Kinetics of nitrate adsorption and reduction by nano-scale zero valent iron (NZVI): Effect of ionic strength and initial pH

DEFF Research Database (Denmark)

Kim, Do-Gun; Hwang, Yuhoon; Shin, Hang-Sik

2016-01-01

Kinetic models for pollutants reduction by Nano-scale Zero Valent Iron (NZVI) were tested in this study to gain a better understanding and description of the reaction. Adsorption kinetic models and a heterogeneous catalytic reaction kinetic equation were proposed for nitrate removal and for ammon...

Experimental kinetic study and modeling of calcium oxide carbonation

International Nuclear Information System (INIS)

Rouchon, L.

2012-01-01

Anthropogenic carbon dioxide (CO 2 ) emissions, major contributors to the greenhouse effect, are considered as the main cause of global warming. So, decrease of CO 2 emitted by large industrial combustion sources or power plants, is an important scientific goal. One of the approaches is based on CO 2 separation and capture from flue gas, followed by sequestration in a wide range of geological formations. In this aim, CO 2 is captured by sorbents like calcium oxide (CaO) in multi-cycle process of carbonation/de-carbonation. However, it was shown that the most important limitations of such process are related to the reversibility of reaction. CaO rapidly loses activity towards CO 2 , so the maximum extent of carbonation decreases as long as the number of cycles increases. In order to well understand the processes and parameters influencing the capture capacity of CaO-based sorbents, it appears important to get details on the kinetic law governing the reaction, which have not been really studied up to now. To investigate this reaction, CaO carbonation kinetics was followed by means of thermogravimetric analysis (TGA) on divided materials. Special care was given to the validation of the usual kinetic assumptions such as steady state and rate-determining step assumptions. The aim was to obtain a model describing the reaction in order to explain the influence of intensive variables such as carbonation temperature and CO 2 partial pressure. TGA curves obtained under isothermal and isobaric conditions showed an induction period linked to the nucleation process and a strong slowing down of the reaction rate once a given fractional conversion was reached. Both phenomena were observed to depend on carbonation temperature and CO 2 partial pressure. To explain these results, the evolution of texture and microstructure of the solid during the reaction was regarded as essential. Reaction at the grain scale induces a volume increase from CaO to CaCO 3 which causes a change in the

The Genome-Scale Integrated Networks in Microorganisms

Directory of Open Access Journals (Sweden)

Tong Hao

2018-02-01

Full Text Available The genome-scale cellular network has become a necessary tool in the systematic analysis of microbes. In a cell, there are several layers (i.e., types of the molecular networks, for example, genome-scale metabolic network (GMN, transcriptional regulatory network (TRN, and signal transduction network (STN. It has been realized that the limitation and inaccuracy of the prediction exist just using only a single-layer network. Therefore, the integrated network constructed based on the networks of the three types attracts more interests. The function of a biological process in living cells is usually performed by the interaction of biological components. Therefore, it is necessary to integrate and analyze all the related components at the systems level for the comprehensively and correctly realizing the physiological function in living organisms. In this review, we discussed three representative genome-scale cellular networks: GMN, TRN, and STN, representing different levels (i.e., metabolism, gene regulation, and cellular signaling of a cell’s activities. Furthermore, we discussed the integration of the networks of the three types. With more understanding on the complexity of microbial cells, the development of integrated network has become an inevitable trend in analyzing genome-scale cellular networks of microorganisms.

Revisiting the density scaling of the non-interacting kinetic energy.

Science.gov (United States)

Borgoo, Alex; Teale, Andrew M; Tozer, David J

2014-07-28

Scaling relations play an important role in the understanding and development of approximate functionals in density functional theory. Recently, a number of these relationships have been redefined in terms of the Kohn-Sham orbitals [Calderín, Phys. Rev. A: At., Mol., Opt. Phys., 2013, 86, 032510]. For density scaling the author proposed a procedure involving a multiplicative scaling of the Kohn-Sham orbitals whilst keeping their occupation numbers fixed. In the present work, the differences between this scaling with fixed occupation numbers and that of previous studies, where the particle number change implied by the scaling was accommodated through the use of the grand canonical ensemble, are examined. We introduce the terms orbital and ensemble density scaling for these approaches, respectively. The natural ambiguity of the density scaling of the non-interacting kinetic energy functional is examined and the ancillary definitions implicit in each approach are highlighted and compared. As a consequence of these differences, Calderín recovered a homogeneity of degree 1 for the non-interacting kinetic energy functional under orbital scaling, contrasting recent work by the present authors [J. Chem. Phys., 2012, 136, 034101] where the functional was found to be inhomogeneous under ensemble density scaling. Furthermore, we show that the orbital scaling result follows directly from the linearity and the single-particle nature of the kinetic energy operator. The inhomogeneity of the non-interacting kinetic energy functional under ensemble density scaling can be quantified by defining an effective homogeneity. This quantity is shown to recover the homogeneity values for important approximate forms that are exact for limiting cases such as the uniform electron gas and one-electron systems. We argue that the ensemble density scaling provides more insight into the development of new functional forms.

LLNL Chemical Kinetics Modeling Group

Energy Technology Data Exchange (ETDEWEB)

Pitz, W J; Westbrook, C K; Mehl, M; Herbinet, O; Curran, H J; Silke, E J

2008-09-24

The LLNL chemical kinetics modeling group has been responsible for much progress in the development of chemical kinetic models for practical fuels. The group began its work in the early 1970s, developing chemical kinetic models for methane, ethane, ethanol and halogenated inhibitors. Most recently, it has been developing chemical kinetic models for large n-alkanes, cycloalkanes, hexenes, and large methyl esters. These component models are needed to represent gasoline, diesel, jet, and oil-sand-derived fuels.

Electron Heating at Kinetic Scales in Magnetosheath Turbulence

International Nuclear Information System (INIS)

Chasapis, Alexandros; Matthaeus, W. H.; Parashar, T. N.; LeContel, O.; Retinò, A.; Breuillard, H.; Khotyaintsev, Y.; Vaivads, A.; Eriksson, E.; Lavraud, B.; Moore, T. E.; Burch, J. L.; Torbert, R. B.; Chutter, M.; Needell, J.; Lindqvist, P.-A.; Marklund, G.; Ergun, R. E.; Goodrich, K. A.; Wilder, F. D.

2017-01-01

We present a statistical study of coherent structures at kinetic scales, using data from the Magnetospheric Multiscale mission in the Earth’s magnetosheath. We implemented the multi-spacecraft partial variance of increments (PVI) technique to detect these structures, which are associated with intermittency at kinetic scales. We examine the properties of the electron heating occurring within such structures. We find that, statistically, structures with a high PVI index are regions of significant electron heating. We also focus on one such structure, a current sheet, which shows some signatures consistent with magnetic reconnection. Strong parallel electron heating coincides with whistler emissions at the edges of the current sheet.

Genome Modeling System: A Knowledge Management Platform for Genomics.

Directory of Open Access Journals (Sweden)

Malachi Griffith

2015-07-01

Full Text Available In this work, we present the Genome Modeling System (GMS, an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395 and matched lymphoblastoid line (HCC1395BL. These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms.

Kinetic model for an up-flow anaerobic packed bed bioreactor: Dairy ...

African Journals Online (AJOL)

Kinetic studies of anaerobic digestion process of cheese whey were conducted in a pilot-scale up-flow anaerobic packed bed bioreactor (UAPB). An influent COD concentration of 59419 mg/l was utilized at steady state condition. Logistic and Monod kinetic models were employed to describe microbial activities of cheese ...

Weakening Gravity on Redshift-Survey Scales with Kinetic Matter Mixing

CERN Document Server

D'Amico, Guido; Mancarella, Michele; Vernizzi, Filippo

2017-01-01

We explore general scalar-tensor models in the presence of a kinetic mixing between matter and the scalar field, which we call Kinetic Matter Mixing. In the frame where gravity is de-mixed from the scalar this is due to disformal couplings of matter species to the gravitational sector, with disformal coefficients that depend on the gradient of the scalar field. In the frame where matter is minimally coupled, it originates from the so-called beyond Horndeski quadratic Lagrangian. We extend the Effective Theory of Interacting Dark Energy by allowing disformal coupling coefficients to depend on the gradient of the scalar field as well. In this very general approach, we derive the conditions to avoid ghost and gradient instabilities and we define Kinetic Matter Mixing independently of the frame metric used to described the action. We study its phenomenological consequences for a $\\Lambda$CDM background evolution, first analytically on small scales. Then, we compute the matter power spectrum and the angular spectr...

IMGMD: A platform for the integration and standardisation of In silico Microbial Genome-scale Metabolic Models.

Science.gov (United States)

Ye, Chao; Xu, Nan; Dong, Chuan; Ye, Yuannong; Zou, Xuan; Chen, Xiulai; Guo, Fengbiao; Liu, Liming

2017-04-07

Genome-scale metabolic models (GSMMs) constitute a platform that combines genome sequences and detailed biochemical information to quantify microbial physiology at the system level. To improve the unity, integrity, correctness, and format of data in published GSMMs, a consensus IMGMD database was built in the LAMP (Linux + Apache + MySQL + PHP) system by integrating and standardizing 328 GSMMs constructed for 139 microorganisms. The IMGMD database can help microbial researchers download manually curated GSMMs, rapidly reconstruct standard GSMMs, design pathways, and identify metabolic targets for strategies on strain improvement. Moreover, the IMGMD database facilitates the integration of wet-lab and in silico data to gain an additional insight into microbial physiology. The IMGMD database is freely available, without any registration requirements, at http://imgmd.jiangnan.edu.cn/database.

An object model for genome information at all levels of resolution

Energy Technology Data Exchange (ETDEWEB)

Honda, S.; Parrott, N.W.; Smith, R.; Lawrence, C.

1993-12-31

An object model for genome data at all levels of resolution is described. The model was derived by considering the requirements for representing genome related objects in three application domains: genome maps, large-scale DNA sequencing, and exploring functional information in gene and protein sequences. The methodology used for the object-oriented analysis is also described.

Genome-based microbial ecology of anammox granules in a full-scale wastewater treatment system

NARCIS (Netherlands)

Speth, D.R.; Zandt, M.H. in 't; Guerrero Cruz, S.; Dutilh, B.E.; Jetten, M.S.M.

2016-01-01

Partial-nitritation anammox (PNA) is a novel wastewater treatment procedure for energy-efficient ammonium removal. Here we use genome-resolved metagenomics to build a genome-based ecological model of the microbial community in a full-scale PNA reactor. Sludge from the bioreactor examined here is

GEMMER: GEnome-wide tool for Multi-scale Modeling data Extraction and Representation for Saccharomyces cerevisiae.

Science.gov (United States)

Mondeel, Thierry D G A; Crémazy, Frédéric; Barberis, Matteo

2018-02-01

Multi-scale modeling of biological systems requires integration of various information about genes and proteins that are connected together in networks. Spatial, temporal and functional information is available; however, it is still a challenge to retrieve and explore this knowledge in an integrated, quick and user-friendly manner. We present GEMMER (GEnome-wide tool for Multi-scale Modelling data Extraction and Representation), a web-based data-integration tool that facilitates high quality visualization of physical, regulatory and genetic interactions between proteins/genes in Saccharomyces cerevisiae. GEMMER creates network visualizations that integrate information on function, temporal expression, localization and abundance from various existing databases. GEMMER supports modeling efforts by effortlessly gathering this information and providing convenient export options for images and their underlying data. GEMMER is freely available at http://gemmer.barberislab.com. Source code, written in Python, JavaScript library D3js, PHP and JSON, is freely available at https://github.com/barberislab/GEMMER. M.Barberis@uva.nl. Supplementary data are available at Bioinformatics online. © The Author(s) 2018. Published by Oxford University Press.

Multi-Spacecraft Study of Kinetic scale Turbulence Using MMS Observations in the Solar Wind

Science.gov (United States)

Chasapis, A.; Matthaeus, W. H.; Parashar, T.; Fuselier, S. A.; Maruca, B.; Burch, J.; Moore, T. E.; Phan, T.; Pollock, C. J.; Gershman, D. J.; Torbert, R. B.; Russell, C. T.; Strangeway, R. J.

2017-12-01

We present a study investigating kinetic scale turbulence in the solar wind. Most previous studies relied on single spacecraft measurements, employing the Taylor hypothesis in order to probe different scales. The small separation of MMS spacecraft, well below the ion inertial scale, allow us for the first time to directly probe turbulent fluctuations at the kinetic range. Using multi-spacecraft measurements, we are able to measure the spatial characteristics of turbulent fluctuations and compare with the traditional Taylor-based single spacecraft approach. Meanwhile, combining observations from Cluster and MMS data we were able to cover a wide range of scales from the inertial range where the turbulent cascade takes place, down to the kinetic range where the energy is eventually dissipated. These observations present an important step in understanding the nature of solar wind turbulence and the processes through which turbulent energy is dissipated into particle heating and acceleration. We compute statistical quantities such as the second order structure function and the scale-dependent kurtosis, along with their dependence on the parameters such as the mean magnetic field direction. Overall, we observe an overall agreement between the single spacecraft and the multi-spacecraft approach. However, a small but significant deviation is observed at the smaller scales near the electron inertial scale. The high values of the scale dependent kurtosis at very small scales, observed via two-point measurements, open up a compelling avenue of investigation for theory and numerical modelling.

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

Science.gov (United States)

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.

Multiscale modeling of three-dimensional genome

Science.gov (United States)

Zhang, Bin; Wolynes, Peter

The genome, the blueprint of life, contains nearly all the information needed to build and maintain an entire organism. A comprehensive understanding of the genome is of paramount interest to human health and will advance progress in many areas, including life sciences, medicine, and biotechnology. The overarching goal of my research is to understand the structure-dynamics-function relationships of the human genome. In this talk, I will be presenting our efforts in moving towards that goal, with a particular emphasis on studying the three-dimensional organization, the structure of the genome with multi-scale approaches. Specifically, I will discuss the reconstruction of genome structures at both interphase and metaphase by making use of data from chromosome conformation capture experiments. Computationally modeling of chromatin fiber at atomistic level from first principles will also be presented as our effort for studying the genome structure from bottom up.

Genome scale engineering techniques for metabolic engineering.

Science.gov (United States)

Liu, Rongming; Bassalo, Marcelo C; Zeitoun, Ramsey I; Gill, Ryan T

2015-11-01

Metabolic engineering has expanded from a focus on designs requiring a small number of genetic modifications to increasingly complex designs driven by advances in genome-scale engineering technologies. Metabolic engineering has been generally defined by the use of iterative cycles of rational genome modifications, strain analysis and characterization, and a synthesis step that fuels additional hypothesis generation. This cycle mirrors the Design-Build-Test-Learn cycle followed throughout various engineering fields that has recently become a defining aspect of synthetic biology. This review will attempt to summarize recent genome-scale design, build, test, and learn technologies and relate their use to a range of metabolic engineering applications. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Contribution to the modelling and multi-scale numerical simulation of kinetic electron transport in hot plasma

International Nuclear Information System (INIS)

Mallet, J.

2012-01-01

This research thesis stands at the crossroad of plasma physics, numerical analysis and applied mathematics. After an introduction presenting the problematic and previous works, the author recalls some basis of classical kinetic models for plasma physics (collisionless kinetic theory and Vlasov equation, collisional kinetic theory with the non-relativistic Maxwell-Fokker-Plansk system) and describes the fundamental properties of the collision operators such as conservation laws, entropy dissipation, and so on. He reports the improvement of a deterministic numerical method to solve the non-relativistic Vlasov-Maxwell system coupled with Fokker-Planck-Landau type operators. The efficiency of each high order scheme is compared. The evolution of the hot spot is studied in the case of thermonuclear reactions in the centre of the pellet in a weakly collisional regime. The author focuses on the simulation of the kinetic electron collisional transport in inertial confinement fusion (ICF) between the laser absorption zone and the ablation front. A new approach is then introduced to reduce the huge computation time obtained with kinetic models. In a last chapter, the kinetic continuous equation in spherical domain is described and a new model is chosen for collisions in order to preserve collision properties

Genome-scale modeling enables metabolic engineering of Saccharomyces cerevisiae for succinic acid production.

Science.gov (United States)

Agren, Rasmus; Otero, José Manuel; Nielsen, Jens

2013-07-01

In this work, we describe the application of a genome-scale metabolic model and flux balance analysis for the prediction of succinic acid overproduction strategies in Saccharomyces cerevisiae. The top three single gene deletion strategies, Δmdh1, Δoac1, and Δdic1, were tested using knock-out strains cultivated anaerobically on glucose, coupled with physiological and DNA microarray characterization. While Δmdh1 and Δoac1 strains failed to produce succinate, Δdic1 produced 0.02 C-mol/C-mol glucose, in close agreement with model predictions (0.03 C-mol/C-mol glucose). Transcriptional profiling suggests that succinate formation is coupled to mitochondrial redox balancing, and more specifically, reductive TCA cycle activity. While far from industrial titers, this proof-of-concept suggests that in silico predictions coupled with experimental validation can be used to identify novel and non-intuitive metabolic engineering strategies.

Genome-Scale, Constraint-Based Modeling of Nitrogen Oxide Fluxes during Coculture of Nitrosomonas europaea and Nitrobacter winogradskyi

Science.gov (United States)

Giguere, Andrew T.; Murthy, Ganti S.; Bottomley, Peter J.; Sayavedra-Soto, Luis A.

2018-01-01

ABSTRACT Nitrification, the aerobic oxidation of ammonia to nitrate via nitrite, emits nitrogen (N) oxide gases (NO, NO2, and N2O), which are potentially hazardous compounds that contribute to global warming. To better understand the dynamics of nitrification-derived N oxide production, we conducted culturing experiments and used an integrative genome-scale, constraint-based approach to model N oxide gas sources and sinks during complete nitrification in an aerobic coculture of two model nitrifying bacteria, the ammonia-oxidizing bacterium Nitrosomonas europaea and the nitrite-oxidizing bacterium Nitrobacter winogradskyi. The model includes biotic genome-scale metabolic models (iFC578 and iFC579) for each nitrifier and abiotic N oxide reactions. Modeling suggested both biotic and abiotic reactions are important sources and sinks of N oxides, particularly under microaerobic conditions predicted to occur in coculture. In particular, integrative modeling suggested that previous models might have underestimated gross NO production during nitrification due to not taking into account its rapid oxidation in both aqueous and gas phases. The integrative model may be found at https://github.com/chaplenf/microBiome-v2.1. IMPORTANCE Modern agriculture is sustained by application of inorganic nitrogen (N) fertilizer in the form of ammonium (NH4+). Up to 60% of NH4+-based fertilizer can be lost through leaching of nitrifier-derived nitrate (NO3−), and through the emission of N oxide gases (i.e., nitric oxide [NO], N dioxide [NO2], and nitrous oxide [N2O] gases), the latter being a potent greenhouse gas. Our approach to modeling of nitrification suggests that both biotic and abiotic mechanisms function as important sources and sinks of N oxides during microaerobic conditions and that previous models might have underestimated gross NO production during nitrification. PMID:29577088

Genome-Scale, Constraint-Based Modeling of Nitrogen Oxide Fluxes during Coculture of Nitrosomonas europaea and Nitrobacter winogradskyi.

Science.gov (United States)

Mellbye, Brett L; Giguere, Andrew T; Murthy, Ganti S; Bottomley, Peter J; Sayavedra-Soto, Luis A; Chaplen, Frank W R

2018-01-01

Nitrification, the aerobic oxidation of ammonia to nitrate via nitrite, emits nitrogen (N) oxide gases (NO, NO 2 , and N 2 O), which are potentially hazardous compounds that contribute to global warming. To better understand the dynamics of nitrification-derived N oxide production, we conducted culturing experiments and used an integrative genome-scale, constraint-based approach to model N oxide gas sources and sinks during complete nitrification in an aerobic coculture of two model nitrifying bacteria, the ammonia-oxidizing bacterium Nitrosomonas europaea and the nitrite-oxidizing bacterium Nitrobacter winogradskyi . The model includes biotic genome-scale metabolic models (iFC578 and iFC579) for each nitrifier and abiotic N oxide reactions. Modeling suggested both biotic and abiotic reactions are important sources and sinks of N oxides, particularly under microaerobic conditions predicted to occur in coculture. In particular, integrative modeling suggested that previous models might have underestimated gross NO production during nitrification due to not taking into account its rapid oxidation in both aqueous and gas phases. The integrative model may be found at https://github.com/chaplenf/microBiome-v2.1. IMPORTANCE Modern agriculture is sustained by application of inorganic nitrogen (N) fertilizer in the form of ammonium (NH 4 + ). Up to 60% of NH 4 + -based fertilizer can be lost through leaching of nitrifier-derived nitrate (NO 3 - ), and through the emission of N oxide gases (i.e., nitric oxide [NO], N dioxide [NO 2 ], and nitrous oxide [N 2 O] gases), the latter being a potent greenhouse gas. Our approach to modeling of nitrification suggests that both biotic and abiotic mechanisms function as important sources and sinks of N oxides during microaerobic conditions and that previous models might have underestimated gross NO production during nitrification.

Topological and kinetic determinants of the modal matrices of dynamic models of metabolism.

Directory of Open Access Journals (Sweden)

Bin Du

Full Text Available Large-scale kinetic models of metabolism are becoming increasingly comprehensive and accurate. A key challenge is to understand the biochemical basis of the dynamic properties of these models. Linear analysis methods are well-established as useful tools for characterizing the dynamic response of metabolic networks. Central to linear analysis methods are two key matrices: the Jacobian matrix (J and the modal matrix (M-1 arising from its eigendecomposition. The modal matrix M-1 contains dynamically independent motions of the kinetic model near a reference state, and it is sparse in practice for metabolic networks. However, connecting the structure of M-1 to the kinetic properties of the underlying reactions is non-trivial. In this study, we analyze the relationship between J, M-1, and the kinetic properties of the underlying network for kinetic models of metabolism. Specifically, we describe the origin of mode sparsity structure based on features of the network stoichiometric matrix S and the reaction kinetic gradient matrix G. First, we show that due to the scaling of kinetic parameters in real networks, diagonal dominance occurs in a substantial fraction of the rows of J, resulting in simple modal structures with clear biological interpretations. Then, we show that more complicated modes originate from topologically-connected reactions that have similar reaction elasticities in G. These elasticities represent dynamic equilibrium balances within reactions and are key determinants of modal structure. The work presented should prove useful towards obtaining an understanding of the dynamics of kinetic models of metabolism, which are rooted in the network structure and the kinetic properties of reactions.

Evaluation of a Genome-Scale In Silico Metabolic Model for Geobacter metallireducens by Using Proteomic Data from a Field Biostimulation Experiment

Science.gov (United States)

Fang, Yilin; Yabusaki, Steven B.; Lipton, Mary S.; Long, Philip E.

2012-01-01

Accurately predicting the interactions between microbial metabolism and the physical subsurface environment is necessary to enhance subsurface energy development, soil and groundwater cleanup, and carbon management. This study was an initial attempt to confirm the metabolic functional roles within an in silico model using environmental proteomic data collected during field experiments. Shotgun global proteomics data collected during a subsurface biostimulation experiment were used to validate a genome-scale metabolic model of Geobacter metallireducens—specifically, the ability of the metabolic model to predict metal reduction, biomass yield, and growth rate under dynamic field conditions. The constraint-based in silico model of G. metallireducens relates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes. Proteomic analysis showed that 180 of the 637 G. metallireducens proteins detected during the 2008 experiment were associated with specific metabolic reactions in the in silico model. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through the in silico model reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low abundances of proteins associated with amino acid transport and metabolism, revealed pathways or flux constraints in the in silico model that could be updated to more accurately predict metabolic processes that occur in the subsurface environment. PMID:23042184

Enumeration of smallest intervention strategies in genome-scale metabolic networks.

Directory of Open Access Journals (Sweden)

Axel von Kamp

2014-01-01

Full Text Available One ultimate goal of metabolic network modeling is the rational redesign of biochemical networks to optimize the production of certain compounds by cellular systems. Although several constraint-based optimization techniques have been developed for this purpose, methods for systematic enumeration of intervention strategies in genome-scale metabolic networks are still lacking. In principle, Minimal Cut Sets (MCSs; inclusion-minimal combinations of reaction or gene deletions that lead to the fulfilment of a given intervention goal provide an exhaustive enumeration approach. However, their disadvantage is the combinatorial explosion in larger networks and the requirement to compute first the elementary modes (EMs which itself is impractical in genome-scale networks. We present MCSEnumerator, a new method for effective enumeration of the smallest MCSs (with fewest interventions in genome-scale metabolic network models. For this we combine two approaches, namely (i the mapping of MCSs to EMs in a dual network, and (ii a modified algorithm by which shortest EMs can be effectively determined in large networks. In this way, we can identify the smallest MCSs by calculating the shortest EMs in the dual network. Realistic application examples demonstrate that our algorithm is able to list thousands of the most efficient intervention strategies in genome-scale networks for various intervention problems. For instance, for the first time we could enumerate all synthetic lethals in E.coli with combinations of up to 5 reactions. We also applied the new algorithm exemplarily to compute strain designs for growth-coupled synthesis of different products (ethanol, fumarate, serine by E.coli. We found numerous new engineering strategies partially requiring less knockouts and guaranteeing higher product yields (even without the assumption of optimal growth than reported previously. The strength of the presented approach is that smallest intervention strategies can be

Chemical kinetics and combustion modelling with CFX 4

Energy Technology Data Exchange (ETDEWEB)

Stopford, P [AEA Technology, Computational Fluid Dynamics Services Harwell, Oxfordshire (United Kingdom)

1998-12-31

The presentation describes some recent developments in combustion and kinetics models used in the CFX software of AEA Technology. Three topics are highlighted: the development of coupled solvers in a traditional `SIMPLE`-based CFD code, the use of detailed chemical kinetics mechanism via `look-up` tables and the application of CFD to large-scale multi-burner combustion plant. The aim is identify those physical approximations and numerical methods that are likely to be most useful in the future and those areas where further developments are required. (author) 6 refs.

Chemical kinetics and combustion modelling with CFX 4

Energy Technology Data Exchange (ETDEWEB)

Stopford, P. [AEA Technology, Computational Fluid Dynamics Services Harwell, Oxfordshire (United Kingdom)

1997-12-31

The presentation describes some recent developments in combustion and kinetics models used in the CFX software of AEA Technology. Three topics are highlighted: the development of coupled solvers in a traditional `SIMPLE`-based CFD code, the use of detailed chemical kinetics mechanism via `look-up` tables and the application of CFD to large-scale multi-burner combustion plant. The aim is identify those physical approximations and numerical methods that are likely to be most useful in the future and those areas where further developments are required. (author) 6 refs.

Toward the automated generation of genome-scale metabolic networks in the SEED.

Science.gov (United States)

DeJongh, Matthew; Formsma, Kevin; Boillot, Paul; Gould, John; Rycenga, Matthew; Best, Aaron

2007-04-26

Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis). We have implemented our tools and database within the SEED, an open-source software environment for comparative genome annotation and analysis. Our method sets the

Toward the automated generation of genome-scale metabolic networks in the SEED

Directory of Open Access Journals (Sweden)

Gould John

2007-04-01

Full Text Available Abstract Background Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. Results We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis. We have implemented our tools and database within the SEED, an open-source software environment for comparative

Analysis of Piscirickettsia salmonis Metabolism Using Genome-Scale Reconstruction, Modeling, and Testing

Directory of Open Access Journals (Sweden)

María P. Cortés

2017-12-01

Full Text Available Piscirickettsia salmonis is an intracellular bacterial fish pathogen that causes piscirickettsiosis, a disease with highly adverse impact in the Chilean salmon farming industry. The development of effective treatment and control methods for piscireckttsiosis is still a challenge. To meet it the number of studies on P. salmonis has grown in the last couple of years but many aspects of the pathogen’s biology are still poorly understood. Studies on its metabolism are scarce and only recently a metabolic model for reference strain LF-89 was developed. We present a new genome-scale model for P. salmonis LF-89 with more than twice as many genes as in the previous model and incorporating specific elements of the fish pathogen metabolism. Comparative analysis with models of different bacterial pathogens revealed a lower flexibility in P. salmonis metabolic network. Through constraint-based analysis, we determined essential metabolites required for its growth and showed that it can benefit from different carbon sources tested experimentally in new defined media. We also built an additional model for strain A1-15972, and together with an analysis of P. salmonis pangenome, we identified metabolic features that differentiate two main species clades. Both models constitute a knowledge-base for P. salmonis metabolism and can be used to guide the efficient culture of the pathogen and the identification of specific drug targets.

Kinetics model development of cocoa bean fermentation

Science.gov (United States)

Kresnowati, M. T. A. P.; Gunawan, Agus Yodi; Muliyadini, Winny

2015-12-01

Although Indonesia is one of the biggest cocoa beans producers in the world, Indonesian cocoa beans are oftenly of low quality and thereby frequently priced low in the world market. In order to improve the quality, adequate post-harvest cocoa processing techniques are required. Fermentation is the vital stage in series of cocoa beans post harvest processing which could improve the quality of cocoa beans, in particular taste, aroma, and colours. During the fermentation process, combination of microbes grow producing metabolites that serve as the precursors for cocoa beans flavour. Microbial composition and thereby their activities will affect the fermentation performance and influence the properties of cocoa beans. The correlation could be reviewed using a kinetic model that includes unstructured microbial growth, substrate utilization and metabolic product formation. The developed kinetic model could be further used to design cocoa bean fermentation process to meet the expected quality. Further the development of kinetic model of cocoa bean fermentation also serve as a good case study of mixed culture solid state fermentation, that has rarely been studied. This paper presents the development of a kinetic model for solid-state cocoa beans fermentation using an empirical approach. Series of lab scale cocoa bean fermentations, either natural fermentations without starter addition or fermentations with mixed yeast and lactic acid bacteria starter addition, were used for model parameters estimation. The results showed that cocoa beans fermentation can be modelled mathematically and the best model included substrate utilization, microbial growth, metabolites production and its transport. Although the developed model still can not explain the dynamics in microbial population, this model can sufficiently explained the observed changes in sugar concentration as well as metabolic products in the cocoa bean pulp.

Global fully kinetic models of planetary magnetospheres with iPic3D

Science.gov (United States)

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 ar

Genome-Scale Analysis of Translation Elongation with a Ribosome Flow Model

Science.gov (United States)

Meilijson, Isaac; Kupiec, Martin; Ruppin, Eytan

2011-01-01

We describe the first large scale analysis of gene translation that is based on a model that takes into account the physical and dynamical nature of this process. The Ribosomal Flow Model (RFM) predicts fundamental features of the translation process, including translation rates, protein abundance levels, ribosomal densities and the relation between all these variables, better than alternative (‘non-physical’) approaches. In addition, we show that the RFM can be used for accurate inference of various other quantities including genes' initiation rates and translation costs. These quantities could not be inferred by previous predictors. We find that increasing the number of available ribosomes (or equivalently the initiation rate) increases the genomic translation rate and the mean ribosome density only up to a certain point, beyond which both saturate. Strikingly, assuming that the translation system is tuned to work at the pre-saturation point maximizes the predictive power of the model with respect to experimental data. This result suggests that in all organisms that were analyzed (from bacteria to Human), the global initiation rate is optimized to attain the pre-saturation point. The fact that similar results were not observed for heterologous genes indicates that this feature is under selection. Remarkably, the gap between the performance of the RFM and alternative predictors is strikingly large in the case of heterologous genes, testifying to the model's promising biotechnological value in predicting the abundance of heterologous proteins before expressing them in the desired host. PMID:21909250

Multi-scale structural community organisation of the human genome.

Science.gov (United States)

Boulos, Rasha E; Tremblay, Nicolas; Arneodo, Alain; Borgnat, Pierre; Audit, Benjamin

2017-04-11

Structural interaction frequency matrices between all genome loci are now experimentally achievable thanks to high-throughput chromosome conformation capture technologies. This ensues a new methodological challenge for computational biology which consists in objectively extracting from these data the structural motifs characteristic of genome organisation. We deployed the fast multi-scale community mining algorithm based on spectral graph wavelets to characterise the networks of intra-chromosomal interactions in human cell lines. We observed that there exist structural domains of all sizes up to chromosome length and demonstrated that the set of structural communities forms a hierarchy of chromosome segments. Hence, at all scales, chromosome folding predominantly involves interactions between neighbouring sites rather than the formation of links between distant loci. Multi-scale structural decomposition of human chromosomes provides an original framework to question structural organisation and its relationship to functional regulation across the scales. By construction the proposed methodology is independent of the precise assembly of the reference genome and is thus directly applicable to genomes whose assembly is not fully determined.

The fractional diffusion limit of a kinetic model with biochemical pathway

Science.gov (United States)

Perthame, Benoît; Sun, Weiran; Tang, Min

2018-06-01

Kinetic-transport equations that take into account the intracellular pathways are now considered as the correct description of bacterial chemotaxis by run and tumble. Recent mathematical studies have shown their interest and their relations to more standard models. Macroscopic equations of Keller-Segel type have been derived using parabolic scaling. Due to the randomness of receptor methylation or intracellular chemical reactions, noise occurs in the signaling pathways and affects the tumbling rate. Then comes the question to understand the role of an internal noise on the behavior of the full population. In this paper we consider a kinetic model for chemotaxis which includes biochemical pathway with noises. We show that under proper scaling and conditions on the tumbling frequency as well as the form of noise, fractional diffusion can arise in the macroscopic limits of the kinetic equation. This gives a new mathematical theory about how long jumps can be due to the internal noise of the bacteria.

Kinetic modelling and characterization of microbial community present in a full-scale UASB reactor treating brewery effluent.

Science.gov (United States)

Enitan, Abimbola M; Kumari, Sheena; Swalaha, Feroz M; Adeyemo, J; Ramdhani, Nishani; Bux, Faizal

2014-02-01

The performance of a full-scale upflow anaerobic sludge blanket (UASB) reactor treating brewery wastewater was investigated by microbial analysis and kinetic modelling. The microbial community present in the granular sludge was detected using fluorescent in situ hybridization (FISH) and further confirmed using polymerase chain reaction. A group of 16S rRNA based fluorescent probes and primers targeting Archaea and Eubacteria were selected for microbial analysis. FISH results indicated the presence and dominance of a significant amount of Eubacteria and diverse group of methanogenic Archaea belonging to the order Methanococcales, Methanobacteriales, and Methanomicrobiales within in the UASB reactor. The influent brewery wastewater had a relatively high amount of volatile fatty acids chemical oxygen demand (COD), 2005 mg/l and the final COD concentration of the reactor was 457 mg/l. The biogas analysis showed 60-69% of methane, confirming the presence and activities of methanogens within the reactor. Biokinetics of the degradable organic substrate present in the brewery wastewater was further explored using Stover and Kincannon kinetic model, with the aim of predicting the final effluent quality. The maximum utilization rate constant U max and the saturation constant (K(B)) in the model were estimated as 18.51 and 13.64 g/l/day, respectively. The model showed an excellent fit between the predicted and the observed effluent COD concentrations. Applicability of this model to predict the effluent quality of the UASB reactor treating brewery wastewater was evident from the regression analysis (R(2) = 0.957) which could be used for optimizing the reactor performance.

iCN718, an Updated and Improved Genome-Scale Metabolic Network Reconstruction of Acinetobacter baumannii AYE.

Science.gov (United States)

Norsigian, Charles J; Kavvas, Erol; Seif, Yara; Palsson, Bernhard O; Monk, Jonathan M

2018-01-01

Acinetobacter baumannii has become an urgent clinical threat due to the recent emergence of multi-drug resistant strains. There is thus a significant need to discover new therapeutic targets in this organism. One means for doing so is through the use of high-quality genome-scale reconstructions. Well-curated and accurate genome-scale models (GEMs) of A. baumannii would be useful for improving treatment options. We present an updated and improved genome-scale reconstruction of A. baumannii AYE, named iCN718, that improves and standardizes previous A. baumannii AYE reconstructions. iCN718 has 80% accuracy for predicting gene essentiality data and additionally can predict large-scale phenotypic data with as much as 89% accuracy, a new capability for an A. baumannii reconstruction. We further demonstrate that iCN718 can be used to analyze conserved metabolic functions in the A. baumannii core genome and to build strain-specific GEMs of 74 other A. baumannii strains from genome sequence alone. iCN718 will serve as a resource to integrate and synthesize new experimental data being generated for this urgent threat pathogen.

Kinetics of corrosion products release from nickel-base alloys corroding in primary water conditions. A new modeling of release

International Nuclear Information System (INIS)

Carrette, F.; Guinard, L.; Pieraggi, B.

2002-01-01

The radioactivity in the primary circuit arises mainly from the activation of corrosion products in the core of pressurised water reactors; corrosion products dissolve from the oxide scales developed on steam generator tubes of alloy 690. The controlling and modelling of this process require a detailed knowledge of the microstructure and chemical composition of oxide scales as well as the kinetics of their corrosion and dissolution. Alloy 690 was studied as tubes and sheets, with three various surface states (as-received, cold-worked, electropolished). Corrosion tests were performed at 325 C and 155 bar in primary water conditions (B/Li - 1000/2 ppm, [H 2 ] 30 cm 3 .kg -1 TPN, [O 2 ] < 5 ppb); test durations ranged between 24 and 2160 hours. Corrosion tests in the TITANE loop provided mainly corrosion and oxidation kinetics, and tests in the BOREAL loop yielded release kinetics. This study revealed asymptotic type kinetics. Characterisation of the oxide scales grown in representative conditions of the primary circuit was performed by several techniques (SEM, TEM, SIMS, XPS, GIXRD). These analyses revealed the essential role of the fine grained cold-worked scale present on as-received and cold-worked materials. This scale controls the corrosion and release phenomena. The kinetic study and the characterisation of the oxide scales contributed to the modelling of the corrosion/release process. A growth/dissolution model was proposed for corrosion product scales grown in non-saturated dynamic fluid. This model provided the temporal evolution of oxide scales and release kinetics for different species (Fe, Ni, Cr). The model was validated for several surface states and several alloys. (authors)

Large-scale genomic 2D visualization reveals extensive CG-AT skew correlation in bird genomes

Directory of Open Access Journals (Sweden)

Deng Xuemei

2007-11-01

Full Text Available Abstract Background Bird genomes have very different compositional structure compared with other warm-blooded animals. The variation in the base skew rules in the vertebrate genomes remains puzzling, but it must relate somehow to large-scale genome evolution. Current research is inclined to relate base skew with mutations and their fixation. Here we wish to explore base skew correlations in bird genomes, to develop methods for displaying and quantifying such correlations at different scales, and to discuss possible explanations for the peculiarities of the bird genomes in skew correlation. Results We have developed a method called Base Skew Double Triangle (BSDT for exhibiting the genome-scale change of AT/CG skew as a two-dimensional square picture, showing base skews at many scales simultaneously in a single image. By this method we found that most chicken chromosomes have high AT/CG skew correlation (symmetry in 2D picture, except for some microchromosomes. No other organisms studied (18 species show such high skew correlations. This visualized high correlation was validated by three kinds of quantitative calculations with overlapping and non-overlapping windows, all indicating that chicken and birds in general have a special genome structure. Similar features were also found in some of the mammal genomes, but clearly much weaker than in chickens. We presume that the skew correlation feature evolved near the time that birds separated from other vertebrate lineages. When we eliminated the repeat sequences from the genomes, the AT and CG skews correlation increased for some mammal genomes, but were still clearly lower than in chickens. Conclusion Our results suggest that BSDT is an expressive visualization method for AT and CG skew and enabled the discovery of the very high skew correlation in bird genomes; this peculiarity is worth further study. Computational analysis indicated that this correlation might be a compositional characteristic

Noise analysis of genome-scale protein synthesis using a discrete computational model of translation

Energy Technology Data Exchange (ETDEWEB)

Racle, Julien; Hatzimanikatis, Vassily, E-mail: vassily.hatzimanikatis@epfl.ch [Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne (Switzerland); Swiss Institute of Bioinformatics (SIB), CH-1015 Lausanne (Switzerland); Stefaniuk, Adam Jan [Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne (Switzerland)

2015-07-28

Noise in genetic networks has been the subject of extensive experimental and computational studies. However, very few of these studies have considered noise properties using mechanistic models that account for the discrete movement of ribosomes and RNA polymerases along their corresponding templates (messenger RNA (mRNA) and DNA). The large size of these systems, which scales with the number of genes, mRNA copies, codons per mRNA, and ribosomes, is responsible for some of the challenges. Additionally, one should be able to describe the dynamics of ribosome exchange between the free ribosome pool and those bound to mRNAs, as well as how mRNA species compete for ribosomes. We developed an efficient algorithm for stochastic simulations that addresses these issues and used it to study the contribution and trade-offs of noise to translation properties (rates, time delays, and rate-limiting steps). The algorithm scales linearly with the number of mRNA copies, which allowed us to study the importance of genome-scale competition between mRNAs for the same ribosomes. We determined that noise is minimized under conditions maximizing the specific synthesis rate. Moreover, sensitivity analysis of the stochastic system revealed the importance of the elongation rate in the resultant noise, whereas the translation initiation rate constant was more closely related to the average protein synthesis rate. We observed significant differences between our results and the noise properties of the most commonly used translation models. Overall, our studies demonstrate that the use of full mechanistic models is essential for the study of noise in translation and transcription.

Large-scale chromosome folding versus genomic DNA sequences: A discrete double Fourier transform technique.

Science.gov (United States)

Chechetkin, V R; Lobzin, V V

2017-08-07

Using state-of-the-art techniques combining imaging methods and high-throughput genomic mapping tools leaded to the significant progress in detailing chromosome architecture of various organisms. However, a gap still remains between the rapidly growing structural data on the chromosome folding and the large-scale genome organization. Could a part of information on the chromosome folding be obtained directly from underlying genomic DNA sequences abundantly stored in the databanks? To answer this question, we developed an original discrete double Fourier transform (DDFT). DDFT serves for the detection of large-scale genome regularities associated with domains/units at the different levels of hierarchical chromosome folding. The method is versatile and can be applied to both genomic DNA sequences and corresponding physico-chemical parameters such as base-pairing free energy. The latter characteristic is closely related to the replication and transcription and can also be used for the assessment of temperature or supercoiling effects on the chromosome folding. We tested the method on the genome of E. coli K-12 and found good correspondence with the annotated domains/units established experimentally. As a brief illustration of further abilities of DDFT, the study of large-scale genome organization for bacteriophage PHIX174 and bacterium Caulobacter crescentus was also added. The combined experimental, modeling, and bioinformatic DDFT analysis should yield more complete knowledge on the chromosome architecture and genome organization. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimal knockout strategies in genome-scale metabolic networks using particle swarm optimization.

Science.gov (United States)

Nair, Govind; Jungreuthmayer, Christian; Zanghellini, Jürgen

2017-02-01

Knockout strategies, particularly the concept of constrained minimal cut sets (cMCSs), are an important part of the arsenal of tools used in manipulating metabolic networks. Given a specific design, cMCSs can be calculated even in genome-scale networks. We would however like to find not only the optimal intervention strategy for a given design but the best possible design too. Our solution (PSOMCS) is to use particle swarm optimization (PSO) along with the direct calculation of cMCSs from the stoichiometric matrix to obtain optimal designs satisfying multiple objectives. To illustrate the working of PSOMCS, we apply it to a toy network. Next we show its superiority by comparing its performance against other comparable methods on a medium sized E. coli core metabolic network. PSOMCS not only finds solutions comparable to previously published results but also it is orders of magnitude faster. Finally, we use PSOMCS to predict knockouts satisfying multiple objectives in a genome-scale metabolic model of E. coli and compare it with OptKnock and RobustKnock. PSOMCS finds competitive knockout strategies and designs compared to other current methods and is in some cases significantly faster. It can be used in identifying knockouts which will force optimal desired behaviors in large and genome scale metabolic networks. It will be even more useful as larger metabolic models of industrially relevant organisms become available.

Kinetic modeling of Nernst effect in magnetized hohlraums

OpenAIRE

Joglekar, A. S.; Ridgers, Christopher Paul; Kingham, R J; Thomas, A. G. R.

2016-01-01

We present nanosecond time-scale Vlasov-Fokker-Planck-Maxwell modeling of magnetized plasma transport and dynamics in a hohlraum with an applied external magnetic field, under conditions similar to recent experiments. Self-consistent modeling of the kinetic electron momentum equation allows for a complete treatment of the heat flow equation and Ohm's law, including Nernst advection of magnetic fields. In addition to showing the prevalence of nonlocal behavior, we demonstrate that effects such...

Kinetic modelling of enzymatic starch hydrolysis

NARCIS (Netherlands)

Bednarska, K.A.

2015-01-01

Kinetic modelling of enzymatic starch hydrolysis – a summary

K.A. Bednarska

The dissertation entitled ‘Kinetic modelling of enzymatic starch hydrolysis’ describes the enzymatic hydrolysis and kinetic modelling of liquefaction and saccharification of wheat starch.

Process Simulation for the Design and Scale Up of Heterogeneous Catalytic Process: Kinetic Modelling Issues

Directory of Open Access Journals (Sweden)

Antonio Tripodi

2017-05-01

Full Text Available Process simulation represents an important tool for plant design and optimization, either applied to well established or to newly developed processes. Suitable thermodynamic packages should be selected in order to properly describe the behavior of reactors and unit operations and to precisely define phase equilibria. Moreover, a detailed and representative kinetic scheme should be available to predict correctly the dependence of the process on its main variables. This review points out some models and methods for kinetic analysis specifically applied to the simulation of catalytic processes, as a basis for process design and optimization. Attention is paid also to microkinetic modelling and to the methods based on first principles, to elucidate mechanisms and independently calculate thermodynamic and kinetic parameters. Different case studies support the discussion. At first, we have selected two basic examples from the industrial chemistry practice, e.g., ammonia and methanol synthesis, which may be described through a relatively simple reaction pathway and the relative available kinetic scheme. Then, a more complex reaction network is deeply discussed to define the conversion of bioethanol into syngas/hydrogen or into building blocks, such as ethylene. In this case, lumped kinetic schemes completely fail the description of process behavior. Thus, in this case, more detailed—e.g., microkinetic—schemes should be available to implement into the simulator. However, the correct definition of all the kinetic data when complex microkinetic mechanisms are used, often leads to unreliable, highly correlated parameters. In such cases, greater effort to independently estimate some relevant kinetic/thermodynamic data through Density Functional Theory (DFT/ab initio methods may be helpful to improve process description.

Exploiting linkage disequilibrium in statistical modelling in quantitative genomics

DEFF Research Database (Denmark)

Wang, Lei

Alleles at two loci are said to be in linkage disequilibrium (LD) when they are correlated or statistically dependent. Genomic prediction and gene mapping rely on the existence of LD between gentic markers and causul variants of complex traits. In the first part of the thesis, a novel method...... to quantify and visualize local variation in LD along chromosomes in describet, and applied to characterize LD patters at the local and genome-wide scale in three Danish pig breeds. In the second part, different ways of taking LD into account in genomic prediction models are studied. One approach is to use...... the recently proposed antedependence models, which treat neighbouring marker effects as correlated; another approach involves use of haplotype block information derived using the program Beagle. The overall conclusion is that taking LD information into account in genomic prediction models potentially improves...

An efficient approach to bioconversion kinetic model generation based on automated microscale experimentation integrated with model driven experimental design

DEFF Research Database (Denmark)

Chen, B. H.; Micheletti, M.; Baganz, F.

2009-01-01

-erythrulose. Experiments were performed using automated microwell studies at the 150 or 800 mu L scale. The derived kinetic parameters were then verified in a second round of experiments where model predictions showed excellent agreement with experimental data obtained under conditions not included in the original......Reliable models of enzyme kinetics are required for the effective design of bioconversion processes. Kinetic expressions of the enzyme-catalysed reaction rate however, are frequently complex and establishing accurate values of kinetic parameters normally requires a large number of experiments....... These can be both time consuming and expensive when working with the types of non-natural chiral intermediates important in pharmaceutical syntheses. This paper presents ail automated microscale approach to the rapid and cost effective generation of reliable kinetic models useful for bioconversion process...

Kinetic modelling of anaerobic hydrolysis of solid wastes, including disintegration processes

Energy Technology Data Exchange (ETDEWEB)

García-Gen, Santiago [Department of Chemical Engineering, Institute of Technology, University of Santiago de Compostela, 15782 Santiago de Compostela (Spain); Sousbie, Philippe; Rangaraj, Ganesh [INRA, UR50, Laboratoire de Biotechnologie de l’Environnement, Avenue des Etangs, Narbonne F-11100 (France); Lema, Juan M. [Department of Chemical Engineering, Institute of Technology, University of Santiago de Compostela, 15782 Santiago de Compostela (Spain); Rodríguez, Jorge, E-mail: jrodriguez@masdar.ac.ae [Department of Chemical Engineering, Institute of Technology, University of Santiago de Compostela, 15782 Santiago de Compostela (Spain); Institute Centre for Water and Environment (iWater), Masdar Institute of Science and Technology, PO Box 54224 Abu Dhabi (United Arab Emirates); Steyer, Jean-Philippe; Torrijos, Michel [INRA, UR50, Laboratoire de Biotechnologie de l’Environnement, Avenue des Etangs, Narbonne F-11100 (France)

2015-01-15

Highlights: • Fractionation of solid wastes into readily and slowly biodegradable fractions. • Kinetic coefficients estimation from mono-digestion batch assays. • Validation of kinetic coefficients with a co-digestion continuous experiment. • Simulation of batch and continuous experiments with an ADM1-based model. - Abstract: A methodology to estimate disintegration and hydrolysis kinetic parameters of solid wastes and validate an ADM1-based anaerobic co-digestion model is presented. Kinetic parameters of the model were calibrated from batch reactor experiments treating individually fruit and vegetable wastes (among other residues) following a new protocol for batch tests. In addition, decoupled disintegration kinetics for readily and slowly biodegradable fractions of solid wastes was considered. Calibrated parameters from batch assays of individual substrates were used to validate the model for a semi-continuous co-digestion operation treating simultaneously 5 fruit and vegetable wastes. The semi-continuous experiment was carried out in a lab-scale CSTR reactor for 15 weeks at organic loading rate ranging between 2.0 and 4.7 g VS/L d. The model (built in Matlab/Simulink) fit to a large extent the experimental results in both batch and semi-continuous mode and served as a powerful tool to simulate the digestion or co-digestion of solid wastes.

Genome-Scale Reconstruction of the Human Astrocyte Metabolic Network

OpenAIRE

Mart?n-Jim?nez, Cynthia A.; Salazar-Barreto, Diego; Barreto, George E.; Gonz?lez, Janneth

2017-01-01

Astrocytes are the most abundant cells of the central nervous system; they have a predominant role in maintaining brain metabolism. In this sense, abnormal metabolic states have been found in different neuropathological diseases. Determination of metabolic states of astrocytes is difficult to model using current experimental approaches given the high number of reactions and metabolites present. Thus, genome-scale metabolic networks derived from transcriptomic data can be used as a framework t...

Rotational and divergent kinetic energy in the mesoscale model ALADIN

Directory of Open Access Journals (Sweden)

V. Blažica

2013-03-01

Full Text Available Kinetic energy spectra from the mesoscale numerical weather prediction (NWP model ALADIN with horizontal resolution 4.4 km are split into divergent and rotational components which are then compared at horizontal scales below 300 km and various vertical levels. It is shown that about 50% of kinetic energy in the free troposphere in ALADIN is divergent energy. The percentage increases towards 70% near the surface and in the upper troposphere towards 100 hPa. The maximal percentage of divergent energy is found at stratospheric levels around 100 hPa and at scales below 100 km which are not represented by the global models. At all levels, the divergent energy spectra are characterised by shallower slopes than the rotational energy spectra, and the difference increases as horizontal scales become larger. A very similar vertical distribution of divergent energy is obtained by using the standard ALADIN approach for the computation of spectra based on the extension zone and by applying detrending approach commonly used in mesoscale NWP community.

Kinetic modeling of Nernst effect in magnetized hohlraums.

Science.gov (United States)

Joglekar, A S; Ridgers, C P; Kingham, R J; Thomas, A G R

2016-04-01

We present nanosecond time-scale Vlasov-Fokker-Planck-Maxwell modeling of magnetized plasma transport and dynamics in a hohlraum with an applied external magnetic field, under conditions similar to recent experiments. Self-consistent modeling of the kinetic electron momentum equation allows for a complete treatment of the heat flow equation and Ohm's law, including Nernst advection of magnetic fields. In addition to showing the prevalence of nonlocal behavior, we demonstrate that effects such as anomalous heat flow are induced by inverse bremsstrahlung heating. We show magnetic field amplification up to a factor of 3 from Nernst compression into the hohlraum wall. The magnetic field is also expelled towards the hohlraum axis due to Nernst advection faster than frozen-in flux would suggest. Nonlocality contributes to the heat flow towards the hohlraum axis and results in an augmented Nernst advection mechanism that is included self-consistently through kinetic modeling.

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

Science.gov (United States)

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.

Crystallization Kinetics within a Generic Modelling Framework

DEFF Research Database (Denmark)

Meisler, Kresten Troelstrup; von Solms, Nicolas; Gernaey, Krist

2013-01-01

An existing generic modelling framework has been expanded with tools for kinetic model analysis. The analysis of kinetics is carried out within the framework where kinetic constitutive models are collected, analysed and utilized for the simulation of crystallization operations. A modelling...... procedure is proposed to gain the information of crystallization operation kinetic model analysis and utilize this for faster evaluation of crystallization operations....

Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

Science.gov (United States)

Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

2016-09-19

Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.

Comprehensive reconstruction and in silico analysis of Aspergillus niger genome-scale metabolic network model that accounts for 1210 ORFs.

Science.gov (United States)

Lu, Hongzhong; Cao, Weiqiang; Ouyang, Liming; Xia, Jianye; Huang, Mingzhi; Chu, Ju; Zhuang, Yingping; Zhang, Siliang; Noorman, Henk

2017-03-01

Aspergillus niger is one of the most important cell factories for industrial enzymes and organic acids production. A comprehensive genome-scale metabolic network model (GSMM) with high quality is crucial for efficient strain improvement and process optimization. The lack of accurate reaction equations and gene-protein-reaction associations (GPRs) in the current best model of A. niger named GSMM iMA871, however, limits its application scope. To overcome these limitations, we updated the A. niger GSMM by combining the latest genome annotation and literature mining technology. Compared with iMA871, the number of reactions in iHL1210 was increased from 1,380 to 1,764, and the number of unique ORFs from 871 to 1,210. With the aid of our transcriptomics analysis, the existence of 63% ORFs and 68% reactions in iHL1210 can be verified when glucose was used as the only carbon source. Physiological data from chemostat cultivations, 13 C-labeled and molecular experiments from the published literature were further used to check the performance of iHL1210. The average correlation coefficients between the predicted fluxes and estimated fluxes from 13 C-labeling data were sufficiently high (above 0.89) and the prediction of cell growth on most of the reported carbon and nitrogen sources was consistent. Using the updated genome-scale model, we evaluated gene essentiality on synthetic and yeast extract medium, as well as the effects of NADPH supply on glucoamylase production in A. niger. In summary, the new A. niger GSMM iHL1210 contains significant improvements with respect to the metabolic coverage and prediction performance, which paves the way for systematic metabolic engineering of A. niger. Biotechnol. Bioeng. 2017;114: 685-695. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Reconstruction and in silico analysis of an Actinoplanes sp. SE50/110 genome-scale metabolic model for acarbose production

Directory of Open Access Journals (Sweden)

Yali eWang

2015-06-01

Full Text Available Actinoplanes sp. SE50/110 produces the -glucosidase inhibitor acarbose, which is used to treat type 2 diabetes mellitus. To obtain a comprehensive understanding of its cellular metabolism, a genome-scale metabolic model of strain SE50/110, iYLW1028, was reconstructed on the bases of the genome annotation, biochemical databases, and extensive literature mining. Model iYLW1028 comprises 1028 genes, 1128 metabolites and 1219 reactions. 122 and 81 genes were essential for cell growth on acarbose synthesis and sucrose media, respectively, and the acarbose biosynthetic pathway in SE50/110 was expounded completely. Based on model predictions, the addition of arginine and histidine to the media increased acarbose production by 78% and 59%, respectively. Additionally, dissolved oxygen has a great effect on acarbose production based on model predictions. Furthermore, genes to be overexpressed for the overproduction of acarbose were identified, and the deletion of treY eliminated the formation of by-product component C. Model iYLW1028 is a useful platform for optimizing and systems metabolic engineering for acarbose production in Actinoplanes sp. SE50/110.

Thermochemical conversion of biomass in smouldering combustion across scales: The roles of heterogeneous kinetics, oxygen and transport phenomena.

Science.gov (United States)

Huang, Xinyan; Rein, Guillermo

2016-05-01

The thermochemical conversion of biomass in smouldering combustion is investigated here by combining experiments and modeling at two scales: matter (1mg) and bench (100g) scales. Emphasis is put on the effect of oxygen (0-33vol.%) and oxidation reactions because these are poorly studied in the literature in comparison to pyrolysis. The results are obtained for peat as a representative biomass for which there is high-quality experimental data published previously. Three kinetic schemes are explored, including various steps of drying, pyrolysis and oxidation. The kinetic parameters are found using the Kissinger-Genetic Algorithm method, and then implemented in a one-dimensional model of heat and mass transfer. The predictions are validated with thermogravimetric and bench-scale experiments and then analyzed to unravel the role of heterogeneous reaction. This is the first time that the influence of oxygen on biomass smouldering is explained in terms of both chemistry and transport phenomena across scales. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

SUPECA kinetics for scaling redox reactions in networks of mixed substrates and consumers and an example application to aerobic soil respiration

Science.gov (United States)

Tang, Jin-Yun; Riley, William J.

2017-09-01

Several land biogeochemical models used for studying carbon-climate feedbacks have begun explicitly representing microbial dynamics. However, to our knowledge, there has been no theoretical work on how to achieve a consistent scaling of the complex biogeochemical reactions from microbial individuals to populations, communities, and interactions with plants and mineral soils. We focus here on developing a mathematical formulation of the substrate-consumer relationships for consumer-mediated redox reactions of the form A + BE→ products, where products could be, e.g., microbial biomass or bioproducts. Under the quasi-steady-state approximation, these substrate-consumer relationships can be formulated as the computationally difficult full equilibrium chemistry problem or approximated analytically with the dual Monod (DM) or synthesizing unit (SU) kinetics. We find that DM kinetics is scaling inconsistently for reaction networks because (1) substrate limitations are not considered, (2) contradictory assumptions are made regarding the substrate processing rate when transitioning from single- to multi-substrate redox reactions, and (3) the product generation rate cannot be scaled from one to multiple substrates. In contrast, SU kinetics consistently scales the product generation rate from one to multiple substrates but predicts unrealistic results as consumer abundances reach large values with respect to their substrates. We attribute this deficit to SU's failure to incorporate substrate limitation in its derivation. To address these issues, we propose SUPECA (SU plus the equilibrium chemistry approximation - ECA) kinetics, which consistently imposes substrate and consumer mass balance constraints. We show that SUPECA kinetics satisfies the partition principle, i.e., scaling invariance across a network of an arbitrary number of reactions (e.g., as in Newton's law of motion and Dalton's law of partial pressures). We tested SUPECA kinetics with the equilibrium chemistry

Crystallization Kinetics within a Generic Modeling Framework

DEFF Research Database (Denmark)

Meisler, Kresten Troelstrup; von Solms, Nicolas; Gernaey, Krist V.

2014-01-01

of employing a well-structured model library for storage, use/reuse, and analysis of the kinetic models are highlighted. Examples illustrating the application of the modeling framework for kinetic model discrimination related to simulation of specific crystallization scenarios and for kinetic model parameter......A new and extended version of a generic modeling framework for analysis and design of crystallization operations is presented. The new features of this framework are described, with focus on development, implementation, identification, and analysis of crystallization kinetic models. Issues related...... to the modeling of various kinetic phenomena like nucleation, growth, agglomeration, and breakage are discussed in terms of model forms, model parameters, their availability and/or estimation, and their selection and application for specific crystallization operational scenarios under study. The advantages...

Annotated Draft Genome Assemblies for the Northern Bobwhite (Colinus virginianus) and the Scaled Quail (Callipepla squamata) Reveal Disparate Estimates of Modern Genome Diversity and Historic Effective Population Size.

Science.gov (United States)

Oldeschulte, David L; Halley, Yvette A; Wilson, Miranda L; Bhattarai, Eric K; Brashear, Wesley; Hill, Joshua; Metz, Richard P; Johnson, Charles D; Rollins, Dale; Peterson, Markus J; Bickhart, Derek M; Decker, Jared E; Sewell, John F; Seabury, Christopher M

2017-09-07

Northern bobwhite ( Colinus virginianus ; hereafter bobwhite) and scaled quail ( Callipepla squamata ) populations have suffered precipitous declines across most of their US ranges. Illumina-based first- (v1.0) and second- (v2.0) generation draft genome assemblies for the scaled quail and the bobwhite produced N50 scaffold sizes of 1.035 and 2.042 Mb, thereby producing a 45-fold improvement in contiguity over the existing bobwhite assembly, and ≥90% of the assembled genomes were captured within 1313 and 8990 scaffolds, respectively. The scaled quail assembly (v1.0 = 1.045 Gb) was ∼20% smaller than the bobwhite (v2.0 = 1.254 Gb), which was supported by kmer-based estimates of genome size. Nevertheless, estimates of GC content (41.72%; 42.66%), genome-wide repetitive content (10.40%; 10.43%), and MAKER-predicted protein coding genes (17,131; 17,165) were similar for the scaled quail (v1.0) and bobwhite (v2.0) assemblies, respectively. BUSCO analyses utilizing 3023 single-copy orthologs revealed a high level of assembly completeness for the scaled quail (v1.0; 84.8%) and the bobwhite (v2.0; 82.5%), as verified by comparison with well-established avian genomes. We also detected 273 putative segmental duplications in the scaled quail genome (v1.0), and 711 in the bobwhite genome (v2.0), including some that were shared among both species. Autosomal variant prediction revealed ∼2.48 and 4.17 heterozygous variants per kilobase within the scaled quail (v1.0) and bobwhite (v2.0) genomes, respectively, and estimates of historic effective population size were uniformly higher for the bobwhite across all time points in a coalescent model. However, large-scale declines were predicted for both species beginning ∼15-20 KYA. Copyright © 2017 Oldeschulte et al.

Annotated Draft Genome Assemblies for the Northern Bobwhite (Colinus virginianus and the Scaled Quail (Callipepla squamata Reveal Disparate Estimates of Modern Genome Diversity and Historic Effective Population Size

Directory of Open Access Journals (Sweden)

David L. Oldeschulte

2017-09-01

Full Text Available Northern bobwhite (Colinus virginianus; hereafter bobwhite and scaled quail (Callipepla squamata populations have suffered precipitous declines across most of their US ranges. Illumina-based first- (v1.0 and second- (v2.0 generation draft genome assemblies for the scaled quail and the bobwhite produced N50 scaffold sizes of 1.035 and 2.042 Mb, thereby producing a 45-fold improvement in contiguity over the existing bobwhite assembly, and ≥90% of the assembled genomes were captured within 1313 and 8990 scaffolds, respectively. The scaled quail assembly (v1.0 = 1.045 Gb was ∼20% smaller than the bobwhite (v2.0 = 1.254 Gb, which was supported by kmer-based estimates of genome size. Nevertheless, estimates of GC content (41.72%; 42.66%, genome-wide repetitive content (10.40%; 10.43%, and MAKER-predicted protein coding genes (17,131; 17,165 were similar for the scaled quail (v1.0 and bobwhite (v2.0 assemblies, respectively. BUSCO analyses utilizing 3023 single-copy orthologs revealed a high level of assembly completeness for the scaled quail (v1.0; 84.8% and the bobwhite (v2.0; 82.5%, as verified by comparison with well-established avian genomes. We also detected 273 putative segmental duplications in the scaled quail genome (v1.0, and 711 in the bobwhite genome (v2.0, including some that were shared among both species. Autosomal variant prediction revealed ∼2.48 and 4.17 heterozygous variants per kilobase within the scaled quail (v1.0 and bobwhite (v2.0 genomes, respectively, and estimates of historic effective population size were uniformly higher for the bobwhite across all time points in a coalescent model. However, large-scale declines were predicted for both species beginning ∼15–20 KYA.

Modeling Coronal Mass Ejections with the Multi-Scale Fluid-Kinetic Simulation Suite

International Nuclear Information System (INIS)

Pogorelov, N. V.; Borovikov, S. N.; Wu, S. T.; Yalim, M. S.; Kryukov, I. A.; Colella, P. C.; Van Straalen, B.

2017-01-01

The solar eruptions and interacting solar wind streams are key drivers of geomagnetic storms and various related space weather disturbances that may have hazardous effects on the space-borne and ground-based technological systems as well as on human health. Coronal mass ejections (CMEs) and their interplanetary counterparts, interplanetary CMEs (ICMEs), belong to the strongest disturbances and therefore are of great importance for the space weather predictions. In this paper we show a few examples of how adaptive mesh refinement makes it possible to resolve the complex CME structure and its evolution in time while a CME propagates from the inner boundary to Earth. Simulations are performed with the Multi-Scale Fluid-Kinetic Simulation Suite (MS-FLUKSS). (paper)

Birth of scale-free molecular networks and the number of distinct DNA and protein domains per genome.

Science.gov (United States)

Rzhetsky, A; Gomez, S M

2001-10-01

Current growth in the field of genomics has provided a number of exciting approaches to the modeling of evolutionary mechanisms within the genome. Separately, dynamical and statistical analyses of networks such as the World Wide Web and the social interactions existing between humans have shown that these networks can exhibit common fractal properties-including the property of being scale-free. This work attempts to bridge these two fields and demonstrate that the fractal properties of molecular networks are linked to the fractal properties of their underlying genomes. We suggest a stochastic model capable of describing the evolutionary growth of metabolic or signal-transduction networks. This model generates networks that share important statistical properties (so-called scale-free behavior) with real molecular networks. In particular, the frequency of vertices connected to exactly k other vertices follows a power-law distribution. The shape of this distribution remains invariant to changes in network scale: a small subgraph has the same distribution as the complete graph from which it is derived. Furthermore, the model correctly predicts that the frequencies of distinct DNA and protein domains also follow a power-law distribution. Finally, the model leads to a simple equation linking the total number of different DNA and protein domains in a genome with both the total number of genes and the overall network topology. MatLab (MathWorks, Inc.) programs described in this manuscript are available on request from the authors. ar345@columbia.edu.

A two-time-scale dynamic-model approach for magnetic and kinetic profile control in advanced tokamak scenarios on JET

International Nuclear Information System (INIS)

Moreau, D.; Mazon, D.; Ariola, M.; Tommasi, G. De; Laborde, L.; Piccolo, F.; Sartori, F.; Zabeo, L.; Boboc, A.; Brix, M.; Challis, C.D.; Felton, R.; Hawkes, N.; Tala, T.; Bouvier, E.; Cordoliani, V.; Brzozowski, J.; Cocilovo, V.; Crisanti, F.; Luna, E. de la

2008-01-01

Real-time simultaneous control of several radially distributed magnetic and kinetic plasma parameters is being investigated on JET, in view of developing integrated control of advanced tokamak scenarios. This paper describes the new model-based profile controller which has been implemented during the 2006-2007 experimental campaigns. The controller aims to use the combination of heating and current drive (H and CD) systems-and optionally the poloidal field (PF) system-in an optimal way to regulate the evolution of plasma parameter profiles such as the safety factor, q(x), and gyro-normalized temperature gradient, ρ Te *(x). In the first part of the paper, a technique for the experimental identification of a minimal dynamic plasma model is described, taking into account the physical structure and couplings of the transport equations, but making no quantitative assumptions on the transport coefficients or on their dependences. To cope with the high dimensionality of the state space and the large ratio between the time scales involved, the model identification procedure and the controller design both make use of the theory of singularly perturbed systems by means of a two-time-scale approximation. The second part of the paper provides the theoretical basis for the controller design. The profile controller is articulated around two composite feedback loops operating on the magnetic and kinetic time scales, respectively, and supplemented by a feedforward compensation of density variations. For any chosen set of target profiles, the closest self-consistent state achievable with the available actuators is uniquely defined. It is reached, with no steady state offset, through a near-optimal proportional-integral control algorithm. Conventional optimal control is recovered in the limiting case where the ratio of the plasma confinement time to the resistive diffusion time tends to zero. Closed-loop simulations of the controller response have been performed in preparation for

Analysing human genomes at different scales

DEFF Research Database (Denmark)

Liu, Siyang

The thriving of the Next-Generation sequencing (NGS) technologies in the past decade has dramatically revolutionized the field of human genetics. We are experiencing a wave of several large-scale whole genome sequencing studies of humans in the world. Those studies vary greatly regarding cohort...... will be reflected by the analysis of real data. This thesis covers studies in two human genome sequencing projects that distinctly differ in terms of studied population, sample size and sequencing depth. In the first project, we sequenced 150 Danish individuals from 50 trio families to 78x coverage....... The sophisticated experimental design enables high-quality de novo assembly of the genomes and provides a good opportunity for mapping the structural variations in the human population. We developed the AsmVar approach to discover, genotype and characterize the structural variations from the assemblies. Our...

Receptivity to Kinetic Fluctuations: A Multiple Scales Approach

Science.gov (United States)

Edwards, Luke; Tumin, Anatoli

2017-11-01

The receptivity of high-speed compressible boundary layers to kinetic fluctuations (KF) is considered within the framework of fluctuating hydrodynamics. The formulation is based on the idea that KF-induced dissipative fluxes may lead to the generation of unstable modes in the boundary layer. Fedorov and Tumin solved the receptivity problem using an asymptotic matching approach which utilized a resonant inner solution in the vicinity of the generation point of the second Mack mode. Here we take a slightly more general approach based on a multiple scales WKB ansatz which requires fewer assumptions about the behavior of the stability spectrum. The approach is modeled after the one taken by Luchini to study low speed incompressible boundary layers over a swept wing. The new framework is used to study examples of high-enthalpy, flat plate boundary layers whose spectra exhibit nuanced behavior near the generation point, such as first mode instabilities and near-neutral evolution over moderate length scales. The configurations considered exhibit supersonic unstable second Mack modes despite the temperature ratio Tw /Te > 1 , contrary to prior expectations. Supported by AFOSR and ONR.

Oxidative desulfurization: kinetic modelling.

Science.gov (United States)

Dhir, S; Uppaluri, R; Purkait, M K

2009-01-30

Increasing environmental legislations coupled with enhanced production of petroleum products demand, the deployment of novel technologies to remove organic sulfur efficiently. This work represents the kinetic modeling of ODS using H(2)O(2) over tungsten-containing layered double hydroxide (LDH) using the experimental data provided by Hulea et al. [V. Hulea, A.L. Maciuca, F. Fajula, E. Dumitriu, Catalytic oxidation of thiophenes and thioethers with hydrogen peroxide in the presence of W-containing layered double hydroxides, Appl. Catal. A: Gen. 313 (2) (2006) 200-207]. The kinetic modeling approach in this work initially targets the scope of the generation of a superstructure of micro-kinetic reaction schemes and models assuming Langmuir-Hinshelwood (LH) and Eley-Rideal (ER) mechanisms. Subsequently, the screening and selection of above models is initially based on profile-based elimination of incompetent schemes followed by non-linear regression search performed using the Levenberg-Marquardt algorithm (LMA) for the chosen models. The above analysis inferred that Eley-Rideal mechanism describes the kinetic behavior of ODS process using tungsten-containing LDH, with adsorption of reactant and intermediate product only taking place on the catalyst surface. Finally, an economic index is presented that scopes the economic aspects of the novel catalytic technology with the parameters obtained during regression analysis to conclude that the cost factor for the catalyst is 0.0062-0.04759 US $ per barrel.

Oxidative desulfurization: Kinetic modelling

International Nuclear Information System (INIS)

Dhir, S.; Uppaluri, R.; Purkait, M.K.

2009-01-01

Increasing environmental legislations coupled with enhanced production of petroleum products demand, the deployment of novel technologies to remove organic sulfur efficiently. This work represents the kinetic modeling of ODS using H 2 O 2 over tungsten-containing layered double hydroxide (LDH) using the experimental data provided by Hulea et al. [V. Hulea, A.L. Maciuca, F. Fajula, E. Dumitriu, Catalytic oxidation of thiophenes and thioethers with hydrogen peroxide in the presence of W-containing layered double hydroxides, Appl. Catal. A: Gen. 313 (2) (2006) 200-207]. The kinetic modeling approach in this work initially targets the scope of the generation of a superstructure of micro-kinetic reaction schemes and models assuming Langmuir-Hinshelwood (LH) and Eley-Rideal (ER) mechanisms. Subsequently, the screening and selection of above models is initially based on profile-based elimination of incompetent schemes followed by non-linear regression search performed using the Levenberg-Marquardt algorithm (LMA) for the chosen models. The above analysis inferred that Eley-Rideal mechanism describes the kinetic behavior of ODS process using tungsten-containing LDH, with adsorption of reactant and intermediate product only taking place on the catalyst surface. Finally, an economic index is presented that scopes the economic aspects of the novel catalytic technology with the parameters obtained during regression analysis to conclude that the cost factor for the catalyst is 0.0062-0.04759 US $ per barrel

Genome-scale reconstruction of metabolic networks of Lactobacillus casei ATCC 334 and 12A.

Directory of Open Access Journals (Sweden)

Elena Vinay-Lara

Full Text Available Lactobacillus casei strains are widely used in industry and the utility of this organism in these industrial applications is strain dependent. Hence, tools capable of predicting strain specific phenotypes would have utility in the selection of strains for specific industrial processes. Genome-scale metabolic models can be utilized to better understand genotype-phenotype relationships and to compare different organisms. To assist in the selection and development of strains with enhanced industrial utility, genome-scale models for L. casei ATCC 334, a well characterized strain, and strain 12A, a corn silage isolate, were constructed. Draft models were generated from RAST genome annotations using the Model SEED database and refined by evaluating ATP generating cycles, mass-and-charge-balances of reactions, and growth phenotypes. After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors. We conclude that the metabolic capabilities of the two networks are highly similar. The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes. The developed L. casei ATCC 334 and 12A metabolic models will enable better understanding of the physiology of these organisms and be valuable tools in the development and selection of strains with enhanced utility in a variety of industrial applications.

Genome-Wide Fine-Scale Recombination Rate Variation in Drosophila melanogaster

Science.gov (United States)

Song, Yun S.

2012-01-01

Estimating fine-scale recombination maps of Drosophila from population genomic data is a challenging problem, in particular because of the high background recombination rate. In this paper, a new computational method is developed to address this challenge. Through an extensive simulation study, it is demonstrated that the method allows more accurate inference, and exhibits greater robustness to the effects of natural selection and noise, compared to a well-used previous method developed for studying fine-scale recombination rate variation in the human genome. As an application, a genome-wide analysis of genetic variation data is performed for two Drosophila melanogaster populations, one from North America (Raleigh, USA) and the other from Africa (Gikongoro, Rwanda). It is shown that fine-scale recombination rate variation is widespread throughout the D. melanogaster genome, across all chromosomes and in both populations. At the fine-scale, a conservative, systematic search for evidence of recombination hotspots suggests the existence of a handful of putative hotspots each with at least a tenfold increase in intensity over the background rate. A wavelet analysis is carried out to compare the estimated recombination maps in the two populations and to quantify the extent to which recombination rates are conserved. In general, similarity is observed at very broad scales, but substantial differences are seen at fine scales. The average recombination rate of the X chromosome appears to be higher than that of the autosomes in both populations, and this pattern is much more pronounced in the African population than the North American population. The correlation between various genomic features—including recombination rates, diversity, divergence, GC content, gene content, and sequence quality—is examined using the wavelet analysis, and it is shown that the most notable difference between D. melanogaster and humans is in the correlation between recombination and

Toward a Multi-scale Phase Transition Kinetics Methodology: From Non-Equilibrium Statistical Mechanics to Hydrodynamics

Science.gov (United States)

Belof, Jonathan; Orlikowski, Daniel; Wu, Christine; McLaughlin, Keith

2013-06-01

Shock and ramp compression experiments are allowing us to probe condensed matter under extreme conditions where phase transitions and other non-equilibrium aspects can now be directly observed, but first principles simulation of kinetics remains a challenge. A multi-scale approach is presented here, with non-equilibrium statistical mechanical quantities calculated by molecular dynamics (MD) and then leveraged to inform a classical nucleation and growth kinetics model at the hydrodynamic scale. Of central interest is the free energy barrier for the formation of a critical nucleus, with direct NEMD presenting the challenge of relatively long timescales necessary to resolve nucleation. Rather than attempt to resolve the time-dependent nucleation sequence directly, the methodology derived here is built upon the non-equilibrium work theorem in order to bias the formation of a critical nucleus and thus construct the nucleation and growth rates. Having determined these kinetic terms from MD, a hydrodynamics implementation of Kolmogorov-Johnson-Mehl-Avrami (KJMA) kinetics and metastabilty is applied to the dynamic compressive freezing of water and compared with recent ramp compression experiments [Dolan et al., Nature (2007)] Lawrence Livermore National Laboratory is operated by Lawrence Livermore National Security, LLC, for the U.S. Department of Energy, National Nuclear Security Administration under Contract DE-AC52-07NA27344.

A methodology for modeling photocatalytic reactors for indoor pollution control using previously estimated kinetic parameters

Energy Technology Data Exchange (ETDEWEB)

Passalia, Claudio; Alfano, Orlando M. [INTEC - Instituto de Desarrollo Tecnologico para la Industria Quimica, CONICET - UNL, Gueemes 3450, 3000 Santa Fe (Argentina); FICH - Departamento de Medio Ambiente, Facultad de Ingenieria y Ciencias Hidricas, Universidad Nacional del Litoral, Ciudad Universitaria, 3000 Santa Fe (Argentina); Brandi, Rodolfo J., E-mail: rbrandi@santafe-conicet.gov.ar [INTEC - Instituto de Desarrollo Tecnologico para la Industria Quimica, CONICET - UNL, Gueemes 3450, 3000 Santa Fe (Argentina); FICH - Departamento de Medio Ambiente, Facultad de Ingenieria y Ciencias Hidricas, Universidad Nacional del Litoral, Ciudad Universitaria, 3000 Santa Fe (Argentina)

2012-04-15

Highlights: Black-Right-Pointing-Pointer Indoor pollution control via photocatalytic reactors. Black-Right-Pointing-Pointer Scaling-up methodology based on previously determined mechanistic kinetics. Black-Right-Pointing-Pointer Radiation interchange model between catalytic walls using configuration factors. Black-Right-Pointing-Pointer Modeling and experimental validation of a complex geometry photocatalytic reactor. - Abstract: A methodology for modeling photocatalytic reactors for their application in indoor air pollution control is carried out. The methodology implies, firstly, the determination of intrinsic reaction kinetics for the removal of formaldehyde. This is achieved by means of a simple geometry, continuous reactor operating under kinetic control regime and steady state. The kinetic parameters were estimated from experimental data by means of a nonlinear optimization algorithm. The second step was the application of the obtained kinetic parameters to a very different photoreactor configuration. In this case, the reactor is a corrugated wall type using nanosize TiO{sub 2} as catalyst irradiated by UV lamps that provided a spatially uniform radiation field. The radiative transfer within the reactor was modeled through a superficial emission model for the lamps, the ray tracing method and the computation of view factors. The velocity and concentration fields were evaluated by means of a commercial CFD tool (Fluent 12) where the radiation model was introduced externally. The results of the model were compared experimentally in a corrugated wall, bench scale reactor constructed in the laboratory. The overall pollutant conversion showed good agreement between model predictions and experiments, with a root mean square error less than 4%.

Modeling in applied sciences a kinetic theory approach

CERN Document Server

Pulvirenti, Mario

2000-01-01

Modeling complex biological, chemical, and physical systems, in the context of spatially heterogeneous mediums, is a challenging task for scientists and engineers using traditional methods of analysis Modeling in Applied Sciences is a comprehensive survey of modeling large systems using kinetic equations, and in particular the Boltzmann equation and its generalizations An interdisciplinary group of leading authorities carefully develop the foundations of kinetic models and discuss the connections and interactions between model theories, qualitative and computational analysis and real-world applications This book provides a thoroughly accessible and lucid overview of the different aspects, models, computations, and methodology for the kinetic-theory modeling process Topics and Features * Integrated modeling perspective utilized in all chapters * Fluid dynamics of reacting gases * Self-contained introduction to kinetic models * Becker–Doring equations * Nonlinear kinetic models with chemical reactions * Kinet...

A Consensus Genome-scale Reconstruction of Chinese Hamster Ovary Cell Metabolism

KAUST Repository

Hefzi, Hooman

2016-11-23

Chinese hamster ovary (CHO) cells dominate biotherapeutic protein production and are widely used in mammalian cell line engineering research. To elucidate metabolic bottlenecks in protein production and to guide cell engineering and bioprocess optimization, we reconstructed the metabolic pathways in CHO and associated them with >1,700 genes in the Cricetulus griseus genome. The genome-scale metabolic model based on this reconstruction, iCHO1766, and cell-line-specific models for CHO-K1, CHO-S, and CHO-DG44 cells provide the biochemical basis of growth and recombinant protein production. The models accurately predict growth phenotypes and known auxotrophies in CHO cells. With the models, we quantify the protein synthesis capacity of CHO cells and demonstrate that common bioprocess treatments, such as histone deacetylase inhibitors, inefficiently increase product yield. However, our simulations show that the metabolic resources in CHO are more than three times more efficiently utilized for growth or recombinant protein synthesis following targeted efforts to engineer the CHO secretory pathway. This model will further accelerate CHO cell engineering and help optimize bioprocesses.

Kinetics and hybrid kinetic-fluid models for nonequilibrium gas and plasmas

International Nuclear Information System (INIS)

Crouseilles, N.

2004-12-01

For a few decades, the application of the physics of plasmas has appeared in different fields like laser-matter interaction, astrophysics or thermonuclear fusion. In this thesis, we are interested in the modeling and the numerical study of nonequilibrium gas and plasmas. To describe such systems, two ways are usually used: the fluid description and the kinetic description. When we study a nonequilibrium system, fluid models are not sufficient and a kinetic description have to be used. However, solving a kinetic model requires the discretization of a large number of variables, which is quite expensive from a numerical point of view. The aim of this work is to propose a hybrid kinetic-fluid model thanks to a domain decomposition method in the velocity space. The derivation of the hybrid model is done in two different contexts: the rarefied gas context and the more complicated plasmas context. The derivation partly relies on Levermore's entropy minimization approach. The so-obtained model is then discretized and validated on various numerical test cases. In a second stage, a numerical study of a fully kinetic model is presented. A collisional plasma constituted of electrons and ions is considered through the Vlasov-Poisson-Fokker-Planck-Landau equation. Then, a numerical scheme which preserves total mass and total energy is presented. This discretization permits in particular a numerical study of the Landau damping. (author)

Phenomenological aspects of no-scale inflation models

Energy Technology Data Exchange (ETDEWEB)

Ellis, John [Theoretical Particle Physics and Cosmology Group, Department of Physics, King' s College London, WC2R 2LS London (United Kingdom); Garcia, Marcos A.G.; Olive, Keith A. [William I. Fine Theoretical Physics Institute, School of Physics and Astronomy, University of Minnesota, 116 Church Street SE, Minneapolis, MN 55455 (United States); Nanopoulos, Dimitri V., E-mail: john.ellis@cern.ch, E-mail: garciagarcia@physics.umn.edu, E-mail: dimitri@physics.tamu.edu, E-mail: olive@physics.umn.edu [George P. and Cynthia W. Mitchell Institute for Fundamental Physics and Astronomy, Texas A and M University, College Station, 77843 Texas (United States)

2015-10-01

We discuss phenomenological aspects of inflationary models wiith a no-scale supergravity Kähler potential motivated by compactified string models, in which the inflaton may be identified either as a Kähler modulus or an untwisted matter field, focusing on models that make predictions for the scalar spectral index n{sub s} and the tensor-to-scalar ratio r that are similar to the Starobinsky model. We discuss possible patterns of soft supersymmetry breaking, exhibiting examples of the pure no-scale type m{sub 0} = B{sub 0} = A{sub 0} = 0, of the CMSSM type with universal A{sub 0} and m{sub 0} ≠ 0 at a high scale, and of the mSUGRA type with A{sub 0} = B{sub 0} + m{sub 0} boundary conditions at the high input scale. These may be combined with a non-trivial gauge kinetic function that generates gaugino masses m{sub 1/2} ≠ 0, or one may have a pure gravity mediation scenario where trilinear terms and gaugino masses are generated through anomalies. We also discuss inflaton decays and reheating, showing possible decay channels for the inflaton when it is either an untwisted matter field or a Kähler modulus. Reheating is very efficient if a matter field inflaton is directly coupled to MSSM fields, and both candidates lead to sufficient reheating in the presence of a non-trivial gauge kinetic function.

Phenomenological aspects of no-scale inflation models

Energy Technology Data Exchange (ETDEWEB)

Ellis, John [Theoretical Particle Physics and Cosmology Group, Department of Physics,King’s College London,WC2R 2LS London (United Kingdom); Theory Division, CERN,CH-1211 Geneva 23 (Switzerland); Garcia, Marcos A.G. [William I. Fine Theoretical Physics Institute, School of Physics and Astronomy,University of Minnesota,116 Church Street SE, Minneapolis, MN 55455 (United States); Nanopoulos, Dimitri V. [George P. and Cynthia W. Mitchell Institute for Fundamental Physics andAstronomy, Texas A& M University,College Station, 77843 Texas (United States); Astroparticle Physics Group, Houston Advanced Research Center (HARC), Mitchell Campus, Woodlands, 77381 Texas (United States); Academy of Athens, Division of Natural Sciences, 28 Panepistimiou Avenue, 10679 Athens (Greece); Olive, Keith A. [William I. Fine Theoretical Physics Institute, School of Physics and Astronomy,University of Minnesota,116 Church Street SE, Minneapolis, MN 55455 (United States)

2015-10-01

We discuss phenomenological aspects of inflationary models wiith a no-scale supergravity Kähler potential motivated by compactified string models, in which the inflaton may be identified either as a Kähler modulus or an untwisted matter field, focusing on models that make predictions for the scalar spectral index n{sub s} and the tensor-to-scalar ratio r that are similar to the Starobinsky model. We discuss possible patterns of soft supersymmetry breaking, exhibiting examples of the pure no-scale type m{sub 0}=B{sub 0}=A{sub 0}=0, of the CMSSM type with universal A{sub 0} and m{sub 0}≠0 at a high scale, and of the mSUGRA type with A{sub 0}=B{sub 0}+m{sub 0} boundary conditions at the high input scale. These may be combined with a non-trivial gauge kinetic function that generates gaugino masses m{sub 1/2}≠0, or one may have a pure gravity mediation scenario where trilinear terms and gaugino masses are generated through anomalies. We also discuss inflaton decays and reheating, showing possible decay channels for the inflaton when it is either an untwisted matter field or a Kähler modulus. Reheating is very efficient if a matter field inflaton is directly coupled to MSSM fields, and both candidates lead to sufficient reheating in the presence of a non-trivial gauge kinetic function.

Reflected kinetics model for nuclear space reactor kinetics and control scoping calculations

Energy Technology Data Exchange (ETDEWEB)

Washington, K.E.

1986-05-01

The objective of this research is to develop a model that offers an alternative to the point kinetics (PK) modelling approach in the analysis of space reactor kinetics and control studies. Modelling effort will focus on the explicit treatment of control drums as reactivity input devices so that the transition to automatic control can be smoothly done. The proposed model is developed for the specific integration of automatic control and the solution of the servo mechanism problem. The integration of the kinetics model with an automatic controller will provide a useful tool for performing space reactor scoping studies for different designs and configurations. Such a tool should prove to be invaluable in the design phase of a space nuclear system from the point of view of kinetics and control limitations.

Reflected kinetics model for nuclear space reactor kinetics and control scoping calculations

International Nuclear Information System (INIS)

Washington, K.E.

1986-05-01

The objective of this research is to develop a model that offers an alternative to the point kinetics (PK) modelling approach in the analysis of space reactor kinetics and control studies. Modelling effort will focus on the explicit treatment of control drums as reactivity input devices so that the transition to automatic control can be smoothly done. The proposed model is developed for the specific integration of automatic control and the solution of the servo mechanism problem. The integration of the kinetics model with an automatic controller will provide a useful tool for performing space reactor scoping studies for different designs and configurations. Such a tool should prove to be invaluable in the design phase of a space nuclear system from the point of view of kinetics and control limitations

Genome-based microbial ecology of anammox granules in a full-scale wastewater treatment system

OpenAIRE

Speth, D.R.; Zandt, M.H. in 't; Guerrero Cruz, S.; Dutilh, B.E.; Jetten, M.S.M.

2016-01-01

Partial-nitritation anammox (PNA) is a novel wastewater treatment procedure for energy-efficient ammonium removal. Here we use genome-resolved metagenomics to build a genome-based ecological model of the microbial community in a full-scale PNA reactor. Sludge from the bioreactor examined here is used to seed reactors in wastewater treatment plants around the world; however, the role of most of its microbial community in ammonium removal remains unknown. Our analysis yielded 23 near-complete d...

Fungal Genomics Program

Energy Technology Data Exchange (ETDEWEB)

Grigoriev, Igor

2012-03-12

The JGI Fungal Genomics Program aims to scale up sequencing and analysis of fungal genomes to explore the diversity of fungi important for energy and the environment, and to promote functional studies on a system level. Combining new sequencing technologies and comparative genomics tools, JGI is now leading the world in fungal genome sequencing and analysis. Over 120 sequenced fungal genomes with analytical tools are available via MycoCosm (www.jgi.doe.gov/fungi), a web-portal for fungal biologists. Our model of interacting with user communities, unique among other sequencing centers, helps organize these communities, improves genome annotation and analysis work, and facilitates new larger-scale genomic projects. This resulted in 20 high-profile papers published in 2011 alone and contributing to the Genomics Encyclopedia of Fungi, which targets fungi related to plant health (symbionts, pathogens, and biocontrol agents) and biorefinery processes (cellulose degradation, sugar fermentation, industrial hosts). Our next grand challenges include larger scale exploration of fungal diversity (1000 fungal genomes), developing molecular tools for DOE-relevant model organisms, and analysis of complex systems and metagenomes.

Microsecond time-scale kinetics of transient biochemical reactions

NARCIS (Netherlands)

Mitic, S.; Strampraad, M.J.F.; Hagen, W.R.; de Vries, S.

2017-01-01

To afford mechanistic studies in enzyme kinetics and protein folding in the microsecond time domain we have developed a continuous-flow microsecond time-scale mixing instrument with an unprecedented dead-time of 3.8 ± 0.3 μs. The instrument employs a micro-mixer with a mixing time of 2.7 μs

A unified gas-kinetic scheme for continuum and rarefied flows IV: Full Boltzmann and model equations

Energy Technology Data Exchange (ETDEWEB)

Liu, Chang, E-mail: cliuaa@ust.hk [Department of Mathematics and Department of Mechanical and Aerospace Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon (Hong Kong); Xu, Kun, E-mail: makxu@ust.hk [Department of Mathematics and Department of Mechanical and Aerospace Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon (Hong Kong); Sun, Quanhua, E-mail: qsun@imech.ac.cn [State Key Laboratory of High-temperature Gas Dynamics, Institute of Mechanics, Chinese Academy of Sciences, No. 15 Beisihuan Xi Rd, Beijing 100190 (China); Cai, Qingdong, E-mail: caiqd@mech.pku.edu.cn [Department of Mechanics and Aerospace Engineering, College of Engineering, Peking University, Beijing 100871 (China)

2016-06-01

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, the 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

GEM System: automatic prototyping of cell-wide metabolic pathway models from genomes

Directory of Open Access Journals (Sweden)

Nakayama Yoichi

2006-03-01

Full Text Available Abstract Background Successful realization of a "systems biology" approach to analyzing cells is a grand challenge for our understanding of life. However, current modeling approaches to cell simulation are labor-intensive, manual affairs, and therefore constitute a major bottleneck in the evolution of computational cell biology. Results We developed the Genome-based Modeling (GEM System for the purpose of automatically prototyping simulation models of cell-wide metabolic pathways from genome sequences and other public biological information. Models generated by the GEM System include an entire Escherichia coli metabolism model comprising 968 reactions of 1195 metabolites, achieving 100% coverage when compared with the KEGG database, 92.38% with the EcoCyc database, and 95.06% with iJR904 genome-scale model. Conclusion The GEM System prototypes qualitative models to reduce the labor-intensive tasks required for systems biology research. Models of over 90 bacterial genomes are available at our web site.

In Silico Genome-Scale Reconstruction and Validation of the Corynebacterium glutamicum Metabolic Network

DEFF Research Database (Denmark)

Kjeldsen, Kjeld Raunkjær; Nielsen, J.

2009-01-01

A genome-scale metabolic model of the Gram-positive bacteria Corynebacterium glutamicum ATCC 13032 was constructed comprising 446 reactions and 411 metabolite, based on the annotated genome and available biochemical information. The network was analyzed using constraint based methods. The model...... was extensively validated against published flux data, and flux distribution values were found to correlate well between simulations and experiments. The split pathway of the lysine synthesis pathway of C. glutamicum was investigated, and it was found that the direct dehydrogenase variant gave a higher lysine...... yield than the alternative succinyl pathway at high lysine production rates. The NADPH demand of the network was not found to be critical for lysine production until lysine yields exceeded 55% (mmol lysine (mmol glucose)(-1)). The model was validated during growth on the organic acids acetate...

Supercritical kinetic analysis in simplified system of fuel debris using integral kinetic model

International Nuclear Information System (INIS)

Tuya, Delgersaikhan; Obara, Toru

2016-01-01

Highlights: • Kinetic analysis in simplified weakly coupled fuel debris system was performed. • The integral kinetic model was used to simulate criticality accidents. • The fission power and released energy during simulated accident were obtained. • Coupling between debris regions and its effect on the fission power was obtained. - Abstract: Preliminary prompt supercritical kinetic analyses in a simplified coupled system of fuel debris designed to roughly resemble a melted core of a nuclear reactor were performed using an integral kinetic model. The integral kinetic model, which can describe region- and time-dependent fission rate in a coupled system of arbitrary geometry, was used because the fuel debris system is weakly coupled in terms of neutronics. The results revealed some important characteristics of coupled systems, such as the coupling between debris regions and the effect of the coupling on the fission rate and released energy in each debris region during the simulated criticality accident. In brief, this study showed that the integral kinetic model can be applied to supercritical kinetic analysis in fuel debris systems and also that it can be a useful tool for investigating the effect of the coupling on consequences of a supercritical accident.

ASPEN: A fully kinetic, reduced-description particle-in-cell model for simulating parametric instabilities

International Nuclear Information System (INIS)

Vu, H.X.; Bezzerides, B.; DuBois, D.F.

1999-01-01

A fully kinetic, reduced-description particle-in-cell (RPIC) model is presented in which deviations from quasineutrality, electron and ion kinetic effects, and nonlinear interactions between low-frequency and high-frequency parametric instabilities are modeled correctly. The model is based on a reduced description where the electromagnetic field is represented by three separate temporal envelopes in order to model parametric instabilities with low-frequency and high-frequency daughter waves. Because temporal envelope approximations are invoked, the simulation can be performed on the electron time scale instead of the time scale of the light waves. The electrons and ions are represented by discrete finite-size particles, permitting electron and ion kinetic effects to be modeled properly. The Poisson equation is utilized to ensure that space-charge effects are included. The RPIC model is fully three dimensional and has been implemented in two dimensions on the Accelerated Strategic Computing Initiative (ASCI) parallel computer at Los Alamos National Laboratory, and the resulting simulation code has been named ASPEN. The authors believe this code is the first particle-in-cell code capable of simulating the interaction between low-frequency and high-frequency parametric instabilities in multiple dimensions. Test simulations of stimulated Raman scattering, stimulated Brillouin scattering, and Langmuir decay instability are presented

Genome-based microbial ecology of anammox granules in a full-scale wastewater treatment system.

Science.gov (United States)

Speth, Daan R; In 't Zandt, Michiel H; Guerrero-Cruz, Simon; Dutilh, Bas E; Jetten, Mike S M

2016-03-31

Partial-nitritation anammox (PNA) is a novel wastewater treatment procedure for energy-efficient ammonium removal. Here we use genome-resolved metagenomics to build a genome-based ecological model of the microbial community in a full-scale PNA reactor. Sludge from the bioreactor examined here is used to seed reactors in wastewater treatment plants around the world; however, the role of most of its microbial community in ammonium removal remains unknown. Our analysis yielded 23 near-complete draft genomes that together represent the majority of the microbial community. We assign these genomes to distinct anaerobic and aerobic microbial communities. In the aerobic community, nitrifying organisms and heterotrophs predominate. In the anaerobic community, widespread potential for partial denitrification suggests a nitrite loop increases treatment efficiency. Of our genomes, 19 have no previously cultivated or sequenced close relatives and six belong to bacterial phyla without any cultivated members, including the most complete Omnitrophica (formerly OP3) genome to date.

GIGGLE: a search engine for large-scale integrated genome analysis.

Science.gov (United States)

Layer, Ryan M; Pedersen, Brent S; DiSera, Tonya; Marth, Gabor T; Gertz, Jason; Quinlan, Aaron R

2018-02-01

GIGGLE is a genomics search engine that identifies and ranks the significance of genomic loci shared between query features and thousands of genome interval files. GIGGLE (https://github.com/ryanlayer/giggle) scales to billions of intervals and is over three orders of magnitude faster than existing methods. Its speed extends the accessibility and utility of resources such as ENCODE, Roadmap Epigenomics, and GTEx by facilitating data integration and hypothesis generation.

GIGGLE: a search engine for large-scale integrated genome analysis

Science.gov (United States)

Layer, Ryan M; Pedersen, Brent S; DiSera, Tonya; Marth, Gabor T; Gertz, Jason; Quinlan, Aaron R

2018-01-01

GIGGLE is a genomics search engine that identifies and ranks the significance of genomic loci shared between query features and thousands of genome interval files. GIGGLE (https://github.com/ryanlayer/giggle) scales to billions of intervals and is over three orders of magnitude faster than existing methods. Its speed extends the accessibility and utility of resources such as ENCODE, Roadmap Epigenomics, and GTEx by facilitating data integration and hypothesis generation. PMID:29309061

Kinetic Model of Growth of Arthropoda Populations

Science.gov (United States)

Ershov, Yu. A.; Kuznetsov, M. A.

2018-05-01

Kinetic equations were derived for calculating the growth of crustacean populations ( Crustacea) based on the biological growth model suggested earlier using shrimp ( Caridea) populations as an example. The development cycle of successive stages for populations can be represented in the form of quasi-chemical equations. The kinetic equations that describe the development cycle of crustaceans allow quantitative prediction of the development of populations depending on conditions. In contrast to extrapolation-simulation models, in the developed kinetic model of biological growth the kinetic parameters are the experimental characteristics of population growth. Verification and parametric identification of the developed model on the basis of the experimental data showed agreement with experiment within the error of the measurement technique.

Genome-scale metabolic analysis of Clostridium thermocellum for bioethanol production

Directory of Open Access Journals (Sweden)

Brooks J Paul

2010-03-01

Full Text Available Abstract Background Microorganisms possess diverse metabolic capabilities that can potentially be leveraged for efficient production of biofuels. Clostridium thermocellum (ATCC 27405 is a thermophilic anaerobe that is both cellulolytic and ethanologenic, meaning that it can directly use the plant sugar, cellulose, and biochemically convert it to ethanol. A major challenge in using microorganisms for chemical production is the need to modify the organism to increase production efficiency. The process of properly engineering an organism is typically arduous. Results Here we present a genome-scale model of C. thermocellum metabolism, iSR432, for the purpose of establishing a computational tool to study the metabolic network of C. thermocellum and facilitate efforts to engineer C. thermocellum for biofuel production. The model consists of 577 reactions involving 525 intracellular metabolites, 432 genes, and a proteomic-based representation of a cellulosome. The process of constructing this metabolic model led to suggested annotation refinements for 27 genes and identification of areas of metabolism requiring further study. The accuracy of the iSR432 model was tested using experimental growth and by-product secretion data for growth on cellobiose and fructose. Analysis using this model captures the relationship between the reduction-oxidation state of the cell and ethanol secretion and allowed for prediction of gene deletions and environmental conditions that would increase ethanol production. Conclusions By incorporating genomic sequence data, network topology, and experimental measurements of enzyme activities and metabolite fluxes, we have generated a model that is reasonably accurate at predicting the cellular phenotype of C. thermocellum and establish a strong foundation for rational strain design. In addition, we are able to draw some important conclusions regarding the underlying metabolic mechanisms for observed behaviors of C. thermocellum

Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis

Science.gov (United States)

Broddrick, Jared T.; Rubin, Benjamin E.; Welkie, David G.; Du, Niu; Mih, Nathan; Diamond, Spencer; Lee, Jenny J.; Golden, Susan S.; Palsson, Bernhard O.

2016-01-01

The model cyanobacterium, Synechococcus elongatus PCC 7942, is a genetically tractable obligate phototroph that is being developed for the bioproduction of high-value chemicals. Genome-scale models (GEMs) have been successfully used to assess and engineer cellular metabolism; however, GEMs of phototrophic metabolism have been limited by the lack of experimental datasets for model validation and the challenges of incorporating photon uptake. Here, we develop a GEM of metabolism in S. elongatus using random barcode transposon site sequencing (RB-TnSeq) essential gene and physiological data specific to photoautotrophic metabolism. The model explicitly describes photon absorption and accounts for shading, resulting in the characteristic linear growth curve of photoautotrophs. GEM predictions of gene essentiality were compared with data obtained from recent dense-transposon mutagenesis experiments. This dataset allowed major improvements to the accuracy of the model. Furthermore, discrepancies between GEM predictions and the in vivo dataset revealed biological characteristics, such as the importance of a truncated, linear TCA pathway, low flux toward amino acid synthesis from photorespiration, and knowledge gaps within nucleotide metabolism. Coupling of strong experimental support and photoautotrophic modeling methods thus resulted in a highly accurate model of S. elongatus metabolism that highlights previously unknown areas of S. elongatus biology. PMID:27911809

Quantitative Assessment of Thermodynamic Constraints on the Solution Space of Genome-Scale Metabolic Models

Science.gov (United States)

Hamilton, Joshua J.; Dwivedi, Vivek; Reed, Jennifer L.

2013-01-01

Constraint-based methods provide powerful computational techniques to allow understanding and prediction of cellular behavior. These methods rely on physiochemical constraints to eliminate infeasible behaviors from the space of available behaviors. One such constraint is thermodynamic feasibility, the requirement that intracellular flux distributions obey the laws of thermodynamics. The past decade has seen several constraint-based methods that interpret this constraint in different ways, including those that are limited to small networks, rely on predefined reaction directions, and/or neglect the relationship between reaction free energies and metabolite concentrations. In this work, we utilize one such approach, thermodynamics-based metabolic flux analysis (TMFA), to make genome-scale, quantitative predictions about metabolite concentrations and reaction free energies in the absence of prior knowledge of reaction directions, while accounting for uncertainties in thermodynamic estimates. We applied TMFA to a genome-scale network reconstruction of Escherichia coli and examined the effect of thermodynamic constraints on the flux space. We also assessed the predictive performance of TMFA against gene essentiality and quantitative metabolomics data, under both aerobic and anaerobic, and optimal and suboptimal growth conditions. Based on these results, we propose that TMFA is a useful tool for validating phenotypes and generating hypotheses, and that additional types of data and constraints can improve predictions of metabolite concentrations. PMID:23870272

Point kinetics modeling

International Nuclear Information System (INIS)

Kimpland, R.H.

1996-01-01

A normalized form of the point kinetics equations, a prompt jump approximation, and the Nordheim-Fuchs model are used to model nuclear systems. Reactivity feedback mechanisms considered include volumetric expansion, thermal neutron temperature effect, Doppler effect and void formation. A sample problem of an excursion occurring in a plutonium solution accidentally formed in a glovebox is presented

Multi-scale method for the resolution of the neutronic kinetics equations

International Nuclear Information System (INIS)

Chauvet, St.

2008-10-01

In this PhD thesis and in order to improve the time/precision ratio of the numerical simulation calculations, we investigate multi-scale techniques for the resolution of the reactor kinetics equations. We choose to focus on the mixed dual diffusion approximation and the quasi-static methods. We introduce a space dependency for the amplitude function which only depends on the time variable in the standard quasi-static context. With this new factorization, we develop two mixed dual problems which can be solved with Cea's solver MINOS. An algorithm is implemented, performing the resolution of these problems defined on different scales (for time and space). We name this approach: the Local Quasi-Static method. We present here this new multi-scale approach and its implementation. The inherent details of amplitude and shape treatments are discussed and justified. Results and performances, compared to MINOS, are studied. They illustrate the improvement on the time/precision ratio for kinetics calculations. Furthermore, we open some new possibilities to parallelize computations with MINOS. For the future, we also introduce some improvement tracks with adaptive scales. (author)

Modelling and experimental evaluation of reaction kinetics in reactive extraction for chiral separation of amines, amino acids and amino-alcohols

NARCIS (Netherlands)

Steensma, M.; Kuipers, N.J.M.; de Haan, A.B.; Kwant, Gerard

2007-01-01

This paper reports on determination of the intrinsic reaction kinetics in reactive extraction of chiral compounds. It is important to know the mass transfer rates and reaction kinetics separately for a reliable scale-up. A kinetic model is developed to interpret the experimental data from the

A kinetic model for the first stage of pygas upgrading

Directory of Open Access Journals (Sweden)

J. L. de Medeiros

2007-03-01

Full Text Available Pyrolysis gasoline - PYGAS - is an intermediate boiling product of naphtha steam cracking with a high octane number and high aromatic/unsaturated contents. Due to stabilization concerns, PYGAS must be hydrotreated in two stages. The first stage uses a mild trickle-bed conversion for removing extremely reactive species (styrene, dienes and olefins prior to the more severe second stage where sulfured and remaining olefins are hydrogenated in gas phase. This work addresses the reaction network and two-phase kinetic model for the first stage of PYGAS upgrading. Nonlinear estimation was used for model tuning with kinetic data obtained in bench-scale trickle-bed hydrogenation with a commercial Pd/Al2O3 catalyst. On-line sampling experiments were designed to study the influence of variables - temperature and spatial velocity - on the conversion of styrene, dienes and olefins.

Integration of Extended MHD and Kinetic Effects in Global Magnetosphere Models

Science.gov (United States)

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.

Chemical Kinetic Modeling of 2-Methylhexane Combustion

KAUST Repository

Mohamed, Samah Y.

2015-03-30

Accurate chemical kinetic combustion models of lightly branched alkanes (e.g., 2-methylalkanes) are important for investigating the combustion behavior of diesel, gasoline, and aviation fuels. Improving the fidelity of existing kinetic models is a necessity, as new experiments and advanced theories show inaccuracy in certain portions of the models. This study focuses on updating thermodynamic data and kinetic model for a gasoline surrogate fuel, 2-methylhexane, with recently published group values and rate rules. These update provides a better agreement with rapid compression machine measurements of ignition delay time, while also strengthening the fundamental basis of the model.

Modeling composting kinetics: A review of approaches

NARCIS (Netherlands)

Hamelers, H.V.M.

2004-01-01

Composting kinetics modeling is necessary to design and operate composting facilities that comply with strict market demands and tight environmental legislation. Current composting kinetics modeling can be characterized as inductive, i.e. the data are the starting point of the modeling process and

Visualisation and orbital-free parametrisation of the large-Z scaling of the kinetic energy density of atoms

Science.gov (United States)

Cancio, Antonio C.; Redd, Jeremy J.

2017-03-01

The scaling of neutral atoms to large Z, combining periodicity with a gradual trend to homogeneity, is a fundamental probe of density functional theory, one that has driven recent advances in understanding both the kinetic and exchange-correlation energies. Although research focus is normally upon the scaling of integrated energies, insights can also be gained from energy densities. We visualise the scaling of the positive-definite kinetic energy density (KED) in closed-shell atoms, in comparison to invariant quantities based upon the gradient and Laplacian of the density. We notice a striking fit of the KED within the core of any atom to a gradient expansion using both the gradient and the Laplacian, appearing as an asymptotic limit around which the KED oscillates. The gradient expansion is qualitatively different from that derived from first principles for a slowly varying electron gas and is correlated with a nonzero Pauli contribution to the KED near the nucleus. We propose and explore orbital-free meta-GGA models for the kinetic energy to describe these features, with some success, but the effects of quantum oscillations in the inner shells of atoms make a complete parametrisation difficult. We discuss implications for improved orbital-free description of molecular properties.

A systems approach to predict oncometabolites via context-specific genome-scale metabolic networks.

Directory of Open Access Journals (Sweden)

Hojung Nam

2014-09-01

Full Text Available Altered metabolism in cancer cells has been viewed as a passive response required for a malignant transformation. However, this view has changed through the recently described metabolic oncogenic factors: mutated isocitrate dehydrogenases (IDH, succinate dehydrogenase (SDH, and fumarate hydratase (FH that produce oncometabolites that competitively inhibit epigenetic regulation. In this study, we demonstrate in silico predictions of oncometabolites that have the potential to dysregulate epigenetic controls in nine types of cancer by incorporating massive scale genetic mutation information (collected from more than 1,700 cancer genomes, expression profiling data, and deploying Recon 2 to reconstruct context-specific genome-scale metabolic models. Our analysis predicted 15 compounds and 24 substructures of potential oncometabolites that could result from the loss-of-function and gain-of-function mutations of metabolic enzymes, respectively. These results suggest a substantial potential for discovering unidentified oncometabolites in various forms of cancers.

A Biophysical Model of CRISPR/Cas9 Activity for Rational Design of Genome Editing and Gene Regulation

Science.gov (United States)

Farasat, Iman; Salis, Howard M.

2016-01-01

The ability to precisely modify genomes and regulate specific genes will greatly accelerate several medical and engineering applications. The CRISPR/Cas9 (Type II) system binds and cuts DNA using guide RNAs, though the variables that control its on-target and off-target activity remain poorly characterized. Here, we develop and parameterize a system-wide biophysical model of Cas9-based genome editing and gene regulation to predict how changing guide RNA sequences, DNA superhelical densities, Cas9 and crRNA expression levels, organisms and growth conditions, and experimental conditions collectively control the dynamics of dCas9-based binding and Cas9-based cleavage at all DNA sites with both canonical and non-canonical PAMs. We combine statistical thermodynamics and kinetics to model Cas9:crRNA complex formation, diffusion, site selection, reversible R-loop formation, and cleavage, using large amounts of structural, biochemical, expression, and next-generation sequencing data to determine kinetic parameters and develop free energy models. Our results identify DNA supercoiling as a novel mechanism controlling Cas9 binding. Using the model, we predict Cas9 off-target binding frequencies across the lambdaphage and human genomes, and explain why Cas9’s off-target activity can be so high. With this improved understanding, we propose several rules for designing experiments for minimizing off-target activity. We also discuss the implications for engineering dCas9-based genetic circuits. PMID:26824432

A kinetic model of municipal sludge degradation during non-catalytic wet oxidation.

Science.gov (United States)

Prince-Pike, Arrian; Wilson, David I; Baroutian, Saeid; Andrews, John; Gapes, Daniel J

2015-12-15

Wet oxidation is a successful process for the treatment of municipal sludge. In addition, the resulting effluent from wet oxidation is a useful carbon source for subsequent biological nutrient removal processes in wastewater treatment. Owing to limitations with current kinetic models, this study produced a kinetic model which predicts the concentrations of key intermediate components during wet oxidation. The model was regressed from lab-scale experiments and then subsequently validated using data from a wet oxidation pilot plant. The model was shown to be accurate in predicting the concentrations of each component, and produced good results when applied to a plant 500 times larger in size. A statistical study was undertaken to investigate the validity of the regressed model parameters. Finally the usefulness of the model was demonstrated by suggesting optimum operating conditions such that volatile fatty acids were maximised. Copyright © 2015 Elsevier Ltd. All rights reserved.

Rapid Prototyping of Microbial Cell Factories via Genome-scale Engineering

Science.gov (United States)

Si, Tong; Xiao, Han; Zhao, Huimin

2014-01-01

Advances in reading, writing and editing genetic materials have greatly expanded our ability to reprogram biological systems at the resolution of a single nucleotide and on the scale of a whole genome. Such capacity has greatly accelerated the cycles of design, build and test to engineer microbes for efficient synthesis of fuels, chemicals and drugs. In this review, we summarize the emerging technologies that have been applied, or are potentially useful for genome-scale engineering in microbial systems. We will focus on the development of high-throughput methodologies, which may accelerate the prototyping of microbial cell factories. PMID:25450192

Kinetic study on the effect of temperature on biogas production using a lab scale batch reactor.

Science.gov (United States)

Deepanraj, B; Sivasubramanian, V; Jayaraj, S

2015-11-01

In the present study, biogas production from food waste through anaerobic digestion was carried out in a 2l laboratory-scale batch reactor operating at different temperatures with a hydraulic retention time of 30 days. The reactors were operated with a solid concentration of 7.5% of total solids and pH 7. The food wastes used in this experiment were subjected to characterization studies before and after digestion. Modified Gompertz model and Logistic model were used for kinetic study of biogas production. The kinetic parameters, biogas yield potential of the substrate (B), the maximum biogas production rate (Rb) and the duration of lag phase (λ), coefficient of determination (R(2)) and root mean square error (RMSE) were estimated in each case. The effect of temperature on biogas production was evaluated experimentally and compared with the results of kinetic study. The results demonstrated that the reactor with operating temperature of 50°C achieved maximum cumulative biogas production of 7556ml with better biodegradation efficiency. Copyright © 2015 Elsevier Inc. All rights reserved.

A critical look at the kinetic models of thermoluminescence-II. Non-first order kinetics

International Nuclear Information System (INIS)

Sunta, C M; Ayta, W E F; Chubaci, J F D; Watanabe, S

2005-01-01

Non-first order (FO) kinetics models are of three types; second order (SO), general order (GO) and mixed order (MO). It is shown that all three of these have constraints in their energy level schemes and their applicable parameter values. In nature such restrictions are not expected to exist. The thermoluminescence (TL) glow peaks produced by these models shift their position and change their shape as the trap occupancies change. Such characteristics are very unlike those found in samples of real materials. In these models, in general, retrapping predominates over recombination. It is shown that the quasi-equilibrium (QE) assumption implied in the derivation of the TL equation of these models is quite valid, thus disproving earlier workers' conclusion that QE cannot be held under retrapping dominant conditions. However notwithstanding their validity, they suffer from the shortcomings as stated above and have certain lacunae. For example, the kinetic order (KO) parameter and the pre-exponential factor which are assumed to be the constant parameters of the GO kinetics expression turn out to be variables when this expression is applied to plausible physical models. Further, in glow peak characterization using the GO expression, the quality of fit is found to deteriorate when the best fitted value of KO parameter is different from 1 and 2. This means that the found value of the basic parameter, namely the activation energy, becomes subject to error. In the MO kinetics model, the value of the KO parameter α would change with dose, and thus in this model also, as in the GO model, no single value of KO can be assigned to a given glow peak. The paper discusses TL of real materials having characteristics typically like those of FO kinetics. Theoretically too, a plausible physical model of TL emission produces glow peaks which have characteristics of FO kinetics under a wide variety of parametric combinations. In the background of the above findings, it is suggested that

A site specific model and analysis of the neutral somatic mutation rate in whole-genome cancer data.

Science.gov (United States)

Bertl, Johanna; Guo, Qianyun; Juul, Malene; Besenbacher, Søren; Nielsen, Morten Muhlig; Hornshøj, Henrik; Pedersen, Jakob Skou; Hobolth, Asger

2018-04-19

Detailed modelling of the neutral mutational process in cancer cells is crucial for identifying driver mutations and understanding the mutational mechanisms that act during cancer development. The neutral mutational process is very complex: whole-genome analyses have revealed that the mutation rate differs between cancer types, between patients and along the genome depending on the genetic and epigenetic context. Therefore, methods that predict the number of different types of mutations in regions or specific genomic elements must consider local genomic explanatory variables. A major drawback of most methods is the need to average the explanatory variables across the entire region or genomic element. This procedure is particularly problematic if the explanatory variable varies dramatically in the element under consideration. To take into account the fine scale of the explanatory variables, we model the probabilities of different types of mutations for each position in the genome by multinomial logistic regression. We analyse 505 cancer genomes from 14 different cancer types and compare the performance in predicting mutation rate for both regional based models and site-specific models. We show that for 1000 randomly selected genomic positions, the site-specific model predicts the mutation rate much better than regional based models. We use a forward selection procedure to identify the most important explanatory variables. The procedure identifies site-specific conservation (phyloP), replication timing, and expression level as the best predictors for the mutation rate. Finally, our model confirms and quantifies certain well-known mutational signatures. We find that our site-specific multinomial regression model outperforms the regional based models. The possibility of including genomic variables on different scales and patient specific variables makes it a versatile framework for studying different mutational mechanisms. Our model can serve as the neutral null model

Quantitative assessment of thermodynamic constraints on the solution space of genome-scale metabolic models.

Science.gov (United States)

Hamilton, Joshua J; Dwivedi, Vivek; Reed, Jennifer L

2013-07-16

Constraint-based methods provide powerful computational techniques to allow understanding and prediction of cellular behavior. These methods rely on physiochemical constraints to eliminate infeasible behaviors from the space of available behaviors. One such constraint is thermodynamic feasibility, the requirement that intracellular flux distributions obey the laws of thermodynamics. The past decade has seen several constraint-based methods that interpret this constraint in different ways, including those that are limited to small networks, rely on predefined reaction directions, and/or neglect the relationship between reaction free energies and metabolite concentrations. In this work, we utilize one such approach, thermodynamics-based metabolic flux analysis (TMFA), to make genome-scale, quantitative predictions about metabolite concentrations and reaction free energies in the absence of prior knowledge of reaction directions, while accounting for uncertainties in thermodynamic estimates. We applied TMFA to a genome-scale network reconstruction of Escherichia coli and examined the effect of thermodynamic constraints on the flux space. We also assessed the predictive performance of TMFA against gene essentiality and quantitative metabolomics data, under both aerobic and anaerobic, and optimal and suboptimal growth conditions. Based on these results, we propose that TMFA is a useful tool for validating phenotypes and generating hypotheses, and that additional types of data and constraints can improve predictions of metabolite concentrations. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Genome-scale comparison and constraint-based metabolic reconstruction of the facultative anaerobic Fe(III-reducer Rhodoferax ferrireducens

Directory of Open Access Journals (Sweden)

Daugherty Sean

2009-09-01

Full Text Available Abstract Background Rhodoferax ferrireducens is a metabolically versatile, Fe(III-reducing, subsurface microorganism that is likely to play an important role in the carbon and metal cycles in the subsurface. It also has the unique ability to convert sugars to electricity, oxidizing the sugars to carbon dioxide with quantitative electron transfer to graphite electrodes in microbial fuel cells. In order to expand our limited knowledge about R. ferrireducens, the complete genome sequence of this organism was further annotated and then the physiology of R. ferrireducens was investigated with a constraint-based, genome-scale in silico metabolic model and laboratory studies. Results The iterative modeling and experimental approach unveiled exciting, previously unknown physiological features, including an expanded range of substrates that support growth, such as cellobiose and citrate, and provided additional insights into important features such as the stoichiometry of the electron transport chain and the ability to grow via fumarate dismutation. Further analysis explained why R. ferrireducens is unable to grow via photosynthesis or fermentation of sugars like other members of this genus and uncovered novel genes for benzoate metabolism. The genome also revealed that R. ferrireducens is well-adapted for growth in the subsurface because it appears to be capable of dealing with a number of environmental insults, including heavy metals, aromatic compounds, nutrient limitation and oxidative stress. Conclusion This study demonstrates that combining genome-scale modeling with the annotation of a new genome sequence can guide experimental studies and accelerate the understanding of the physiology of under-studied yet environmentally relevant microorganisms.

Kinetic mixing and the supersymmetric gauge hierarchy

International Nuclear Information System (INIS)

Dienes, K.R.; Kolda, C.; March-Russell, J.

1997-01-01

The most general Lagrangian for a model with two U(1) gauge symmetries contains a renormalizable operator which mixes their gauge kinetic terms. Such kinetic mixing can be generated at arbitrarily high scales but will not be suppressed by large masses. In models whose supersymmetry (SUSY)-breaking hidden sectors contain U(1) gauge factors, we show that such terms will generically arise and communicate SUSY breaking to the visible sector through mixing with hypercharge. In the context of the usual supergravity- or gauge-mediated communication scenarios with D-terms of order the fundamental scale of SUSY breaking, this effect can destabilize the gauge hierarchy. Even in models for which kinetic mixing is suppressed or the D-terms are arranged to be small, this effect is a potentially large correction to the soft scalar masses and therefore introduces a new measurable low-energy parameter. We calculate the size of kinetic mixing both in field theory and in string theory, and argue that appreciable kinetic mixing is a generic feature of string models. We conclude that the possibility of kinetic mixing effects cannot be ignored in model building and in phenomenological studies of the low-energy SUSY spectra. (orig.)

Modeling the homogenization kinetics of as-cast U-10wt% Mo alloys

Energy Technology Data Exchange (ETDEWEB)

Xu, Zhijie, E-mail: zhijie.xu@pnnl.gov [Computational Mathematics Group, Pacific Northwest National Laboratory, Richland, WA 99352 (United States); Joshi, Vineet [Energy Processes & Materials Division, Pacific Northwest National Laboratory, Richland, WA 99352 (United States); Hu, Shenyang [Reactor Materials & Mechanical Design, Pacific Northwest National Laboratory, Richland, WA 99352 (United States); Paxton, Dean [Nuclear Engineering and Analysis Group, Pacific Northwest National Laboratory, Richland, WA 99352 (United States); Lavender, Curt [Energy Processes & Materials Division, Pacific Northwest National Laboratory, Richland, WA 99352 (United States); Burkes, Douglas [Nuclear Engineering and Analysis Group, Pacific Northwest National Laboratory, Richland, WA 99352 (United States)

2016-04-01

Low-enriched U-22at% Mo (U–10Mo) alloy has been considered as an alternative material to replace the highly enriched fuels in research reactors. For the U–10Mo to work effectively and replace the existing fuel material, a thorough understanding of the microstructure development from as-cast to the final formed structure is required. The as-cast microstructure typically resembles an inhomogeneous microstructure with regions containing molybdenum-rich and -lean regions, which may affect the processing and possibly the in-reactor performance. This as-cast structure must be homogenized by thermal treatment to produce a uniform Mo distribution. The development of a modeling capability will improve the understanding of the effect of initial microstructures on the Mo homogenization kinetics. In the current work, we investigated the effect of as-cast microstructure on the homogenization kinetics. The kinetics of the homogenization was modeled based on a rigorous algorithm that relates the line scan data of Mo concentration to the gray scale in energy dispersive spectroscopy images, which was used to generate a reconstructed Mo concentration map. The map was then used as realistic microstructure input for physics-based homogenization models, where the entire homogenization kinetics can be simulated and validated against the available experiment data at different homogenization times and temperatures.

Genome-scale model-driven strain design for dicarboxylic acid production in Yarrowia lipolytica.

Science.gov (United States)

Mishra, Pranjul; Lee, Na-Rae; Lakshmanan, Meiyappan; Kim, Minsuk; Kim, Byung-Gee; Lee, Dong-Yup

2018-03-19

Recently, there have been several attempts to produce long-chain dicarboxylic acids (DCAs) in various microbial hosts. Of these, Yarrowia lipolytica has great potential due to its oleaginous characteristics and unique ability to utilize hydrophobic substrates. However, Y. lipolytica should be further engineered to make it more competitive: the current approaches are mostly intuitive and cumbersome, thus limiting its industrial application. In this study, we proposed model-guided metabolic engineering strategies for enhanced production of DCAs in Y. lipolytica. At the outset, we reconstructed genome-scale metabolic model (GSMM) of Y. lipolytica (iYLI647) by substantially expanding the previous models. Subsequently, the model was validated using three sets of published culture experiment data. It was finally exploited to identify genetic engineering targets for overexpression, knockout, and cofactor modification by applying several in silico strain design methods, which potentially give rise to high yield production of the industrially relevant long-chain DCAs, e.g., dodecanedioic acid (DDDA). The resultant targets include (1) malate dehydrogenase and malic enzyme genes and (2) glutamate dehydrogenase gene, in silico overexpression of which generated additional NADPH required for fatty acid synthesis, leading to the increased DDDA fluxes by 48% and 22% higher, respectively, compared to wild-type. We further investigated the effect of supplying branched-chain amino acids on the acetyl-CoA turn-over rate which is key metabolite for fatty acid synthesis, suggesting their significance for production of DDDA in Y. lipolytica. In silico model-based strain design strategies allowed us to identify several metabolic engineering targets for overproducing DCAs in lipid accumulating yeast, Y. lipolytica. Thus, the current study can provide a methodological framework that is applicable to other oleaginous yeasts for value-added biochemical production.

Computer-Aided Construction of Chemical Kinetic Models

Energy Technology Data Exchange (ETDEWEB)

Green, William H. [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)

2014-12-31

The combustion chemistry of even simple fuels can be extremely complex, involving hundreds or thousands of kinetically significant species. The most reasonable way to deal with this complexity is to use a computer not only to numerically solve the kinetic model, but also to construct the kinetic model in the first place. Because these large models contain so many numerical parameters (e.g. rate coefficients, thermochemistry) one never has sufficient data to uniquely determine them all experimentally. Instead one must work in “predictive” mode, using theoretical rather than experimental values for many of the numbers in the model, and as appropriate refining the most sensitive numbers through experiments. Predictive chemical kinetics is exactly what is needed for computer-aided design of combustion systems based on proposed alternative fuels, particularly for early assessment of the value and viability of proposed new fuels before those fuels are commercially available. This project was aimed at making accurate predictive chemical kinetics practical; this is a challenging goal which requires a range of science advances. The project spanned a wide range from quantum chemical calculations on individual molecules and elementary-step reactions, through the development of improved rate/thermo calculation procedures, the creation of algorithms and software for constructing and solving kinetic simulations, the invention of methods for model-reduction while maintaining error control, and finally comparisons with experiment. Many of the parameters in the models were derived from quantum chemistry calculations, and the models were compared with experimental data measured in our lab or in collaboration with others.

Kinetic model for torrefaction of wood chips in a pilot-scale continuous reactor

DEFF Research Database (Denmark)

Shang, Lei; Ahrenfeldt, Jesper; Holm, Jens Kai

2014-01-01

accordance with the model data. In an additional step a continuous, pilot scale reactor was built to produce torrefied wood chips in large quantities. The "two-step reaction in series" model was applied to predict the mass yield of the torrefaction reaction. Parameters used for the calculation were...... at different torrefaction temperatures, it was possible to predict the HHV of torrefied wood chips from the pilot reactor. The results from this study and the presented modeling approach can be used to predict the product quality from pilot scale torrefaction reactors based on small scale experiments and could...

Study of physical mechanisms and their influence on dry anaerobic digestion kinetics: experimentations and modelization

International Nuclear Information System (INIS)

Bollon, Julien

2012-01-01

Anaerobic digestion is a biological process that converts organic matter into a methane rich gas (biogas). Among industrial technologies, dry processes (above 15 % total solid content) are more and more used because of their advantages in comparison with conventional wet processes. However, dry anaerobic digestion processes are poorly known and studied because of the 'pasty' nature of digestion media (rheological behavior, equilibria, transfers, biological kinetics). This thesis focuses on two major aspects: i) the nature of the chemical equilibria (sorption, diffusion) involved in digestion media, ii) the establishment and application of a kinetic model adapted to dry media. We first demonstrated that the diffusional mass transfer is highly reduced with increasing total solid without any agitation. One of the consequences is the importance of the liquid-gas transfer for the production of biogas. Then, we have developed a dedicated kinetic model that enables to understand the variability of the kinetic with total solid content. The impacts of this work are both at the laboratory scale, especially for the operation of Specific Methanogenic Activity tests, and at industrial scale, with the need to control total solid content for optimal efficiency, and to adapt the agitation to improve degradation yields. The developed model can be useful for the design and operation of bio-methanization facilities. (author) [fr

Chemical kinetics and combustion modeling

Energy Technology Data Exchange (ETDEWEB)

Miller, J.A. [Sandia National Laboratories, Livermore, CA (United States)

1993-12-01

The goal of this program is to gain qualitative insight into how pollutants are formed in combustion systems and to develop quantitative mathematical models to predict their formation rates. The approach is an integrated one, combining low-pressure flame experiments, chemical kinetics modeling, theory, and kinetics experiments to gain as clear a picture as possible of the process in question. These efforts are focused on problems involved with the nitrogen chemistry of combustion systems and on the formation of soot and PAH in flames.

Large-Scale Sequencing: The Future of Genomic Sciences Colloquium

Energy Technology Data Exchange (ETDEWEB)

Margaret Riley; Merry Buckley

2009-01-01

Genetic sequencing and the various molecular techniques it has enabled have revolutionized the field of microbiology. Examining and comparing the genetic sequences borne by microbes - including bacteria, archaea, viruses, and microbial eukaryotes - provides researchers insights into the processes microbes carry out, their pathogenic traits, and new ways to use microorganisms in medicine and manufacturing. Until recently, sequencing entire microbial genomes has been laborious and expensive, and the decision to sequence the genome of an organism was made on a case-by-case basis by individual researchers and funding agencies. Now, thanks to new technologies, the cost and effort of sequencing is within reach for even the smallest facilities, and the ability to sequence the genomes of a significant fraction of microbial life may be possible. The availability of numerous microbial genomes will enable unprecedented insights into microbial evolution, function, and physiology. However, the current ad hoc approach to gathering sequence data has resulted in an unbalanced and highly biased sampling of microbial diversity. A well-coordinated, large-scale effort to target the breadth and depth of microbial diversity would result in the greatest impact. The American Academy of Microbiology convened a colloquium to discuss the scientific benefits of engaging in a large-scale, taxonomically-based sequencing project. A group of individuals with expertise in microbiology, genomics, informatics, ecology, and evolution deliberated on the issues inherent in such an effort and generated a set of specific recommendations for how best to proceed. The vast majority of microbes are presently uncultured and, thus, pose significant challenges to such a taxonomically-based approach to sampling genome diversity. However, we have yet to even scratch the surface of the genomic diversity among cultured microbes. A coordinated sequencing effort of cultured organisms is an appropriate place to begin

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

Science.gov (United States)

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.

Rapid prototyping of microbial cell factories via genome-scale engineering.

Science.gov (United States)

Si, Tong; Xiao, Han; Zhao, Huimin

2015-11-15

Advances in reading, writing and editing genetic materials have greatly expanded our ability to reprogram biological systems at the resolution of a single nucleotide and on the scale of a whole genome. Such capacity has greatly accelerated the cycles of design, build and test to engineer microbes for efficient synthesis of fuels, chemicals and drugs. In this review, we summarize the emerging technologies that have been applied, or are potentially useful for genome-scale engineering in microbial systems. We will focus on the development of high-throughput methodologies, which may accelerate the prototyping of microbial cell factories. Copyright © 2014 Elsevier Inc. All rights reserved.

Small velocity and finite temperature variations in kinetic relaxation models

KAUST Repository

Markowich, Peter; Jü ngel, Ansgar; Aoki, Kazuo

2010-01-01

A small Knuden number analysis of a kinetic equation in the diffusive scaling is performed. The collision kernel is of BGK type with a general local Gibbs state. Assuming that the flow velocity is of the order of the Knudsen number, a Hilbert expansion yields a macroscopic model with finite temperature variations, whose complexity lies in between the hydrodynamic and the energy-transport equations. Its mathematical structure is explored and macroscopic models for specific examples of the global Gibbs state are presented. © American Institute of Mathematical Sciences.

A discontinuous Galerkin method on kinetic flocking models

OpenAIRE

Tan, Changhui

2014-01-01

We study kinetic representations of flocking models. They arise from agent-based models for self-organized dynamics, such as Cucker-Smale and Motsch-Tadmor models. We prove flocking behavior for the kinetic descriptions of flocking systems, which indicates a concentration in velocity variable in infinite time. We propose a discontinuous Galerkin method to treat the asymptotic $\\delta$-singularity, and construct high order positive preserving scheme to solve kinetic flocking systems.

A genome-wide, fine-scale map of natural pigmentation variation in Drosophila melanogaster.

Directory of Open Access Journals (Sweden)

Héloïse Bastide

2013-06-01

Full Text Available Various approaches can be applied to uncover the genetic basis of natural phenotypic variation, each with their specific strengths and limitations. Here, we use a replicated genome-wide association approach (Pool-GWAS to fine-scale map genomic regions contributing to natural variation in female abdominal pigmentation in Drosophila melanogaster, a trait that is highly variable in natural populations and highly heritable in the laboratory. We examined abdominal pigmentation phenotypes in approximately 8000 female European D. melanogaster, isolating 1000 individuals with extreme phenotypes. We then used whole-genome Illumina sequencing to identify single nucleotide polymorphisms (SNPs segregating in our sample, and tested these for associations with pigmentation by contrasting allele frequencies between replicate pools of light and dark individuals. We identify two small regions near the pigmentation genes tan and bric-à-brac 1, both corresponding to known cis-regulatory regions, which contain SNPs showing significant associations with pigmentation variation. While the Pool-GWAS approach suffers some limitations, its cost advantage facilitates replication and it can be applied to any non-model system with an available reference genome.

A genome-wide, fine-scale map of natural pigmentation variation in Drosophila melanogaster.

Science.gov (United States)

Bastide, Héloïse; Betancourt, Andrea; Nolte, Viola; Tobler, Raymond; Stöbe, Petra; Futschik, Andreas; Schlötterer, Christian

2013-06-01

Various approaches can be applied to uncover the genetic basis of natural phenotypic variation, each with their specific strengths and limitations. Here, we use a replicated genome-wide association approach (Pool-GWAS) to fine-scale map genomic regions contributing to natural variation in female abdominal pigmentation in Drosophila melanogaster, a trait that is highly variable in natural populations and highly heritable in the laboratory. We examined abdominal pigmentation phenotypes in approximately 8000 female European D. melanogaster, isolating 1000 individuals with extreme phenotypes. We then used whole-genome Illumina sequencing to identify single nucleotide polymorphisms (SNPs) segregating in our sample, and tested these for associations with pigmentation by contrasting allele frequencies between replicate pools of light and dark individuals. We identify two small regions near the pigmentation genes tan and bric-à-brac 1, both corresponding to known cis-regulatory regions, which contain SNPs showing significant associations with pigmentation variation. While the Pool-GWAS approach suffers some limitations, its cost advantage facilitates replication and it can be applied to any non-model system with an available reference genome.

KINETIC ALFVÉN WAVE GENERATION BY LARGE-SCALE PHASE MIXING

International Nuclear Information System (INIS)

Vásconez, C. L.; Pucci, F.; Valentini, F.; Servidio, S.; Malara, F.; Matthaeus, W. H.

2015-01-01

One view of the solar wind turbulence is that the observed highly anisotropic fluctuations at spatial scales near the proton inertial length d p may be considered as kinetic Alfvén waves (KAWs). In the present paper, we show how phase mixing of large-scale parallel-propagating Alfvén waves is an efficient mechanism for the production of KAWs at wavelengths close to d p and at a large propagation angle with respect to the magnetic field. Magnetohydrodynamic (MHD), Hall magnetohydrodynamic (HMHD), and hybrid Vlasov–Maxwell (HVM) simulations modeling the propagation of Alfvén waves in inhomogeneous plasmas are performed. In the linear regime, the role of dispersive effects is singled out by comparing MHD and HMHD results. Fluctuations produced by phase mixing are identified as KAWs through a comparison of polarization of magnetic fluctuations and wave-group velocity with analytical linear predictions. In the nonlinear regime, a comparison of HMHD and HVM simulations allows us to point out the role of kinetic effects in shaping the proton-distribution function. We observe the generation of temperature anisotropy with respect to the local magnetic field and the production of field-aligned beams. The regions where the proton-distribution function highly departs from thermal equilibrium are located inside the shear layers, where the KAWs are excited, this suggesting that the distortions of the proton distribution are driven by a resonant interaction of protons with KAW fluctuations. Our results are relevant in configurations where magnetic-field inhomogeneities are present, as, for example, in the solar corona, where the presence of Alfvén waves has been ascertained

KINETIC ALFVÉN WAVE GENERATION BY LARGE-SCALE PHASE MIXING

Energy Technology Data Exchange (ETDEWEB)

Vásconez, C. L.; Pucci, F.; Valentini, F.; Servidio, S.; Malara, F. [Dipartimento di Fisica, Università della Calabria, I-87036, Rende (CS) (Italy); Matthaeus, W. H. [Department of Physics and Astronomy, University of Delaware, DE 19716 (United States)

2015-12-10

One view of the solar wind turbulence is that the observed highly anisotropic fluctuations at spatial scales near the proton inertial length d{sub p} may be considered as kinetic Alfvén waves (KAWs). In the present paper, we show how phase mixing of large-scale parallel-propagating Alfvén waves is an efficient mechanism for the production of KAWs at wavelengths close to d{sub p} and at a large propagation angle with respect to the magnetic field. Magnetohydrodynamic (MHD), Hall magnetohydrodynamic (HMHD), and hybrid Vlasov–Maxwell (HVM) simulations modeling the propagation of Alfvén waves in inhomogeneous plasmas are performed. In the linear regime, the role of dispersive effects is singled out by comparing MHD and HMHD results. Fluctuations produced by phase mixing are identified as KAWs through a comparison of polarization of magnetic fluctuations and wave-group velocity with analytical linear predictions. In the nonlinear regime, a comparison of HMHD and HVM simulations allows us to point out the role of kinetic effects in shaping the proton-distribution function. We observe the generation of temperature anisotropy with respect to the local magnetic field and the production of field-aligned beams. The regions where the proton-distribution function highly departs from thermal equilibrium are located inside the shear layers, where the KAWs are excited, this suggesting that the distortions of the proton distribution are driven by a resonant interaction of protons with KAW fluctuations. Our results are relevant in configurations where magnetic-field inhomogeneities are present, as, for example, in the solar corona, where the presence of Alfvén waves has been ascertained.

MHD model including small-scale perturbations in a plasma with temperature variations

International Nuclear Information System (INIS)

Kuvshinov, B.N.; Mikhailovskii, A.B.

1996-01-01

The possibility is studied of using a hydrodynamic model to describe a magnetized plasma with density and temperature variations on scales that are arbitrary with respect to the ion Larmor radius. It is shown that the inertial component of the transverse ion thermal flux should be taken into account. This component is found from the collisionless kinetic equation. It can also be obtained from the equations of the Grad type. A set of two-dimensional hydrodynamic equations for ions is obtained with this component taken into account. These equations are used to derive model hydrodynamic expressions for the density and temperature variations. It is shown that, for large-scale perturbations (when the wavelengths are longer than the ion Larmor radius), the expressions derived coincide with the corresponding kinetic expressions and, for perturbations on sub-Larmor scales (when the wavelengths are shorter than the Larmor radius), they agree qualitatively. Hydrodynamic dispersion relations are derived for several types of drift waves with arbitrary wavenumbers. The range of applicability of the MHD model is determined from a comparison of these dispersion relations with the kinetic ones. It is noted that, on the basis of results obtained, drift effects can be included in numerical MHD codes for studying plasma instabilities in high-temperature regimes in tokamaks

Insertion Sequence-Caused Large Scale-Rearrangements in the Genome of Escherichia coli

Science.gov (United States)

2016-07-18

affordable ap- proach to genome-wide characterization of genetic varia - tion in bacterial and eukaryotic genomes (1–3). In addition to small-scale...Paired-End Reads), that uses a graph-based al- gorithm (27) capable of detecting most large-scale varia - tion involving repetitive regions, including novel...Avila,P., Grinsted,J. and De La Cruz,F. (1988) Analysis of the variable endpoints generated by one-ended transposition of Tn21.. J. Bacteriol., 170

Ensembl Genomes 2016: more genomes, more complexity.

Science.gov (United States)

Kersey, Paul Julian; Allen, James E; Armean, Irina; Boddu, Sanjay; Bolt, Bruce J; Carvalho-Silva, Denise; Christensen, Mikkel; Davis, Paul; Falin, Lee J; Grabmueller, Christoph; Humphrey, Jay; Kerhornou, Arnaud; Khobova, Julia; Aranganathan, Naveen K; Langridge, Nicholas; Lowy, Ernesto; McDowall, Mark D; Maheswari, Uma; Nuhn, Michael; Ong, Chuang Kee; Overduin, Bert; Paulini, Michael; Pedro, Helder; Perry, Emily; Spudich, Giulietta; Tapanari, Electra; Walts, Brandon; Williams, Gareth; Tello-Ruiz, Marcela; Stein, Joshua; Wei, Sharon; Ware, Doreen; Bolser, Daniel M; Howe, Kevin L; Kulesha, Eugene; Lawson, Daniel; Maslen, Gareth; Staines, Daniel M

2016-01-04

Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species, complementing the resources for vertebrate genomics developed in the context of the Ensembl project (http://www.ensembl.org). Together, the two resources provide a consistent set of programmatic and interactive interfaces to a rich range of data including reference sequence, gene models, transcriptional data, genetic variation and comparative analysis. This paper provides an update to the previous publications about the resource, with a focus on recent developments. These include the development of new analyses and views to represent polyploid genomes (of which bread wheat is the primary exemplar); and the continued up-scaling of the resource, which now includes over 23 000 bacterial genomes, 400 fungal genomes and 100 protist genomes, in addition to 55 genomes from invertebrate metazoa and 39 genomes from plants. This dramatic increase in the number of included genomes is one part of a broader effort to automate the integration of archival data (genome sequence, but also associated RNA sequence data and variant calls) within the context of reference genomes and make it available through the Ensembl user interfaces. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Inference of sigma factor controlled networks by using numerical modeling applied to microarray time series data of the germinating prokaryote.

Science.gov (United States)

Strakova, Eva; Zikova, Alice; Vohradsky, Jiri

2014-01-01

A computational model of gene expression was applied to a novel test set of microarray time series measurements to reveal regulatory interactions between transcriptional regulators represented by 45 sigma factors and the genes expressed during germination of a prokaryote Streptomyces coelicolor. Using microarrays, the first 5.5 h of the process was recorded in 13 time points, which provided a database of gene expression time series on genome-wide scale. The computational modeling of the kinetic relations between the sigma factors, individual genes and genes clustered according to the similarity of their expression kinetics identified kinetically plausible sigma factor-controlled networks. Using genome sequence annotations, functional groups of genes that were predominantly controlled by specific sigma factors were identified. Using external binding data complementing the modeling approach, specific genes involved in the control of the studied process were identified and their function suggested.

Analysis of Aspergillus nidulans metabolism at the genome-scale

DEFF Research Database (Denmark)

David, Helga; Ozcelik, İlknur Ş; Hofmann, Gerald

2008-01-01

of relevant secondary metabolites, was reconstructed based on detailed metabolic reconstructions available for A. niger and Saccharomyces cerevisiae, and information on the genetics, biochemistry and physiology of A. nidulans. Thereby, it was possible to identify metabolic functions without a gene associated...... a function. Results: In this work, we have manually assigned functions to 472 orphan genes in the metabolism of A. nidulans, by using a pathway-driven approach and by employing comparative genomics tools based on sequence similarity. The central metabolism of A. nidulans, as well as biosynthetic pathways......, in an objective and systematic manner. The functional assignments served as a basis to develop a mathematical model, linking 666 genes (both previously and newly annotated) to metabolic roles. The model was used to simulate metabolic behavior and additionally to integrate, analyze and interpret large-scale gene...

High-resolution Statistics of Solar Wind Turbulence at Kinetic Scales Using the Magnetospheric Multiscale Mission

Energy Technology Data Exchange (ETDEWEB)

Chasapis, Alexandros; Matthaeus, W. H.; Parashar, T. N.; Maruca, B. A. [University of Delaware, Newark, DE (United States); Fuselier, S. A.; Burch, J. L. [Southwest Research Institute, San Antonio, TX (United States); Phan, T. D. [Space Sciences Laboratory, University of California, Berkeley, CA (United States); Moore, T. E.; Pollock, C. J.; Gershman, D. J. [NASA Goddard Space Flight Center, Greenbelt, MD (United States); Torbert, R. B. [University of New Hampshire, Durham, NH (United States); Russell, C. T.; Strangeway, R. J., E-mail: chasapis@udel.edu [University of California, Los Angeles, CA (United States)

2017-07-20

Using data from the Magnetospheric Multiscale (MMS) and Cluster missions obtained in the solar wind, we examine second-order and fourth-order structure functions at varying spatial lags normalized to ion inertial scales. The analysis includes direct two-spacecraft results and single-spacecraft results employing the familiar Taylor frozen-in flow approximation. Several familiar statistical results, including the spectral distribution of energy, and the sale-dependent kurtosis, are extended down to unprecedented spatial scales of ∼6 km, approaching electron scales. The Taylor approximation is also confirmed at those small scales, although small deviations are present in the kinetic range. The kurtosis is seen to attain very high values at sub-proton scales, supporting the previously reported suggestion that monofractal behavior may be due to high-frequency plasma waves at kinetic scales.

Ozonation kinetics of winery wastewater in a pilot-scale bubble column reactor.

Science.gov (United States)

Lucas, Marco S; Peres, José A; Lan, Bing Yan; Li Puma, Gianluca

2009-04-01

The degradation of organic substances present in winery wastewater was studied in a pilot-scale, bubble column ozonation reactor. A steady reduction of chemical oxygen demand (COD) was observed under the action of ozone at the natural pH of the wastewater (pH 4). At alkaline and neutral pH the degradation rate was accelerated by the formation of radical species from the decomposition of ozone. Furthermore, the reaction of hydrogen peroxide (formed from natural organic matter in the wastewater) and ozone enhances the oxidation capacity of the ozonation process. The monitoring of pH, redox potential (ORP), UV absorbance (254 nm), polyphenol content and ozone consumption was correlated with the oxidation of the organic species in the water. The ozonation of winery wastewater in the bubble column was analysed in terms of a mole balance coupled with ozonation kinetics modeled by the two-film theory of mass transfer and chemical reaction. It was determined that the ozonation reaction can develop both in and across different kinetic regimes: fast, moderate and slow, depending on the experimental conditions. The dynamic change of the rate coefficient estimated by the model was correlated with changes in the water composition and oxidant species.

Performance of neutron kinetics models for ADS transient analyses

International Nuclear Information System (INIS)

Rineiski, A.; Maschek, W.; Rimpault, G.

2002-01-01

Within the framework of the SIMMER code development, neutron kinetics models for simulating transients and hypothetical accidents in advanced reactor systems, in particular in Accelerator Driven Systems (ADSs), have been developed at FZK/IKET in cooperation with CE Cadarache. SIMMER is a fluid-dynamics/thermal-hydraulics code, coupled with a structure model and a space-, time- and energy-dependent neutronics module for analyzing transients and accidents. The advanced kinetics models have also been implemented into KIN3D, a module of the VARIANT/TGV code (stand-alone neutron kinetics) for broadening application and for testing and benchmarking. In the paper, a short review of the SIMMER and KIN3D neutron kinetics models is given. Some typical transients related to ADS perturbations are analyzed. The general models of SIMMER and KIN3D are compared with more simple techniques developed in the context of this work to get a better understanding of the specifics of transients in subcritical systems and to estimate the performance of different kinetics options. These comparisons may also help in elaborating new kinetics models and extending existing computation tools for ADS transient analyses. The traditional point-kinetics model may give rather inaccurate transient reaction rate distributions in an ADS even if the material configuration does not change significantly. This inaccuracy is not related to the problem of choosing a 'right' weighting function: the point-kinetics model with any weighting function cannot take into account pronounced flux shape variations related to possible significant changes in the criticality level or to fast beam trips. To improve the accuracy of the point-kinetics option for slow transients, we have introduced a correction factor technique. The related analyses give a better understanding of 'long-timescale' kinetics phenomena in the subcritical domain and help to evaluate the performance of the quasi-static scheme in a particular case. One

A numerical scheme for a kinetic model for mixtures in the diffusive limit using the moment method

OpenAIRE

Bondesan , Andrea; Boudin , Laurent; Grec , Bérénice

2018-01-01

In this article, we consider a multi-species kinetic model which leads to the Maxwell-Stefan equations under a standard diffusive scaling (small Knudsen and Mach numbers). We propose a suitable numerical scheme which approximates both the solution of the kinetic model in rarefied regime and the one in the diffusion limit. We prove some a priori estimates (mass conservation and nonnegativity) and well-posedness of the discrete problem. We also present numerical examples where we observe the as...

MODELLING OF KINETICS OF FLUORINE ADSORPTION ONTO MODIFIED DIATOMITE

Directory of Open Access Journals (Sweden)

VEACESLAV ZELENTSOV

2017-03-01

Full Text Available The paper presents kinetics modelling of adsorption of fluorine onto modified diatomite, its fundamental characteristics and mathematical derivations. Three models of defluoridation kinetics were used to fit the experimental results on adsorption fluorine onto diatomite: the pseudo-first order model Lagergren, the pseudo-second order model G. McKay and H.S. Ho and intraparticle diffusion model of W.J. Weber and J.C. Morris. Kinetics studies revealed that the adsorption of fluorine followed second-order rate model, complimented by intraparticle diffusion kinetics. The adsorption mechanism of fluorine involved three stages – external surface adsorption, intraparticle diffusion and the stage of equilibrium.

A physiologically based kinetic model for bacterial sulfide oxidation.

Science.gov (United States)

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.

Kinetic models for irreversible processes on a lattice

Energy Technology Data Exchange (ETDEWEB)

Wolf, N.O.

1979-04-01

The development and application of kinetic lattice models are considered. For the most part, the discussions are restricted to lattices in one-dimension. In Chapter 1, a brief overview of kinetic lattice model formalisms and an extensive literature survey are presented. A review of the kinetic models for non-cooperative lattice events is presented in Chapter 2. The development of cooperative lattice models and solution of the resulting kinetic equations for an infinite and a semi-infinite lattice are thoroughly discussed in Chapters 3 and 4. The cooperative models are then applied to the problem of theoretically dtermining the sticking coefficient for molecular chemisorption in Chapter 5. In Chapter 6, other possible applications of these models and several model generalizations are considered. Finally, in Chapter 7, an experimental study directed toward elucidating the mechanistic factors influencing the chemisorption of methane on single crystal tungsten is reported. In this it differs from the rest of the thesis which deals with the statistical distributions resulting from a given mechanism.

Kinetic models for irreversible processes on a lattice

International Nuclear Information System (INIS)

Wolf, N.O.

1979-04-01

The development and application of kinetic lattice models are considered. For the most part, the discussions are restricted to lattices in one-dimension. In Chapter 1, a brief overview of kinetic lattice model formalisms and an extensive literature survey are presented. A review of the kinetic models for non-cooperative lattice events is presented in Chapter 2. The development of cooperative lattice models and solution of the resulting kinetic equations for an infinite and a semi-infinite lattice are thoroughly discussed in Chapters 3 and 4. The cooperative models are then applied to the problem of theoretically dtermining the sticking coefficient for molecular chemisorption in Chapter 5. In Chapter 6, other possible applications of these models and several model generalizations are considered. Finally, in Chapter 7, an experimental study directed toward elucidating the mechanistic factors influencing the chemisorption of methane on single crystal tungsten is reported. In this it differs from the rest of the thesis which deals with the statistical distributions resulting from a given mechanism

Kinetic modeling in pre-clinical positron emission tomography

Energy Technology Data Exchange (ETDEWEB)

Kuntner, Claudia [AIT Austrian Institute of Technology GmbH, Seibersdorf (Austria). Biomedical Systems, Health and Environment Dept.

2014-07-01

Pre-clinical positron emission tomography (PET) has evolved in the last few years from pure visualization of radiotracer uptake and distribution towards quantification of the physiological parameters. For reliable and reproducible quantification the kinetic modeling methods used to obtain relevant parameters of radiotracer tissue interaction are important. Here we present different kinetic modeling techniques with a focus on compartmental models including plasma input models and reference tissue input models. The experimental challenges of deriving the plasma input function in rodents and the effect of anesthesia are discussed. Finally, in vivo application of kinetic modeling in various areas of pre-clinical research is presented and compared to human data.

Modeling the degradation kinetics of ascorbic acid.

Science.gov (United States)

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.

Macro-scale turbulence modelling for flows in porous media

International Nuclear Information System (INIS)

Pinson, F.

2006-03-01

- This work deals with the macroscopic modeling of turbulence in porous media. It concerns heat exchangers, nuclear reactors as well as urban flows, etc. The objective of this study is to describe in an homogenized way, by the mean of a spatial average operator, turbulent flows in a solid matrix. In addition to this first operator, the use of a statistical average operator permits to handle the pseudo-aleatory character of turbulence. The successive application of both operators allows us to derive the balance equations of the kind of flows under study. Two major issues are then highlighted, the modeling of dispersion induced by the solid matrix and the turbulence modeling at a macroscopic scale (Reynolds tensor and turbulent dispersion). To this aim, we lean on the local modeling of turbulence and more precisely on the k - ε RANS models. The methodology of dispersion study, derived thanks to the volume averaging theory, is extended to turbulent flows. Its application includes the simulation, at a microscopic scale, of turbulent flows within a representative elementary volume of the porous media. Applied to channel flows, this analysis shows that even within the turbulent regime, dispersion remains one of the dominating phenomena within the macro-scale modeling framework. A two-scale analysis of the flow allows us to understand the dominating role of the drag force in the kinetic energy transfers between scales. Transfers between the mean part and the turbulent part of the flow are formally derived. This description significantly improves our understanding of the issue of macroscopic modeling of turbulence and leads us to define the sub-filter production and the wake dissipation. A f - f - w >f model is derived. It is based on three balance equations for the turbulent kinetic energy, the viscous dissipation and the wake dissipation. Furthermore, a dynamical predictor for the friction coefficient is proposed. This model is then successfully applied to the study of

Two-scale large deviations for chemical reaction kinetics through second quantization path integral

International Nuclear Information System (INIS)

Li, Tiejun; Lin, Feng

2016-01-01

Motivated by the study of rare events for a typical genetic switching model in systems biology, in this paper we aim to establish the general two-scale large deviations for chemical reaction systems. We build a formal approach to explicitly obtain the large deviation rate functionals for the considered two-scale processes based upon the second quantization path integral technique. We get three important types of large deviation results when the underlying two timescales are in three different regimes. This is realized by singular perturbation analysis to the rate functionals obtained by the path integral. We find that the three regimes possess the same deterministic mean-field limit but completely different chemical Langevin approximations. The obtained results are natural extensions of the classical large volume limit for chemical reactions. We also discuss its implication on the single-molecule Michaelis–Menten kinetics. Our framework and results can be applied to understand general multi-scale systems including diffusion processes. (paper)

Bridging scales through multiscale modeling: A case study on Protein Kinase A

Directory of Open Access Journals (Sweden)

Sophia P Hirakis

2015-09-01

Full Text Available The goal of multiscale modeling in biology is to use structurally based physico-chemical models to integrate across temporal and spatial scales of biology and thereby improve mechanistic understanding of, for example, how a single mutation can alter organism-scale phenotypes. This approach may also inform therapeutic strategies or identify candidate drug targets that might otherwise have been overlooked. However, in many cases, it remains unclear how best to synthesize information obtained from various scales and analysis approaches, such as atomistic molecular models, Markov state models (MSM, subcellular network models, and whole cell models. In this paper, we use protein kinase A (PKA activation as a case study to explore how computational methods that model different physical scales can complement each other and integrate into an improved multiscale representation of the biological mechanisms. Using measured crystal structures, we show how molecular dynamics (MD simulations coupled with atomic-scale MSMs can provide conformations for Brownian dynamics (BD simulations to feed transitional states and kinetic parameters into protein-scale MSMs. We discuss how milestoning can give reaction probabilities and forward-rate constants of cAMP association events by seamlessly integrating MD and BD simulation scales. These rate constants coupled with MSMs provide a robust representation of the free energy landscape, enabling access to kinetic and thermodynamic parameters unavailable from current experimental data. These approaches have helped to illuminate the cooperative nature of PKA activation in response to distinct cAMP binding events. Collectively, this approach exemplifies a general strategy for multiscale model development that is applicable to a wide range of biological problems.

Kinetic-Scale Magnetic Turbulence and Finite Larmor Radius Effects at Mercury

Science.gov (United States)

Uritsky, V. M.; Slavin, J. A.; Khazanov, G. V.; Donovan, E. F.; Boardsen, S. A.; Anderson, B. J.; Korth, H.

2011-01-01

We use a nonstationary generalization of the higher-order structure function technique to investigate statistical properties of the magnetic field fluctuations recorded by MESSENGER spacecraft during its first flyby (01/14/2008) through the near-Mercury space environment, with the emphasis on key boundary regions participating in the solar wind - magnetosphere interaction. Our analysis shows, for the first time, that kinetic-scale fluctuations play a significant role in the Mercury's magnetosphere up to the largest resolvable timescale (approx.20 s) imposed by the signal nonstationariry, suggesting that turbulence at this plane I is largely controlled by finite Larmor radius effects. In particular, we report the presence of a highly turbulent and extended foreshock system filled with packets of ULF oscillations, broad-band intermittent fluctuations in the magnetosheath, ion-kinetic turbulence in the central plasma sheet of Mercury's magnetotail, and kinetic-scale fluctuations in the inner current sheet encountered at the outbound (dawn-side) magnetopause. Overall, our measurements indicate that the Hermean magnetosphere, as well as the surrounding region, are strongly affected by non-MHD effects introduced by finite sizes of cyclotron orbits of the constituting ion species. Physical mechanisms of these effects and their potentially critical impact on the structure and dynamics of Mercury's magnetic field remain to be understood.

Reactor kinetics revisited: a coefficient based model (CBM)

International Nuclear Information System (INIS)

Ratemi, W.M.

2011-01-01

In this paper, a nuclear reactor kinetics model based on Guelph expansion coefficients calculation ( Coefficients Based Model, CBM), for n groups of delayed neutrons is developed. The accompanying characteristic equation is a polynomial form of the Inhour equation with the same coefficients of the CBM- kinetics model. Those coefficients depend on Universal abc- values which are dependent on the type of the fuel fueling a nuclear reactor. Furthermore, such coefficients are linearly dependent on the inserted reactivity. In this paper, the Universal abc- values have been presented symbolically, for the first time, as well as with their numerical values for U-235 fueled reactors for one, two, three, and six groups of delayed neutrons. Simulation studies for constant and variable reactivity insertions are made for the CBM kinetics model, and a comparison of results, with numerical solutions of classical kinetics models for one, two, three, and six groups of delayed neutrons are presented. The results show good agreements, especially for single step insertion of reactivity, with the advantage of the CBM- solution of not encountering the stiffness problem accompanying the numerical solutions of the classical kinetics model. (author)

Product sampling during transient continuous countercurrent hydrolysis of canola oil and development of a kinetic model

KAUST Repository

Wang, Weicheng

2013-11-01

A chemical kinetic model has been developed for the transient stage of the continuous countercurrent hydrolysis of triglycerides to free fatty acids and glycerol. Departure functions and group contribution methods were applied to determine the equilibrium constants of the four reversible reactions in the kinetic model. Continuous countercurrent hydrolysis of canola oil in subcritical water was conducted experimentally in a lab-scale reactor over a range of temperatures and the concentrations of all neutral components were quantified. Several of the rate constants in the model were obtained by modeling this experimental data, with the remaining determined from calculated equilibrium constants. Some reactions not included in the present, or previous, hydrolysis modeling efforts were identified from glycerolysis kinetic studies and may explain the slight discrepancy between model and experiment. The rate constants determined in this paper indicate that diglycerides in the feedstock accelerate the transition from "emulsive hydrolysis" to "rapid hydrolysis". © 2013 Elsevier Ltd.

Multi-Scale Modelling of the Gamma Radiolysis of Nitrate Solutions

OpenAIRE

Horne, Gregory; Donoclift, Thomas; Sims, Howard E.; M. Orr, Robin; Pimblott, Simon

2016-01-01

A multi-scale modelling approach has been developed for the extended timescale long-term radiolysis of aqueous systems. The approach uses a combination of stochastic track structure and track chemistry as well as deterministic homogeneous chemistry techniques and involves four key stages; radiation track structure simulation, the subsequent physicochemical processes, nonhomogeneous diffusion-reaction kinetic evolution, and homogeneous bulk chemistry modelling. The first three components model...

Decoding Synteny Blocks and Large-Scale Duplications in Mammalian and Plant Genomes

Science.gov (United States)

Peng, Qian; Alekseyev, Max A.; Tesler, Glenn; Pevzner, Pavel A.

The existing synteny block reconstruction algorithms use anchors (e.g., orthologous genes) shared over all genomes to construct the synteny blocks for multiple genomes. This approach, while efficient for a few genomes, cannot be scaled to address the need to construct synteny blocks in many mammalian genomes that are currently being sequenced. The problem is that the number of anchors shared among all genomes quickly decreases with the increase in the number of genomes. Another problem is that many genomes (plant genomes in particular) had extensive duplications, which makes decoding of genomic architecture and rearrangement analysis in plants difficult. The existing synteny block generation algorithms in plants do not address the issue of generating non-overlapping synteny blocks suitable for analyzing rearrangements and evolution history of duplications. We present a new algorithm based on the A-Bruijn graph framework that overcomes these difficulties and provides a unified approach to synteny block reconstruction for multiple genomes, and for genomes with large duplications.

Genomic divergences among cattle, dog and human estimated from large-scale alignments of genomic sequences

Directory of Open Access Journals (Sweden)

Shade Larry L

2006-06-01

Full Text Available Abstract Background Approximately 11 Mb of finished high quality genomic sequences were sampled from cattle, dog and human to estimate genomic divergences and their regional variation among these lineages. Results Optimal three-way multi-species global sequence alignments for 84 cattle clones or loci (each >50 kb of genomic sequence were constructed using the human and dog genome assemblies as references. Genomic divergences and substitution rates were examined for each clone and for various sequence classes under different functional constraints. Analysis of these alignments revealed that the overall genomic divergences are relatively constant (0.32–0.37 change/site for pairwise comparisons among cattle, dog and human; however substitution rates vary across genomic regions and among different sequence classes. A neutral mutation rate (2.0–2.2 × 10(-9 change/site/year was derived from ancestral repetitive sequences, whereas the substitution rate in coding sequences (1.1 × 10(-9 change/site/year was approximately half of the overall rate (1.9–2.0 × 10(-9 change/site/year. Relative rate tests also indicated that cattle have a significantly faster rate of substitution as compared to dog and that this difference is about 6%. Conclusion This analysis provides a large-scale and unbiased assessment of genomic divergences and regional variation of substitution rates among cattle, dog and human. It is expected that these data will serve as a baseline for future mammalian molecular evolution studies.

Thermal oxidative degradation kinetics of agricultural residues using distributed activation energy model and global kinetic model.

Science.gov (United States)

Ren, Xiu'e; Chen, Jianbiao; Li, Gang; Wang, Yanhong; Lang, Xuemei; Fan, Shuanshi

2018-08-01

The study concerned the thermal oxidative degradation kinetics of agricultural residues, peanut shell (PS) and sunflower shell (SS). The thermal behaviors were evaluated via thermogravimetric analysis and the kinetic parameters were determined by using distributed activation energy model (DAEM) and global kinetic model (GKM). Results showed that thermal oxidative decomposition of two samples processed in three zones; the ignition, burnout, and comprehensive combustibility between two agricultural residues were of great difference; and the combustion performance could be improved by boosting heating rate. The activation energy ranges calculated by the DAEM for the thermal oxidative degradation of PS and SS were 88.94-145.30 kJ mol -1 and 94.86-169.18 kJ mol -1 , respectively. The activation energy obtained by the GKM for the oxidative decomposition of hemicellulose and cellulose was obviously lower than that for the lignin oxidation at identical heating rate. To some degree, the determined kinetic parameters could acceptably simulate experimental data. Copyright © 2018 Elsevier Ltd. All rights reserved.

Experimental study and kinetic modeling of the hydro-fluorination of uranium dioxide

International Nuclear Information System (INIS)

Pages, Simon

2014-01-01

A kinetic study of hydro-fluorination of uranium dioxide was performed between 375 and 475 C under partial pressures of HF between 42 and 720 mbar. The reaction was followed by thermogravimetry in isothermal and isobaric conditions. The kinetic data obtained coupled with a characterization of the powder before, during and after reaction by SEM, EDS, BET and XRD showed that the powder grains of UO 2 are transformed according a model of instantaneous germination, anisotropic growth and internal development. The rate limiting step of the growth process is the diffusion of HF in the UF 4 layer. A mechanism of growth of the UF 4 layer has been proposed. In the temperature and pressure range studied, the reaction is of first order with respect to HF and follows an Arrhenius law. A rate equation was determined and used to perform kinetic simulations which have shown a very good correlation with experience. Coupling of this rate equation with heat and mass transport phenomena allowed to perform simulations at the scale of a powder's agglomerate. They have shown that some structures of agglomerates influence the rate of diffusion of the gases in the porous medium and thereby influence the reaction rate. Finally kinetic simulations on powder's beds and pellets were carried out and compared with experimental rates. The experimental and simulated kinetic curves have the same paces, but improvements in the simulations are needed to accurately predict rates: the coupling between the three scales (grain, agglomerate, oven) would be a good example. (author) [fr

Musa sebagai Model Genom

Directory of Open Access Journals (Sweden)

RITA MEGIA

2005-12-01

Full Text Available During the meeting in Arlington, USA in 2001, the scientists grouped in PROMUSA agreed with the launching of the Global Musa Genomics Consortium. The Consortium aims to apply genomics technologies to the improvement of this important crop. These genome projects put banana as the third model species after Arabidopsis and rice that will be analyzed and sequenced. Comparing to Arabidopsis and rice, banana genome provides a unique and powerful insight into structural and in functional genomics that could not be found in those two species. This paper discussed these subjects-including the importance of banana as the fourth main food in the world, the evolution and biodiversity of this genetic resource and its parasite.

Development of a novel once-through flow visualization technique for kinetic study of bulk and surface scaling

Science.gov (United States)

Sanni, O.; Bukuaghangin, O.; Huggan, M.; Kapur, N.; Charpentier, T.; Neville, A.

2017-10-01

There is a considerable interest to investigate surface crystallization in order to have a full mechanistic understanding of how layers of sparingly soluble salts (scale) build on component surfaces. Despite much recent attention, a suitable methodology to improve on the understanding of the precipitation/deposition systems to enable the construction of an accurate surface deposition kinetic model is still needed. In this work, an experimental flow rig and associated methodology to study mineral scale deposition is developed. The once-through flow rig allows us to follow mineral scale precipitation and surface deposition in situ and in real time. The rig enables us to assess the effects of various parameters such as brine chemistry and scaling indices, temperature, flow rates, and scale inhibitor concentrations on scaling kinetics. Calcium carbonate (CaCO3) scaling at different values of the saturation ratio (SR) is evaluated using image analysis procedures that enable the assessment of surface coverage, nucleation, and growth of the particles with time. The result for turbidity values measured in the flow cell is zero for all the SR considered. The residence time from the mixing point to the sample is shorter than the induction time for bulk precipitation; therefore, there are no crystals in the bulk solution as the flow passes through the sample. The study shows that surface scaling is not always a result of pre-precipitated crystals in the bulk solution. The technique enables both precipitation and surface deposition of scale to be decoupled and for the surface deposition process to be studied in real time and assessed under constant condition.

Genome-scale reconstruction and in silico analysis of the Ralstonia eutropha H16 for polyhydroxyalkanoate synthesis, lithoautotrophic growth, and 2-methyl citric acid production

Directory of Open Access Journals (Sweden)

Kim Tae

2011-06-01

Full Text Available Abstract Background Ralstonia eutropha H16, found in both soil and water, is a Gram-negative lithoautotrophic bacterium that can utillize CO2 and H2 as its sources of carbon and energy in the absence of organic substrates. R. eutropha H16 can reach high cell densities either under lithoautotrophic or heterotrophic conditions, which makes it suitable for a number of biotechnological applications. It is the best known and most promising producer of polyhydroxyalkanoates (PHAs from various carbon substrates and is an environmentally important bacterium that can degrade aromatic compounds. In order to make R. eutropha H16 a more efficient and robust biofactory, system-wide metabolic engineering to improve its metabolic performance is essential. Thus, it is necessary to analyze its metabolic characteristics systematically and optimize the entire metabolic network at systems level. Results We present the lithoautotrophic genome-scale metabolic model of R. eutropha H16 based on the annotated genome with biochemical and physiological information. The stoichiometic model, RehMBEL1391, is composed of 1391 reactions including 229 transport reactions and 1171 metabolites. Constraints-based flux analyses were performed to refine and validate the genome-scale metabolic model under environmental and genetic perturbations. First, the lithoautotrophic growth characteristics of R. eutropha H16 were investigated under varying feeding ratios of gas mixture. Second, the genome-scale metabolic model was used to design the strategies for the production of poly[R-(--3hydroxybutyrate] (PHB under different pH values and carbon/nitrogen source uptake ratios. It was also used to analyze the metabolic characteristics of R. eutropha when the phosphofructokinase gene was expressed. Finally, in silico gene knockout simulations were performed to identify targets for metabolic engineering essential for the production of 2-methylcitric acid in R. eutropha H16. Conclusion The

Genome-scale cold stress response regulatory networks in ten Arabidopsis thaliana ecotypes

DEFF Research Database (Denmark)

Barah, Pankaj; Jayavelu, Naresh Doni; Rasmussen, Simon

2013-01-01

available from Arabidopsis thaliana 1001 genome project, we further investigated sequence polymorphisms in the core cold stress regulon genes. Significant numbers of non-synonymous amino acid changes were observed in the coding region of the CBF regulon genes. Considering the limited knowledge about......BACKGROUND: Low temperature leads to major crop losses every year. Although several studies have been conducted focusing on diversity of cold tolerance level in multiple phenotypically divergent Arabidopsis thaliana (A. thaliana) ecotypes, genome-scale molecular understanding is still lacking....... RESULTS: In this study, we report genome-scale transcript response diversity of 10 A. thaliana ecotypes originating from different geographical locations to non-freezing cold stress (10°C). To analyze the transcriptional response diversity, we initially compared transcriptome changes in all 10 ecotypes...

Modeling the isochronal crystallization kinetics

International Nuclear Information System (INIS)

Sahay, S.S.; Krishnan, Karthik

2004-01-01

The classical Johnson-Mehl-Avrami-Kolmogorov (JMAK) model, originally formulated for the isothermal condition, is often used in conjunction with additivity principle for modeling the non-isothermal crystallization kinetics. This approach at times results in significant differences between the model prediction and experimental data. In this article, a modification to this approach has been imposed via an additional functional relationship between the activation energy and heating rate. The methodology has been validated with experimental isochronal crystallization kinetic data in Se 71 Te 20 Sb 9 glass and Ge 20 Te 80 systems. It has been shown that the functional relationship between heating rate and activation energy, ascribed to the reduction in apparent activation energy due to increasing non-isothermality, provides better phenomenological description and therefore improves the prediction capability of the JMAK model under isochronal condition

Chemical kinetic modeling of H{sub 2} applications

Energy Technology Data Exchange (ETDEWEB)

Marinov, N.M.; Westbrook, C.K.; Cloutman, L.D. [Lawrence Livermore National Lab., CA (United States)] [and others

1995-09-01

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 dynamic 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.

Kinetics of ethylcyclohexane pyrolysis and oxidation: An experimental and detailed kinetic modeling study

KAUST Repository

Wang, Zhandong

2015-07-01

Ethylcyclohexane (ECH) is a model compound for cycloalkanes with long alkyl side-chains. A preliminary investigation on ECH (Wang et al., Proc. Combust. Inst., 35, 2015, 367-375) revealed that an accurate ECH kinetic model with detailed fuel consumption mechanism and aromatic growth pathways, as well as additional ECH pyrolysis and oxidation data with detailed species concentration covering a wide pressure and temperature range are required to understand the ECH combustion kinetics. In this work, the flow reactor pyrolysis of ECH at various pressures (30, 150 and 760Torr) was studied using synchrotron vacuum ultraviolet (VUV) photoionization mass spectrometry (PIMS) and gas chromatography (GC). The mole fraction profiles of numerous major and minor species were evaluated, and good agreement was observed between the PIMS and GC data sets. Furthermore, a fuel-rich burner-stabilized laminar premixed ECH/O2/Ar flame at 30Torr was studied using synchrotron VUV PIMS. A detailed kinetic model for ECH high temperature pyrolysis and oxidation was developed and validated against the pyrolysis and flame data performed in this work. Further validation of the kinetic model is presented against literature data including species concentrations in jet-stirred reactor oxidation, ignition delay times in a shock tube, and laminar flame speeds at various pressures and equivalence ratios. The model well predicts the consumption of ECH, the growth of aromatics, and the global combustion properties. Reaction flux and sensitivity analysis were utilized to elucidate chemical kinetic features of ECH combustion under various reaction conditions. © 2015 The Combustion Institute.

In Situ Observation of Intermittent Dissipation at Kinetic Scales in the Earth's Magnetosheath

Science.gov (United States)

Chasapis, Alexandros; Matthaeus, W. H.; Parashar, T. N.; Wan, M.; Haggerty, C. C.; Pollock, C. J.; Giles, B. L.; Paterson, W. R.; Dorelli, J.; Gershman, D. J.; Torbert, R. B.; Russell, C. T.; Lindqvist, P.-A.; Khotyaintsev, Y.; Moore, T. E.; Ergun, R. E.; Burch, J. L.

2018-03-01

We present a study of signatures of energy dissipation at kinetic scales in plasma turbulence based on observations by the Magnetospheric Multiscale mission (MMS) in the Earth’s magnetosheath. Using several intervals, and taking advantage of the high-resolution instrumentation on board MMS, we compute and discuss several statistical measures of coherent structures and heating associated with electrons, at previously unattainable scales in space and time. We use the multi-spacecraft Partial Variance of Increments (PVI) technique to study the intermittent structure of the magnetic field. Furthermore, we examine a measure of dissipation and its behavior with respect to the PVI as well as the current density. Additionally, we analyze the evolution of the anisotropic electron temperature and non-Maxwellian features of the particle distribution function. From these diagnostics emerges strong statistical evidence that electrons are preferentially heated in subproton-scale regions of strong electric current density, and this heating is preferentially in the parallel direction relative to the local magnetic field. Accordingly, the conversion of magnetic energy into electron kinetic energy occurs more strongly in regions of stronger current density, a finding consistent with several kinetic plasma simulation studies and hinted at by prior studies using lower resolution Cluster observations.

Mixing Rules Formulation for a Kinetic Model of the Langmuir-Hinshelwood Semipredictive Type Applied to the Heterogeneous Photocatalytic Degradation of Multicomponent Mixtures

Directory of Open Access Journals (Sweden)

John Wilman Rodriguez-Acosta

2014-01-01

Full Text Available Mixing rules coupled to a semipredictive kinetic model of the Langmuir-Hinshelwood type were proposed to determine the behavior of the heterogeneous solar photodegradation with TiO2-P25 of multicomponent mixtures at pilot scale. The kinetic expressions were expressed in terms of the effective concentration of total organic carbon (xTOC. An expression was obtained in a generalized form which is a function of the mixing rules as a product of a global contribution of the reaction rate constant k′ and a mixing function fC. Kinetic parameters of the model were obtained using the Nelder and Mead (N-M algorithm. The kinetic model was validated with experimental data obtained from the degradation of binary mixtures of chlorinated compounds (DCA: dichloroacetic acid and 4-CP: 4-chlorophenol at different initial global concentration, using a CPC reactor at pilot scale. A simplex-lattice {2,3} design experiment was adopted to perform the runs.

One-dimensional reactor kinetics model for RETRAN

International Nuclear Information System (INIS)

Gose, G.C.; Peterson, C.E.; Ellis, N.L.; McClure, J.A.

1981-01-01

This paper describes a one-dimensional spatial neutron kinetics model that was developed for the RETRAN code. The RETRAN -01 code has a point kinetics model to describe the reactor core behavior during thermal-hydraulic transients. A one-dimensional neutronics model has been developed for RETRAN-02. The ability to account for flux shape changes will permit an improved representation of the thermal and hydraulic feedback effects for many operational transients. 19 refs

Modeling and Elucidation of the Kinetics of Multiple Consecutive Photoreactions AB4(4Φ) With Φ-order Kinetics. Application to the Photodegradation of Riboflavin.

Science.gov (United States)

Maafi, Mounir; Maafi, Wassila

2016-12-01

New semi-empirical rate-law system of equations is proposed for the first time for consecutive photoreactions that involve up to 4 photoreaction steps, AB 4 (4Φ). The equation system was developed, tested, and validated against synthetic kinetic traces generated by fifth-order Runge-Kutta calculations. The model accurately fitted the kinetic traces of Riboflavin photodegradation in ethanol which decomposes via the AB 2 (2Φ) mechanism involving 2 consecutive photoreaction steps. A kinetic elucidation methodology useful for consecutive photoreactions was also proposed to determine all the kinetic parameters and reaction attributes defining AB 2 (2Φ) reactions. The quantum yields of photodegradation, determined for wavelengths in the visible region 400-480 nm, ranged from 0.005 to 0.00756 and 0.0012 to 8 10 -5 for the first and second photoreaction steps, respectively. They were found to increase with wavelength in defined sigmoid functions. For this monochromatic irradiation range, riboflavin proved to be a useful actinometer. Finally, a photodegradation scale based on pseudo-rate-constant values was also proposed for drugs. This scale (including 4 groups) is thought to contribute to rationalizing photodegradation testing and might prove useful in categorizing drugs' photodegradation reactivity. Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Genome-scale reconstruction of the Streptococcus pyogenes M49 metabolic network reveals growth requirements and indicates potential drug targets.

Science.gov (United States)

Levering, Jennifer; Fiedler, Tomas; Sieg, Antje; van Grinsven, Koen W A; Hering, Silvio; Veith, Nadine; Olivier, Brett G; Klett, Lara; Hugenholtz, Jeroen; Teusink, Bas; Kreikemeyer, Bernd; Kummer, Ursula

2016-08-20

Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes M49. Initially, we based the reconstruction on genome annotations and already existing and curated metabolic networks of Bacillus subtilis, Escherichia coli, Lactobacillus plantarum and Lactococcus lactis. This initial draft was manually curated with the final reconstruction accounting for 480 genes associated with 576 reactions and 558 metabolites. In order to constrain the model further, we performed growth experiments of wild type and arcA deletion strains of S. pyogenes M49 in a chemically defined medium and calculated nutrient uptake and production fluxes. We additionally performed amino acid auxotrophy experiments to test the consistency of the model. The established genome-scale model can be used to understand the growth requirements of the human pathogen S. pyogenes and define optimal and suboptimal conditions, but also to describe differences and similarities between S. pyogenes and related lactic acid bacteria such as L. lactis in order to find strategies to reduce the growth of the pathogen and propose drug targets. Copyright © 2016 Elsevier B.V. All rights reserved.

RegPrecise 3.0--a resource for genome-scale exploration of transcriptional regulation in bacteria.

Science.gov (United States)

Novichkov, Pavel S; Kazakov, Alexey E; Ravcheev, Dmitry A; Leyn, Semen A; Kovaleva, Galina Y; Sutormin, Roman A; Kazanov, Marat D; Riehl, William; Arkin, Adam P; Dubchak, Inna; Rodionov, Dmitry A

2013-11-01

bacterial genomes. Analytical capabilities include exploration of: regulon content, structure and function; TF binding site motifs; conservation and variations in genome-wide regulatory networks across all taxonomic groups of Bacteria. RegPrecise 3.0 was selected as a core resource on transcriptional regulation of the Department of Energy Systems Biology Knowledgebase, an emerging software and data environment designed to enable researchers to collaboratively generate, test and share new hypotheses about gene and protein functions, perform large-scale analyses, and model interactions in microbes, plants, and their communities.

Kinetic and allometric models for dosimetry using radiopharmaceuticals labeled with lanthanides; Proposicao de modelos cineticos e alometricos para a dosimetria de radiofarmacos marcados com lantanideos

Energy Technology Data Exchange (ETDEWEB)

Lima, Marina Ferreira

2012-07-01

This work proposes two models based in compartmental analyses: Animal model and Human model, using images from gamma camera measurements to determinate the kinetic constants of the {sup 177}Lu-DOTATATE to three animal species (rat Wistar, Armenian hamster and Syrian hamster) and to the human in biodistribution studies split in two phases: Phase 1 governed by uptake from the blood and Phase 2 governed by the real excretion. The kinetic constants obtained from the animals' data ere used to build allometric scaling to predict radiopharmaceutical biodistribution in the human employing relations by mass, metabolism, by life span and by physiological parameters. These extrapolation results were compared with the PRRT (Peptide receptor radiotherapy) patients kinetic data calculated using the Human model. The kinetic constants obtained from humans were used in dose assessment to PRRT patients considering MIRD 26 organs and tissues. Dosimetry results were in agreement with available results from literature. For the Phase 1 allometric scaling from kinetic data from the blood to the organs straight responsible for the {sup 177}Lu-DOTATATE metabolism and excretion - liver, kidneys and urinary bladder -show good correlation in the scaling by mass, metabolism and physiological and parameters. For the Phase 2, only the kinetic data from blood to the liver and to the kidneys show good correlation. Based in the anaesthetics inhibitory action over the renal excretion, there is not empirical basis to allow measurement times over 40 minutes in in vivo studies with small animals. Consequently, the Phase 1 results seem enough to make allometric scaling to assessment dose in PRRT. (author)

Biodegradation of phenol with chromium(VI) reduction in an anaerobic fixed-biofilm process-Kinetic model and reactor performance

International Nuclear Information System (INIS)

Lin, Yen-Hui; Wu, Chih-Lung; Hsu, Chih-Hao; Li, Hsin-Lung

2009-01-01

A mathematical model system was derived to describe the simultaneous removal of phenol biodegradation with chromium(VI) reduction in an anaerobic fixed-biofilm reactor. The model system incorporates diffusive mass transport and double Monod kinetics. The model was solved using a combination of the orthogonal collocation method and Gear's method. A laboratory-scale column reactor was employed to validate the kinetic model system. Batch kinetic tests were conducted independently to evaluate the biokinetic parameters used in the model simulation. The removal efficiencies of phenol and chromium(VI) in an anaerobic fixed-biofilm process were approximately 980 mg/g and 910 mg/g, respectively, under a steady-state condition. In the steady state, model-predicted biofilm thickness reached up to 350 μm and suspended cells in the effluent were 85 mg cell/l. The experimental results agree closely with the results of the model simulations.

Kinetic model of water disinfection using peracetic acid including synergistic effects.

Science.gov (United States)

Flores, Marina J; Brandi, Rodolfo J; Cassano, Alberto E; Labas, Marisol D

2016-01-01

The disinfection efficiencies of a commercial mixture of peracetic acid against Escherichia coli were studied in laboratory scale experiments. The joint and separate action of two disinfectant agents, hydrogen peroxide and peracetic acid, were evaluated in order to observe synergistic effects. A kinetic model for each component of the mixture and for the commercial mixture was proposed. Through simple mathematical equations, the model describes different stages of attack by disinfectants during the inactivation process. Based on the experiments and the kinetic parameters obtained, it could be established that the efficiency of hydrogen peroxide was much lower than that of peracetic acid alone. However, the contribution of hydrogen peroxide was very important in the commercial mixture. It should be noted that this improvement occurred only after peracetic acid had initiated the attack on the cell. This synergistic effect was successfully explained by the proposed scheme and was verified by experimental results. Besides providing a clearer mechanistic understanding of water disinfection, such models may improve our ability to design reactors.

Solar Plasma Radio Emission in the Presence of Imbalanced Turbulence of Kinetic-Scale Alfvén Waves

Science.gov (United States)

Lyubchyk, O.; Kontar, E. P.; Voitenko, Y. M.; Bian, N. H.; Melrose, D. B.

2017-09-01

We study the influence of kinetic-scale Alfvénic turbulence on the generation of plasma radio emission in the solar coronal regions where the ratio β of plasma to magnetic pressure is lower than the electron-to-ion mass ratio me/mi. The present study is motivated by the phenomenon of solar type I radio storms that are associated with the strong magnetic field of active regions. The measured brightness temperature of the type I storms can be up to 10^{10} K for continuum emission, and can exceed 10^{11} K for type I bursts. At present, there is no generally accepted theory explaining such high brightness temperatures and some other properties of the type I storms. We propose a model with an imbalanced turbulence of kinetic-scale Alfvén waves that produce an asymmetric quasi-linear plateau on the upper half of the electron velocity distribution. The Landau damping of resonant Langmuir waves is suppressed and their amplitudes grow spontaneously above the thermal level. The estimated saturation level of Langmuir waves is high enough to generate observed type I radio emission at the fundamental plasma frequency. Harmonic emission does not appear in our model because the backward-propagating Langmuir waves undergo strong Landau damping. Our model predicts 100% polarization in the sense of the ordinary (o-) mode of type I emission.

Active mechanics in living oocytes reveal molecular-scale force kinetics

Science.gov (United States)

Ahmed, Wylie; Fodor, Etienne; Almonacid, Maria; Bussonnier, Matthias; Verlhac, Marie-Helene; Gov, Nir; Visco, Paolo; van Wijland, Frederic; Betz, Timo

Unlike traditional materials, living cells actively generate forces at the molecular scale that change their structure and mechanical properties. This nonequilibrium activity is essential for cellular function, and drives processes such as cell division. Single molecule studies have uncovered the detailed force kinetics of isolated motor proteins in-vitro, however their behavior in-vivo has been elusive due to the complex environment inside the cell. Here, we quantify active forces and intracellular mechanics in living oocytes using in-vivo optical trapping and laser interferometry of endogenous vesicles. We integrate an experimental and theoretical framework to connect mesoscopic measurements of nonequilibrium properties to the underlying molecular- scale force kinetics. Our results show that force generation by myosin-V drives the cytoplasmic-skeleton out-of-equilibrium (at frequencies below 300 Hz) and actively softens the environment. In vivo myosin-V activity generates a force of F ~ 0 . 4 pN, with a power-stroke of length Δx ~ 20 nm and duration τ ~ 300 μs, that drives vesicle motion at vv ~ 320 nm/s. This framework is widely applicable to characterize living cells and other soft active materials.

Genome-scale reconstruction of the Streptococcus pyogenes M49 metabolic network reveals growth requirements and indicates potential drug targets

NARCIS (Netherlands)

Levering, J.; Fiedler, T.; Sieg, A.; van Grinsven, K.W.A.; Hering, S.; Veith, N.; Olivier, B.G.; Klett, L.; Hugenholtz, J.; Teusink, B.; Kreikemeyer, B.; Kummer, U.

2016-01-01

Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes

Genome-scale reconstruction of the metabolic network in Yersinia pestis, strain 91001

Energy Technology Data Exchange (ETDEWEB)

Navid, A; Almaas, E

2009-01-13

The gram-negative bacterium Yersinia pestis, the aetiological agent of bubonic plague, is one the deadliest pathogens known to man. Despite its historical reputation, plague is a modern disease which annually afflicts thousands of people. Public safety considerations greatly limit clinical experimentation on this organism and thus development of theoretical tools to analyze the capabilities of this pathogen is of utmost importance. Here, we report the first genome-scale metabolic model of Yersinia pestis biovar Mediaevalis based both on its recently annotated genome, and physiological and biochemical data from literature. Our model demonstrates excellent agreement with Y. pestis known metabolic needs and capabilities. Since Y. pestis is a meiotrophic organism, we have developed CryptFind, a systematic approach to identify all candidate cryptic genes responsible for known and theoretical meiotrophic phenomena. In addition to uncovering every known cryptic gene for Y. pestis, our analysis of the rhamnose fermentation pathway suggests that betB is the responsible cryptic gene. Despite all of our medical advances, we still do not have a vaccine for bubonic plague. Recent discoveries of antibiotic resistant strains of Yersinia pestis coupled with the threat of plague being used as a bioterrorism weapon compel us to develop new tools for studying the physiology of this deadly pathogen. Using our theoretical model, we can study the cell's phenotypic behavior under different circumstances and identify metabolic weaknesses which may be harnessed for the development of therapeutics. Additionally, the automatic identification of cryptic genes expands the usage of genomic data for pharmaceutical purposes.

Modeling chemical kinetics graphically

NARCIS (Netherlands)

Heck, A.

2012-01-01

In literature on chemistry education it has often been suggested that students, at high school level and beyond, can benefit in their studies of chemical kinetics from computer supported activities. Use of system dynamics modeling software is one of the suggested quantitative approaches that could

Analysis of a kinetic multi-segment foot model part II: kinetics and clinical implications.

Science.gov (United States)

Bruening, Dustin A; Cooney, Kevin M; Buczek, Frank L

2012-04-01

Kinematic multi-segment foot models have seen increased use in clinical and research settings, but the addition of kinetics has been limited and hampered by measurement limitations and modeling assumptions. In this second of two companion papers, we complete the presentation and analysis of a three segment kinetic foot model by incorporating kinetic parameters and calculating joint moments and powers. The model was tested on 17 pediatric subjects (ages 7-18 years) during normal gait. Ground reaction forces were measured using two adjacent force platforms, requiring targeted walking and the creation of two sub-models to analyze ankle, midtarsal, and 1st metatarsophalangeal joints. Targeted walking resulted in only minimal kinematic and kinetic differences compared with walking at self selected speeds. Joint moments and powers were calculated and ensemble averages are presented as a normative database for comparison purposes. Ankle joint powers are shown to be overestimated when using a traditional single-segment foot model, as substantial angular velocities are attributed to the mid-tarsal joint. Power transfer is apparent between the 1st metatarsophalangeal and mid-tarsal joints in terminal stance/pre-swing. While the measurement approach presented here is limited to clinical populations with only minimal impairments, some elements of the model can also be incorporated into routine clinical gait analysis. Copyright © 2011 Elsevier B.V. All rights reserved.

A kinetic reaction model for biomass pyrolysis processes in Aspen Plus

International Nuclear Information System (INIS)

Peters, Jens F.; Banks, Scott W.; Bridgwater, Anthony V.; Dufour, Javier

2017-01-01

Highlights: • Predictive kinetic reaction model applicable to any lignocellulosic feedstock. • Calculates pyrolysis yields and product composition as function of reactor conditions. • Detailed modelling of product composition (33 model compounds for the bio-oil). • Good agreement with literature regarding yield curves and product composition. • Successful validation with pyrolysis experiments in bench scale fast pyrolysis rig. - Abstract: This paper presents a novel kinetic reaction model for biomass pyrolysis processes. The model is based on the three main building blocks of lignocellulosic biomass, cellulose, hemicellulose and lignin and can be readily implemented in Aspen Plus and easily adapted to other process simulation software packages. It uses a set of 149 individual reactions that represent the volatilization, decomposition and recomposition processes of biomass pyrolysis. A linear regression algorithm accounts for the secondary pyrolysis reactions, thus allowing the calculation of slow and intermediate pyrolysis reactions. The bio-oil is modelled with a high level of detail, using up to 33 model compounds, which allows for a comprehensive estimation of the properties of the bio-oil and the prediction of further upgrading reactions. After showing good agreement with existing literature data, our own pyrolysis experiments are reported for validating the reaction model. A beech wood feedstock is subjected to pyrolysis under well-defined conditions at different temperatures and the product yields and compositions are determined. Reproducing the experimental pyrolysis runs with the simulation model, a high coincidence is found for the obtained fraction yields (bio-oil, char and gas), for the water content and for the elemental composition of the pyrolysis products. The kinetic reaction model is found to be suited for predicting pyrolysis yields and product composition for any lignocellulosic biomass feedstock under typical pyrolysis conditions

A kinetics database and scripts for PHREEQC

Science.gov (United States)

Hu, B.; Zhang, Y.; Teng, Y.; Zhu, C.

2017-12-01

Kinetics of geochemical reactions has been increasingly used in numerical models to simulate coupled flow, mass transport, and chemical reactions. However, the kinetic data are scattered in the literature. To assemble a kinetic dataset for a modeling project is an intimidating task for most. In order to facilitate the application of kinetics in geochemical modeling, we assembled kinetics parameters into a database for the geochemical simulation program, PHREEQC (version 3.0). Kinetics data were collected from the literature. Our database includes kinetic data for over 70 minerals. The rate equations are also programmed into scripts with the Basic language. Using the new kinetic database, we simulated reaction path during the albite dissolution process using various rate equations in the literature. The simulation results with three different rate equations gave difference reaction paths at different time scale. Another application involves a coupled reactive transport model simulating the advancement of an acid plume in an acid mine drainage site associated with Bear Creek Uranium tailings pond. Geochemical reactions including calcite, gypsum, and illite were simulated with PHREEQC using the new kinetic database. The simulation results successfully demonstrated the utility of new kinetic database.

A kinetic model for the penicillin biosynthetic pathway in

DEFF Research Database (Denmark)

Nielsen, Jens; Jørgensen, Henrik

1996-01-01

A kinetic model for the first two steps in the penicillin biosynthetic pathway, i.e. the ACV synthetase (ACVS) and the isopenicillin N synthetase (IPNS) is proposed. The model is based on Michaelis-Menten type kinetics with non-competitive inhibition of the ACVS by ACV, and competitive inhibition...... of the IPNS by glutathione. The model predicted flux through the pathway corresponds well with the measured rate of penicillin biosynthesis. From the kinetic model the elasticity coefficients and the flux control coefficients are calculated throughout a fed-batch cultivation, and it is found...

Genome organization in the nucleus: From dynamic measurements to a functional model.

Science.gov (United States)

Vivante, Anat; Brozgol, Eugene; Bronshtein, Irena; Garini, Yuval

2017-07-01

A biological system is by definition a dynamic environment encompassing kinetic processes that occur at different length scales and time ranges. To explore this type of system, spatial information needs to be acquired at different time scales. This means overcoming significant hurdles, including the need for stable and precise labeling of the required probes and the use of state of the art optical methods. However, to interpret the acquired data, biophysical models that can account for these biological mechanisms need to be developed. The structure and function of a biological system are closely related to its dynamic properties, thus further emphasizing the importance of identifying the rules governing the dynamics that cannot be directly deduced from information on the structure itself. In eukaryotic cells, tens of thousands of genes are packed in the small volume of the nucleus. The genome itself is organized in chromosomes that occupy specific volumes referred to as chromosome territories. This organization is preserved throughout the cell cycle, even though there are no sub-compartments in the nucleus itself. This organization, which is still not fully understood, is crucial for a large number of cellular functions such as gene regulation, DNA breakage repair and error-free cell division. Various techniques are in use today, including imaging, live cell imaging and molecular methods such as chromosome conformation capture (3C) methods to better understand these mechanisms. Live cell imaging methods are becoming well established. These include methods such as Single Particle Tracking (SPT), Continuous Photobleaching (CP), Fluorescence Recovery After Photobleaching (FRAP) and Fluorescence Correlation Spectroscopy (FCS) that are currently used for studying proteins, RNA, DNA, gene loci and nuclear bodies. They provide crucial information on its mobility, reorganization, interactions and binding properties. Here we describe how these dynamic methods can be used to

A kinetic model for chemical neurotransmission

Science.gov (United States)

Ramirez-Santiago, Guillermo; Martinez-Valencia, Alejandro; Fernandez de Miguel, Francisco

Recent experimental observations in presynaptic terminals at the neuromuscular junction indicate that there are stereotyped patterns of cooperativeness in the fusion of adjacent vesicles. That is, a vesicle in hemifusion process appears on the side of a fused vesicle and which is followed by another vesicle in a priming state while the next one is in a docking state. In this talk we present a kinetic model for this morphological pattern in which each vesicle state previous to the exocytosis is represented by a kinetic state. This chain states kinetic model can be analyzed by means of a Master equation whose solution is simulated with the stochastic Gillespie algorithm. With this approach we have reproduced the responses to the basal release in the absence of stimulation evoked by the electrical activity and the phenomena of facilitation and depression of neuromuscular synapses. This model offers new perspectives to understand the underlying phenomena in chemical neurotransmission based on molecular interactions that result in the cooperativity between vesicles during neurotransmitter release. DGAPA Grants IN118410 and IN200914 and Conacyt Grant 130031.

Using relational databases for improved sequence similarity searching and large-scale genomic analyses.

Science.gov (United States)

Mackey, Aaron J; Pearson, William R

2004-10-01

Relational databases are designed to integrate diverse types of information and manage large sets of search results, greatly simplifying genome-scale analyses. Relational databases are essential for management and analysis of large-scale sequence analyses, and can also be used to improve the statistical significance of similarity searches by focusing on subsets of sequence libraries most likely to contain homologs. This unit describes using relational databases to improve the efficiency of sequence similarity searching and to demonstrate various large-scale genomic analyses of homology-related data. This unit describes the installation and use of a simple protein sequence database, seqdb_demo, which is used as a basis for the other protocols. These include basic use of the database to generate a novel sequence library subset, how to extend and use seqdb_demo for the storage of sequence similarity search results and making use of various kinds of stored search results to address aspects of comparative genomic analysis.

Revisiting the chlorophyll biosynthesis pathway using genome scale metabolic model of Oryza sativa japonica

Science.gov (United States)

Chatterjee, Ankita; Kundu, Sudip

2015-01-01

Chlorophyll is one of the most important pigments present in green plants and rice is one of the major food crops consumed worldwide. We curated the existing genome scale metabolic model (GSM) of rice leaf by incorporating new compartment, reactions and transporters. We used this modified GSM to elucidate how the chlorophyll is synthesized in a leaf through a series of bio-chemical reactions spanned over different organelles using inorganic macronutrients and light energy. We predicted the essential reactions and the associated genes of chlorophyll synthesis and validated against the existing experimental evidences. Further, ammonia is known to be the preferred source of nitrogen in rice paddy fields. The ammonia entering into the plant is assimilated in the root and leaf. The focus of the present work is centered on rice leaf metabolism. We studied the relative importance of ammonia transporters through the chloroplast and the cytosol and their interlink with other intracellular transporters. Ammonia assimilation in the leaves takes place by the enzyme glutamine synthetase (GS) which is present in the cytosol (GS1) and chloroplast (GS2). Our results provided possible explanation why GS2 mutants show normal growth under minimum photorespiration and appear chlorotic when exposed to air. PMID:26443104

Modeling inhomogeneous DNA replication kinetics.

Directory of Open Access Journals (Sweden)

Michel G Gauthier

Full Text Available In eukaryotic organisms, DNA replication is initiated at a series of chromosomal locations called origins, where replication forks are assembled proceeding bidirectionally to replicate the genome. The distribution and firing rate of these origins, in conjunction with the velocity at which forks progress, dictate the program of the replication process. Previous attempts at modeling DNA replication in eukaryotes have focused on cases where the firing rate and the velocity of replication forks are homogeneous, or uniform, across the genome. However, it is now known that there are large variations in origin activity along the genome and variations in fork velocities can also take place. Here, we generalize previous approaches to modeling replication, to allow for arbitrary spatial variation of initiation rates and fork velocities. We derive rate equations for left- and right-moving forks and for replication probability over time that can be solved numerically to obtain the mean-field replication program. This method accurately reproduces the results of DNA replication simulation. We also successfully adapted our approach to the inverse problem of fitting measurements of DNA replication performed on single DNA molecules. Since such measurements are performed on specified portion of the genome, the examined DNA molecules may be replicated by forks that originate either within the studied molecule or outside of it. This problem was solved by using an effective flux of incoming replication forks at the model boundaries to represent the origin activity outside the studied region. Using this approach, we show that reliable inferences can be made about the replication of specific portions of the genome even if the amount of data that can be obtained from single-molecule experiments is generally limited.

MODELING STYRENE HYDROGENATION KINETICS USING PALLADIUM CATALYSTS

Directory of Open Access Journals (Sweden)

G. T. Justino

Full Text Available Abstract The high octane number of pyrolysis gasoline (PYGAS explains its insertion in the gasoline pool. However, its use is troublesome due to the presence of gum-forming chemicals which, in turn, can be removed via hydrogenation. The use of Langmuir-Hinshelwood kinetic models was evaluated for hydrogenation of styrene, a typical gum monomer, using Pd/9%Nb2O5-Al2O3 as catalyst. Kinetic models accounting for hydrogen dissociative and non-dissociative adsorption were considered. The availability of one or two kinds of catalytic sites was analyzed. Experiments were carried out in a semi-batch reactor at constant temperature and pressure in the absence of transport limitations. The conditions used in each experiment varied between 16 - 56 bar and 60 - 100 ºC for pressure and temperature, respectively. The kinetic models were evaluated using MATLAB and EMSO software. Models using adsorption of hydrogen and organic molecules on the same type of site fitted the data best.

On the Flow Instabilities and Turbulent Kinetic Energy of Large-Scale Francis Hydroturbine Model at Low Flow Rate Conditions

Directory of Open Access Journals (Sweden)

Wen-Tao Su

2014-07-01

Full Text Available This paper is to make a better understanding of the flow instabilities and turbulent kinetic energy (TKE features in a large-scale Francis hydroturbine model. The flow instability with aspect of pressure oscillation and pressure-velocity correlation was investigated using large eddy simulation (LES method along with two-phase cavitation model. The numerical simulation procedures were validated by the existing experimental result, and further the TKE evolution was analyzed in a curvilinear coordinates. By monitoring the fluctuating pressure and velocities in the vanes’ wake region, the local pressure and velocity variations were proven to have a phase difference approaching π/2, with a reasonable cross-correlation coefficient. Also the simultaneous evolution of pressure fluctuations at the opposite locations possessed a clear phase difference of π, indicating the stresses variations on the runner induced by pressure oscillation were in an odd number of nodal diameter. Considering the TKE generation, the streamwise velocity component us′2 contributed the most to the TKE, and thus the normal stress production term and shear stress production term imparted more instability to the flow than other production terms.

A probabilistic model to predict clinical phenotypic traits from genome sequencing.

Science.gov (United States)

Chen, Yun-Ching; Douville, Christopher; Wang, Cheng; Niknafs, Noushin; Yeo, Grace; Beleva-Guthrie, Violeta; Carter, Hannah; Stenson, Peter D; Cooper, David N; Li, Biao; Mooney, Sean; Karchin, Rachel

2014-09-01

Genetic screening is becoming possible on an unprecedented scale. However, its utility remains controversial. Although most variant genotypes cannot be easily interpreted, many individuals nevertheless attempt to interpret their genetic information. Initiatives such as the Personal Genome Project (PGP) and Illumina's Understand Your Genome are sequencing thousands of adults, collecting phenotypic information and developing computational pipelines to identify the most important variant genotypes harbored by each individual. These pipelines consider database and allele frequency annotations and bioinformatics classifications. We propose that the next step will be to integrate these different sources of information to estimate the probability that a given individual has specific phenotypes of clinical interest. To this end, we have designed a Bayesian probabilistic model to predict the probability of dichotomous phenotypes. When applied to a cohort from PGP, predictions of Gilbert syndrome, Graves' disease, non-Hodgkin lymphoma, and various blood groups were accurate, as individuals manifesting the phenotype in question exhibited the highest, or among the highest, predicted probabilities. Thirty-eight PGP phenotypes (26%) were predicted with area-under-the-ROC curve (AUC)>0.7, and 23 (15.8%) of these were statistically significant, based on permutation tests. Moreover, in a Critical Assessment of Genome Interpretation (CAGI) blinded prediction experiment, the models were used to match 77 PGP genomes to phenotypic profiles, generating the most accurate prediction of 16 submissions, according to an independent assessor. Although the models are currently insufficiently accurate for diagnostic utility, we expect their performance to improve with growth of publicly available genomics data and model refinement by domain experts.

Study of subgrid-scale velocity models for reacting and nonreacting flows

Science.gov (United States)

Langella, I.; Doan, N. A. K.; Swaminathan, N.; Pope, S. B.

2018-05-01

A study is conducted to identify advantages and limitations of existing large-eddy simulation (LES) closures for the subgrid-scale (SGS) kinetic energy using a database of direct numerical simulations (DNS). The analysis is conducted for both reacting and nonreacting flows, different turbulence conditions, and various filter sizes. A model, based on dissipation and diffusion of momentum (LD-D model), is proposed in this paper based on the observed behavior of four existing models. Our model shows the best overall agreements with DNS statistics. Two main investigations are conducted for both reacting and nonreacting flows: (i) an investigation on the robustness of the model constants, showing that commonly used constants lead to a severe underestimation of the SGS kinetic energy and enlightening their dependence on Reynolds number and filter size; and (ii) an investigation on the statistical behavior of the SGS closures, which suggests that the dissipation of momentum is the key parameter to be considered in such closures and that dilatation effect is important and must be captured correctly in reacting flows. Additional properties of SGS kinetic energy modeling are identified and discussed.

KiMoSys: a web-based repository of experimental data for KInetic MOdels of biological SYStems.

Science.gov (United States)

Costa, Rafael S; Veríssimo, André; Vinga, Susana

2014-08-13

The kinetic modeling of biological systems is mainly composed of three steps that proceed iteratively: model building, simulation and analysis. In the first step, it is usually required to set initial metabolite concentrations, and to assign kinetic rate laws, along with estimating parameter values using kinetic data through optimization when these are not known. Although the rapid development of high-throughput methods has generated much omics data, experimentalists present only a summary of obtained results for publication, the experimental data files are not usually submitted to any public repository, or simply not available at all. In order to automatize as much as possible the steps of building kinetic models, there is a growing requirement in the systems biology community for easily exchanging data in combination with models, which represents the main motivation of KiMoSys development. KiMoSys is a user-friendly platform that includes a public data repository of published experimental data, containing concentration data of metabolites and enzymes and flux data. It was designed to ensure data management, storage and sharing for a wider systems biology community. This community repository offers a web-based interface and upload facility to turn available data into publicly accessible, centralized and structured-format data files. Moreover, it compiles and integrates available kinetic models associated with the data.KiMoSys also integrates some tools to facilitate the kinetic model construction process of large-scale metabolic networks, especially when the systems biologists perform computational research. KiMoSys is a web-based system that integrates a public data and associated model(s) repository with computational tools, providing the systems biology community with a novel application facilitating data storage and sharing, thus supporting construction of ODE-based kinetic models and collaborative research projects.The web application implemented using Ruby

Large-scale parallel genome assembler over cloud computing environment.

Science.gov (United States)

Das, Arghya Kusum; Koppa, Praveen Kumar; Goswami, Sayan; Platania, Richard; Park, Seung-Jong

2017-06-01

The size of high throughput DNA sequencing data has already reached the terabyte scale. To manage this huge volume of data, many downstream sequencing applications started using locality-based computing over different cloud infrastructures to take advantage of elastic (pay as you go) resources at a lower cost. However, the locality-based programming model (e.g. MapReduce) is relatively new. Consequently, developing scalable data-intensive bioinformatics applications using this model and understanding the hardware environment that these applications require for good performance, both require further research. In this paper, we present a de Bruijn graph oriented Parallel Giraph-based Genome Assembler (GiGA), as well as the hardware platform required for its optimal performance. GiGA uses the power of Hadoop (MapReduce) and Giraph (large-scale graph analysis) to achieve high scalability over hundreds of compute nodes by collocating the computation and data. GiGA achieves significantly higher scalability with competitive assembly quality compared to contemporary parallel assemblers (e.g. ABySS and Contrail) over traditional HPC cluster. Moreover, we show that the performance of GiGA is significantly improved by using an SSD-based private cloud infrastructure over traditional HPC cluster. We observe that the performance of GiGA on 256 cores of this SSD-based cloud infrastructure closely matches that of 512 cores of traditional HPC cluster.

Kinetics programs for simulation of tropospheric photochemistry on the global scale

International Nuclear Information System (INIS)

Elliott, S.; Kao, C.Y.J.; Turco, R.P.; Zhao, X.P.

1993-08-01

The study of tropospheric kinetics underlies global change because key greenhouse gases are photochemically active. Modeling of tropospheric chemistry on a global scale is essential because some indirect greenhouse gases are short-lived and interact in a non-linear fashion. It is also extremely challenging, however; the global change grid is extensive in both the physical and temporal domains, and critical lower atmospheric species include the organics and their oxidized derivatives, which are numerous. Several types of optimization may be incorporated into kinetics modules to enhance their ability to simulate the complete lower atmospheric gas phase chemical system. (1) The photochemical integrator can be accelerated by avoiding matrix and iterative solutions and by establishing families. Accuracy and mass conservation are sacrificed in the absence of iteration, but atom balancing is restorable post hoc. (2) Chemistry can be arranged upon the massive grid to exploit parallel processing, and solutions to its continuity equations can be automated to permit experimentation with species and reaction lists or family definitions. Costs in programming effort will be incurred in these cases. (3) Complex hydrocarbon decay sequences can be streamlined either through structural lumping methods descended from smog investigations, which require considerable calibration, or by defining surrogates for classes of compounds, with a loss in constituent detail. From among the available options, the most advantageous permutations will vary with the specific nature of any eventual global scale study, and there is likely to be demand for many approaches. Tracer transport codes serve as a foundation upon which tropospheric chemistry packages will be tested. Encroachment of the NO x sphere of influence upon tropical rain forests and the upper free troposphere are two examples of specific problems to which full three-dimensional chemical simulations might be applied

Kinetic models for supercritical CO2 extraction of oilseeds - a review

Directory of Open Access Journals (Sweden)

B. Nagy

2011-01-01

Full Text Available The supercritical fluid extraction of oilseeds is gaining increasing interest in commercial application for the last few decades, most particularly thanks to technical and environmental advantages of supercritical fluid extraction technology compared to current extraction methods with organic solvents. Furthermore, CO2 as a solvent is generally recognized as safe (GRAS. At present moment, supercritical fluid extractions on a commercial scale are limited to decaffeination, production of soluble hops extracts, sesame seed oil production and extraction of certain petroleum products. When considering industrial application, it is essential to test the applicability of the appropriate model for supercritical fluid extraction of oilseeds used for scale up of laboratory data to industrial design purposes. The aim of this paper is to review the most significant kinetic models reported in the literature for supercritical fluid extraction.

A mathematical model for iodine kinetics

International Nuclear Information System (INIS)

Silva, E.A.T. da.

1976-01-01

A mathematical model for the iodine kinetics in thyroid is presented followed by its analytical solution. An eletroanalogical model is also developed for a simplified stage and another is proposed for the main case [pt

A kinetic model for hydrodesulfurisation

Energy Technology Data Exchange (ETDEWEB)

Sau, M.; Narasimhan, C.S.L.; Verma, R.P. [Indian Oil Corporation Limited, Research and Development Centre, Faridabad (India)

1997-07-01

Due to stringent environmental considerations and related insistence on low sulfur fuels, hydrodesulfurisation has emerged as an important component of any refining scheme globally. The process is used ranging from Naphta/Kerosine hydrotreating to heavy oil hydrotreating. Processes such as Deep gas oil desulfurisation aiming at reduction of sulfur levels to less than 500 ppm have emerged as major players in the scenario. Hydrodesulfurisation (HDS) involves parallel desulfurisation of different organo-sulfur compounds present in the complex petroleum mixtures. In order to design, monitor, optimise and control the HDS reactor, it is necessary to have a detailed, yet simple model which follows the reaction chemistry accurately. In the present paper, a kinetic model is presented for HDS using continuum theory of lumping. The sulfur distribution in the reaction mixture is treated as continuum and parallel reaction networks are devised for kinetic modelling using continuum theory of lumping approach. The model based on the above approach follows the HDS chemistry reasonably well and hence the model parameters are almost feed invariant. Methods are also devised to incorporate heat and pressure effects into the model. The model has been validated based on commercial kero-HDS data. It is found that the model predictions agree with the experimental/commercial data. 17 refs.

Genomic prediction of complex human traits: relatedness, trait architecture and predictive meta-models

Science.gov (United States)

Spiliopoulou, Athina; Nagy, Reka; Bermingham, Mairead L.; Huffman, Jennifer E.; Hayward, Caroline; Vitart, Veronique; Rudan, Igor; Campbell, Harry; Wright, Alan F.; Wilson, James F.; Pong-Wong, Ricardo; Agakov, Felix; Navarro, Pau; Haley, Chris S.

2015-01-01

We explore the prediction of individuals' phenotypes for complex traits using genomic data. We compare several widely used prediction models, including Ridge Regression, LASSO and Elastic Nets estimated from cohort data, and polygenic risk scores constructed using published summary statistics from genome-wide association meta-analyses (GWAMA). We evaluate the interplay between relatedness, trait architecture and optimal marker density, by predicting height, body mass index (BMI) and high-density lipoprotein level (HDL) in two data cohorts, originating from Croatia and Scotland. We empirically demonstrate that dense models are better when all genetic effects are small (height and BMI) and target individuals are related to the training samples, while sparse models predict better in unrelated individuals and when some effects have moderate size (HDL). For HDL sparse models achieved good across-cohort prediction, performing similarly to the GWAMA risk score and to models trained within the same cohort, which indicates that, for predicting traits with moderately sized effects, large sample sizes and familial structure become less important, though still potentially useful. Finally, we propose a novel ensemble of whole-genome predictors with GWAMA risk scores and demonstrate that the resulting meta-model achieves higher prediction accuracy than either model on its own. We conclude that although current genomic predictors are not accurate enough for diagnostic purposes, performance can be improved without requiring access to large-scale individual-level data. Our methodologically simple meta-model is a means of performing predictive meta-analysis for optimizing genomic predictions and can be easily extended to incorporate multiple population-level summary statistics or other domain knowledge. PMID:25918167

Kinetic modeling studies of SOA formation from α-pinene ozonolysis

Science.gov (United States)

Gatzsche, Kathrin; Iinuma, Yoshiteru; Tilgner, Andreas; Mutzel, Anke; Berndt, Torsten; Wolke, Ralf

2017-11-01

implementations, allowing backward reactions in the particle phase and considering a composition-dependent particle-phase bulk diffusion coefficient, the potential overprediction of the SOA mass with the basic kinetic approach is reduced by about 40 %. HOMs are an important compound group in the early stage of SOA formation because they contribute up to 65 % of the total SOA mass at this stage. HOMs also induce further SOA formation by providing an absorptive medium for SVOCs (semi-volatile organic compounds). This process contributes about 27 % of the total organic mass. The model results are very similar to the LEAK chamber results. Overall, the sensitivity studies demonstrate that the particle reactivity and the particle-phase bulk diffusion require a better characterization in order to improve the current model implementations and to validate the assumptions made from the chamber simulations. The successful implementation and testing of the current kinetic gas-particle partitioning approach in a box model framework will allow further applications in a 3-D model for regional-scale process investigations.

In silico method for modelling metabolism and gene product expression at genome scale

Energy Technology Data Exchange (ETDEWEB)

Lerman, Joshua A.; Hyduke, Daniel R.; Latif, Haythem; Portnoy, Vasiliy A.; Lewis, Nathan E.; Orth, Jeffrey D.; Rutledge, Alexandra C.; Smith, Richard D.; Adkins, Joshua N.; Zengler, Karsten; Palsson, Bernard O.

2012-07-03

Transcription and translation use raw materials and energy generated metabolically to create the macromolecular machinery responsible for all cellular functions, including metabolism. A biochemically accurate model of molecular biology and metabolism will facilitate comprehensive and quantitative computations of an organism's molecular constitution as a function of genetic and environmental parameters. Here we formulate a model of metabolism and macromolecular expression. Prototyping it using the simple microorganism Thermotoga maritima, we show our model accurately simulates variations in cellular composition and gene expression. Moreover, through in silico comparative transcriptomics, the model allows the discovery of new regulons and improving the genome and transcription unit annotations. Our method presents a framework for investigating molecular biology and cellular physiology in silico and may allow quantitative interpretation of multi-omics data sets in the context of an integrated biochemical description of an organism.

Modeling of a Large-Scale High Temperature Regenerative Sulfur Removal Process

DEFF Research Database (Denmark)

Konttinen, Jukka T.; Johnsson, Jan Erik

1999-01-01

model that does not account for bed hydrodynamics. The pilot-scale test run results, obtained in the test runs of the sulfur removal process with real coal gasifier gas, have been used for parameter estimation. The validity of the reactor model for commercial-scale design applications is discussed.......Regenerable mixed metal oxide sorbents are prime candidates for the removal of hydrogen sulfide from hot gasifier gas in the simplified integrated gasification combined cycle (IGCC) process. As part of the regenerative sulfur removal process development, reactor models are needed for scale......-up. Steady-state kinetic reactor models are needed for reactor sizing, and dynamic models can be used for process control design and operator training. The regenerative sulfur removal process to be studied in this paper consists of two side-by-side fluidized bed reactors operating at temperatures of 400...

p-Nitrophenol degradation by electro-Fenton process: Pathway, kinetic model and optimization using central composite design.

Science.gov (United States)

Meijide, J; Rosales, E; Pazos, M; Sanromán, M A

2017-10-01

The chemical process scale-up, from lab studies to industrial production, is challenging and requires deep knowledge of the kinetic model and the reactions that take place in the system. This knowledge is also useful in order to be employed for the reactor design and the determination of the optimal operational conditions. In this study, a model substituted phenol such as p-nitrophenol was degraded by electro-Fenton process and the reaction products yielded along the treatment were recorded. The kinetic model was developed using Matlab software and was based on main reactions that occurred until total mineralization which allowed predicting the degradation pathway under this advanced oxidation process. The predicted concentration profiles of p-nitrophenol, their intermediates and by-products in electro-Fenton process were validated with experimental assays and the results were consistent. Finally, based on the developed kinetic model the degradation process was optimized using central composite design taking as key parameters the ferrous ion concentration and current density. Copyright © 2017 Elsevier Ltd. All rights reserved.

Kinetic and thermodynamic modelling of TBP synthesis processes

International Nuclear Information System (INIS)

Azzouz, A.; Attou, M.

1989-02-01

The present paper deals with kinetic and thermodynamic modellisation of tributylphosphate (TBP) synthesis processes. Its aim consists in a purely comparative study of two different synthesis ways i.e. direct and indirect estirification of butanol. The methodology involves two steps. The first step consists in approximating curves which describe the process evolution and their dependence on the main parameters. The results gave a kinetic model of the process rate yielding in TBP. Further, on the basis of thermodynamic data concerning the various involved compounds a theoretical model was achieved. The calculations were carried out in Basic language and an interpolation mathematical method was applied to approximate the kinetic curves. The thermodynamic calculations were achieved on the basis of GIBBS' free energy using a VAX type computer and a VT240 terminal. The calculations accuracy was reasonable and within the norms. For each process, the confrontation of both models leads to an appreciable accord. In the two processes, the thermodynamic models were similar although the kinetic equations present different reaction orders. Hence the reaction orders were determined by a mathematical method which conists in searching the minimal difference between an empiric relation and a kinetic model with fixed order. This corresponds in fact in testing the model proposed at various reaction order around the suspected value. The main idea which results from such a work is that this kind of processes is well fitting with the model without taking into account the side chain reactions. The process behaviour is like that of a single reaction having a quasi linear dependence of the rate yielding and the reaction time for both processes

Modeling bubble dynamics and radical kinetics in ultrasound induced microalgal cell disruption.

Science.gov (United States)

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.

Determining the control circuitry of redox metabolism at the genome-scale.

Directory of Open Access Journals (Sweden)

Stephen Federowicz

2014-04-01

Full Text Available Determining how facultative anaerobic organisms sense and direct cellular responses to electron acceptor availability has been a subject of intense study. However, even in the model organism Escherichia coli, established mechanisms only explain a small fraction of the hundreds of genes that are regulated during electron acceptor shifts. Here we propose a qualitative model that accounts for the full breadth of regulated genes by detailing how two global transcription factors (TFs, ArcA and Fnr of E. coli, sense key metabolic redox ratios and act on a genome-wide basis to regulate anabolic, catabolic, and energy generation pathways. We first fill gaps in our knowledge of this transcriptional regulatory network by carrying out ChIP-chip and gene expression experiments to identify 463 regulatory events. We then interfaced this reconstructed regulatory network with a highly curated genome-scale metabolic model to show that ArcA and Fnr regulate >80% of total metabolic flux and 96% of differential gene expression across fermentative and nitrate respiratory conditions. Based on the data, we propose a feedforward with feedback trim regulatory scheme, given the extensive repression of catabolic genes by ArcA and extensive activation of chemiosmotic genes by Fnr. We further corroborated this regulatory scheme by showing a 0.71 r(2 (p<1e-6 correlation between changes in metabolic flux and changes in regulatory activity across fermentative and nitrate respiratory conditions. Finally, we are able to relate the proposed model to a wealth of previously generated data by contextualizing the existing transcriptional regulatory network.

A scale-free structure prior for graphical models with applications in functional genomics.

Directory of Open Access Journals (Sweden)

Paul Sheridan

Full Text Available The problem of reconstructing large-scale, gene regulatory networks from gene expression data has garnered considerable attention in bioinformatics over the past decade with the graphical modeling paradigm having emerged as a popular framework for inference. Analysis in a full Bayesian setting is contingent upon the assignment of a so-called structure prior-a probability distribution on networks, encoding a priori biological knowledge either in the form of supplemental data or high-level topological features. A key topological consideration is that a wide range of cellular networks are approximately scale-free, meaning that the fraction, , of nodes in a network with degree is roughly described by a power-law with exponent between and . The standard practice, however, is to utilize a random structure prior, which favors networks with binomially distributed degree distributions. In this paper, we introduce a scale-free structure prior for graphical models based on the formula for the probability of a network under a simple scale-free network model. Unlike the random structure prior, its scale-free counterpart requires a node labeling as a parameter. In order to use this prior for large-scale network inference, we design a novel Metropolis-Hastings sampler for graphical models that includes a node labeling as a state space variable. In a simulation study, we demonstrate that the scale-free structure prior outperforms the random structure prior at recovering scale-free networks while at the same time retains the ability to recover random networks. We then estimate a gene association network from gene expression data taken from a breast cancer tumor study, showing that scale-free structure prior recovers hubs, including the previously unknown hub SLC39A6, which is a zinc transporter that has been implicated with the spread of breast cancer to the lymph nodes. Our analysis of the breast cancer expression data underscores the value of the scale

Local CFD kinetic model of cadmium vaporization during fluid bed incineration of municipal solid waste

Energy Technology Data Exchange (ETDEWEB)

Soria, J. [Instituto Multidisciplinario de Investigación y Desarrollo de la Patagonia Norte (IDEPA, CONICET-UNCo) y Facultad de Ingeniería, Universidad Nacional del Comahue, Buenos Aires 1400, 8300 Neuquén (Argentina); Laboratoire Procédés, Matériaux et Energie Solaire (CNRS-PROMES), 7 Rue du Four Solaire, Odeillo, 66120 Font-Romeu (France); Gauthier, D., E-mail: Daniel.Gauthier@promes.cnrs.fr [Laboratoire Procédés, Matériaux et Energie Solaire (CNRS-PROMES), 7 Rue du Four Solaire, Odeillo, 66120 Font-Romeu (France); Falcoz, Q.; Flamant, G. [Laboratoire Procédés, Matériaux et Energie Solaire (CNRS-PROMES), 7 Rue du Four Solaire, Odeillo, 66120 Font-Romeu (France); Mazza, G. [Instituto Multidisciplinario de Investigación y Desarrollo de la Patagonia Norte (IDEPA, CONICET-UNCo) y Facultad de Ingeniería, Universidad Nacional del Comahue, Buenos Aires 1400, 8300 Neuquén (Argentina)

2013-03-15

Highlights: ► A 2-D local CFD model for simulating the Cd vaporization process is presented. ► It includes a kinetic expression of Cd vaporization into the incineration process. ► Pyrolysis, volatiles’ combustion and residual carbon combustion are also taken into account. ► It fits very well the experimental results obtained on a lab-scale fluidized bed reported in literature. ► It also compares favorably with a model developed previously by the group. -- Abstract: The emissions of heavy metals during incineration of Municipal Solid Waste (MSW) are a major issue to health and the environment. It is then necessary to well quantify these emissions in order to accomplish an adequate control and prevent the heavy metals from leaving the stacks. In this study the kinetic behavior of Cadmium during Fluidized Bed Incineration (FBI) of artificial MSW pellets, for bed temperatures ranging from 923 to 1073 K, was modeled. FLUENT 12.1.4 was used as the modeling framework for the simulations and implemented together with a complete set of user-defined functions (UDFs). The CFD model combines the combustion of a single solid waste particle with heavy metal (HM) vaporization from the burning particle, and it takes also into account both pyrolysis and volatiles’ combustion. A kinetic rate law for the Cd release, derived from the CFD thermal analysis of the combusting particle, is proposed. The simulation results are compared with experimental data obtained in a lab-scale fluidized bed incinerator reported in literature, and with the predicted values from a particulate non-isothermal model, formerly developed by the authors. The comparison shows that the proposed CFD model represents very well the evolution of the HM release for the considered range of bed temperature.

Extracellular enzyme kinetics scale with resource availability

Science.gov (United States)

Sinsabaugh, Robert L.; Belnap, Jayne; Findlay, Stuart G.; Follstad Shah, Jennifer J.; Hill, Brian H.; Kuehn, Kevin A.; Kuske, Cheryl; Litvak, Marcy E.; Martinez, Noelle G.; Moorhead, Daryl L.; Warnock, Daniel D.

2014-01-01

Microbial community metabolism relies on external digestion, mediated by extracellular enzymes that break down complex organic matter into molecules small enough for cells to assimilate. We analyzed the kinetics of 40 extracellular enzymes that mediate the degradation and assimilation of carbon, nitrogen and phosphorus by diverse aquatic and terrestrial microbial communities (1160 cases). Regression analyses were conducted by habitat (aquatic and terrestrial), enzyme class (hydrolases and oxidoreductases) and assay methodology (low affinity and high affinity substrates) to relate potential reaction rates to substrate availability. Across enzyme classes and habitats, the scaling relationships between apparent Vmax and apparent Km followed similar power laws with exponents of 0.44 to 0.67. These exponents, called elasticities, were not statistically distinct from a central value of 0.50, which occurs when the Km of an enzyme equals substrate concentration, a condition optimal for maintenance of steady state. We also conducted an ecosystem scale analysis of ten extracellular hydrolase activities in relation to soil and sediment organic carbon (2,000–5,000 cases/enzyme) that yielded elasticities near 1.0 (0.9 ± 0.2, n = 36). At the metabolomic scale, the elasticity of extracellular enzymatic reactions is the proportionality constant that connects the C:N:P stoichiometries of organic matter and ecoenzymatic activities. At the ecosystem scale, the elasticity of extracellular enzymatic reactions shows that organic matter ultimately limits effective enzyme binding sites. Our findings suggest that one mechanism by which microbial communities maintain homeostasis is regulating extracellular enzyme expression to optimize the short-term responsiveness of substrate acquisition. The analyses also show that, like elemental stoichiometry, the fundamental attributes of enzymatic reactions can be extrapolated from biochemical to community and ecosystem scales.

Kinetics model of bainitic transformation with stress

Science.gov (United States)

Zhou, Mingxing; Xu, Guang; Hu, Haijiang; Yuan, Qing; Tian, Junyu

2018-01-01

Thermal simulations were conducted on a Gleeble 3800 simulator. The main purpose is to investigate the effects of stress on the kinetics of bainitic transformation in a Fe-C-Mn-Si advanced high strength bainitic steel. Previous studies on modeling the kinetics of stress affected bainitic transformation only considered the stress below the yield strength of prior austenite. In the present study, the stress above the yield strength of prior austenite is taken into account. A new kinetics model of bainitic transformation dependent on the stress (including the stresses below and above the yield strength of prior austenite) and the transformation temperature is proposed. The new model presents a good agreement with experimental results. In addition, it is found that the acceleration degree of stress on bainitic transformation increases with the stress whether its magnitude is below or above the yield strength of austenite, but the increasing rate gradually slows down when the stress is above the yield strength of austenite.

Integration of Genome Scale Metabolic Networks and Gene Regulation of Metabolic Enzymes With Physiologically Based Pharmacokinetics.

Science.gov (United States)

Maldonado, Elaina M; Leoncikas, Vytautas; Fisher, Ciarán P; Moore, J Bernadette; Plant, Nick J; Kierzek, Andrzej M

2017-11-01

The scope of physiologically based pharmacokinetic (PBPK) modeling can be expanded by assimilation of the mechanistic models of intracellular processes from systems biology field. The genome scale metabolic networks (GSMNs) represent a whole set of metabolic enzymes expressed in human tissues. Dynamic models of the gene regulation of key drug metabolism enzymes are available. Here, we introduce GSMNs and review ongoing work on integration of PBPK, GSMNs, and metabolic gene regulation. We demonstrate example models. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Zea mays iRS1563: A Comprehensive Genome-Scale Metabolic Reconstruction of Maize Metabolism

Science.gov (United States)

Saha, Rajib; Suthers, Patrick F.; Maranas, Costas D.

2011-01-01

The scope and breadth of genome-scale metabolic reconstructions have continued to expand over the last decade. Herein, we introduce a genome-scale model for a plant with direct applications to food and bioenergy production (i.e., maize). Maize annotation is still underway, which introduces significant challenges in the association of metabolic functions to genes. The developed model is designed to meet rigorous standards on gene-protein-reaction (GPR) associations, elementally and charged balanced reactions and a biomass reaction abstracting the relative contribution of all biomass constituents. The metabolic network contains 1,563 genes and 1,825 metabolites involved in 1,985 reactions from primary and secondary maize metabolism. For approximately 42% of the reactions direct literature evidence for the participation of the reaction in maize was found. As many as 445 reactions and 369 metabolites are unique to the maize model compared to the AraGEM model for A. thaliana. 674 metabolites and 893 reactions are present in Zea mays iRS1563 that are not accounted for in maize C4GEM. All reactions are elementally and charged balanced and localized into six different compartments (i.e., cytoplasm, mitochondrion, plastid, peroxisome, vacuole and extracellular). GPR associations are also established based on the functional annotation information and homology prediction accounting for monofunctional, multifunctional and multimeric proteins, isozymes and protein complexes. We describe results from performing flux balance analysis under different physiological conditions, (i.e., photosynthesis, photorespiration and respiration) of a C4 plant and also explore model predictions against experimental observations for two naturally occurring mutants (i.e., bm1 and bm3). The developed model corresponds to the largest and more complete to-date effort at cataloguing metabolism for a plant species. PMID:21755001

Kinetic computer modeling of microwave surface-wave plasma production

International Nuclear Information System (INIS)

Ganachev, Ivan P.

2004-01-01

Kinetic computer plasma modeling occupies an intermediate position between the time consuming rigorous particle dynamic simulation and the fast but rather rough cold- or warm-plasma fluid models. The present paper reviews the kinetic modeling of microwave surface-wave discharges with accent on recent kinetic self-consistent models, where the external input parameters are reduced to the necessary minimum (frequency and intensity of the applied microwave field and pressure and geometry of the discharge vessel). The presentation is limited to low pressures, so that Boltzmann equation is solved in non-local approximation and collisional electron heating is neglected. The numerical results reproduce correctly the bi-Maxwellian electron energy distribution functions observed experimentally. (author)

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

Energy Technology Data Exchange (ETDEWEB)

Tian, Lei [School of Environment and Energy, South China University of Technology, Guangzhou, Guangdong 510006, People’s Republic of China; The Key Lab of Pollution Control and Ecosystem Restoration in Industry; Shi, Zhenqing [School of Environment and Energy, South China University of Technology, Guangzhou, Guangdong 510006, People’s Republic of China; The Key Lab of Pollution Control and Ecosystem Restoration in Industry; Lu, Yang [School of Environment and Energy, South China University of Technology, Guangzhou, Guangdong 510006, People’s Republic of China; The Key Lab of Pollution Control and Ecosystem Restoration in Industry; Dohnalkova, Alice C. [Environmental; Lin, Zhang [School of Environment and Energy, South China University of Technology, Guangzhou, Guangdong 510006, People’s Republic of China; The Key Lab of Pollution Control and Ecosystem Restoration in Industry; Dang, Zhi [School of Environment and Energy, South China University of Technology, Guangzhou, Guangdong 510006, People’s Republic of China; The Key Lab of Pollution Control and Ecosystem Restoration in Industry

2017-08-29

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 four 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.

Formulation, construction and analysis of kinetic models of metabolism: A review of modelling frameworks

DEFF Research Database (Denmark)

Saa, Pedro A.; Nielsen, Lars K.

2017-01-01

Kinetic models are critical to predict the dynamic behaviour of metabolic networks. Mechanistic kinetic models for large networks remain uncommon due to the difficulty of fitting their parameters. Recent modelling frameworks promise new ways to overcome this obstacle while retaining predictive ca...

Using proteomic data to assess a genome-scale "in silico" model of metal reducing bacteria in the simulation of field-scale uranium bioremediation

Science.gov (United States)

Yabusaki, S.; Fang, Y.; Wilkins, M. J.; Long, P.; Rifle IFRC Science Team

2011-12-01

A series of field experiments in a shallow alluvial aquifer at a former uranium mill tailings site have demonstrated that indigenous bacteria can be stimulated with acetate to catalyze the conversion of hexavalent uranium in a groundwater plume to immobile solid-associated uranium in the +4 oxidation state. While this bioreduction of uranium has been shown to lower groundwater concentrations below actionable standards, a viable remediation methodology will need a mechanistic, predictive and quantitative understanding of the microbially-mediated reactions that catalyze the reduction of uranium in the context of site-specific processes, properties, and conditions. At the Rifle IFRC site, we are investigating the impacts on uranium behavior of pulsed acetate amendment, acetate-oxidizing iron and sulfate reducing bacteria, seasonal water table variation, spatially-variable physical (hydraulic conductivity, porosity) and geochemical (reactive surface area) material properties. The simulation of three-dimensional, variably saturated flow and biogeochemical reactive transport during a uranium bioremediation field experiment includes a genome-scale in silico model of Geobacter sp. to represent the Fe(III) terminal electron accepting process (TEAP). The Geobacter in silico model of cell-scale physiological metabolic pathways is comprised of hundreds of intra-cellular and environmental exchange reactions. One advantage of this approach is that the TEAP reaction stoichiometry and rate are now functions of the metabolic status of the microorganism. The linkage of in silico model reactions to specific Geobacter proteins has enabled the use of groundwater proteomic analyses to assess the accuracy of the model under evolving hydrologic and biogeochemical conditions. In this case, the largest predicted fluxes through in silico model reactions generally correspond to high abundances of proteins linked to those reactions (e.g. the condensation reaction catalyzed by the protein

Sum rule limitations of kinetic particle-production models

International Nuclear Information System (INIS)

Knoll, J.; CEA Centre d'Etudes Nucleaires de Grenoble, 38; Guet, C.

1988-04-01

Photoproduction and absorption sum rules generalized to systems at finite temperature provide a stringent check on the validity of kinetic models for the production of hard photons in intermediate energy nuclear collisions. We inspect such models for the case of nuclear matter at finite temperature employed in a kinetic regime which copes those encountered in energetic nuclear collisions, and find photon production rates which significantly exceed the limits imposed by the sum rule even under favourable concession. This suggests that coherence effects are quite important and the production of photons cannot be considered as an incoherent addition of individual NNγ production processes. The deficiencies of present kinetic models may also apply for the production of probes such as the pion which do not couple perturbatively to the nuclear currents. (orig.)

Kinetic models of cell growth, substrate utilization and bio ...

African Journals Online (AJOL)

Bio-decolorization kinetic studies of distillery effluent in a batch culture were conducted using Aspergillus fumigatus. A simple model was proposed using the Logistic Equation for the growth, Leudeking-Piret kinetics for bio-decolorization, and also for substrate utilization. The proposed models appeared to provide a suitable ...

Physical time scale in kinetic Monte Carlo simulations of continuous-time Markov chains.

Science.gov (United States)

Serebrinsky, Santiago A

2011-03-01

We rigorously establish a physical time scale for a general class of kinetic Monte Carlo algorithms for the simulation of continuous-time Markov chains. This class of algorithms encompasses rejection-free (or BKL) and rejection (or "standard") algorithms. For rejection algorithms, it was formerly considered that the availability of a physical time scale (instead of Monte Carlo steps) was empirical, at best. Use of Monte Carlo steps as a time unit now becomes completely unnecessary.

Integration of genome-scale metabolic networks into whole-body PBPK models shows phenotype-specific cases of drug-induced metabolic perturbation.

Science.gov (United States)

Cordes, Henrik; Thiel, Christoph; Baier, Vanessa; Blank, Lars M; Kuepfer, Lars

2018-01-01

Drug-induced perturbations of the endogenous metabolic network are a potential root cause of cellular toxicity. A mechanistic understanding of such unwanted side effects during drug therapy is therefore vital for patient safety. The comprehensive assessment of such drug-induced injuries requires the simultaneous consideration of both drug exposure at the whole-body and resulting biochemical responses at the cellular level. We here present a computational multi-scale workflow that combines whole-body physiologically based pharmacokinetic (PBPK) models and organ-specific genome-scale metabolic network (GSMN) models through shared reactions of the xenobiotic metabolism. The applicability of the proposed workflow is illustrated for isoniazid, a first-line antibacterial agent against Mycobacterium tuberculosis , which is known to cause idiosyncratic drug-induced liver injuries (DILI). We combined GSMN models of a human liver with N-acetyl transferase 2 (NAT2)-phenotype-specific PBPK models of isoniazid. The combined PBPK-GSMN models quantitatively describe isoniazid pharmacokinetics, as well as intracellular responses, and changes in the exometabolome in a human liver following isoniazid administration. Notably, intracellular and extracellular responses identified with the PBPK-GSMN models are in line with experimental and clinical findings. Moreover, the drug-induced metabolic perturbations are distributed and attenuated in the metabolic network in a phenotype-dependent manner. Our simulation results show that a simultaneous consideration of both drug pharmacokinetics at the whole-body and metabolism at the cellular level is mandatory to explain drug-induced injuries at the patient level. The proposed workflow extends our mechanistic understanding of the biochemistry underlying adverse events and may be used to prevent drug-induced injuries in the future.

Phenomenology of local scale invariance: from conformal invariance to dynamical scaling

International Nuclear Information System (INIS)

Henkel, Malte

2002-01-01

Statistical systems displaying a strongly anisotropic or dynamical scaling behaviour are characterized by an anisotropy exponent θ or a dynamical exponent z. For a given value of θ (or z), we construct local scale transformations, which can be viewed as scale transformations with a space-time-dependent dilatation factor. Two distinct types of local scale transformations are found. The first type may describe strongly anisotropic scaling of static systems with a given value of θ, whereas the second type may describe dynamical scaling with a dynamical exponent z. Local scale transformations act as a dynamical symmetry group of certain non-local free-field theories. Known special cases of local scale invariance are conformal invariance for θ=1 and Schroedinger invariance for θ=2. The hypothesis of local scale invariance implies that two-point functions of quasi primary operators satisfy certain linear fractional differential equations, which are constructed from commuting fractional derivatives. The explicit solution of these yields exact expressions for two-point correlators at equilibrium and for two-point response functions out of equilibrium. A particularly simple and general form is found for the two-time auto response function. These predictions are explicitly confirmed at the uniaxial Lifshitz points in the ANNNI and ANNNS models and in the aging behaviour of simple ferromagnets such as the kinetic Glauber-Ising model and the kinetic spherical model with a non-conserved order parameter undergoing either phase-ordering kinetics or non-equilibrium critical dynamics

Land use/land cover and scale influences on in-stream nitrogen uptake kinetics

Science.gov (United States)

Covino, Tim; McGlynn, Brian; McNamara, Rebecca

2012-06-01

Land use/land cover change often leads to increased nutrient loading to streams; however, its influence on stream ecosystem nutrient transport remains poorly understood. Given the deleterious impacts elevated nutrient loading can have on aquatic ecosystems, it is imperative to improve understanding of nutrient retention capacities across stream scales and watershed development gradients. We performed 17 nutrient addition experiments on six streams across the West Fork Gallatin Watershed, Montana, USA, to quantify nitrogen uptake kinetics and retention dynamics across stream sizes (first to fourth order) and along a watershed development gradient. We observed that stream nitrogen (N) uptake kinetics and spiraling parameters varied across streams of different development intensity and scale. In more developed watersheds we observed a fertilization affect. This fertilization affect was evident as increased ash-free dry mass, chlorophylla, and ambient and maximum uptake rates in developed as compared to undeveloped streams. Ash-free dry mass, chlorophylla, and the number of structures in a subwatershed were significantly correlated to nutrient spiraling and kinetic parameters, while ambient and average annual N concentrations were not. Additionally, increased maximum uptake capacities in developed streams contributed to low in-stream nutrient concentrations during the growing season, and helped maintain watershed export at low levels during base flow. Our results indicate that land use/land cover change can enhance in-stream uptake of limiting nutrients and highlight the need for improved understanding of the watershed dynamics that control nutrient export across scales and development intensities for mitigation and protection of aquatic ecosystems.

Phase-field modeling of corrosion kinetics under dual-oxidants

Science.gov (United States)

Wen, You-Hai; Chen, Long-Qing; Hawk, Jeffrey A.

2012-04-01

A phase-field model is proposed to simulate corrosion kinetics under a dual-oxidant atmosphere. It will be demonstrated that the model can be applied to simulate corrosion kinetics under oxidation, sulfidation and simultaneous oxidation/sulfidation processes. Phase-dependent diffusivities are incorporated in a natural manner and allow more realistic modeling as the diffusivities usually differ by many orders of magnitude in different phases. Simple free energy models are then used for testing the model while calibrated free energy models can be implemented for quantitative modeling.

Kinetic equations for the collisional plasma model

International Nuclear Information System (INIS)

Rij, W.I. Van; Meier, H.K.; Beasley, C.O. Jr.; McCune, J.E.

1977-01-01

Using the Collisional Plasma Model (CPM) representation, expressions are derived for the Vlasov operator, both in its general form and in the drift-kinetic approximation following the recursive derivation by Hazeltine. The expressions for the operators give easily calculated couplings between neighbouring components of the CPM representation. Expressions for various macroscopic observables in the drift-kinetics approximation are also given. (author)

The importance of becoming double-stranded: Innate immunity and the kinetic model of HIV-1 central plus strand synthesis

International Nuclear Information System (INIS)

Poeschla, Eric

2013-01-01

Central initiation of plus strand synthesis is a conserved feature of lentiviruses and certain other retroelements. This complication of the standard reverse transcription mechanism produces a transient “central DNA flap” in the viral cDNA, which has been proposed to mediate its subsequent nuclear import. This model has assumed that the important feature is the flapped DNA structure itself rather than the process that produces it. Recently, an alternative kinetic model was proposed. It posits that central plus strand synthesis functions to accelerate conversion to the double-stranded state, thereby helping HIV-1 to evade single-strand DNA-targeting antiviral restrictions such as APOBEC3 proteins, and perhaps to avoid innate immune sensor mechanisms. The model is consistent with evidence that lentiviruses must often synthesize their cDNAs when dNTP concentrations are limiting and with data linking reverse transcription and uncoating. There may be additional kinetic advantages for the artificial genomes of lentiviral gene therapy vectors. - Highlights: • Two main functional models for HIV central plus strand synthesis have been proposed. • In one, a transient central DNA flap in the viral cDNA mediates HIV-1 nuclear import. • In the other, multiple kinetic consequences are emphasized. • One is defense against APOBEC3G, which deaminates single-stranded DNA. • Future questions pertain to antiviral restriction, uncoating and nuclear import

RETRAN-02 one-dimensional kinetics model: a review

International Nuclear Information System (INIS)

Gose, G.C.; McClure, J.A.

1986-01-01

RETRAN-02 is a modular code system that has been designed for one-dimensional, transient thermal-hydraulics analysis. In RETRAN-02, core power behavior may be treated using a one-dimensional reactor kinetics model. This model allows the user to investigate the interaction of time- and space-dependent effects in the reactor core on overall system behavior for specific LWR operational transients. The purpose of this paper is to review the recent analysis and development activities related to the one dimensional kinetics model in RETRAN-02

Lumping procedure for a kinetic model of catalytic naphtha reforming

Directory of Open Access Journals (Sweden)

H. M. Arani

2009-12-01

Full Text Available A lumping procedure is developed for obtaining kinetic and thermodynamic parameters of catalytic naphtha reforming. All kinetic and deactivation parameters are estimated from industrial data and thermodynamic parameters are calculated from derived mathematical expressions. The proposed model contains 17 lumps that include the C6 to C8+ hydrocarbon range and 15 reaction pathways. Hougen-Watson Langmuir-Hinshelwood type reaction rate expressions are used for kinetic simulation of catalytic reactions. The kinetic parameters are benchmarked with several sets of plant data and estimated by the SQP optimization method. After calculation of deactivation and kinetic parameters, plant data are compared with model predictions and only minor deviations between experimental and calculated data are generally observed.

Improved point-kinetics model for the BWR control rod drop accident

International Nuclear Information System (INIS)

Neogy, P.; Wakabayashi, T.; Carew, J.F.

1985-01-01

A simple prescription to account for spatial feedback weighting effects in RDA (rod drop accident) point-kinetics analyses has been derived and tested. The point-kinetics feedback model is linear in the core peaking factor, F/sub Q/, and in the core average void fraction and fuel temperature. Comparison with detailed spatial kinetics analyses indicates that the improved point-kinetics model provides an accurate description of the BWR RDA

Drift-Scale THC Seepage Model

International Nuclear Information System (INIS)

C.R. Bryan

2005-01-01

process model relying on the same conceptual model and many of the same input data (i.e., physical, hydrologic, thermodynamic, and kinetic) as the THC seepage model. The DST THC submodel is the primary means for validating the THC seepage model. The DST THC submodel compares predicted water and gas compositions, and mineral alteration patterns, with observed data from the DST. These models provide the framework to evaluate THC coupled processes at the drift scale, predict flow and transport behavior for specified thermal-loading conditions, and predict the evolution of mineral alteration and fluid chemistry around potential waste emplacement drifts. The DST THC submodel is used solely for the validation of the THC seepage model and is not used for calibration to measured data

Rarefied gas flow simulations using high-order gas-kinetic unified algorithms for Boltzmann model equations

Science.gov (United States)

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

Rainbow: a tool for large-scale whole-genome sequencing data analysis using cloud computing.

Science.gov (United States)

Zhao, Shanrong; Prenger, Kurt; Smith, Lance; Messina, Thomas; Fan, Hongtao; Jaeger, Edward; Stephens, Susan

2013-06-27

Technical improvements have decreased sequencing costs and, as a result, the size and number of genomic datasets have increased rapidly. Because of the lower cost, large amounts of sequence data are now being produced by small to midsize research groups. Crossbow is a software tool that can detect single nucleotide polymorphisms (SNPs) in whole-genome sequencing (WGS) data from a single subject; however, Crossbow has a number of limitations when applied to multiple subjects from large-scale WGS projects. The data storage and CPU resources that are required for large-scale whole genome sequencing data analyses are too large for many core facilities and individual laboratories to provide. To help meet these challenges, we have developed Rainbow, a cloud-based software package that can assist in the automation of large-scale WGS data analyses. Here, we evaluated the performance of Rainbow by analyzing 44 different whole-genome-sequenced subjects. Rainbow has the capacity to process genomic data from more than 500 subjects in two weeks using cloud computing provided by the Amazon Web Service. The time includes the import and export of the data using Amazon Import/Export service. The average cost of processing a single sample in the cloud was less than 120 US dollars. Compared with Crossbow, the main improvements incorporated into Rainbow include the ability: (1) to handle BAM as well as FASTQ input files; (2) to split large sequence files for better load balance downstream; (3) to log the running metrics in data processing and monitoring multiple Amazon Elastic Compute Cloud (EC2) instances; and (4) to merge SOAPsnp outputs for multiple individuals into a single file to facilitate downstream genome-wide association studies. Rainbow is a scalable, cost-effective, and open-source tool for large-scale WGS data analysis. For human WGS data sequenced by either the Illumina HiSeq 2000 or HiSeq 2500 platforms, Rainbow can be used straight out of the box. Rainbow is available

Quantum kinetic Ising models

International Nuclear Information System (INIS)

Augusiak, R; Cucchietti, F M; Lewenstein, M; Haake, F

2010-01-01

In this paper, we introduce a quantum generalization of classical kinetic Ising models (KIM), described by a certain class of quantum many-body master equations. Similarly to KIMs with detailed balance that are equivalent to certain Hamiltonian systems, our models reduce to a set of Hamiltonian systems determining the dynamics of the elements of the many-body density matrix. The ground states of these Hamiltonians are well described by the matrix product, or pair entangled projected states. We discuss critical properties of such Hamiltonians, as well as entanglement properties of their low-energy states.

On the scale similarity in large eddy simulation. A proposal of a new model

International Nuclear Information System (INIS)

Pasero, E.; Cannata, G.; Gallerano, F.

2004-01-01

Among the most common LES models present in literature there are the Eddy Viscosity-type models. In these models the subgrid scale (SGS) stress tensor is related to the resolved strain rate tensor through a scalar eddy viscosity coefficient. These models are affected by three fundamental drawbacks: they are purely dissipative, i.e. they cannot account for back scatter; they assume that the principal axes of the resolved strain rate tensor and SGS stress tensor are aligned; and that a local balance exists between the SGS turbulent kinetic energy production and its dissipation. Scale similarity models (SSM) were created to overcome the drawbacks of eddy viscosity-type models. The SSM models, such as that of Bardina et al. and that of Liu et al., assume that scales adjacent in wave number space present similar hydrodynamic features. This similarity makes it possible to effectively relate the unresolved scales, represented by the modified Cross tensor and the modified Reynolds tensor, to the smallest resolved scales represented by the modified Leonard tensor] or by a term obtained through multiple filtering operations at different scales. The models of Bardina et al. and Liu et al. are affected, however, by a fundamental drawback: they are not dissipative enough, i.e they are not able to ensure a sufficient energy drain from the resolved scales of motion to the unresolved ones. In this paper it is shown that such a drawback is due to the fact that such models do not take into account the smallest unresolved scales where the most dissipation of turbulent SGS energy takes place. A new scale similarity LES model that is able to grant an adequate drain of energy from the resolved scales to the unresolved ones is presented. The SGS stress tensor is aligned with the modified Leonard tensor. The coefficient of proportionality is expressed in terms of the trace of the modified Leonard tensor and in terms of the SGS kinetic energy (computed by solving its balance equation). The

Finding Nemo's Genes: A chromosome-scale reference assembly of the genome of the orange clownfish Amphiprion percula

KAUST Repository

Lehmann, Robert; Lightfoot, Damien J; Schunter, Celia Marei; Michell, Craig T; Ohyanagi, Hajime; Mineta, Katsuhiko; Foret, Sylvain; Berumen, Michael L.; Miller, David J; Aranda, Manuel; Gojobori, Takashi; Munday, Philip L; Ravasi, Timothy

2018-01-01

The iconic orange clownfish, Amphiprion percula, is a model organism for studying the ecology and evolution of reef fishes, including patterns of population connectivity, sex change, social organization, habitat selection and adaptation to climate change. Notably, the orange clownfish is the only reef fish for which a complete larval dispersal kernel has been established and was the first fish species for which it was demonstrated that anti-predator responses of reef fishes could be impaired by ocean acidification. Despite its importance, molecular resources for this species remain scarce and until now it lacked a reference genome assembly. Here we present a de novo chromosome-scale assembly of the genome of the orange clownfish Amphiprion percula. We utilized single-molecule real-time sequencing technology from Pacific Biosciences to produce an initial polished assembly comprised of 1,414 contigs, with a contig N50 length of 1.86 Mb. Using Hi-C based chromatin contact maps, 98% of the genome assembly were placed into 24 chromosomes, resulting in a final assembly of 908.8 Mb in length with contig and scaffold N50s of 3.12 and 38.4 Mb, respectively. This makes it one of the most contiguous and complete fish genome assemblies currently available. The genome was annotated with 26,597 protein coding genes and contains 96% of the core set of conserved actinopterygian orthologs. The availability of this reference genome assembly as a community resource will further strengthen the role of the orange clownfish as a model species for research on the ecology and evolution of reef fishes.

Finding Nemo's Genes: A chromosome-scale reference assembly of the genome of the orange clownfish Amphiprion percula

KAUST Repository

Lehmann, Robert

2018-03-08

The iconic orange clownfish, Amphiprion percula, is a model organism for studying the ecology and evolution of reef fishes, including patterns of population connectivity, sex change, social organization, habitat selection and adaptation to climate change. Notably, the orange clownfish is the only reef fish for which a complete larval dispersal kernel has been established and was the first fish species for which it was demonstrated that anti-predator responses of reef fishes could be impaired by ocean acidification. Despite its importance, molecular resources for this species remain scarce and until now it lacked a reference genome assembly. Here we present a de novo chromosome-scale assembly of the genome of the orange clownfish Amphiprion percula. We utilized single-molecule real-time sequencing technology from Pacific Biosciences to produce an initial polished assembly comprised of 1,414 contigs, with a contig N50 length of 1.86 Mb. Using Hi-C based chromatin contact maps, 98% of the genome assembly were placed into 24 chromosomes, resulting in a final assembly of 908.8 Mb in length with contig and scaffold N50s of 3.12 and 38.4 Mb, respectively. This makes it one of the most contiguous and complete fish genome assemblies currently available. The genome was annotated with 26,597 protein coding genes and contains 96% of the core set of conserved actinopterygian orthologs. The availability of this reference genome assembly as a community resource will further strengthen the role of the orange clownfish as a model species for research on the ecology and evolution of reef fishes.

Kinetics of steel slag leaching: Batch tests and modeling

International Nuclear Information System (INIS)

De Windt, Laurent; Chaurand, Perrine; Rose, Jerome

2011-01-01

Reusing steel slag as an aggregate for road construction requires to characterize the leaching kinetics and metal releases. In this study, basic oxygen furnace (BOF) steel slag were subjected to batch leaching tests at liquid to solid ratios (L/S) of 10 and 100 over 30 days; the leachate chemistry being regularly sampled in time. A geochemical model of the steel slag is developed and validated from experimental data, particularly the evolution with leaching of mineralogical composition of the slag and trace element speciation. Kinetics is necessary for modeling the primary phase leaching, whereas a simple thermodynamic equilibrium approach can be used for secondary phase precipitation. The proposed model simulates the kinetically-controlled dissolution (hydrolysis) of primary phases, the precipitation of secondary phases (C-S-H, hydroxide and spinel), the pH and redox conditions, and the progressive release of major elements as well as the metals Cr and V. Modeling indicates that the dilution effect of the L/S ratio is often coupled to solubility-controlled processes, which are sensitive to both the pH and the redox potential. A sensitivity analysis of kinetic uncertainties on the modeling of element releases is performed.

One-dimensional reactor kinetics model for RETRAN

International Nuclear Information System (INIS)

Gose, G.C.; Peterson, C.E.; Ellis, N.L.; McClure, J.A.

1981-01-01

Previous versions of RETRAN have had only a point kinetics model to describe the reactor core behavior during thermal-hydraulic transients. The principal assumption in deriving the point kinetics model is that the neutron flux may be separated into a time-dependent amplitude funtion and a time-independent shape function. Certain types of transients cannot be correctly analyzed under this assumption, since proper definitions for core average quantities such as reactivity or lifetime include the inner product of the adjoint flux with the perturbed flux. A one-dimensional neutronics model has been included in a preliminary version of RETRAN-02. The ability to account for flux shape changes will permit an improved representation of the thermal and hydraulic feedback effects. This paper describes the neutronics model and discusses some of the analyses

Technical note: Equivalent genomic models with a residual polygenic effect.

Science.gov (United States)

Liu, Z; Goddard, M E; Hayes, B J; Reinhardt, F; Reents, R

2016-03-01

Routine genomic evaluations in animal breeding are usually based on either a BLUP with genomic relationship matrix (GBLUP) or single nucleotide polymorphism (SNP) BLUP model. For a multi-step genomic evaluation, these 2 alternative genomic models were proven to give equivalent predictions for genomic reference animals. The model equivalence was verified also for young genotyped animals without phenotypes. Due to incomplete linkage disequilibrium of SNP markers to genes or causal mutations responsible for genetic inheritance of quantitative traits, SNP markers cannot explain all the genetic variance. A residual polygenic effect is normally fitted in the genomic model to account for the incomplete linkage disequilibrium. In this study, we start by showing the proof that the multi-step GBLUP and SNP BLUP models are equivalent for the reference animals, when they have a residual polygenic effect included. Second, the equivalence of both multi-step genomic models with a residual polygenic effect was also verified for young genotyped animals without phenotypes. Additionally, we derived formulas to convert genomic estimated breeding values of the GBLUP model to its components, direct genomic values and residual polygenic effect. Third, we made a proof that the equivalence of these 2 genomic models with a residual polygenic effect holds also for single-step genomic evaluation. Both the single-step GBLUP and SNP BLUP models lead to equal prediction for genotyped animals with phenotypes (e.g., reference animals), as well as for (young) genotyped animals without phenotypes. Finally, these 2 single-step genomic models with a residual polygenic effect were proven to be equivalent for estimation of SNP effects, too. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Kinetic modeling of antimony(III) oxidation and sorption in soils.

Science.gov (United States)

Cai, Yongbing; Mi, Yuting; Zhang, Hua

2016-10-05

Kinetic batch and saturated column experiments were performed to study the oxidation, adsorption and transport of Sb(III) in two soils with contrasting properties. Kinetic and column experiment results clearly demonstrated the extensive oxidation of Sb(III) in soils, and this can in return influence the adsorption and transport of Sb. Both sorption capacity and kinetic oxidation rate were much higher in calcareous Huanjiang soil than in acid red Yingtan soil. The results indicate that soil serve as a catalyst in promoting oxidation of Sb(III) even under anaerobic conditions. A PHREEQC model with kinetic formulations was developed to simulate the oxidation, sorption and transport of Sb(III) in soils. The model successfully described Sb(III) oxidation and sorption data in kinetic batch experiment. It was less successful in simulating the reactive transport of Sb(III) in soil columns. Additional processes such as colloid facilitated transport need to be quantified and considered in the model. Copyright © 2016 Elsevier B.V. All rights reserved.

Kinetic Modeling of a Heterogeneous Fenton Oxidative Treatment of Petroleum Refining Wastewater

Science.gov (United States)

Basheer Hasan, Diya'uddeen; Abdul Raman, Abdul Aziz; Wan Daud, Wan Mohd Ashri

2014-01-01

The mineralisation kinetics of petroleum refinery effluent (PRE) by Fenton oxidation were evaluated. Within the ambit of the experimental data generated, first-order kinetic model (FKM), generalised lumped kinetic model (GLKM), and generalized kinetic model (GKM) were tested. The obtained apparent kinetic rate constants for the initial oxidation step (k 2′), their final oxidation step (k 1′), and the direct conversion to endproducts step (k 3′) were 10.12, 3.78, and 0.24 min−1 for GKM; 0.98, 0.98, and nil min−1 for GLKM; and nil, nil, and >0.005 min−1 for FKM. The findings showed that GKM is superior in estimating the mineralization kinetics. PMID:24592152

Genome-scale metabolic network validation of Shewanella oneidensis using transposon insertion frequency analysis.

Directory of Open Access Journals (Sweden)

Hong Yang

2014-09-01

Full Text Available Transposon mutagenesis, in combination with parallel sequencing, is becoming a powerful tool for en-masse mutant analysis. A probability generating function was used to explain observed miniHimar transposon insertion patterns, and gene essentiality calls were made by transposon insertion frequency analysis (TIFA. TIFA incorporated the observed genome and sequence motif bias of the miniHimar transposon. The gene essentiality calls were compared to: 1 previous genome-wide direct gene-essentiality assignments; and, 2 flux balance analysis (FBA predictions from an existing genome-scale metabolic model of Shewanella oneidensis MR-1. A three-way comparison between FBA, TIFA, and the direct essentiality calls was made to validate the TIFA approach. The refinement in the interpretation of observed transposon insertions demonstrated that genes without insertions are not necessarily essential, and that genes that contain insertions are not always nonessential. The TIFA calls were in reasonable agreement with direct essentiality calls for S. oneidensis, but agreed more closely with E. coli essentiality calls for orthologs. The TIFA gene essentiality calls were in good agreement with the MR-1 FBA essentiality predictions, and the agreement between TIFA and FBA predictions was substantially better than between the FBA and the direct gene essentiality predictions.

Genome scale metabolic network reconstruction of Spirochaeta cellobiosiphila

Directory of Open Access Journals (Sweden)

Bharat Manna

2017-10-01

Full Text Available Substantial rise in the global energy demand is one of the biggest challenges in this century. Environmental pollution due to rapid depletion of the fossil fuel resources and its alarming impact on the climate change and Global Warming have motivated researchers to look for non-petroleum-based sustainable, eco-friendly, renewable, low-cost energy alternatives, such as biofuel. Lignocellulosic biomass is one of the most promising bio-resources with huge potential to contribute to this worldwide energy demand. However, the complex organization of the Cellulose, Hemicellulose and Lignin in the Lignocellulosic biomass requires extensive pre-treatment and enzymatic hydrolysis followed by fermentation, raising overall production cost of biofuel. This encourages researchers to design cost-effective approaches for the production of second generation biofuels. The products from enzymatic hydrolysis of cellulose are mostly glucose monomer or cellobiose unit that are subjected to fermentation. Spirochaeta genus is a well-known group of obligate or facultative anaerobes, living primarily on carbohydrate metabolism. Spirochaeta cellobiosiphila sp. is a facultative anaerobe under this genus, which uses a variety of monosaccharides and disaccharides as energy sources. However, most rapid growth occurs on cellobiose and fermentation yields significant amount of ethanol, acetate, CO2, H2 and small amounts of formate. It is predicted to be promising microbial machinery for industrial fermentation processes for biofuel production. The metabolic pathways that govern cellobiose metabolism in Spirochaeta cellobiosiphila are yet to be explored. The function annotation of the genome sequence of Spirochaeta cellobiosiphila is in progress. In this work we aim to map all the metabolic activities for reconstruction of genome-scale metabolic model of Spirochaeta cellobiosiphila.

Chemical Kinetic Modeling of 2-Methylhexane Combustion

KAUST Repository

Mohamed, Samah Y.; Sarathy, Mani

2015-01-01

necessity, as new experiments and advanced theories show inaccuracy in certain portions of the models. This study focuses on updating thermodynamic data and kinetic model for a gasoline surrogate fuel, 2-methylhexane, with recently published group values

A kinetic model for the glucose/glycine Maillard reaction pathways

NARCIS (Netherlands)

Martins, S.I.F.S.; Boekel, van M.A.J.S.

2005-01-01

A comprehensive kinetic model for the glucose/glycine Maillard reaction is proposed based on an approach called multiresponse kinetic modelling. Special attention was paid to reactants, intermediates and end products: -fructose, N-(1-deoxy--fructos-1-yl)-glycine (DFG), 1-deoxy-2,3-hexodiulose and

Modeling of hydrogen production methods: Single particle model and kinetics assessment

Energy Technology Data Exchange (ETDEWEB)

Miller, R.S.; Bellan, J. [California Institute of Technology, Pasadena, CA (United States)

1996-10-01

The investigation carried out by the Jet Propulsion Laboratory (JPL) is devoted to the modeling of biomass pyrolysis reactors producing an oil vapor (tar) which is a precursor to hydrogen. This is an informal collaboration with NREL whereby JPL uses the experimentally-generated NREL data both as initial and boundary conditions for the calculations, and as a benchmark for model validation. The goal of this investigation is to find drivers of biomass fast-pyrolysis in the low temperature regime. The rationale is that experimental observations produce sparse discrete conditions for model validation, and that numerical simulations produced with a validated model are an economic way to find control parameters and an optimal operation regime, thereby circumventing costly changes in hardware and tests. During this first year of the investigation, a detailed mathematical model has been formulated for the temporal and spatial accurate modeling of solid-fluid reactions in biomass particles. These are porous particles for which volumetric reaction rate data is known a priori and both the porosity and the permeability of the particle are large enough to allow for continuous gas phase flow. The methodology has been applied to the pyrolysis of spherically symmetric biomass particles by considering previously published kinetics schemes for both cellulose and wood. The results show that models which neglect the thermal and species boundary layers exterior to the particle will generally over predict both the pyrolysis rates and experimentally obtainable tar yields. An evaluation of the simulation results through comparisons with experimental data indicates that while the cellulose kinetics is reasonably accurate, the wood pyrolysis kinetics is not accurate; particularly at high reactor temperatures. Current effort in collaboration with NREL is aimed at finding accurate wood kinetics.

Dynamic Model of Basic Oxygen Steelmaking Process Based on Multi-zone Reaction Kinetics: Model Derivation and Validation

Science.gov (United States)

Rout, Bapin Kumar; Brooks, Geoff; Rhamdhani, M. Akbar; Li, Zushu; Schrama, Frank N. H.; Sun, Jianjun

2018-04-01

A multi-zone kinetic model coupled with a dynamic slag generation model was developed for the simulation of hot metal and slag composition during the basic oxygen furnace (BOF) operation. The three reaction zones (i) jet impact zone, (ii) slag-bulk metal zone, (iii) slag-metal-gas emulsion zone were considered for the calculation of overall refining kinetics. In the rate equations, the transient rate parameters were mathematically described as a function of process variables. A micro and macroscopic rate calculation methodology (micro-kinetics and macro-kinetics) were developed to estimate the total refining contributed by the recirculating metal droplets through the slag-metal emulsion zone. The micro-kinetics involves developing the rate equation for individual droplets in the emulsion. The mathematical models for the size distribution of initial droplets, kinetics of simultaneous refining of elements, the residence time in the emulsion, and dynamic interfacial area change were established in the micro-kinetic model. In the macro-kinetics calculation, a droplet generation model was employed and the total amount of refining by emulsion was calculated by summing the refining from the entire population of returning droplets. A dynamic FetO generation model based on oxygen mass balance was developed and coupled with the multi-zone kinetic model. The effect of post-combustion on the evolution of slag and metal composition was investigated. The model was applied to a 200-ton top blowing converter and the simulated value of metal and slag was found to be in good agreement with the measured data. The post-combustion ratio was found to be an important factor in controlling FetO content in the slag and the kinetics of Mn and P in a BOF process.

Scales of gravity

International Nuclear Information System (INIS)

Dvali, Gia; Kolanovic, Marko; Nitti, Francesco; Gabadadze, Gregory

2002-01-01

We propose a framework in which the quantum gravity scale can be as low as 10 -3 eV. The key assumption is that the standard model ultraviolet cutoff is much higher than the quantum gravity scale. This ensures that we observe conventional weak gravity. We construct an explicit brane-world model in which the brane-localized standard model is coupled to strong 5D gravity of infinite-volume flat extra space. Because of the high ultraviolet scale, the standard model fields generate a large graviton kinetic term on the brane. This kinetic term 'shields' the standard model from the strong bulk gravity. As a result, an observer on the brane sees weak 4D gravity up to astronomically large distances beyond which gravity becomes five dimensional. Modeling quantum gravity above its scale by the closed string spectrum we show that the shielding phenomenon protects the standard model from an apparent phenomenological catastrophe due to the exponentially large number of light string states. The collider experiments, astrophysics, cosmology and gravity measurements independently point to the same lower bound on the quantum gravity scale, 10 -3 eV. For this value the model has experimental signatures both for colliders and for submillimeter gravity measurements. Black holes reveal certain interesting properties in this framework

Probing the genome-scale metabolic landscape of Bordetella pertussis, the causative agent of whooping cough.

Science.gov (United States)

Branco Dos Santos, Filipe; Olivier, Brett G; Boele, Joost; Smessaert, Vincent; De Rop, Philippe; Krumpochova, Petra; Klau, Gunnar W; Giera, Martin; Dehottay, Philippe; Teusink, Bas; Goffin, Philippe

2017-08-25

Whooping cough is a highly-contagious respiratory disease caused by Bordetella pertussi s. Despite vaccination, its incidence has been rising alarmingly, and yet, the physiology of B. pertussis remains poorly understood. We combined genome-scale metabolic reconstruction, a novel optimization algorithm and experimental data to probe the full metabolic potential of this pathogen, using strain Tohama I as a reference. Experimental validation showed that B. pertussis secretes a significant proportion of nitrogen as arginine and purine nucleosides, which may contribute to modulation of the host response. We also found that B. pertussis can be unexpectedly versatile, being able to metabolize many compounds while displaying minimal nutrient requirements. It can grow without cysteine - using inorganic sulfur sources such as thiosulfate - and it can grow on organic acids such as citrate or lactate as sole carbon sources, providing in vivo demonstration that its TCA cycle is functional. Although the metabolic reconstruction of eight additional strains indicates that the structural genes underlying this metabolic flexibility are widespread, experimental validation suggests a role of strain-specific regulatory mechanisms in shaping metabolic capabilities. Among five alternative strains tested, three were shown to grow on substrate combinations requiring a functional TCA cycle, but only one could use thiosulfate. Finally, the metabolic model was used to rationally design growth media with over two-fold improvements in pertussis toxin production. This study thus provides novel insights into B. pertussis physiology, and highlights the potential, but also limitations of models solely based on metabolic gene content. IMPORTANCE The metabolic capabilities of Bordetella pertussis - the causative agent of whooping cough - were investigated from a systems-level perspective. We constructed a comprehensive genome-scale metabolic model for B. pertussis , and challenged its predictions

Modelling reveals kinetic advantages of co-transcriptional splicing.

Directory of Open Access Journals (Sweden)

Stuart Aitken

2011-10-01

Full Text Available Messenger RNA splicing is an essential and complex process for the removal of intron sequences. Whereas the composition of the splicing machinery is mostly known, the kinetics of splicing, the catalytic activity of splicing factors and the interdependency of transcription, splicing and mRNA 3' end formation are less well understood. We propose a stochastic model of splicing kinetics that explains data obtained from high-resolution kinetic analyses of transcription, splicing and 3' end formation during induction of an intron-containing reporter gene in budding yeast. Modelling reveals co-transcriptional splicing to be the most probable and most efficient splicing pathway for the reporter transcripts, due in part to a positive feedback mechanism for co-transcriptional second step splicing. Model comparison is used to assess the alternative representations of reactions. Modelling also indicates the functional coupling of transcription and splicing, because both the rate of initiation of transcription and the probability that step one of splicing occurs co-transcriptionally are reduced, when the second step of splicing is abolished in a mutant reporter.

Modelling reveals kinetic advantages of co-transcriptional splicing.

Science.gov (United States)

Aitken, Stuart; Alexander, Ross D; Beggs, Jean D

2011-10-01

Messenger RNA splicing is an essential and complex process for the removal of intron sequences. Whereas the composition of the splicing machinery is mostly known, the kinetics of splicing, the catalytic activity of splicing factors and the interdependency of transcription, splicing and mRNA 3' end formation are less well understood. We propose a stochastic model of splicing kinetics that explains data obtained from high-resolution kinetic analyses of transcription, splicing and 3' end formation during induction of an intron-containing reporter gene in budding yeast. Modelling reveals co-transcriptional splicing to be the most probable and most efficient splicing pathway for the reporter transcripts, due in part to a positive feedback mechanism for co-transcriptional second step splicing. Model comparison is used to assess the alternative representations of reactions. Modelling also indicates the functional coupling of transcription and splicing, because both the rate of initiation of transcription and the probability that step one of splicing occurs co-transcriptionally are reduced, when the second step of splicing is abolished in a mutant reporter.

Survey of protein–DNA interactions in Aspergillus oryzae on a genomic scale

Science.gov (United States)

Wang, Chao; Lv, Yangyong; Wang, Bin; Yin, Chao; Lin, Ying; Pan, Li

2015-01-01

The genome-scale delineation of in vivo protein–DNA interactions is key to understanding genome function. Only ∼5% of transcription factors (TFs) in the Aspergillus genus have been identified using traditional methods. Although the Aspergillus oryzae genome contains >600 TFs, knowledge of the in vivo genome-wide TF-binding sites (TFBSs) in aspergilli remains limited because of the lack of high-quality antibodies. We investigated the landscape of in vivo protein–DNA interactions across the A. oryzae genome through coupling the DNase I digestion of intact nuclei with massively parallel sequencing and the analysis of cleavage patterns in protein–DNA interactions at single-nucleotide resolution. The resulting map identified overrepresented de novo TF-binding motifs from genomic footprints, and provided the detailed chromatin remodeling patterns and the distribution of digital footprints near transcription start sites. The TFBSs of 19 known Aspergillus TFs were also identified based on DNase I digestion data surrounding potential binding sites in conjunction with TF binding specificity information. We observed that the cleavage patterns of TFBSs were dependent on the orientation of TF motifs and independent of strand orientation, consistent with the DNA shape features of binding motifs with flanking sequences. PMID:25883143

Modeling and Simulation of Optimal Resource Management during the Diurnal Cycle in Emiliania huxleyi by Genome-Scale Reconstruction and an Extended Flux Balance Analysis Approach.

Science.gov (United States)

Knies, David; Wittmüß, Philipp; Appel, Sebastian; Sawodny, Oliver; Ederer, Michael; Feuer, Ronny

2015-10-28

The coccolithophorid unicellular alga Emiliania huxleyi is known to form large blooms, which have a strong effect on the marine carbon cycle. As a photosynthetic organism, it is subjected to a circadian rhythm due to the changing light conditions throughout the day. For a better understanding of the metabolic processes under these periodically-changing environmental conditions, a genome-scale model based on a genome reconstruction of the E. huxleyi strain CCMP 1516 was created. It comprises 410 reactions and 363 metabolites. Biomass composition is variable based on the differentiation into functional biomass components and storage metabolites. The model is analyzed with a flux balance analysis approach called diurnal flux balance analysis (diuFBA) that was designed for organisms with a circadian rhythm. It allows storage metabolites to accumulate or be consumed over the diurnal cycle, while keeping the structure of a classical FBA problem. A feature of this approach is that the production and consumption of storage metabolites is not defined externally via the biomass composition, but the result of optimal resource management adapted to the diurnally-changing environmental conditions. The model in combination with this approach is able to simulate the variable biomass composition during the diurnal cycle in proximity to literature data.

Modeling and Simulation of Optimal Resource Management during the Diurnal Cycle in Emiliania huxleyi by Genome-Scale Reconstruction and an Extended Flux Balance Analysis Approach

Directory of Open Access Journals (Sweden)

David Knies

2015-10-01

Full Text Available The coccolithophorid unicellular alga Emiliania huxleyi is known to form large blooms, which have a strong effect on the marine carbon cycle. As a photosynthetic organism, it is subjected to a circadian rhythm due to the changing light conditions throughout the day. For a better understanding of the metabolic processes under these periodically-changing environmental conditions, a genome-scale model based on a genome reconstruction of the E. huxleyi strain CCMP 1516 was created. It comprises 410 reactions and 363 metabolites. Biomass composition is variable based on the differentiation into functional biomass components and storage metabolites. The model is analyzed with a flux balance analysis approach called diurnal flux balance analysis (diuFBA that was designed for organisms with a circadian rhythm. It allows storage metabolites to accumulate or be consumed over the diurnal cycle, while keeping the structure of a classical FBA problem. A feature of this approach is that the production and consumption of storage metabolites is not defined externally via the biomass composition, but the result of optimal resource management adapted to the diurnally-changing environmental conditions. The model in combination with this approach is able to simulate the variable biomass composition during the diurnal cycle in proximity to literature data.

A multi water bag model of drift kinetic electron plasma

International Nuclear Information System (INIS)

Morel, P.; Dreydemy Ghiro, F.; Berionni, V.; Gurcan, O.D.; Coulette, D.; Besse, N.

2014-01-01

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)]. (authors)

On mathematical modeling and numerical simulation of chemical kinetics in turbulent lean premixed combustion

Energy Technology Data Exchange (ETDEWEB)

Lilleberg, Bjorn

2011-07-01

This thesis investigates turbulent reacting lean premixed flows with detailed treatment of the chemistry. First, the fundamental equations which govern laminar and turbulent reacting flows are presented. A perfectly stirred reactor numerical code is developed to investigate the role of unmixedness and chemical kinetics in driving combustion instabilities. This includes both global single-step and detailed chemical kinetic mechanisms. The single-step mechanisms predict to some degree a similar behavior as the detailed mechanisms. However, it is shown that simple mechanisms can by themselves introduce instabilities. Magnussens Eddy Dissipation Concept (EDC) for turbulent combustion is implemented in the open source CFD toolbox OpenFOAM R for treatment of both fast and detailed chemistry. RANS turbulence models account for the turbulent compressible flow. A database of pre-calculated chemical time scales, which contains the influence of chemical kinetics, is coupled to EDC with fast chemistry to account for local extinction in both diffusion and premixed flames. Results are compared to fast and detailed chemistry calculations. The inclusion of the database shows significantly better results than the fast chemistry calculations while having a comparably small computational cost. Numerical simulations of four piloted lean premixed jet flames falling into the 'well stirred reactor/broken reaction zones' regime, with strong finite-rate chemistry effects, are performed. Measured and predicted scalars compare well for the two jets with the lowest velocities. The two jets with the highest velocities experience extinction and reignition, and the simulations are able to capture the decrease and increase of the OH mass fractions, but the peak values are higher than in the experiments. Also numerical simulations of a lean premixed lifted jet flame with high sensitivity to turbulence modeling and chemical kinetics are performed. Limitations of the applied turbulence and

Bayesian inference of chemical kinetic models from proposed reactions

KAUST Repository

Galagali, Nikhil

2015-02-01

© 2014 Elsevier Ltd. Bayesian inference provides a natural framework for combining experimental data with prior knowledge to develop chemical kinetic models and quantify the associated uncertainties, not only in parameter values but also in model structure. Most existing applications of Bayesian model selection methods to chemical kinetics have been limited to comparisons among a small set of models, however. The significant computational cost of evaluating posterior model probabilities renders traditional Bayesian methods infeasible when the model space becomes large. We present a new framework for tractable Bayesian model inference and uncertainty quantification using a large number of systematically generated model hypotheses. The approach involves imposing point-mass mixture priors over rate constants and exploring the resulting posterior distribution using an adaptive Markov chain Monte Carlo method. The posterior samples are used to identify plausible models, to quantify rate constant uncertainties, and to extract key diagnostic information about model structure-such as the reactions and operating pathways most strongly supported by the data. We provide numerical demonstrations of the proposed framework by inferring kinetic models for catalytic steam and dry reforming of methane using available experimental data.

Kinetics of Infection-Driven Growth Model with Birth and Death

International Nuclear Information System (INIS)

Yang Shunyou; Zhu Shengqing; Ke Jianhong; Lin Zhenquan

2008-01-01

We propose a two-species infection model, in which an infected aggregate can gain one monomer from a healthy one due to infection when they meet together. Moreover, both the healthy and infected aggregates may lose one monomer because of self-death, but a healthy aggregate can spontaneously yield a new monomer. Consider a simple system in which the birth/death rates are directly proportional to the aggregate size, namely, the birth and death rates of the healthy aggregate of size k are J 1 k and J 2 k while the self-death rate of the infected aggregate of size k is J 3 k. We then investigate the kinetics of such a system by means of rate equation approach. For the J 1 > J 2 case, the aggregate size distribution of either species approaches the generalized scaling form and the typical size of either species increases wavily at large times. For the J 1 = J 2 case, the size distribution of healthy aggregates approaches the generalized scaling form while that of infected aggregates satisfies the modified scaling form. For the J 1 2 case, the size distribution of healthy aggregates satisfies the modified scaling form, but that of infected aggregates does not scale

A Fokker-Planck based kinetic model for diatomic rarefied gas flows

Science.gov (United States)

Gorji, M. Hossein; Jenny, Patrick

2013-06-01

A Fokker-Planck based kinetic model is presented here, which also accounts for internal energy modes characteristic for diatomic gas molecules. The model is based on a Fokker-Planck approximation of the Boltzmann equation for monatomic molecules, whereas phenomenological principles were employed for the derivation. It is shown that the model honors the equipartition theorem in equilibrium and fulfills the Landau-Teller relaxation equations for internal degrees of freedom. The objective behind this approximate kinetic model is accuracy at reasonably low computational cost. This can be achieved due to the fact that the resulting stochastic differential equations are continuous in time; therefore, no collisions between the simulated particles have to be calculated. Besides, because of the devised energy conserving time integration scheme, it is not required to resolve the collisional scales, i.e., the mean collision time and the mean free path of molecules. This, of course, gives rise to much more efficient simulations with respect to other particle methods, especially the conventional direct simulation Monte Carlo (DSMC), for small and moderate Knudsen numbers. To examine the new approach, first the computational cost of the model was compared with respect to DSMC, where significant speed up could be obtained for small Knudsen numbers. Second, the structure of a high Mach shock (in nitrogen) was studied, and the good performance of the model for such out of equilibrium conditions could be demonstrated. At last, a hypersonic flow of nitrogen over a wedge was studied, where good agreement with respect to DSMC (with level to level transition model) for vibrational and translational temperatures is shown.

A Chromosome-Scale Assembly of the Bactrocera cucurbitae Genome Provides Insight to the Genetic Basis of white pupae

Directory of Open Access Journals (Sweden)

Sheina B. Sim

2017-06-01

Full Text Available Genetic sexing strains (GSS used in sterile insect technique (SIT programs are textbook examples of how classical Mendelian genetics can be directly implemented in the management of agricultural insect pests. Although the foundation of traditionally developed GSS are single locus, autosomal recessive traits, their genetic basis are largely unknown. With the advent of modern genomic techniques, the genetic basis of sexing traits in GSS can now be further investigated. This study is the first of its kind to integrate traditional genetic techniques with emerging genomics to characterize a GSS using the tephritid fruit fly pest Bactrocera cucurbitae as a model. These techniques include whole-genome sequencing, the development of a mapping population and linkage map, and quantitative trait analysis. The experiment designed to map the genetic sexing trait in B. cucurbitae, white pupae (wp, also enabled the generation of a chromosome-scale genome assembly by integrating the linkage map with the assembly. Quantitative trait loci analysis revealed SNP loci near position 42 MB on chromosome 3 to be tightly linked to wp. Gene annotation and synteny analysis show a near perfect relationship between chromosomes in B. cucurbitae and Muller elements A–E in Drosophila melanogaster. This chromosome-scale genome assembly is complete, has high contiguity, was generated using a minimal input DNA, and will be used to further characterize the genetic mechanisms underlying wp. Knowledge of the genetic basis of genetic sexing traits can be used to improve SIT in this species and expand it to other economically important Diptera.

Drift-Scale THC Seepage Model

Energy Technology Data Exchange (ETDEWEB)

C.R. Bryan

2005-02-17

alteration on flow in rocks surrounding drifts. The DST THC submodel uses a drift-scale process model relying on the same conceptual model and many of the same input data (i.e., physical, hydrologic, thermodynamic, and kinetic) as the THC seepage model. The DST THC submodel is the primary means for validating the THC seepage model. The DST THC submodel compares predicted water and gas compositions, and mineral alteration patterns, with observed data from the DST. These models provide the framework to evaluate THC coupled processes at the drift scale, predict flow and transport behavior for specified thermal-loading conditions, and predict the evolution of mineral alteration and fluid chemistry around potential waste emplacement drifts. The DST THC submodel is used solely for the validation of the THC seepage model and is not used for calibration to measured data.

A protocol for generating a high-quality genome-scale metabolic reconstruction.

Science.gov (United States)

Thiele, Ines; Palsson, Bernhard Ø

2010-01-01

Network reconstructions are a common denominator in systems biology. Bottom-up metabolic network reconstructions have been developed over the last 10 years. These reconstructions represent structured knowledge bases that abstract pertinent information on the biochemical transformations taking place within specific target organisms. The conversion of a reconstruction into a mathematical format facilitates a myriad of computational biological studies, including evaluation of network content, hypothesis testing and generation, analysis of phenotypic characteristics and metabolic engineering. To date, genome-scale metabolic reconstructions for more than 30 organisms have been published and this number is expected to increase rapidly. However, these reconstructions differ in quality and coverage that may minimize their predictive potential and use as knowledge bases. Here we present a comprehensive protocol describing each step necessary to build a high-quality genome-scale metabolic reconstruction, as well as the common trials and tribulations. Therefore, this protocol provides a helpful manual for all stages of the reconstruction process.

Genomic Feature Models

DEFF Research Database (Denmark)

Sørensen, Peter; Edwards, Stefan McKinnon; Rohde, Palle Duun

-additive genetic mechanisms. These modeling approaches have proven to be highly useful to determine population genetic parameters as well as prediction of genetic risk or value. We present a series of statistical modelling approaches that use prior biological information for evaluating the collective action......Whole-genome sequences and multiple trait phenotypes from large numbers of individuals will soon be available in many populations. Well established statistical modeling approaches enable the genetic analyses of complex trait phenotypes while accounting for a variety of additive and non...... regions and gene ontologies) that provide better model fit and increase predictive ability of the statistical model for this trait....

Integrating chemistry into 3D climate models: Detailed kinetics in the troposphere and stratosphere of a global climate model

Energy Technology Data Exchange (ETDEWEB)

Kao, C.Y.J.; Elliott, S. [Los Alamos National Lab., NM (United States). Earth and Environmental Sciences Div.; Turco, R.P.; Zhao, X. [Univ. of California, Los Angeles, CA (United States)

1997-11-01

This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). The motivation for the project is to create the first complete, three-dimensional climate model that enfolds atmospheric photochemistry. The LANL chemical global climate model (GCM) not only distributes the trace greenhouse gases and modifies their concentrations within the detailed photochemical web, but also permits them to influence the radiation field and so force their own transport. Both atmospheric chemistry and fluid dynamics are nonlinear and zonally asymmetric phenomena. They can only be adequately modeled in three dimensions on the global grid. The kinetics-augmented GCM is the only program within the atmospheric community capable of investigating interaction involving chemistry and transport. The authors have conducted case studies of timely three-dimensional chemistry issues. Examples include ozone production from biomass burning plumes, kinetic feedbacks in zonally asymmetric transport phenomena with month- to year-long time scales, and volcano sulfate aerosols with respect to their potential effects on tropospheric ozone depletion.

Modeling uptake kinetics of cadmium by field-grown lettuce

Energy Technology Data Exchange (ETDEWEB)

Chen Weiping [Department of Environmental Sciences, University of California, 900 University Avenue, Riverside, CA 92521 (United States)], E-mail: chenweip@yahoo.com.cn; Li Lianqing [Institute of Resources, Ecosystem and Environment of Agriculture, Nanjing Agricultural University, Nanjing 210095 (China); Chang, Andrew C.; Wu Laosheng [Department of Environmental Sciences, University of California, 900 University Avenue, Riverside, CA 92521 (United States); Kwon, Soon-Ik [Agricultural Environmental and Ecology Division, National Institute of Agricultural Science and Technology, Suwon 441-707 (Korea, Republic of); Bottoms, Rick [Desert Research and Extension Center, 1004 East Holton Road, El Centro, CA 92243 (United States)

2008-03-15

Cadmium uptake by field grown Romaine lettuce treated with P-fertilizers of different Cd levels was investigated over an entire growing season. Results indicated that the rate of Cd uptake at a given time of the season can be satisfactorily described by the Michaelis-Menten kinetics, that is, plant uptake increases as the Cd concentration in soil solution increases, and it gradually approaches a saturation level. However, the rate constant of the Michaelis-Menten kinetics changes over the growing season. Under a given soil Cd level, the cadmium content in plant tissue decreases exponentially with time. To account for the dynamic nature of Cd uptake, a kinetic model integrating the time factor was developed to simulate Cd plant uptake over the growing season: C{sub Plant} = C{sub Solution} . PUF{sub max} . exp[-b . t], where C{sub Plant} and C{sub Solution} refer to the Cd content in plant tissue and soil solution, respectively, PUF{sub max} and b are kinetic constants. - A kinetic model was developed to evaluate the uptake of Cd under field conditions.

Modeling uptake kinetics of cadmium by field-grown lettuce

International Nuclear Information System (INIS)

Chen Weiping; Li Lianqing; Chang, Andrew C.; Wu Laosheng; Kwon, Soon-Ik; Bottoms, Rick

2008-01-01

Cadmium uptake by field grown Romaine lettuce treated with P-fertilizers of different Cd levels was investigated over an entire growing season. Results indicated that the rate of Cd uptake at a given time of the season can be satisfactorily described by the Michaelis-Menten kinetics, that is, plant uptake increases as the Cd concentration in soil solution increases, and it gradually approaches a saturation level. However, the rate constant of the Michaelis-Menten kinetics changes over the growing season. Under a given soil Cd level, the cadmium content in plant tissue decreases exponentially with time. To account for the dynamic nature of Cd uptake, a kinetic model integrating the time factor was developed to simulate Cd plant uptake over the growing season: C Plant = C Solution . PUF max . exp[-b . t], where C Plant and C Solution refer to the Cd content in plant tissue and soil solution, respectively, PUF max and b are kinetic constants. - A kinetic model was developed to evaluate the uptake of Cd under field conditions

Experimental kinetic parameters in the thermo-fluid-dynamic modelling of coal combustion

International Nuclear Information System (INIS)

Migliavacca, G.; Perini, M.; Parodi, E.

2001-01-01

The designing and the optimisation of modern and efficient combustion systems are nowadays frequently based on calculation tools for mathematical modelling, which are able to predict the evolution of the process starting from the first principles of physics. Otherwise, in many cases, specific experimental parameters are needed to describe the specific nature of the materials considered in the calculations. It is especially true in the modelling of coal combustion, which is a complex process strongly dependent on the chemical and physical features of the fuel. This paper describes some experimental techniques used to estimate the fundamental kinetic parameters of coal combustion and shows how this data may be introduced in a model calculation to predict the pollutant emissions from a real scale combustion plant [it

Comparison of kinetic and fluid neutral models for attached and detached state

International Nuclear Information System (INIS)

Furubayashi, M.; Hoshino, K.; Toma, M.; Hatayama, A.; Coster, D.; Schneider, R.; Bonnin, X.; Kawashima, H.; Asakura, N.; Suzuki, Y.

2009-01-01

Neutral behavior has an important role in the transport simulations of the edge plasma. Most of the edge plasma transport codes treat neutral particles by a simple fluid model or a kinetic model. The fluid model allows faster calculations. However, the applicability of the fluid model is limited. In this study, simulation results of JT-60U from kinetic neutral model and fluid neutral model are compared under the attached and detached state, using the 2D edge plasma code package, SOLPS5.0. In the SOL region, no significant differences are observed in the upstream plasma profiles between kinetic and fluid neutral models. However, in the divertor region, large differences are observed in plasma and neutral profiles. Therefore, further optimization of the fluid neutral model should be performed. Otherwise kinetic neutral model should be used to analyze the divertor region.

Point kinetics model with one-dimensional (radial) heat conduction formalism

International Nuclear Information System (INIS)

Jain, V.K.

1989-01-01

A point-kinetics model with one-dimensional (radial) heat conduction formalism has been developed. The heat conduction formalism is based on corner-mesh finite difference method. To get average temperatures in various conducting regions, a novel weighting scheme has been devised. The heat conduction model has been incorporated in the point-kinetics code MRTF-FUEL. The point-kinetics equations are solved using the method of real integrating factors. It has been shown by analysing the simulation of hypothetical loss of regulation accident in NAPP reactor that the model is superior to the conventional one in accuracy and speed of computation. (author). 3 refs., 3 tabs

Multi-scale coding of genomic information: From DNA sequence to genome structure and function

International Nuclear Information System (INIS)

Arneodo, Alain; Vaillant, Cedric; Audit, Benjamin; Argoul, Francoise; D'Aubenton-Carafa, Yves; Thermes, Claude

2011-01-01

Understanding how chromatin is spatially and dynamically organized in the nucleus of eukaryotic cells and how this affects genome functions is one of the main challenges of cell biology. Since the different orders of packaging in the hierarchical organization of DNA condition the accessibility of DNA sequence elements to trans-acting factors that control the transcription and replication processes, there is actually a wealth of structural and dynamical information to learn in the primary DNA sequence. In this review, we show that when using concepts, methodologies, numerical and experimental techniques coming from statistical mechanics and nonlinear physics combined with wavelet-based multi-scale signal processing, we are able to decipher the multi-scale sequence encoding of chromatin condensation-decondensation mechanisms that play a fundamental role in regulating many molecular processes involved in nuclear functions.

Stepwise kinetic equilibrium models of quantitative polymerase chain reaction

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Cobbs Gary

2012-08-01

Full Text Available Abstract Background Numerous models for use in interpreting quantitative PCR (qPCR data are present in recent literature. The most commonly used models assume the amplification in qPCR is exponential and fit an exponential model with a constant rate of increase to a select part of the curve. Kinetic theory may be used to model the annealing phase and does not assume constant efficiency of amplification. Mechanistic models describing the annealing phase with kinetic theory offer the most potential for accurate interpretation of qPCR data. Even so, they have not been thoroughly investigated and are rarely used for interpretation of qPCR data. New results for kinetic modeling of qPCR are presented. Results Two models are presented in which the efficiency of amplification is based on equilibrium solutions for the annealing phase of the qPCR process. Model 1 assumes annealing of complementary targets strands and annealing of target and primers are both reversible reactions and reach a dynamic equilibrium. Model 2 assumes all annealing reactions are nonreversible and equilibrium is static. Both models include the effect of primer concentration during the annealing phase. Analytic formulae are given for the equilibrium values of all single and double stranded molecules at the end of the annealing step. The equilibrium values are then used in a stepwise method to describe the whole qPCR process. Rate constants of kinetic models are the same for solutions that are identical except for possibly having different initial target concentrations. Analysis of qPCR curves from such solutions are thus analyzed by simultaneous non-linear curve fitting with the same rate constant values applying to all curves and each curve having a unique value for initial target concentration. The models were fit to two data sets for which the true initial target concentrations are known. Both models give better fit to observed qPCR data than other kinetic models present in the

Stepwise kinetic equilibrium models of quantitative polymerase chain reaction.

Science.gov (United States)

Cobbs, Gary

2012-08-16

Numerous models for use in interpreting quantitative PCR (qPCR) data are present in recent literature. The most commonly used models assume the amplification in qPCR is exponential and fit an exponential model with a constant rate of increase to a select part of the curve. Kinetic theory may be used to model the annealing phase and does not assume constant efficiency of amplification. Mechanistic models describing the annealing phase with kinetic theory offer the most potential for accurate interpretation of qPCR data. Even so, they have not been thoroughly investigated and are rarely used for interpretation of qPCR data. New results for kinetic modeling of qPCR are presented. Two models are presented in which the efficiency of amplification is based on equilibrium solutions for the annealing phase of the qPCR process. Model 1 assumes annealing of complementary targets strands and annealing of target and primers are both reversible reactions and reach a dynamic equilibrium. Model 2 assumes all annealing reactions are nonreversible and equilibrium is static. Both models include the effect of primer concentration during the annealing phase. Analytic formulae are given for the equilibrium values of all single and double stranded molecules at the end of the annealing step. The equilibrium values are then used in a stepwise method to describe the whole qPCR process. Rate constants of kinetic models are the same for solutions that are identical except for possibly having different initial target concentrations. Analysis of qPCR curves from such solutions are thus analyzed by simultaneous non-linear curve fitting with the same rate constant values applying to all curves and each curve having a unique value for initial target concentration. The models were fit to two data sets for which the true initial target concentrations are known. Both models give better fit to observed qPCR data than other kinetic models present in the literature. They also give better estimates of

Incorporation of chemical kinetic models into process control

International Nuclear Information System (INIS)

Herget, C.J.; Frazer, J.W.

1981-01-01

An important consideration in chemical process control is to determine the precise rationing of reactant streams, particularly when a large time delay exists between the mixing of the reactants and the measurement of the product. In this paper, a method is described for incorporating chemical kinetic models into the control strategy in order to achieve optimum operating conditions. The system is first characterized by determining a reaction rate surface as a function of all input reactant concentrations over a feasible range. A nonlinear constrained optimization program is then used to determine the combination of reactants which produces the specified yield at minimum cost. This operating condition is then used to establish the nominal concentrations of the reactants. The actual operation is determined through a feedback control system employing a Smith predictor. The method is demonstrated on a laboratory bench scale enzyme reactor

Updated and standardized genome-scale reconstruction of Mycobacterium tuberculosis H37Rv, iEK1011, simulates flux states indicative of physiological conditions

DEFF Research Database (Denmark)

Kavvas, Erol S.; Seif, Yara; Yurkovich, James T.

2018-01-01

previous M. tuberculosis H37Rv genome-scale reconstructions. We functionally assess iEK1011 against previous models and show that the model increases correct gene essentiality predictions on two different experimental datasets by 6% (53% to 60%) and 18% (60% to 71%), respectively. We compared simulations...

Ab initio calculations and kinetic modeling of thermal conversion of methyl chloride: implications for gasification of biomass

DEFF Research Database (Denmark)

Singla, Mallika; Rasmussen, Morten Lund; Hashemi, Hamid

2018-01-01

. In the present work, the thermal conversion of CH3Cl under gasification conditions was investigated. A detailed chemical kinetic model for pyrolysis and oxidation of methyl chloride was developed and validated against selected experimental data from the literature. Key reactions of CH2Cl with O2 and C2H4......Limitations in current hot gas cleaning methods for chlorine species from biomass gasification may be a challenge for end use such as gas turbines, engines, and fuel cells, all requiring very low levels of chlorine. During devolatilization of biomass, chlorine is released partly as methyl chloride...... in low-temperature gasification. The present work illustrates how ab initio theory and chemical kinetic modeling can help to resolve emission issues for thermal processes in industrial scale....

Probabilistic parameter estimation in a 2-step chemical kinetics model for n-dodecane jet autoignition

Science.gov (United States)

Hakim, Layal; Lacaze, Guilhem; Khalil, Mohammad; Sargsyan, Khachik; Najm, Habib; Oefelein, Joseph

2018-05-01

This paper demonstrates the development of a simple chemical kinetics model designed for autoignition of n-dodecane in air using Bayesian inference with a model-error representation. The model error, i.e. intrinsic discrepancy from a high-fidelity benchmark model, is represented by allowing additional variability in selected parameters. Subsequently, we quantify predictive uncertainties in the results of autoignition simulations of homogeneous reactors at realistic diesel engine conditions. We demonstrate that these predictive error bars capture model error as well. The uncertainty propagation is performed using non-intrusive spectral projection that can also be used in principle with larger scale computations, such as large eddy simulation. While the present calibration is performed to match a skeletal mechanism, it can be done with equal success using experimental data only (e.g. shock-tube measurements). Since our method captures the error associated with structural model simplifications, we believe that the optimised model could then lead to better qualified predictions of autoignition delay time in high-fidelity large eddy simulations than the existing detailed mechanisms. This methodology provides a way to reduce the cost of reaction kinetics in simulations systematically, while quantifying the accuracy of predictions of important target quantities.

Discretized kinetic theory on scale-free networks

Science.gov (United States)

Bertotti, Maria Letizia; Modanese, Giovanni

2016-10-01

The network of interpersonal connections is one of the possible heterogeneous factors which affect the income distribution emerging from micro-to-macro economic models. In this paper we equip our model discussed in [1, 2] with a network structure. The model is based on a system of n differential equations of the kinetic discretized-Boltzmann kind. The network structure is incorporated in a probabilistic way, through the introduction of a link density P(α) and of correlation coefficients P(β|α), which give the conditioned probability that an individual with α links is connected to one with β links. We study the properties of the equations and give analytical results concerning the existence, normalization and positivity of the solutions. For a fixed network with P(α) = c/α q , we investigate numerically the dependence of the detailed and marginal equilibrium distributions on the initial conditions and on the exponent q. Our results are compatible with those obtained from the Bouchaud-Mezard model and from agent-based simulations, and provide additional information about the dependence of the individual income on the level of connectivity.

Subgrid-scale models for large-eddy simulation of rotating turbulent channel flows

Science.gov (United States)

Silvis, Maurits H.; Bae, Hyunji Jane; Trias, F. Xavier; Abkar, Mahdi; Moin, Parviz; Verstappen, Roel

2017-11-01

We aim to design subgrid-scale models for large-eddy simulation of rotating turbulent flows. Rotating turbulent flows form a challenging test case for large-eddy simulation due to the presence of the Coriolis force. The Coriolis force conserves the total kinetic energy while transporting it from small to large scales of motion, leading to the formation of large-scale anisotropic flow structures. The Coriolis force may also cause partial flow laminarization and the occurrence of turbulent bursts. Many subgrid-scale models for large-eddy simulation are, however, primarily designed to parametrize the dissipative nature of turbulent flows, ignoring the specific characteristics of transport processes. We, therefore, propose a new subgrid-scale model that, in addition to the usual dissipative eddy viscosity term, contains a nondissipative nonlinear model term designed to capture transport processes, such as those due to rotation. We show that the addition of this nonlinear model term leads to improved predictions of the energy spectra of rotating homogeneous isotropic turbulence as well as of the Reynolds stress anisotropy in spanwise-rotating plane-channel flows. This work is financed by the Netherlands Organisation for Scientific Research (NWO) under Project Number 613.001.212.

A turbulent time scale based k–ε model for probability density function modeling of turbulence/chemistry interactions: Application to HCCI combustion

International Nuclear Information System (INIS)

Maroteaux, Fadila; Pommier, Pierre-Lin

2013-01-01

Highlights: ► Turbulent time evolution is introduced in stochastic modeling approach. ► The particles number is optimized trough a restricted initial distribution. ► The initial distribution amplitude is modeled by magnitude of turbulence field. -- Abstract: Homogenous Charge Compression Ignition (HCCI) engine technology is known as an alternative to reduce NO x and particulate matter (PM) emissions. As shown by several experimental studies published in the literature, the ideally homogeneous mixture charge becomes stratified in composition and temperature, and turbulent mixing is found to play an important role in controlling the combustion progress. In a previous study, an IEM model (Interaction by Exchange with the Mean) has been used to describe the micromixing in a stochastic reactor model that simulates the HCCI process. The IEM model is a deterministic model, based on the principle that the scalar value approaches the mean value over the entire volume with a characteristic mixing time. In this previous model, the turbulent time scale was treated as a fixed parameter. The present study focuses on the development of a micro-mixing time model, in order to take into account the physical phenomena it stands for. For that purpose, a (k–ε) model is used to express this micro-mixing time model. The turbulence model used here is based on zero dimensional energy cascade applied during the compression and the expansion cycle; mean kinetic energy is converted to turbulent kinetic energy. Turbulent kinetic energy is converted to heat through viscous dissipation. Besides, in this study a relation to calculate the initial heterogeneities amplitude is proposed. The comparison of simulation results against experimental data shows overall satisfactory agreement at variable turbulent time scale

RELATIONSHIPS BETWEEN FLUID VORTICITY, KINETIC HELICITY, AND MAGNETIC FIELD ON SMALL-SCALES (QUIET-NETWORK) ON THE SUN

Energy Technology Data Exchange (ETDEWEB)

Sangeetha, C. R.; Rajaguru, S. P., E-mail: crsangeetha@iiap.res.in [Indian Institute of Astrophysics, Bangalore-34 (India)

2016-06-20

We derive horizontal fluid motions on the solar surface over large areas covering the quiet-Sun magnetic network from local correlation tracking of convective granules imaged in continuum intensity and Doppler velocity by the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory . From these we calculate the horizontal divergence, the vertical component of vorticity, and the kinetic helicity of fluid motions. We study the correlations between fluid divergence and vorticity, and between vorticity (kinetic helicity) and the magnetic field. We find that the vorticity (kinetic helicity) around small-scale fields exhibits a hemispherical pattern (in sign) similar to that followed by the magnetic helicity of large-scale active regions (containing sunspots). We identify this pattern to be a result of the Coriolis force acting on supergranular-scale flows (both the outflows and inflows), consistent with earlier studies using local helioseismology. Furthermore, we show that the magnetic fields cause transfer of vorticity from supergranular inflow regions to outflow regions, and that they tend to suppress the vortical motions around them when magnetic flux densities exceed about 300 G (from HMI). We also show that such an action of the magnetic fields leads to marked changes in the correlations between fluid divergence and vorticity. These results are speculated to be of importance to local dynamo action (if present) and to the dynamical evolution of magnetic helicity at the small-scale.

Ensemble Kinetic Modeling of Metabolic Networks from Dynamic Metabolic Profiles

Directory of Open Access Journals (Sweden)

Gengjie Jia

2012-11-01

Full Text Available Kinetic modeling of metabolic pathways has important applications in metabolic engineering, but significant challenges still remain. The difficulties faced vary from finding best-fit parameters in a highly multidimensional search space to incomplete parameter identifiability. To meet some of these challenges, an ensemble modeling method is developed for characterizing a subset of kinetic parameters that give statistically equivalent goodness-of-fit to time series concentration data. The method is based on the incremental identification approach, where the parameter estimation is done in a step-wise manner. Numerical efficacy is achieved by reducing the dimensionality of parameter space and using efficient random parameter exploration algorithms. The shift toward using model ensembles, instead of the traditional “best-fit” models, is necessary to directly account for model uncertainty during the application of such models. The performance of the ensemble modeling approach has been demonstrated in the modeling of a generic branched pathway and the trehalose pathway in Saccharomyces cerevisiae using generalized mass action (GMA kinetics.

Kinetic parameter estimation model for anaerobic co-digestion of waste activated sludge and microalgae.

Science.gov (United States)

Lee, Eunyoung; Cumberbatch, Jewel; Wang, Meng; Zhang, Qiong

2017-03-01

Anaerobic co-digestion has a potential to improve biogas production, but limited kinetic information is available for co-digestion. This study introduced regression-based models to estimate the kinetic parameters for the co-digestion of microalgae and Waste Activated Sludge (WAS). The models were developed using the ratios of co-substrates and the kinetic parameters for the single substrate as indicators. The models were applied to the modified first-order kinetics and Monod model to determine the rate of hydrolysis and methanogenesis for the co-digestion. The results showed that the model using a hyperbola function was better for the estimation of the first-order kinetic coefficients, while the model using inverse tangent function closely estimated the Monod kinetic parameters. The models can be used for estimating kinetic parameters for not only microalgae-WAS co-digestion but also other substrates' co-digestion such as microalgae-swine manure and WAS-aquatic plants. Copyright © 2016 Elsevier Ltd. All rights reserved.

Thermodynamic and kinetic modelling: creep resistant materials

DEFF Research Database (Denmark)

Hald, John; Korcakova, L.; Danielsen, Hilmar Kjartansson

2008-01-01

The use of thermodynamic and kinetic modelling of microstructure evolution in materials exposed to high temperatures in power plants is demonstrated with two examples. Precipitate stability in martensitic 9–12%Cr steels is modelled including equilibrium phase stability, growth of Laves phase part...

Density-temperature scaling of the fragility in a model glass-former

DEFF Research Database (Denmark)