imaging using the HYPR kernel method

NASA Astrophysics Data System (ADS)

Spencer, Benjamin; Qi, Jinyi; Badawi, Ramsey D.; Wang, Guobao

2017-03-01

Dynamic PET image reconstruction is a challenging problem because of the ill-conditioned nature of PET and the lowcounting statistics resulted from short time-frames in dynamic imaging. The kernel method for image reconstruction has been developed to improve image reconstruction of low-count PET data by incorporating prior information derived from high-count composite data. In contrast to most of the existing regularization-based methods, the kernel method embeds image prior information in the forward projection model and does not require an explicit regularization term in the reconstruction formula. Inspired by the existing highly constrained back-projection (HYPR) algorithm for dynamic PET image denoising, we propose in this work a new type of kernel that is simpler to implement and further improves the kernel-based dynamic PET image reconstruction. Our evaluation study using a physical phantom scan with synthetic FDG tracer kinetics has demonstrated that the new HYPR kernel-based reconstruction can achieve a better region-of-interest (ROI) bias versus standard deviation trade-off for dynamic PET parametric imaging than the post-reconstruction HYPR denoising method and the previously used nonlocal-means kernel.

Mathematical modelling of disintegration-limited co-digestion of OFMSW and sewage sludge.

PubMed

Esposito, G; Frunzo, L; Panico, A; d'Antonio, G

2008-01-01

This paper presents a mathematical model able to simulate under dynamic conditions the physical, chemical and biological processes prevailing in a OFMSW and sewage sludge anaerobic digestion system. The model proposed is based on differential mass balance equations for substrates, products and bacterial groups involved in the co-digestion process and includes the biochemical reactions of the substrate conversion and the kinetics of microbial growth and decay. The main peculiarity of the model is the surface based kinetic description of the OFMSW disintegration process, whereas the pH determination is based on a nine-order polynomial equation derived by acid-base equilibria. The model can be applied to simulate the co-digestion process for several purposes, such as the evaluation of the optimal process conditions in terms of OFMSW/sewage sludge ratio, temperature, OFMSW particle size, solid mixture retention time, reactor stirring rate, etc. Biogas production and composition can also be evaluated to estimate the potential energy production under different process conditions. In particular, model simulations reported in this paper show the model capability to predict the OFMSW amount which can be treated in the digester of an existing MWWTP and to assess the OFMSW particle size diminution pre-treatment required to increase the rate of the disintegration process, which otherwise can highly limit the co-digestion system. Copyright IWA Publishing 2008.

Investigation of Coal-biomass Catalytic Gasification using Experiments, Reaction Kinetics and Computational Fluid Dynamics

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

Battaglia, Francine; Agblevor, Foster; Klein, Michael

A collaborative effort involving experiments, kinetic modeling, and computational fluid dynamics (CFD) was used to understand co-gasification of coal-biomass mixtures. The overall goal of the work was to determine the key reactive properties for coal-biomass mixed fuels. Sub-bituminous coal was mixed with biomass feedstocks to determine the fluidization and gasification characteristics of hybrid poplar wood, switchgrass and corn stover. It was found that corn stover and poplar wood were the best feedstocks to use with coal. The novel approach of this project was the use of a red mud catalyst to improve gasification and lower gasification temperatures. An important resultsmore » was the reduction of agglomeration of the biomass using the catalyst. An outcome of this work was the characterization of the chemical kinetics and reaction mechanisms of the co-gasification fuels, and the development of a set of models that can be integrated into other modeling environments. The multiphase flow code, MFIX, was used to simulate and predict the hydrodynamics and co-gasification, and results were validated with the experiments. The reaction kinetics modeling was used to develop a smaller set of reactions for tractable CFD calculations that represented the experiments. Finally, an efficient tool was developed, MCHARS, and coupled with MFIX to efficiently simulate the complex reaction kinetics.« less

Integration of Extended MHD and Kinetic Effects in Global Magnetosphere Models

NASA Astrophysics Data System (ADS)

Germaschewski, K.; Wang, L.; Maynard, K. R. M.; Raeder, J.; Bhattacharjee, A.

2015-12-01

Computational models of Earth's geospace environment are an important tool to investigate the science of the coupled solar-wind -- magnetosphere -- ionosphere system, complementing satellite and ground observations with a global perspective. They are also crucial in understanding and predicting space weather, in particular under extreme conditions. Traditionally, global models have employed the one-fluid MHD approximation, which captures large-scale dynamics quite well. However, in Earth's nearly collisionless plasma environment it breaks down on small scales, where ion and electron dynamics and kinetic effects become important, and greatly change the reconnection dynamics. A number of approaches have recently been taken to advance global modeling, e.g., including multiple ion species, adding Hall physics in a Generalized Ohm's Law, embedding local PIC simulations into a larger fluid domain and also some work on simulating the entire system with hybrid or fully kinetic models, the latter however being to computationally expensive to be run at realistic parameters. We will present an alternate approach, ie., a multi-fluid moment model that is derived rigorously from the Vlasov-Maxwell system. The advantage is that the computational cost remains managable, as we are still solving fluid equations. While the evolution equation for each moment is exact, it depends on the next higher-order moment, so that truncating the hiearchy and closing the system to capture the essential kinetic physics is crucial. We implement 5-moment (density, momentum, scalar pressure) and 10-moment (includes pressure tensor) versions of the model, and use local approximations for the heat flux to close the system. We test these closures by local simulations where we can compare directly to PIC / hybrid codes, and employ them in global simulations using the next-generation OpenGGCM to contrast them to MHD / Hall-MHD results and compare with observations.

Application of dynamic recurrent neural networks in nonlinear system identification

NASA Astrophysics Data System (ADS)

Du, Yun; Wu, Xueli; Sun, Huiqin; Zhang, Suying; Tian, Qiang

2006-11-01

An adaptive identification method of simple dynamic recurrent neural network (SRNN) for nonlinear dynamic systems is presented in this paper. This method based on the theory that by using the inner-states feed-back of dynamic network to describe the nonlinear kinetic characteristics of system can reflect the dynamic characteristics more directly, deduces the recursive prediction error (RPE) learning algorithm of SRNN, and improves the algorithm by studying topological structure on recursion layer without the weight values. The simulation results indicate that this kind of neural network can be used in real-time control, due to its less weight values, simpler learning algorithm, higher identification speed, and higher precision of model. It solves the problems of intricate in training algorithm and slow rate in convergence caused by the complicate topological structure in usual dynamic recurrent neural network.

Grain formation around carbon stars. 1: Stationary outflow models

NASA Technical Reports Server (NTRS)

Egan, Michael P.; Leung, Chun Ming

1995-01-01

Asymptotic giant branch (AGB) stars are known to be sites of dust formation and undergo significant mass loss. The outflow is believed to be driven by radiation pressure on grains and momentum coupling between the grains and gas. While the physics of shell dynamics and grain formation are closely coupled, most previous models of circumstellar shells have treated the problem separately. Studies of shell dynamics typically assume the existence of grains needed to drive the outflow, while most grain formation models assume a constant veolcity wind in which grains form. Furthermore, models of grain formation have relied primarily on classical nucleation theory instead of using a more realistic approach based on chemical kinetics. To model grain formation in carbon-rich AGB stars, we have coupled the kinetic equations governing small cluster growth to moment equations which determine the growth of large particles. Phenomenological models assuming stationary outflow are presented to demonstrate the differences between the classical nucleation approach and the kinetic equation method. It is found that classical nucleation theory predicts nucleation at a lower supersaturation ratio than is predicted by the kinetic equations, resulting in significant differences in grain properties. Coagulation of clusters larger than monomers is unimportant for grain formation in high mass-loss models but becomes more important to grain growth in low mass-loss situations. The properties of the dust grains are altered considerably if differential drift velocities are ignored in modeling grain formation. The effect of stellar temperature, stellar luminosity, and different outflow velocities are investigated. The models indicate that changing the stellar temperature while keeping the stellar luminosity constant has little effect on the physical parameters of the dust shell formed. Increasing the stellar luminosity while keeping the stellar temperature constant results in large differences in grain properties. For small outflow velocities, grains form at lower supersaturation ratios and close to the stellar photosphere, resulting in larger but fewer grains. The reverse is true when grains form under high outflow velocities, i.e., they form at higher supersaturation ratios, farther from the star, and are much smaller but at larger quantities.

Comparison of detailed and reduced kinetics mechanisms of silane oxidation in the basis of detonation wave structure problem

NASA Astrophysics Data System (ADS)

Fedorov, A. V.; Tropin, D. A.; Fomin, P. A.

2018-03-01

The paper deals with the problem of the structure of detonation waves in the silane-air mixture within the framework of mathematical model of a nonequilibrium gas dynamics. Detailed kinetic scheme of silane oxidation as well as the newly developed reduced kinetic model of detonation combustion of silane are used. On its basis the detonation wave (DW) structure in stoichiometric silane - air mixture and dependences of Chapman-Jouguet parameters of mixture on stoichiometric ratio between the fuel (silane) and an oxidizer (air) were obtained.

A theoretical study of the relaxation of a phenyl group chemisorbed to an RDX freestanding thin film

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

Pereverzev, Andrey, E-mail: pereverzeva@missouri.edu; Sewell, Thomas D., E-mail: sewellt@missouri.edu

Energy relaxation from an excited phenyl group chemisorbed to the surface of a crystalline thin film of α-1,3,5-trinitro-1,3,5-triazacyclohexane (α-RDX) at 298 K and 1 atm is simulated using molecular dynamics. Two schemes are used to excite the phenyl group. In the first scheme, the excitation energy is added instantaneously as kinetic energy by rescaling momenta of the 11 atoms in the phenyl group. In the second scheme, the phenyl group is equilibrated at a higher temperature in the presence of static RDX geometries representative of the 298 K thin film. An analytical model based on ballistic phonon transport that requiresmore » only the harmonic part of the total Hamiltonian and includes no adjustable parameters is shown to predict, essentially quantitatively, the short-time dynamics of the kinetic energy relaxation (∼200 fs). The dynamics of the phenyl group for times longer than about 6 ps follows exponential decay and agrees qualitatively with the dynamics described by a master equation. Long-time heat propagation within the bulk of the crystal film is consistent with the heat equation.« less

Modeling the Population Dynamics of Antibiotic-Resistant Bacteria:. AN Agent-Based Approach

NASA Astrophysics Data System (ADS)

Murphy, James T.; Walshe, Ray; Devocelle, Marc

The response of bacterial populations to antibiotic treatment is often a function of a diverse range of interacting factors. In order to develop strategies to minimize the spread of antibiotic resistance in pathogenic bacteria, a sound theoretical understanding of the systems of interactions taking place within a colony must be developed. The agent-based approach to modeling bacterial populations is a useful tool for relating data obtained at the molecular and cellular level with the overall population dynamics. Here we demonstrate an agent-based model, called Micro-Gen, which has been developed to simulate the growth and development of bacterial colonies in culture. The model also incorporates biochemical rules and parameters describing the kinetic interactions of bacterial cells with antibiotic molecules. Simulations were carried out to replicate the development of methicillin-resistant S. aureus (MRSA) colonies growing in the presence of antibiotics. The model was explored to see how the properties of the system emerge from the interactions of the individual bacterial agents in order to achieve a better mechanistic understanding of the population dynamics taking place. Micro-Gen provides a good theoretical framework for investigating the effects of local environmental conditions and cellular properties on the response of bacterial populations to antibiotic exposure in the context of a simulated environment.

Quantitative evaluation of dual-flip-angle T1 mapping on DCE-MRI kinetic parameter estimation in head and neck

PubMed Central

Chow, Steven Kwok Keung; Yeung, David Ka Wai; Ahuja, Anil T; King, Ann D

2012-01-01

Purpose To quantitatively evaluate the kinetic parameter estimation for head and neck (HN) dynamic contrast-enhanced (DCE) MRI with dual-flip-angle (DFA) T1 mapping. Materials and methods Clinical DCE-MRI datasets of 23 patients with HN tumors were included in this study. T1 maps were generated based on multiple-flip-angle (MFA) method and different DFA combinations. Tofts model parameter maps of kep, Ktrans and vp based on MFA and DFAs were calculated and compared. Fitted parameter by MFA and DFAs were quantitatively evaluated in primary tumor, salivary gland and muscle. Results T1 mapping deviations by DFAs produced remarkable kinetic parameter estimation deviations in head and neck tissues. In particular, the DFA of [2º, 7º] overestimated, while [7º, 12º] and [7º, 15º] underestimated Ktrans and vp, significantly (P<0.01). [2º, 15º] achieved the smallest but still statistically significant overestimation for Ktrans and vp in primary tumors, 32.1% and 16.2% respectively. kep fitting results by DFAs were relatively close to the MFA reference compared to Ktrans and vp. Conclusions T1 deviations induced by DFA could result in significant errors in kinetic parameter estimation, particularly Ktrans and vp, through Tofts model fitting. MFA method should be more reliable and robust for accurate quantitative pharmacokinetic analysis in head and neck. PMID:23289084

In situ dynamic observations of perovskite crystallisation and microstructure evolution intermediated from [PbI 6] 4– cage nanoparticles

DOE PAGES

Hu, Qin; Zhao, Lichen; Wu, Jiang; ...

2017-06-21

Hybrid lead halide perovskites have emerged as high-performance photovoltaic materials with their extraordinary optoelectronic properties. In particular, the remarkable device efficiency is strongly influenced by the perovskite crystallinity and the film morphology. Here, we investigate the perovskites crystallisation kinetics and growth mechanism in real time from liquid precursor continually to the final uniform film. We utilize some advanced in situ characterisation techniques including synchrotron-based grazing incident X-ray diffraction to observe crystal structure and chemical transition of perovskites. The nano-assemble model from perovskite intermediated [PbI 6] 4– cage nanoparticles to bulk polycrystals is proposed to understand perovskites formation at a molecular-more » or nano-level. A crystallisation-depletion mechanism is developed to elucidate the periodic crystallisation and the kinetically trapped morphology at a mesoscopic level. Based on these in situ dynamics studies, the whole process of the perovskites formation and transformation from the molecular to the microstructure over relevant temperature and time scales is successfully demonstrated.« less

VAMPnets for deep learning of molecular kinetics.

PubMed

Mardt, Andreas; Pasquali, Luca; Wu, Hao; Noé, Frank

2018-01-02

There is an increasing demand for computing the relevant structures, equilibria, and long-timescale kinetics of biomolecular processes, such as protein-drug binding, from high-throughput molecular dynamics simulations. Current methods employ transformation of simulated coordinates into structural features, dimension reduction, clustering the dimension-reduced data, and estimation of a Markov state model or related model of the interconversion rates between molecular structures. This handcrafted approach demands a substantial amount of modeling expertise, as poor decisions at any step will lead to large modeling errors. Here we employ the variational approach for Markov processes (VAMP) to develop a deep learning framework for molecular kinetics using neural networks, dubbed VAMPnets. A VAMPnet encodes the entire mapping from molecular coordinates to Markov states, thus combining the whole data processing pipeline in a single end-to-end framework. Our method performs equally or better than state-of-the-art Markov modeling methods and provides easily interpretable few-state kinetic models.

ROCKETSHIP: a flexible and modular software tool for the planning, processing and analysis of dynamic MRI studies.

PubMed

Barnes, Samuel R; Ng, Thomas S C; Santa-Maria, Naomi; Montagne, Axel; Zlokovic, Berislav V; Jacobs, Russell E

2015-06-16

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a promising technique to characterize pathology and evaluate treatment response. However, analysis of DCE-MRI data is complex and benefits from concurrent analysis of multiple kinetic models and parameters. Few software tools are currently available that specifically focuses on DCE-MRI analysis with multiple kinetic models. Here, we developed ROCKETSHIP, an open-source, flexible and modular software for DCE-MRI analysis. ROCKETSHIP incorporates analyses with multiple kinetic models, including data-driven nested model analysis. ROCKETSHIP was implemented using the MATLAB programming language. Robustness of the software to provide reliable fits using multiple kinetic models is demonstrated using simulated data. Simulations also demonstrate the utility of the data-driven nested model analysis. Applicability of ROCKETSHIP for both preclinical and clinical studies is shown using DCE-MRI studies of the human brain and a murine tumor model. A DCE-MRI software suite was implemented and tested using simulations. Its applicability to both preclinical and clinical datasets is shown. ROCKETSHIP was designed to be easily accessible for the beginner, but flexible enough for changes or additions to be made by the advanced user as well. The availability of a flexible analysis tool will aid future studies using DCE-MRI. A public release of ROCKETSHIP is available at https://github.com/petmri/ROCKETSHIP .

Piezoresistive microcantilever aptasensor for ricin detection and kinetic analysis

NASA Astrophysics Data System (ADS)

Liu, Zhi-Wei; Tong, Zhao-Yang; Liu, Bing; Hao, Lan-Qun; Mu, Xi-Hui; Zhang, Jin-Ping; Gao, Chuan

2015-04-01

Up to now, there has been no report on target molecules detection by a piezoresistive microcantilever aptasensor. In order to evaluate the test performance and investigate the response dynamic characteristics of a piezoresistive microcantilever aptasensor, a novel method for ricin detection and kinetic analysis based on a piezoresistive microcantilever aptasensor was proposed, where ricin aptamer was immobilised on the microcantilever surface by biotin-avidin binding system. Results showed that the detection limit of ricin was 0.04μg L-1 (S/N ≥ 3). A linear relationship between the response voltage and the concentration of ricin in the range of 0.2μg L-1-40μg L-1 was obtained, with the linear regression equation of ΔUe = 0.904C + 5.852 (n = 5, R = 0.991, p < 0.001). The sensor showed no response for abrin, BSA, and could overcome the influence of complex environmental disruptors, indicating high specificity and good selectivity. Recovery and reproducibility in the result of simulated samples (simulated water, soil, and flour sample) determination met the analysis requirements, which was 90.5˜95.5% and 7.85%˜9.39%, respectively. On this basis, a reaction kinetic model based on ligand-receptor binding and the relationship with response voltage was established. The model could well reflect the dynamic response of the sensor. The correlation coefficient (R) was greater than or equal to 0.9456 (p < 0.001). Response voltage (ΔUe) and response time (t0) obtained from the fitting equation on different concentrations of ricin fitted well with the measured values.

Femtosecond laser pulse driven melting in gold nanorod aqueous colloidal suspension: Identification of a transition from stretched to exponential kinetics

DOE PAGES

Li, Yuelin; Jiang, Zhang; Lin, Xiao -Min; ...

2015-01-30

Many potential industrial, medical, and environmental applications of metal nanorods rely on the physics and resultant kinetics and dynamics of the interaction of these particles with light. We report a surprising kinetics transition in the global melting of femtosecond laser-driven gold nanorod aqueous colloidal suspension. At low laser intensity, the melting exhibits a stretched exponential kinetics, which abruptly transforms into a compressed exponential kinetics when the laser intensity is raised. It is found the relative formation and reduction rate of intermediate shapes play a key role in the transition. Supported by both molecular dynamics simulations and a kinetic model, themore » behavior is traced back to the persistent heterogeneous nature of the shape dependence of the energy uptake, dissipation and melting of individual nanoparticles. These results could have significant implications for various applications such as water purification and electrolytes for energy storage that involve heat transport between metal nanorod ensembles and surrounding solvents.« less

4D-PET reconstruction using a spline-residue model with spatial and temporal roughness penalties

NASA Astrophysics Data System (ADS)

Ralli, George P.; Chappell, Michael A.; McGowan, Daniel R.; Sharma, Ricky A.; Higgins, Geoff S.; Fenwick, John D.

2018-05-01

4D reconstruction of dynamic positron emission tomography (dPET) data can improve the signal-to-noise ratio in reconstructed image sequences by fitting smooth temporal functions to the voxel time-activity-curves (TACs) during the reconstruction, though the optimal choice of function remains an open question. We propose a spline-residue model, which describes TACs as weighted sums of convolutions of the arterial input function with cubic B-spline basis functions. Convolution with the input function constrains the spline-residue model at early time-points, potentially enhancing noise suppression in early time-frames, while still allowing a wide range of TAC descriptions over the entire imaged time-course, thus limiting bias. Spline-residue based 4D-reconstruction is compared to that of a conventional (non-4D) maximum a posteriori (MAP) algorithm, and to 4D-reconstructions based on adaptive-knot cubic B-splines, the spectral model and an irreversible two-tissue compartment (‘2C3K’) model. 4D reconstructions were carried out using a nested-MAP algorithm including spatial and temporal roughness penalties. The algorithms were tested using Monte-Carlo simulated scanner data, generated for a digital thoracic phantom with uptake kinetics based on a dynamic [18F]-Fluromisonidazole scan of a non-small cell lung cancer patient. For every algorithm, parametric maps were calculated by fitting each voxel TAC within a sub-region of the reconstructed images with the 2C3K model. Compared to conventional MAP reconstruction, spline-residue-based 4D reconstruction achieved  >50% improvements for five of the eight combinations of the four kinetics parameters for which parametric maps were created with the bias and noise measures used to analyse them, and produced better results for 5/8 combinations than any of the other reconstruction algorithms studied, while spectral model-based 4D reconstruction produced the best results for 2/8. 2C3K model-based 4D reconstruction generated the most biased parametric maps. Inclusion of a temporal roughness penalty function improved the performance of 4D reconstruction based on the cubic B-spline, spectral and spline-residue models.

Dynamic Modeling of Cell-Free Biochemical Networks Using Effective Kinetic Models

DTIC Science & Technology

2015-03-03

whether we could simultaneously estimate kinetic parameters and regulatory connectivity, in the absence of specific mechanistic knowledge , from synthetic...that manage metabolism. Of course, these issues are not independent; any description of enzyme activity regulation will be a function of system state...the absence of specific mechanistic knowledge , from synthetic experimental data. Toward these questions, we explored five hypothetical cell-free

Multi-scale individual-based model of microbial and bioconversion dynamics in aerobic granular sludge.

PubMed

Xavier, Joao B; De Kreuk, Merle K; Picioreanu, Cristian; Van Loosdrecht, Mark C M

2007-09-15

Aerobic granular sludge is a novel compact biological wastewater treatment technology for integrated removal of COD (chemical oxygen demand), nitrogen, and phosphate charges. We present here a multiscale model of aerobic granular sludge sequencing batch reactors (GSBR) describing the complex dynamics of populations and nutrient removal. The macro scale describes bulk concentrations and effluent composition in six solutes (oxygen, acetate, ammonium, nitrite, nitrate, and phosphate). A finer scale, the scale of one granule (1.1 mm of diameter), describes the two-dimensional spatial arrangement of four bacterial groups--heterotrophs, ammonium oxidizers, nitrite oxidizers, and phosphate accumulating organisms (PAO)--using individual based modeling (IbM) with species-specific kinetic models. The model for PAO includes three internal storage compounds: polyhydroxyalkanoates (PHA), poly phosphate, and glycogen. Simulations of long-term reactor operation show how the microbial population and activity depends on the operating conditions. Short-term dynamics of solute bulk concentrations are also generated with results comparable to experimental data from lab scale reactors. Our results suggest that N-removal in GSBR occurs mostly via alternating nitrification/denitrification rather than simultaneous nitrification/denitrification, supporting an alternative strategy to improve N-removal in this promising wastewater treatment process.

Crystal-melt interface mobility in bcc Fe: Linking molecular dynamics to phase-field and phase-field crystal modeling

NASA Astrophysics Data System (ADS)

Guerdane, M.; Berghoff, M.

2018-04-01

By combining molecular dynamics (MD) simulations with phase-field (PF) and phase-field crystal (PFC) modeling we study collision-controlled growth kinetics from the melt for pure Fe. The MD/PF comparison shows, on the one hand, that the PF model can be properly designed to reproduce quantitatively different aspects of the growth kinetics and anisotropy of planar and curved solid-liquid interfaces. On the other hand, this comparison demonstrates the ability of classical MD simulations to predict morphology and dynamics of moving curved interfaces up to a length scale of about 0.15 μ m . After mapping the MD model to the PF one, the latter permits to analyze the separate contribution of different anisotropies to the interface morphology. The MD/PFC agreement regarding the growth anisotropy and morphology extends the trend already observed for the here used PFC model in describing structural and elastic properties of bcc Fe.

Dynamic modeling of reversible methanolysis of Jatropha curcas oil to biodiesel.

PubMed

Syam, Azhari M; Hamid, Hamidah A; Yunus, Robiah; Rashid, Umer

2013-01-01

Many kinetics studies on methanolysis assumed the reactions to be irreversible. The aim of the present work was to study the dynamic modeling of reversible methanolysis of Jatropha curcas oil (JCO) to biodiesel. The experimental data were collected under the optimal reaction conditions: molar ratio of methanol to JCO at 6 : 1, reaction temperature of 60°C, 60 min of reaction time, and 1% w/w of catalyst concentration. The dynamic modeling involved the derivation of differential equations for rates of three stepwise reactions. The simulation study was then performed on the resulting equations using MATLAB. The newly developed reversible models were fitted with various rate constants and compared with the experimental data for fitting purposes. In addition, analysis of variance was done statistically to evaluate the adequacy and quality of model parameters. The kinetics study revealed that the reverse reactions were significantly slower than forward reactions. The activation energies ranged from 6.5 to 44.4 KJ mol⁻¹.

Dynamic Modeling of Reversible Methanolysis of Jatropha curcas Oil to Biodiesel

PubMed Central

Syam, Azhari M.; Hamid, Hamidah A.; Yunus, Robiah; Rashid, Umer

2013-01-01

Many kinetics studies on methanolysis assumed the reactions to be irreversible. The aim of the present work was to study the dynamic modeling of reversible methanolysis of Jatropha curcas oil (JCO) to biodiesel. The experimental data were collected under the optimal reaction conditions: molar ratio of methanol to JCO at 6 : 1, reaction temperature of 60°C, 60 min of reaction time, and 1% w/w of catalyst concentration. The dynamic modeling involved the derivation of differential equations for rates of three stepwise reactions. The simulation study was then performed on the resulting equations using MATLAB. The newly developed reversible models were fitted with various rate constants and compared with the experimental data for fitting purposes. In addition, analysis of variance was done statistically to evaluate the adequacy and quality of model parameters. The kinetics study revealed that the reverse reactions were significantly slower than forward reactions. The activation energies ranged from 6.5 to 44.4 KJ mol−1. PMID:24363616

A unified gas-kinetic scheme for continuum and rarefied flows IV: Full Boltzmann and model equations

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

Liu, Chang, E-mail: cliuaa@ust.hk; Xu, Kun, E-mail: makxu@ust.hk; Sun, Quanhua, E-mail: qsun@imech.ac.cn

Fluid dynamic equations are valid in their respective modeling scales, such as the particle mean free path scale of the Boltzmann equation and the hydrodynamic scale of the Navier–Stokes (NS) equations. With a variation of the modeling scales, theoretically there should have a continuous spectrum of fluid dynamic equations. Even though the Boltzmann equation is claimed to be valid in all scales, many Boltzmann solvers, including direct simulation Monte Carlo method, require the cell resolution to the order of particle mean free path scale. Therefore, they are still single scale methods. In order to study multiscale flow evolution efficiently, themore » dynamics in the computational fluid has to be changed with the scales. A direct modeling of flow physics with a changeable scale may become an appropriate approach. The unified gas-kinetic scheme (UGKS) is a direct modeling method in the mesh size scale, and its underlying flow physics depends on the resolution of the cell size relative to the particle mean free path. The cell size of UGKS is not limited by the particle mean free path. With the variation of the ratio between the numerical cell size and local particle mean free path, the UGKS recovers the flow dynamics from the particle transport and collision in the kinetic scale to the wave propagation in the hydrodynamic scale. The previous UGKS is mostly constructed from the evolution solution of kinetic model equations. Even though the UGKS is very accurate and effective in the low transition and continuum flow regimes with the time step being much larger than the particle mean free time, it still has space to develop more accurate flow solver in the region, where the time step is comparable with the local particle mean free time. In such a scale, there is dynamic difference from the full Boltzmann collision term and the model equations. This work is about the further development of the UGKS with the implementation of the full Boltzmann collision term in the region where it is needed. The central ingredient of the UGKS is the coupled treatment of particle transport and collision in the flux evaluation across a cell interface, where a continuous flow dynamics from kinetic to hydrodynamic scales is modeled. The newly developed UGKS has the asymptotic preserving (AP) property of recovering the NS solutions in the continuum flow regime, and the full Boltzmann solution in the rarefied regime. In the mostly unexplored transition regime, the UGKS itself provides a valuable tool for the non-equilibrium flow study. The mathematical properties of the scheme, such as stability, accuracy, and the asymptotic preserving, will be analyzed in this paper as well.« less

A molecular dynamics approach to barrodiffusion

NASA Astrophysics Data System (ADS)

Cooley, James; Marciante, Mathieu; Murillo, Michael

2016-10-01

Unexpected phenomena in the reaction rates for Inertial Confinement Fusion (ICF) capsules have led to a renewed interest in the thermo-dynamically driven diffusion process for the past 10 years, often described collectively as barodiffusion. In the current context, barodiffusion would manifest as a process that separates ions of differing mass and charge ratios due to pressure and temperature gradients set-up through shock structures in the capsule core. Barrodiffusion includes additional mass transfer terms that account for the irreversible transport of species due to gradients in the system, both thermodynamic and electric e.g, i = - ρD [ ∇c +kp ∇ln(pi) +kT(i) ∇ln(Ti) +kt(e) ∇ln(Te) +eke/Ti ∇ϕ ] . Several groups have attacked this phenomena using continuum scale models and supplemented with kinetic theory to derive coefficients for the different diffusion terms based on assumptions about the collisional processes. In contrast, we have applied a molecular dynamics (MD) simulation to this system to gain a first-principle understanding of the rate kinetics and to assess the accuracy of the differin

A Multi Water Bag model of drift kinetic electron plasmaa

NASA Astrophysics Data System (ADS)

Morel, Pierre; Ghiro, Florent Dreydemy; Berionni, Vincent; Coulette, David; Besse, Nicolas; Gürcan, Özgür D.

2014-08-01

A Multi Water Bag model is proposed for describing drift kinetic plasmas in a magnetized cylindrical geometry, relevant for various experimental devices, solar wind modeling... The Multi Water Bag (MWB) model is adapted to the description of a plasma with kinetic electrons as well as an arbitrary number of kinetic ions. This allows to describe the kinetic dynamics of the electrons, making possible the study of electron temperature gradient (ETG) modes, in addition to the effects of non adiabatic electrons on the ion temperature gradient (ITG) modes, that are of prime importance in the magnetized plasmas micro-turbulence [X. Garbet, Y. Idomura, L. Villard, T.H. Watanabe, Nucl. Fusion 50, 043002 (2010); J.A. Krommes, Ann. Rev. Fluid Mech. 44, 175 (2012)]. The MWB model is shown to link kinetic and fluid descriptions, depending on the number of bags considered. Linear stability of the ETG modes is presented and compared to the existing results regarding cylindrical ITG modes [P. Morel, E. Gravier, N. Besse, R. Klein, A. Ghizzo, P. Bertrand, W. Garbet, Ph. Ghendrih, V. Grandgirard, Y. Sarazin, Phys. Plasmas 14, 112109 (2007)].

Dissolution of covalent adaptable network polymers in organic solvent

NASA Astrophysics Data System (ADS)

Yu, Kai; Yang, Hua; Dao, Binh H.; Shi, Qian; Yakacki, Christopher M.

2017-12-01

It was recently reported that thermosetting polymers can be fully dissolved in a proper organic solvent utilizing a bond-exchange reaction (BER), where small molecules diffuse into the polymer, break the long polymer chains into short segments, and eventually dissolve the network when sufficient solvent is provided. The solvent-assisted dissolution approach was applied to fully recycle thermosets and their fiber composites. This paper presents the first multi-scale modeling framework to predict the dissolution kinetics and mechanics of thermosets in organic solvent. The model connects the micro-scale network dynamics with macro-scale material properties: in the micro-scale, a model is developed based on the kinetics of BERs to describe the cleavage rate of polymer chains and evolution of chain segment length during the dissolution. The micro-scale model is then fed into a continuum-level model with considerations of the transportation of solvent molecules and chain segments in the system. The model shows good prediction on conversion rate of functional groups, degradation of network mechanical properties, and dissolution rate of thermosets during the dissolution. It identifies the underlying kinetic factors governing the dissolution process, and reveals the influence of different material and processing variables on the dissolution process, such as time, temperature, catalyst concentration, and chain length between cross-links.

Joint estimation of subject motion and tracer kinetic parameters of dynamic PET data in an EM framework

NASA Astrophysics Data System (ADS)

Jiao, Jieqing; Salinas, Cristian A.; Searle, Graham E.; Gunn, Roger N.; Schnabel, Julia A.

2012-02-01

Dynamic Positron Emission Tomography is a powerful tool for quantitative imaging of in vivo biological processes. The long scan durations necessitate motion correction, to maintain the validity of the dynamic measurements, which can be particularly challenging due to the low signal-to-noise ratio (SNR) and spatial resolution, as well as the complex tracer behaviour in the dynamic PET data. In this paper we develop a novel automated expectation-maximisation image registration framework that incorporates temporal tracer kinetic information to correct for inter-frame subject motion during dynamic PET scans. We employ the Zubal human brain phantom to simulate dynamic PET data using SORTEO (a Monte Carlo-based simulator), in order to validate the proposed method for its ability to recover imposed rigid motion. We have conducted a range of simulations using different noise levels, and corrupted the data with a range of rigid motion artefacts. The performance of our motion correction method is compared with pairwise registration using normalised mutual information as a voxel similarity measure (an approach conventionally used to correct for dynamic PET inter-frame motion based solely on intensity information). To quantify registration accuracy, we calculate the target registration error across the images. The results show that our new dynamic image registration method based on tracer kinetics yields better realignment of the simulated datasets, halving the target registration error when compared to the conventional method at small motion levels, as well as yielding smaller residuals in translation and rotation parameters. We also show that our new method is less affected by the low signal in the first few frames, which the conventional method based on normalised mutual information fails to realign.

A CONTINUUM HARD-SPHERE MODEL OF PROTEIN ADSORPTION

PubMed Central

Finch, Craig; Clarke, Thomas; Hickman, James J.

2012-01-01

Protein adsorption plays a significant role in biological phenomena such as cell-surface interactions and the coagulation of blood. Two-dimensional random sequential adsorption (RSA) models are widely used to model the adsorption of proteins on solid surfaces. Continuum equations have been developed so that the results of RSA simulations can be used to predict the kinetics of adsorption. Recently, Brownian dynamics simulations have become popular for modeling protein adsorption. In this work a continuum model was developed to allow the results from a Brownian dynamics simulation to be used as the boundary condition in a computational fluid dynamics (CFD) simulation. Brownian dynamics simulations were used to model the diffusive transport of hard-sphere particles in a liquid and the adsorption of the particles onto a solid surface. The configuration of the adsorbed particles was analyzed to quantify the chemical potential near the surface, which was found to be a function of the distance from the surface and the fractional surface coverage. The near-surface chemical potential was used to derive a continuum model of adsorption that incorporates the results from the Brownian dynamics simulations. The equations of the continuum model were discretized and coupled to a CFD simulation of diffusive transport to the surface. The kinetics of adsorption predicted by the continuum model closely matched the results from the Brownian dynamics simulation. This new model allows the results from mesoscale simulations to be incorporated into micro- or macro-scale CFD transport simulations of protein adsorption in practical devices. PMID:23729843

Inherent structure versus geometric metric for state space discretization.

PubMed

Liu, Hanzhong; Li, Minghai; Fan, Jue; Huo, Shuanghong

2016-05-30

Inherent structure (IS) and geometry-based clustering methods are commonly used for analyzing molecular dynamics trajectories. ISs are obtained by minimizing the sampled conformations into local minima on potential/effective energy surface. The conformations that are minimized into the same energy basin belong to one cluster. We investigate the influence of the applications of these two methods of trajectory decomposition on our understanding of the thermodynamics and kinetics of alanine tetrapeptide. We find that at the microcluster level, the IS approach and root-mean-square deviation (RMSD)-based clustering method give totally different results. Depending on the local features of energy landscape, the conformations with close RMSDs can be minimized into different minima, while the conformations with large RMSDs could be minimized into the same basin. However, the relaxation timescales calculated based on the transition matrices built from the microclusters are similar. The discrepancy at the microcluster level leads to different macroclusters. Although the dynamic models established through both clustering methods are validated approximately Markovian, the IS approach seems to give a meaningful state space discretization at the macrocluster level in terms of conformational features and kinetics. © 2016 Wiley Periodicals, Inc.

Integrated Physics-based Modeling and Experiments for Improved Prediction of Combustion Dynamics in Low-Emission Systems

NASA Technical Reports Server (NTRS)

Anderson, William E.; Lucht, Robert P.; Mongia, Hukam

2015-01-01

Concurrent simulation and experiment was undertaken to assess the ability of a hybrid RANS-LES model to predict combustion dynamics in a single-element lean direct-inject (LDI) combustor showing self-excited instabilities. High frequency pressure modes produced by Fourier and modal decomposition analysis were compared quantitatively, and trends with equivalence ratio and inlet temperature were compared qualitatively. High frequency OH PLIF and PIV measurements were also taken. Submodels for chemical kinetics and primary and secondary atomization were also tested against the measured behavior. For a point-wise comparison, the amplitudes matched within a factor of two. The dependence on equivalence ratio was matched. Preliminary results from simulation using an 18-reaction kinetics model indicated instability amplitudes closer to measurement. Analysis of the simulations suggested a band of modes around 1400 Hz were due to a vortex bubble breakdown and a band of modes around 6 kHz were due to a precessing vortex core hydrodynamic instability. The primary needs are directly coupled and validated ab initio models of the atomizer free surface flow and the primary atomization processes, and more detailed study of the coupling between the 3D swirling flow and the local thermoacoustics in the diverging venturi section.

Gaussian process inference for estimating pharmacokinetic parameters of dynamic contrast-enhanced MR images.

PubMed

Wang, Shijun; Liu, Peter; Turkbey, Baris; Choyke, Peter; Pinto, Peter; Summers, Ronald M

2012-01-01

In this paper, we propose a new pharmacokinetic model for parameter estimation of dynamic contrast-enhanced (DCE) MRI by using Gaussian process inference. Our model is based on the Tofts dual-compartment model for the description of tracer kinetics and the observed time series from DCE-MRI is treated as a Gaussian stochastic process. The parameter estimation is done through a maximum likelihood approach and we propose a variant of the coordinate descent method to solve this likelihood maximization problem. The new model was shown to outperform a baseline method on simulated data. Parametric maps generated on prostate DCE data with the new model also provided better enhancement of tumors, lower intensity on false positives, and better boundary delineation when compared with the baseline method. New statistical parameter maps from the process model were also found to be informative, particularly when paired with the PK parameter maps.

Thermodynamically Feasible Kinetic Models of Reaction Networks

PubMed Central

Ederer, Michael; Gilles, Ernst Dieter

2007-01-01

The dynamics of biological reaction networks are strongly constrained by thermodynamics. An holistic understanding of their behavior and regulation requires mathematical models that observe these constraints. However, kinetic models may easily violate the constraints imposed by the principle of detailed balance, if no special care is taken. Detailed balance demands that in thermodynamic equilibrium all fluxes vanish. We introduce a thermodynamic-kinetic modeling (TKM) formalism that adapts the concepts of potentials and forces from irreversible thermodynamics to kinetic modeling. In the proposed formalism, the thermokinetic potential of a compound is proportional to its concentration. The proportionality factor is a compound-specific parameter called capacity. The thermokinetic force of a reaction is a function of the potentials. Every reaction has a resistance that is the ratio of thermokinetic force and reaction rate. For mass-action type kinetics, the resistances are constant. Since it relies on the thermodynamic concept of potentials and forces, the TKM formalism structurally observes detailed balance for all values of capacities and resistances. Thus, it provides an easy way to formulate physically feasible, kinetic models of biological reaction networks. The TKM formalism is useful for modeling large biological networks that are subject to many detailed balance relations. PMID:17208985

Kinetics of the Tau PET Tracer 18F-AV-1451 (T807) in Subjects with Normal Cognitive Function, Mild Cognitive Impairment, and Alzheimer Disease.

PubMed

Shcherbinin, Sergey; Schwarz, Adam J; Joshi, Abhinay; Navitsky, Michael; Flitter, Matthew; Shankle, William R; Devous, Michael D; Mintun, Mark A

2016-10-01

We report kinetic modeling results of dynamic acquisition data from 0 to 100 min after injection with the tau PET tracer 18 F-AV-1451 in 19 subjects. Subjects were clinically diagnosed as 4 young cognitively normal, 5 old cognitively normal, 5 mild cognitive impairment, and 5 Alzheimer disease (AD). Kinetic modeling was performed using Logan graphical analysis with the cerebellum crus as a reference region. Voxelwise binding potential ([Formula: see text]) and SUV ratio ([Formula: see text]) images were compared. In AD subjects, slower and spatially nonuniform clearance from cortical regions was observed as compared with the controls, which led to focal uptake and elevated retention in the imaging data from 80 to 100 min after injection. BP from the dynamic data from 0 to 100 min correlated strongly (R 2 > 0.86) with corresponding regional [Formula: see text] values. In the putamen, the observed kinetics (positive [Formula: see text] at the tracer delivery stage and plateauing time-SUVR curves for all diagnostic categories) may suggest either additional off-target binding or a second binding site with different kinetics. The kinetics of the 18 F-AV-1451 tracer in cortical areas, as examined in this small group of subjects, differed by diagnostic stage. A delayed 80- to 100-min scan provided a reasonable substitute for a dynamic 0- to 100-min acquisition for cortical regions although other windows (e.g., 75-105 min) may be useful to evaluate. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

A Kinetic Model of Trp-Cage Folding from Multiple Biased Molecular Dynamics Simulations

PubMed Central

Marinelli, Fabrizio; Pietrucci, Fabio; Laio, Alessandro; Piana, Stefano

2009-01-01

Trp-cage is a designed 20-residue polypeptide that, in spite of its size, shares several features with larger globular proteins. Although the system has been intensively investigated experimentally and theoretically, its folding mechanism is not yet fully understood. Indeed, some experiments suggest a two-state behavior, while others point to the presence of intermediates. In this work we show that the results of a bias-exchange metadynamics simulation can be used for constructing a detailed thermodynamic and kinetic model of the system. The model, although constructed from a biased simulation, has a quality similar to those extracted from the analysis of long unbiased molecular dynamics trajectories. This is demonstrated by a careful benchmark of the approach on a smaller system, the solvated Ace-Ala3-Nme peptide. For the Trp-cage folding, the model predicts that the relaxation time of 3100 ns observed experimentally is due to the presence of a compact molten globule-like conformation. This state has an occupancy of only 3% at 300 K, but acts as a kinetic trap. Instead, non-compact structures relax to the folded state on the sub-microsecond timescale. The model also predicts the presence of a state at of 4.4 Å from the NMR structure in which the Trp strongly interacts with Pro12. This state can explain the abnormal temperature dependence of the and chemical shifts. The structures of the two most stable misfolded intermediates are in agreement with NMR experiments on the unfolded protein. Our work shows that, using biased molecular dynamics trajectories, it is possible to construct a model describing in detail the Trp-cage folding kinetics and thermodynamics in agreement with experimental data. PMID:19662155

Surface chemistry characterization of hydrodesulfurization and methanol synthesis model nanocatalysts

NASA Astrophysics Data System (ADS)

Komarneni, Mallikharjuna Rao

Surface science investigations of model catalysts have contributed significantly to heterogeneous catalysis over the past several decades. The unique properties of nanomaterials are being exploited in catalysis for the development of highly active and selective catalysts. Surface science investigations of model catalysts such as inorganic fullerene-like (IF) nanoparticles (NP), inorganic nanotubes (INT), and the oxide-supported nanoclusters are included in this dissertation. Thermal desorption spectroscopy and molecular beam scattering were respectively utilized to study the adsorption kinetics and dynamics of gas phase molecules on catalyst surfaces. In addition, ambient pressure kinetics experiments were performed to characterize the catalytic activity of hydrodesulfurization (HDS) nanocatalysts. The nanocatalysts were characterized with a variety of techniques, including Auger electron spectroscopy, x-ray photoelectron spectroscopy, electron microscopy, and x-ray diffraction. The adsorption kinetics studies of thiophene on novel HDS catalysts provided the first evidence for the presence of different adsorption sites on INT-WS2. Additionally, the adsorption sites on IF-MoS2 NP and silica-supported Mo clusters (Mo/silica) were characterized. Furthermore, the C-S bond activation energy of thiophene on Mo/silica was determined. These studies finally led to the fabrication of Ni/Co coated INT-WS2, which showed good catalytic activity towards HDS of thiophene. The studies of methanol synthesis catalysts include the adsorption kinetics and dynamics studies of CO and CO2 on Cu/silica and silica-supported EBL-fabricated Cu/CuOx nanoclusters. The adsorption dynamics of CO on Cu/silica are modeled within the frame work of the capture zone model (CZM), and the active sites of the silica-supported Au/Cu catalysts are successfully mapped. Studies on EBL model catalysts identify the rims of the CuOx nanoclusters as catalytically active sites. This observation has implications for new methanol catalyst design.

A kinetic model of trp-cage folding from multiple biased molecular dynamics simulations.

PubMed

Marinelli, Fabrizio; Pietrucci, Fabio; Laio, Alessandro; Piana, Stefano

2009-08-01

Trp-cage is a designed 20-residue polypeptide that, in spite of its size, shares several features with larger globular proteins.Although the system has been intensively investigated experimentally and theoretically, its folding mechanism is not yet fully understood. Indeed, some experiments suggest a two-state behavior, while others point to the presence of intermediates. In this work we show that the results of a bias-exchange metadynamics simulation can be used for constructing a detailed thermodynamic and kinetic model of the system. The model, although constructed from a biased simulation, has a quality similar to those extracted from the analysis of long unbiased molecular dynamics trajectories. This is demonstrated by a careful benchmark of the approach on a smaller system, the solvated Ace-Ala3-Nme peptide. For theTrp-cage folding, the model predicts that the relaxation time of 3100 ns observed experimentally is due to the presence of a compact molten globule-like conformation. This state has an occupancy of only 3% at 300 K, but acts as a kinetic trap.Instead, non-compact structures relax to the folded state on the sub-microsecond timescale. The model also predicts the presence of a state at Calpha-RMSD of 4.4 A from the NMR structure in which the Trp strongly interacts with Pro12. This state can explain the abnormal temperature dependence of the Pro12-delta3 and Gly11-alpha3 chemical shifts. The structures of the two most stable misfolded intermediates are in agreement with NMR experiments on the unfolded protein. Our work shows that, using biased molecular dynamics trajectories, it is possible to construct a model describing in detail the Trp-cage folding kinetics and thermodynamics in agreement with experimental data.

Turbulent Radiation Effects in HSCT Combustor Rich Zone

NASA Technical Reports Server (NTRS)

Hall, Robert J.; Vranos, Alexander; Yu, Weiduo

1998-01-01

A joint UTRC-University of Connecticut theoretical program was based on describing coupled soot formation and radiation in turbulent flows using stretched flamelet theory. This effort was involved with using the model jet fuel kinetics mechanism to predict soot growth in flamelets at elevated pressure, to incorporate an efficient model for turbulent thermal radiation into a discrete transfer radiation code, and to couple die soot growth, flowfield, and radiation algorithm. The soot calculations used a recently developed opposed jet code which couples the dynamical equations of size-class dependent particle growth with complex chemistry. Several of the tasks represent technical firsts; among these are the prediction of soot from a detailed jet fuel kinetics mechanism, the inclusion of pressure effects in the soot particle growth equations, and the inclusion of the efficient turbulent radiation algorithm in a combustor code.

On the kinetics of the capillary imbibition of a simple fluid through a designed nanochannel using the molecular dynamics simulation approach.

PubMed

Ahadian, Samad; Mizuseki, Hiroshi; Kawazoe, Yoshiyuki

2010-12-15

A molecular dynamics (MD) approach was employed to simulate the imbibition of a designed nanopore by a simple fluid (i.e., a Lennard-Jones (LJ) fluid). The length of imbibition as a function of time for various interactions between the LJ fluid and the pore wall was recorded for this system (i.e., the LJ fluid and the nanopore). By and large, the kinetics of imbibition was successfully described by the Lucas-Washburn (LW) equation, although deviation from it was observed in some cases. This lack of agreement is due to the neglect of the dynamic contact angle (DCA) in the LW equation. Two commonly used models (i.e., hydrodynamic and molecular-kinetic (MK) models) were thus employed to calculate the DCA. It is demonstrated that the MK model is able to justify the simulation results in which are not in good agreement with the simple LW equation. However, the hydrodynamic model is not capable of doing that. Further investigation of the MD simulation data revealed an interesting fact that there is a direct relationship between the wall-fluid interaction and the speed of the capillary imbibition. More evidence to support this claim is presented. Copyright © 2010 Elsevier Inc. All rights reserved.

Reverse engineering of logic-based differential equation models using a mixed-integer dynamic optimization approach

PubMed Central

Henriques, David; Rocha, Miguel; Saez-Rodriguez, Julio; Banga, Julio R.

2015-01-01

Motivation: Systems biology models can be used to test new hypotheses formulated on the basis of previous knowledge or new experimental data, contradictory with a previously existing model. New hypotheses often come in the shape of a set of possible regulatory mechanisms. This search is usually not limited to finding a single regulation link, but rather a combination of links subject to great uncertainty or no information about the kinetic parameters. Results: In this work, we combine a logic-based formalism, to describe all the possible regulatory structures for a given dynamic model of a pathway, with mixed-integer dynamic optimization (MIDO). This framework aims to simultaneously identify the regulatory structure (represented by binary parameters) and the real-valued parameters that are consistent with the available experimental data, resulting in a logic-based differential equation model. The alternative to this would be to perform real-valued parameter estimation for each possible model structure, which is not tractable for models of the size presented in this work. The performance of the method presented here is illustrated with several case studies: a synthetic pathway problem of signaling regulation, a two-component signal transduction pathway in bacterial homeostasis, and a signaling network in liver cancer cells. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: julio@iim.csic.es or saezrodriguez@ebi.ac.uk PMID:26002881

Reverse engineering of logic-based differential equation models using a mixed-integer dynamic optimization approach.

PubMed

Henriques, David; Rocha, Miguel; Saez-Rodriguez, Julio; Banga, Julio R

2015-09-15

Systems biology models can be used to test new hypotheses formulated on the basis of previous knowledge or new experimental data, contradictory with a previously existing model. New hypotheses often come in the shape of a set of possible regulatory mechanisms. This search is usually not limited to finding a single regulation link, but rather a combination of links subject to great uncertainty or no information about the kinetic parameters. In this work, we combine a logic-based formalism, to describe all the possible regulatory structures for a given dynamic model of a pathway, with mixed-integer dynamic optimization (MIDO). This framework aims to simultaneously identify the regulatory structure (represented by binary parameters) and the real-valued parameters that are consistent with the available experimental data, resulting in a logic-based differential equation model. The alternative to this would be to perform real-valued parameter estimation for each possible model structure, which is not tractable for models of the size presented in this work. The performance of the method presented here is illustrated with several case studies: a synthetic pathway problem of signaling regulation, a two-component signal transduction pathway in bacterial homeostasis, and a signaling network in liver cancer cells. Supplementary data are available at Bioinformatics online. julio@iim.csic.es or saezrodriguez@ebi.ac.uk. © The Author 2015. Published by Oxford University Press.

Analysis of Electromagnetic Wave Propagation in a Magnetized Re-Entry Plasma Sheath Via the Kinetic Equation

NASA Technical Reports Server (NTRS)

Manning, Robert M.

2009-01-01

Based on a theoretical model of the propagation of electromagnetic waves through a hypersonically induced plasma, it has been demonstrated that the classical radiofrequency communications blackout that is experienced during atmospheric reentry can be mitigated through the appropriate control of an external magnetic field of nominal magnitude. The model is based on the kinetic equation treatment of Vlasov and involves an analytical solution for the electric and magnetic fields within the plasma allowing for a description of the attendant transmission, reflection and absorption coefficients. The ability to transmit through the magnetized plasma is due to the magnetic windows that are created within the plasma via the well-known whistler modes of propagation. The case of 2 GHz transmission through a re-entry plasma is considered. The coefficients are found to be highly sensitive to the prevailing electron density and will thus require a dynamic control mechanism to vary the magnetic field as the plasma evolves through the re-entry phase.

A consistent hierarchy of generalized kinetic equation approximations to the master equation applied to surface catalysis.

PubMed

Herschlag, Gregory J; Mitran, Sorin; Lin, Guang

2015-06-21

We develop a hierarchy of approximations to the master equation for systems that exhibit translational invariance and finite-range spatial correlation. Each approximation within the hierarchy is a set of ordinary differential equations that considers spatial correlations of varying lattice distance; the assumption is that the full system will have finite spatial correlations and thus the behavior of the models within the hierarchy will approach that of the full system. We provide evidence of this convergence in the context of one- and two-dimensional numerical examples. Lower levels within the hierarchy that consider shorter spatial correlations are shown to be up to three orders of magnitude faster than traditional kinetic Monte Carlo methods (KMC) for one-dimensional systems, while predicting similar system dynamics and steady states as KMC methods. We then test the hierarchy on a two-dimensional model for the oxidation of CO on RuO2(110), showing that low-order truncations of the hierarchy efficiently capture the essential system dynamics. By considering sequences of models in the hierarchy that account for longer spatial correlations, successive model predictions may be used to establish empirical approximation of error estimates. The hierarchy may be thought of as a class of generalized phenomenological kinetic models since each element of the hierarchy approximates the master equation and the lowest level in the hierarchy is identical to a simple existing phenomenological kinetic models.

A multiscale computational approach to dissect early events in the Erb family receptor mediated activation, differential signaling, and relevance to oncogenic transformations.

PubMed

Liu, Yingting; Purvis, Jeremy; Shih, Andrew; Weinstein, Joshua; Agrawal, Neeraj; Radhakrishnan, Ravi

2007-06-01

We describe a hierarchical multiscale computational approach based on molecular dynamics simulations, free energy-based molecular docking simulations, deterministic network-based kinetic modeling, and hybrid discrete/continuum stochastic dynamics protocols to study the dimer-mediated receptor activation characteristics of the Erb family receptors, specifically the epidermal growth factor receptor (EGFR). Through these modeling approaches, we are able to extend the prior modeling of EGF-mediated signal transduction by considering specific EGFR tyrosine kinase (EGFRTK) docking interactions mediated by differential binding and phosphorylation of different C-terminal peptide tyrosines on the RTK tail. By modeling signal flows through branching pathways of the EGFRTK resolved on a molecular basis, we are able to transcribe the effects of molecular alterations in the receptor (e.g., mutant forms of the receptor) to differing kinetic behavior and downstream signaling response. Our molecular dynamics simulations show that the drug sensitizing mutation (L834R) of EGFR stabilizes the active conformation to make the system constitutively active. Docking simulations show preferential characteristics (for wildtype vs. mutant receptors) in inhibitor binding as well as preferential enhancement of phosphorylation of particular substrate tyrosines over others. We find that in comparison to the wildtype system, the L834R mutant RTK preferentially binds the inhibitor erlotinib, as well as preferentially phosphorylates the substrate tyrosine Y1068 but not Y1173. We predict that these molecular level changes result in preferential activation of the Akt signaling pathway in comparison to the Erk signaling pathway for cells with normal EGFR expression. For cells with EGFR over expression, the mutant over activates both Erk and Akt pathways, in comparison to wildtype. These results are consistent with qualitative experimental measurements reported in the literature. We discuss these consequences in light of how the network topology and signaling characteristics of altered (mutant) cell lines are shaped differently in relationship to native cell lines.

Identifying the Oscillatory Mechanism of the Glucose Oxidase-Catalase Coupled Enzyme System.

PubMed

Muzika, František; Jurašek, Radovan; Schreiberová, Lenka; Radojković, Vuk; Schreiber, Igor

2017-10-12

We provide experimental evidence of periodic and aperiodic oscillations in an enzymatic system of glucose oxidase-catalase in a continuous-flow stirred reactor coupled by a membrane with a continuous-flow reservoir supplied with hydrogen peroxide. To describe such dynamics, we formulate a detailed mechanism based on partial results in the literature. Finally, we introduce a novel method for estimation of unknown kinetic parameters. The method is based on matching experimental data at an oscillatory instability with stoichiometric constraints of the mechanism formulated by applying the stability theory of reaction networks. This approach has been used to estimate rate coefficients in the catalase part of the mechanism. Remarkably, model simulations show good agreement with the observed oscillatory dynamics, including apparently chaotic intermittent behavior. Our method can be applied to any reaction system with an experimentally observable dynamical instability.

Breathing dynamics based parameter sensitivity analysis of hetero-polymeric DNA

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

Talukder, Srijeeta; Sen, Shrabani; Chaudhury, Pinaki, E-mail: pinakc@rediffmail.com

We study the parameter sensitivity of hetero-polymeric DNA within the purview of DNA breathing dynamics. The degree of correlation between the mean bubble size and the model parameters is estimated for this purpose for three different DNA sequences. The analysis leads us to a better understanding of the sequence dependent nature of the breathing dynamics of hetero-polymeric DNA. Out of the 14 model parameters for DNA stability in the statistical Poland-Scheraga approach, the hydrogen bond interaction ε{sub hb}(AT) for an AT base pair and the ring factor ξ turn out to be the most sensitive parameters. In addition, the stackingmore » interaction ε{sub st}(TA-TA) for an TA-TA nearest neighbor pair of base-pairs is found to be the most sensitive one among all stacking interactions. Moreover, we also establish that the nature of stacking interaction has a deciding effect on the DNA breathing dynamics, not the number of times a particular stacking interaction appears in a sequence. We show that the sensitivity analysis can be used as an effective measure to guide a stochastic optimization technique to find the kinetic rate constants related to the dynamics as opposed to the case where the rate constants are measured using the conventional unbiased way of optimization.« less

Modeling bubble dynamics and radical kinetics in ultrasound induced microalgal cell disruption.

PubMed

Wang, Meng; Yuan, Wenqiao

2016-01-01

Microalgal cell disruption induced by acoustic cavitation was simulated through solving the bubble dynamics in an acoustical field and their radial kinetics (chemical kinetics of radical species) occurring in the bubble during its oscillation, as well as calculating the bubble wall pressure at the collapse point. Modeling results indicated that increasing ultrasonic intensity led to a substantial increase in the number of bubbles formed during acoustic cavitation, however, the pressure generated when the bubbles collapsed decreased. Therefore, cumulative collapse pressure (CCP) of bubbles was used to quantify acoustic disruption of a freshwater alga, Scenedesmus dimorphus, and a marine alga, Nannochloropsis oculata and compare with experimental results. The strong correlations between CCP and the intracellular lipid fluorescence density, chlorophyll-a fluorescence density, and cell particle/debris concentration were found, which suggests that the developed models could accurately predict acoustic cell disruption, and can be utilized in the scale up and optimization of the process. Copyright © 2015 Elsevier B.V. All rights reserved.

Algorithmic developments of the kinetic activation-relaxation technique: Accessing long-time kinetics of larger and more complex systems

NASA Astrophysics Data System (ADS)

Trochet, Mickaël; Sauvé-Lacoursière, Alecsandre; Mousseau, Normand

2017-10-01

In spite of the considerable computer speed increase of the last decades, long-time atomic simulations remain a challenge and most molecular dynamical simulations are limited to 1 μ s at the very best in condensed matter and materials science. There is a need, therefore, for accelerated methods that can bridge the gap between the full dynamical description of molecular dynamics and experimentally relevant time scales. This is the goal of the kinetic Activation-Relaxation Technique (k-ART), an off-lattice kinetic Monte-Carlo method with on-the-fly catalog building capabilities based on the topological tool NAUTY and the open-ended search method Activation-Relaxation Technique (ART nouveau) that has been applied with success to the study of long-time kinetics of complex materials, including grain boundaries, alloys, and amorphous materials. We present a number of recent algorithmic additions, including the use of local force calculation, two-level parallelization, improved topological description, and biased sampling and show how they perform on two applications linked to defect diffusion and relaxation after ion bombardement in Si.

Local dynamic subgrid-scale models in channel flow

NASA Technical Reports Server (NTRS)

Cabot, William H.

1994-01-01

The dynamic subgrid-scale (SGS) model has given good results in the large-eddy simulation (LES) of homogeneous isotropic or shear flow, and in the LES of channel flow, using averaging in two or three homogeneous directions (the DA model). In order to simulate flows in general, complex geometries (with few or no homogeneous directions), the dynamic SGS model needs to be applied at a local level in a numerically stable way. Channel flow, which is inhomogeneous and wall-bounded flow in only one direction, provides a good initial test for local SGS models. Tests of the dynamic localization model were performed previously in channel flow using a pseudospectral code and good results were obtained. Numerical instability due to persistently negative eddy viscosity was avoided by either constraining the eddy viscosity to be positive or by limiting the time that eddy viscosities could remain negative by co-evolving the SGS kinetic energy (the DLk model). The DLk model, however, was too expensive to run in the pseudospectral code due to a large near-wall term in the auxiliary SGS kinetic energy (k) equation. One objective was then to implement the DLk model in a second-order central finite difference channel code, in which the auxiliary k equation could be integrated implicitly in time at great reduction in cost, and to assess its performance in comparison with the plane-averaged dynamic model or with no model at all, and with direct numerical simulation (DNS) and/or experimental data. Other local dynamic SGS models have been proposed recently, e.g., constrained dynamic models with random backscatter, and with eddy viscosity terms that are averaged in time over material path lines rather than in space. Another objective was to incorporate and test these models in channel flow.

Cluster dynamics and cluster size distributions in systems of self-propelled particles

NASA Astrophysics Data System (ADS)

Peruani, F.; Schimansky-Geier, L.; Bär, M.

2010-12-01

Systems of self-propelled particles (SPP) interacting by a velocity alignment mechanism in the presence of noise exhibit rich clustering dynamics. Often, clusters are responsible for the distribution of (local) information in these systems. Here, we investigate the properties of individual clusters in SPP systems, in particular the asymmetric spreading behavior of clusters with respect to their direction of motion. In addition, we formulate a Smoluchowski-type kinetic model to describe the evolution of the cluster size distribution (CSD). This model predicts the emergence of steady-state CSDs in SPP systems. We test our theoretical predictions in simulations of SPP with nematic interactions and find that our simple kinetic model reproduces qualitatively the transition to aggregation observed in simulations.

Continuous time Boolean modeling for biological signaling: application of Gillespie algorithm.

PubMed

Stoll, Gautier; Viara, Eric; Barillot, Emmanuel; Calzone, Laurence

2012-08-29

Mathematical modeling is used as a Systems Biology tool to answer biological questions, and more precisely, to validate a network that describes biological observations and predict the effect of perturbations. This article presents an algorithm for modeling biological networks in a discrete framework with continuous time. There exist two major types of mathematical modeling approaches: (1) quantitative modeling, representing various chemical species concentrations by real numbers, mainly based on differential equations and chemical kinetics formalism; (2) and qualitative modeling, representing chemical species concentrations or activities by a finite set of discrete values. Both approaches answer particular (and often different) biological questions. Qualitative modeling approach permits a simple and less detailed description of the biological systems, efficiently describes stable state identification but remains inconvenient in describing the transient kinetics leading to these states. In this context, time is represented by discrete steps. Quantitative modeling, on the other hand, can describe more accurately the dynamical behavior of biological processes as it follows the evolution of concentration or activities of chemical species as a function of time, but requires an important amount of information on the parameters difficult to find in the literature. Here, we propose a modeling framework based on a qualitative approach that is intrinsically continuous in time. The algorithm presented in this article fills the gap between qualitative and quantitative modeling. It is based on continuous time Markov process applied on a Boolean state space. In order to describe the temporal evolution of the biological process we wish to model, we explicitly specify the transition rates for each node. For that purpose, we built a language that can be seen as a generalization of Boolean equations. Mathematically, this approach can be translated in a set of ordinary differential equations on probability distributions. We developed a C++ software, MaBoSS, that is able to simulate such a system by applying Kinetic Monte-Carlo (or Gillespie algorithm) on the Boolean state space. This software, parallelized and optimized, computes the temporal evolution of probability distributions and estimates stationary distributions. Applications of the Boolean Kinetic Monte-Carlo are demonstrated for three qualitative models: a toy model, a published model of p53/Mdm2 interaction and a published model of the mammalian cell cycle. Our approach allows to describe kinetic phenomena which were difficult to handle in the original models. In particular, transient effects are represented by time dependent probability distributions, interpretable in terms of cell populations.

Flow-Induced New Channels of Energy Exchange in Multi-Scale Plasma Dynamics - Revisiting Perturbative Hybrid Kinetic-MHD Theory.

PubMed

Shiraishi, Junya; Miyato, Naoaki; Matsunaga, Go

2016-05-10

It is found that new channels of energy exchange between macro- and microscopic dynamics exist in plasmas. They are induced by macroscopic plasma flow. This finding is based on the kinetic-magnetohydrodynamic (MHD) theory, which analyses interaction between macroscopic (MHD-scale) motion and microscopic (particle-scale) dynamics. The kinetic-MHD theory is extended to include effects of macroscopic plasma flow self-consistently. The extension is realised by generalising an energy exchange term due to wave-particle resonance, denoted by δ WK. The first extension is generalisation of the particle's Lagrangian, and the second one stems from modification to the particle distribution function due to flow. These extensions lead to a generalised expression of δ WK, which affects the MHD stability of plasmas.

Dynamic modeling of Listeria monocytogenes growth in pasteurized vanilla cream after postprocessing contamination.

PubMed

Panagou, Efstathios Z; Nychas, George-John E

2008-09-01

A product-specific model was developed and validated under dynamic temperature conditions for predicting the growth of Listeria monocytogenes in pasteurized vanilla cream, a traditional milk-based product. Model performance was also compared with Growth Predictor and Sym'Previus predictive microbiology software packages. Commercially prepared vanilla cream samples were artificially inoculated with a five-strain cocktail of L. monocytogenes, with an initial concentration of 102 CFU g(-1), and stored at 3, 5, 10, and 15 degrees C for 36 days. The growth kinetic parameters at each temperature were determined by the primary model of Baranyi and Roberts. The maximum specific growth rate (mu(max)) was further modeled as a function of temperature by means of a square root-type model. The performance of the model in predicting the growth of the pathogen under dynamic temperature conditions was based on two different temperature scenarios with periodic changes from 4 to 15 degrees C. Growth prediction for dynamic temperature profiles was based on the square root model and the differential equations of the Baranyi and Roberts model, which were numerically integrated with respect to time. Model performance was based on the bias factor (B(f)), the accuracy factor (A(f)), the goodness-of-fit index (GoF), and the percent relative errors between observed and predicted growth. The product-specific model developed in the present study accurately predicted the growth of L. monocytogenes under dynamic temperature conditions. The average values for the performance indices were 1.038, 1.068, and 0.397 for B(f), A(f), and GoF, respectively for both temperature scenarios assayed. Predictions from Growth Predictor and Sym'Previus overestimated pathogen growth. The average values of B(f), A(f), and GoF were 1.173, 1.174, 1.162, and 0.956, 1.115, 0.713 for [corrected] Growth Predictor and Sym'Previus, respectively.

Emergence of dynamic cooperativity in the stochastic kinetics of fluctuating enzymes

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

Kumar, Ashutosh; Chatterjee, Sambarta; Nandi, Mintu

Dynamic co-operativity in monomeric enzymes is characterized in terms of a non-Michaelis-Menten kinetic behaviour. The latter is believed to be associated with mechanisms that include multiple reaction pathways due to enzymatic conformational fluctuations. Recent advances in single-molecule fluorescence spectroscopy have provided new fundamental insights on the possible mechanisms underlying reactions catalyzed by fluctuating enzymes. Here, we present a bottom-up approach to understand enzyme turnover kinetics at physiologically relevant mesoscopic concentrations informed by mechanisms extracted from single-molecule stochastic trajectories. The stochastic approach, presented here, shows the emergence of dynamic co-operativity in terms of a slowing down of the Michaelis-Menten (MM) kineticsmore » resulting in negative co-operativity. For fewer enzymes, dynamic co-operativity emerges due to the combined effects of enzymatic conformational fluctuations and molecular discreteness. The increase in the number of enzymes, however, suppresses the effect of enzymatic conformational fluctuations such that dynamic co-operativity emerges solely due to the discrete changes in the number of reacting species. These results confirm that the turnover kinetics of fluctuating enzyme based on the parallel-pathway MM mechanism switches over to the single-pathway MM mechanism with the increase in the number of enzymes. For large enzyme numbers, convergence to the exact MM equation occurs in the limit of very high substrate concentration as the stochastic kinetics approaches the deterministic behaviour.« less

Dynamic dual-energy chest radiography: a potential tool for lung tissue motion monitoring and kinetic study

PubMed Central

Xu, Tong; Ducote, Justin L.; Wong, Jerry T.; Molloi, Sabee

2011-01-01

Dual-energy chest radiography has the potential to provide better diagnosis of lung disease by removing the bone signal from the image. Dynamic dual-energy radiography is now possible with the introduction of digital flat panel detectors. The purpose of this study is to evaluate the feasibility of using dynamic dual-energy chest radiography for functional lung imaging and tumor motion assessment. The dual energy system used in this study can acquire up to 15 frame of dual-energy images per second. A swine animal model was mechanically ventilated and imaged using the dual-energy system. Sequences of soft-tissue images were obtained using dual-energy subtraction. Time subtracted soft-tissue images were shown to be able to provide information on regional ventilation. Motion tracking of a lung anatomic feature (a branch of pulmonary artery) was performed based on an image cross-correlation algorithm. The tracking precision was found to be better than 1 mm. An adaptive correlation model was established between the above tracked motion and an external surrogate signal (temperature within the tracheal tube). This model is used to predict lung feature motion using the continuous surrogate signal and low frame rate dual-energy images (0.1 to 3.0 frames /sec). The average RMS error of the prediction was (1.1 ± 0.3) mm. The dynamic dual-energy was shown to be potentially useful for lung functional imaging such as regional ventilation and kinetic studies. It can also be used for lung tumor motion assessment and prediction during radiation therapy. PMID:21285477

Dynamic dual-energy chest radiography: a potential tool for lung tissue motion monitoring and kinetic study.

PubMed

Xu, Tong; Ducote, Justin L; Wong, Jerry T; Molloi, Sabee

2011-02-21

Dual-energy chest radiography has the potential to provide better diagnosis of lung disease by removing the bone signal from the image. Dynamic dual-energy radiography is now possible with the introduction of digital flat-panel detectors. The purpose of this study is to evaluate the feasibility of using dynamic dual-energy chest radiography for functional lung imaging and tumor motion assessment. The dual-energy system used in this study can acquire up to 15 frames of dual-energy images per second. A swine animal model was mechanically ventilated and imaged using the dual-energy system. Sequences of soft-tissue images were obtained using dual-energy subtraction. Time subtracted soft-tissue images were shown to be able to provide information on regional ventilation. Motion tracking of a lung anatomic feature (a branch of pulmonary artery) was performed based on an image cross-correlation algorithm. The tracking precision was found to be better than 1 mm. An adaptive correlation model was established between the above tracked motion and an external surrogate signal (temperature within the tracheal tube). This model is used to predict lung feature motion using the continuous surrogate signal and low frame rate dual-energy images (0.1-3.0 frames per second). The average RMS error of the prediction was (1.1 ± 0.3) mm. The dynamic dual energy was shown to be potentially useful for lung functional imaging such as regional ventilation and kinetic studies. It can also be used for lung tumor motion assessment and prediction during radiation therapy.

In Situ μGISAXS: II. Thaumatin Crystal Growth Kinetic

PubMed Central

Gebhardt, Ronald; Pechkova, Eugenia; Riekel, Christian; Nicolini, Claudio

2010-01-01

The formation of thaumatin crystals by Langmuir-Blodgett (LB) film nanotemplates was studied by the hanging-drop technique in a flow-through cell by synchrotron radiation micrograzing-incidence small-angle x-ray scattering. The kinetics of crystallization was measured directly on the interface of the LB film crystallization nanotemplate. The evolution of the micrograzing-incidence small-angle x-ray scattering patterns suggests that the increase in intensity in the Yoneda region is due to protein incorporation into the LB film. The intensity variation suggests several steps, which were modeled by system dynamics based on first-order differential equations. The kinetic data can be described by two processes that take place on the LB film, a first, fast, process, attributed to the crystal growth and its detachment from the LB film, and a second, slower process, attributed to an unordered association and conversion of protein on the LB film. PMID:20713011

Significance of DNA bond strength in programmable nanoparticle thermodynamics and dynamics.

PubMed

Yu, Qiuyan; Hu, Jinglei; Hu, Yi; Wang, Rong

2018-04-04

Assembly of nanoparticles (NPs) coated with complementary DNA strands leads to novel crystals with nanosized basic units rather than classic atoms, ions or molecules. The assembly process is mediated by hybridization of DNA via specific base pairing interaction, and is kinetically linked to the disassociation of DNA duplexes. DNA-level physiochemical quantities, both thermodynamic and kinetic, are key to understanding this process and essential for the design of DNA-NP crystals. The melting transition properties are helpful to judge the thermostability and sensitivity of relative DNA probes or other applications. Three different cases are investigated by changing the linker length and the spacer length on which the melting properties depend using the molecular dynamics method. Melting temperature is determined by sigmoidal melting curves based on hybridization percentage versus temperature and the Lindemann melting rule simultaneously. We provide a computational strategy based on a coarse-grained model to estimate the hybridization enthalpy, entropy and free energy from percentages of hybridizations which are readily accessible in experiments. Importantly, the lifetime of DNA bond dehybridization based on temperature and the activation energy depending on DNA bond strength are also calculated. The simulation results are in good agreement with the theoretical analysis and the present experimental data. Our study provides a good strategy to predict the melting temperature which is important for the DNA-directed nanoparticle system, and bridges the dynamics and thermodynamics of DNA-directed nanoparticle systems by estimating the equilibrium constant from the hybridization of DNA bonds quantitatively.

Development of a Model for Dynamic Recrystallization Consistent with the Second Derivative Criterion.

PubMed

Imran, Muhammad; Kühbach, Markus; Roters, Franz; Bambach, Markus

2017-11-02

Dynamic recrystallization (DRX) processes are widely used in industrial hot working operations, not only to keep the forming forces low but also to control the microstructure and final properties of the workpiece. According to the second derivative criterion (SDC) by Poliak and Jonas, the onset of DRX can be detected from an inflection point in the strain-hardening rate as a function of flow stress. Various models are available that can predict the evolution of flow stress from incipient plastic flow up to steady-state deformation in the presence of DRX. Some of these models have been implemented into finite element codes and are widely used for the design of metal forming processes, but their consistency with the SDC has not been investigated. This work identifies three sources of inconsistencies that models for DRX may exhibit. For a consistent modeling of the DRX kinetics, a new strain-hardening model for the hardening stages III to IV is proposed and combined with consistent recrystallization kinetics. The model is devised in the Kocks-Mecking space based on characteristic transition in the strain-hardening rate. A linear variation of the transition and inflection points is observed for alloy 800H at all tested temperatures and strain rates. The comparison of experimental and model results shows that the model is able to follow the course of the strain-hardening rate very precisely, such that highly accurate flow stress predictions are obtained.

Development of a Model for Dynamic Recrystallization Consistent with the Second Derivative Criterion

PubMed Central

Imran, Muhammad; Kühbach, Markus; Roters, Franz; Bambach, Markus

2017-01-01

Dynamic recrystallization (DRX) processes are widely used in industrial hot working operations, not only to keep the forming forces low but also to control the microstructure and final properties of the workpiece. According to the second derivative criterion (SDC) by Poliak and Jonas, the onset of DRX can be detected from an inflection point in the strain-hardening rate as a function of flow stress. Various models are available that can predict the evolution of flow stress from incipient plastic flow up to steady-state deformation in the presence of DRX. Some of these models have been implemented into finite element codes and are widely used for the design of metal forming processes, but their consistency with the SDC has not been investigated. This work identifies three sources of inconsistencies that models for DRX may exhibit. For a consistent modeling of the DRX kinetics, a new strain-hardening model for the hardening stages III to IV is proposed and combined with consistent recrystallization kinetics. The model is devised in the Kocks-Mecking space based on characteristic transition in the strain-hardening rate. A linear variation of the transition and inflection points is observed for alloy 800H at all tested temperatures and strain rates. The comparison of experimental and model results shows that the model is able to follow the course of the strain-hardening rate very precisely, such that highly accurate flow stress predictions are obtained. PMID:29099068

A mathematical model for foreign body reactions in 2D.

PubMed

Su, Jianzhong; Gonzales, Humberto Perez; Todorov, Michail; Kojouharov, Hristo; Tang, Liping

2011-02-01

The foreign body reactions are commonly referred to the network of immune and inflammatory reactions of human or animals to foreign objects placed in tissues. They are basic biological processes, and are also highly relevant to bioengineering applications in implants, as fibrotic tissue formations surrounding medical implants have been found to substantially reduce the effectiveness of devices. Despite of intensive research on determining the mechanisms governing such complex responses, few mechanistic mathematical models have been developed to study such foreign body reactions. This study focuses on a kinetics-based predictive tool in order to analyze outcomes of multiple interactive complex reactions of various cells/proteins and biochemical processes and to understand transient behavior during the entire period (up to several months). A computational model in two spatial dimensions is constructed to investigate the time dynamics as well as spatial variation of foreign body reaction kinetics. The simulation results have been consistent with experimental data and the model can facilitate quantitative insights for study of foreign body reaction process in general.

Experimental characterisation and modelling of deformation- induced microstructure in an A6061 aluminium alloy

NASA Astrophysics Data System (ADS)

Kreyca, J. F.; Falahati, A.; Kozeschnik, E.

2016-03-01

For industry, the mechanical properties of a material in form of flow curves are essential input data for finite element simulations. Current practice is to obtain flow curves experimentally and to apply fitting procedures to obtain constitutive equations that describe the material response to external loading as a function of temperature and strain rate. Unfortunately, the experimental procedure for characterizing flow curves is complex and expensive, which is why the prediction of flow-curves by computer modelling becomes increasingly important. In the present work, we introduce a state parameter based model that is capable of predicting the flow curves of an A6061 aluminium alloy in different heat-treatment conditions. The model is implemented in the thermo-kinetic software package MatCalc and takes into account precipitation kinetics, subgrain formation, dynamic recovery by spontaneous annihilation and dislocation climb. To validate the simulation results, a series of compression tests is performed on the thermo-mechanical simulator Gleeble 1500.

Mean Field Analysis of Large-Scale Interacting Populations of Stochastic Conductance-Based Spiking Neurons Using the Klimontovich Method

NASA Astrophysics Data System (ADS)

Gandolfo, Daniel; Rodriguez, Roger; Tuckwell, Henry C.

2017-03-01

We investigate the dynamics of large-scale interacting neural populations, composed of conductance based, spiking model neurons with modifiable synaptic connection strengths, which are possibly also subjected to external noisy currents. The network dynamics is controlled by a set of neural population probability distributions (PPD) which are constructed along the same lines as in the Klimontovich approach to the kinetic theory of plasmas. An exact non-closed, nonlinear, system of integro-partial differential equations is derived for the PPDs. As is customary, a closing procedure leads to a mean field limit. The equations we have obtained are of the same type as those which have been recently derived using rigorous techniques of probability theory. The numerical solutions of these so called McKean-Vlasov-Fokker-Planck equations, which are only valid in the limit of infinite size networks, actually shows that the statistical measures as obtained from PPDs are in good agreement with those obtained through direct integration of the stochastic dynamical system for large but finite size networks. Although numerical solutions have been obtained for networks of Fitzhugh-Nagumo model neurons, which are often used to approximate Hodgkin-Huxley model neurons, the theory can be readily applied to networks of general conductance-based model neurons of arbitrary dimension.

Modelling non-equilibrium secondary organic aerosol formation and evaporation with the aerosol dynamics, gas- and particle-phase chemistry kinetic multilayer model ADCHAM

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

Roldin, P.; Eriksson, A. C.; Nordin, E. Z.

2014-08-11

We have developed the novel Aerosol Dynamics, gas- and particle- phase chemistry model for laboratory CHAMber studies (ADCHAM). The model combines the detailed gas phase Master Chemical Mechanism version 3.2, an aerosol dynamics and particle phase chemistry module (which considers acid catalysed oligomerization, heterogeneous oxidation reactions in the particle phase and non-ideal interactions between organic compounds, water and inorganic ions) and a kinetic multilayer module for diffusion limited transport of compounds between the gas phase, particle surface and particle bulk phase. In this article we describe and use ADCHAM to study: 1) the mass transfer limited uptake of ammonia (NH3)more » and formation of organic salts between ammonium (NH4+) and carboxylic acids (RCOOH), 2) the slow and almost particle size independent evaporation of α-pinene secondary organic aerosol (SOA) particles, and 3) the influence of chamber wall effects on the observed SOA formation in smog chambers.« less

An Integrative Model for Phytochrome B Mediated Photomorphogenesis: From Protein Dynamics to Physiology

PubMed Central

Kircher, Stefan; Kirchenbauer, Daniel; Timmer, Jens; Nagy, Ferenc; Schäfer, Eberhard; Fleck, Christian

2010-01-01

Background Plants have evolved various sophisticated mechanisms to respond and adapt to changes of abiotic factors in their natural environment. Light is one of the most important abiotic environmental factors and it regulates plant growth and development throughout their entire life cycle. To monitor the intensity and spectral composition of the ambient light environment, plants have evolved multiple photoreceptors, including the red/far-red light-sensing phytochromes. Methodology/Principal Findings We have developed an integrative mathematical model that describes how phytochrome B (phyB), an essential receptor in Arabidopsis thaliana, controls growth. Our model is based on a multiscale approach and connects the mesoscopic intracellular phyB protein dynamics to the macroscopic growth phenotype. To establish reliable and relevant parameters for the model phyB regulated growth we measured: accumulation and degradation, dark reversion kinetics and the dynamic behavior of different nuclear phyB pools using in vivo spectroscopy, western blotting and Fluorescence Recovery After Photobleaching (FRAP) technique, respectively. Conclusions/Significance The newly developed model predicts that the phyB-containing nuclear bodies (NBs) (i) serve as storage sites for phyB and (ii) control prolonged dark reversion kinetics as well as partial reversibility of phyB Pfr in extended darkness. The predictive power of this mathematical model is further validated by the fact that we are able to formalize a basic photobiological observation, namely that in light-grown seedlings hypocotyl length depends on the total amount of phyB. In addition, we demonstrate that our theoretical predictions are in excellent agreement with quantitative data concerning phyB levels and the corresponding hypocotyl lengths. Hence, we conclude that the integrative model suggested in this study captures the main features of phyB-mediated photomorphogenesis in Arabidopsis. PMID:20502669

Insilico study of the A(2A)R-D (2)R kinetics and interfacial contact surface for heteromerization.

PubMed

Prakash, Amresh; Luthra, Pratibha Mehta

2012-10-01

G-protein-coupled receptors (GPCRs) are cell surface receptors. The dynamic property of receptor-receptor interactions in GPCRs modulates the kinetics of G-protein signaling and stability. In the present work, the structural and dynamic study of A(2A)R-D(2)R interactions was carried to acquire the understanding of the A(2A)R-D(2)R receptor activation and deactivation process, facilitating the design of novel drugs and therapeutic target for Parkinson's disease. The structure-based features (Alpha, Beta, SurfAlpha, and SurfBeta; GapIndex, Leakiness and Gap Volume) and slow mode model (ENM) facilitated the prediction of kinetics (K (off), K (on), and K (d)) of A(2A)R-D(2)R interactions. The results demonstrated the correlation coefficient 0.294 for K (d) and K (on) and the correlation coefficient 0.635 for K (d) and K (off), and indicated stable interfacial contacts in the formation of heterodimer. The coulombic interaction involving the C-terminal tails of the A(2A)R and intracellular loops (ICLs) of D(2)R led to the formation of interfacial contacts between A(2A)R-D(2)R. The properties of structural dynamics, ENM and KFC server-based hot-spot analysis illustrated the stoichiometry of A(2A)R-D(2)R contact interfaces as dimer. The propensity of amino acid residues involved in A(2A)R-D(2)R interaction revealed the presence of positively (R, H and K) and negatively (E and D) charged structural motif of TMs and ICL3 of A(2A)R and D(2)R at interface of dimer contact. Essentially, in silico structural and dynamic study of A(2A)R-D(2)R interactions will provide the basic understanding of the A(2A)R-D(2)R interfacial contact surface for activation and deactivation processes, and could be used as constructive model to recognize the protein-protein interactions in receptor assimilations.

Dynamic FDG-PET Imaging to Differentiate Malignancies from Inflammation in Subcutaneous and In Situ Mouse Model for Non-Small Cell Lung Carcinoma (NSCLC).

PubMed

Yang, Zhen; Zan, Yunlong; Zheng, Xiujuan; Hai, Wangxi; Chen, Kewei; Huang, Qiu; Xu, Yuhong; Peng, Jinliang

2015-01-01

[18F]fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) has been widely used in oncologic procedures such as tumor diagnosis and staging. However, false-positive rates have been high, unacceptable and mainly caused by inflammatory lesions. Misinterpretations take place especially when non-subcutaneous inflammations appear at the tumor site, for instance in the lung. The aim of the current study is to evaluate the use of dynamic PET imaging procedure to differentiate in situ and subcutaneous non-small cell lung carcinoma (NSCLC) from inflammation, and estimate the kinetics of inflammations in various locations. Dynamic FDG-PET was performed on 33 female mice inoculated with tumor and/or inflammation subcutaneously or inside the lung. Standardized Uptake Values (SUVs) from static imaging (SUVmax) as well as values of influx rate constant (Ki) of compartmental modeling from dynamic imaging were obtained. Static and kinetic data from different lesions (tumor and inflammations) or different locations (subcutaneous, in situ and spontaneous group) were compared. Values of SUVmax showed significant difference in subcutaneous tumor and inflammation (p<0.01), and in inflammations from different locations (p<0.005). However, SUVmax showed no statistical difference between in situ tumor and inflammation (p = 1.0) and among tumors from different locations (subcutaneous and in situ, p = 0.91). Values of Ki calculated from compartmental modeling showed significant difference between tumor and inflammation both subcutaneously (p<0.005) and orthotopically (p<0.01). Ki showed also location specific values for inflammations (subcutaneous, in situ and spontaneous, p<0.015). However, Ki of tumors from different locations (subcutaneous and in situ) showed no significant difference (p = 0.46). In contrast to static PET based SUVmax, both subcutaneous and in situ inflammations and malignancies can be differentiated via dynamic FDG-PET based Ki. Moreover, Values of influx rate constant Ki from compartmental modeling can offer an assessment for inflammations at different locations of the body, which also implies further validation is necessary before the replacement of in situ inflammation with its subcutaneous counterpart in animal experiments.

The Einstein-Vlasov System/Kinetic Theory.

PubMed

Andréasson, Håkan

2005-01-01

The main purpose of this article is to provide a guide to theorems on global properties of solutions to the Einstein-Vlasov system. This system couples Einstein's equations to a kinetic matter model. Kinetic theory has been an important field of research during several decades in which the main focus has been on nonrelativistic and special relativistic physics, i.e. to model the dynamics of neutral gases, plasmas, and Newtonian self-gravitating systems. In 1990, Rendall and Rein initiated a mathematical study of the Einstein-Vlasov system. Since then many theorems on global properties of solutions to this system have been established. The Vlasov equation describes matter phenomenologically, and it should be stressed that most of the theorems presented in this article are not presently known for other such matter models (i.e. fluid models). This paper gives introductions to kinetic theory in non-curved spacetimes and then the Einstein-Vlasov system is introduced. We believe that a good understanding of kinetic theory in non-curved spacetimes is fundamental to good comprehension of kinetic theory in general relativity.

The Einstein-Vlasov System/Kinetic Theory.

PubMed

Andréasson, Håkan

2002-01-01

The main purpose of this article is to provide a guide to theorems on global properties of solutions to the Einstein-Vlasov system. This system couples Einstein's equations to a kinetic matter model. Kinetic theory has been an important field of research during several decades in which the main focus has been on nonrelativistic and special relativistic physics, i.e. to model the dynamics of neutral gases, plasmas, and Newtonian self-gravitating systems. In 1990, Rendall and Rein initiated a mathematical study of the Einstein-Vlasov system. Since then many theorems on global properties of solutions to this system have been established. The Vlasov equation describes matter phenomenologically, and it should be stressed that most of the theorems presented in this article are not presently known for other such matter models (i.e. fluid models). This paper gives introductions to kinetic theory in non-curved spacetimes and then the Einstein-Vlasov system is introduced. We believe that a good understanding of kinetic theory in non-curved spacetimes is fundamental to good comprehension of kinetic theory in general relativity.

Mutation-induced protein interaction kinetics changes affect apoptotic network dynamic properties and facilitate oncogenesis

PubMed Central

Zhao, Linjie; Sun, Tanlin; Pei, Jianfeng; Ouyang, Qi

2015-01-01

It has been a consensus in cancer research that cancer is a disease caused primarily by genomic alterations, especially somatic mutations. However, the mechanism of mutation-induced oncogenesis is not fully understood. Here, we used the mitochondrial apoptotic pathway as a case study and performed a systematic analysis of integrating pathway dynamics with protein interaction kinetics to quantitatively investigate the causal molecular mechanism of mutation-induced oncogenesis. A mathematical model of the regulatory network was constructed to establish the functional role of dynamic bifurcation in the apoptotic process. The oncogenic mutation enrichment of each of the protein functional domains involved was found strongly correlated with the parameter sensitivity of the bifurcation point. We further dissected the causal mechanism underlying this correlation by evaluating the mutational influence on protein interaction kinetics using molecular dynamics simulation. We analyzed 29 matched mutant–wild-type and 16 matched SNP—wild-type protein systems. We found that the binding kinetics changes reflected by the changes of free energy changes induced by protein interaction mutations, which induce variations in the sensitive parameters of the bifurcation point, were a major cause of apoptosis pathway dysfunction, and mutations involved in sensitive interaction domains show high oncogenic potential. Our analysis provided a molecular basis for connecting protein mutations, protein interaction kinetics, network dynamics properties, and physiological function of a regulatory network. These insights provide a framework for coupling mutation genotype to tumorigenesis phenotype and help elucidate the logic of cancer initiation. PMID:26170328

Antipersistent dynamics in kinetic models of wealth exchange

NASA Astrophysics Data System (ADS)

Goswami, Sanchari; Chatterjee, Arnab; Sen, Parongama

2011-11-01

We investigate the detailed dynamics of gains and losses made by agents in some kinetic models of wealth exchange. An earlier work suggested that a walk in an abstract gain-loss space can be conceived for the agents. For models in which agents do not save, or save with uniform saving propensity, the walk has diffusive behavior. For the case in which the saving propensity λ is distributed randomly (0≤λ<1), the resultant walk showed a ballistic nature (except at a particular value of λ*≈0.47). Here we consider several other features of the walk with random λ. While some macroscopic properties of this walk are comparable to a biased random walk, at microscopic level, there are gross differences. The difference turns out to be due to an antipersistent tendency toward making a gain (loss) immediately after making a loss (gain). This correlation is in fact present in kinetic models without saving or with uniform saving as well, such that the corresponding walks are not identical to ordinary random walks. In the distributed saving case, antipersistence occurs with a simultaneous overall bias.

Graph-based analysis of kinetics on multidimensional potential-energy surfaces.

PubMed

Okushima, T; Niiyama, T; Ikeda, K S; Shimizu, Y

2009-09-01

The aim of this paper is twofold: one is to give a detailed description of an alternative graph-based analysis method, which we call saddle connectivity graph, for analyzing the global topography and the dynamical properties of many-dimensional potential-energy landscapes and the other is to give examples of applications of this method in the analysis of the kinetics of realistic systems. A Dijkstra-type shortest path algorithm is proposed to extract dynamically dominant transition pathways by kinetically defining transition costs. The applicability of this approach is first confirmed by an illustrative example of a low-dimensional random potential. We then show that a coarse-graining procedure tailored for saddle connectivity graphs can be used to obtain the kinetic properties of 13- and 38-atom Lennard-Jones clusters. The coarse-graining method not only reduces the complexity of the graphs, but also, with iterative use, reveals a self-similar hierarchical structure in these clusters. We also propose that the self-similarity is common to many-atom Lennard-Jones clusters.

Continuous Time Random Walk and Migration-Proliferation Dichotomy of Brain Cancer

NASA Astrophysics Data System (ADS)

Iomin, A.

A theory of fractional kinetics of glial cancer cells is presented. A role of the migration-proliferation dichotomy in the fractional cancer cell dynamics in the outer-invasive zone is discussed and explained in the framework of a continuous time random walk. The main suggested model is based on a construction of a 3D comb model, where the migration-proliferation dichotomy becomes naturally apparent and the outer-invasive zone of glioma cancer is considered as a fractal composite with a fractal dimension Dfr < 3.

Chain Dynamics and Structure Property Relation in High Impact Strength Polycarbonate Plastic.

DTIC Science & Technology

1985-01-04

computerized for cases involving more than one kinetic process simultaneously contributing to line narrowing. The model introduces a distributional character...F. O’Gara (Research Assistant) Department of Chemitry , Graduate Student Clark University PhD Clark University June, 1984. 4. The following...on a tetrahedral lattice is compared with a a v ,del by Weber and Hel- fand (8), based on computer simulaticns cct pOlVethvlece type chafins. These two

Mass accommodation of water: bridging the gap between molecular dynamics simulations and kinetic condensation models.

PubMed

Julin, Jan; Shiraiwa, Manabu; Miles, Rachael E H; Reid, Jonathan P; Pöschl, Ulrich; Riipinen, Ilona

2013-01-17

The condensational growth of submicrometer aerosol particles to climate relevant sizes is sensitive to their ability to accommodate vapor molecules, which is described by the mass accommodation coefficient. However, the underlying processes are not yet fully understood. We have simulated the mass accommodation and evaporation processes of water using molecular dynamics, and the results are compared to the condensation equations derived from the kinetic gas theory to shed light on the compatibility of the two. Molecular dynamics simulations were performed for a planar TIP4P-Ew water surface at four temperatures in the range 268-300 K as well as two droplets, with radii of 1.92 and 4.14 nm at T = 273.15 K. The evaporation flux from molecular dynamics was found to be in good qualitative agreement with that predicted by the simple kinetic condensation equations. Water droplet growth was also modeled with the kinetic multilayer model KM-GAP of Shiraiwa et al. [Atmos. Chem. Phys. 2012, 12, 2777]. It was found that, due to the fast transport across the interface, the growth of a pure water droplet is controlled by gas phase diffusion. These facts indicate that the simple kinetic treatment is sufficient in describing pure water condensation and evaporation. The droplet size was found to have minimal effect on the value of the mass accommodation coefficient. The mass accommodation coefficient was found to be unity (within 0.004) for all studied surfaces, which is in agreement with previous simulation work. Additionally, the simulated evaporation fluxes imply that the evaporation coefficient is also unity. Comparing the evaporation rates of the mass accommodation and evaporation simulations indicated that the high collision flux, corresponding to high supersaturation, present in typical molecular dynamics mass accommodation simulations can under certain conditions lead to an increase in the evaporation rate. Consequently, in such situations the mass accommodation coefficient can be overestimated, but in the present cases the corrected values were still close to unity with the lowest value at ≈0.99.

Mass Accommodation of Water: Bridging the Gap Between Molecular Dynamics Simulations and Kinetic Condensation Models

PubMed Central

2012-01-01

The condensational growth of submicrometer aerosol particles to climate relevant sizes is sensitive to their ability to accommodate vapor molecules, which is described by the mass accommodation coefficient. However, the underlying processes are not yet fully understood. We have simulated the mass accommodation and evaporation processes of water using molecular dynamics, and the results are compared to the condensation equations derived from the kinetic gas theory to shed light on the compatibility of the two. Molecular dynamics simulations were performed for a planar TIP4P-Ew water surface at four temperatures in the range 268–300 K as well as two droplets, with radii of 1.92 and 4.14 nm at T = 273.15 K. The evaporation flux from molecular dynamics was found to be in good qualitative agreement with that predicted by the simple kinetic condensation equations. Water droplet growth was also modeled with the kinetic multilayer model KM-GAP of Shiraiwa et al. [Atmos. Chem. Phys.2012, 117, 2777]. It was found that, due to the fast transport across the interface, the growth of a pure water droplet is controlled by gas phase diffusion. These facts indicate that the simple kinetic treatment is sufficient in describing pure water condensation and evaporation. The droplet size was found to have minimal effect on the value of the mass accommodation coefficient. The mass accommodation coefficient was found to be unity (within 0.004) for all studied surfaces, which is in agreement with previous simulation work. Additionally, the simulated evaporation fluxes imply that the evaporation coefficient is also unity. Comparing the evaporation rates of the mass accommodation and evaporation simulations indicated that the high collision flux, corresponding to high supersaturation, present in typical molecular dynamics mass accommodation simulations can under certain conditions lead to an increase in the evaporation rate. Consequently, in such situations the mass accommodation coefficient can be overestimated, but in the present cases the corrected values were still close to unity with the lowest value at ≈0.99. PMID:23253100

Kinetic Monte Carlo simulations of nucleation and growth in electrodeposition.

PubMed

Guo, Lian; Radisic, Aleksandar; Searson, Peter C

2005-12-22

Nucleation and growth during bulk electrodeposition is studied using kinetic Monte Carlo (KMC) simulations. Ion transport in solution is modeled using Brownian dynamics, and the kinetics of nucleation and growth are dependent on the probabilities of metal-on-substrate and metal-on-metal deposition. Using this approach, we make no assumptions about the nucleation rate, island density, or island distribution. The influence of the attachment probabilities and concentration on the time-dependent island density and current transients is reported. Various models have been assessed by recovering the nucleation rate and island density from the current-time transients.

Learning Kinetic Monte Carlo Models of Condensed Phase High Temperature Chemistry from Molecular Dynamics

NASA Astrophysics Data System (ADS)

Yang, Qian; Sing-Long, Carlos; Chen, Enze; Reed, Evan

2017-06-01

Complex chemical processes, such as the decomposition of energetic materials and the chemistry of planetary interiors, are typically studied using large-scale molecular dynamics simulations that run for weeks on high performance parallel machines. These computations may involve thousands of atoms forming hundreds of molecular species and undergoing thousands of reactions. It is natural to wonder whether this wealth of data can be utilized to build more efficient, interpretable, and predictive models. In this talk, we will use techniques from statistical learning to develop a framework for constructing Kinetic Monte Carlo (KMC) models from molecular dynamics data. We will show that our KMC models can not only extrapolate the behavior of the chemical system by as much as an order of magnitude in time, but can also be used to study the dynamics of entirely different chemical trajectories with a high degree of fidelity. Then, we will discuss three different methods for reducing our learned KMC models, including a new and efficient data-driven algorithm using L1-regularization. We demonstrate our framework throughout on a system of high-temperature high-pressure liquid methane, thought to be a major component of gas giant planetary interiors.

The Einstein-Vlasov System/Kinetic Theory.

PubMed

Andréasson, Håkan

2011-01-01

The main purpose of this article is to provide a guide to theorems on global properties of solutions to the Einstein-Vlasov system. This system couples Einstein's equations to a kinetic matter model. Kinetic theory has been an important field of research during several decades in which the main focus has been on non-relativistic and special relativistic physics, i.e., to model the dynamics of neutral gases, plasmas, and Newtonian self-gravitating systems. In 1990, Rendall and Rein initiated a mathematical study of the Einstein-Vlasov system. Since then many theorems on global properties of solutions to this system have been established. This paper gives introductions to kinetic theory in non-curved spacetimes and then the Einstein-Vlasov system is introduced. We believe that a good understanding of kinetic theory in non-curved spacetimes is fundamental to a good comprehension of kinetic theory in general relativity.

Outcome regimes of binary raindrop collisions

NASA Astrophysics Data System (ADS)

Testik, Firat Y.

2009-11-01

This study delineates the physical conditions that are responsible for the occurrence of main outcome regimes (i.e., bounce, coalescence, and breakup) for binary drop collisions with a precipitation microphysics perspective. Physical considerations based on the collision kinetic energy and the surface energies of the colliding drops lead to the development of a theoretical regime diagram for the drop/raindrop collision outcomes in the We- p plane ( We — Weber number, p — raindrop diameter ratio). This theoretical regime diagram is supported by laboratory experimental observations of drop collisions using high-speed imaging. Results of this fundamental study bring in new insights into the quantitative understanding of drop dynamics, applications of which extend beyond precipitation microphysics. In particular, results of this drop collision study are expected to give impetus to the physics-based dynamic modeling of the drop size distributions that is essential for various typical modern engineering applications, including numerical modeling of evolution of raindrop size distribution in rain shaft.

VOXEL-LEVEL MAPPING OF TRACER KINETICS IN PET STUDIES: A STATISTICAL APPROACH EMPHASIZING TISSUE LIFE TABLES.

PubMed

O'Sullivan, Finbarr; Muzi, Mark; Mankoff, David A; Eary, Janet F; Spence, Alexander M; Krohn, Kenneth A

2014-06-01

Most radiotracers used in dynamic positron emission tomography (PET) scanning act in a linear time-invariant fashion so that the measured time-course data are a convolution between the time course of the tracer in the arterial supply and the local tissue impulse response, known as the tissue residue function. In statistical terms the residue is a life table for the transit time of injected radiotracer atoms. The residue provides a description of the tracer kinetic information measurable by a dynamic PET scan. Decomposition of the residue function allows separation of rapid vascular kinetics from slower blood-tissue exchanges and tissue retention. For voxel-level analysis, we propose that residues be modeled by mixtures of nonparametrically derived basis residues obtained by segmentation of the full data volume. Spatial and temporal aspects of diagnostics associated with voxel-level model fitting are emphasized. Illustrative examples, some involving cancer imaging studies, are presented. Data from cerebral PET scanning with 18 F fluoro-deoxyglucose (FDG) and 15 O water (H2O) in normal subjects is used to evaluate the approach. Cross-validation is used to make regional comparisons between residues estimated using adaptive mixture models with more conventional compartmental modeling techniques. Simulations studies are used to theoretically examine mean square error performance and to explore the benefit of voxel-level analysis when the primary interest is a statistical summary of regional kinetics. The work highlights the contribution that multivariate analysis tools and life-table concepts can make in the recovery of local metabolic information from dynamic PET studies, particularly ones in which the assumptions of compartmental-like models, with residues that are sums of exponentials, might not be certain.

Dynamic hysteresis behaviors in the kinetic Ising system on triangular lattice

NASA Astrophysics Data System (ADS)

Kantar, Ersin; Ertaş, Mehmet

2018-04-01

We studied dynamic hysteresis behaviors of the spin-1 Blume-Capel (BC) model in a triangular lattice by means of the effective-field theory (EFT) with correlations and using Glauber-type stochastic dynamics. The effects of the exchange interaction (J), crystal field (D), temperature (T) and oscillating frequency (w) on the hysteresis behaviors of the BC model in a triangular lattice are investigated in detail. Results are compared with some other dynamic studies and quantitatively good agreement is found.

Microsecond kinetics in model single- and double-stranded amylose polymers.

PubMed

Sattelle, Benedict M; Almond, Andrew

2014-05-07

Amylose, a component of starch with increasing biotechnological significance, is a linear glucose polysaccharide that self-organizes into single- and double-helical assemblies. Starch granule packing, gelation and inclusion-complex formation result from finely balanced macromolecular kinetics that have eluded precise experimental quantification. Here, graphics processing unit (GPU) accelerated multi-microsecond aqueous simulations are employed to explore conformational kinetics in model single- and double-stranded amylose. The all-atom dynamics concur with prior X-ray and NMR data while surprising and previously overlooked microsecond helix-coil, glycosidic linkage and pyranose ring exchange are hypothesized. In a dodecasaccharide, single-helical collapse was correlated with linkages and rings transitioning from their expected syn and (4)C1 chair conformers. The associated microsecond exchange rates were dependent on proximity to the termini and chain length (comparing hexa- and trisaccharides), while kinetic features of dodecasaccharide linkage and ring flexing are proposed to be a good model for polymers. Similar length double-helices were stable on microsecond timescales but the parallel configuration was sturdier than the antiparallel equivalent. In both, tertiary organization restricted local chain dynamics, implying that simulations of single amylose strands cannot be extrapolated to dimers. Unbiased multi-microsecond simulations of amylose are proposed as a valuable route to probing macromolecular kinetics in water, assessing the impact of chemical modifications on helical stability and accelerating the development of new biotechnologies.

Biodegradation kinetics of dissolved organic matter chromatographic fractions in an intermittent river

NASA Astrophysics Data System (ADS)

Catalán, N.; Casas-Ruiz, J. P.; von Schiller, D.; Proia, L.; Obrador, B.; Zwirnmann, E.; Marcé, R.

2017-01-01

Controls on the degradation of dissolved organic matter (DOM) are complex but key to understand the role of freshwaters in the carbon cycle. Both the origin and previous degradation history have been suggested to determine DOM reactivity, but it is still a major challenge to understand the links between DOM composition and biodegradation kinetics. An appropriate context to study these links are intermittent rivers, as summer drought naturally diversifies DOM sources and sinks. Here we investigated the biodegradation kinetics of DOM in the main aquatic environments present in a temporary river. During dark incubations we traced the dynamics of bulk DOM and its main chromatographic fractions defined using LC-OCD: high molecular weight substances (HMWS), low molecular weight substances (LMWS), and humic substances and building blocks. Bulk DOM decay patterns were successfully fitted to the reactivity continuum (RC) biodegradation model. The RC parameters depicted running waters as the sites presenting a more reactive DOM, and temporary pools, enriched in leaf litter, as the ones with slowest DOM decay. The decay patterns of each DOM fraction were consistent throughout sites. LMWS and HMWS decayed in all cases and could be modeled using the RC model. Notably, the dynamics of LMWS controlled the bulk DOM kinetics. We discuss the mechanistic basis for the chromatographic fractions' kinetics during biodegradation and the implications that preconditioning and summer drought can have for DOM biodegradation in intermittent rivers.

Analytical approach to impurity transport studies: Charge state dynamics in tokamak plasmas

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

Shurygin, V. A.

2006-08-15

Ionization and recombination of plasma impurities govern their charge state kinetics, which is imposed upon the dynamics of ions that implies a superposition of the appropriate probabilities and causes an impurity charge state dynamics. The latter is considered in terms of a vector field of conditional probabilities and presented by a vector charge state distribution function with coupled equations of the Kolmogorov type. Analytical solutions of a diffusion problem are derived with the basic spatial and temporal dimensionless parameters. Analysis shows that the empirical scaling D{sub A}{proportional_to}n{sub e}{sup -1} [K. Krieger, G. Fussmann, and the ASDEX Upgrade Team, Nucl. Fusionmore » 30, 2392 (1990)] can be explained by the ratio of the diffusive and kinetic terms, D{sub A}/(n{sub e}a{sup 2}), being used instead of diffusivity, D{sub A}. The derived time scales of charge state dynamics are given by a sum of the diffusive and kinetic times. Detailed simulations of charge state dynamics are performed for argon impurity and compared with the reference modeling.« less

Shortened acquisition protocols for the quantitative assessment of the 2-tissue-compartment model using dynamic PET/CT 18F-FDG studies.

PubMed

Strauss, Ludwig G; Pan, Leyun; Cheng, Caixia; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

2011-03-01

(18)F-FDG kinetics are quantified by a 2-tissue-compartment model. The routine use of dynamic PET is limited because of this modality's 1-h acquisition time. We evaluated shortened acquisition protocols up to 0-30 min regarding the accuracy for data analysis with the 2-tissue-compartment model. Full dynamic series for 0-60 min were analyzed using a 2-tissue-compartment model. The time-activity curves and the resulting parameters for the model were stored in a database. Shortened acquisition data were generated from the database using the following time intervals: 0-10, 0-16, 0-20, 0-25, and 0-30 min. Furthermore, the impact of adding a 60-min uptake value to the dynamic series was evaluated. The datasets were analyzed using dedicated software to predict the results of the full dynamic series. The software is based on a modified support vector machines (SVM) algorithm and predicts the compartment parameters of the full dynamic series. The SVM-based software provides user-independent results and was accurate at predicting the compartment parameters of the full dynamic series. If a squared correlation coefficient of 0.8 (corresponding to 80% explained variance of the data) was used as a limit, a shortened acquisition of 0-16 min was accurate at predicting the 60-min 2-tissue-compartment parameters. If a limit of 0.9 (90% explained variance) was used, a dynamic series of at least 0-20 min together with the 60-min uptake values is required. Shortened acquisition protocols can be used to predict the parameters of the 2-tissue-compartment model. Either a dynamic PET series of 0-16 min or a combination of a dynamic PET/CT series of 0-20 min and a 60-min uptake value is accurate for analysis with a 2-tissue-compartment model.

How EF-Tu can contribute to efficient proofreading of aa-tRNA by the ribosome

PubMed Central

Noel, Jeffrey K.; Whitford, Paul C.

2016-01-01

It has long been recognized that the thermodynamics of mRNA–tRNA base pairing is insufficient to explain the high fidelity and efficiency of aminoacyl-tRNA (aa-tRNA) selection by the ribosome. To rationalize this apparent inconsistency, Hopfield proposed that the ribosome may improve accuracy by utilizing a multi-step kinetic proofreading mechanism. While biochemical, structural and single-molecule studies have provided a detailed characterization of aa-tRNA selection, there is a limited understanding of how the physical–chemical properties of the ribosome enable proofreading. To this end, we probe the role of EF-Tu during aa-tRNA accommodation (the proofreading step) through the use of energy landscape principles, molecular dynamics simulations and kinetic models. We find that the steric composition of EF-Tu can reduce the free-energy barrier associated with the first step of accommodation: elbow accommodation. We interpret this effect within an extended kinetic model of accommodation and show how EF-Tu can contribute to efficient and accurate proofreading. PMID:27796304

Effects of Transition-Metal Mixing on Na Ordering and Kinetics in Layered P 2 Oxides

NASA Astrophysics Data System (ADS)

Zheng, Chen; Radhakrishnan, Balachandran; Chu, Iek-Heng; Wang, Zhenbin; Ong, Shyue Ping

2017-06-01

Layered P 2 oxides are promising cathode materials for rechargeable sodium-ion batteries. In this work, we systematically investigate the effects of transition-metal (TM) mixing on Na ordering and kinetics in the NaxCo1 -yMnyO2 model system using density-functional-theory (DFT) calculations. The DFT-predicted 0-K stability diagrams indicate that Co-Mn mixing reduces the energetic differences between Na orderings, which may account for the reduction of the number of phase transformations observed during the cycling of mixed-TM P 2 layered oxides compared to a single TM. Using ab initio molecular-dynamics simulations and nudged elastic-band calculations, we show that the TM composition at the Na(1) (face-sharing) site has a strong influence on the Na site energies, which in turn impacts the kinetics of Na diffusion towards the end of the charge. By employing a site-percolation model, we establish theoretical upper and lower bounds for TM concentrations based on their effect on Na(1) site energies, providing a framework to rationally tune mixed-TM compositions for optimal Na diffusion.

Parallel replica dynamics with a heterogeneous distribution of barriers: Application to n-hexadecane pyrolysis

NASA Astrophysics Data System (ADS)

Kum, Oyeon; Dickson, Brad M.; Stuart, Steven J.; Uberuaga, Blas P.; Voter, Arthur F.

2004-11-01

Parallel replica dynamics simulation methods appropriate for the simulation of chemical reactions in molecular systems with many conformational degrees of freedom have been developed and applied to study the microsecond-scale pyrolysis of n-hexadecane in the temperature range of 2100-2500 K. The algorithm uses a transition detection scheme that is based on molecular topology, rather than energetic basins. This algorithm allows efficient parallelization of small systems even when using more processors than particles (in contrast to more traditional parallelization algorithms), and even when there are frequent conformational transitions (in contrast to previous implementations of the parallel replica algorithm). The parallel efficiency for pyrolysis initiation reactions was over 90% on 61 processors for this 50-atom system. The parallel replica dynamics technique results in reaction probabilities that are statistically indistinguishable from those obtained from direct molecular dynamics, under conditions where both are feasible, but allows simulations at temperatures as much as 1000 K lower than direct molecular dynamics simulations. The rate of initiation displayed Arrhenius behavior over the entire temperature range, with an activation energy and frequency factor of Ea=79.7 kcal/mol and log A/s-1=14.8, respectively, in reasonable agreement with experiment and empirical kinetic models. Several interesting unimolecular reaction mechanisms were observed in simulations of the chain propagation reactions above 2000 K, which are not included in most coarse-grained kinetic models. More studies are needed in order to determine whether these mechanisms are experimentally relevant, or specific to the potential energy surface used.

Process Analytical Technology for Advanced Process Control in Biologics Manufacturing with the Aid of Macroscopic Kinetic Modeling.

PubMed

Kornecki, Martin; Strube, Jochen

2018-03-16

Productivity improvements of mammalian cell culture in the production of recombinant proteins have been made by optimizing cell lines, media, and process operation. This led to enhanced titers and process robustness without increasing the cost of the upstream processing (USP); however, a downstream bottleneck remains. In terms of process control improvement, the process analytical technology (PAT) initiative, initiated by the American Food and Drug Administration (FDA), aims to measure, analyze, monitor, and ultimately control all important attributes of a bioprocess. Especially, spectroscopic methods such as Raman or near-infrared spectroscopy enable one to meet these analytical requirements, preferably in-situ. In combination with chemometric techniques like partial least square (PLS) or principal component analysis (PCA), it is possible to generate soft sensors, which estimate process variables based on process and measurement models for the enhanced control of bioprocesses. Macroscopic kinetic models can be used to simulate cell metabolism. These models are able to enhance the process understanding by predicting the dynamic of cells during cultivation. In this article, in-situ turbidity (transmission, 880 nm) and ex-situ Raman spectroscopy (785 nm) measurements are combined with an offline macroscopic Monod kinetic model in order to predict substrate concentrations. Experimental data of Chinese hamster ovary cultivations in bioreactors show a sufficiently linear correlation (R² ≥ 0.97) between turbidity and total cell concentration. PLS regression of Raman spectra generates a prediction model, which was validated via offline viable cell concentration measurement (RMSE ≤ 13.82, R² ≥ 0.92). Based on these measurements, the macroscopic Monod model can be used to determine different process attributes, e.g., glucose concentration. In consequence, it is possible to approximately calculate (R² ≥ 0.96) glucose concentration based on online cell concentration measurements using turbidity or Raman spectroscopy. Future approaches will use these online substrate concentration measurements with turbidity and Raman measurements, in combination with the kinetic model, in order to control the bioprocess in terms of feeding strategies, by employing an open platform communication (OPC) network-either in fed-batch or perfusion mode, integrated into a continuous operation of upstream and downstream.

Process Analytical Technology for Advanced Process Control in Biologics Manufacturing with the Aid of Macroscopic Kinetic Modeling

PubMed Central

Kornecki, Martin; Strube, Jochen

2018-01-01

Productivity improvements of mammalian cell culture in the production of recombinant proteins have been made by optimizing cell lines, media, and process operation. This led to enhanced titers and process robustness without increasing the cost of the upstream processing (USP); however, a downstream bottleneck remains. In terms of process control improvement, the process analytical technology (PAT) initiative, initiated by the American Food and Drug Administration (FDA), aims to measure, analyze, monitor, and ultimately control all important attributes of a bioprocess. Especially, spectroscopic methods such as Raman or near-infrared spectroscopy enable one to meet these analytical requirements, preferably in-situ. In combination with chemometric techniques like partial least square (PLS) or principal component analysis (PCA), it is possible to generate soft sensors, which estimate process variables based on process and measurement models for the enhanced control of bioprocesses. Macroscopic kinetic models can be used to simulate cell metabolism. These models are able to enhance the process understanding by predicting the dynamic of cells during cultivation. In this article, in-situ turbidity (transmission, 880 nm) and ex-situ Raman spectroscopy (785 nm) measurements are combined with an offline macroscopic Monod kinetic model in order to predict substrate concentrations. Experimental data of Chinese hamster ovary cultivations in bioreactors show a sufficiently linear correlation (R2 ≥ 0.97) between turbidity and total cell concentration. PLS regression of Raman spectra generates a prediction model, which was validated via offline viable cell concentration measurement (RMSE ≤ 13.82, R2 ≥ 0.92). Based on these measurements, the macroscopic Monod model can be used to determine different process attributes, e.g., glucose concentration. In consequence, it is possible to approximately calculate (R2 ≥ 0.96) glucose concentration based on online cell concentration measurements using turbidity or Raman spectroscopy. Future approaches will use these online substrate concentration measurements with turbidity and Raman measurements, in combination with the kinetic model, in order to control the bioprocess in terms of feeding strategies, by employing an open platform communication (OPC) network—either in fed-batch or perfusion mode, integrated into a continuous operation of upstream and downstream. PMID:29547557

Analyzing milestoning networks for molecular kinetics: definitions, algorithms, and examples.

PubMed

Viswanath, Shruthi; Kreuzer, Steven M; Cardenas, Alfredo E; Elber, Ron

2013-11-07

Network representations are becoming increasingly popular for analyzing kinetic data from techniques like Milestoning, Markov State Models, and Transition Path Theory. Mapping continuous phase space trajectories into a relatively small number of discrete states helps in visualization of the data and in dissecting complex dynamics to concrete mechanisms. However, not only are molecular networks derived from molecular dynamics simulations growing in number, they are also getting increasingly complex, owing partly to the growth in computer power that allows us to generate longer and better converged trajectories. The increased complexity of the networks makes simple interpretation and qualitative insight of the molecular systems more difficult to achieve. In this paper, we focus on various network representations of kinetic data and algorithms to identify important edges and pathways in these networks. The kinetic data can be local and partial (such as the value of rate coefficients between states) or an exact solution to kinetic equations for the entire system (such as the stationary flux between vertices). In particular, we focus on the Milestoning method that provides fluxes as the main output. We proposed Global Maximum Weight Pathways as a useful tool for analyzing molecular mechanism in Milestoning networks. A closely related definition was made in the context of Transition Path Theory. We consider three algorithms to find Global Maximum Weight Pathways: Recursive Dijkstra's, Edge-Elimination, and Edge-List Bisection. The asymptotic efficiency of the algorithms is analyzed and numerical tests on finite networks show that Edge-List Bisection and Recursive Dijkstra's algorithms are most efficient for sparse and dense networks, respectively. Pathways are illustrated for two examples: helix unfolding and membrane permeation. Finally, we illustrate that networks based on local kinetic information can lead to incorrect interpretation of molecular mechanisms.

Influence of dynamic compressive loading on the in vitro degradation behavior of pure PLA and Mg/PLA composite.

PubMed

Li, Xuan; Qi, Chenxi; Han, Linyuan; Chu, Chenglin; Bai, Jing; Guo, Chao; Xue, Feng; Shen, Baolong; Chu, Paul K

2017-12-01

The effects of dynamic compressive loading on the in vitro degradation behavior of pure poly-lactic acid (PLA) and PLA-based composite unidirectionally reinforced with micro-arc oxidized magnesium alloy wires (Mg/PLA) are investigated. Dynamic compressive loading is shown to accelerate degradation of pure PLA and Mg/PLA. As the applied stress is increased from 0.1MPa to 0.9MPa or frequency from 0.5Hz to 2.5Hz, the overall degradation rate goes up. After immersion for 21days at 0.9MPa and 2.5Hz, the bending strength retention of the composite and pure PLA is 60.1% and 50%, respectively. Dynamic loading enhances diffusion of small acidic molecules resulting in significant pH decrease in the immersion solution. The synergistic reaction between magnesium alloy wires and PLA in the composite is further clarified by electrochemical tests. The degradation behavior of the pure PLA and PLA matrix in the composite under dynamic conditions obey the first order degradation kinetics and a numerical model is postulated to elucidate the relationship of the bending strength, stress, frequency, and immersion time under dynamic conditions. We systematically study the influence of dynamic loading on the degradation behavior of pure PLA and Mg/PLA. Dynamic compressive loading is shown to accelerate degradation of pure PLA and Mg/PLA. The synergistic reaction between magnesium alloy wires and PLA in the composite is firstly clarified by electrochemical tests. The degradation behavior of the pure PLA and PLA matrix in the composite under dynamic conditions obey the first order degradation kinetics. Then, a numerical model is postulated to elucidate the relationship of the bending strength, stress, frequency, and immersion time under dynamic conditions. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Particle-based simulations of self-motile suspensions

NASA Astrophysics Data System (ADS)

Hinz, Denis F.; Panchenko, Alexander; Kim, Tae-Yeon; Fried, Eliot

2015-11-01

A simple model for simulating flows of active suspensions is investigated. The approach is based on dissipative particle dynamics. While the model is potentially applicable to a wide range of self-propelled particle systems, the specific class of self-motile bacterial suspensions is considered as a modeling scenario. To mimic the rod-like geometry of a bacterium, two dissipative particle dynamics particles are connected by a stiff harmonic spring to form an aggregate dissipative particle dynamics molecule. Bacterial motility is modeled through a constant self-propulsion force applied along the axis of each such aggregate molecule. The model accounts for hydrodynamic interactions between self-propelled agents through the pairwise dissipative interactions conventional to dissipative particle dynamics. Numerical simulations are performed using a customized version of the open-source software package LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) software package. Detailed studies of the influence of agent concentration, pairwise dissipative interactions, and Stokes friction on the statistics of the system are provided. The simulations are used to explore the influence of hydrodynamic interactions in active suspensions. For high agent concentrations in combination with dominating pairwise dissipative forces, strongly correlated motion patterns and a fluid-like spectral distributions of kinetic energy are found. In contrast, systems dominated by Stokes friction exhibit weaker spatial correlations of the velocity field. These results indicate that hydrodynamic interactions may play an important role in the formation of spatially extended structures in active suspensions.

Evaporation rate-based selection of supramolecular chirality.

PubMed

Hattori, Shingo; Vandendriessche, Stefaan; Koeckelberghs, Guy; Verbiest, Thierry; Ishii, Kazuyuki

2017-03-09

We demonstrate the evaporation rate-based selection of supramolecular chirality for the first time. P-type aggregates prepared by fast evaporation, and M-type aggregates prepared by slow evaporation are kinetic and thermodynamic products under dynamic reaction conditions, respectively. These findings provide a novel solution reaction chemistry under the dynamic reaction conditions.

WE-FG-206-06: Dual-Input Tracer Kinetic Modeling and Its Analog Implementation for Dynamic Contrast-Enhanced (DCE-) MRI of Malignant Mesothelioma (MPM)

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

Lee, S; Rimner, A; Hayes, S

Purpose: To use dual-input tracer kinetic modeling of the lung for mapping spatial heterogeneity of various kinetic parameters in malignant MPM Methods: Six MPM patients received DCE-MRI as part of their radiation therapy simulation scan. 5 patients had the epitheloid subtype of MPM, while one was biphasic. A 3D fast-field echo sequence with TR/TE/Flip angle of 3.62ms/1.69ms/15° was used for DCE-MRI acquisition. The scan was collected for 5 minutes with a temporal resolution of 5-9 seconds depending on the spatial extent of the tumor. A principal component analysis-based groupwise deformable registration was used to co-register all the DCE-MRI series formore » motion compensation. All the images were analyzed using five different dual-input tracer kinetic models implemented in analog continuous-time formalism: the Tofts-Kety (TK), extended TK (ETK), two compartment exchange (2CX), adiabatic approximation to the tissue homogeneity (AATH), and distributed parameter (DP) models. The following parameters were computed for each model: total blood flow (BF), pulmonary flow fraction (γ), pulmonary blood flow (BF-pa), systemic blood flow (BF-a), blood volume (BV), mean transit time (MTT), permeability-surface area product (PS), fractional interstitial volume (vi), extraction fraction (E), volume transfer constant (Ktrans) and efflux rate constant (kep). Results: Although the majority of patients had epitheloid histologies, kinetic parameter values varied across different models. One patient showed a higher total BF value in all models among the epitheloid histologies, although the γ value was varying among these different models. In one tumor with a large area of necrosis, the TK and ETK models showed higher E, Ktrans, and kep values and lower interstitial volume as compared to AATH and DP and 2CX models. Kinetic parameters such as BF-pa, BF-a, PS, Ktrans values were higher in surviving group compared to non-surviving group across most models. Conclusion: Dual-input tracer kinetic modeling is feasible in determining micro-vascular characteristics of MPM. This project was supported from Cycle for Survival and MSK Imaging and radiation science (IMRAS) grants.« less

Mechanisms of kinetic stabilization by the drugs paclitaxel and vinblastine.

PubMed

Castle, Brian T; McCubbin, Seth; Prahl, Louis S; Bernens, Jordan N; Sept, David; Odde, David J

2017-05-01

Microtubule-targeting agents (MTAs), widely used as biological probes and chemotherapeutic drugs, bind directly to tubulin subunits and "kinetically stabilize" microtubules, suppressing the characteristic self-assembly process of dynamic instability. However, the molecular-level mechanisms of kinetic stabilization are unclear, and the fundamental thermodynamic and kinetic requirements for dynamic instability and its elimination by MTAs have yet to be defined. Here we integrate a computational model for microtubule assembly with nanometer-scale fluorescence microscopy measurements to identify the kinetic and thermodynamic basis of kinetic stabilization by the MTAs paclitaxel, an assembly promoter, and vinblastine, a disassembly promoter. We identify two distinct modes of kinetic stabilization in live cells, one that truly suppresses on-off kinetics, characteristic of vinblastine, and the other a "pseudo" kinetic stabilization, characteristic of paclitaxel, that nearly eliminates the energy difference between the GTP- and GDP-tubulin thermodynamic states. By either mechanism, the main effect of both MTAs is to effectively stabilize the microtubule against disassembly in the absence of a robust GTP cap. © 2017 Castle et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Predictive Modeling of Fast-Curing Thermosets in Nozzle-Based Extrusion

NASA Technical Reports Server (NTRS)

Xie, Jingjin; Randolph, Robert; Simmons, Gary; Hull, Patrick V.; Mazzeo, Aaron D.

2017-01-01

This work presents an approach to modeling the dynamic spreading and curing behavior of thermosets in nozzle-based extrusions. Thermosets cover a wide range of materials, some of which permit low-temperature processing with subsequent high-temperature and high-strength working properties. Extruding thermosets may overcome the limited working temperatures and strengths of conventional thermoplastic materials used in additive manufacturing. This project aims to produce technology for the fabrication of thermoset-based structures leveraging advances made in nozzle-based extrusion, such as fused deposition modeling (FDM), material jetting, and direct writing. Understanding the synergistic interactions between spreading and fast curing of extruded thermosetting materials will provide essential insights for applications that require accurate dimensional controls, such as additive manufacturing [1], [2] and centrifugal coating/forming [3]. Two types of thermally curing thermosets -- one being a soft silicone (Ecoflex 0050) and the other being a toughened epoxy (G/Flex) -- served as the test materials in this work to obtain models for cure kinetics and viscosity. The developed models align with extensive measurements made with differential scanning calorimetry (DSC) and rheology. DSC monitors the change in the heat of reaction, which reflects the rate and degree of cure at different crosslinking stages. Rheology measures the change in complex viscosity, shear moduli, yield stress, and other properties dictated by chemical composition. By combining DSC and rheological measurements, it is possible to establish a set of models profiling the cure kinetics and chemorheology without prior knowledge of chemical composition, which is usually necessary for sophisticated mechanistic modeling. In this work, we conducted both isothermal and dynamic measurements with both DSC and rheology. With the developed models, numerical simulations yielded predictions of diameter and height of droplets, along with width and height of extruded lines cured at varied temperatures. Experimental results carried out on a goniometric platform and a nozzle-based 3D printer showed agreement with the numerical simulations. Finally, this presentation will show how the models are adaptable to the planning of tool paths and designs in additive manufacturing.

Kinetic quantitation of cerebral PET-FDG studies without concurrent blood sampling: statistical recovery of the arterial input function.

PubMed

O'Sullivan, F; Kirrane, J; Muzi, M; O'Sullivan, J N; Spence, A M; Mankoff, D A; Krohn, K A

2010-03-01

Kinetic quantitation of dynamic positron emission tomography (PET) studies via compartmental modeling usually requires the time-course of the radio-tracer concentration in the arterial blood as an arterial input function (AIF). For human and animal imaging applications, significant practical difficulties are associated with direct arterial sampling and as a result there is substantial interest in alternative methods that require no blood sampling at the time of the study. A fixed population template input function derived from prior experience with directly sampled arterial curves is one possibility. Image-based extraction, including requisite adjustment for spillover and recovery, is another approach. The present work considers a hybrid statistical approach based on a penalty formulation in which the information derived from a priori studies is combined in a Bayesian manner with information contained in the sampled image data in order to obtain an input function estimate. The absolute scaling of the input is achieved by an empirical calibration equation involving the injected dose together with the subject's weight, height and gender. The technique is illustrated in the context of (18)F -Fluorodeoxyglucose (FDG) PET studies in humans. A collection of 79 arterially sampled FDG blood curves are used as a basis for a priori characterization of input function variability, including scaling characteristics. Data from a series of 12 dynamic cerebral FDG PET studies in normal subjects are used to evaluate the performance of the penalty-based AIF estimation technique. The focus of evaluations is on quantitation of FDG kinetics over a set of 10 regional brain structures. As well as the new method, a fixed population template AIF and a direct AIF estimate based on segmentation are also considered. Kinetics analyses resulting from these three AIFs are compared with those resulting from radially sampled AIFs. The proposed penalty-based AIF extraction method is found to achieve significant improvements over the fixed template and the segmentation methods. As well as achieving acceptable kinetic parameter accuracy, the quality of fit of the region of interest (ROI) time-course data based on the extracted AIF, matches results based on arterially sampled AIFs. In comparison, significant deviation in the estimation of FDG flux and degradation in ROI data fit are found with the template and segmentation methods. The proposed AIF extraction method is recommended for practical use.

Atomistic modeling of crystal-to-amorphous transition and associated kinetics in the Ni-Nb system by molecular dynamics simulations.

PubMed

Dai, X D; Li, J H; Liu, B X

2005-03-17

With the aid of ab initio calculations, an n-body potential of the Ni-Nb system is constructed under the Finnis-Sinclair formalism and the constructed potential is capable of not only reproducing some static physical properties but also revealing the atomistic mechanism of crystal-to-amorphous transition and associated kinetics. With application of the constructed potential, molecular dynamics simulations using the solid solution models reveal that the physical origin of crystal-to-amorphous transition is the crystalline lattice collapsing while the solute atoms are exceeding the critical solid solubilities, which are determined to be 19 atom % Ni and 13 atom % Nb for the Nb- and Ni-based solid solutions, respectively. It follows that an intrinsic glass-forming ability of the Ni-Nb system is within 19-87 atom % Ni, which matches well with that observed in ion beam mixing/solid-state reaction experiments. Simulations using the Nb/Ni/Nb (Ni/Nb/Ni) sandwich models indicate that the amorphous layer at the interfaces grows in a layer-by-layer mode and that, upon dissolving solute atoms, the Ni lattice approaches and exceeds its critical solid solubility faster than the Nb lattice, revealing an asymmetric behavior in growth kinetics. Moreover, an energy diagram is obtained by computing the energetic sequence of the Ni(x)Nb(100)(-)(x) alloy in fcc, bcc, and amorphous structures, respectively, over the entire composition range, and the diagram could serve as a guide for predicting the metastable alloy formation in the Ni-Nb system.

The What and Where of Adding Channel Noise to the Hodgkin-Huxley Equations

PubMed Central

Goldwyn, Joshua H.; Shea-Brown, Eric

2011-01-01

Conductance-based equations for electrically active cells form one of the most widely studied mathematical frameworks in computational biology. This framework, as expressed through a set of differential equations by Hodgkin and Huxley, synthesizes the impact of ionic currents on a cell's voltage—and the highly nonlinear impact of that voltage back on the currents themselves—into the rapid push and pull of the action potential. Later studies confirmed that these cellular dynamics are orchestrated by individual ion channels, whose conformational changes regulate the conductance of each ionic current. Thus, kinetic equations familiar from physical chemistry are the natural setting for describing conductances; for small-to-moderate numbers of channels, these will predict fluctuations in conductances and stochasticity in the resulting action potentials. At first glance, the kinetic equations provide a far more complex (and higher-dimensional) description than the original Hodgkin-Huxley equations or their counterparts. This has prompted more than a decade of efforts to capture channel fluctuations with noise terms added to the equations of Hodgkin-Huxley type. Many of these approaches, while intuitively appealing, produce quantitative errors when compared to kinetic equations; others, as only very recently demonstrated, are both accurate and relatively simple. We review what works, what doesn't, and why, seeking to build a bridge to well-established results for the deterministic equations of Hodgkin-Huxley type as well as to more modern models of ion channel dynamics. As such, we hope that this review will speed emerging studies of how channel noise modulates electrophysiological dynamics and function. We supply user-friendly MATLAB simulation code of these stochastic versions of the Hodgkin-Huxley equations on the ModelDB website (accession number 138950) and http://www.amath.washington.edu/~etsb/tutorials.html. PMID:22125479

Ring Current Ion Coupling with Electromagnetic Ion Cyclotron Waves

NASA Technical Reports Server (NTRS)

Khazanov. G. V.; Gamayunov, K. V.; Jordanova, V. K.; Six, N. Frank (Technical Monitor)

2002-01-01

A new ring current global model has been developed that couples the system of two kinetic equations: one equation describes the ring current (RC) ion dynamic, and another equation describes wave evolution of electromagnetic ion cyclotron waves (EMIC). The coupled model is able to simulate, for the first time self-consistently calculated RC ion kinetic and evolution of EMIC waves that propagate along geomagnetic field lines and reflect from the ionosphere. Ionospheric properties affect the reflection index through the integral Pedersen and Hall conductivities. The structure and dynamics of the ring current proton precipitating flux regions, intensities of EMIC global RC energy balance, and some other parameters will be studied in detail for the selected geomagnetic storms.

Extracting a respiratory signal from raw dynamic PET data that contain tracer kinetics.

PubMed

Schleyer, P J; Thielemans, K; Marsden, P K

2014-08-07

Data driven gating (DDG) methods provide an alternative to hardware based respiratory gating for PET imaging. Several existing DDG approaches obtain a respiratory signal by observing the change in PET-counts within specific regions of acquired PET data. Currently, these methods do not allow for tracer kinetics which can interfere with the respiratory signal and introduce error. In this work, we produced a DDG method for dynamic PET studies that exhibit tracer kinetics. Our method is based on an existing approach that uses frequency-domain analysis to locate regions within raw PET data that are subject to respiratory motion. In the new approach, an optimised non-stationary short-time Fourier transform was used to create a time-varying 4D map of motion affected regions. Additional processing was required to ensure that the relationship between the sign of the respiratory signal and the physical direction of movement remained consistent for each temporal segment of the 4D map. The change in PET-counts within the 4D map during the PET acquisition was then used to generate a respiratory curve. Using 26 min dynamic cardiac NH3 PET acquisitions which included a hardware derived respiratory measurement, we show that tracer kinetics can severely degrade the respiratory signal generated by the original DDG method. In some cases, the transition of tracer from the liver to the lungs caused the respiratory signal to invert. The new approach successfully compensated for tracer kinetics and improved the correlation between the data-driven and hardware based signals. On average, good correlation was maintained throughout the PET acquisitions.

Shock Wave Dynamics in Weakly Ionized Plasmas

NASA Technical Reports Server (NTRS)

Johnson, Joseph A., III

1999-01-01

An investigation of the dynamics of shock waves in weakly ionized argon plasmas has been performed using a pressure ruptured shock tube. The velocity of the shock is observed to increase when the shock traverses the plasma. The observed increases cannot be accounted for by thermal effects alone. Possible mechanisms that could explain the anomalous behavior include a vibrational/translational relaxation in the nonequilibrium plasma, electron diffusion across the shock front resulting from high electron mobility, and the propagation of ion-acoustic waves generated at the shock front. Using a turbulence model based on reduced kinetic theory, analysis of the observed results suggest a role for turbulence in anomalous shock dynamics in weakly ionized media and plasma-induced hypersonic drag reduction.

Rarefied gas flow simulations using high-order gas-kinetic unified algorithms for Boltzmann model equations

NASA Astrophysics Data System (ADS)

Li, Zhi-Hui; Peng, Ao-Ping; Zhang, Han-Xin; Yang, Jaw-Yen

2015-04-01

This article reviews rarefied gas flow computations based on nonlinear model Boltzmann equations using deterministic high-order gas-kinetic unified algorithms (GKUA) in phase space. The nonlinear Boltzmann model equations considered include the BGK model, the Shakhov model, the Ellipsoidal Statistical model and the Morse model. Several high-order gas-kinetic unified algorithms, which combine the discrete velocity ordinate method in velocity space and the compact high-order finite-difference schemes in physical space, are developed. The parallel strategies implemented with the accompanying algorithms are of equal importance. Accurate computations of rarefied gas flow problems using various kinetic models over wide ranges of Mach numbers 1.2-20 and Knudsen numbers 0.0001-5 are reported. The effects of different high resolution schemes on the flow resolution under the same discrete velocity ordinate method are studied. A conservative discrete velocity ordinate method to ensure the kinetic compatibility condition is also implemented. The present algorithms are tested for the one-dimensional unsteady shock-tube problems with various Knudsen numbers, the steady normal shock wave structures for different Mach numbers, the two-dimensional flows past a circular cylinder and a NACA 0012 airfoil to verify the present methodology and to simulate gas transport phenomena covering various flow regimes. Illustrations of large scale parallel computations of three-dimensional hypersonic rarefied flows over the reusable sphere-cone satellite and the re-entry spacecraft using almost the largest computer systems available in China are also reported. The present computed results are compared with the theoretical prediction from gas dynamics, related DSMC results, slip N-S solutions and experimental data, and good agreement can be found. The numerical experience indicates that although the direct model Boltzmann equation solver in phase space can be computationally expensive, nevertheless, the present GKUAs for kinetic model Boltzmann equations in conjunction with current available high-performance parallel computer power can provide a vital engineering tool for analyzing rarefied gas flows covering the whole range of flow regimes in aerospace engineering applications.

Kinetics of Cd(ii) adsorption and desorption on ferrihydrite: experiments and modeling.

PubMed

Liang, Yuzhen; Tian, Lei; Lu, Yang; Peng, Lanfang; Wang, Pei; Lin, Jingyi; Cheng, Tao; Dang, Zhi; Shi, Zhenqing

2018-05-15

The kinetics of Cd(ii) adsorption/desorption on ferrihydrite is an important process affecting the fate, transport, and bioavailability of Cd(ii) in the environment, which was rarely systematically studied and understood at quantitative levels. In this work, a combination of stirred-flow kinetic experiments, batch adsorption equilibrium experiments, high-resolution transmission electron microscopy (HR-TEM), and mechanistic kinetic modeling were used to study the kinetic behaviors of Cd(ii) adsorption/desorption on ferrihydrite. HR-TEM images showed the open, loose, and sponge-like structure of ferrihydrite. The batch adsorption equilibrium experiments revealed that higher pH and initial metal concentration increased Cd(ii) adsorption on ferrihydrite. The stirred-flow kinetic results demonstrated the increased adsorption rate and capacity as a result of the increased pH, influent concentration, and ferrihydrite concentration. The mechanistic kinetic model successfully described the kinetic behaviors of Cd(ii) during the adsorption and desorption stages under various chemistry conditions. The model calculations showed that the adsorption rate coefficients varied as a function of solution chemistry, and the relative contributions of the weak and strong ferrihydrite sites for Cd(ii) binding varied with time at different pH and initial metal concentrations. Our model is able to quantitatively assess the contributions of each individual ferrihydrite binding site to the overall Cd(ii) adsorption/desorption kinetics. This study provided insights into the dynamic behavior of Cd(ii) and a predictive modeling tool for Cd(ii) adsorption/desorption kinetics when ferrihydrite is present, which may be helpful for the risk assessment and management of Cd contaminated sites.

Dynamic curvature sensing employing ionic-polymer-metal composite sensors

NASA Astrophysics Data System (ADS)

Bahramzadeh, Yousef; Shahinpoor, Mohsen

2011-09-01

A dynamic curvature sensor is presented based on ionic-polymer-metal composite (IPMC) for curvature monitoring of deployable/inflatable dynamic space structures. Monitoring the curvature variation is of high importance in various engineering structures including shape monitoring of deployable/inflatable space structures in which the structural boundaries undergo a dynamic deployment process. The high sensitivity of IPMCs to the applied deformations as well as its flexibility make IPMCs a promising candidate for sensing of dynamic curvature changes. Herein, we explore the dynamic response of an IPMC sensor strip with respect to controlled curvature deformations subjected to different forms of input functions. Using a specially designed experimental setup, the voltage recovery effect, phase delay, and rate dependency of the output voltage signal of an IPMC curvature sensor are analyzed. Experimental results show that the IPMC sensor maintains the linearity, sensitivity, and repeatability required for curvature sensing. Besides, in order to describe the dynamic phenomena such as the rate dependency of the IPMC sensor, a chemo-electro-mechanical model based on the Poisson-Nernst-Planck (PNP) equation for the kinetics of ion diffusion is presented. By solving the governing partial differential equations the frequency response of the IPMC sensor is derived. The physical model is able to describe the dynamic properties of the IPMC sensor and the dependency of the signal on rate of excitations.

Interstitial diffusion and the relationship between compartment modelling and multi-scale spatial-temporal modelling of (18)F-FLT tumour uptake dynamics.

PubMed

Liu, Dan; Chalkidou, Anastasia; Landau, David B; Marsden, Paul K; Fenwick, John D

2014-09-07

Tumour cell proliferation can be imaged via positron emission tomography of the radiotracer 3'-deoxy-3'-18F-fluorothymidine (18F-FLT). Conceptually, the number of proliferating cells might be expected to correlate more closely with the kinetics of 18F-FLT uptake than with uptake at a fixed time. Radiotracer uptake kinetics are standardly visualized using parametric maps of compartment model fits to time-activity-curves (TACs) of individual voxels. However the relationship between the underlying spatiotemporal accumulation of FLT and the kinetics described by compartment models has not yet been explored. In this work tumour tracer uptake is simulated using a mechanistic spatial-temporal model based on a convection-diffusion-reaction equation solved via the finite difference method. The model describes a chain of processes: the flow of FLT between the spatially heterogeneous tumour vasculature and interstitium; diffusion and convection of FLT within the interstitium; transport of FLT into cells; and intracellular phosphorylation. Using values of model parameters estimated from the biological literature, simulated FLT TACs are generated with shapes and magnitudes similar to those seen clinically. Results show that the kinetics of the spatial-temporal model can be recovered accurately by fitting a 3-tissue compartment model to FLT TACs simulated for those tumours or tumour sub-volumes that can be viewed as approximately closed, for which tracer diffusion throughout the interstitium makes only a small fractional change to the quantity of FLT they contain. For a single PET voxel of width 2.5-5 mm we show that this condition is roughly equivalent to requiring that the relative difference in tracer uptake between the voxel and its neighbours is much less than one.

Protein folding simulations: from coarse-grained model to all-atom model.

PubMed

Zhang, Jian; Li, Wenfei; Wang, Jun; Qin, Meng; Wu, Lei; Yan, Zhiqiang; Xu, Weixin; Zuo, Guanghong; Wang, Wei

2009-06-01

Protein folding is an important and challenging problem in molecular biology. During the last two decades, molecular dynamics (MD) simulation has proved to be a paramount tool and was widely used to study protein structures, folding kinetics and thermodynamics, and structure-stability-function relationship. It was also used to help engineering and designing new proteins, and to answer even more general questions such as the minimal number of amino acid or the evolution principle of protein families. Nowadays, the MD simulation is still undergoing rapid developments. The first trend is to toward developing new coarse-grained models and studying larger and more complex molecular systems such as protein-protein complex and their assembling process, amyloid related aggregations, and structure and motion of chaperons, motors, channels and virus capsides; the second trend is toward building high resolution models and explore more detailed and accurate pictures of protein folding and the associated processes, such as the coordination bond or disulfide bond involved folding, the polarization, charge transfer and protonate/deprotonate process involved in metal coupled folding, and the ion permeation and its coupling with the kinetics of channels. On these new territories, MD simulations have given many promising results and will continue to offer exciting views. Here, we review several new subjects investigated by using MD simulations as well as the corresponding developments of appropriate protein models. These include but are not limited to the attempt to go beyond the topology based Gō-like model and characterize the energetic factors in protein structures and dynamics, the study of the thermodynamics and kinetics of disulfide bond involved protein folding, the modeling of the interactions between chaperonin and the encapsulated protein and the protein folding under this circumstance, the effort to clarify the important yet still elusive folding mechanism of protein BBL, the development of discrete MD and its application in studying the alpha-beta conformational conversion and oligomer assembling process, and the modeling of metal ion involved protein folding. (c) 2009 IUBMB.

Effects of film growth kinetics on grain coarsening and grain shape.

PubMed

Reis, F D A Aarão

2017-04-01

We study models of grain nucleation and coarsening during the deposition of a thin film using numerical simulations and scaling approaches. The incorporation of new particles in the film is determined by lattice growth models in three different universality classes, with no effect of the grain structure. The first model of grain coarsening is similar to that proposed by Saito and Omura [Phys. Rev. E 84, 021601 (2011)PLEEE81539-375510.1103/PhysRevE.84.021601], in which nucleation occurs only at the substrate, and the grain boundary evolution at the film surface is determined by a probabilistic competition of neighboring grains. The surface grain density has a power-law decay, with an exponent related to the dynamical exponent of the underlying growth kinetics, and the average radius of gyration scales with the film thickness with the same exponent. This model is extended by allowing nucleation of new grains during the deposition, with constant but small rates. The surface grain density crosses over from the initial power law decay to a saturation; at the crossover, the time, grain mass, and surface grain density are estimated as a function of the nucleation rate. The distributions of grain mass, height, and radius of gyration show remarkable power law decays, similar to other systems with coarsening and particle injection, with exponents also related to the dynamical exponent. The scaling of the radius of gyration with the height h relative to the base of the grain show clearly different exponents in growth dominated by surface tension and growth dominated by surface diffusion; thus it may be interesting for investigating the effects of kinetic roughening on grain morphology. In growth dominated by surface diffusion, the increase of grain size with temperature is observed.

A Self-Consistent Model of the Interacting Ring Current Ions and Electromagnetic Ion Cyclotron Waves, Initial Results: Waves and Precipitating Fluxes

NASA Technical Reports Server (NTRS)

Khazanov, G. V.; Gamayunov, K. V.; Jordanova, V. K.; Krivorutsky, E. N.

2002-01-01

Initial results from a newly developed model of the interacting ring current ions and ion cyclotron waves are presented. The model is based on the system of two kinetic equations: one equation describes the ring current ion dynamics, and another equation describes wave evolution. The system gives a self-consistent description of the ring current ions and ion cyclotron waves in a quasilinear approach. These equations for the ion phase space distribution function and for the wave power spectral density were solved on aglobal magnetospheric scale undernonsteady state conditions during the 2-5 May 1998 storm. The structure and dynamics of the ring current proton precipitating flux regions and the ion cyclotron wave-active zones during extreme geomagnetic disturbances on 4 May 1998 are presented and discussed in detail.

How Kinetics within the Unfolded State Affects Protein Folding: an Analysis Based on Markov State Models and an Ultra-Long MD Trajectory

PubMed Central

Deng, Nan-jie; Dai, Wei

2013-01-01

Understanding how kinetics in the unfolded state affects protein folding is a fundamentally important yet less well-understood issue. Here we employ three different models to analyze the unfolded landscape and folding kinetics of the miniprotein Trp-cage. The first is a 208 μs explicit solvent molecular dynamics (MD) simulation from D. E. Shaw Research containing tens of folding events. The second is a Markov state model (MSM-MD) constructed from the same ultra-long MD simulation; MSM-MD can be used to generate thousands of folding events. The third is a Markov state model built from temperature replica exchange MD simulations in implicit solvent (MSM-REMD). All the models exhibit multiple folding pathways, and there is a good correspondence between the folding pathways from direct MD and those computed from the MSMs. The unfolded populations interconvert rapidly between extended and collapsed conformations on time scales ≤ 40 ns, compared with the folding time of ≈ 5 μs. The folding rates are independent of where the folding is initiated from within the unfolded ensemble. About 90 % of the unfolded states are sampled within the first 40 μs of the ultra-long MD trajectory, which on average explores ~27 % of the unfolded state ensemble between consecutive folding events. We clustered the folding pathways according to structural similarity into “tubes”, and kinetically partitioned the unfolded state into populations that fold along different tubes. From our analysis of the simulations and a simple kinetic model, we find that when the mixing within the unfolded state is comparable to or faster than folding, the folding waiting times for all the folding tubes are similar and the folding kinetics is essentially single exponential despite the presence of heterogeneous folding paths with non-uniform barriers. When the mixing is much slower than folding, different unfolded populations fold independently leading to non-exponential kinetics. A kinetic partition of the Trp-cage unfolded state is constructed which reveals that different unfolded populations have almost the same probability to fold along any of the multiple folding paths. We are investigating whether the results for the kinetics in the unfolded state of the twenty-residue Trp-cage is representative of larger single domain proteins. PMID:23705683

Global sensitivity analysis in stochastic simulators of uncertain reaction networks.

PubMed

Navarro Jimenez, M; Le Maître, O P; Knio, O M

2016-12-28

Stochastic models of chemical systems are often subjected to uncertainties in kinetic parameters in addition to the inherent random nature of their dynamics. Uncertainty quantification in such systems is generally achieved by means of sensitivity analyses in which one characterizes the variability with the uncertain kinetic parameters of the first statistical moments of model predictions. In this work, we propose an original global sensitivity analysis method where the parametric and inherent variability sources are both treated through Sobol's decomposition of the variance into contributions from arbitrary subset of uncertain parameters and stochastic reaction channels. The conceptual development only assumes that the inherent and parametric sources are independent, and considers the Poisson processes in the random-time-change representation of the state dynamics as the fundamental objects governing the inherent stochasticity. A sampling algorithm is proposed to perform the global sensitivity analysis, and to estimate the partial variances and sensitivity indices characterizing the importance of the various sources of variability and their interactions. The birth-death and Schlögl models are used to illustrate both the implementation of the algorithm and the richness of the proposed analysis method. The output of the proposed sensitivity analysis is also contrasted with a local derivative-based sensitivity analysis method classically used for this type of systems.

Homologous Chromosome Pairing in Drosophila melanogaster Proceeds through Multiple Independent Initiations

PubMed Central

Fung, Jennifer C.; Marshall, Wallace F.; Dernburg, Abby; Agard, David A.; Sedat, John W.

1998-01-01

The dynamics by which homologous chromosomes pair is currently unknown. Here, we use fluorescence in situ hybridization in combination with three-dimensional optical microscopy to show that homologous pairing of the somatic chromosome arm 2L in Drosophila occurs by independent initiation of pairing at discrete loci rather than by a processive zippering of sites along the length of chromosome. By evaluating the pairing frequencies of 11 loci on chromosome arm 2L over several timepoints during Drosophila embryonic development, we show that all 11 loci are paired very early in Drosophila development, within 13 h after egg deposition. To elucidate whether such pairing occurs by directed or undirected motion, we analyzed the pairing kinetics of histone loci during nuclear cycle 14. By measuring changes of nuclear length and correlating these changes with progression of time during cycle 14, we were able to express the pairing frequency and distance between homologous loci as a function of time. Comparing the experimentally determined dynamics of pairing to simulations based on previously proposed models of pairing motion, we show that the observed pairing kinetics are most consistent with a constrained random walk model and not consistent with a directed motion model. Thus, we conclude that simple random contacts through diffusion could suffice to allow pairing of homologous sites. PMID:9531544

Homologous chromosome pairing in Drosophila melanogaster proceeds through multiple independent initiations.

PubMed

Fung, J C; Marshall, W F; Dernburg, A; Agard, D A; Sedat, J W

1998-04-06

The dynamics by which homologous chromosomes pair is currently unknown. Here, we use fluorescence in situ hybridization in combination with three-dimensional optical microscopy to show that homologous pairing of the somatic chromosome arm 2L in Drosophila occurs by independent initiation of pairing at discrete loci rather than by a processive zippering of sites along the length of chromosome. By evaluating the pairing frequencies of 11 loci on chromosome arm 2L over several timepoints during Drosophila embryonic development, we show that all 11 loci are paired very early in Drosophila development, within 13 h after egg deposition. To elucidate whether such pairing occurs by directed or undirected motion, we analyzed the pairing kinetics of histone loci during nuclear cycle 14. By measuring changes of nuclear length and correlating these changes with progression of time during cycle 14, we were able to express the pairing frequency and distance between homologous loci as a function of time. Comparing the experimentally determined dynamics of pairing to simulations based on previously proposed models of pairing motion, we show that the observed pairing kinetics are most consistent with a constrained random walk model and not consistent with a directed motion model. Thus, we conclude that simple random contacts through diffusion could suffice to allow pairing of homologous sites.

Global sensitivity analysis in stochastic simulators of uncertain reaction networks

DOE PAGES

Navarro Jimenez, M.; Le Maître, O. P.; Knio, O. M.

2016-12-23

Stochastic models of chemical systems are often subjected to uncertainties in kinetic parameters in addition to the inherent random nature of their dynamics. Uncertainty quantification in such systems is generally achieved by means of sensitivity analyses in which one characterizes the variability with the uncertain kinetic parameters of the first statistical moments of model predictions. In this work, we propose an original global sensitivity analysis method where the parametric and inherent variability sources are both treated through Sobol’s decomposition of the variance into contributions from arbitrary subset of uncertain parameters and stochastic reaction channels. The conceptual development only assumes thatmore » the inherent and parametric sources are independent, and considers the Poisson processes in the random-time-change representation of the state dynamics as the fundamental objects governing the inherent stochasticity. Here, a sampling algorithm is proposed to perform the global sensitivity analysis, and to estimate the partial variances and sensitivity indices characterizing the importance of the various sources of variability and their interactions. The birth-death and Schlögl models are used to illustrate both the implementation of the algorithm and the richness of the proposed analysis method. The output of the proposed sensitivity analysis is also contrasted with a local derivative-based sensitivity analysis method classically used for this type of systems.« less

Global sensitivity analysis in stochastic simulators of uncertain reaction networks

NASA Astrophysics Data System (ADS)

Navarro Jimenez, M.; Le Maître, O. P.; Knio, O. M.

2016-12-01

Stochastic models of chemical systems are often subjected to uncertainties in kinetic parameters in addition to the inherent random nature of their dynamics. Uncertainty quantification in such systems is generally achieved by means of sensitivity analyses in which one characterizes the variability with the uncertain kinetic parameters of the first statistical moments of model predictions. In this work, we propose an original global sensitivity analysis method where the parametric and inherent variability sources are both treated through Sobol's decomposition of the variance into contributions from arbitrary subset of uncertain parameters and stochastic reaction channels. The conceptual development only assumes that the inherent and parametric sources are independent, and considers the Poisson processes in the random-time-change representation of the state dynamics as the fundamental objects governing the inherent stochasticity. A sampling algorithm is proposed to perform the global sensitivity analysis, and to estimate the partial variances and sensitivity indices characterizing the importance of the various sources of variability and their interactions. The birth-death and Schlögl models are used to illustrate both the implementation of the algorithm and the richness of the proposed analysis method. The output of the proposed sensitivity analysis is also contrasted with a local derivative-based sensitivity analysis method classically used for this type of systems.

Kinetics of SiHCl3 chemical vapor deposition and fluid dynamic simulations.

PubMed

Cavallotti, Carlo; Masi, Maurizio

2011-09-01

Though most of the current silicon photovoltaic technology relies on trichlorosilane (SiHCl3) as a precursor gas to deposit Si, only a few studies have been devoted to the investigation of its gas phase and surface kinetics. In the present work we propose a new kinetic mechanism apt to describe the gas phase and surface chemistry active during the deposition of Si from SiHCl3. Kinetic constants of key reactions were either taken from the literature or determined through ab initio calculations. The capability of the mechanism to reproduce experimental data was tested through the implementation of the kinetic scheme in a fluid dynamic model and in the simulation of both deposition and etching of Si in horizontal reactors. The results of the simulations show that the reactivity of HCl is of key importance in order to control the Si deposition rate. When HCl reaches a critical concentration in the gas phase it starts etching the Si surface, so that the net deposition rate is the net sum of the adsorption rate of the gas phase precursors and the etching rate due to HCl. In these conditions the possibility to further deposit Si is directly related to the rate of consumption of HCl through its reaction with SiHCl3 to give SiCl4. The proposed reaction mechanism was implemented in a 3D fluid dynamic model of a simple Siemens reactor. The simulation results indicate that the proposed interpretation of the growth process applies also to this class of reactors, which operate in what can be defined as a mixed kinetic-transport controlled regime.

Flow-Induced New Channels of Energy Exchange in Multi-Scale Plasma Dynamics – Revisiting Perturbative Hybrid Kinetic-MHD Theory

PubMed Central

Shiraishi, Junya; Miyato, Naoaki; Matsunaga, Go

2016-01-01

It is found that new channels of energy exchange between macro- and microscopic dynamics exist in plasmas. They are induced by macroscopic plasma flow. This finding is based on the kinetic-magnetohydrodynamic (MHD) theory, which analyses interaction between macroscopic (MHD-scale) motion and microscopic (particle-scale) dynamics. The kinetic-MHD theory is extended to include effects of macroscopic plasma flow self-consistently. The extension is realised by generalising an energy exchange term due to wave-particle resonance, denoted by δ WK. The first extension is generalisation of the particle’s Lagrangian, and the second one stems from modification to the particle distribution function due to flow. These extensions lead to a generalised expression of δ WK, which affects the MHD stability of plasmas. PMID:27160346

A Self-Consistent Model of the Interacting Ring Current Ions with Electromagnetic ICWs

NASA Technical Reports Server (NTRS)

Khazanov, G. V.; Gamayunov, K. V.; Jordanova, V. K.; Krivorutsky, E. N.; Whitaker, Ann F. (Technical Monitor)

2001-01-01

Initial results from a newly developed model of the interacting ring current ions and ion cyclotron waves are presented. The model is based on the system of two bound kinetic equations: one equation describes the ring current ion dynamics, and another equation describes wave evolution. The system gives a self-consistent description of ring current ions and ion cyclotron waves in a quasilinear approach. These two equations were solved on a global scale under non steady-state conditions during the May 2-5, 1998 storm. The structure and dynamics of the ring current proton precipitating flux regions and the wave active zones at three time cuts around initial, main, and late recovery phases of the May 4, 1998 storm phase are presented and discussed in detail. Comparisons of the model wave-ion data with the Polar/HYDRA and Polar/MFE instruments results are presented..

Effect of EMIC Wave Normal Angle Distribution on Relativistic Electron Scattering Based on the Newly Developed Self-consistent RC/EMIC Waves Model by Khazanov et al. [2006

NASA Technical Reports Server (NTRS)

Khazanov, G. V.; Gallagher, D. L.; Gamayunov, K.

2007-01-01

It is well known that the effects of EMIC waves on RC ion and RB electron dynamics strongly depend on such particle/wave characteristics as the phase-space distribution function, frequency, wave-normal angle, wave energy, and the form of wave spectral energy density. Therefore, realistic characteristics of EMIC waves should be properly determined by modeling the RC-EMIC waves evolution self-consistently. Such a selfconsistent model progressively has been developing by Khaznnov et al. [2002-2006]. It solves a system of two coupled kinetic equations: one equation describes the RC ion dynamics and another equation describes the energy density evolution of EMIC waves. Using this model, we present the effectiveness of relativistic electron scattering and compare our results with previous work in this area of research.

Interfacial mixing in high-energy-density matter with a multiphysics kinetic model

NASA Astrophysics Data System (ADS)

Haack, Jeffrey R.; Hauck, Cory D.; Murillo, Michael S.

2017-12-01

We have extended a recently developed multispecies, multitemperature Bhatnagar-Gross-Krook model [Haack et al., J. Stat. Phys. 168, 822 (2017), 10.1007/s10955-017-1824-9], to include multiphysics capabilities that enable modeling of a wider range of physical conditions. In terms of geometry, we have extended from the spatially homogeneous setting to one spatial dimension. In terms of the physics, we have included an atomic ionization model, accurate collision physics across coupling regimes, self-consistent electric fields, and degeneracy in the electronic screening. We apply the model to a warm dense matter scenario in which the ablator-fuel interface of an inertial confinement fusion target is heated, but for larger length and time scales and for much higher temperatures than can be simulated using molecular dynamics. Relative to molecular dynamics, the kinetic model greatly extends the temperature regime and the spatiotemporal scales over which we are able to model. In our numerical results we observe hydrogen from the ablator material jetting into the fuel during the early stages of the implosion and compare the relative size of various diffusion components (Fickean diffusion, electrodiffusion, and barodiffusion) that drive this process. We also examine kinetic effects, such as anisotropic distributions and velocity separation, in order to determine when this problem can be described with a hydrodynamic model.

Hard versus soft dynamics for adsorption-desorption kinetics: Exact results in one-dimension.

PubMed

Manzi, S J; Huespe, V J; Belardinelli, R E; Pereyra, V D

2009-11-01

The adsorption-desorption kinetics is discussed in the framework of the kinetic lattice-gas model. The master equation formalism has been introduced to describe the evolution of the system, where the transition probabilities are written as an expansion of the occupation configurations of all neighboring sites. Since the detailed balance principle determines half of the coefficients that arise from the expansion, it is necessary to introduce ad hoc, a dynamic scheme to get the rest of them. Three schemes of the so-called hard dynamics, in which the probability of transition from single site cannot be factored into a part which depends only on the interaction energy and one that only depends on the field energy, and five schemes of the so-called soft dynamics, in which this factorization is possible, were introduced for this purpose. It is observed that for the hard dynamic schemes, the equilibrium and nonequilibrium observables, such as adsorption isotherms, sticking coefficients, and thermal desorption spectra, have a normal or physical sustainable behavior. While for the soft dynamics schemes, with the exception of the transition state theory, the equilibrium and nonequilibrium observables have several problems. Some of them can be regarded as abnormal behavior.

A Joint Model for the Kinetics of CTC Count and PSA Concentration During Treatment in Metastatic Castration-Resistant Prostate Cancer*

PubMed Central

Wilbaux, M; Tod, M; De Bono, J; Lorente, D; Mateo, J; Freyer, G; You, B; Hénin, E

2015-01-01

Assessment of treatment efficacy in metastatic castration-resistant prostate cancer (mCRPC) is limited by frequent nonmeasurable bone metastases. The count of circulating tumor cells (CTCs) is a promising surrogate marker that may replace the widely used prostate-specific antigen (PSA). The purpose of this study was to quantify the dynamic relationships between the longitudinal kinetics of these markers during treatment in patients with mCRPC. Data from 223 patients with mCRPC treated by chemotherapy and/or hormonotherapy were analyzed for up to 6 months of treatment. A semimechanistic model was built, combining the following several pharmacometric advanced features: (1) Kinetic-Pharmacodynamic (K-PD) compartments for treatments (chemotherapy and hormonotherapy); (2) a latent variable linking both marker kinetics; (3) modeling of CTC kinetics with a cell lifespan model; and (4) a negative binomial distribution for the CTC random sampling. Linked with survival, this model would potentially be useful for predicting treatment efficacy during drug development or for therapeutic adjustment in treated patients. PMID:26225253

Non-equilibrium dynamics of artificial quantum matter

NASA Astrophysics Data System (ADS)

Babadi, Mehrtash

The rapid progress of the field of ultracold atoms during the past two decades has set new milestones in our control over matter. By cooling dilute atomic gases and molecules to nano-Kelvin temperatures, novel quantum mechanical states of matter can be realized and studied on a table-top experimental setup while bulk matter can be tailored to faithfully simulate abstract theoretical models. Two of such models which have witnessed significant experimental and theoretical attention are (1) the two-component Fermi gas with resonant s-wave interactions, and (2) the single-component Fermi gas with dipole-dipole interactions. This thesis is devoted to studying the non-equilibrium collective dynamics of these systems using the general framework of quantum kinetic theory. We present a concise review of the utilized mathematical methods in the first two chapters, including the Schwinger-Keldysh formalism of non-equilibrium quantum fields, two-particle irreducible (2PI) effective actions and the framework of quantum kinetic theory. We study the collective dynamics of the dipolar Fermi gas in a quasi-two-dimensional optical trap in chapter 3 and provide a detailed account of its dynamical crossover from the collisionless to the hydrodynamical regime. Chapter 4 is devoted to studying the dynamics of the attractive Fermi gas in the normal phase. Starting from the self-consistent T-matrix (pairing fluctuation) approximation, we systematically derive a set of quantum kinetic equations and show that they provide a globally valid description of the dynamics of the attractive Fermi gas, ranging from the weak-coupling Fermi liquid phase to the intermediate non-Fermi liquid pairing pseudogap regime and finally the strong-coupling Bose liquid phase. The shortcomings of the self-consistent T-matrix approximation in two spatial dimensions are discussed along with a proposal to overcome its unphysical behaviors. The developed kinetic formalism is finally utilized to reproduce and interpret the findings of a recent experiment done on the collective dynamics of trapped two-dimensional ultracold gases.

Kinetics of propagation of the lattice excitation in a swift heavy ion track

NASA Astrophysics Data System (ADS)

Lipp, V. P.; Volkov, A. E.; Sorokin, M. V.; Rethfeld, B.

2011-05-01

In this research we verify the applicability of the temperature and heat diffusion conceptions for the description of subpicosecond lattice excitations in nanometric tracks of swift heavy ions (SHI) decelerated in solids in the electronic stopping regime. The method is based on the molecular dynamics (MD) analysis of temporal evolutions of the local kinetic and configurational temperatures of a lattice. We used solid argon as the model system. MD simulations demonstrated that in a SHI track (a) thermalization of lattice excitations takes time of several picoseconds, and (b) application of the parabolic heat diffusion equations for the description of spatial and temporal propagation of lattice excitations is questionable at least up to 10 ps after the ion passage.

Nonlinear Response of Layer Growth Dynamics in the Mixed Kinetics-Bulk-Transport Regime

NASA Technical Reports Server (NTRS)

Vekilov, Peter G.; Alexander, J. Iwan D.; Rosenberger, Franz

1996-01-01

In situ high-resolution interferometry on horizontal facets of the protein lysozyme reveal that the local growth rate R, vicinal slope p, and tangential (step) velocity v fluctuate by up to 80% of their average values. The time scale of these fluctuations, which occur under steady bulk transport conditions through the formation and decay of step bunches (macrosteps), is of the order of 10 min. The fluctuation amplitude of R increases with growth rate (supersaturation) and crystal size, while the amplitude of the v and p fluctuations changes relatively little. Based on a stability analysis for equidistant step trains in the mixed transport-interface-kinetics regime, we argue that the fluctuations originate from the coupling of bulk transport with nonlinear interface kinetics. Furthermore, step bunches moving across the interface in the direction of or opposite to the buoyancy-driven convective flow increase or decrease in height, respectively. This is in agreement with analytical treatments of the interaction of moving steps with solution flow. Major excursions in growth rate are associated with the formation of lattice defects (striations). We show that, in general, the system-dependent kinetic Peclet number, Pe(sub k) , i.e., the relative weight of bulk transport and interface kinetics in the control of the growth process, governs the step bunching dynamics. Since Pe(sub k) can be modified by either forced solution flow or suppression of buoyancy-driven convection under reduced gravity, this model provides a rationale for the choice of specific transport conditions to minimize the formation of compositional inhomogeneities under steady bulk nutrient crystallization conditions.

Matrix product algorithm for stochastic dynamics on networks applied to nonequilibrium Glauber dynamics

NASA Astrophysics Data System (ADS)

Barthel, Thomas; De Bacco, Caterina; Franz, Silvio

2018-01-01

We introduce and apply an efficient method for the precise simulation of stochastic dynamical processes on locally treelike graphs. Networks with cycles are treated in the framework of the cavity method. Such models correspond, for example, to spin-glass systems, Boolean networks, neural networks, or other technological, biological, and social networks. Building upon ideas from quantum many-body theory, our approach is based on a matrix product approximation of the so-called edge messages—conditional probabilities of vertex variable trajectories. Computation costs and accuracy can be tuned by controlling the matrix dimensions of the matrix product edge messages (MPEM) in truncations. In contrast to Monte Carlo simulations, the algorithm has a better error scaling and works for both single instances as well as the thermodynamic limit. We employ it to examine prototypical nonequilibrium Glauber dynamics in the kinetic Ising model. Because of the absence of cancellation effects, observables with small expectation values can be evaluated accurately, allowing for the study of decay processes and temporal correlations.

Kinetic hindrance of Fe(II) oxidation at alkaline pH and in the presence of nitrate and oxygen in a facultative wastewater stabilization pond.

PubMed

Rockne, Karl J

2007-02-15

To better understand the dynamics of Fe2 + oxidation in facultative wastewater stabilization ponds, water samples from a three-pond system were taken throughout the period of transition from anoxic conditions with high aqueous Fe2 + levels in the early spring to fully aerobic conditions in late spring. Fe2 + levels showed a highly significant correlation with pH but were not correlated with dissolved oxygen (DO). Water column Fe2 + levels were modeled using the kinetic rate law for Fe2 + oxidation of Sung and Morgan.[5] The fitted kinetic coefficients were 5 +/- 3 x 10(6) M(- 2) atm(-1) min(-1); more than six orders of magnitude lower than typically reported. Comparison of four potential Fe redox couples demonstrated that the rhoepsilon was at least 3-4 orders of magnitude higher than would be expected based on internal equilibrium. Surprisingly, measured nitrate and DO (when present) were typically consistent with both nitrate (from denitrification) and DO levels (from aerobic respiration) predicted from equilibrium. Although the hydrous Fe oxide/FeCO3 couple was closest to equilibrium and most consistent with the observed pH dependence (in contrast to predicted lepidocrocite), Fe2 + oxidation is kinetically hindered, resulting in up to 10(7)-fold higher levels than expected based on both kinetic and equilibrium analyses.

Inverse problems and computational cell metabolic models: a statistical approach

NASA Astrophysics Data System (ADS)

Calvetti, D.; Somersalo, E.

2008-07-01

In this article, we give an overview of the Bayesian modelling of metabolic systems at the cellular and subcellular level. The models are based on detailed description of key biochemical reactions occurring in tissue, which may in turn be compartmentalized into cytosol and mitochondria, and of transports between the compartments. The classical deterministic approach which models metabolic systems as dynamical systems with Michaelis-Menten kinetics, is replaced by a stochastic extension where the model parameters are interpreted as random variables with an appropriate probability density. The inverse problem of cell metabolism in this setting consists of estimating the density of the model parameters. After discussing some possible approaches to solving the problem, we address the issue of how to assess the reliability of the predictions of a stochastic model by proposing an output analysis in terms of model uncertainties. Visualization modalities for organizing the large amount of information provided by the Bayesian dynamic sensitivity analysis are also illustrated.

Dynamic flux balancing elucidates NAD(P)H production as limiting response to furfural inhibition in Saccharomyces cerevisiae.

PubMed

Pornkamol, Unrean; Franzen, Carl J

2015-08-01

Achieving efficient and economical lignocellulose-based bioprocess requires a robust organism tolerant to furfural, a major inhibitory compound present in lignocellulosic hydrolysate. The aim of this study was to develop a model that could generate quantitative descriptions of cell metabolism for elucidating the cell's adaptive response to furfural. Such a modelling tool could provide strategies for the design of more robust cells. A dynamic flux balance (dFBA) model of Saccharomyces cerevisiae was created by coupling a kinetic fermentation model with a previously published genome-scale stoichiometric model. The dFBA model was used for studying intracellular and extracellular flux responses to furfural perturbations under steady state and dynamic conditions. The predicted effects of furfural on dynamic flux profiles agreed well with previously published experimental results. The model showed that the yeast cell adjusts its metabolism in response to furfural challenge by increasing fluxes through the pentose phosphate pathway, TCA cycle, and proline and serine biosynthesis in order to meet the high demand of NAD(P)H cofactors. The model described here can be used to aid in systematic optimization of the yeast, as well as of the fermentation process, for efficient lignocellulosic ethanol production. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Correlated receptor transport processes buffer single-cell heterogeneity

PubMed Central

Kallenberger, Stefan M.; Unger, Anne L.; Legewie, Stefan; Lymperopoulos, Konstantinos; Eils, Roland

2017-01-01

Cells typically vary in their response to extracellular ligands. Receptor transport processes modulate ligand-receptor induced signal transduction and impact the variability in cellular responses. Here, we quantitatively characterized cellular variability in erythropoietin receptor (EpoR) trafficking at the single-cell level based on live-cell imaging and mathematical modeling. Using ensembles of single-cell mathematical models reduced parameter uncertainties and showed that rapid EpoR turnover, transport of internalized EpoR back to the plasma membrane, and degradation of Epo-EpoR complexes were essential for receptor trafficking. EpoR trafficking dynamics in adherent H838 lung cancer cells closely resembled the dynamics previously characterized by mathematical modeling in suspension cells, indicating that dynamic properties of the EpoR system are widely conserved. Receptor transport processes differed by one order of magnitude between individual cells. However, the concentration of activated Epo-EpoR complexes was less variable due to the correlated kinetics of opposing transport processes acting as a buffering system. PMID:28945754

Tris(trimethylsilyl)silane as a co-initiator for dental adhesive: Photo-polymerization kinetics and dynamic mechanical property

PubMed Central

Song, Linyong; Ye, Qiang; Ge, Xueping; Misra, Anil; Spencer, Paulette

2017-01-01

Objectives The purpose of this study was to evaluate the polymerization behavior of a model dentin adhesive with tris(trimethylsilyl)silane (TTMSS) as a co-initiator, and to investigate the polymerization kinetics and mechanical properties of copolymers in dry and wet conditions. Methods A co-monomer mixture based on HEMA/BisGMA (45/55, w/w) was used as a model dentin adhesive. The photoinitiator system included camphorquinone (CQ) as the photosensitizer and the co-initiator was ethyl-4-(dimethylamino) benzoate (EDMAB) or TTMSS. Iodonium salt, diphenyliodonium hexafluorophosphate (DPIHP) serving as a catalyst, was selectively added into the adhesive formulations. The control and the experimental formulations were characterized with regard to the degree of conversion (DC) and dynamic mechanical properties under dry and wet conditions. Results In two-component photoinitiator system (CQ/TTMSS), with an increase of TTMSS concentration, the polymerization rate and DC of C═C double bond increased, and showed a dependence on the irradiation time and curing light intensity. The copolymers that contained the three-component photoinitiator system (CQ/TTMSS/DPIHP) showed similar dynamic mechanical properties, under both dry and wet conditions, to the EDMAB-containing system. Significance The DC of formulations using TTMSS as co-initiator showed a strong dependence on irradiation time. With the addition of TTMSS, the maximum polymerization rate can be adjusted and the network structure became more homogenous. The results indicated that the TTMSS could be used as a substitute for amine-type co-initiator in visible-light induced free radical polymerization of methacrylate-based dentin adhesives. PMID:26616688

A pulse radiolysis study of the dynamics of ascorbic acid free radicals within a liposomal environment.

PubMed

Kobayashi, Kazuo; Seike, Yumiko; Saeki, Akinori; Kozawa, Takahiro; Takeuchi, Fusako; Tsubaki, Motonari

2014-10-06

The dynamics of free-radical species in a model cellular system are examined by measuring the formation and decay of ascorbate radicals within a liposome with pulse radiolysis techniques. Upon pulse radiolysis of an N2O-saturated aqueous solution containing ascorbate-loaded liposome vesicles, ascorbate radicals are formed by the reaction of OH(·) radicals with ascorbate in unilamellar vesicles exclusively, irrespective of the presence of vesicle lipids. The radicals are found to decay rapidly compared with the decay kinetics in an aqueous solution. The distinct radical reaction kinetics in the vesicles and in bulk solution are characterized, and the kinetic data are analyzed. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Dynamics in poly vinyl alcohol (PVA) based hydrogel: Neutron scattering study

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

Prabhudesai, S. A., E-mail: swapnil@barc.gov.in; Mitra, S.; Mukhopadhyay, R.

2015-06-24

Results of quasielastic neutron scattering measurements carried out on Poly Vinyl Alcohol (PVA) based hydrogels are reported here. PVA hydrogels are formed using Borax as a cross-linking agent in D{sub 2}O solvent. This synthetic polymer can be used for obtaining the hydrogels with potential use in the field of biomaterials. The aim of this paper is to study the dynamics of polymer chain in the hydrogel since it is known that polymer mobility influences the kinetics of loading and release of drugs. It is found that the dynamics of hydrogen atoms in the polymer chain could be described by amore » model where the diffusion of hydrogen atoms is limited within a spherical volume of radius 3.3 Å. Average diffusivity estimated from the behavior of quasielastic width is found to be 1.2 × 10{sup −5} cm{sup 2}/sec.« less