Reaction-based Model Research Articles

Modeling and designing for nitrogen removal in bioretention basins

The bioretention basin is a type of green infrastructure that treats stormwater runoff. However, there is a limited understanding of its treatment potential with different design configurations and limited capability to model bioretention systems. Current modeling practice fails to represent bacteria-mediated biochemical reactions that remove nitrogen. This study provides a reaction-based model of water quality treatment processes using multiple bacterial Monod kinetics under variably saturated flow conditions to predict the dynamics of nitrogen and organics in a bioretention system. The model was calibrated and validated against concentrations measured during an eight-month field monitoring program. Because the model simulates both basin hydrologic performance and biological treatment performance, it can be used to verify design guidelines by evaluating the response of the system to different design parameters. The model shows that nitrogen removal is enhanced by increasing bioretention basin volume and by setting an optimal value of hydraulic conductivity for subsurface infiltration.

Fabrication of Polyethersulfone/Functionalized MWCNTs Nanocomposite and Investigation its Efficiency as an Adsorbent of Pb(II) Ions

The novel polyethersulfone/ethylenediamine-functionalized multiwall carbon nanotubes (PES/MWCNTs-NH2) nanocomposite was synthesized and introduced as an efficient adsorbent for Pb(II) removal from aqueous solutions. The characterization analyses, including FTIR, TGA, SEM, and EDX, confirmed the successful functionalization of MWCNTs through three steps acidic treatment, acylation with SOCL2, and amine functionalization. The influence of MWCNTs functionalization, pH, stirring speed, contact time, and adsorbent dosage on the Pb(II) adsorption by PES/MWCNTs-NH2 nanocomposite was investigated. The optimum condition was obtained on neutral pH, contact time 10 min, stirring speed 400 rpm, and adsorbent dosage 0.1 g of PES/1% MWCNTs-NH2, which reached the maximum adsorption capacity of 272 mg/g. The equilibrium studies were investigated by consideration of Langmuir, Freundlich, Temkin, and D-R isotherm models, which revealed that Pb(II) adsorption onto PES/MWCNTs-NH2 was performed on a heterogeneous surface with a non-uniform distribution of heat of adsorption. Also, it confirmed that the chemisorption process was favorable. The kinetic studies through pseudo-first-order, pseudo-second-order (as a reaction-based model), and Boyd models (diffusion-based model) showed that the chemisorption adsorption rate was fast, and controlled by film diffusion. Thermodynamic studies indicated that Pb(II) adsorption process onto PES/MWCNTs-NH2 was spontaneous, endothermic, by increasing the randomness of the solid/liquid interface.

Correction to "A Reaction-Based Model of the State Space of Chemical Reaction Systems Enables Efficient Simulations".

Correction to "A Reaction-Based Model of the State Space of Chemical Reaction Systems Enables Efficient Simulations".

CONTROLLING THE CELL CYCLE RESTRICTION SWITCH ACROSS THE INFORMATION GRADIENT

Boolean models represent a drastic simplification of complex biomolecular systems, and yet accurately predict system properties, e.g., effective control strategies. Why is this? Parameter robustness has been highlighted as a general feature of biomolecular systems and may play an important role in the accuracy of Boolean models. We argue here that a useful way to view a system’s controllability properties is through its repertoire of self-sustaining positive circuits (stable motifs). We examine attractor control and self-sustaining circuits within the cell cycle restriction switch, a bistable regulatory circuit that allows or prevents entry into the cell cycle. We explore this system using three models: a previously published Boolean model, a Hill kinetics model that we construct from the Boolean model using the HillCube methodology, and a reaction-based model we construct from the literature. We highlight the robustness of stable motifs across these three levels of modeling detail. We also show how consideration of control-robust regulatory circuits can aid in parameter specification.

A Reaction-Based Model of the State Space of Chemical Reaction Systems Enables Efficient Simulations.

The choice of the state space representation of a system can turn into a prominent advantage or burden in any endeavour to mathematically model dynamical systems since it entails the analytical tractability of the related modelling formalism and the efficiency of the numerical computation. The Reaction-Based Model (RBM) of the state space, which is presented in this article, is a novel formalization of the kinetics of a system of interacting molecules. According to our representation, the state Sμ of a system of M reactions and N molecular species, is identified with the occurrence of the reaction Rμ ( μ = 1, ..., M). The transition between any two states Sμ and Sν is modelled as a first-order reaction Sμ → Sν and described by mass action-like equation for the partial time derivative of the variables P(Sμ, t) and P(Sν, t), which denote the probabilities that the system lies in the two states, respectively. The rate equations for the state probabilities are coupled with those for the abundance of molecular species. Altogether, the rate equations along with the specification of the initial conditions define the Cauchy problem whose solution describes the time-evolution of the system. The RBM has been applied to a typical severely stiff biological case study. The numerical solutions of the system's dynamics turned out to be computationally more efficient and in agreement with the results of the stochastic and hybrid stochastic/deterministic simulation algorithms.

Model-based calibration of reaction-based diesel combustion dynamics

This paper presents a control-oriented, reaction-based diesel combustion model that predicts the time-based rate of combustion, in-cylinder gas temperature, and pressure over one engine cycle. The model, based on the assumption of a homogeneous thermodynamic combustion process, uses a two-step chemical reaction mechanism that consists of six species: diesel fuel (C10.8H18.7), oxygen (O2), carbon dioxide (CO2), water (H2O), nitrogen (N2), and carbon monoxide (CO). The temperature variation rate is calculated based on the rate of change of species concentrations; the heat loss correlation is also used to study the model performance. The accuracy of the model is evaluated using test data from a GM 6.6 L, eight-cylinder Duramax engine. The main contribution is the model calibration under different key operational conditions over a large engine speed and load range as well as different injection timings and exhaust gas recirculation rates by solving the optimal calibration problem. The calibrated reaction-based model accurately predicts the indicated mean effective pressure, while keeping the errors of in-cylinder pressure and temperature small, and, at the same time, significantly reduces the calibration effort, especially when the engine is operated under multiple fuel injection operations compared with Wiebe-based combustion models. The calibrated model parameters have a strong correlation to engine speed, load, and injection timings, and, as a result, a universal parameter calibration structure is proposed for entire operational conditions.

LASSIE: simulating large-scale models of biochemical systems on GPUs

BackgroundMathematical modeling and in silico analysis are widely acknowledged as complementary tools to biological laboratory methods, to achieve a thorough understanding of emergent behaviors of cellular processes in both physiological and perturbed conditions. Though, the simulation of large-scale models—consisting in hundreds or thousands of reactions and molecular species—can rapidly overtake the capabilities of Central Processing Units (CPUs). The purpose of this work is to exploit alternative high-performance computing solutions, such as Graphics Processing Units (GPUs), to allow the investigation of these models at reduced computational costs.ResultsLASSIE is a “black-box” GPU-accelerated deterministic simulator, specifically designed for large-scale models and not requiring any expertise in mathematical modeling, simulation algorithms or GPU programming. Given a reaction-based model of a cellular process, LASSIE automatically generates the corresponding system of Ordinary Differential Equations (ODEs), assuming mass-action kinetics. The numerical solution of the ODEs is obtained by automatically switching between the Runge-Kutta-Fehlberg method in the absence of stiffness, and the Backward Differentiation Formulae of first order in presence of stiffness. The computational performance of LASSIE are assessed using a set of randomly generated synthetic reaction-based models of increasing size, ranging from 64 to 8192 reactions and species, and compared to a CPU-implementation of the LSODA numerical integration algorithm.ConclusionsLASSIE adopts a novel fine-grained parallelization strategy to distribute on the GPU cores all the calculations required to solve the system of ODEs. By virtue of this implementation, LASSIE achieves up to 92× speed-up with respect to LSODA, therefore reducing the running time from approximately 1 month down to 8 h to simulate models consisting in, for instance, four thousands of reactions and species. Notably, thanks to its smaller memory footprint, LASSIE is able to perform fast simulations of even larger models, whereby the tested CPU-implementation of LSODA failed to reach termination. LASSIE is therefore expected to make an important breakthrough in Systems Biology applications, for the execution of faster and in-depth computational analyses of large-scale models of complex biological systems.

Kinetics behavior of methylene blue onto agricultural waste

ABSTRACTIn the present work, investigations on a potential use of agricultural waste for the removal of methylene blue (MB) from wastewater are presented. Adsorption kinetics of MB has been studied using reaction-based and diffusion-based models. Three kinetic models, namely pseudo-first-order, pseudo-second-order, and the Elovich are analyzed at the temperature of 298 K for the reaction-based model. The kinetic studies showed that the data were well described by the pseudo-second-order kinetic model. Intraparticle diffusion, external-film diffusion, and internal-pore diffusion models characterizing MB were obtained. The results suggested that the agricultural waste has a high potential to be used as an effective adsorbent for MB adsorption. Pseudo-first-order, pseudo-second-order, and the Elovich models were employed to describe the desorption mechanism. The experimental results showed that the pseudo-second-order equation is the best model.

Composition Colored Petri Nets for the Refinement of Reaction-based Models

Model refinement is an important step in the model building process. For reaction-based models, data refinement consists in replacing one species with several of its variants in the refined model. We discuss in this paper the implementation of data refinement with Petri nets such that the size of the model (in terms of number of places and transitions) does not increase. We capture the compositional structure of species by introducing a new class of Petri nets, composition Petri nets (ComP-nets), and their colored counterpart, colored composition Petri nets (ComCP-nets). Given a reaction-based model with known compositional structure, represented as a ComP-net, we propose an algorithm for building a ComCP-net which implements the data refinement of the model and has the same network structure as the initial ComP-net.

Marine systems biology.

EDITORIAL article Front. Genet., 13 May 2015Sec. Systems Biology Archive Volume 6 - 2015 | https://doi.org/10.3389/fgene.2015.00181

Performance Evaluation of a Portable Neutron Generator for Prompt Gamma-Ray Applications

Performance of a D–D reaction-based portable pulsed neutron generator model MP320 was evaluated for prompt gamma applications. The operating beam energy and beam current of the MP320 generator were determined through prompt gamma-ray yield measurements from iron. The chlorine prompt gamma-ray yield was also measured from saline water samples containing 1.0–4.0 wt% chlorine to test the neutron flux efficacy of the MP320 generator for prompt gamma applications. The results of the study showed satisfactory performance of the MP320 generator for prompt gamma neutron activation application studies.

Investigation of nutrient feeding strategies in a countercurrent mixed-acid multi-staged fermentation: Development of segregated-nitrogen model

The MixAlco process is a biorefinery based on the production of carboxylic acids via mixed-culture fermentation. Nitrogen is essential for microbial growth and metabolism, and may exist in soluble (e.g., ammonia) or insoluble forms (e.g., cells). Understanding the dynamics of nitrogen flow in a countercurrent fermentation is necessary to develop control strategies to maximize performance. To estimate nitrogen concentration profiles in a four-stage fermentation train, a mass balance-based segregated-nitrogen model was developed, which uses separate balances for solid- and liquid-phase nitrogen with nitrogen reaction flux between phases assumed to be zero. Comparison of predictions with measured nitrogen profiles from five trains, each with a different nutrient contacting pattern, shows the segregated-nitrogen model captures basic behavior and is a reasonable tool for estimating nitrogen profiles. The segregated-nitrogen model may be used to (1) estimate optimal nitrogen loading patterns, (2) develop a reaction-based model, (3) understand influence of model inputs (e.g., operating parameters, feedstock properties, nutrient loading pattern) on the steady-state nitrogen profile, and (4) determine the direction of the nitrogen reaction flux between liquid and solid phases.

Reaction-based modeling of quinone-mediated bacterial iron(III) reduction

This paper presents and validates a new paradigm for modeling complex biogeochemical systems using a diagonalized reaction-based approach. The bioreduction kinetics of hematite (α-Fe 2O 3) by the dissimilatory metal-reducing bacterium (DMRB) Shewanella putrefaciens strain CN32 in the presence of the soluble electron shuttling compound anthraquinone-2,6-disulfonate (AQDS) is used for presentation/validation purposes. Experiments were conducted under nongrowth conditions with H 2 as the electron donor. In the presence of AQDS, both direct biological reduction and indirect chemical reduction of hematite by bioreduced anthrahydroquinone-2,6-disulfonate (AH 2DS) can produce Fe(II). Separate experiments were performed to describe the bioreduction of hematite, bioreduction of AQDS, chemical reduction of hematite by AH 2DS, Fe(II) sorption to hematite, and Fe(II) biosorption to DMRB. The independently determined rate parameters and equilibrium constants were then used to simulate the parallel kinetic reactions of Fe(II) production in the hematite-with-AQDS experiments. Previously determined rate formulations/parameters for the bioreduction of hematite and Fe(II) sorption to hematite were systematically tested by conducting experiments with different initial conditions. As a result, the rate formulation/parameter for hematite bioreduction was not modified, but the rate parameters for Fe(II) sorption to hematite were modified slightly. The hematite bioreduction rate formulation was first-order with respect to hematite ”free“ surface sites and zero-order with respect to DMRB based on experiments conducted with variable concentrations of hematite and DMRB. The AQDS bioreduction rate formulation was first-order with respect to AQDS and first-order with respect to DMRB based on experiments conducted with variable concentrations of AQDS and DMRB. The chemical reduction of hematite by AH 2DS was fast and considered to be an equilibrium reaction. The simulations of hematite-with-AQDS experiments were very sensitive to the equilibrium constant for the hematite-AH 2DS reaction. The model simulated the hematite-with-AQDS experiments well if it was assumed that the ferric oxide “surface” phase was more disordered than pure hematite. This is the first reported study where a diagonalized reaction-based model was used to simulate parallel kinetic reactions based on rate formulations/parameters independently obtained from segregated experiments.

Modeling and measuring biogeochemical reactions: system consistency, data needs, and rate formulations

This paper intends to lay-out a foundation of protocols for planning and analyzing biogeochemical experiments. It presents critical theoretical issues that must be considered for proper application of reaction-based biogeochemical models. The selection of chemical components is not unique and a decomposition of the reaction matrix should be used for formal selection. The decomposition reduces the set of ordinary differential equations governing the production–consumption of chemical species into three subsets of equations: mass action; kinetic-variable; and mass conservation. The consistency of mass conservation equations must be assessed with experimental data before kinetic modeling is initiated. Assumptions regarding equilibrium reactions should also be assessed. For a system with M chemical species involved in N reactions with N I linearly-independent reactions and N E linearly-independent equilibrium reactions, the minimum number of chemical species concentration vs. time curves that must be measured to evaluate the kinetic suite of reactions using a reaction-based model will be ( N I− N E). However, for a partial assessment of system consistency, at least one more species must be measured [i.e. ( N I− N E+1)]. For a complete assessment of system consistency, ( N I− N E+ N C) additional species would have to be measured, where N C is the number of chemical components. Reaction rates for kinetic reactions that are linearly independent of other kinetic reactions can be determined based on only one profile of a kinetic-variable concentration vs. time for each kinetic reaction. Reaction rates for parallel kinetic reactions that are linearly dependent on each other cannot be uniquely segregated when they result in production of the same species, however, they must be included for simulation purposes. Kinetic reactions that are linearly dependent only on equilibrium reactions are redundant and do not have to be modeled. The bioreduction of ferric oxide is used as an example to functionally demonstrate these points, and shows that Henri–Michaelis–Benton–Monod kinetics should be applied with care to coupled abiotic and biotic systems.

Reaction-based model describing competitive sorption and transport of Cd, Zn, and Ni in an acidic soil.

Predicting the mobility of heavy metals in soils requires models that accurately describe metal adsorption in the presence of competing cations. They should also be easily adjustable to specific soil materials and applicable in reactive transport codes. In this study, Cd adsorption to an acidic soil material was investigated over a wide concentration range (10(-8) to 10(-2) M CdCl2) in the presence of different background electrolytes (10(-4) to 10(-2) M CaCl2 or MgCl2 or 0.05 to 0.5 M NaCl). The adsorption experiments were conducted at pH values between 4.6 and 6.5 A reaction-based sorption model was developed using a combination of nonspecific cation exchange reactions and competitive sorption reactions to sites with high affinity for heavy metals. This combined cation exchange/specific sorption (CESS) model accurately described the entire Cd sorption data set. Coupled to a solute transport code, the model accurately predicted Cd breakthrough curves obtained in column transport experiments. The model was further extended to describe competitive sorption and transport of Cd, Zn, and Ni. At pH 4.6, both Zn and Ni exhibited similar sorption and transport behavior as observed for Cd. In all transport experiments conducted under acidic conditions, heavy metal adsorption was shown to be reversible and kinetic effects were negligible within time periods ranging from hours up to four weeks.