Flavour chemicals in a sample of non-cigarette tobacco products without explicit flavour names sold in New York City in 2015

PubMed Central

Farley, Shannon M; Schroth, Kevin RJ; Grimshaw, Victoria; Luo, Wentai; DeGagne, Julia L; Tierney, Peyton A; Kim, Kilsun; Pankow, James F

2018-01-01

Background Youth who experiment with tobacco often start with flavoured products. In New York City (NYC), local law restricts sales of all tobacco products with ‘characterising flavours’ except for ‘tobacco, menthol, mint and wintergreen’. Enforcement is based on packaging: explicit use of a flavour name (eg, ‘strawberry’) or image depicting a flavour (eg, a fruit) is presumptive evidence that a product is flavoured and therefore prohibited. However, a tobacco product may contain significant levels of added flavour chemicals even when the label does not explicitly use a flavour name. Methods Sixteen tobacco products were purchased within NYC in 2015 that did not have explicit flavour names, along with three with flavour names. These were analysed for 92 known flavour chemicals plus triacetin by gas chromatography/mass spectrometry. Results 14 of the 16 products had total determined flavour chemical levels that were higher (>0.3 mg/g) than in previously studied flavour-labelled products and of a chemical profile indicating added flavour chemicals. Conclusions The results suggest that the tobacco industry has responded to sales restrictions by renaming flavoured products to avoid explicitly identifying them as flavoured. While chemical analysis is the most precise means of identifying flavours in tobacco products, federal tobacco laws pre-empt localities from basing regulations on that approach, limiting enforcement options. If the Food and Drug Administration would mandate that all tobacco products must indicate when flavourings are present above a specific level, local jurisdictions could enforce their sales restrictions. A level of 0.1 mg/g for total added flavour chemicals is suggested here as a relevant reference value for regulating added flavour chemicals in tobacco products. PMID:28400490

Template Directed Replication Supports the Maintenance of the Metabolically Coupled Replicator System

NASA Astrophysics Data System (ADS)

Könnyű, Balázs; Czárán, Tamás

2015-06-01

The RNA World scenario of prebiotic chemical evolution is among the most plausible conceptual framework available today for modelling the origin of life. RNA offers genetic and catalytic (metabolic) functionality embodied in a single chemical entity, and a metabolically cooperating community of RNA molecules would constitute a viable infrabiological subsystem with a potential to evolve into proto-cellular life. Our Metabolically Coupled Replicator System (MCRS) model is a spatially explicit computer simulation implementation of the RNA-World scenario, in which replicable ribozymes cooperate in supplying each other with monomers for their own replication. MCRS has been repeatedly demonstrated to be viable and evolvable, with different versions of the model improved in depth (chemical detail of metabolism) or in extension (additional functions of RNA molecules). One of the dynamically relevant extensions of the MCRS approach to prebiotic RNA evolution is the explicit inclusion of template replication into its assumptions, which we have studied in the present version. We found that this modification has not changed the behaviour of the system in the qualitative sense, just the range of the parameter space which is optimal for the coexistence of metabolically cooperating replicators has shifted in terms of metabolite mobility. The system also remains resistant and tolerant to parasitic replicators.

Explicit modeling of organic chemistry and secondary organic aerosol partitioning for Mexico City and its outflow plume

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

Lee-Taylor, J.; Madronich, Sasha; Aumont, B.

2011-12-21

The evolution of organic aerosols (OA) in Mexico City and its outflow is investigated with the nearly explicit gas phase photochemistry model GECKO-A (Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere), wherein precursor hydrocarbons are oxidized to numerous intermediate species for which vapor pressures are computed and used to determine gas/particle partitioning in a chemical box model. Precursor emissions included observed C3-10 alkanes, alkenes, and light aromatics, as well as larger n-alkanes (up to C25) not directly observed but estimated by scaling to particulate emissions according to their volatility. Conditions were selected for comparison with observations mademore » in March 2006 (MILAGRO). The model successfully reproduces the magnitude and diurnal shape for both primary (POA) and secondary (SOA) organic aerosols, with POA peaking in the early morning at 15-20 ug m-3, and SOA peaking at 10-15 μg m-3 during mid-day. The majority (> 75%) of the model SOA stems from the large n-alkanes, with the remainder mostly from the light aromatics. Simulated OA elemental composition reproduces observed H/C and O/C ratios reasonably well, although modeled ratios develop more slowly than observations suggest. SOA chemical composition is initially dominated by *- hydroxy ketones and nitrates from the large alkanes, with contributions from peroxy acyl nitrates and, at later times when NOx is lower, organic hydroperoxides. The simulated plume-integrated OA mass continues to increase for several days downwind despite dilution-induced particle evaporation, since oxidation chemistry leading to SOA formation remains strong. In this model, the plume SOA burden several days downwind exceeds that leaving the city by a factor of >3. These results suggest significant regional radiative impacts of SOA.« less

The development of an explicit thermochemical nonequilibrium algorithm and its application to compute three dimensional AFE flowfields

NASA Technical Reports Server (NTRS)

Palmer, Grant

1989-01-01

This study presents a three-dimensional explicit, finite-difference, shock-capturing numerical algorithm applied to viscous hypersonic flows in thermochemical nonequilibrium. The algorithm employs a two-temperature physical model. Equations governing the finite-rate chemical reactions are fully-coupled to the gas dynamic equations using a novel coupling technique. The new coupling method maintains stability in the explicit, finite-rate formulation while allowing relatively large global time steps. The code uses flux-vector accuracy. Comparisons with experimental data and other numerical computations verify the accuracy of the present method. The code is used to compute the three-dimensional flowfield over the Aeroassist Flight Experiment (AFE) vehicle at one of its trajectory points.

Mass balance modelling of contaminants in river basins: a flexible matrix approach.

PubMed

Warren, Christopher; Mackay, Don; Whelan, Mick; Fox, Kay

2005-12-01

A novel and flexible approach is described for simulating the behaviour of chemicals in river basins. A number (n) of river reaches are defined and their connectivity is described by entries in an n x n matrix. Changes in segmentation can be readily accommodated by altering the matrix entries, without the need for model revision. Two models are described. The simpler QMX-R model only considers advection and an overall loss due to the combined processes of volatilization, net transfer to sediment and degradation. The rate constant for the overall loss is derived from fugacity calculations for a single segment system. The more rigorous QMX-F model performs fugacity calculations for each segment and explicitly includes the processes of advection, evaporation, water-sediment exchange and degradation in both water and sediment. In this way chemical exposure in all compartments (including equilibrium concentrations in biota) can be estimated. Both models are designed to serve as intermediate-complexity exposure assessment tools for river basins with relatively low data requirements. By considering the spatially explicit nature of emission sources and the changes in concentration which occur with transport in the channel system, the approach offers significant advantages over simple one-segment simulations while being more readily applicable than more sophisticated, highly segmented, GIS-based models.

Theory of wavelet-based coarse-graining hierarchies for molecular dynamics.

PubMed

Rinderspacher, Berend Christopher; Bardhan, Jaydeep P; Ismail, Ahmed E

2017-07-01

We present a multiresolution approach to compressing the degrees of freedom and potentials associated with molecular dynamics, such as the bond potentials. The approach suggests a systematic way to accelerate large-scale molecular simulations with more than two levels of coarse graining, particularly applications of polymeric materials. In particular, we derive explicit models for (arbitrarily large) linear (homo)polymers and iterative methods to compute large-scale wavelet decompositions from fragment solutions. This approach does not require explicit preparation of atomistic-to-coarse-grained mappings, but instead uses the theory of diffusion wavelets for graph Laplacians to develop system-specific mappings. Our methodology leads to a hierarchy of system-specific coarse-grained degrees of freedom that provides a conceptually clear and mathematically rigorous framework for modeling chemical systems at relevant model scales. The approach is capable of automatically generating as many coarse-grained model scales as necessary, that is, to go beyond the two scales in conventional coarse-grained strategies; furthermore, the wavelet-based coarse-grained models explicitly link time and length scales. Furthermore, a straightforward method for the reintroduction of omitted degrees of freedom is presented, which plays a major role in maintaining model fidelity in long-time simulations and in capturing emergent behaviors.

Transdimensional Bayesian tomography of the lowermost mantle from shear waves

NASA Astrophysics Data System (ADS)

Richardson, C.; Mousavi, S. S.; Tkalcic, H.; Masters, G.

2017-12-01

The lowermost layer of the mantle, known as D'', is a complex region that contains significant heterogeneities on different spatial scales and a wide range of physical and chemical features such as partial melting, seismic anisotropy, and variations in thermal and chemical composition. The most powerful tools we have to probe this region are seismic waves and corresponding imaging techniques such as tomography. Recently, we developed compressional velocity tomograms of D'' using a transdimensional Bayesian inversion, where the model parameterization is not explicit and regularization is not required. This has produced a far more nuanced P-wave velocity model of D'' than that from traditional S-wave tomography. We also note that P-wave models of D'' vary much more significantly among various research groups than the corresponding S-wave models. This study therefore seeks to develop a new S-wave velocity model of D'' underneath Australia by using predominantly ScS-S differential travel times measured through waveform correlation and Bayesian transdimensional inversion to further understand and characterize heterogeneities in D''. We used events at epicentral distances between 45 and 75 degrees from stations in Australia at depths of over 200 km and with magnitudes between 6.0 and 6.7. Because of globally incomplete coverage of station and earthquake locations, a major limitation of deep earth tomography has been the explicit parameterization of the region of interest. Explicit parameterization has been foundational in most studies, but faces inherent problems of either over-smoothing the data, or allowing for too much noise. To avoid this, we use spherical Voronoi polygons, which allow for a high level of flexibility as the polygons can grow, shrink, or be altogether deleted throughout a sequence of iterations. Our technique also yields highly desired model parameter uncertainties. While there is little doubt that D'' is heterogeneous, there is still much that is unclear about the extent and spatial distribution of different heterogeneous domains, as there are open questions about their dynamics and chemical interactions in the context of the surrounding mantle and outer core. In this context, our goal is also to quantify and understand the differences between S-wave and P-wave velocity tomographic models.

Charge-dependent many-body exchange and dispersion interactions in combined QM/MM simulations

NASA Astrophysics Data System (ADS)

Kuechler, Erich R.; Giese, Timothy J.; York, Darrin M.

2015-12-01

Accurate modeling of the molecular environment is critical in condensed phase simulations of chemical reactions. Conventional quantum mechanical/molecular mechanical (QM/MM) simulations traditionally model non-electrostatic non-bonded interactions through an empirical Lennard-Jones (LJ) potential which, in violation of intuitive chemical principles, is bereft of any explicit coupling to an atom's local electronic structure. This oversight results in a model whereby short-ranged exchange-repulsion and long-ranged dispersion interactions are invariant to changes in the local atomic charge, leading to accuracy limitations for chemical reactions where significant atomic charge transfer can occur along the reaction coordinate. The present work presents a variational, charge-dependent exchange-repulsion and dispersion model, referred to as the charge-dependent exchange and dispersion (QXD) model, for hybrid QM/MM simulations. Analytic expressions for the energy and gradients are provided, as well as a description of the integration of the model into existing QM/MM frameworks, allowing QXD to replace traditional LJ interactions in simulations of reactive condensed phase systems. After initial validation against QM data, the method is demonstrated by capturing the solvation free energies of a series of small, chlorine-containing compounds that have varying charge on the chlorine atom. The model is further tested on the SN2 attack of a chloride anion on methylchloride. Results suggest that the QXD model, unlike the traditional LJ model, is able to simultaneously obtain accurate solvation free energies for a range of compounds while at the same time closely reproducing the experimental reaction free energy barrier. The QXD interaction model allows explicit coupling of atomic charge with many-body exchange and dispersion interactions that are related to atomic size and provides a more accurate and robust representation of non-electrostatic non-bonded QM/MM interactions.

The feasibility of using explicit method for linear correction of the particle size variation using NIR Spectroscopy combined with PLS2regression method

NASA Astrophysics Data System (ADS)

Yulia, M.; Suhandy, D.

2018-03-01

NIR spectra obtained from spectral data acquisition system contains both chemical information of samples as well as physical information of the samples, such as particle size and bulk density. Several methods have been established for developing calibration models that can compensate for sample physical information variations. One common approach is to include physical information variation in the calibration model both explicitly and implicitly. The objective of this study was to evaluate the feasibility of using explicit method to compensate the influence of different particle size of coffee powder in NIR calibration model performance. A number of 220 coffee powder samples with two different types of coffee (civet and non-civet) and two different particle sizes (212 and 500 µm) were prepared. Spectral data was acquired using NIR spectrometer equipped with an integrating sphere for diffuse reflectance measurement. A discrimination method based on PLS-DA was conducted and the influence of different particle size on the performance of PLS-DA was investigated. In explicit method, we add directly the particle size as predicted variable results in an X block containing only the NIR spectra and a Y block containing the particle size and type of coffee. The explicit inclusion of the particle size into the calibration model is expected to improve the accuracy of type of coffee determination. The result shows that using explicit method the quality of the developed calibration model for type of coffee determination is a little bit superior with coefficient of determination (R2) = 0.99 and root mean square error of cross-validation (RMSECV) = 0.041. The performance of the PLS2 calibration model for type of coffee determination with particle size compensation was quite good and able to predict the type of coffee in two different particle sizes with relatively high R2 pred values. The prediction also resulted in low bias and RMSEP values.

Flavour chemicals in a sample of non-cigarette tobacco products without explicit flavour names sold in New York City in 2015.

PubMed

Farley, Shannon M; Schroth, Kevin Rj; Grimshaw, Victoria; Luo, Wentai; DeGagne, Julia L; Tierney, Peyton A; Kim, Kilsun; Pankow, James F

2018-03-01

Youth who experiment with tobacco often start with flavoured products. In New York City (NYC), local law restricts sales of all tobacco products with 'characterising flavours' except for 'tobacco, menthol, mint and wintergreen'. Enforcement is based on packaging: explicit use of a flavour name (eg, 'strawberry') or image depicting a flavour (eg, a fruit) is presumptive evidence that a product is flavoured and therefore prohibited. However, a tobacco product may contain significant levels of added flavour chemicals even when the label does not explicitly use a flavour name. Sixteen tobacco products were purchased within NYC in 2015 that did not have explicit flavour names, along with three with flavour names. These were analysed for 92 known flavour chemicals plus triacetin by gas chromatography/mass spectrometry. 14 of the 16 products had total determined flavour chemical levels that were higher (>0.3 mg/g) than in previously studied flavour-labelled products and of a chemical profile indicating added flavour chemicals. The results suggest that the tobacco industry has responded to sales restrictions by renaming flavoured products to avoid explicitly identifying them as flavoured. While chemical analysis is the most precise means of identifying flavours in tobacco products, federal tobacco laws pre-empt localities from basing regulations on that approach, limiting enforcement options. If the Food and Drug Administration would mandate that all tobacco products must indicate when flavourings are present above a specific level, local jurisdictions could enforce their sales restrictions. A level of 0.1 mg/g for total added flavour chemicals is suggested here as a relevant reference value for regulating added flavour chemicals in tobacco products. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Confronting effective models for deconfinement in dense quark matter with lattice data

NASA Astrophysics Data System (ADS)

Andersen, Jens O.; Brauner, Tomáš; Naylor, William R.

2015-12-01

Ab initio numerical simulations of the thermodynamics of dense quark matter remain a challenge. Apart from the infamous sign problem, lattice methods have to deal with finite volume and discretization effects as well as with the necessity to introduce sources for symmetry-breaking order parameters. We study these artifacts in the Polyakov-loop-extended Nambu-Jona-Lasinio (PNJL) model and compare its predictions to existing lattice data for cold and dense two-color matter with two flavors of Wilson quarks. To achieve even qualitative agreement with lattice data requires the introduction of two novel elements in the model: (i) explicit chiral symmetry breaking in the effective contact four-fermion interaction, referred to as the chiral twist, and (ii) renormalization of the Polyakov loop. The feedback of the dense medium to the gauge sector is modeled by a chemical-potential-dependent scale in the Polyakov-loop potential. In contrast to previously used analytical Ansätze, we determine its dependence on the chemical potential from lattice data for the expectation value of the Polyakov loop. Finally, we propose adding a two-derivative operator to our effective model. This term acts as an additional source of explicit chiral symmetry breaking, mimicking an analogous term in the lattice Wilson action.

Explicit modeling of volatile organic compounds partitioning in the atmospheric aqueous phase

NASA Astrophysics Data System (ADS)

Mouchel-Vallon, C.; Bräuer, P.; Camredon, M.; Valorso, R.; Madronich, S.; Herrmann, H.; Aumont, B.

2012-09-01

The gas phase oxidation of organic species is a multigenerational process involving a large number of secondary compounds. Most secondary organic species are water-soluble multifunctional oxygenated molecules. The fully explicit chemical mechanism GECKO-A (Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere) is used to describe the oxidation of organics in the gas phase and their mass transfer to the aqueous phase. The oxidation of three hydrocarbons of atmospheric interest (isoprene, octane and α-pinene) is investigated for various NOx conditions. The simulated oxidative trajectories are examined in a new two dimensional space defined by the mean oxidation state and the solubility. The amount of dissolved organic matter was found to be very low (<2%) under a water content typical of deliquescent aerosols. For cloud water content, 50% (isoprene oxidation) to 70% (octane oxidation) of the carbon atoms are found in the aqueous phase after the removal of the parent hydrocarbons for low NOx conditions. For high NOx conditions, this ratio is only 5% in the isoprene oxidation case, but remains large for α-pinene and octane oxidation cases (40% and 60%, respectively). Although the model does not yet include chemical reactions in the aqueous phase, much of this dissolved organic matter should be processed in cloud drops and modify both oxidation rates and the speciation of organic species.

Explicit modeling of volatile organic compounds partitioning in the atmospheric aqueous phase

NASA Astrophysics Data System (ADS)

Mouchel-Vallon, C.; Bräuer, P.; Camredon, M.; Valorso, R.; Madronich, S.; Herrmann, H.; Aumont, B.

2013-01-01

The gas phase oxidation of organic species is a multigenerational process involving a large number of secondary compounds. Most secondary organic species are water-soluble multifunctional oxygenated molecules. The fully explicit chemical mechanism GECKO-A (Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere) is used to describe the oxidation of organics in the gas phase and their mass transfer to the aqueous phase. The oxidation of three hydrocarbons of atmospheric interest (isoprene, octane and α-pinene) is investigated for various NOx conditions. The simulated oxidative trajectories are examined in a new two dimensional space defined by the mean oxidation state and the solubility. The amount of dissolved organic matter was found to be very low (yield less than 2% on carbon atom basis) under a water content typical of deliquescent aerosols. For cloud water content, 50% (isoprene oxidation) to 70% (octane oxidation) of the carbon atoms are found in the aqueous phase after the removal of the parent hydrocarbons for low NOx conditions. For high NOx conditions, this ratio is only 5% in the isoprene oxidation case, but remains large for α-pinene and octane oxidation cases (40% and 60%, respectively). Although the model does not yet include chemical reactions in the aqueous phase, much of this dissolved organic matter should be processed in cloud drops and modify both oxidation rates and the speciation of organic species.

Modeling of outgassing and matrix decomposition in carbon-phenolic composites

NASA Technical Reports Server (NTRS)

Mcmanus, Hugh L.

1994-01-01

Work done in the period Jan. - June 1994 is summarized. Two threads of research have been followed. First, the thermodynamics approach was used to model the chemical and mechanical responses of composites exposed to high temperatures. The thermodynamics approach lends itself easily to the usage of variational principles. This thermodynamic-variational approach has been applied to the transpiration cooling problem. The second thread is the development of a better algorithm to solve the governing equations resulting from the modeling. Explicit finite difference method is explored for solving the governing nonlinear, partial differential equations. The method allows detailed material models to be included and solution on massively parallel supercomputers. To demonstrate the feasibility of the explicit scheme in solving nonlinear partial differential equations, a transpiration cooling problem was solved. Some interesting transient behaviors were captured such as stress waves and small spatial oscillations of transient pressure distribution.

Simulating adsorption of U(VI) under transient groundwater flow and hydrochemistry: Physical versus chemical nonequilibrium model

USGS Publications Warehouse

Greskowiak, J.; Hay, M.B.; Prommer, H.; Liu, C.; Post, V.E.A.; Ma, R.; Davis, J.A.; Zheng, C.; Zachara, J.M.

2011-01-01

Coupled intragrain diffusional mass transfer and nonlinear surface complexation processes play an important role in the transport behavior of U(VI) in contaminated aquifers. Two alternative model approaches for simulating these coupled processes were analyzed and compared: (1) the physical nonequilibrium approach that explicitly accounts for aqueous speciation and instantaneous surface complexation reactions in the intragrain regions and approximates the diffusive mass exchange between the immobile intragrain pore water and the advective pore water as multirate first-order mass transfer and (2) the chemical nonequilibrium approach that approximates the diffusion-limited intragrain surface complexation reactions by a set of multiple first-order surface complexation reaction kinetics, thereby eliminating the explicit treatment of aqueous speciation in the intragrain pore water. A model comparison has been carried out for column and field scale scenarios, representing the highly transient hydrological and geochemical conditions in the U(VI)-contaminated aquifer at the Hanford 300A site, Washington, USA. It was found that the response of U(VI) mass transfer behavior to hydrogeochemically induced changes in U(VI) adsorption strength was more pronounced in the physical than in the chemical nonequilibrium model. The magnitude of the differences in model behavior depended particularly on the degree of disequilibrium between the advective and immobile phase U(VI) concentrations. While a clear difference in U(VI) transport behavior between the two models was noticeable for the column-scale scenarios, only minor differences were found for the Hanford 300A field scale scenarios, where the model-generated disequilibrium conditions were less pronounced as a result of frequent groundwater flow reversals. Copyright 2011 by the American Geophysical Union.

Active colloids in the context of chemical kinetics

NASA Astrophysics Data System (ADS)

Oshanin, G.; Popescu, M. N.; Dietrich, S.

2017-03-01

We study a mesoscopic model of a chemically active colloidal particle which on certain parts of its surface promotes chemical reactions in the surrounding solution. For reasons of simplicity and conceptual clarity, we focus on the case in which only electrically neutral species are present in the solution and on chemical reactions which are described by first order kinetics. Within a self-consistent approach we explicitly determine the steady state product and reactant number density fields around the colloid as functionals of the interaction potentials of the various molecular species in solution with the colloid. By using a reciprocal theorem, this allows us to compute and to interpret—in a transparent way in terms of the classical Smoluchowski theory of chemical kinetics—the external force needed to keep such a catalytically active colloid at rest (stall force) or, equivalently, the corresponding velocity of the colloid if it is free to move. We use the particular case of triangular-well interaction potentials as a benchmark example for applying the general theoretical framework developed here. For this latter case, we derive explicit expressions for the dependences of the quantities of interest on the diffusion coefficients of the chemical species, the reaction rate constant, the coverage by catalyst, the size of the colloid, as well as on the parameters of the interaction potentials. These expressions provide a detailed picture of the phenomenology associated with catalytically-active colloids and self-diffusiophoresis.

The role of mesocosm studies in ecological risk analysis

USGS Publications Warehouse

Boyle, Terence P.; Fairchild, James F.

1997-01-01

Mesocosms have been primarily used as research tools for the evaluation of the fate and effects of xenobiotic chemicals at the population, community, and ecosystem levels of biological organization. This paper provides suggestions for future applications of mesocosm research. Attention should be given to the configuration of mesocosm parameters to explicitly study regional questions of ecological interest. The initial physical, chemical, and biological conditions within mesocosms should be considered as factors shaping the final results of experiments. Certain fundamental questions such as the ecological inertia and resilience of systems with different initial ecological properties should be addressed. Researchers should develop closer working relationships with mathematical modelers in linking computer models to the outcomes of mesocosm studies. Mesocosm tests, linked with models, could enable managers and regulators to forecast the regional consequences of chemicals released into the environment.

QSAR modeling based on structure-information for properties of interest in human health.

PubMed

Hall, L H; Hall, L M

2005-01-01

The development of QSAR models based on topological structure description is presented for problems in human health. These models are based on the structure-information approach to quantitative biological modeling and prediction, in contrast to the mechanism-based approach. The structure-information approach is outlined, starting with basic structure information developed from the chemical graph (connection table). Information explicit in the connection table (element identity and skeletal connections) leads to significant (implicit) structure information that is useful for establishing sound models of a wide range of properties of interest in drug design. Valence state definition leads to relationships for valence state electronegativity and atom/group molar volume. Based on these important aspects of molecules, together with skeletal branching patterns, both the electrotopological state (E-state) and molecular connectivity (chi indices) structure descriptors are developed and described. A summary of four QSAR models indicates the wide range of applicability of these structure descriptors and the predictive quality of QSAR models based on them: aqueous solubility (5535 chemically diverse compounds, 938 in external validation), percent oral absorption (%OA, 417 therapeutic drugs, 195 drugs in external validation testing), AMES mutagenicity (2963 compounds including 290 therapeutic drugs, 400 in external validation), fish toxicity (92 substituted phenols, anilines and substituted aromatics). These models are established independent of explicit three-dimensional (3-D) structure information and are directly interpretable in terms of the implicit structure information useful to the drug design process.

A BGK model for reactive mixtures of polyatomic gases with continuous internal energy

NASA Astrophysics Data System (ADS)

Bisi, M.; Monaco, R.; Soares, A. J.

2018-03-01

In this paper we derive a BGK relaxation model for a mixture of polyatomic gases with a continuous structure of internal energies. The emphasis of the paper is on the case of a quaternary mixture undergoing a reversible chemical reaction of bimolecular type. For such a mixture we prove an H -theorem and characterize the equilibrium solutions with the related mass action law of chemical kinetics. Further, a Chapman-Enskog asymptotic analysis is performed in view of computing the first-order non-equilibrium corrections to the distribution functions and investigating the transport properties of the reactive mixture. The chemical reaction rate is explicitly derived at the first order and the balance equations for the constituent number densities are derived at the Euler level.

Assessing chemistry schemes and constraints in air quality models used to predict ozone in London against the detailed Master Chemical Mechanism.

PubMed

Malkin, Tamsin L; Heard, Dwayne E; Hood, Christina; Stocker, Jenny; Carruthers, David; MacKenzie, Ian A; Doherty, Ruth M; Vieno, Massimo; Lee, James; Kleffmann, Jörg; Laufs, Sebastian; Whalley, Lisa K

2016-07-18

Air pollution is the environmental factor with the greatest impact on human health in Europe. Understanding the key processes driving air quality across the relevant spatial scales, especially during pollution exceedances and episodes, is essential to provide effective predictions for both policymakers and the public. It is particularly important for policy regulators to understand the drivers of local air quality that can be regulated by national policies versus the contribution from regional pollution transported from mainland Europe or elsewhere. One of the main objectives of the Coupled Urban and Regional processes: Effects on AIR quality (CUREAIR) project is to determine local and regional contributions to ozone events. A detailed zero-dimensional (0-D) box model run with the Master Chemical Mechanism (MCMv3.2) is used as the benchmark model against which the less explicit chemistry mechanisms of the Generic Reaction Set (GRS) and the Common Representative Intermediates (CRIv2-R5) schemes are evaluated. GRS and CRI are used by the Atmospheric Dispersion Modelling System (ADMS-Urban) and the regional chemistry transport model EMEP4UK, respectively. The MCM model uses a near-explicit chemical scheme for the oxidation of volatile organic compounds (VOCs) and is constrained to observations of VOCs, NOx, CO, HONO (nitrous acid), photolysis frequencies and meteorological parameters measured during the ClearfLo (Clean Air for London) campaign. The sensitivity of the less explicit chemistry schemes to different model inputs has been investigated: Constraining GRS to the total VOC observed during ClearfLo as opposed to VOC derived from ADMS-Urban dispersion calculations, including emissions and background concentrations, led to a significant increase (674% during winter) in modelled ozone. The inclusion of HONO chemistry in this mechanism, particularly during wintertime when other radical sources are limited, led to substantial increases in the ozone levels predicted (223%). When the GRS and CRIv2-R5 schemes are run with the equivalent model constraints to the MCM, they are able to reproduce the level of ozone predicted by the near-explicit MCM to within 40% and 20% respectively for the majority of the time. An exception to this trend was observed during pollution episodes experienced in the summer, when anticyclonic conditions favoured increased temperatures and elevated O3. The in situ O3 predicted by the MCM was heavily influenced by biogenic VOCs during these conditions and the low GRS [O3] : MCM [O3] ratio (and low CRIv2-R5 [O3] : MCM [O3] ratio) demonstrates that these less explicit schemes under-represent the full O3 creation potential of these VOCs. To fully assess the influence of the in situ O3 generated from local emissions versus O3 generated upwind of London and advected in, the time since emission (and, hence, how far the real atmosphere is from steady state) must be determined. From estimates of the mean transport time determined from the NOx : NOy ratio observed at North Kensington during the summer and comparison of the O3 predicted by the MCM model after this time, ∼60% of the median observed [O3] could be generated from local emissions. During the warmer conditions experienced during the easterly flows, however, the observed [O3] may be even more heavily influenced by London's emissions.

Surface plasmons for doped graphene

NASA Astrophysics Data System (ADS)

Bordag, M.; Pirozhenko, I. G.

2015-04-01

Within the Dirac model for the electronic excitations of graphene, we calculate the full polarization tensor with finite mass and chemical potential. It has, besides the (00)-component, a second form factor, which must be accounted for. We obtain explicit formulas for both form factors and for the reflection coefficients. Using these, we discuss the regions in the momentum-frequency plane where plasmons may exist and give numeric solutions for the plasmon dispersion relations. It turns out that plasmons exist for both, transverse electric and transverse magnetic polarizations over the whole range of the ratio of mass to chemical potential, except for zero chemical potential, where only a TE plasmon exists.

Modelling the collective response of heterogeneous cell populations to stationary gradients and chemical signal relay

NASA Astrophysics Data System (ADS)

Pineda, M.; Eftimie, R.

2017-12-01

The directed motion of cell aggregates toward a chemical source occurs in many relevant biological processes. Understanding the mechanisms that control this complex behavior is of great relevance for our understanding of developmental biological processes and many diseases. In this paper, we consider a self-propelled particle model for the movement of heterogeneous subpopulations of chemically interacting cells towards an imposed stable chemical gradient. Our simulations show explicitly how self-organisation of cell populations (which could lead to engulfment or complete cell segregation) can arise from the heterogeneity of chemotactic responses alone. This new result complements current theoretical and experimental studies that emphasise the role of differential cell-cell adhesion on self-organisation and spatial structure of cellular aggregates. We also investigate how the speed of individual cell aggregations increases with the chemotactic sensitivity of the cells, and decreases with the number of cells inside the aggregates

Charge-dependent many-body exchange and dispersion interactions in combined QM/MM simulations

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

Kuechler, Erich R.; Department of Chemistry, University of Minnesota, Minneapolis, Minnesota 55455-0431; Giese, Timothy J.

2015-12-21

Accurate modeling of the molecular environment is critical in condensed phase simulations of chemical reactions. Conventional quantum mechanical/molecular mechanical (QM/MM) simulations traditionally model non-electrostatic non-bonded interactions through an empirical Lennard-Jones (LJ) potential which, in violation of intuitive chemical principles, is bereft of any explicit coupling to an atom’s local electronic structure. This oversight results in a model whereby short-ranged exchange-repulsion and long-ranged dispersion interactions are invariant to changes in the local atomic charge, leading to accuracy limitations for chemical reactions where significant atomic charge transfer can occur along the reaction coordinate. The present work presents a variational, charge-dependent exchange-repulsion andmore » dispersion model, referred to as the charge-dependent exchange and dispersion (QXD) model, for hybrid QM/MM simulations. Analytic expressions for the energy and gradients are provided, as well as a description of the integration of the model into existing QM/MM frameworks, allowing QXD to replace traditional LJ interactions in simulations of reactive condensed phase systems. After initial validation against QM data, the method is demonstrated by capturing the solvation free energies of a series of small, chlorine-containing compounds that have varying charge on the chlorine atom. The model is further tested on the S{sub N}2 attack of a chloride anion on methylchloride. Results suggest that the QXD model, unlike the traditional LJ model, is able to simultaneously obtain accurate solvation free energies for a range of compounds while at the same time closely reproducing the experimental reaction free energy barrier. The QXD interaction model allows explicit coupling of atomic charge with many-body exchange and dispersion interactions that are related to atomic size and provides a more accurate and robust representation of non-electrostatic non-bonded QM/MM interactions.« less

Convergence to equilibrium of renormalised solutions to nonlinear chemical reaction–diffusion systems

NASA Astrophysics Data System (ADS)

Fellner, Klemens; Tang, Bao Quoc

2018-06-01

The convergence to equilibrium for renormalised solutions to nonlinear reaction-diffusion systems is studied. The considered reaction-diffusion systems arise from chemical reaction networks with mass action kinetics and satisfy the complex balanced condition. By applying the so-called entropy method, we show that if the system does not have boundary equilibria, i.e. equilibrium states lying on the boundary of R_+^N, then any renormalised solution converges exponentially to the complex balanced equilibrium with a rate, which can be computed explicitly up to a finite-dimensional inequality. This inequality is proven via a contradiction argument and thus not explicitly. An explicit method of proof, however, is provided for a specific application modelling a reversible enzyme reaction by exploiting the specific structure of the conservation laws. Our approach is also useful to study the trend to equilibrium for systems possessing boundary equilibria. More precisely, to show the convergence to equilibrium for systems with boundary equilibria, we establish a sufficient condition in terms of a modified finite-dimensional inequality along trajectories of the system. By assuming this condition, which roughly means that the system produces too much entropy to stay close to a boundary equilibrium for infinite time, the entropy method shows exponential convergence to equilibrium for renormalised solutions to complex balanced systems with boundary equilibria.

A Model to Couple Flow, Thermal and Reactive Chemical Transport, and Geo-mechanics in Variably Saturated Media

NASA Astrophysics Data System (ADS)

Yeh, G. T.; Tsai, C. H.

2015-12-01

This paper presents the development of a THMC (thermal-hydrology-mechanics-chemistry) process model in variably saturated media. The governing equations for variably saturated flow and reactive chemical transport are obtained based on the mass conservation principle of species transport supplemented with Darcy's law, constraint of species concentration, equation of states, and constitutive law of K-S-P (Conductivity-Degree of Saturation-Capillary Pressure). The thermal transport equation is obtained based on the conservation of energy. The geo-mechanic displacement is obtained based on the assumption of equilibrium. Conventionally, these equations have been implicitly coupled via the calculations of secondary variables based on primary variables. The mechanisms of coupling have not been obvious. In this paper, governing equations are explicitly coupled for all primary variables. The coupling is accomplished via the storage coefficients, transporting velocities, and conduction-dispersion-diffusion coefficient tensor; one set each for every primary variable. With this new system of equations, the coupling mechanisms become clear. Physical interpretations of every term in the coupled equations will be discussed. Examples will be employed to demonstrate the intuition and superiority of these explicit coupling approaches. Keywords: Variably Saturated Flow, Thermal Transport, Geo-mechanics, Reactive Transport.

Corrosion Thermodynamics of Magnesium and Alloys from First Principles as a Function of Solvation

NASA Astrophysics Data System (ADS)

Limmer, Krista; Williams, Kristen; Andzelm, Jan

Thermodynamics of corrosion processes occurring on magnesium surfaces, such as hydrogen evolution and water dissociation, have been examined with density functional theory (DFT) to evaluate the effect of impurities and dilute alloying additions. The modeling of corrosion thermodynamics requires examination of species in a variety of chemical and electronic states in order to accurately represent the complex electrochemical corrosion process. In this study, DFT calculations for magnesium corrosion thermodynamics were performed with two DFT codes (VASP and DMol3), with multiple exchange-correlation functionals for chemical accuracy, as well as with various levels of implicit and explicit solvation for surfaces and solvated ions. The accuracy of the first principles calculations has been validated against Pourbaix diagrams constructed from solid, gas and solvated charged ion calculations. For aqueous corrosion, it is shown that a well parameterized implicit solvent is capable of accurately representing all but the first coordinating layer of explicit water for charged ions.

Predicting long-range transport: a systematic evaluation of two multimedia transport models.

PubMed

Bennett, D H; Scheringer, M; McKone, T E; Hungerbühler, K

2001-03-15

The United Nations Environment Program has recently developed criteria to identify and restrict chemicals with a potential for persistence and long-range transport (persistent organic pollutants or POPs). There are many stakeholders involved, and the issues are not only scientific but also include social, economic, and political factors. This work focuses on one aspect of the POPs debate, the criteria for determining the potential for long-range transport (LRT). Our goal is to determine if current models are reliable enough to support decisions that classify a chemical based on the LRT potential. We examine the robustness of two multimedia fate models for determining the relative ranking and absolute spatial range of various chemicals in the environment. We also consider the effect of parameter uncertainties and the model uncertainty associated with the selection of an algorithm for gas-particle partitioning on the model results. Given the same chemical properties, both models give virtually the same ranking. However, when chemical parameter uncertainties and model uncertainties such as particle partitioning are considered, the spatial range distributions obtained for the individual chemicals overlap, preventing a distinct rank order. The absolute values obtained for the predicted spatial range or travel distance differ significantly between the two models for the uncertainties evaluated. We find that to evaluate a chemical when large and unresolved uncertainties exist, it is more informative to use two or more models and include multiple types of uncertainty. Model differences and uncertainties must be explicitly confronted to determine how the limitations of scientific knowledge impact predictions in the decision-making process.

Phase structure of the Polyakov-quark-meson model

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

Schaefer, B.-J.; Pawlowski, J. M.; Wambach, J.

2007-10-01

The relation between the deconfinement and chiral phase transition is explored in the framework of a Polyakov-loop-extended two-flavor quark-meson (PQM) model. In this model the Polyakov loop dynamics is represented by a background temporal gauge field which also couples to the quarks. As a novelty an explicit quark chemical potential and N{sub f}-dependence in the Polyakov loop potential is proposed by using renormalization group arguments. The behavior of the Polyakov loop as well as the chiral condensate as function of temperature and quark chemical potential is obtained by minimizing the grand canonical thermodynamic potential of the system. The effect ofmore » the Polyakov loop dynamics on the chiral phase diagram and on several thermodynamic bulk quantities is presented.« less

Identifying Hydrologic Processes in Agricultural Watersheds Using Precipitation-Runoff Models

USGS Publications Warehouse

Linard, Joshua I.; Wolock, David M.; Webb, Richard M.T.; Wieczorek, Michael

2009-01-01

Understanding the fate and transport of agricultural chemicals applied to agricultural fields will assist in designing the most effective strategies to prevent water-quality impairments. At a watershed scale, the processes controlling the fate and transport of agricultural chemicals are generally understood only conceptually. To examine the applicability of conceptual models to the processes actually occurring, two precipitation-runoff models - the Soil and Water Assessment Tool (SWAT) and the Water, Energy, and Biogeochemical Model (WEBMOD) - were applied in different agricultural settings of the contiguous United States. Each model, through different physical processes, simulated the transport of water to a stream from the surface, the unsaturated zone, and the saturated zone. Models were calibrated for watersheds in Maryland, Indiana, and Nebraska. The calibrated sets of input parameters for each model at each watershed are discussed, and the criteria used to validate the models are explained. The SWAT and WEBMOD model results at each watershed conformed to each other and to the processes identified in each watershed's conceptual hydrology. In Maryland the conceptual understanding of the hydrology indicated groundwater flow was the largest annual source of streamflow; the simulation results for the validation period confirm this. The dominant source of water to the Indiana watershed was thought to be tile drains. Although tile drains were not explicitly simulated in the SWAT model, a large component of streamflow was received from lateral flow, which could be attributed to tile drains. Being able to explicitly account for tile drains, WEBMOD indicated water from tile drains constituted most of the annual streamflow in the Indiana watershed. The Nebraska models indicated annual streamflow was composed primarily of perennial groundwater flow and infiltration-excess runoff, which conformed to the conceptual hydrology developed for that watershed. The hydrologic processes represented in the parameter sets resulting from each model were comparable at individual watersheds, but varied between watersheds. The models were unable to show, however, whether hydrologic processes other than those included in the original conceptual models were major contributors to streamflow. Supplemental simulations of agricultural chemical transport could improve the ability to assess conceptual models.

Computational modeling of chemical reactions and interstitial growth and remodeling involving charged solutes and solid-bound molecules

PubMed Central

Nims, Robert J.; Maas, Steve; Weiss, Jeffrey A.

2014-01-01

Mechanobiological processes are rooted in mechanics and chemistry, and such processes may be modeled in a framework that couples their governing equations starting from fundamental principles. In many biological applications, the reactants and products of chemical reactions may be electrically charged, and these charge effects may produce driving forces and constraints that significantly influence outcomes. In this study, a novel formulation and computational implementation are presented for modeling chemical reactions in biological tissues that involve charged solutes and solid-bound molecules within a deformable porous hydrated solid matrix, coupling mechanics with chemistry while accounting for electric charges. The deposition or removal of solid-bound molecules contributes to the growth and remodeling of the solid matrix; in particular, volumetric growth may be driven by Donnan osmotic swelling, resulting from charged molecular species fixed to the solid matrix. This formulation incorporates the state of strain as a state variable in the production rate of chemical reactions, explicitly tying chemistry with mechanics for the purpose of modeling mechanobiology. To achieve these objectives, this treatment identifies the specific theoretical and computational challenges faced in modeling complex systems of interacting neutral and charged constituents while accommodating any number of simultaneous reactions where reactants and products may be modeled explicitly or implicitly. Several finite element verification problems are shown to agree with closed-form analytical solutions. An illustrative tissue engineering analysis demonstrates tissue growth and swelling resulting from the deposition of chondroitin sulfate, a charged solid-bound molecular species. This implementation is released in the open-source program FEBio (www.febio.org). The availability of this framework may be particularly beneficial to optimizing tissue engineering culture systems by examining the influence of nutrient availability on the evolution of inhomogeneous tissue composition and mechanical properties, the evolution of construct dimensions with growth, the influence of solute and solid matrix electric charge on the transport of cytokines, the influence of binding kinetics on transport, the influence of loading on binding kinetics, and the differential growth response to dynamically loaded versus free-swelling culture conditions. PMID:24558059

Computational modeling of chemical reactions and interstitial growth and remodeling involving charged solutes and solid-bound molecules.

PubMed

Ateshian, Gerard A; Nims, Robert J; Maas, Steve; Weiss, Jeffrey A

2014-10-01

Mechanobiological processes are rooted in mechanics and chemistry, and such processes may be modeled in a framework that couples their governing equations starting from fundamental principles. In many biological applications, the reactants and products of chemical reactions may be electrically charged, and these charge effects may produce driving forces and constraints that significantly influence outcomes. In this study, a novel formulation and computational implementation are presented for modeling chemical reactions in biological tissues that involve charged solutes and solid-bound molecules within a deformable porous hydrated solid matrix, coupling mechanics with chemistry while accounting for electric charges. The deposition or removal of solid-bound molecules contributes to the growth and remodeling of the solid matrix; in particular, volumetric growth may be driven by Donnan osmotic swelling, resulting from charged molecular species fixed to the solid matrix. This formulation incorporates the state of strain as a state variable in the production rate of chemical reactions, explicitly tying chemistry with mechanics for the purpose of modeling mechanobiology. To achieve these objectives, this treatment identifies the specific theoretical and computational challenges faced in modeling complex systems of interacting neutral and charged constituents while accommodating any number of simultaneous reactions where reactants and products may be modeled explicitly or implicitly. Several finite element verification problems are shown to agree with closed-form analytical solutions. An illustrative tissue engineering analysis demonstrates tissue growth and swelling resulting from the deposition of chondroitin sulfate, a charged solid-bound molecular species. This implementation is released in the open-source program FEBio ( www.febio.org ). The availability of this framework may be particularly beneficial to optimizing tissue engineering culture systems by examining the influence of nutrient availability on the evolution of inhomogeneous tissue composition and mechanical properties, the evolution of construct dimensions with growth, the influence of solute and solid matrix electric charge on the transport of cytokines, the influence of binding kinetics on transport, the influence of loading on binding kinetics, and the differential growth response to dynamically loaded versus free-swelling culture conditions.

Screening of benzamidine-based thrombin inhibitors via a linear interaction energy in continuum electrostatics model

NASA Astrophysics Data System (ADS)

Nicolotti, Orazio; Giangreco, Ilenia; Miscioscia, Teresa Fabiola; Convertino, Marino; Leonetti, Francesco; Pisani, Leonardo; Carotti, Angelo

2010-02-01

A series of 27 benzamidine inhibitors covering a wide range of biological activity and chemical diversity was analysed to derive a Linear Interaction Energy in Continuum Electrostatics (LIECE) model for analysing the thrombin inhibitory activity. The main interactions occurring at the thrombin binding site and the preferred binding conformations of inhibitors were explicitly biased by including into the LIECE model 10 compounds extracted from X-ray solved thrombin-inhibitor complexes available from the Protein Data Bank (PDB). Supported by a robust statistics ( r 2 = 0.698; q 2 = 0.662), the LIECE model was successful in predicting the inhibitory activity for about 76% of compounds ( r ext 2 ≥ 0.600) from a larger external test set encompassing 88 known thrombin inhibitors and, more importantly, in retrieving, at high sensitivity and with better performance than docking and shape-based methods, active compounds from a thrombin combinatorial library of 10240 mimetic chemical products. The herein proposed LIECE model has the potential for successfully driving the design of novel thrombin inhibitors with benzamidine and/or benzamidine-like chemical structure.

Nonadiabatic dynamics of electron transfer in solution: Explicit and implicit solvent treatments that include multiple relaxation time scales

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

Schwerdtfeger, Christine A.; Soudackov, Alexander V.; Hammes-Schiffer, Sharon, E-mail: shs3@illinois.edu

2014-01-21

The development of efficient theoretical methods for describing electron transfer (ET) reactions in condensed phases is important for a variety of chemical and biological applications. Previously, dynamical dielectric continuum theory was used to derive Langevin equations for a single collective solvent coordinate describing ET in a polar solvent. In this theory, the parameters are directly related to the physical properties of the system and can be determined from experimental data or explicit molecular dynamics simulations. Herein, we combine these Langevin equations with surface hopping nonadiabatic dynamics methods to calculate the rate constants for thermal ET reactions in polar solvents formore » a wide range of electronic couplings and reaction free energies. Comparison of explicit and implicit solvent calculations illustrates that the mapping from explicit to implicit solvent models is valid even for solvents exhibiting complex relaxation behavior with multiple relaxation time scales and a short-time inertial response. The rate constants calculated for implicit solvent models with a single solvent relaxation time scale corresponding to water, acetonitrile, and methanol agree well with analytical theories in the Golden rule and solvent-controlled regimes, as well as in the intermediate regime. The implicit solvent models with two relaxation time scales are in qualitative agreement with the analytical theories but quantitatively overestimate the rate constants compared to these theories. Analysis of these simulations elucidates the importance of multiple relaxation time scales and the inertial component of the solvent response, as well as potential shortcomings of the analytical theories based on single time scale solvent relaxation models. This implicit solvent approach will enable the simulation of a wide range of ET reactions via the stochastic dynamics of a single collective solvent coordinate with parameters that are relevant to experimentally accessible systems.« less

Covalent bonding effect on the mean excitation energy of H2 with the local plasma model

NASA Technical Reports Server (NTRS)

Kamaratos, E.

1984-01-01

Chemical bonding is taken into account explicitly in the determination of the mean excitation energy (I) for stopping power of H2 with the local plasma approximation by employing molecular electronic wave functions for H2 for the first time. This procedure leads to a new value for IH2 that is higher than all accepted experimental and theoretical values.

Source apportionment of exposures to volatile organic compounds. I. Evaluation of receptor models using simulated exposure data

NASA Astrophysics Data System (ADS)

Miller, Shelly L.; Anderson, Melissa J.; Daly, Eileen P.; Milford, Jana B.

Four receptor-oriented source apportionment models were evaluated by applying them to simulated personal exposure data for select volatile organic compounds (VOCs) that were generated by Monte Carlo sampling from known source contributions and profiles. The exposure sources modeled are environmental tobacco smoke, paint emissions, cleaning and/or pesticide products, gasoline vapors, automobile exhaust, and wastewater treatment plant emissions. The receptor models analyzed are chemical mass balance, principal component analysis/absolute principal component scores, positive matrix factorization (PMF), and graphical ratio analysis for composition estimates/source apportionment by factors with explicit restriction, incorporated in the UNMIX model. All models identified only the major contributors to total exposure concentrations. PMF extracted factor profiles that most closely represented the major sources used to generate the simulated data. None of the models were able to distinguish between sources with similar chemical profiles. Sources that contributed <5% to the average total VOC exposure were not identified.

Structure-reactivity modeling using mixture-based representation of chemical reactions.

PubMed

Polishchuk, Pavel; Madzhidov, Timur; Gimadiev, Timur; Bodrov, Andrey; Nugmanov, Ramil; Varnek, Alexandre

2017-09-01

We describe a novel approach of reaction representation as a combination of two mixtures: a mixture of reactants and a mixture of products. In turn, each mixture can be encoded using an earlier reported approach involving simplex descriptors (SiRMS). The feature vector representing these two mixtures results from either concatenated product and reactant descriptors or the difference between descriptors of products and reactants. This reaction representation doesn't need an explicit labeling of a reaction center. The rigorous "product-out" cross-validation (CV) strategy has been suggested. Unlike the naïve "reaction-out" CV approach based on a random selection of items, the proposed one provides with more realistic estimation of prediction accuracy for reactions resulting in novel products. The new methodology has been applied to model rate constants of E2 reactions. It has been demonstrated that the use of the fragment control domain applicability approach significantly increases prediction accuracy of the models. The models obtained with new "mixture" approach performed better than those required either explicit (Condensed Graph of Reaction) or implicit (reaction fingerprints) reaction center labeling.

Strengthening materials specifications

NASA Astrophysics Data System (ADS)

Sampath, K.

2005-10-01

Continuing efforts to strengthen materials specifications readily recognize that a mere compliance with a materials specification only assures a material meeting or exceeding the minimum expectations explicitly detailed in the specification. Implicitly, such efforts also recognize that additional and specific client needs must be addressed as supplementary requirements and introduced during material procurement to reduce risks and assure enhanced performance. This article describes two U.S. Navy-related case studies that allowed further strengthening of the materials specification process, using newer methods and renewed understanding. The first case demonstrates the use of a constraints-based modeling approach to specify the chemical composition of high-performance welding electrodes for critical U.S. Navy applications. This approach helps to distinguish high-performance welding electrode chemical compositions from rich and lean welding electrode chemical compositions that might limit the operational envelope, reduce performance, or both, while increasing overall cost of fabrication but otherwise meet electrode specification requirements. The second case identifies that the size of an ingot could be an important factor while specifying the aluminum and sulfur contents of very large-size, heavy-gauge plates. Renewed understanding of melt fluidity issues associated with the solidification of very large-size ingots shows that deficiencies in through-thickness ductility of heavy-gauge plates are related to controlling aluminum and sulfur contents of the voluminous melt, notwithstanding explicit compliance with specification requirements.

Brief communication: the ecosystem perspective in ecotoxicology as a way forward for the ecological risk assessment of chemicals.

PubMed

De Laender, Frederik; Janssen, Colin R

2013-07-01

One of the objectives of the European Union (EU) ecological risk assessment of chemicals (ERA) is to derive maximum environmental concentrations that are not expected to cause adverse ecological effects. To this end, related EU directives list protection goals as well as guidelines that should be used to reach these goals. It is generally accepted that the individual-level endpoints on which these guidelines are based do not correspond to the listed population- and ecosystem-level protection goals. In this article, we identify 5 research topics that are key to bridging this gap: 1) the refinement of population-level effects and recovery rates by explicitly taking into account competition and 2) predation, 3) the assessment of chemical effects on biodiversity, 4) the assessment of chemical stress on ecosystem functions and services, and 5) the quantification of the effects of chemical mixtures. In addition, we illustrate why an ecosystem perspective is needed to address these topics and to inform the risk assessment process. We propose the use of existing ecotoxicological community, food web, and ecosystem models to tackle these issues and discuss why new models are needed to predict chemical effects on biodiversity. Copyright © 2013 SETAC.

Evaluation of New and Proposed Organic Aerosol Sources and Mechanisms using the Aerosol Modeling Testbed. MILAGRO, CARES, CalNex, BEACHON, and GVAX

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

Hodzic, Alma; Jimenez, Jose L.

2015-04-09

This work investigated the formation and evolution of organic aerosols (OA) arising from anthropogenic and biogenic sources in a framework that combined state-of-the-science process and regional modeling, and their evaluation against advanced and emerging field measurements. Although OA are the dominant constituents of submicron particles, our understanding of their atmospheric lifecycle is limited, and current models fail to describe the observed amounts and properties of chemically formed secondary organic aerosols (SOA), leaving large uncertainties on the effects of SOA on climate. Our work has provided novel modeling constraints on sources, formation, aging and removal of SOA by investigating in particularmore » (i) the contribution of trash burning emissions to OA levels in a megacity, (ii) the contribution of glyoxal to SOA formation in aqueous particles in California during CARES/CalNex and over the continental U.S., (iii) SOA formation and regional growth over a pine forest in Colorado and its sensitivity to anthropogenic NOx levels during BEACHON, and the sensitivity of SOA to (iv) the sunlight exposure during its atmospheric lifetime, and to (v) changes in solubility and removal of organic vapors in the urban plume (MILAGRO, Mexico City), and over the continental U.S.. We have also developed a parameterization of water solubility for condensable organic gases produced from major anthropogenic and biogenic precursors based on explicit chemical modeling, and made it available to the wider community. This work used for the first time constraints from the explicit model GECKO-A to improve SOA representation in 3D regional models such as WRF-Chem.« less

Adaptive Sampling using Support Vector Machines

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

D. Mandelli; C. Smith

2012-11-01

Reliability/safety analysis of stochastic dynamic systems (e.g., nuclear power plants, airplanes, chemical plants) is currently performed through a combination of Event-Tress and Fault-Trees. However, these conventional methods suffer from certain drawbacks: • Timing of events is not explicitly modeled • Ordering of events is preset by the analyst • The modeling of complex accident scenarios is driven by expert-judgment For these reasons, there is currently an increasing interest into the development of dynamic PRA methodologies since they can be used to address the deficiencies of conventional methods listed above.

Toward refined environmental scenarios for ecological risk assessment of down-the-drain chemicals in freshwater environments.

PubMed

Franco, Antonio; Price, Oliver R; Marshall, Stuart; Jolliet, Olivier; Van den Brink, Paul J; Rico, Andreu; Focks, Andreas; De Laender, Frederik; Ashauer, Roman

2017-03-01

Current regulatory practice for chemical risk assessment suffers from the lack of realism in conventional frameworks. Despite significant advances in exposure and ecological effect modeling, the implementation of novel approaches as high-tier options for prospective regulatory risk assessment remains limited, particularly among general chemicals such as down-the-drain ingredients. While reviewing the current state of the art in environmental exposure and ecological effect modeling, we propose a scenario-based framework that enables a better integration of exposure and effect assessments in a tiered approach. Global- to catchment-scale spatially explicit exposure models can be used to identify areas of higher exposure and to generate ecologically relevant exposure information for input into effect models. Numerous examples of mechanistic ecological effect models demonstrate that it is technically feasible to extrapolate from individual-level effects to effects at higher levels of biological organization and from laboratory to environmental conditions. However, the data required to parameterize effect models that can embrace the complexity of ecosystems are large and require a targeted approach. Experimental efforts should, therefore, focus on vulnerable species and/or traits and ecological conditions of relevance. We outline key research needs to address the challenges that currently hinder the practical application of advanced model-based approaches to risk assessment of down-the-drain chemicals. Integr Environ Assess Manag 2017;13:233-248. © 2016 SETAC. © 2016 SETAC.

Advancing environmental toxicology through chemical dosimetry: External exposures versus tissue residues

USGS Publications Warehouse

McCarty, L.S.; Landrum, P.F.; Luoma, S.N.; Meador, J.P.; Merten, A.A.; Shephard, B.K.; van Wezelzz, A.P.

2011-01-01

The tissue residue dose concept has been used, although in a limited manner, in environmental toxicology for more than 100 y. This review outlines the history of this approach and the technical background for organic chemicals and metals. Although the toxicity of both can be explained in tissue residue terms, the relationship between external exposure concentration, body and/or tissues dose surrogates, and the effective internal dose at the sites of toxic action tends to be more complex for metals. Various issues and current limitations related to research and regulatory applications are also examined. It is clear that the tissue residue approach (TRA) should be an integral component in future efforts to enhance the generation, understanding, and utility of toxicity testing data, both in the laboratory and in the field. To accomplish these goals, several key areas need to be addressed: 1) development of a risk-based interpretive framework linking toxicology and ecology at multiple levels of biological organization and incorporating organism-based dose metrics; 2) a broadly applicable, generally accepted classification scheme for modes/mechanisms of toxic action with explicit consideration of residue information to improve both single chemical and mixture toxicity data interpretation and regulatory risk assessment; 3) toxicity testing protocols updated to ensure collection of adequate residue information, along with toxicokinetics and toxicodynamics information, based on explicitly defined toxicological models accompanied by toxicological model validation; 4) continued development of residueeffect databases is needed ensure their ongoing utility; and 5) regulatory guidance incorporating residue-based testing and interpretation approaches, essential in various jurisdictions. ??:2010 SETAC.

Reactive Radial Diffusion Model for the Aging/Sequestration Process

NASA Astrophysics Data System (ADS)

Ginn, T. R.; Basagaoglu, H.; McCoy, B. J.; Scow, K. M.

2001-12-01

A radial diffusion model has been formulated to simulate age-dependent bioavailability of chemical compounds to micro-organisms residing outside (and/or inside) the porous soil particles. Experimental findings in the literature indicate that the sequestration and reduction in bioavailability of contaminants are controlled presumably by the diffusion-limited sorption kinetics and the time-variant desorption process. Here we combine radial-diffusion mass transfer modeling with the exposure-time concept to generate mass-balance equations for the intra- and extra-particle concentrations. The model accomodates reversible sorption kinetics involving sorption time-dependence of the rate coefficients, distinct intra- and extra-particle biodegradation rates; and a dynamic mass interaction between the intra- and extra-particle concentrations arising from the radial diffusion concept. The model explicitly treats multiple particle classes distributed in size and chemical properties in a bulk aquifer or soil volume, which allows the simulation of the sequestration and bioavailability of contaminants in different particle size classes that have distinct diffusion, reaction, and aging properties.

Surveying implicit solvent models for estimating small molecule absolute hydration free energies

PubMed Central

Knight, Jennifer L.

2011-01-01

Implicit solvent models are powerful tools in accounting for the aqueous environment at a fraction of the computational expense of explicit solvent representations. Here, we compare the ability of common implicit solvent models (TC, OBC, OBC2, GBMV, GBMV2, GBSW, GBSW/MS, GBSW/MS2 and FACTS) to reproduce experimental absolute hydration free energies for a series of 499 small neutral molecules that are modeled using AMBER/GAFF parameters and AM1-BCC charges. Given optimized surface tension coefficients for scaling the surface area term in the nonpolar contribution, most implicit solvent models demonstrate reasonable agreement with extensive explicit solvent simulations (average difference 1.0-1.7 kcal/mol and R2=0.81-0.91) and with experimental hydration free energies (average unsigned errors=1.1-1.4 kcal/mol and R2=0.66-0.81). Chemical classes of compounds are identified that need further optimization of their ligand force field parameters and others that require improvement in the physical parameters of the implicit solvent models themselves. More sophisticated nonpolar models are also likely necessary to more effectively represent the underlying physics of solvation and take the quality of hydration free energies estimated from implicit solvent models to the next level. PMID:21735452

Validating spatiotemporal predictions of an important pest of small grains.

PubMed

Merrill, Scott C; Holtzer, Thomas O; Peairs, Frank B; Lester, Philip J

2015-01-01

Arthropod pests are typically managed using tactics applied uniformly to the whole field. Precision pest management applies tactics under the assumption that within-field pest pressure differences exist. This approach allows for more precise and judicious use of scouting resources and management tactics. For example, a portion of a field delineated as attractive to pests may be selected to receive extra monitoring attention. Likely because of the high variability in pest dynamics, little attention has been given to developing precision pest prediction models. Here, multimodel synthesis was used to develop a spatiotemporal model predicting the density of a key pest of wheat, the Russian wheat aphid, Diuraphis noxia (Kurdjumov). Spatially implicit and spatially explicit models were synthesized to generate spatiotemporal pest pressure predictions. Cross-validation and field validation were used to confirm model efficacy. A strong within-field signal depicting aphid density was confirmed with low prediction errors. Results show that the within-field model predictions will provide higher-quality information than would be provided by traditional field scouting. With improvements to the broad-scale model component, the model synthesis approach and resulting tool could improve pest management strategy and provide a template for the development of spatially explicit pest pressure models. © 2014 Society of Chemical Industry.

Probing the free energy landscape of the FBP28WW domain using multiple techniques.

PubMed

Periole, Xavier; Allen, Lucy R; Tamiola, Kamil; Mark, Alan E; Paci, Emanuele

2009-05-01

The free-energy landscape of a small protein, the FBP 28 WW domain, has been explored using molecular dynamics (MD) simulations with alternative descriptions of the molecule. The molecular models used range from coarse-grained to all-atom with either an implicit or explicit treatment of the solvent. Sampling of conformation space was performed using both conventional and temperature-replica exchange MD simulations. Experimental chemical shifts and NOEs were used to validate the simulations, and experimental phi values both for validation and as restraints. This combination of different approaches has provided insight into the free energy landscape and barriers encountered by the protein during folding and enabled the characterization of native, denatured and transition states which are compatible with the available experimental data. All the molecular models used stabilize well defined native and denatured basins; however, the degree of agreement with the available experimental data varies. While the most detailed, explicit solvent model predicts the data reasonably accurately, it does not fold despite a simulation time 10 times that of the experimental folding time. The less detailed models performed poorly relative to the explicit solvent model: an implicit solvent model stabilizes a ground state which differs from the experimental native state, and a structure-based model underestimates the size of the barrier between the two states. The use of experimental phi values both as restraints, and to extract structures from unfolding simulations, result in conformations which, although not necessarily true transition states, appear to share the geometrical characteristics of transition state structures. In addition to characterizing the native, transition and denatured states of this particular system in this work, the advantages and limitations of using varying levels of representation are discussed. 2008 Wiley Periodicals, Inc.

GIAO-DFT calculation of 15 N NMR chemical shifts of Schiff bases: Accuracy factors and protonation effects.

PubMed

Semenov, Valentin A; Samultsev, Dmitry O; Krivdin, Leonid B

2018-02-09

15 N NMR chemical shifts in the representative series of Schiff bases together with their protonated forms have been calculated at the density functional theory level in comparison with available experiment. A number of functionals and basis sets have been tested in terms of a better agreement with experiment. Complimentary to gas phase results, 2 solvation models, namely, a classical Tomasi's polarizable continuum model (PCM) and that in combination with an explicit inclusion of one molecule of solvent into calculation space to form supermolecule 1:1 (SM + PCM), were examined. Best results are achieved with PCM and SM + PCM models resulting in mean absolute errors of calculated 15 N NMR chemical shifts in the whole series of neutral and protonated Schiff bases of accordingly 5.2 and 5.8 ppm as compared with 15.2 ppm in gas phase for the range of about 200 ppm. Noticeable protonation effects (exceeding 100 ppm) in protonated Schiff bases are rationalized in terms of a general natural bond orbital approach. Copyright © 2018 John Wiley & Sons, Ltd.

The Paleoclimate Uncertainty Cascade: Tracking Proxy Errors Via Proxy System Models.

NASA Astrophysics Data System (ADS)

Emile-Geay, J.; Dee, S. G.; Evans, M. N.; Adkins, J. F.

2014-12-01

Paleoclimatic observations are, by nature, imperfect recorders of climate variables. Empirical approaches to their calibration are challenged by the presence of multiple sources of uncertainty, which may confound the interpretation of signals and the identifiability of the noise. In this talk, I will demonstrate the utility of proxy system models (PSMs, Evans et al, 2013, 10.1016/j.quascirev.2013.05.024) to quantify the impact of all known sources of uncertainty. PSMs explicitly encode the mechanistic knowledge of the physical, chemical, biological and geological processes from which paleoclimatic observations arise. PSMs may be divided into sensor, archive and observation components, all of which may conspire to obscure climate signals in actual paleo-observations. As an example, we couple a PSM for the δ18O of speleothem calcite to an isotope-enabled climate model (Dee et al, submitted) to analyze the potential of this measurement as a proxy for precipitation amount. A simple soil/karst model (Partin et al, 2013, 10.1130/G34718.1) is used as sensor model, while a hiatus-permitting chronological model (Haslett & Parnell, 2008, 10.1111/j.1467-9876.2008.00623.x) is used as part of the observation model. This subdivision allows us to explicitly model the transformation from precipitation amount to speleothem calcite δ18O as a multi-stage process via a physical and chemical sensor model, and a stochastic archive model. By illustrating the PSM's behavior within the context of the climate simulations, we show how estimates of climate variability may be affected by each submodel's transformation of the signal. By specifying idealized climate signals(periodic vs. episodic, slow vs. fast) to the PSM, we investigate how frequency and amplitude patterns are modulated by sensor and archive submodels. To the extent that the PSM and the climate models are representative of real world processes, then the results may help us more accurately interpret existing paleodata, characterize their uncertainties, and design sampling strategies that exploit their strengths while mitigating their weaknesses.

Cluster-Continuum Calculations of Hydration Free Energies of Anions and Group 12 Divalent Cations.

PubMed

Riccardi, Demian; Guo, Hao-Bo; Parks, Jerry M; Gu, Baohua; Liang, Liyuan; Smith, Jeremy C

2013-01-08

Understanding aqueous phase processes involving group 12 metal cations is relevant to both environmental and biological sciences. Here, quantum chemical methods and polarizable continuum models are used to compute the hydration free energies of a series of divalent group 12 metal cations (Zn(2+), Cd(2+), and Hg(2+)) together with Cu(2+) and the anions OH(-), SH(-), Cl(-), and F(-). A cluster-continuum method is employed, in which gas-phase clusters of the ion and explicit solvent molecules are immersed in a dielectric continuum. Two approaches to define the size of the solute-water cluster are compared, in which the number of explicit waters used is either held constant or determined variationally as that of the most favorable hydration free energy. Results obtained with various polarizable continuum models are also presented. Each leg of the relevant thermodynamic cycle is analyzed in detail to determine how different terms contribute to the observed mean signed error (MSE) and the standard deviation of the error (STDEV) between theory and experiment. The use of a constant number of water molecules for each set of ions is found to lead to predicted relative trends that benefit from error cancellation. Overall, the best results are obtained with MP2 and the Solvent Model D polarizable continuum model (SMD), with eight explicit water molecules for anions and 10 for the metal cations, yielding a STDEV of 2.3 kcal mol(-1) and MSE of 0.9 kcal mol(-1) between theoretical and experimental hydration free energies, which range from -72.4 kcal mol(-1) for SH(-) to -505.9 kcal mol(-1) for Cu(2+). Using B3PW91 with DFT-D3 dispersion corrections (B3PW91-D) and SMD yields a STDEV of 3.3 kcal mol(-1) and MSE of 1.6 kcal mol(-1), to which adding MP2 corrections from smaller divalent metal cation water molecule clusters yields very good agreement with the full MP2 results. Using B3PW91-D and SMD, with two explicit water molecules for anions and six for divalent metal cations, also yields reasonable agreement with experimental values, due in part to fortuitous error cancellation associated with the metal cations. Overall, the results indicate that the careful application of quantum chemical cluster-continuum methods provides valuable insight into aqueous ionic processes that depend on both local and long-range electrostatic interactions with the solvent.

First-Principles Molecular Dynamics Studies of Organometallic Complexes and Homogeneous Catalytic Processes.

PubMed

Vidossich, Pietro; Lledós, Agustí; Ujaque, Gregori

2016-06-21

Computational chemistry is a valuable aid to complement experimental studies of organometallic systems and their reactivity. It allows probing mechanistic hypotheses and investigating molecular structures, shedding light on the behavior and properties of molecular assemblies at the atomic scale. When approaching a chemical problem, the computational chemist has to decide on the theoretical approach needed to describe electron/nuclear interactions and the composition of the model used to approximate the actual system. Both factors determine the reliability of the modeling study. The community dedicated much effort to developing and improving the performance and accuracy of theoretical approaches for electronic structure calculations, on which the description of (inter)atomic interactions rely. Here, the importance of the model system used in computational studies is highlighted through examples from our recent research focused on organometallic systems and homogeneous catalytic processes. We show how the inclusion of explicit solvent allows the characterization of molecular events that would otherwise not be accessible in reduced model systems (clusters). These include the stabilization of nascent charged fragments via microscopic solvation (notably, hydrogen bonding), transfer of charge (protons) between distant fragments mediated by solvent molecules, and solvent coordination to unsaturated metal centers. Furthermore, when weak interactions are involved, we show how conformational and solvation properties of organometallic complexes are also affected by the explicit inclusion of solvent molecules. Such extended model systems may be treated under periodic boundary conditions, thus removing the cluster/continuum (or vacuum) boundary, and require a statistical mechanics simulation technique to sample the accessible configurational space. First-principles molecular dynamics, in which atomic forces are computed from electronic structure calculations (namely, density functional theory), is certainly the technique of choice to investigate chemical events in solution. This methodology is well established and thanks to advances in both algorithms and computational resources simulation times required for the modeling of chemical events are nowadays accessible, though the computational requirements use to be high. Specific applications reviewed here include mechanistic studies of the Shilov and Wacker processes, speciation in Pd chemistry, hydrogen bonding to metal centers, and the dynamics of agostic interactions.

A new solution method for wheel/rail rolling contact.

PubMed

Yang, Jian; Song, Hua; Fu, Lihua; Wang, Meng; Li, Wei

2016-01-01

To solve the problem of wheel/rail rolling contact of nonlinear steady-state curving, a three-dimensional transient finite element (FE) model is developed by the explicit software ANSYS/LS-DYNA. To improve the solving speed and efficiency, an explicit-explicit order solution method is put forward based on analysis of the features of implicit and explicit algorithm. The solution method was first applied to calculate the pre-loading of wheel/rail rolling contact with explicit algorithm, and then the results became the initial conditions in solving the dynamic process of wheel/rail rolling contact with explicit algorithm as well. Simultaneously, the common implicit-explicit order solution method is used to solve the FE model. Results show that the explicit-explicit order solution method has faster operation speed and higher efficiency than the implicit-explicit order solution method while the solution accuracy is almost the same. Hence, the explicit-explicit order solution method is more suitable for the wheel/rail rolling contact model with large scale and high nonlinearity.

Transported PDF Modeling of Nonpremixed Turbulent CO/H-2/N-2 Jet Flames

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

Zhao, xinyu; Haworth, D. C.; Huckaby, E. David

2012-01-01

Turbulent CO/H{sub 2}/N{sub 2} (“syngas”) flames are simulated using a transported composition probability density function (PDF) method. A consistent hybrid Lagrangian particle/Eulerian mesh algorithm is used to solve the modeled PDF transport equation. The model includes standard k–ϵ turbulence, gradient transport for scalars, and Euclidean minimum spanning tree (EMST) mixing. Sensitivities of model results to variations in the turbulence model, the treatment of radiation heat transfer, the choice of chemical mechanism, and the PDF mixing model are explored. A baseline model reproduces the measured mean and rms temperature, major species, and minor species profiles reasonably well, and captures the scalingmore » that is observed in the experiments. Both our results and the literature suggest that further improvements can be realized with adjustments in the turbulence model, the radiation heat transfer model, and the chemical mechanism. Although radiation effects are relatively small in these flames, consideration of radiation is important for accurate NO prediction. Chemical mechanisms that have been developed specifically for fuels with high concentrations of CO and H{sub 2} perform better than a methane mechanism that was not designed for this purpose. It is important to account explicitly for turbulence–chemistry interactions, although the details of the mixing model do not make a large difference in the results, within reasonable limits.« less

A three-dimensional method-of-characteristics solute-transport model (MOC3D)

USGS Publications Warehouse

Konikow, Leonard F.; Goode, D.J.; Hornberger, G.Z.

1996-01-01

This report presents a model, MOC3D, that simulates three-dimensional solute transport in flowing ground water. The model computes changes in concentration of a single dissolved chemical constituent over time that are caused by advective transport, hydrodynamic dispersion (including both mechanical dispersion and diffusion), mixing (or dilution) from fluid sources, and mathematically simple chemical reactions (including linear sorption, which is represented by a retardation factor, and decay). The transport model is integrated with MODFLOW, a three-dimensional ground-water flow model that uses implicit finite-difference methods to solve the transient flow equation. MOC3D uses the method of characteristics to solve the transport equation on the basis of the hydraulic gradients computed with MODFLOW for a given time step. This implementation of the method of characteristics uses particle tracking to represent advective transport and explicit finite-difference methods to calculate the effects of other processes. However, the explicit procedure has several stability criteria that may limit the size of time increments for solving the transport equation; these are automatically determined by the program. For improved efficiency, the user can apply MOC3D to a subgrid of the primary MODFLOW grid that is used to solve the flow equation. However, the transport subgrid must have uniform grid spacing along rows and columns. The report includes a description of the theoretical basis of the model, a detailed description of input requirements and output options, and the results of model testing and evaluation. The model was evaluated for several problems for which exact analytical solutions are available and by benchmarking against other numerical codes for selected complex problems for which no exact solutions are available. These test results indicate that the model is very accurate for a wide range of conditions and yields minimal numerical dispersion for advection-dominated problems. Mass-balance errors are generally less than 10 percent, and tend to decrease and stabilize with time.

Chemical-Specific Representation of Air-Soil Exchange and Soil Penetration in Regional Multimedia Models

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

McKone, T.E.; Bennett, D.H.

2002-08-01

In multimedia mass-balance models, the soil compartment is an important sink as well as a conduit for transfers to vegetation and shallow groundwater. Here a novel approach for constructing soil transport algorithms for multimedia fate models is developed and evaluated. The resulting algorithms account for diffusion in gas and liquid components; advection in gas, liquid, or solid phases; and multiple transformation processes. They also provide an explicit quantification of the characteristic soil penetration depth. We construct a compartment model using three and four soil layers to replicate with high reliability the flux and mass distribution obtained from the exact analyticalmore » solution describing the transient dispersion, advection, and transformation of chemicals in soil with fixed properties and boundary conditions. Unlike the analytical solution, which requires fixed boundary conditions, the soil compartment algorithms can be dynamically linked to other compartments (air, vegetation, ground water, surface water) in multimedia fate models. We demonstrate and evaluate the performance of the algorithms in a model with applications to benzene, benzo(a)pyrene, MTBE, TCDD, and tritium.« less

Development of Comprehensive Reduced Kinetic Models for Supersonic Reacting Shear Layer Simulations

NASA Technical Reports Server (NTRS)

Zambon, A. C.; Chelliah, H. K.; Drummond, J. P.

2006-01-01

Large-scale simulations of multi-dimensional unsteady turbulent reacting flows with detailed chemistry and transport can be computationally extremely intensive even on distributed computing architectures. With the development of suitable reduced chemical kinetic models, the number of scalar variables to be integrated can be decreased, leading to a significant reduction in the computational time required for the simulation with limited loss of accuracy in the results. A general MATLAB-based automated mechanism reduction procedure is presented to reduce any complex starting mechanism (detailed or skeletal) with minimal human intervention. Based on the application of the quasi steady-state (QSS) approximation for certain chemical species and on the elimination of the fast reaction rates in the mechanism, several comprehensive reduced models, capable of handling different fuels such as C2H4, CH4 and H2, have been developed and thoroughly tested for several combustion problems (ignition, propagation and extinction) and physical conditions (reactant compositions, temperatures, and pressures). A key feature of the present reduction procedure is the explicit solution of the concentrations of the QSS species, needed for the evaluation of the elementary reaction rates. In contrast, previous approaches relied on an implicit solution due to the strong coupling between QSS species, requiring computationally expensive inner iterations. A novel algorithm, based on the definition of a QSS species coupling matrix, is presented to (i) introduce appropriate truncations to the QSS algebraic relations and (ii) identify the optimal sequence for the explicit solution of the concentration of the QSS species. With the automatic generation of the relevant source code, the resulting reduced models can be readily implemented into numerical codes.

Isoprene derived secondary organic aerosol in a global aerosol chemistry climate model

NASA Astrophysics Data System (ADS)

Stadtler, Scarlet; Kühn, Thomas; Taraborrelli, Domenico; Kokkola, Harri; Schultz, Martin

2017-04-01

Secondary organic aerosol (SOA) impacts earth's climate and human health. Since its precursor chemistry and its formation are not fully understood, climate models cannot catch its direct and indirect effects. Global isoprene emissions are higher than any other non-methane hydrocarbons. Therefore, SOA from isoprene-derived, low volatile species (iSOA) is simulated using a global aerosol chemistry climate model ECHAM6-HAM-SALSA-MOZ. Isoprene oxidation in the chemistry model MOZ is following a novel semi-explicit scheme, embedded in a detailed atmospheric chemical mechanism. For iSOA formation four low volatile isoprene oxidation products were identified. The group method by Nanoonlal et al. 2008 was used to estimate their evaporation enthalpies ΔHvap. To calculate the saturation concentration C∗(T) the sectional aerosol model SALSA uses the gas phase concentrations simulated by MOZ and their corresponding ΔHvap to obtain the saturation vapor pressure p∗(T) from the Clausius Clapeyron equation. Subsequently, the saturation concentration is used to calculate the explicit kinetic partitioning of these compounds forming iSOA. Furthermore, the irreversible heterogeneous reactions of IEPOX and glyoxal from isoprene were included. The possibility of reversible heterogeneous uptake was ignored at this stage, leading to an upper estimate of the contribution of glyoxal to iSOA mass.

Modeling the partitioning of organic chemical species in cloud phases with CLEPS (1.1)

NASA Astrophysics Data System (ADS)

Rose, Clémence; Chaumerliac, Nadine; Deguillaume, Laurent; Perroux, Hélène; Mouchel-Vallon, Camille; Leriche, Maud; Patryl, Luc; Armand, Patrick

2018-02-01

The new detailed aqueous-phase mechanism Cloud Explicit Physico-chemical Scheme (CLEPS 1.0), which describes the oxidation of isoprene-derived water-soluble organic compounds, is coupled with a warm microphysical module simulating the activation of aerosol particles into cloud droplets. CLEPS 1.0 was then extended to CLEPS 1.1 to include the chemistry of the newly added dicarboxylic acids dissolved from the particulate phase. The resulting coupled model allows the prediction of the aqueous-phase concentrations of chemical compounds originating from particle scavenging, mass transfer from the gas-phase and in-cloud aqueous chemical reactivity. The aim of the present study was more particularly to investigate the effect of particle scavenging on cloud chemistry. Several simulations were performed to assess the influence of various parameters on model predictions and to interpret long-term measurements conducted at the top of Puy de Dôme (PUY, France) in marine air masses. Specific attention was paid to carboxylic acids, whose predicted concentrations are on average in the lower range of the observations, with the exception of formic acid, which is rather overestimated in the model. The different sensitivity runs highlight the fact that formic and acetic acids mainly originate from the gas phase and have highly variable aqueous-phase reactivity depending on the cloud acidity, whereas C3-C4 carboxylic acids mainly originate from the particulate phase and are supersaturated in the cloud.

Evaluation of unsaturated-zone solute-transport models for studies of agricultural chemicals

USGS Publications Warehouse

Nolan, Bernard T.; Bayless, E. Randall; Green, Christopher T.; Garg, Sheena; Voss, Frank D.; Lampe, David C.; Barbash, Jack E.; Capel, Paul D.; Bekins, Barbara A.

2005-01-01

Of the models tested, RZWQM, HYDRUS2D, VS2DT, GLEAMS and PRZM had graphical user interfaces. Extensive documentation was available for RZWQM, HYDRUS2D, and VS2DT. RZWQM can explicitly simulate water and solute flux in macropores, and both HYDRUS2D and VS2DT can simulate water and solute flux in two dimensions. The version of RZWQM tested had a maximum simulation depth of 3 meters. The complex models simulate the formation, transport, and fate of degradates of up to three to five compounds including the parent, with the exception of VS2DT, which simulates the transport and fate of a single compound.

Computational assignment of redox states to Coulomb blockade diamonds.

PubMed

Olsen, Stine T; Arcisauskaite, Vaida; Hansen, Thorsten; Kongsted, Jacob; Mikkelsen, Kurt V

2014-09-07

With the advent of molecular transistors, electrochemistry can now be studied at the single-molecule level. Experimentally, the redox chemistry of the molecule manifests itself as features in the observed Coulomb blockade diamonds. We present a simple theoretical method for explicit construction of the Coulomb blockade diamonds of a molecule. A combined quantum mechanical/molecular mechanical method is invoked to calculate redox energies and polarizabilities of the molecules, including the screening effect of the metal leads. This direct approach circumvents the need for explicit modelling of the gate electrode. From the calculated parameters the Coulomb blockade diamonds are constructed using simple theory. We offer a theoretical tool for assignment of Coulomb blockade diamonds to specific redox states in particular, and a study of chemical details in the diamonds in general. With the ongoing experimental developments in molecular transistor experiments, our tool could find use in molecular electronics, electrochemistry, and electrocatalysis.

Kinetic Monte Carlo Method for Rule-based Modeling of Biochemical Networks

PubMed Central

Yang, Jin; Monine, Michael I.; Faeder, James R.; Hlavacek, William S.

2009-01-01

We present a kinetic Monte Carlo method for simulating chemical transformations specified by reaction rules, which can be viewed as generators of chemical reactions, or equivalently, definitions of reaction classes. A rule identifies the molecular components involved in a transformation, how these components change, conditions that affect whether a transformation occurs, and a rate law. The computational cost of the method, unlike conventional simulation approaches, is independent of the number of possible reactions, which need not be specified in advance or explicitly generated in a simulation. To demonstrate the method, we apply it to study the kinetics of multivalent ligand-receptor interactions. We expect the method will be useful for studying cellular signaling systems and other physical systems involving aggregation phenomena. PMID:18851068

Coupling microscopic and mesoscopic scales to simulate chemical equilibrium between a nanometric carbon cluster and detonation products fluid.

PubMed

Bourasseau, Emeric; Maillet, Jean-Bernard

2011-04-21

This paper presents a new method to obtain chemical equilibrium properties of detonation products mixtures including a solid carbon phase. In this work, the solid phase is modelled through a mesoparticle immersed in the fluid, such that the heterogeneous character of the mixture is explicitly taken into account. Inner properties of the clusters are taken from an equation of state obtained in a previous work, and interaction potential between the nanocluster and the fluid particles is derived from all-atoms simulations using the LCBOPII potential (Long range Carbon Bond Order Potential II). It appears that differences in chemical equilibrium results obtained with this method and the "composite ensemble method" (A. Hervouet et al., J. Phys. Chem. B, 2008, 112.), where fluid and solid phases are considered as non-interacting, are not significant, underlining the fact that considering the inhomogeneity of such system is crucial.

User`s guide for UTCHEM-5.32m a three dimensional chemical flood simulator. Final report, September 30, 1992--December 31, 1995

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

NONE

1996-07-01

UTCHEM is a three-dimensional chemical flooding simulator. The solution scheme is analogous to IMPES, where pressure is solved for implicitly, but concentrations rather than saturations are then solved for explicitly. Phase saturations and concentrations are then solved in a flash routine. An energy balance equation is solved explicitly for reservoir temperature. The energy balance equation includes heat flow between the reservoir and the over-and under-burden rocks. The major physical phenomena modeled in the simulator are: dispersion; dilution effects; adsorption; interfacial tension; relative permeability; capillary trapping; cation exchange; phase density; compositional phase viscosity; phase behavior (pseudoquaternary); aqueous reactions; partitioning of chemicalmore » species between oil and water; dissolution/precipitation; cation exchange reactions involving more than two cations; in-situ generation of surfactant from acidic crude oil; pH dependent adsorption; polymer properties: shear thinning viscosity; inaccessible pore volume; permeability reduction; adsorption; gel properties: viscosity; permeability reduction; adsorption; tracer properties: partitioning; adsorption; radioactive decay; reaction (ester hydrolization); temperature dependent properties: viscosity; tracer reaction; gel reactions The following options are available with UTCHEM: isothermal or non-isothermal conditions, a constant or variable time-step, constant pressure or constant rate well conditions, horizontal and vertical wells, and a radial or Cartesian geometry. Please refer to the dissertation {open_quotes}Field Scale Simulation of Chemical Flooding{close_quotes} by Naji Saad, August, 1989, for a more detailed discussion of the UTCHEM simulator and its formulation.« less

Assessing Uncertainty in the Toxicology of PFOA

EPA Science Inventory

We use an approach known as Bayesian statistics to characterize our knowledge about the behavior of a chemical prior to an experiment and make explicit our assumptions about how we think the chemical behaves. When we then analyze the results of an experiment, we determine probab...

CKow -- A More Transparent and Reliable Model for Chemical Transfer to Meat and Milk

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

Rosenbaum, Ralph K.; McKone, Thomas E.; Jolliet, Olivier

The objective of this study is to increase the understanding and transparency of chemical biotransfer modeling into meat and milk and explicitly confront the uncertainties in exposure assessments of chemicals that require such estimates. In cumulative exposure assessments that include food pathways, much of the overall uncertainty is attributable to the estimation of transfer into biota and through food webs. Currently, the most commonly used meat and milk-biotransfer models date back two decades and, in spite of their widespread use in multimedia exposure models few attempts have been made to advance or improve the outdated and highly uncertain Kow regressionsmore » used in these models. Furthermore, in the range of Kow where meat and milk become the dominant human exposure pathways, these models often provide unrealistic rates and do not reflect properly the transfer dynamics. To address these issues, we developed a dynamic three-compartment cow model (called CKow), distinguishing lactating and non-lactating cows. For chemicals without available overall removal rates in the cow, a correlation is derived from measured values reported in the literature to predict this parameter from Kow. Results on carry over rates (COR) and biotransfer factors (BTF) demonstrate that a steady-state ratio between animal intake and meat concentrations is almost never reached. For meat, empirical data collected on short term experiments need to be adjusted to provide estimates of average longer term behaviors. The performance of the new model in matching measurements is improved relative to existing models--thus reducing uncertainty. The CKow model is straight forward to apply at steady state for milk and dynamically for realistic exposure durations for meat COR.« less

Alchemical and structural distribution based representation for universal quantum machine learning

NASA Astrophysics Data System (ADS)

Faber, Felix A.; Christensen, Anders S.; Huang, Bing; von Lilienfeld, O. Anatole

2018-06-01

We introduce a representation of any atom in any chemical environment for the automatized generation of universal kernel ridge regression-based quantum machine learning (QML) models of electronic properties, trained throughout chemical compound space. The representation is based on Gaussian distribution functions, scaled by power laws and explicitly accounting for structural as well as elemental degrees of freedom. The elemental components help us to lower the QML model's learning curve, and, through interpolation across the periodic table, even enable "alchemical extrapolation" to covalent bonding between elements not part of training. This point is demonstrated for the prediction of covalent binding in single, double, and triple bonds among main-group elements as well as for atomization energies in organic molecules. We present numerical evidence that resulting QML energy models, after training on a few thousand random training instances, reach chemical accuracy for out-of-sample compounds. Compound datasets studied include thousands of structurally and compositionally diverse organic molecules, non-covalently bonded protein side-chains, (H2O)40-clusters, and crystalline solids. Learning curves for QML models also indicate competitive predictive power for various other electronic ground state properties of organic molecules, calculated with hybrid density functional theory, including polarizability, heat-capacity, HOMO-LUMO eigenvalues and gap, zero point vibrational energy, dipole moment, and highest vibrational fundamental frequency.

Ozone formation during an episode over Europe: A 3-D chemical/transport model simulation

NASA Technical Reports Server (NTRS)

Berntsen, Terje; Isaksen, Ivar S. A.

1994-01-01

A 3-D regional photochemical tracer/transport model for Europe and the Eastern Atlantic has been developed based on the NASA/GISS CTM. The model resolution is 4x5 degrees latitude and longitude with 9 layers in the vertical (7 in the troposphere). Advective winds, convection statistics and other meteorological data from the NASA/GISS GCM are used. An extensive gas-phase chemical scheme based on the scheme used in our global 2D model has been incorporated in the 3D model. In this work ozone formation in the troposphere is studied with the 3D model during a 5 day period starting June 30. Extensive local ozone production is found and the relationship between the source regions and the downwind areas are discussed. Variations in local ozone formation as a function of total emission rate, as well as the composition of the emissions (HC/NO(x)) ratio and isoprene emissions) are elucidated. An important vertical transport process in the troposphere is by convective clouds. The 3D model includes an explicit parameterization of this process. It is shown that this process has significant influence on the calculated surface ozone concentrations.

A comparison of three-dimensional nonequilibrium solution algorithms applied to hypersonic flows with stiff chemical source terms

NASA Technical Reports Server (NTRS)

Palmer, Grant; Venkatapathy, Ethiraj

1993-01-01

Three solution algorithms, explicit underrelaxation, point implicit, and lower upper symmetric Gauss-Seidel (LUSGS), are used to compute nonequilibrium flow around the Apollo 4 return capsule at 62 km altitude. By varying the Mach number, the efficiency and robustness of the solution algorithms were tested for different levels of chemical stiffness. The performance of the solution algorithms degraded as the Mach number and stiffness of the flow increased. At Mach 15, 23, and 30, the LUSGS method produces an eight order of magnitude drop in the L2 norm of the energy residual in 1/3 to 1/2 the Cray C-90 computer time as compared to the point implicit and explicit under-relaxation methods. The explicit under-relaxation algorithm experienced convergence difficulties at Mach 23 and above. At Mach 40 the performance of the LUSGS algorithm deteriorates to the point it is out-performed by the point implicit method. The effects of the viscous terms are investigated. Grid dependency questions are explored.

Generalizing Gillespie’s Direct Method to Enable Network-Free Simulations

DOE PAGES

Suderman, Ryan T.; Mitra, Eshan David; Lin, Yen Ting; ...

2018-03-28

Gillespie’s direct method for stochastic simulation of chemical kinetics is a staple of computational systems biology research. However, the algorithm requires explicit enumeration of all reactions and all chemical species that may arise in the system. In many cases, this is not feasible due to the combinatorial explosion of reactions and species in biological networks. Rule-based modeling frameworks provide a way to exactly represent networks containing such combinatorial complexity, and generalizations of Gillespie’s direct method have been developed as simulation engines for rule-based modeling languages. Here, we provide both a high-level description of the algorithms underlying the simulation engines, termedmore » network-free simulation algorithms, and how they have been applied in systems biology research. We also define a generic rule-based modeling framework and describe a number of technical details required for adapting Gillespie’s direct method for network-free simulation. Lastly, we briefly discuss potential avenues for advancing network-free simulation and the role they continue to play in modeling dynamical systems in biology.« less

Generalizing Gillespie’s Direct Method to Enable Network-Free Simulations

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

Suderman, Ryan T.; Mitra, Eshan David; Lin, Yen Ting

Gillespie’s direct method for stochastic simulation of chemical kinetics is a staple of computational systems biology research. However, the algorithm requires explicit enumeration of all reactions and all chemical species that may arise in the system. In many cases, this is not feasible due to the combinatorial explosion of reactions and species in biological networks. Rule-based modeling frameworks provide a way to exactly represent networks containing such combinatorial complexity, and generalizations of Gillespie’s direct method have been developed as simulation engines for rule-based modeling languages. Here, we provide both a high-level description of the algorithms underlying the simulation engines, termedmore » network-free simulation algorithms, and how they have been applied in systems biology research. We also define a generic rule-based modeling framework and describe a number of technical details required for adapting Gillespie’s direct method for network-free simulation. Lastly, we briefly discuss potential avenues for advancing network-free simulation and the role they continue to play in modeling dynamical systems in biology.« less

An improved flux-split algorithm applied to hypersonic flows in chemical equilibrium

NASA Technical Reports Server (NTRS)

Palmer, Grant

1988-01-01

An explicit, finite-difference, shock-capturing numerical algorithm is presented and applied to hypersonic flows assumed to be in thermochemical equilibrium. Real-gas chemistry is either loosely coupled to the gasdynamics by way of a Gibbs free energy minimization package or fully coupled using species mass conservation equations with finite-rate chemical reactions. A scheme is developed that maintains stability in the explicit, finite-rate formulation while allowing relatively high time steps. The codes use flux vector splitting to difference the inviscid fluxes and employ real-gas corrections to viscosity and thermal conductivity. Numerical results are compared against existing ballistic range and flight data. Flows about complex geometries are also computed.

Explicitly represented polygon wall boundary model for the explicit MPS method

NASA Astrophysics Data System (ADS)

Mitsume, Naoto; Yoshimura, Shinobu; Murotani, Kohei; Yamada, Tomonori

2015-05-01

This study presents an accurate and robust boundary model, the explicitly represented polygon (ERP) wall boundary model, to treat arbitrarily shaped wall boundaries in the explicit moving particle simulation (E-MPS) method, which is a mesh-free particle method for strong form partial differential equations. The ERP model expresses wall boundaries as polygons, which are explicitly represented without using the distance function. These are derived so that for viscous fluids, and with less computational cost, they satisfy the Neumann boundary condition for the pressure and the slip/no-slip condition on the wall surface. The proposed model is verified and validated by comparing computed results with the theoretical solution, results obtained by other models, and experimental results. Two simulations with complex boundary movements are conducted to demonstrate the applicability of the E-MPS method to the ERP model.

Chemical Continuous Time Random Walks

NASA Astrophysics Data System (ADS)

Aquino, T.; Dentz, M.

2017-12-01

Traditional methods for modeling solute transport through heterogeneous media employ Eulerian schemes to solve for solute concentration. More recently, Lagrangian methods have removed the need for spatial discretization through the use of Monte Carlo implementations of Langevin equations for solute particle motions. While there have been recent advances in modeling chemically reactive transport with recourse to Lagrangian methods, these remain less developed than their Eulerian counterparts, and many open problems such as efficient convergence and reconstruction of the concentration field remain. We explore a different avenue and consider the question: In heterogeneous chemically reactive systems, is it possible to describe the evolution of macroscopic reactant concentrations without explicitly resolving the spatial transport? Traditional Kinetic Monte Carlo methods, such as the Gillespie algorithm, model chemical reactions as random walks in particle number space, without the introduction of spatial coordinates. The inter-reaction times are exponentially distributed under the assumption that the system is well mixed. In real systems, transport limitations lead to incomplete mixing and decreased reaction efficiency. We introduce an arbitrary inter-reaction time distribution, which may account for the impact of incomplete mixing. This process defines an inhomogeneous continuous time random walk in particle number space, from which we derive a generalized chemical Master equation and formulate a generalized Gillespie algorithm. We then determine the modified chemical rate laws for different inter-reaction time distributions. We trace Michaelis-Menten-type kinetics back to finite-mean delay times, and predict time-nonlocal macroscopic reaction kinetics as a consequence of broadly distributed delays. Non-Markovian kinetics exhibit weak ergodicity breaking and show key features of reactions under local non-equilibrium.

A thermodynamic framework for thermo-chemo-elastic interactions in chemically active materials

NASA Astrophysics Data System (ADS)

Zhang, XiaoLong; Zhong, Zheng

2017-08-01

In this paper, a general thermodynamic framework is developed to describe the thermo-chemo-mechanical interactions in elastic solids undergoing mechanical deformation, imbibition of diffusive chemical species, chemical reactions and heat exchanges. Fully coupled constitutive relations and evolving laws for irreversible fluxes are provided based on entropy imbalance and stoichiometry that governs reactions. The framework manifests itself with a special feature that the change of Helmholtz free energy is attributed to separate contributions of the diffusion-swelling process and chemical reaction-dilation process. Both the extent of reaction and the concentrations of diffusive species are taken as independent state variables, which describe the reaction-activated responses with underlying variation of microstructures and properties of a material in an explicit way. A specialized isothermal formulation for isotropic materials is proposed that can properly account for volumetric constraints from material incompressibility under chemo-mechanical loadings, in which inhomogeneous deformation is associated with reaction and diffusion under various kinetic time scales. This framework can be easily applied to model the transient volumetric swelling of a solid caused by imbibition of external chemical species and simultaneous chemical dilation arising from reactions between the diffusing species and the solid.

Sensitivity of ab Initio vs Empirical Methods in Computing Structural Effects on NMR Chemical Shifts for the Example of Peptides.

PubMed

Sumowski, Chris Vanessa; Hanni, Matti; Schweizer, Sabine; Ochsenfeld, Christian

2014-01-14

The structural sensitivity of NMR chemical shifts as computed by quantum chemical methods is compared to a variety of empirical approaches for the example of a prototypical peptide, the 38-residue kaliotoxin KTX comprising 573 atoms. Despite the simplicity of empirical chemical shift prediction programs, the agreement with experimental results is rather good, underlining their usefulness. However, we show in our present work that they are highly insensitive to structural changes, which renders their use for validating predicted structures questionable. In contrast, quantum chemical methods show the expected high sensitivity to structural and electronic changes. This appears to be independent of the quantum chemical approach or the inclusion of solvent effects. For the latter, explicit solvent simulations with increasing number of snapshots were performed for two conformers of an eight amino acid sequence. In conclusion, the empirical approaches neither provide the expected magnitude nor the patterns of NMR chemical shifts determined by the clearly more costly ab initio methods upon structural changes. This restricts the use of empirical prediction programs in studies where peptide and protein structures are utilized for the NMR chemical shift evaluation such as in NMR refinement processes, structural model verifications, or calculations of NMR nuclear spin relaxation rates.

Estimating Soil Cation Exchange Capacity from Soil Physical and Chemical Properties

NASA Astrophysics Data System (ADS)

Bateni, S. M.; Emamgholizadeh, S.; Shahsavani, D.

2014-12-01

The soil Cation Exchange Capacity (CEC) is an important soil characteristic that has many applications in soil science and environmental studies. For example, CEC influences soil fertility by controlling the exchange of ions in the soil. Measurement of CEC is costly and difficult. Consequently, several studies attempted to obtain CEC from readily measurable soil physical and chemical properties such as soil pH, organic matter, soil texture, bulk density, and particle size distribution. These studies have often used multiple regression or artificial neural network models. Regression-based models cannot capture the intricate relationship between CEC and soil physical and chemical attributes and provide inaccurate CEC estimates. Although neural network models perform better than regression methods, they act like a black-box and cannot generate an explicit expression for retrieval of CEC from soil properties. In a departure with regression and neural network models, this study uses Genetic Expression Programming (GEP) and Multivariate Adaptive Regression Splines (MARS) to estimate CEC from easily measurable soil variables such as clay, pH, and OM. CEC estimates from GEP and MARS are compared with measurements at two field sites in Iran. Results show that GEP and MARS can estimate CEC accurately. Also, the MARS model performs slightly better than GEP. Finally, a sensitivity test indicates that organic matter and pH have respectively the least and the most significant impact on CEC.

Dynamics of cross-bridge cycling, ATP hydrolysis, force generation, and deformation in cardiac muscle

PubMed Central

Tewari, Shivendra G.; Bugenhagen, Scott M.; Palmer, Bradley M.; Beard, Daniel A.

2015-01-01

Despite extensive study over the past six decades the coupling of chemical reaction and mechanical processes in muscle dynamics is not well understood. We lack a theoretical description of how chemical processes (metabolite binding, ATP hydrolysis) influence and are influenced by mechanical processes (deformation and force generation). To address this need, a mathematical model of the muscle cross-bridge (XB) cycle based on Huxley’s sliding filament theory is developed that explicitly accounts for the chemical transformation events and the influence of strain on state transitions. The model is identified based on elastic and viscous moduli data from mouse and rat myocardial strips over a range of perturbation frequencies, and MgATP and inorganic phosphate (Pi) concentrations. Simulations of the identified model reproduce the observed effects of MgATP and MgADP on the rate of force development. Furthermore, simulations reveal that the rate of force re-development measured in slack-restretch experiments is not directly proportional to the rate of XB cycling. For these experiments, the model predicts that the observed increase in the rate of force generation with increased Pi concentration is due to inhibition of cycle turnover by Pi. Finally, the model captures the observed phenomena of force yielding suggesting that it is a result of rapid detachment of stretched attached myosin heads. PMID:25681584

Efficient Conformational Sampling in Explicit Solvent Using a Hybrid Replica Exchange Molecular Dynamics Method

DTIC Science & Technology

2011-12-01

REMD while reproducing the energy landscape of explicit solvent simulations . ’ INTRODUCTION Molecular dynamics (MD) simulations of proteins can pro...Mongan, J.; McCammon, J. A. Accelerated molecular dynamics : a promising and efficient simulation method for biomolecules. J. Chem. Phys. 2004, 120 (24...Chemical Theory and Computation ARTICLE (8) Abraham,M. J.; Gready, J. E. Ensuringmixing efficiency of replica- exchange molecular dynamics simulations . J

Investigation of chemically reacting and radiating supersonic internal flows

NASA Technical Reports Server (NTRS)

Mani, M.; Tiwari, S. N.

1986-01-01

The two-dimensional spatially elliptic Navier-Stokes equations are used to investigate the chemically reacting and radiating supersonic flow of the hydrogen-air system between two parallel plates and in a channel with a ten degree compression-expansion ramp at the lower boundary. The explicit unsplit finite-difference technique of MacCormack is used to advance the governing equations in time until convergence is achieved. The chemistry source term in the species equation is treated implicitly to alleviate the stiffness associated with fast reactions. The tangent slab approximation is employed in the radiative flux formation. Both pseudo-gray and nongray models are used to represent the absorption characteristics of the participating species. Results obtained for specific conditions indicate that the radiative interaction can have a significant influence on the flow field.

A multi-species exchange model for fully fluctuating polymer field theory simulations.

PubMed

Düchs, Dominik; Delaney, Kris T; Fredrickson, Glenn H

2014-11-07

Field-theoretic models have been used extensively to study the phase behavior of inhomogeneous polymer melts and solutions, both in self-consistent mean-field calculations and in numerical simulations of the full theory capturing composition fluctuations. The models commonly used can be grouped into two categories, namely, species models and exchange models. Species models involve integrations of functionals that explicitly depend on fields originating both from species density operators and their conjugate chemical potential fields. In contrast, exchange models retain only linear combinations of the chemical potential fields. In the two-component case, development of exchange models has been instrumental in enabling stable complex Langevin (CL) simulations of the full complex-valued theory. No comparable stable CL approach has yet been established for field theories of the species type. Here, we introduce an extension of the exchange model to an arbitrary number of components, namely, the multi-species exchange (MSE) model, which greatly expands the classes of soft material systems that can be accessed by the complex Langevin simulation technique. We demonstrate the stability and accuracy of the MSE-CL sampling approach using numerical simulations of triblock and tetrablock terpolymer melts, and tetrablock quaterpolymer melts. This method should enable studies of a wide range of fluctuation phenomena in multiblock/multi-species polymer blends and composites.

Multiscale investigation of chemical interference in proteins

NASA Astrophysics Data System (ADS)

Samiotakis, Antonios; Homouz, Dirar; Cheung, Margaret S.

2010-05-01

We developed a multiscale approach (MultiSCAAL) that integrates the potential of mean force obtained from all-atomistic molecular dynamics simulations with a knowledge-based energy function for coarse-grained molecular simulations in better exploring the energy landscape of a small protein under chemical interference such as chemical denaturation. An excessive amount of water molecules in all-atomistic molecular dynamics simulations often negatively impacts the sampling efficiency of some advanced sampling techniques such as the replica exchange method and it makes the investigation of chemical interferences on protein dynamics difficult. Thus, there is a need to develop an effective strategy that focuses on sampling structural changes in protein conformations rather than solvent molecule fluctuations. In this work, we address this issue by devising a multiscale simulation scheme (MultiSCAAL) that bridges the gap between all-atomistic molecular dynamics simulation and coarse-grained molecular simulation. The two key features of this scheme are the Boltzmann inversion and a protein atomistic reconstruction method we previously developed (SCAAL). Using MultiSCAAL, we were able to enhance the sampling efficiency of proteins solvated by explicit water molecules. Our method has been tested on the folding energy landscape of a small protein Trp-cage with explicit solvent under 8M urea using both the all-atomistic replica exchange molecular dynamics and MultiSCAAL. We compared computational analyses on ensemble conformations of Trp-cage with its available experimental NOE distances. The analysis demonstrated that conformations explored by MultiSCAAL better agree with the ones probed in the experiments because it can effectively capture the changes in side-chain orientations that can flip out of the hydrophobic pocket in the presence of urea and water molecules. In this regard, MultiSCAAL is a promising and effective sampling scheme for investigating chemical interference which presents a great challenge when modeling protein interactions in vivo.

Thermodynamics of natural selection III: Landauer's principle in computation and chemistry.

PubMed

Smith, Eric

2008-05-21

This is the third in a series of three papers devoted to energy flow and entropy changes in chemical and biological processes, and their relations to the thermodynamics of computation. The previous two papers have developed reversible chemical transformations as idealizations for studying physiology and natural selection, and derived bounds from the second law of thermodynamics, between information gain in an ensemble and the chemical work required to produce it. This paper concerns the explicit mapping of chemistry to computation, and particularly the Landauer decomposition of irreversible computations, in which reversible logical operations generating no heat are separated from heat-generating erasure steps which are logically irreversible but thermodynamically reversible. The Landauer arrangement of computation is shown to produce the same entropy-flow diagram as that of the chemical Carnot cycles used in the second paper of the series to idealize physiological cycles. The specific application of computation to data compression and error-correcting encoding also makes possible a Landauer analysis of the somewhat different problem of optimal molecular recognition, which has been considered as an information theory problem. It is shown here that bounds on maximum sequence discrimination from the enthalpy of complex formation, although derived from the same logical model as the Shannon theorem for channel capacity, arise from exactly the opposite model for erasure.

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

Düchs, Dominik; Delaney, Kris T., E-mail: kdelaney@mrl.ucsb.edu; Fredrickson, Glenn H., E-mail: ghf@mrl.ucsb.edu

Field-theoretic models have been used extensively to study the phase behavior of inhomogeneous polymer melts and solutions, both in self-consistent mean-field calculations and in numerical simulations of the full theory capturing composition fluctuations. The models commonly used can be grouped into two categories, namely, species models and exchange models. Species models involve integrations of functionals that explicitly depend on fields originating both from species density operators and their conjugate chemical potential fields. In contrast, exchange models retain only linear combinations of the chemical potential fields. In the two-component case, development of exchange models has been instrumental in enabling stable complexmore » Langevin (CL) simulations of the full complex-valued theory. No comparable stable CL approach has yet been established for field theories of the species type. Here, we introduce an extension of the exchange model to an arbitrary number of components, namely, the multi-species exchange (MSE) model, which greatly expands the classes of soft material systems that can be accessed by the complex Langevin simulation technique. We demonstrate the stability and accuracy of the MSE-CL sampling approach using numerical simulations of triblock and tetrablock terpolymer melts, and tetrablock quaterpolymer melts. This method should enable studies of a wide range of fluctuation phenomena in multiblock/multi-species polymer blends and composites.« less

Numerical modelling of multiphase multicomponent reactive transport in the Earth's interior

NASA Astrophysics Data System (ADS)

Oliveira, Beñat; Afonso, Juan Carlos; Zlotnik, Sergio; Diez, Pedro

2018-01-01

We present a conceptual and numerical approach to model processes in the Earth's interior that involve multiple phases that simultaneously interact thermally, mechanically and chemically. The approach is truly multiphase in the sense that each dynamic phase is explicitly modelled with an individual set of mass, momentum, energy and chemical mass balance equations coupled via interfacial interaction terms. It is also truly multicomponent in the sense that the compositions of the system and its constituent phases are expressed by a full set of fundamental chemical components (e.g. SiO2, Al2O3, MgO, etc.) rather than proxies. These chemical components evolve, react with and partition into different phases according to an internally consistent thermodynamic model. We combine concepts from Ensemble Averaging and Classical Irreversible Thermodynamics to obtain sets of macroscopic balance equations that describe the evolution of systems governed by multiphase multicomponent reactive transport (MPMCRT). Equilibrium mineral assemblages, their compositions and physical properties, and closure relations for the balance equations are obtained via a `dynamic' Gibbs free-energy minimization procedure (i.e. minimizations are performed on-the-fly as needed by the simulation). Surface tension and surface energy contributions to the dynamics and energetics of the system are taken into account. We show how complex rheologies, that is, visco-elasto-plastic, and/or different interfacial models can be incorporated into our MPMCRT ensemble-averaged formulation. The resulting model provides a reliable platform to study the dynamics and nonlinear feedbacks of MPMCRT systems of different nature and scales, as well as to make realistic comparisons with both geophysical and geochemical data sets. Several numerical examples are presented to illustrate the benefits and limitations of the model.

CDPOP: A spatially explicit cost distance population genetics program

Treesearch

Erin L. Landguth; S. A. Cushman

2010-01-01

Spatially explicit simulation of gene flow in complex landscapes is essential to explain observed population responses and provide a foundation for landscape genetics. To address this need, we wrote a spatially explicit, individual-based population genetics model (CDPOP). The model implements individual-based population modelling with Mendelian inheritance and k-allele...

Improved EOS for describing high-temperature off-hugoniot states in epoxy

NASA Astrophysics Data System (ADS)

Mulford, R. N.; Lanier, N. E.; Swift, D.; Workman, J.; Graham, Peter; Moore, Alastair

2007-06-01

Modeling of off-hugoniot states in an expanding interface subjected to a shock reveals the importance of a chemically complete description of the materials. Hydrodynamic experiments typically rely on pre-shot target characterization to predict how initial perturbations will affect the late-time hydrodynamic mixing. However, it is the condition of these perturbations at the time of shock arrival that dominates their eventual late-time evolution. In some cases these perturbations are heated prior to the arrival of the main shock. Correctly modeling how temperature and density gradients will develop in the pre-heated material requires an understanding of the equation-of-state. In the experiment modelled, an epoxy/foam layered package was subjected to tin L-shell radiation, producing an expanding assembly at a well-defined temperature. This assembly was then subjected to a controlled shock, and the evolution of the epoxy-foam interface imaged with x-ray radiography. Modeling of the data with the hydrodynamics code RAGE is unsuccessful under certain shock conditions, unless condensation of chemical species from the plasma is explicitly included. The EOS code CHEETAH was used to prepare suitable EOS for input into the hydrodynamics modeling.

Improved EOS for Describing High-Temperature Off-Hugoniot States in Epoxy

NASA Astrophysics Data System (ADS)

Mulford, R. N.; Swift, D. C.; Lanier, N. E.; Workman, J.; Holmes, R. L.; Graham, P.; Moore, A.

2007-12-01

Modelling of off-Hugoniot states in an expanding interface subjected to a shock reveals the importance of a chemically complete description of the materials. Hydrodynamic experiments typically rely on pre-shot target characterization to predict how initial perturbations will affect the late-time hydrodynamic mixing. However, it is the condition of these perturbations at the time of shock arrival that dominates their eventual late-time evolution. In some cases these perturbations are heated prior to the arrival of the main shock. Correctly modelling how temperature and density gradients will develop in the pre-heated material requires an understanding of the equation-of-state. In the experiment modelled, an epoxy/foam layered package was subjected to tin L-shell radiation, producing an expanding assembly at a well-defined temperature. This assembly was then subjected to a controlled shock, and the evolution of the epoxy-foam interface imaged with x-ray radiography. Modelling of the data with the hydrodynamics code RAGE was unsuccessful under certain shock conditions, unless condensation of chemical species from the plasma is explicitly included. The EOS code Cheetah was used to prepare suitable EOS for input into the hydrodynamics modelling.

Simulations of reactive transport and precipitation with smoothed particle hydrodynamics

NASA Astrophysics Data System (ADS)

Tartakovsky, Alexandre M.; Meakin, Paul; Scheibe, Timothy D.; Eichler West, Rogene M.

2007-03-01

A numerical model based on smoothed particle hydrodynamics (SPH) was developed for reactive transport and mineral precipitation in fractured and porous materials. Because of its Lagrangian particle nature, SPH has several advantages for modeling Navier-Stokes flow and reactive transport including: (1) in a Lagrangian framework there is no non-linear term in the momentum conservation equation, so that accurate solutions can be obtained for momentum dominated flows and; (2) complicated physical and chemical processes such as surface growth due to precipitation/dissolution and chemical reactions are easy to implement. In addition, SPH simulations explicitly conserve mass and linear momentum. The SPH solution of the diffusion equation with fixed and moving reactive solid-fluid boundaries was compared with analytical solutions, Lattice Boltzmann [Q. Kang, D. Zhang, P. Lichtner, I. Tsimpanogiannis, Lattice Boltzmann model for crystal growth from supersaturated solution, Geophysical Research Letters, 31 (2004) L21604] simulations and diffusion limited aggregation (DLA) [P. Meakin, Fractals, scaling and far from equilibrium. Cambridge University Press, Cambridge, UK, 1998] model simulations. To illustrate the capabilities of the model, coupled three-dimensional flow, reactive transport and precipitation in a fracture aperture with a complex geometry were simulated.

Diagnostic tools for mixing models of stream water chemistry

USGS Publications Warehouse

Hooper, Richard P.

2003-01-01

Mixing models provide a useful null hypothesis against which to evaluate processes controlling stream water chemical data. Because conservative mixing of end‐members with constant concentration is a linear process, a number of simple mathematical and multivariate statistical methods can be applied to this problem. Although mixing models have been most typically used in the context of mixing soil and groundwater end‐members, an extension of the mathematics of mixing models is presented that assesses the “fit” of a multivariate data set to a lower dimensional mixing subspace without the need for explicitly identified end‐members. Diagnostic tools are developed to determine the approximate rank of the data set and to assess lack of fit of the data. This permits identification of processes that violate the assumptions of the mixing model and can suggest the dominant processes controlling stream water chemical variation. These same diagnostic tools can be used to assess the fit of the chemistry of one site into the mixing subspace of a different site, thereby permitting an assessment of the consistency of controlling end‐members across sites. This technique is applied to a number of sites at the Panola Mountain Research Watershed located near Atlanta, Georgia.

Operational models of pharmacological agonism.

PubMed

Black, J W; Leff, P

1983-12-22

The traditional receptor-stimulus model of agonism began with a description of drug action based on the law of mass action and has developed by a series of modifications, each accounting for new experimental evidence. By contrast, in this paper an approach to modelling agonism is taken that begins with the observation that experimental agonist-concentration effect, E/[A], curves are commonly hyperbolic and develops using the deduction that the relation between occupancy and effect must be hyperbolic if the law of mass action applies at the agonist-receptor level. The result is a general model that explicitly describes agonism by three parameters: an agonist-receptor dissociation constant, KA; the total receptor concentration, [R0]; and a parameter, KE, defining the transduction of agonist-receptor complex, AR, into pharmacological effect. The ratio, [R0]/KE, described here as the 'transducer ratio', tau, is a logical definition for the efficacy of an agonist in a system. The model may be extended to account for non-hyperbolic E/[A] curves with no loss of meaning. Analysis shows that an explicit formulation of the traditional receptor-stimulus model is one particular form of the general model but that it is not the simplest. An alternative model is proposed, representing the cognitive and transducer functions of a receptor, that describes agonist action with one fewer parameter than the traditional model. In addition, this model provides a chemical definition of intrinsic efficacy making this parameter experimentally accessible in principle. The alternative models are compared and contrasted with regard to their practical and conceptual utilities in experimental pharmacology.

Designing molecular complexes using free-energy derivatives from liquid-state integral equation theory

NASA Astrophysics Data System (ADS)

Mrugalla, Florian; Kast, Stefan M.

2016-09-01

Complex formation between molecules in solution is the key process by which molecular interactions are translated into functional systems. These processes are governed by the binding or free energy of association which depends on both direct molecular interactions and the solvation contribution. A design goal frequently addressed in pharmaceutical sciences is the optimization of chemical properties of the complex partners in the sense of minimizing their binding free energy with respect to a change in chemical structure. Here, we demonstrate that liquid-state theory in the form of the solute-solute equation of the reference interaction site model provides all necessary information for such a task with high efficiency. In particular, computing derivatives of the potential of mean force (PMF), which defines the free-energy surface of complex formation, with respect to potential parameters can be viewed as a means to define a direction in chemical space toward better binders. We illustrate the methodology in the benchmark case of alkali ion binding to the crown ether 18-crown-6 in aqueous solution. In order to examine the validity of the underlying solute-solute theory, we first compare PMFs computed by different approaches, including explicit free-energy molecular dynamics simulations as a reference. Predictions of an optimally binding ion radius based on free-energy derivatives are then shown to yield consistent results for different ion parameter sets and to compare well with earlier, orders-of-magnitude more costly explicit simulation results. This proof-of-principle study, therefore, demonstrates the potential of liquid-state theory for molecular design problems.

Designing molecular complexes using free-energy derivatives from liquid-state integral equation theory.

PubMed

Mrugalla, Florian; Kast, Stefan M

2016-09-01

Complex formation between molecules in solution is the key process by which molecular interactions are translated into functional systems. These processes are governed by the binding or free energy of association which depends on both direct molecular interactions and the solvation contribution. A design goal frequently addressed in pharmaceutical sciences is the optimization of chemical properties of the complex partners in the sense of minimizing their binding free energy with respect to a change in chemical structure. Here, we demonstrate that liquid-state theory in the form of the solute-solute equation of the reference interaction site model provides all necessary information for such a task with high efficiency. In particular, computing derivatives of the potential of mean force (PMF), which defines the free-energy surface of complex formation, with respect to potential parameters can be viewed as a means to define a direction in chemical space toward better binders. We illustrate the methodology in the benchmark case of alkali ion binding to the crown ether 18-crown-6 in aqueous solution. In order to examine the validity of the underlying solute-solute theory, we first compare PMFs computed by different approaches, including explicit free-energy molecular dynamics simulations as a reference. Predictions of an optimally binding ion radius based on free-energy derivatives are then shown to yield consistent results for different ion parameter sets and to compare well with earlier, orders-of-magnitude more costly explicit simulation results. This proof-of-principle study, therefore, demonstrates the potential of liquid-state theory for molecular design problems.

Soil fauna and plant litter decomposition in tropical and subalpine forests

Treesearch

G. Gonzalez; T.R. Seastedt

2001-01-01

The decomposition of plant residues is influenced by their chemical composition, the physical-chemical environment, and the decomposer organisms. Most studies interested in latitudinal gradients of decomposition have focused on substrate quality and climate effects on decomposition, and have excluded explicit recognition of the soil organisms involved in the process....

Representational Classroom Practices that Contribute to Students' Conceptual and Representational Understanding of Chemical Bonding

ERIC Educational Resources Information Center

Hilton, Annette; Nichols, Kim

2011-01-01

Understanding bonding is fundamental to success in chemistry. A number of alternative conceptions related to chemical bonding have been reported in the literature. Research suggests that many alternative conceptions held by chemistry students result from previous teaching; if teachers are explicit in the use of representations and explain their…

A THC Simulator for Modeling Fluid-Rock Interactions

NASA Astrophysics Data System (ADS)

Hamidi, Sahar; Galvan, Boris; Heinze, Thomas; Miller, Stephen

2014-05-01

Fluid-rock interactions play an essential role in many earth processes, from a likely influence on earthquake nucleation and aftershocks, to enhanced geothermal system, carbon capture and storage (CCS), and underground nuclear waste repositories. In THC models, two-way interactions between different processes (thermal, hydraulic and chemical) are present. Fluid flow influences the permeability of the rock especially if chemical reactions are taken into account. On one hand solute concentration influences fluid properties while, on the other hand, heat can affect further chemical reactions. Estimating heat production from a naturally fractured geothermal systems remains a complex problem. Previous works are typically based on a local thermal equilibrium assumption and rarely consider the salinity. The dissolved salt in fluid affects the hydro- and thermodynamical behavior of the system by changing the hydraulic properties of the circulating fluid. Coupled thermal-hydraulic-chemical models (THC) are important for investigating these processes, but what is needed is a coupling to mechanics to result in THMC models. Although similar models currently exist (e.g. PFLOTRAN), our objective here is to develop algorithms for implementation using the Graphics Processing Unit (GPU) computer architecture to be run on GPU clusters. To that aim, we present a two-dimensional numerical simulation of a fully coupled non-isothermal non-reactive solute flow. The thermal part of the simulation models heat transfer processes for either local thermal equilibrium or nonequilibrium cases, and coupled to a non-reactive mass transfer described by a non-linear diffusion/dispersion model. The flow process of the model includes a non-linear Darcian flow for either saturated or unsaturated scenarios. For the unsaturated case, we use the Richards' approximation for a mixture of liquid and gas phases. Relative permeability and capillary pressure are determined by the van Genuchten relations. Permeability of rock is controlled by porosity, which is itself related to effective stress. The theoretical model is solved using explicit finite differences, and runs in parallel mode with OpenMP. The code is fully modular so that any combination of current THC processes, one- and two-phase, can be chosen. Future developments will include dissolution and precipitation of chemical components in addition to chemical erosion.

Developing a molecular picture of soil organic matter–mineral interactions by quantifying organo–mineral binding

DOE PAGES

Newcomb, C. J.; Qafoku, N. P.; Grate, J. W.; ...

2017-08-30

Long residence times of soil organic matter have been attributed to reactive mineral surface sites that sorb organic species and cause inaccessibility due to isolation and chemical stabilization at the organic-mineral interface. Instrumentation for probing this interface is limited. As a result, much of the micron- and molecular-scale knowledge about organic-mineral interactions remains largely qualitative. We report the use of force spectroscopy to directly measure the binding between organic ligands with known chemical functionalities to soil minerals in aqueous environments. By systematically studying the role of organic functional group chemistry with model minerals, we demonstrate that the chemistry of bothmore » the organic ligand and mineral contribute to values of binding free energy and that changes in pH and ionic strength produce significant differences in binding energies. These direct measurements of molecular binding provide mechanistic insights into organo-mineral interactions, which could potentially inform land-carbon models that explicitly include mineral-bound C pools.« less

Developing a molecular picture of soil organic matter–mineral interactions by quantifying organo–mineral binding

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

Newcomb, C. J.; Qafoku, N. P.; Grate, J. W.

Long residence times of soil organic matter have been attributed to reactive mineral surface sites that sorb organic species and cause inaccessibility due to isolation and chemical stabilization at the organic-mineral interface. Instrumentation for probing this interface is limited. As a result, much of the micron- and molecular-scale knowledge about organic-mineral interactions remains largely qualitative. We report the use of force spectroscopy to directly measure the binding between organic ligands with known chemical functionalities to soil minerals in aqueous environments. By systematically studying the role of organic functional group chemistry with model minerals, we demonstrate that the chemistry of bothmore » the organic ligand and mineral contribute to values of binding free energy and that changes in pH and ionic strength produce significant differences in binding energies. These direct measurements of molecular binding provide mechanistic insights into organo-mineral interactions, which could potentially inform land-carbon models that explicitly include mineral-bound C pools.« less

Reduced atomic pair-interaction design (RAPID) model for simulations of proteins.

PubMed

Ni, Boris; Baumketner, Andrij

2013-02-14

Increasingly, theoretical studies of proteins focus on large systems. This trend demands the development of computational models that are fast, to overcome the growing complexity, and accurate, to capture the physically relevant features. To address this demand, we introduce a protein model that uses all-atom architecture to ensure the highest level of chemical detail while employing effective pair potentials to represent the effect of solvent to achieve the maximum speed. The effective potentials are derived for amino acid residues based on the condition that the solvent-free model matches the relevant pair-distribution functions observed in explicit solvent simulations. As a test, the model is applied to alanine polypeptides. For the chain with 10 amino acid residues, the model is found to reproduce properly the native state and its population. Small discrepancies are observed for other folding properties and can be attributed to the approximations inherent in the model. The transferability of the generated effective potentials is investigated in simulations of a longer peptide with 25 residues. A minimal set of potentials is identified that leads to qualitatively correct results in comparison with the explicit solvent simulations. Further tests, conducted for multiple peptide chains, show that the transferable model correctly reproduces the experimentally observed tendency of polyalanines to aggregate into β-sheets more strongly with the growing length of the peptide chain. Taken together, the reported results suggest that the proposed model could be used to succesfully simulate folding and aggregation of small peptides in atomic detail. Further tests are needed to assess the strengths and limitations of the model more thoroughly.

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

PubMed Central

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

2013-01-01

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

A method for the direct numerical simulation of hypersonic boundary-layer instability with finite-rate chemistry

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

Marxen, Olaf, E-mail: olaf.marxen@vki.ac.be; Aeronautics and Aerospace Department, von Karman Institute for Fluid Dynamics, Chaussée de Waterloo, 72, 1640 Rhode-St-Genèse; Magin, Thierry E.

2013-12-15

A new numerical method is presented here that allows to consider chemically reacting gases during the direct numerical simulation of a hypersonic fluid flow. The method comprises the direct coupling of a solver for the fluid mechanical model and a library providing the physio-chemical model. The numerical method for the fluid mechanical model integrates the compressible Navier–Stokes equations using an explicit time advancement scheme and high-order finite differences. This Navier–Stokes code can be applied to the investigation of laminar-turbulent transition and boundary-layer instability. The numerical method for the physio-chemical model provides thermodynamic and transport properties for different gases as wellmore » as chemical production rates, while here we exclusively consider a five species air mixture. The new method is verified for a number of test cases at Mach 10, including the one-dimensional high-temperature flow downstream of a normal shock, a hypersonic chemical reacting boundary layer in local thermodynamic equilibrium and a hypersonic reacting boundary layer with finite-rate chemistry. We are able to confirm that the diffusion flux plays an important role for a high-temperature boundary layer in local thermodynamic equilibrium. Moreover, we demonstrate that the flow for a case previously considered as a benchmark for the investigation of non-equilibrium chemistry can be regarded as frozen. Finally, the new method is applied to investigate the effect of finite-rate chemistry on boundary layer instability by considering the downstream evolution of a small-amplitude wave and comparing results with those obtained for a frozen gas as well as a gas in local thermodynamic equilibrium.« less

Xenobiotic metabolism in human skin and 3D human skin reconstructs: a review.

PubMed

Gibbs, Sue; van de Sandt, Johannes J M; Merk, Hans F; Lockley, David J; Pendlington, Ruth U; Pease, Camilla K

2007-12-01

In this review, we discuss and compare studies of xenobiotic metabolism in both human skin and 3D human skin reconstructs. In comparison to the liver, the skin is a less studied organ in terms of characterising metabolic capability. While the skin forms the major protective barrier to environmental chemical exposure, it is also a potential target organ for adverse health effects. Occupational, accidental or intended-use exposure to toxic chemicals could result in acute or delayed injury to the skin (e.g. inflammation, allergy, cancer). Skin metabolism may play a role in the manifestation or amelioration of adverse effects via the topical route. Today, we have robust testing strategies to assess the potential for local skin toxicity of chemical exposure. Such methods (e.g. the local lymph node assay for assessing skin sensitisation; skin painting carcinogenicity studies) incorporate skin metabolism implicitly in the in vivo model system used. In light of recent European legislation (i.e. 7(th) Amendment to the Cosmetics Directive and Registration Evaluation and Authorisation of existing Chemicals (REACH)), non-animal approaches will be required to reduce and replace animal experiments for chemical risk assessment. It is expected that new models and approaches will need to account for skin metabolism explicitly, as the mechanisms of adverse effects in the skin are deconvoluted. 3D skin models have been proposed as a tool to use in new in vitro alternative approaches. In order to be able to use 3D skin models in this context, we need to understand their metabolic competency in relation to xenobiotic biotransformation and whether functional activity is representative of that seen in human skin.

Comparison of Nonequilibrium Solution Algorithms Applied to Chemically Stiff Hypersonic Flows

NASA Technical Reports Server (NTRS)

Palmer, Grant; Venkatapathy, Ethiraj

1995-01-01

Three solution algorithms, explicit under-relaxation, point implicit, and lower-upper symmetric Gauss-Seidel, are used to compute nonequilibrium flow around the Apollo 4 return capsule at the 62-km altitude point in its descent trajectory. By varying the Mach number, the efficiency and robustness of the solution algorithms were tested for different levels of chemical stiffness.The performance of the solution algorithms degraded as the Mach number and stiffness of the flow increased. At Mach 15 and 30, the lower-upper symmetric Gauss-Seidel method produces an eight order of magnitude drop in the energy residual in one-third to one-half the Cray C-90 computer time as compared to the point implicit and explicit under-relaxation methods. The explicit under-relaxation algorithm experienced convergence difficulties at Mach 30 and above. At Mach 40 the performance of the lower-upper symmetric Gauss-Seidel algorithm deteriorates to the point that it is out performed by the point implicit method. The effects of the viscous terms are investigated. Grid dependency questions are explored.

Deriving an explicit hepatic clearance equation accounting for plasma protein binding and hepatocellular uptake.

PubMed

Yoon, Miyoung; Clewell, Harvey J; Andersen, Melvin E

2013-02-01

High throughput in vitro biochemical and cell-based assays have the promise to provide more mechanism-based assessments of the adverse effects of large numbers of chemicals. One of the most challenging hurdles for interpreting in vitro toxicity findings is the need for reverse dosimetry tools that estimate the exposures that will give concentrations in vivo similar to the active concentrations in vitro. Recent experience using IVIVE approaches to estimate in vivo pharmacokinetics (Wetmore et al., 2012) identified the need to develop a hepatic clearance equation that explicitly accounted for a broader set of protein binding and membrane transport processes and did not depend on a well-mixed description of the liver compartment. Here we derive an explicit steady-state hepatic clearance equation that includes these factors. In addition to the derivation, we provide simple computer code to calculate steady-state extraction for any combination of blood flow, membrane transport processes and plasma protein-chemical binding rates. This expanded equation provides a tool to estimate hepatic clearance for a more diverse array of compounds. Copyright © 2012 Elsevier Ltd. All rights reserved.

Monte Carlo kinetics simulations of ice-mantle formation on interstellar grains

NASA Astrophysics Data System (ADS)

Garrod, Robin

2015-08-01

The majority of interstellar dust-grain chemical kinetics models use rate equations, or alternative population-based simulation methods, to trace the time-dependent formation of grain-surface molecules and ice mantles. Such methods are efficient, but are incapable of considering explicitly the morphologies of the dust grains, the structure of the ices formed thereon, or the influence of local surface composition on the chemistry.A new Monte Carlo chemical kinetics model, MIMICK, is presented here, whose prototype results were published recently (Garrod 2013, ApJ, 778, 158). The model calculates the strengths and positions of the potential mimima on the surface, on the fly, according to the individual pair-wise (van der Waals) bonds between surface species, allowing the structure of the ice to build up naturally as surface diffusion and chemistry occur. The prototype model considered contributions to a surface particle's potential only from contiguous (or "bonded") neighbors; the full model considers contributions from surface constituents from short to long range. Simulations are conducted on a fully 3-D user-generated dust-grain with amorphous surface characteristics. The chemical network has also been extended from the simple water system previously published, and now includes 33 chemical species and 55 reactions. This allows the major interstellar ice components to be simulated, such as water, methane, ammonia and methanol, as well as a small selection of more complex molecules, including methyl formate (HCOOCH3).The new model results indicate that the porosity of interstellar ices are dependent on multiple variables, including gas density, the dust temperature, and the relative accretion rates of key gas-phase species. The results presented also have implications for the formation of complex organic molecules on dust-grain surfaces at very low temperatures.

GroPBS: Fast Solver for Implicit Electrostatics of Biomolecules

PubMed Central

Bertelshofer, Franziska; Sun, Liping; Greiner, Günther; Böckmann, Rainer A.

2015-01-01

Knowledge about the electrostatic potential on the surface of biomolecules or biomembranes under physiological conditions is an important step in the attempt to characterize the physico-chemical properties of these molecules and, in particular, also their interactions with each other. Additionally, knowledge about solution electrostatics may also guide the design of molecules with specified properties. However, explicit water models come at a high computational cost, rendering them unsuitable for large design studies or for docking purposes. Implicit models with the water phase treated as a continuum require the numerical solution of the Poisson–Boltzmann equation (PBE). Here, we present a new flexible program for the numerical solution of the PBE, allowing for different geometries, and the explicit and implicit inclusion of membranes. It involves a discretization of space and the computation of the molecular surface. The PBE is solved using finite differences, the resulting set of equations is solved using a Gauss–Seidel method. It is shown for the example of the sucrose transporter ScrY that the implicit inclusion of a surrounding membrane has a strong effect also on the electrostatics within the pore region and, thus, needs to be carefully considered, e.g., in design studies on membrane proteins. PMID:26636074

Shock Wave Propagation in Cementitious Materials at Micro/Meso Scales

NASA Astrophysics Data System (ADS)

Rajendran, Arunachalam

2015-06-01

The mechanical and constitutive response of materials like cement, and bio materials like fish scale and abalone shell is very complex due to heterogeneities that are inherently present in the nano and microstructures. The intrinsic constitutive behaviors are driven by the chemical composition and the molecular, micro, and meso structures. Therefore, it becomes important to identify the material genome as the building block for the material. For instance, in cementitious materials, the genome of C-S-H phase (the glue or the paste) that holds the various clinkers, such as the dicalcium silicate, tricalcium silicate, calcium ferroaluminates, and others is extremely complex. Often mechanical behaviors of C-S-H type materials are influenced by the chemistry and the structures at all nano to micro length scales. By explicitly modeling the molecular structures using appropriate potentials, it is then possible to compute the elastic tensor from molecular dynamics simulations using all atom method. The elastic tensors for the C-S-H gel and other clinkers are determined using the software suite ``Accelrys Materials Studio.'' A strain rate dependent, fracture mechanics based tensile damage model has been incorporated into ABAQUS finite element code to model spall evolution in the heterogeneous cementitious material with all constituents explicitly modeled through one micron element resolution. This paper presents results from nano/micro/meso scale analyses of shock wave propagation in a heterogeneous cementitious material using both molecular dynamic and finite element codes.

Modeling SOA formation from the oxidation of intermediate volatility n-alkanes

NASA Astrophysics Data System (ADS)

Aumont, B.; Valorso, R.; Mouchel-Vallon, C.; Camredon, M.; Lee-Taylor, J.; Madronich, S.

2012-08-01

The chemical mechanism leading to SOA formation and ageing is expected to be a multigenerational process, i.e. a successive formation of organic compounds with higher oxidation degree and lower vapor pressure. This process is here investigated with the explicit oxidation model GECKO-A (Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere). Gas phase oxidation schemes are generated for the C8-C24 series of n-alkanes. Simulations are conducted to explore the time evolution of organic compounds and the behavior of secondary organic aerosol (SOA) formation for various preexisting organic aerosol concentration (COA). As expected, simulation results show that (i) SOA yield increases with the carbon chain length of the parent hydrocarbon, (ii) SOA yield decreases with decreasing COA, (iii) SOA production rates increase with increasing COA and (iv) the number of oxidation steps (i.e. generations) needed to describe SOA formation and evolution grows when COA decreases. The simulated oxidative trajectories are examined in a two dimensional space defined by the mean carbon oxidation state and the volatility. Most SOA contributors are not oxidized enough to be categorized as highly oxygenated organic aerosols (OOA) but reduced enough to be categorized as hydrocarbon like organic aerosols (HOA), suggesting that OOA may underestimate SOA. Results show that the model is unable to produce highly oxygenated aerosols (OOA) with large yields. The limitations of the model are discussed.

Modeling SOA formation from the oxidation of intermediate volatility n-alkanes

NASA Astrophysics Data System (ADS)

Aumont, B.; Valorso, R.; Mouchel-Vallon, C.; Camredon, M.; Lee-Taylor, J.; Madronich, S.

2012-06-01

The chemical mechanism leading to SOA formation and ageing is expected to be a multigenerational process, i.e. a successive formation of organic compounds with higher oxidation degree and lower vapor pressure. This process is here investigated with the explicit oxidation model GECKO-A (Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere). Gas phase oxidation schemes are generated for the C8-C24 series of n-alkanes. Simulations are conducted to explore the time evolution of organic compounds and the behavior of secondary organic aerosol (SOA) formation for various preexisting organic aerosol concentration (COA). As expected, simulation results show that (i) SOA yield increases with the carbon chain length of the parent hydrocarbon, (ii) SOA yield decreases with decreasing COA, (iii) SOA production rates increase with increasing COA and (iv) the number of oxidation steps (i.e. generations) needed to describe SOA formation and evolution grows when COA decreases. The simulated oxidative trajectories are examined in a two dimensional space defined by the mean carbon oxidation state and the volatility. Most SOA contributors are not oxidized enough to be categorized as highly oxygenated organic aerosols (OOA) but reduced enough to be categorized as hydrocarbon like organic aerosols (HOA), suggesting that OOA may underestimate SOA. Results show that the model is unable to produce highly oxygenated aerosols (OOA) with large yields. The limitations of the model are discussed.

Phenotypic responses to microbial volatiles render a mold fungus more susceptible to insect damage.

PubMed

Caballero Ortiz, Silvia; Trienens, Monika; Pfohl, Katharina; Karlovsky, Petr; Holighaus, Gerrit; Rohlfs, Marko

2018-04-01

In decomposer systems, fungi show diverse phenotypic responses to volatile organic compounds of microbial origin (volatiles). The mechanisms underlying such responses and their consequences for the performance and ecological success of fungi in a multitrophic community context have rarely been tested explicitly. We used a laboratory-based approach in which we investigated a tripartite yeast-mold-insect model decomposer system to understand the possible influence of yeast-borne volatiles on the ability of a chemically defended mold fungus to resist insect damage. The volatile-exposed mold phenotype (1) did not exhibit protein kinase A-dependent morphological differentiation, (2) was more susceptible to insect foraging activity, and (3) had reduced insecticidal properties. Additionally, the volatile-exposed phenotype was strongly impaired in secondary metabolite formation and unable to activate "chemical defense" genes upon insect damage. These results suggest that volatiles can be ecologically important factors that affect the chemical-based combative abilities of fungi against insect antagonists and, consequently, the structure and dynamics of decomposer communities.

High potential for weathering and climate effects of non-vascular vegetation in the Late Ordovician

PubMed Central

Porada, P.; Lenton, T. M.; Pohl, A.; Weber, B.; Mander, L.; Donnadieu, Y.; Beer, C.; Pöschl, U.; Kleidon, A.

2016-01-01

It has been hypothesized that predecessors of today's bryophytes significantly increased global chemical weathering in the Late Ordovician, thus reducing atmospheric CO2 concentration and contributing to climate cooling and an interval of glaciations. Studies that try to quantify the enhancement of weathering by non-vascular vegetation, however, are usually limited to small areas and low numbers of species, which hampers extrapolating to the global scale and to past climatic conditions. Here we present a spatially explicit modelling approach to simulate global weathering by non-vascular vegetation in the Late Ordovician. We estimate a potential global weathering flux of 2.8 (km3 rock) yr−1, defined here as volume of primary minerals affected by chemical transformation. This is around three times larger than today's global chemical weathering flux. Moreover, we find that simulated weathering is highly sensitive to atmospheric CO2 concentration. This implies a strong negative feedback between weathering by non-vascular vegetation and Ordovician climate. PMID:27385026

Improving Secondary Organic Aerosol (SOA) Models using Global Sensitivity Analysis and by Comparison to Chamber Data.

NASA Astrophysics Data System (ADS)

Miller, D. O.; Brune, W. H.

2017-12-01

Accurate estimates of secondary organic aerosol (SOA) from atmospheric models is a major research challenge due to the complexity of the chemical and physical processes involved in the SOA formation and continuous aging. The primary uncertainties of SOA models include those associated with the formation of gas-phase products, the conversion between gas phase and particle phase, the aging mechanisms of SOA, and other processes related to the heterogeneous and particle-phase reactions. To address this challenge, we us a modular modeling framework that combines both simple and near-explicit gas-phase reactions and a two-dimensional volatility basis set (2D-VBS) to simulate the formation and evolution of SOA. Global sensitivity analysis is used to assess the relative importance of the model input parameters. In addition, the model is compared to the measurements from the Focused Isoprene eXperiment at the California Institute of Technology (FIXCIT).

Extended artificial neural networks: incorporation of a priori chemical knowledge enables use of ion selective electrodes for in-situ measurement of ions at environmentally relevant levels.

PubMed

Mueller, Amy V; Hemond, Harold F

2013-12-15

A novel artificial neural network (ANN) architecture is proposed which explicitly incorporates a priori system knowledge, i.e., relationships between output signals, while preserving the unconstrained non-linear function estimator characteristics of the traditional ANN. A method is provided for architecture layout, disabling training on a subset of neurons, and encoding system knowledge into the neuron structure. The novel architecture is applied to raw readings from a chemical sensor multi-probe (electric tongue), comprised of off-the-shelf ion selective electrodes (ISEs), to estimate individual ion concentrations in solutions at environmentally relevant concentrations and containing environmentally representative ion mixtures. Conductivity measurements and the concept of charge balance are incorporated into the ANN structure, resulting in (1) removal of estimation bias typically seen with use of ISEs in mixtures of unknown composition and (2) improvement of signal estimation by an order of magnitude or more for both major and minor constituents relative to use of ISEs as stand-alone sensors and error reduction by 30-50% relative to use of standard ANN models. This method is suggested as an alternative to parameterization of traditional models (e.g., Nikolsky-Eisenman), for which parameters are strongly dependent on both analyte concentration and temperature, and to standard ANN models which have no mechanism for incorporation of system knowledge. Network architecture and weighting are presented for the base case where the dot product can be used to relate ion concentrations to both conductivity and charge balance as well as for an extension to log-normalized data where the model can no longer be represented in this manner. While parameterization in this case study is analyte-dependent, the architecture is generalizable, allowing application of this method to other environmental problems for which mathematical constraints can be explicitly stated. © 2013 Elsevier B.V. All rights reserved.

Reactive Force Fields via Explicit Valency

NASA Astrophysics Data System (ADS)

Kale, Seyit

Computational simulations are invaluable in elucidating the dynamics of biological macromolecules. Unfortunately, reactions present a fundamental challenge. Calculations based on quantum mechanics can predict bond formation and rupture; however they suffer from severe length- and time-limitations. At the other extreme, classical approaches provide orders of magnitude faster simulations; however they regard chemical bonds as immutable entities. A few exceptions exist, but these are not always trivial to adopt for routine use. We bridge this gap by providing a novel, pseudo-classical approach, based on explicit valency. We unpack molecules into valence electron pairs and atomic cores. Particles bear ionic charges and interact via pairwise-only potentials. The potentials are informed of quantum effects in the short-range and obey dissociation limits in the long-range. They are trained against a small set of isolated species, including geometries and thermodynamics of small hydrides and of dimers formed by them. The resulting force field captures the essentials of reactivity, polarizability and flexibility in a simple, seamless setting. We call this model LEWIS, after the chemical theory that inspired the use of valence pairs. Following the introduction in Chapter 1, we initially focus on the properties of water. Chapter 2 considers gas phase clusters. To transition to the liquid phase, Chapter 3 describes a novel pairwise long-range compensation that performs comparably to infinite lattice summations. The approach is suited to ionic solutions in general. In Chapters 4 and 5, LEWIS is shown to correctly predict the dipolar and quadrupolar response in bulk liquid, and can accommodate proton transfers in both acid and base. Efficiency permits the study of proton defects at dilutions not accessible to experiment or quantum mechanics. Chapter 6 discusses explicit valency approaches in other hydrides, forming the basis of a reactive organic force field. Examples of simple proton transfer and more complex reactions are discussed. Chapter 7 provides a framework for variable electron spread. This addition resolves some of the inherent limitations of the former model which implicitly assumed that electron spread was not affected by the environment. A brief summary is provided in Chapter 8.

The importance of the external potential on group electronegativity.

PubMed

Leyssens, Tom; Geerlings, Paul; Peeters, Daniel

2005-11-03

The electronegativity of groups placed in a molecular environment is obtained using CCSD calculations of the electron affinity and ionization energy. A point charge model is used as an approximation of the molecular environment. The electronegativity values obtained in the presence of a point charge model are compared to the isolated group property to estimate the importance of the external potential on the group's electronegativity. The validity of the "group in molecule" electronegativities is verified by comparing EEM (electronegativity equalization method) charge transfer values to the explicitly calculated natural population analysis (NPA) ones, as well as by comparing the variation in electronegativity between the isolated functional group and the functional group in the presence of a modeled environment with the variation based on a perturbation expansion of the chemical potential.

Exact results in the large system size limit for the dynamics of the chemical master equation, a one dimensional chain of equations.

PubMed

Martirosyan, A; Saakian, David B

2011-08-01

We apply the Hamilton-Jacobi equation (HJE) formalism to solve the dynamics of the chemical master equation (CME). We found exact analytical expressions (in large system-size limit) for the probability distribution, including explicit expression for the dynamics of variance of distribution. We also give the solution for some simple cases of the model with time-dependent rates. We derived the results of the Van Kampen method from the HJE approach using a special ansatz. Using the Van Kampen method, we give a system of ordinary differential equations (ODEs) to define the variance in a two-dimensional case. We performed numerics for the CME with stationary noise. We give analytical criteria for the disappearance of bistability in the case of stationary noise in one-dimensional CMEs.

Effects of magnetic, radiation and chemical reaction on unsteady heat and mass transfer flow of an oscillating cylinder

NASA Astrophysics Data System (ADS)

Ahmed, Rubel; Rana, B. M. Jewel; Ahmmed, S. F.

2017-06-01

The effects of magnetic, radiation and chemical reaction parameters on the unsteady heat and mass transfer boundary layer flow past an oscillating cylinder is considered. The dimensionless momentum, energy and concentration equations are solved numerically by using explicit finite difference method with the help of a computer programming language Compaq visual FORTRAN 6.6a. The obtained results of this study have been discussed for different values of well-known parameters with different time steps. The effect of these parameters on the velocity field, temperature field and concentration field, skin-friction, Nusselt number, streamlines and isotherms has been studied and results are presented by graphically represented by the tabular form quantitatively. The stability and convergence analysis of the solution parameters that have been used in the mathematical model have been tested.

Effects of Explicit Instructions, Metacognition, and Motivation on Creative Performance

ERIC Educational Resources Information Center

Hong, Eunsook; O'Neil, Harold F.; Peng, Yun

2016-01-01

Effects of explicit instructions, metacognition, and intrinsic motivation on creative homework performance were examined in 303 Chinese 10th-grade students. Models that represent hypothesized relations among these constructs and trait covariates were tested using structural equation modelling. Explicit instructions geared to originality were…

The History of Chemistry. The Case of the Supposed Isomerism of the Hydrocarbon Ethane in the Construction of Knowledge: Implications for Chemical Education.

ERIC Educational Resources Information Center

Cross, Roger T.; Price, Ronald F.

2001-01-01

Contends that chemical education proposals for changing the conception of chemistry literacy should include making explicit the relationship between chemistry as science and chemistry as technology. Illustrates the importance of distinguishing between scientific and technological activities by explaining the events and processes that are…

Superfluid transition in the attractive Hofstadter-Hubbard model

NASA Astrophysics Data System (ADS)

Umucalılar, R. O.; Iskin, M.

2016-08-01

We consider a Fermi gas that is loaded onto a square optical lattice and subjected to a perpendicular artificial magnetic field, and determine its superfluid transition boundary by adopting a BCS-like mean-field approach in momentum space. The multiband structure of the single-particle Hofstadter spectrum is taken explicitly into account while deriving a generalized pairing equation. We present the numerical solutions as functions of the artificial magnetic flux, interaction strength, Zeeman field, chemical potential, and temperature, with a special emphasis on the roles played by the density of single-particle states and center-of-mass momentum of Cooper pairs.

Aromatic ring generation as a dust precursor in acetylene discharges

NASA Astrophysics Data System (ADS)

De Bleecker, Kathleen; Bogaerts, Annemie; Goedheer, Wim

2006-04-01

Production of aromatic hydrocarbon compounds as an intermediate step for particle formation in low-pressure acetylene discharges is investigated via a kinetic approach. The detailed chemical reaction mechanism contains 140 reactions among 55 species. The cyclic hydrocarbon chemistry is mainly based on studies of polycyclic aromatic hydrocarbon formation in cosmic environments. The model explicitly includes organic chain, cyclic molecules, radicals, and ions up to a size of 12 carbon atoms. The calculated density profiles show that the aromatic formation yields are quite significant, suggesting that aromatic compounds play a role in the underlying mechanisms of particle formation in hydrocarbon plasmas.

Mean field treatment of heterogeneous steady state kinetics

NASA Astrophysics Data System (ADS)

Geva, Nadav; Vaissier, Valerie; Shepherd, James; Van Voorhis, Troy

2017-10-01

We propose a method to quickly compute steady state populations of species undergoing a set of chemical reactions whose rate constants are heterogeneous. Using an average environment in place of an explicit nearest neighbor configuration, we obtain a set of equations describing a single fluctuating active site in the presence of an averaged bath. We apply this Mean Field Steady State (MFSS) method to a model of H2 production on a disordered surface for which the activation energy for the reaction varies from site to site. The MFSS populations quantitatively reproduce the KMC results across the range of rate parameters considered.

Invasion waves in the biochemical warfare between living organisms

NASA Astrophysics Data System (ADS)

Carvalho, S. A.; Martins, M. L.

2018-04-01

Microorganisms and plants very commonly release toxic secondary chemical compounds (allelochemicals) that inhibit or kill sensitive strains or individuals from their own or other species. In this work we study a model that describes two species interacting through allelopathic suppression and competing for resources. Employing linear stability analysis, the conditions for coexistence or extinction of species in spatially homogeneous systems were determined. We found that the borders between the regimes of bistability, coexistence, and the extinction of the weaker by the stronger competitor, are altered by allelopathic interactions. In addition, traveling wave solutions for one species invasion were obtained considering the spatially explicit nature of the model. Our findings indicate that the minimum speed of the invasion wavefronts depends primarily on the competition coefficients and the parameters characterizing the species' functional responses to their allelochemicals. As a general rule, the species provided with the most effective chemical weapons dominates the population dynamics. Finally, we found a tristability at the coexistence region due to the combination of allelopathy and patchy population distributions in space. So, our model provides a distinct mechanism, independent of social behaviors, that produces such unexpected tristability impossible in classical competition models involving one-to-one individual interactions.

Invasion waves in the biochemical warfare between living organisms.

PubMed

Carvalho, S A; Martins, M L

2018-04-01

Microorganisms and plants very commonly release toxic secondary chemical compounds (allelochemicals) that inhibit or kill sensitive strains or individuals from their own or other species. In this work we study a model that describes two species interacting through allelopathic suppression and competing for resources. Employing linear stability analysis, the conditions for coexistence or extinction of species in spatially homogeneous systems were determined. We found that the borders between the regimes of bistability, coexistence, and the extinction of the weaker by the stronger competitor, are altered by allelopathic interactions. In addition, traveling wave solutions for one species invasion were obtained considering the spatially explicit nature of the model. Our findings indicate that the minimum speed of the invasion wavefronts depends primarily on the competition coefficients and the parameters characterizing the species' functional responses to their allelochemicals. As a general rule, the species provided with the most effective chemical weapons dominates the population dynamics. Finally, we found a tristability at the coexistence region due to the combination of allelopathy and patchy population distributions in space. So, our model provides a distinct mechanism, independent of social behaviors, that produces such unexpected tristability impossible in classical competition models involving one-to-one individual interactions.

Evaluation of modeled cloud chemistry mechanism against laboratory irradiation experiments: The HxOy/iron/carboxylic acid chemical system

NASA Astrophysics Data System (ADS)

Long, Yoann; Charbouillot, Tiffany; Brigante, Marcello; Mailhot, Gilles; Delort, Anne-Marie; Chaumerliac, Nadine; Deguillaume, Laurent

2013-10-01

Currently, cloud chemistry models are including more detailed and explicit multiphase mechanisms based on laboratory experiments that determine such values as kinetic constants, stability constants of complexes and hydration constants. However, these models are still subject to many uncertainties related to the aqueous chemical mechanism they used. Particularly, the role of oxidants such as iron and hydrogen peroxide in the oxidative capacity of the cloud aqueous phase has typically never been validated against laboratory experimental data. To fill this gap, we adapted the M2C2 model (Model of Multiphase Cloud Chemistry) to simulate irradiation experiments on synthetic aqueous solutions under controlled conditions (e.g., pH, temperature, light intensity) and for actual cloud water samples. Various chemical compounds that purportedly contribute to the oxidative budget in cloud water (i.e., iron, oxidants, such as hydrogen peroxide: H2O2) were considered. Organic compounds (oxalic, formic and acetic acids) were taken into account as target species because they have the potential to form iron complexes and are good indicators of the oxidative capacity of the cloud aqueous phase via their oxidation in this medium. The range of concentrations for all of the chemical compounds evaluated was representative of in situ measurements. Numerical outputs were compared with experimental data that consisted of a time evolution of the concentrations of the target species. The chemical mechanism in the model describing the “oxidative engine” of the HxOy/iron (HxOy = H2O2, HO2rad /O2rad - and HOrad ) chemical system was consistent with laboratory measurements. Thus, the degradation of the carboxylic acids evaluated was closely reproduced by the model. However, photolysis of the Fe(C2O4)+ complex needs to be considered in cloud chemistry models for polluted conditions (i.e., acidic pH) to correctly reproduce oxalic acid degradation. We also show that iron and formic acid lead to a stable complex whose photoreactivity has currently not been investigated. The updated aqueous chemical mechanism was compared with data from irradiation experiments using natural cloud water. The new reactions considered in the model (i.e., iron complex formation with oxalic and formic acids) correctly reproduced the experimental observations.

The mathematical properties of the quasi-chemical model for microorganism growth-death kinetics in foods.

PubMed

Ross, E W; Taub, I A; Doona, C J; Feeherry, F E; Kustin, K

2005-03-15

Knowledge of the mathematical properties of the quasi-chemical model [Taub, Feeherry, Ross, Kustin, Doona, 2003. A quasi-chemical kinetics model for the growth and death of Staphylococcus aureus in intermediate moisture bread. J. Food Sci. 68 (8), 2530-2537], which is used to characterize and predict microbial growth-death kinetics in foods, is important for its applications in predictive microbiology. The model consists of a system of four ordinary differential equations (ODEs), which govern the temporal dependence of the bacterial life cycle (the lag, exponential growth, stationary, and death phases, respectively). The ODE system derives from a hypothetical four-step reaction scheme that postulates the activity of a critical intermediate as an antagonist to growth (perhaps through a quorum sensing biomechanism). The general behavior of the solutions to the ODEs is illustrated by several examples. In instances when explicit mathematical solutions to these ODEs are not obtainable, mathematical approximations are used to find solutions that are helpful in evaluating growth in the early stages and again near the end of the process. Useful solutions for the ODE system are also obtained in the case where the rate of antagonist formation is small. The examples and the approximate solutions provide guidance in the parameter estimation that must be done when fitting the model to data. The general behavior of the solutions is illustrated by examples, and the MATLAB programs with worked examples are included in the appendices for use by predictive microbiologists for data collected independently.

Improvement, Verification, and Refinement of Spatially-Explicit Exposure Models in Risk Assessment - FishRand Spatially-Explicit Bioaccumulation Model Demonstration

DTIC Science & Technology

2015-08-01

21  Figure 4. Data-based proportion of DDD , DDE and DDT in total DDx in fish and sediment by... DDD dichlorodiphenyldichloroethane DDE dichlorodiphenyldichloroethylene DDT dichlorodiphenyltrichloroethane DoD Department of Defense ERM... DDD ) at the other site. The spatially-explicit model consistently predicts tissue concentrations that closely match both the average and the

Intuitive, but not simple: including explicit water molecules in protein-protein docking simulations improves model quality.

PubMed

Parikh, Hardik I; Kellogg, Glen E

2014-06-01

Characterizing the nature of interaction between proteins that have not been experimentally cocrystallized requires a computational docking approach that can successfully predict the spatial conformation adopted in the complex. In this work, the Hydropathic INTeractions (HINT) force field model was used for scoring docked models in a data set of 30 high-resolution crystallographically characterized "dry" protein-protein complexes and was shown to reliably identify native-like models. However, most current protein-protein docking algorithms fail to explicitly account for water molecules involved in bridging interactions that mediate and stabilize the association of the protein partners, so we used HINT to illuminate the physical and chemical properties of bridging waters and account for their energetic stabilizing contributions. The HINT water Relevance metric identified the "truly" bridging waters at the 30 protein-protein interfaces and we utilized them in "solvated" docking by manually inserting them into the input files for the rigid body ZDOCK program. By accounting for these interfacial waters, a statistically significant improvement of ∼24% in the average hit-count within the top-10 predictions the protein-protein dataset was seen, compared to standard "dry" docking. The results also show scoring improvement, with medium and high accuracy models ranking much better than incorrect ones. These improvements can be attributed to the physical presence of water molecules that alter surface properties and better represent native shape and hydropathic complementarity between interacting partners, with concomitantly more accurate native-like structure predictions. © 2013 Wiley Periodicals, Inc.

Geo-referenced multimedia environmental fate model (G-CIEMS): model formulation and comparison to the generic model and monitoring approaches.

PubMed

Suzuki, Noriyuki; Murasawa, Kaori; Sakurai, Takeo; Nansai, Keisuke; Matsuhashi, Keisuke; Moriguchi, Yuichi; Tanabe, Kiyoshi; Nakasugi, Osami; Morita, Masatoshi

2004-11-01

A spatially resolved and geo-referenced dynamic multimedia environmental fate model, G-CIEMS (Grid-Catchment Integrated Environmental Modeling System) was developed on a geographical information system (GIS). The case study for Japan based on the air grid cells of 5 x 5 km resolution and catchments with an average area of 9.3 km2, which corresponds to about 40,000 air grid cells and 38,000 river segments/catchment polygons, were performed for dioxins, benzene, 1,3-butadiene, and di-(2-ethyhexyl)phthalate. The averaged concentration of the model and monitoring output were within a factor of 2-3 for all the media. Outputs from G-CIEMS and the generic model were essentially comparable when identical parameters were employed, whereas the G-CIEMS model gave explicit information of distribution of chemicals in the environment. Exposure-weighted averaged concentrations (EWAC) in air were calculated to estimate the exposure ofthe population, based on the results of generic, G-CIEMS, and monitoring approaches. The G-CIEMS approach showed significantly better agreement with the monitoring-derived EWAC than the generic model approach. Implication for the use of a geo-referenced modeling approach in the risk assessment scheme is discussed as a generic-spatial approach, which can be used to provide more accurate exposure estimation with distribution information, using generally available data sources for a wide range of chemicals.

Prediction of Complex Aerodynamic Flows with Explicit Algebraic Stress Models

NASA Technical Reports Server (NTRS)

Abid, Ridha; Morrison, Joseph H.; Gatski, Thomas B.; Speziale, Charles G.

1996-01-01

An explicit algebraic stress equation, developed by Gatski and Speziale, is used in the framework of K-epsilon formulation to predict complex aerodynamic turbulent flows. The nonequilibrium effects are modeled through coefficients that depend nonlinearly on both rotational and irrotational strains. The proposed model was implemented in the ISAAC Navier-Stokes code. Comparisons with the experimental data are presented which clearly demonstrate that explicit algebraic stress models can predict the correct response to nonequilibrium flow.

Program SPACECAP: software for estimating animal density using spatially explicit capture-recapture models

USGS Publications Warehouse

Gopalaswamy, Arjun M.; Royle, J. Andrew; Hines, James E.; Singh, Pallavi; Jathanna, Devcharan; Kumar, N. Samba; Karanth, K. Ullas

2012-01-01

1. The advent of spatially explicit capture-recapture models is changing the way ecologists analyse capture-recapture data. However, the advantages offered by these new models are not fully exploited because they can be difficult to implement. 2. To address this need, we developed a user-friendly software package, created within the R programming environment, called SPACECAP. This package implements Bayesian spatially explicit hierarchical models to analyse spatial capture-recapture data. 3. Given that a large number of field biologists prefer software with graphical user interfaces for analysing their data, SPACECAP is particularly useful as a tool to increase the adoption of Bayesian spatially explicit capture-recapture methods in practice.

The role of chemistry in under-predictions of NO2 in the upper troposphere

NASA Astrophysics Data System (ADS)

Henderson, B. H.; Pinder, R. W.; Goliff, W. S.; Stockwell, W. R.; Fahr, A.; Sarwar, G.; Hutzell, W. T.; Mathur, R.; Vizuete, W.; Cohen, R. C.

2009-12-01

Global and regional atmospheric models under-predict upper troposphere NO2 compared to satellite and aircraft observations. The upper tropospheric under-prediction of NO2 could be a function of emissions, transport, chemistry or some combination. Previous researchers have linked poor performance in the model to over-prediction of the OH and under-prediction of the HO2 by chemistry (Olson et al. 2006, Bertram et al. 2007). This study isolates upper tropospheric chemistry to evaluate the chemical contribution to NO2 under-predictions and to diagnose OH and HO2 discrepancies.

We use a 0-dimensional time dependent model to evaluate seven chemical mechanisms. Because chamber data representing upper tropospheric conditions does not exist, we evaluate the predictions based against an observation-based aging model. Following Bertram et al (2007), we use the NOx:HNO3 ratio to categorize the chemical age of thousands of 10 second average observations between 8 and 10km. Measurements of 10 inorganics and 32 hydrocarbons are translated to model species for each of seven chemical mechanisms. We chose mechanisms ranging from condensed to semi-explicit. The seven mechanisms' design scopes range from urban to global scale. Results include simulations from Model for OZone And Related chemical Tracers (MOZART), Carbon Bond 05 (CB05), State Air Pollution Research Center (SAPRC) 99, SAPRC 07, GEOS-Chem, Regional Atmospheric Chemical Mechanism version 2, and the LEEDS Master Chemical Mechanism.

Results from each chemical mechanism are compared to aircraft observations and to those obtained with other chemical mechanisms. Each mechanism is then further evaluated using integrated reaction rate analysis to identify sources of NO2 bias. We find that the largest contributors to the NO2 bias are over-predictions of PAN and HNO3. The formation of PAN is sensitive to the acetone photolysis rate. The conversion of NOx to HNO3 is most sensitive to hydroxyl radical concentrations. Hydroxyl radical sources and sinks have been quantified for each chemical mechanism using IRR analysis. Based on our modeling experience and results, we make recommendations for better simulating upper tropospheric photochemistry and we identify future research needs.

Bertram et al. Direct Measurements of the Convective Recycling of the Upper Troposphere. Science (2007)
Olson et al. A reevaluation of airborne HOx observations from NASA field campaigns. J Geophys Res-Atmos (2006) vol. 111 pp. D10301

Connecting Free Energy Surfaces in Implicit and Explicit Solvent: an Efficient Method to Compute Conformational and Solvation Free Energies

PubMed Central

Deng, Nanjie; Zhang, Bin W.; Levy, Ronald M.

2015-01-01

The ability to accurately model solvent effects on free energy surfaces is important for understanding many biophysical processes including protein folding and misfolding, allosteric transitions and protein-ligand binding. Although all-atom simulations in explicit solvent can provide an accurate model for biomolecules in solution, explicit solvent simulations are hampered by the slow equilibration on rugged landscapes containing multiple basins separated by barriers. In many cases, implicit solvent models can be used to significantly speed up the conformational sampling; however, implicit solvent simulations do not fully capture the effects of a molecular solvent, and this can lead to loss of accuracy in the estimated free energies. Here we introduce a new approach to compute free energy changes in which the molecular details of explicit solvent simulations are retained while also taking advantage of the speed of the implicit solvent simulations. In this approach, the slow equilibration in explicit solvent, due to the long waiting times before barrier crossing, is avoided by using a thermodynamic cycle which connects the free energy basins in implicit solvent and explicit solvent using a localized decoupling scheme. We test this method by computing conformational free energy differences and solvation free energies of the model system alanine dipeptide in water. The free energy changes between basins in explicit solvent calculated using fully explicit solvent paths agree with the corresponding free energy differences obtained using the implicit/explicit thermodynamic cycle to within 0.3 kcal/mol out of ~3 kcal/mol at only ~8 % of the computational cost. We note that WHAM methods can be used to further improve the efficiency and accuracy of the explicit/implicit thermodynamic cycle. PMID:26236174

Connecting free energy surfaces in implicit and explicit solvent: an efficient method to compute conformational and solvation free energies.

PubMed

Deng, Nanjie; Zhang, Bin W; Levy, Ronald M

2015-06-09

The ability to accurately model solvent effects on free energy surfaces is important for understanding many biophysical processes including protein folding and misfolding, allosteric transitions, and protein–ligand binding. Although all-atom simulations in explicit solvent can provide an accurate model for biomolecules in solution, explicit solvent simulations are hampered by the slow equilibration on rugged landscapes containing multiple basins separated by barriers. In many cases, implicit solvent models can be used to significantly speed up the conformational sampling; however, implicit solvent simulations do not fully capture the effects of a molecular solvent, and this can lead to loss of accuracy in the estimated free energies. Here we introduce a new approach to compute free energy changes in which the molecular details of explicit solvent simulations are retained while also taking advantage of the speed of the implicit solvent simulations. In this approach, the slow equilibration in explicit solvent, due to the long waiting times before barrier crossing, is avoided by using a thermodynamic cycle which connects the free energy basins in implicit solvent and explicit solvent using a localized decoupling scheme. We test this method by computing conformational free energy differences and solvation free energies of the model system alanine dipeptide in water. The free energy changes between basins in explicit solvent calculated using fully explicit solvent paths agree with the corresponding free energy differences obtained using the implicit/explicit thermodynamic cycle to within 0.3 kcal/mol out of ∼3 kcal/mol at only ∼8% of the computational cost. We note that WHAM methods can be used to further improve the efficiency and accuracy of the implicit/explicit thermodynamic cycle.

Fractional Stochastic Field Theory

NASA Astrophysics Data System (ADS)

Honkonen, Juha

2018-02-01

Models describing evolution of physical, chemical, biological, social and financial processes are often formulated as differential equations with the understanding that they are large-scale equations for averages of quantities describing intrinsically random processes. Explicit account of randomness may lead to significant changes in the asymptotic behaviour (anomalous scaling) in such models especially in low spatial dimensions, which in many cases may be captured with the use of the renormalization group. Anomalous scaling and memory effects may also be introduced with the use of fractional derivatives and fractional noise. Construction of renormalized stochastic field theory with fractional derivatives and fractional noise in the underlying stochastic differential equations and master equations and the interplay between fluctuation-induced and built-in anomalous scaling behaviour is reviewed and discussed.

A microgenetic study of learning about the molecular theory of matter and chemical reactions

NASA Astrophysics Data System (ADS)

Chinn, Clark Allen

This paper reports the results of an experimental microgenetic study of children learning complex knowledge from text and experiments. The study had two goals. The first was to investigate fine-grained, moment-to-moment changes in knowledge as middle-school students learned about molecules and chemical reactions over thirteen sessions. The second was to investigate the effects of two instructional treatments, one using implicit textbook explanations and one using explicit explanations developed according to a theory of how scientific knowledge is structured. In the study, 61 sixth- and seventh-graders worked one on one with undergraduate instructors in eleven sessions of about 50 to 80 minutes. The instructors guided the students in conducting experiments and thinking out loud about texts. Topics studied included molecules, states of matter, chemical reactions, and heat transfer. A dense array of questions provided a detailed picture of children's moment-to-moment and day-to-day changes in knowledge. Three results chapters address students' preinstructional knowledge, the effects of the experimental treatment at posttest, and five detailed case studies of students' step-by-step knowledge change over eleven sessions. The chapter on preinstructional knowledge discussed three aspects of global knowledge change: conceptual change, coherence, and entrenchment. Notably, this chapter provides systematic evidence that children's knowledge was fragmented and that consistency with general unifying principles did not guarantee a highly coherent body of knowledge. The experimental manipulation revealed a strong advantage for explicit explanations over implicit textbook explanations. Multiple explicit explanations (e.g., highly explicit explanations of three or four chemical reactions) appeared to be necessary for students to master key concepts. Microgenetic analyses of five cases addressed eight empirical issues that should be addressed by any theory of knowledge acquisition: (a) the nature of the overall knowledge change, (b) the progression of intermediate states during knowledge change, (c) initiators of knowledge change, (d) interactions of prior background knowledge and prior domain knowledge during knowledge changes, (e) the fate of old and new knowledge, (f) the relationship between belief and knowledge, (g) changes in meta-awareness, and (h) factors that influenced the course of knowledge change.

Numerical simulation of electromagnetic wave attenuation in a nonequilibrium chemically reacting hypervelocity flow

NASA Astrophysics Data System (ADS)

Nusca, Michael Joseph, Jr.

The effects of various gasdynamic phenomena on the attenuation of an electromagnetic wave propagating through the nonequilibrium chemically reacting air flow field generated by an aerodynamic body travelling at high velocity is investigated. The nonequilibrium flow field is assumed to consist of seven species including nitric oxide ions and free electrons. The ionization of oxygen and nitrogen atoms is ignored. The aerodynamic body considered is a blunt wedge. The nonequilibrium chemically reacting flow field around this body is numerically simulated using a computer code based on computational fluid dynamics. The computer code solves the Navier-Stokes equations including mass diffusion and heat transfer, using a time-marching, explicit Runge-Kutta scheme. A nonequilibrium air kinetics model consisting of seven species and twenty-eight reactions as well as an equilibrium air model consisting of the same seven species are used. The body surface boundaries are considered as adiabatic or isothermal walls, as well as fully-catalytic and non-catalytic surfaces. Both laminar and turbulent flows are considered; wall generated flow turbulence is simulated using an algebraic mixing length model. An electromagnetic wave is considered as originating from an antenna within the body and is effected by the free electrons in the chemically reacting flow. Analysis of the electromagnetics is performed separately from the fluid dynamic analysis using a series solution of Maxwell's equations valid for the propagation of a long-wavelength plane electromagnetic wave through a thin (i.e., in comparison to wavelength) inhomogeneous plasma layer. The plasma layer is the chemically reacting shock layer around the body. The Navier-Stokes equations are uncoupled from Maxwell's equations. The results of this computational study demonstrate for the first time and in a systematic fashion, the importance of several parameters including equilibrium chemistry, nonequilibrium chemical kinetics, the reaction mechanism, flow viscosity, mass diffusion, and wall boundary conditions on modeling wave attenuation resulting from the interaction of an electromagnetic wave with an aerodynamic plasma. Comparison is made with experimental data.

Chemical and biochemical thermodynamics: Is it time for a reunification?

PubMed

Iotti, Stefano; Raff, Lionel; Sabatini, Antonio

2017-02-01

The thermodynamics of chemical reactions in which all species are explicitly considered with atoms and charge balanced is compared with the transformed thermodynamics generally used to treat biochemical reactions where atoms and charges are not balanced. The transformed thermodynamic quantities suggested by Alberty are obtained by execution of Legendre transformation of the usual thermodynamic potentials. The present analysis demonstrates that the transformed values for Δ r G' 0 and Δ r H' 0 can be obtained directly without performing Legendre transformations by simply writing the chemical reactions with all the pseudoisomers explicitly included and charges balanced. The appropriate procedures for computing the stoichiometric coefficients for the pseudoisomers are fully explained by means of an example calculation for the biochemical ATP hydrolysis reaction. It is concluded that the analysis has reunited the "two separate worlds" of conventional thermodynamics and transformed thermodynamics. In addition, it is also shown that the value of the conditional Gibbs energy of reaction, Δ r G', for a biochemical reaction is the same of the value of Δ r G for any chemical reaction involving pseudoisomers of the biochemical reagents. Copyright © 2016 Elsevier B.V. All rights reserved.

Analysis of composite ablators using massively parallel computation

NASA Technical Reports Server (NTRS)

Shia, David

1995-01-01

In this work, the feasibility of using massively parallel computation to study the response of ablative materials is investigated. Explicit and implicit finite difference methods are used on a massively parallel computer, the Thinking Machines CM-5. The governing equations are a set of nonlinear partial differential equations. The governing equations are developed for three sample problems: (1) transpiration cooling, (2) ablative composite plate, and (3) restrained thermal growth testing. The transpiration cooling problem is solved using a solution scheme based solely on the explicit finite difference method. The results are compared with available analytical steady-state through-thickness temperature and pressure distributions and good agreement between the numerical and analytical solutions is found. It is also found that a solution scheme based on the explicit finite difference method has the following advantages: incorporates complex physics easily, results in a simple algorithm, and is easily parallelizable. However, a solution scheme of this kind needs very small time steps to maintain stability. A solution scheme based on the implicit finite difference method has the advantage that it does not require very small times steps to maintain stability. However, this kind of solution scheme has the disadvantages that complex physics cannot be easily incorporated into the algorithm and that the solution scheme is difficult to parallelize. A hybrid solution scheme is then developed to combine the strengths of the explicit and implicit finite difference methods and minimize their weaknesses. This is achieved by identifying the critical time scale associated with the governing equations and applying the appropriate finite difference method according to this critical time scale. The hybrid solution scheme is then applied to the ablative composite plate and restrained thermal growth problems. The gas storage term is included in the explicit pressure calculation of both problems. Results from ablative composite plate problems are compared with previous numerical results which did not include the gas storage term. It is found that the through-thickness temperature distribution is not affected much by the gas storage term. However, the through-thickness pressure and stress distributions, and the extent of chemical reactions are different from the previous numerical results. Two types of chemical reaction models are used in the restrained thermal growth testing problem: (1) pressure-independent Arrhenius type rate equations and (2) pressure-dependent Arrhenius type rate equations. The numerical results are compared to experimental results and the pressure-dependent model is able to capture the trend better than the pressure-independent one. Finally, a performance study is done on the hybrid algorithm using the ablative composite plate problem. It is found that there is a good speedup of performance on the CM-5. For 32 CPU's, the speedup of performance is 20. The efficiency of the algorithm is found to be a function of the size and execution time of a given problem and the effective parallelization of the algorithm. It also seems that there is an optimum number of CPU's to use for a given problem.

Organic photolysis reactions in tropospheric aerosols: effect on secondary organic aerosol formation and lifetime

NASA Astrophysics Data System (ADS)

Hodzic, A.; Madronich, S.; Kasibhatla, P. S.; Tyndall, G.; Aumont, B.; Jimenez, J. L.; Lee-Taylor, J.; Orlando, J.

2015-08-01

This study presents the first modeling estimates of the potential effect of gas- and particle-phase organic photolysis reactions on the formation and lifetime of secondary organic aerosols (SOAs). Typically only photolysis of smaller organic molecules (e.g., formaldehyde) for which explicit data exist is included in chemistry-climate models. Here, we specifically examine the photolysis of larger molecules that actively partition between the gas and particle phases. The chemical mechanism generator GECKO-A is used to explicitly model SOA formation from α-pinene, toluene, and C12 and C16 n-alkane reactions with OH at low and high NOx. Simulations are conducted for typical mid-latitude conditions and a solar zenith angle of 45° (permanent daylight). The results show that after 4 days of chemical aging under those conditions (equivalent to 8 days in the summer mid-latitudes), gas-phase photolysis leads to a moderate decrease in SOA yields, i.e., ~15 % (low NOx) to ~45 % (high NOx) for α-pinene, ~15 % for toluene, ~25 % for C12 n-alkane, and ~10 % for C16 n-alkane. The small effect of gas-phase photolysis on low-volatility n-alkanes such as C16 n-alkane is due to the rapid partitioning of early-generation products to the particle phase, where they are protected from gas-phase photolysis. Minor changes are found in the volatility distribution of organic products and in oxygen to carbon ratios. The decrease in SOA mass is increasingly more important after a day of chemical processing, suggesting that most laboratory experiments are likely too short to quantify the effect of gas-phase photolysis on SOA yields. Our results also suggest that many molecules containing chromophores are preferentially partitioned into the particle phase before they can be photolyzed in the gas phase. Given the growing experimental evidence that these molecules can undergo in-particle photolysis, we performed sensitivity simulations using an empirically estimated SOA photolysis rate of JSOA = 4 × 10-4 JNO2. Modeling results indicate that this photolytic loss rate would decrease SOA mass by 40-60 % for most species after 10 days of equivalent atmospheric aging at mid-latitudes in the summer. It should be noted that in our simulations we do not consider in-particle or aqueous-phase reactions which could modify the chemical composition of the particle and thus the quantity of photolabile species. The atmospheric implications of our results are significant for both the SOA global distribution and lifetime. GEOS-Chem global model results suggest that particle-phase photolytic reactions could be an important loss process for SOA in the atmosphere, removing aerosols from the troposphere on timescales of less than 7 days that are comparable to wet deposition.

Organic photolysis reactions in tropospheric aerosols: effect on secondary organic aerosol formation and lifetime

NASA Astrophysics Data System (ADS)

Hodzic, A.; Madronich, S.; Kasibhatla, P. S.; Tyndall, G.; Aumont, B.; Jimenez, J. L.; Lee-Taylor, J.; Orlando, J.

2015-03-01

This study presents the first modeling estimates of the potential effect of gas- and particle-phase organic photolysis reactions on the formation and lifetime of secondary organic aerosols (SOA). Typically only photolysis of smaller organic molecules (e.g. formaldehyde) for which explicit data exist is included in chemistry-climate models. Here, we specifically examine the photolysis of larger molecules that actively partition between the gas and particle phases. The chemical mechanism generator GECKO-A is used to explicitly model SOA formation from α-pinene, toluene, and C12 and C16 n-alkane reactions with OH at low- and high-NOx. Simulations are conducted for typical mid-latitude conditions and a solar zenith angle of 45° (permanent daylight). The results show that after four days of chemical aging under those conditions (equivalent to eight days in the summer mid-latitudes), gas-phase photolysis leads to a moderate decrease in SOA yields i.e ~15% (low-NOx) to ~45% (high-NOx) for α-pinene, ~15% for toluene, ~25% for C12-alkane, and ~10% for C16-alkane. The small effect on low volatility n-alkanes such as C16-alkane is due to the rapid partitioning of early-generation products to the particle phase where they are assumed to be protected from gas-phase photolysis. Minor changes are found in the volatility distribution of organic products and in oxygen to carbon ratios. The decrease in SOA mass seems increasingly more important after a day of chemical processing, suggesting that most laboratory experiments are likely too short to quantify the effect of gas-phase photolysis on SOA yields. Our results also suggest that many molecules containing chromophores are preferentially partitioned into the particle phase before they can be photolyzed in the gas-phase. Given the growing experimental evidence that these molecules can undergo in-particle photolysis, we performed sensitivity simulations using an estimated SOA photolysis rate of JSOA=4 x 10-4JNO2. Modeling results indicate that this photolytic loss rate would decrease SOA mass by 40-60% for most species after ten days of equivalent atmospheric aging at mid-latitudes in the summer. It should be noted that in our simulations we do not consider in-particle or aqueous-phase reactions which could modify the chemical composition of the particle, and thus the amount of photolabile species. The atmospheric implications of our results are significant for both the SOA global distribution and lifetime. GEOS-Chem global model results suggest that particle-phase photolytic reactions could be an important loss process for SOA in the atmosphere, removing aerosols from the troposphere on timescales (less than 7 days) that are comparable to wet deposition.

Diffusion-controlled reactions modeling in Geant4-DNA

NASA Astrophysics Data System (ADS)

Karamitros, M.; Luan, S.; Bernal, M. A.; Allison, J.; Baldacchino, G.; Davidkova, M.; Francis, Z.; Friedland, W.; Ivantchenko, V.; Ivantchenko, A.; Mantero, A.; Nieminem, P.; Santin, G.; Tran, H. N.; Stepan, V.; Incerti, S.

2014-10-01

Context Under irradiation, a biological system undergoes a cascade of chemical reactions that can lead to an alteration of its normal operation. There are different types of radiation and many competing reactions. As a result the kinetics of chemical species is extremely complex. The simulation becomes then a powerful tool which, by describing the basic principles of chemical reactions, can reveal the dynamics of the macroscopic system. To understand the dynamics of biological systems under radiation, since the 80s there have been on-going efforts carried out by several research groups to establish a mechanistic model that consists in describing all the physical, chemical and biological phenomena following the irradiation of single cells. This approach is generally divided into a succession of stages that follow each other in time: (1) the physical stage, where the ionizing particles interact directly with the biological material; (2) the physico-chemical stage, where the targeted molecules release their energy by dissociating, creating new chemical species; (3) the chemical stage, where the new chemical species interact with each other or with the biomolecules; (4) the biological stage, where the repairing mechanisms of the cell come into play. This article focuses on the modeling of the chemical stage. Method This article presents a general method of speeding-up chemical reaction simulations in fluids based on the Smoluchowski equation and Monte-Carlo methods, where all molecules are explicitly simulated and the solvent is treated as a continuum. The model describes diffusion-controlled reactions. This method has been implemented in Geant4-DNA. The keys to the new algorithm include: (1) the combination of a method to compute time steps dynamically with a Brownian bridge process to account for chemical reactions, which avoids costly fixed time step simulations; (2) a k-d tree data structure for quickly locating, for a given molecule, its closest reactants. The performance advantage is presented in terms of complexity, and the accuracy of the new algorithm is demonstrated by simulating radiation chemistry in the context of the Geant4-DNA project. Application The time-dependent radiolytic yields of the main chemical species formed after irradiation are computed for incident protons at different energies (from 50 MeV to 500 keV). Both the time-evolution and energy dependency of the yields are discussed. The evolution, at one microsecond, of the yields of hydroxyls and solvated electrons with respect to the linear energy transfer is compared to theoretical and experimental data. According to our results, at high linear energy transfer, modeling radiation chemistry in the trading compartment representation might be adopted.

Chemical evolution of Local Group dwarf galaxies in a cosmological context - I. A new modelling approach and its application to the Sculptor dwarf spheroidal galaxy

NASA Astrophysics Data System (ADS)

Romano, Donatella; Starkenburg, Else

2013-09-01

We present a new approach for chemical evolution modelling, specifically designed to investigate the chemical properties of dwarf galaxies in a full cosmological framework. In particular, we focus on the Sculptor dwarf spheroidal galaxy, for which a wealth of observational data exists, as a test bed for our model. We select four candidate Sculptor-like galaxies from the satellite galaxy catalogue generated by implementation of a version of the Munich semi-analytic model for galaxy formation on the level 2 Aquarius dark matter simulations and use the mass assembly and star formation histories predicted for these four systems as an input for the chemical evolution code. We follow explicitly the evolution of several chemical elements, both in the cold gas out of which the stars form and in the hot medium residing in the halo. We take into account in detail the lifetimes of stars of different initial masses, the distribution of the delay times for Type Ia supernova explosions and the dependence of the stellar yields from the initial metallicity of the stars. We allow large fractions of metals to be deposited into the hot phase, either directly as stars die or through reheated gas flows powered by supernova explosions. We find that, in order to reproduce both the observed metallicity distribution function and the observed abundance ratios of long-lived stars of Sculptor, large fractions of the reheated metals must never re-enter regions of active star formation. With this prescription, all the four analogues to the Sculptor dwarf spheroidal galaxy extracted from the simulated satellites catalogue on the basis of luminosity and stellar population ages are found to reasonably match the detailed chemical properties of real Sculptor stars. However, all model galaxies do severely underestimate the fraction of very metal poor stars observed in Sculptor. Our analysis thus sets further constraints on the semi-analytical models and, at large, on possible metal enrichment scenarios for the Sculptor dwarf spheroidal galaxy.

Computationally Efficient Multiconfigurational Reactive Molecular Dynamics

PubMed Central

Yamashita, Takefumi; Peng, Yuxing; Knight, Chris; Voth, Gregory A.

2012-01-01

It is a computationally demanding task to explicitly simulate the electronic degrees of freedom in a system to observe the chemical transformations of interest, while at the same time sampling the time and length scales required to converge statistical properties and thus reduce artifacts due to initial conditions, finite-size effects, and limited sampling. One solution that significantly reduces the computational expense consists of molecular models in which effective interactions between particles govern the dynamics of the system. If the interaction potentials in these models are developed to reproduce calculated properties from electronic structure calculations and/or ab initio molecular dynamics simulations, then one can calculate accurate properties at a fraction of the computational cost. Multiconfigurational algorithms model the system as a linear combination of several chemical bonding topologies to simulate chemical reactions, also sometimes referred to as “multistate”. These algorithms typically utilize energy and force calculations already found in popular molecular dynamics software packages, thus facilitating their implementation without significant changes to the structure of the code. However, the evaluation of energies and forces for several bonding topologies per simulation step can lead to poor computational efficiency if redundancy is not efficiently removed, particularly with respect to the calculation of long-ranged Coulombic interactions. This paper presents accurate approximations (effective long-range interaction and resulting hybrid methods) and multiple-program parallelization strategies for the efficient calculation of electrostatic interactions in reactive molecular simulations. PMID:25100924

Modeling Protein Excited-state Structures from "Over-length" Chemical Cross-links.

PubMed

Ding, Yue-He; Gong, Zhou; Dong, Xu; Liu, Kan; Liu, Zhu; Liu, Chao; He, Si-Min; Dong, Meng-Qiu; Tang, Chun

2017-01-27

Chemical cross-linking coupled with mass spectroscopy (CXMS) provides proximity information for the cross-linked residues and is used increasingly for modeling protein structures. However, experimentally identified cross-links are sometimes incompatible with the known structure of a protein, as the distance calculated between the cross-linked residues far exceeds the maximum length of the cross-linker. The discrepancies may persist even after eliminating potentially false cross-links and excluding intermolecular ones. Thus the "over-length" cross-links may arise from alternative excited-state conformation of the protein. Here we present a method and associated software DynaXL for visualizing the ensemble structures of multidomain proteins based on intramolecular cross-links identified by mass spectrometry with high confidence. Representing the cross-linkers and cross-linking reactions explicitly, we show that the protein excited-state structure can be modeled with as few as two over-length cross-links. We demonstrate the generality of our method with three systems: calmodulin, enzyme I, and glutamine-binding protein, and we show that these proteins alternate between different conformations for interacting with other proteins and ligands. Taken together, the over-length chemical cross-links contain valuable information about protein dynamics, and our findings here illustrate the relationship between dynamic domain movement and protein function. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Modeling free energy availability from Hadean hydrothermal systems to the first metabolism.

PubMed

Simoncini, E; Russell, M J; Kleidon, A

2011-12-01

Off-axis Hydrothermal Systems (HSs) are seen as the possible setting for the emergence of life. As the availability of free energy is a general requirement to drive any form of metabolism, we ask here under which conditions free energy generation by geologic processes is greatest and relate these to the conditions found at off-axis HSs. To do so, we present a conceptual model in which we explicitly capture the energetics of fluid motion and its interaction with exothermic reactions to maintain a state of chemical disequilibrium. Central to the interaction is the temperature at which the exothermic reactions take place. This temperature not only sets the equilibrium constant of the chemical reactions and thereby the distance of the actual state to chemical equilibrium, but these reactions also shape the temperature gradient that drives convection and thereby the advection of reactants to the reaction sites and the removal of the products that relate to geochemical free energy generation. What this conceptual model shows is that the positive feedback between convection and the chemical kinetics that is found at HSs favors a greater rate of free energy generation than in the absence of convection. Because of the lower temperatures and because the temperature of reactions is determined more strongly by these dynamics rather than an external heat flux, the conditions found at off-axis HSs should result in the greatest rates of geochemical free energy generation. Hence, we hypothesize from these thermodynamic considerations that off-axis HSs seem most conducive for the emergence of protometabolic pathways as these provide the greatest, abiotic generation rates of chemical free energy.

Impacts of New Particle Formation on Midwestern Climate and Air Quality as Determined by the NPF-explicit WRF-Chem

NASA Astrophysics Data System (ADS)

Dong, C.; Stanier, C. O.; Bullard, R.; Singh, A.

2016-12-01

A one month simulation has been performed using the New particle formation (NPF)-explicit WRF-Chem (Matsui et al, Journal of Geophysical Research, 116(D19208), 2011). The simulation was run for a domain of the continental United States, with analysis focused on the Midwestern and eastern portions of the U.S. Analysis focused on quantification and explanation of planetary boundary layer (PBL) NPF in the model on variables beyond condensation nuclei (CN), cloud condensation nuclei (CCN), and cloud droplet size distributions. The model was evaluated against meteorology, chemical species and aerosol physical property observations. Comparison shows the model performance was comparable to that of other studies. Nucleation enhanced the concentration of condensation nuclei (CN). Cloud condensation nuclei (CCN) concentrations were enhanced and suppressed at high and low supersaturations, respectively. For air pollutants, the most pronounced influence of PBL nucleation was PM2.5 reduction, which was mainly caused by SO4 decreases (62.7%). For shortwave radiation, changes due to indirect effects of NPF were larger than direct effects. Shortwave radiation and cloud droplet concentration typically changed in the same way. Similar change patterns were found for T2 and PBL height. PBL nucleation led to a net increase of precipitation during the simulation period. Sensitivity tests showed that the combination of PBL NPF together with aqueous chemistry was the predominant cause of SO4 reduction.

Modeling diffuse sources of surface water contamination with plant protection products

NASA Astrophysics Data System (ADS)

Wendland, Sandra; Bock, Michael; Böhner, Jürgen; Lembrich, David

2015-04-01

Entries of chemical pollutants in surface waters are a serious environmental problem. Among water pollutants plant protection products (ppp) from farming practice are of major concern not only for water suppliers and environmental agencies, but also for farmers and industrial manufacturers. Lost chemicals no longer fulfill their original purpose on the field, but lead to severe damage of the environment and surface waters. Besides point-source inputs of chemical pollutants, the diffuse-source inputs from agricultural procedures play an important and not yet sufficiently studied role concerning water quality. The two most important factors for diffuse inputs are erosion and runoff. The latter usually occurs before erosion begins, and is thus often not visible in hindsight. Only if it has come to erosion, it is obvious to expect runoff in foresight at this area, too. In addition to numerous erosion models, there are also few applications to model runoff processes available. However, these conventional models utilize approximations of catchment parameters based on long-term average values or theoretically calculated concentration peaks which can only provide indications to relative amounts. Our study aims to develop and validate a simplified spatially-explicit dynamic model with high spatiotemporal resolution that enables to measure current and forecast runoff potential not only at catchment scale but field-differentiated. This method allows very precise estimations of runoff risks and supports risk reduction measures to be targeted before fields are treated. By focusing on water pathways occurring on arable land, targeted risk reduction measures like buffer strips at certain points and adapted ppp use can be taken early and pollution of rivers and other surface waters through transported pesticides, fertilizers and their products could be nearly avoided or largely minimized. Using a SAGA-based physical-parametric modeling approach, major factors influencing runoff (relief, soil properties, weather conditions and crop coverage) are represented. Water balance parameters are modeled in daily steps, taking into account relief determined discharge pathways, runoff velocity and number of field boundaries passed until receiving streams are reached. Model development is based on a comprehensive monitoring campaign at 3 smaller catchments in North Rhine-Westphalia (Germany), equipped with two gauges each, upstream and downstream, an optical Trios probe and four Isco-Samplers. The temporal high resolution monitoring of discharge, ppp, orthophosphate and nitrate-nitrogen enables an evaluation of runoff simulations in relation with rain events. First model results suggest that the simulation of surface runoff pathways enables a spatial-explicit identification of fields contributing to pollutant inputs. We assume that targeted actions on few fields will help solving the problem of diffuse inputs of ppp in our surface water to a considerable extent.

Magnon edge states in the hardcore- Bose-Hubbard model.

PubMed

Owerre, S A

2016-11-02

Quantum Monte Carlo (QMC) simulation has uncovered nonzero Berry curvature and bosonic edge states in the hardcore-Bose-Hubbard model on the gapped honeycomb lattice. The competition between the chemical potential and staggered onsite potential leads to an interesting quantum phase diagram comprising the superfluid phase, Mott insulator, and charge density wave insulator. In this paper, we present a semiclassical perspective of this system by mapping to a spin-1/2 quantum XY model. We give an explicit analytical origin of the quantum phase diagram, the Berry curvatures, and the edge states using semiclassical approximations. We find very good agreement between the semiclassical analyses and the QMC results. Our results show that the topological properties of the hardcore-Bose-Hubbard model are the same as those of magnon in the corresponding quantum spin system. Our results are applicable to systems of ultracold bosonic atoms trapped in honeycomb optical lattices.

De Novo Design of Bioactive Small Molecules by Artificial Intelligence

PubMed Central

Merk, Daniel; Friedrich, Lukas; Grisoni, Francesca

2018-01-01

Abstract Generative artificial intelligence offers a fresh view on molecular design. We present the first‐time prospective application of a deep learning model for designing new druglike compounds with desired activities. For this purpose, we trained a recurrent neural network to capture the constitution of a large set of known bioactive compounds represented as SMILES strings. By transfer learning, this general model was fine‐tuned on recognizing retinoid X and peroxisome proliferator‐activated receptor agonists. We synthesized five top‐ranking compounds designed by the generative model. Four of the compounds revealed nanomolar to low‐micromolar receptor modulatory activity in cell‐based assays. Apparently, the computational model intrinsically captured relevant chemical and biological knowledge without the need for explicit rules. The results of this study advocate generative artificial intelligence for prospective de novo molecular design, and demonstrate the potential of these methods for future medicinal chemistry. PMID:29319225

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

Jin, XF; Zhao, X; Huang, K

A high-fidelity two-dimensional axial symmetrical multi-physics model is described in this paper as an effort to simulate the cycle performance of a recently discovered solid oxide metal-air redox battery (SOMARB). The model collectively considers mass transport, charge transfer and chemical redox cycle kinetics occurring across the components of the battery, and is validated by experimental data obtained from independent research. In particular, the redox kinetics at the energy storage unit is well represented by Johnson-Mehl-Avrami-Kolmogorov (JIVIAK) and Shrinking Core models. The results explicitly show that the reduction of Fe3O4 during the charging cycle limits the overall performance. Distributions of electrodemore » potential, overpotential, Nernst potential, and H-2/H2O-concentration across various components of the battery are also systematically investigated. (C) 2015 Elsevier B.V. All rights reserved.« less

Theoretical modeling of UV-Vis absorption and emission spectra in liquid state systems including vibrational and conformational effects: explicit treatment of the vibronic transitions.

PubMed

D'Abramo, Marco; Aschi, Massimiliano; Amadei, Andrea

2014-04-28

Here, we extend a recently introduced theoretical-computational procedure [M. D'Alessandro, M. Aschi, C. Mazzuca, A. Palleschi, and A. Amadei, J. Chem. Phys. 139, 114102 (2013)] to include quantum vibrational transitions in modelling electronic spectra of atomic molecular systems in condensed phase. The method is based on the combination of Molecular Dynamics simulations and quantum chemical calculations within the Perturbed Matrix Method approach. The main aim of the presented approach is to reproduce as much as possible the spectral line shape which results from a subtle combination of environmental and intrinsic (chromophore) mechanical-dynamical features. As a case study, we were able to model the low energy UV-vis transitions of pyrene in liquid acetonitrile in good agreement with the experimental data.

Numerical study of supersonic combustion using a finite rate chemistry model

NASA Technical Reports Server (NTRS)

Chitsomboon, T.; Tiwari, S. N.; Kumar, A.; Drummond, J. P.

1986-01-01

The governing equations of two-dimensional chemically reacting flows are presented together with a global two-step chemistry model for H2-air combustion. The explicit unsplit MacCormack finite difference algorithm is used to advance the discrete system of the governing equations in time until convergence is attained. The source terms in the species equations are evaluated implicitly to alleviate stiffness associated with fast reactions. With implicit source terms, the species equations give rise to a block-diagonal system which can be solved very efficiently on vector-processing computers. A supersonic reacting flow in an inlet-combustor configuration is calculated for the case where H2 is injected into the flow from the side walls and the strut. Results of the calculation are compared against the results obtained by using a complete reaction model.

Implicit and explicit self-esteem and their reciprocal relationship with symptoms of depression and social anxiety: a longitudinal study in adolescents.

PubMed

van Tuijl, Lonneke A; de Jong, Peter J; Sportel, B Esther; de Hullu, Eva; Nauta, Maaike H

2014-03-01

A negative self-view is a prominent factor in most cognitive vulnerability models of depression and anxiety. Recently, there has been increased attention to differentiate between the implicit (automatic) and the explicit (reflective) processing of self-related evaluations. This longitudinal study aimed to test the association between implicit and explicit self-esteem and symptoms of adolescent depression and social anxiety disorder. Two complementary models were tested: the vulnerability model and the scarring effect model. Participants were 1641 first and second year pupils of secondary schools in the Netherlands. The Rosenberg Self-Esteem Scale, self-esteem Implicit Association Test and Revised Child Anxiety and Depression Scale were completed to measure explicit self-esteem, implicit self-esteem and symptoms of social anxiety disorder (SAD) and major depressive disorder (MDD), respectively, at baseline and two-year follow-up. Explicit self-esteem at baseline was associated with symptoms of MDD and SAD at follow-up. Symptomatology at baseline was not associated with explicit self-esteem at follow-up. Implicit self-esteem was not associated with symptoms of MDD or SAD in either direction. We relied on self-report measures of MDD and SAD symptomatology. Also, findings are based on a non-clinical sample. Our findings support the vulnerability model, and not the scarring effect model. The implications of these findings suggest support of an explicit self-esteem intervention to prevent increases in MDD and SAD symptomatology in non-clinical adolescents. Copyright © 2013 Elsevier Ltd. All rights reserved.

Are mixed explicit/implicit solvation models reliable for studying phosphate hydrolysis? A comparative study of continuum, explicit and mixed solvation models.

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

Kamerlin, Shina C. L.; Haranczyk, Maciej; Warshel, Arieh

2009-05-01

Phosphate hydrolysis is ubiquitous in biology. However, despite intensive research on this class of reactions, the precise nature of the reaction mechanism remains controversial. In this work, we have examined the hydrolysis of three homologous phosphate diesters. The solvation free energy was simulated by means of either an implicit solvation model (COSMO), hybrid quantum mechanical / molecular mechanical free energy perturbation (QM/MM-FEP) or a mixed solvation model in which N water molecules were explicitly included in the ab initio description of the reacting system (where N=1-3), with the remainder of the solvent being implicitly modelled as a continuum. Here, bothmore » COSMO and QM/MM-FEP reproduce Delta Gobs within an error of about 2kcal/mol. However, we demonstrate that in order to obtain any form of reliable results from a mixed model, it is essential to carefully select the explicit water molecules from short QM/MM runs that act as a model for the true infinite system. Additionally, the mixed models tend to be increasingly inaccurate the more explicit water molecules are placed into the system. Thus, our analysis indicates that this approach provides an unreliable way for modelling phosphate hydrolysis in solution.« less

Explicit filtering in large eddy simulation using a discontinuous Galerkin method

NASA Astrophysics Data System (ADS)

Brazell, Matthew J.

The discontinuous Galerkin (DG) method is a formulation of the finite element method (FEM). DG provides the ability for a high order of accuracy in complex geometries, and allows for highly efficient parallelization algorithms. These attributes make the DG method attractive for solving the Navier-Stokes equations for large eddy simulation (LES). The main goal of this work is to investigate the feasibility of adopting an explicit filter in the numerical solution of the Navier-Stokes equations with DG. Explicit filtering has been shown to increase the numerical stability of under-resolved simulations and is needed for LES with dynamic sub-grid scale (SGS) models. The explicit filter takes advantage of DG's framework where the solution is approximated using a polyno- mial basis where the higher modes of the solution correspond to a higher order polynomial basis. By removing high order modes, the filtered solution contains low order frequency content much like an explicit low pass filter. The explicit filter implementation is tested on a simple 1-D solver with an initial condi- tion that has some similarity to turbulent flows. The explicit filter does restrict the resolution as well as remove accumulated energy in the higher modes from aliasing. However, the ex- plicit filter is unable to remove numerical errors causing numerical dissipation. A second test case solves the 3-D Navier-Stokes equations of the Taylor-Green vortex flow (TGV). The TGV is useful for SGS model testing because it is initially laminar and transitions into a fully turbulent flow. The SGS models investigated include the constant coefficient Smagorinsky model, dynamic Smagorinsky model, and dynamic Heinz model. The constant coefficient Smagorinsky model is over dissipative, this is generally not desirable however it does add stability. The dynamic Smagorinsky model generally performs better, especially during the laminar-turbulent transition region as expected. The dynamic Heinz model which is based on an improved model, handles the laminar-turbulent transition region well while also showing additional robustness.

Embedded-explicit emergent literacy intervention I: Background and description of approach.

PubMed

Justice, Laura M; Kaderavek, Joan N

2004-07-01

This article, the first of a two-part series, provides background information and a general description of an emergent literacy intervention model for at-risk preschoolers and kindergartners. The embedded-explicit intervention model emphasizes the dual importance of providing young children with socially embedded opportunities for meaningful, naturalistic literacy experiences throughout the day, in addition to regular structured therapeutic interactions that explicitly target critical emergent literacy goals. The role of the speech-language pathologist (SLP) in the embedded-explicit model encompasses both indirect and direct service delivery: The SLP consults and collaborates with teachers and parents to ensure the highest quality and quantity of socially embedded literacy-focused experiences and serves as a direct provider of explicit interventions using structured curricula and/or lesson plans. The goal of this integrated model is to provide comprehensive emergent literacy interventions across a spectrum of early literacy skills to ensure the successful transition of at-risk children from prereaders to readers.

Numerical investigation of the boundary layer separation in chemical oxygen iodine laser

NASA Astrophysics Data System (ADS)

Huai, Ying; Jia, Shuqin; Wu, Kenan; Jin, Yuqi; Sang, Fengting

2017-11-01

Large eddy simulation is carried out to model the flow process in a supersonic chemical oxygen iodine laser. Unlike the common approaches relying on the tensor representation theory only, the model in the present work is an explicit anisotropy-resolving algebraic Subgrid-scale scalar flux formulation. With an accuracy in capturing the unsteady flow behaviours in the laser. Boundary layer separation initiated by the adverse pressure gradient is identified using Large Eddy Simulation. To quantify the influences of flow boundary layer on the laser performance, the fluid computations coupled with a physical optics loaded cavity model is developed. It has been found that boundary layer separation has a profound effect on the laser outputs due to the introduced shock waves. The F factor of the output beam decreases to 10% of the original one when the boundary transit into turbulence for the setup depicted in the paper. Because the pressure is always greater on the downstream of the boundary layer, there will always be a tendency of boundary separation in the laser. The results inspire designs of the laser to apply positive/passive control methods avoiding the boundary layer perturbation.

The prediction of mineral solubilities in natural waters: A chemical equilibrium model for the Na-Ca-Cl-SO 4-H 2O system, to high temperature and concentration

NASA Astrophysics Data System (ADS)

Møller, Nancy

1988-04-01

This paper describes a chemical equilibrium model for the Na-Ca-Cl-SO 4-H 2O system which calculates solubilities from 25°C to 250°C and from zero to high concentration ( I ~ 18. m) within experimental uncertainty. The concentration and temperature dependence of the model were established by fitting available activity (solubility, osmotic and emf) data. A single ion complex, CaSO 04, which increases in strength with temperature, is included explicitly in the model. The validation of model accuracy by comparison to laboratory and field solubility data is included. Applications of the model are also given. Phase diagrams constructed for the Na-Ca-Cl-SO 4-H 2O system and predicted solubilities of anhydrite and hemihydrate in concentrated seawater at high temperature are in very good agreement with the data. Calculations of the temperature of gypsum-anhydrite coexistence as a function of water activity are compared to reported values, and are used to estimate the composition-temperature relation for gypsum-anhydrite transition in a natural brine evaporation. A preliminary model for barite solubility in sodium chloride solutions at high temperature (100°C to 250°C), based on this parameterization of the CaSO 4-NaCl-H 2O system, gives good agreement with the data.

Advances in In Vitro and In Silico Tools for Toxicokinetic Dose ...

EPA Pesticide Factsheets

Recent advances in vitro assays, in silico tools, and systems biology approaches provide opportunities for refined mechanistic understanding for chemical safety assessment that will ultimately lead to reduced reliance on animal-based methods. With the U.S. commercial chemical landscape encompassing thousands of chemicals with limited data, safety assessment strategies that reliably predict in vivo systemic exposures and subsequent in vivo effects efficiently are a priority. Quantitative in vitro-in vivo extrapolation (QIVIVE) is a methodology that facilitates the explicit and quantitative application of in vitro experimental data and in silico modeling to predict in vivo system behaviors and can be applied to predict chemical toxicokinetics, toxicodynamics and also population variability. Tiered strategies that incorporate sufficient information to reliably inform the relevant decision context will facilitate acceptance of these alternative data streams for safety assessments. This abstract does not necessarily reflect U.S. EPA policy. This talk will provide an update to an international audience on the state of science being conducted within the EPA’s Office of Research and Development to develop and refine approaches that estimate internal chemical concentrations following a given exposure, known as toxicokinetics. Toxicokinetic approaches hold great potential in their ability to link in vitro activities or toxicities identified during high-throughput screen

Developing Spatially Explicit Habitat Models for Grassland Bird Conservation Planning in the Prairie Pothole Region of North Dakota

Treesearch

Neal D. Niemuth; Michael E. Estey; Charles R. Loesch

2005-01-01

Conservation planning for birds is increasingly focused on landscapes. However, little spatially explicit information is available to guide landscape-level conservation planning for many species of birds. We used georeferenced 1995 Breeding Bird Survey (BBS) data in conjunction with land-cover information to develop a spatially explicit habitat model predicting the...

Explicit robust schemes for implementation of general principal value-based constitutive models

NASA Technical Reports Server (NTRS)

Arnold, S. M.; Saleeb, A. F.; Tan, H. Q.; Zhang, Y.

1993-01-01

The issue of developing effective and robust schemes to implement general hyperelastic constitutive models is addressed. To this end, special purpose functions are used to symbolically derive, evaluate, and automatically generate the associated FORTRAN code for the explicit forms of the corresponding stress function and material tangent stiffness tensors. These explicit forms are valid for the entire deformation range. The analytical form of these explicit expressions is given here for the case in which the strain-energy potential is taken as a nonseparable polynomial function of the principle stretches.

Mechanistic modeling of the loss of protein sieving due to internal and external fouling of microfilters.

PubMed

Bolton, Glen R; Apostolidis, Alex J

2017-09-01

Fed-batch and perfusion cell culture processes used to produce therapeutic proteins can use microfilters for product harvest. In this study, new explicit mathematical models of sieving loss due to internal membrane fouling, external membrane fouling, or a combination of the two were generated. The models accounted for membrane and cake structures and hindered solute transport. Internal membrane fouling was assumed to occur due to the accumulation of foulant on either membrane pore walls (pore-retention model) or membrane fibers (fiber-retention model). External cake fouling was assumed to occur either by the growth of a single incompressible cake layer (cake-growth) or by the accumulation of a number of independent cake layers (cake-series). The pore-retention model was combined with either the cake-series or cake-growth models to obtain models that describe internal and external fouling occurring either simultaneously or sequentially. The models were tested using well-documented sieving decline data available in the literature. The sequential pore-retention followed by cake-growth model provided a good fit of sieving decline data during beer microfiltration. The cake-series and cake-growth models provided good fits of sieving decline data during the microfiltration of a perfusion cell culture. The new models provide insights into the mechanisms of fouling that result in the loss of product sieving. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:1323-1333, 2017. © 2017 American Institute of Chemical Engineers.

Investigation of supersonic chemically reacting and radiating channel flow

NASA Technical Reports Server (NTRS)

Mani, Mortaza; Tiwari, Surendra N.

1988-01-01

The 2-D time-dependent Navier-Stokes equations are used to investigate supersonic flows undergoing finite rate chemical reaction and radiation interaction for a hydrogen-air system. The explicit multistage finite volume technique of Jameson is used to advance the governing equations in time until convergence is achieved. The chemistry source term in the species equation is treated implicitly to alleviate the stiffness associated with fast reactions. The multidimensional radiative transfer equations for a nongray model are provided for a general configuration and then reduced for a planar geometry. Both pseudo-gray and nongray models are used to represent the absorption-emission characteristics of the participating species. The supersonic inviscid and viscous, nonreacting flows are solved by employing the finite volume technique of Jameson and the unsplit finite difference scheme of MacCormack. The specified problem considered is of the flow in a channel with a 10 deg compression-expansion ramp. The calculated results are compared with those of an upwind scheme. The problem of chemically reacting and radiating flows are solved for the flow of premixed hydrogen-air through a channel with parallel boundaries, and a channel with a compression corner. Results obtained for specific conditions indicate that the radiative interaction can have a significant influence on the entire flow field.

Chemical bonding and the equilibrium composition of Grignard reagents in ethereal solutions.

PubMed

Henriques, André M; Barbosa, André G H

2011-11-10

A thorough analysis of the electronic structure and thermodynamic aspects of Grignard reagents and its associated equilibrium composition in ethereal solutions is performed. Considering methylmagnesium halides containing fluorine, chlorine, and bromine, we studied the neutral, charged, and radical species associated with their chemical equilibrium in solution. The ethereal solvents considered, tetrahydrofuran (THF) and ethyl ether (Et(2)O), were modeled using the polarizable continuum model (PCM) and also by explicit coordination to the Mg atoms in a cluster. The chemical bonding of the species that constitute the Grignard reagent is analyzed in detail with generalized valence bond (GVB) wave functions. Equilibrium constants were calculated with the DFT/M06 functional and GVB wave functions, yielding similar results. According to our calculations and existing kinetic and electrochemical evidence, the species R(•), R(-), (•)MgX, and RMgX(2)(-) must be present in low concentration in the equilibrium. We conclude that depending on the halogen, a different route must be followed to produce the relevant equilibrium species in each case. Chloride and bromide must preferably follow a "radical-based" pathway, and fluoride must follow a "carbanionic-based" pathway. These different mechanisms are contrasted against the available experimental results and are proven to be consistent with the existing thermodynamic data on the Grignard reagent equilibria.

Fixed-Charge Atomistic Force Fields for Molecular Dynamics Simulations in the Condensed Phase: An Overview.

PubMed

Riniker, Sereina

2018-03-26

In molecular dynamics or Monte Carlo simulations, the interactions between the particles (atoms) in the system are described by a so-called force field. The empirical functional form of classical fixed-charge force fields dates back to 1969 and remains essentially unchanged. In a fixed-charge force field, the polarization is not modeled explicitly, i.e. the effective partial charges do not change depending on conformation and environment. This simplification allows, however, a dramatic reduction in computational cost compared to polarizable force fields and in particular quantum-chemical modeling. The past decades have shown that simulations employing carefully parametrized fixed-charge force fields can provide useful insights into biological and chemical questions. This overview focuses on the four major force-field families, i.e. AMBER, CHARMM, GROMOS, and OPLS, which are based on the same classical functional form and are continuously improved to the present day. The overview is aimed at readers entering the field of (bio)molecular simulations. More experienced users may find the comparison and historical development of the force-field families interesting.

Entropy production of active particles and for particles in active baths

NASA Astrophysics Data System (ADS)

Pietzonka, Patrick; Seifert, Udo

2018-01-01

Entropy production of an active particle in an external potential is identified through a thermodynamically consistent minimal lattice model that includes the chemical reaction providing the propulsion and ordinary translational noise. In the continuum limit, a unique expression follows, comprising a direct contribution from the active process and an indirect contribution from ordinary diffusive motion. From the corresponding Langevin equation, this physical entropy production cannot be inferred through the conventional, yet here ambiguous, comparison of forward and time-reversed trajectories. Generalizations to several interacting active particles and passive particles in a bath of active ones are presented explicitly, further ones are briefly indicated.

Communication: a density functional with accurate fractional-charge and fractional-spin behaviour for s-electrons.

PubMed

Johnson, Erin R; Contreras-García, Julia

2011-08-28

We develop a new density-functional approach combining physical insight from chemical structure with treatment of multi-reference character by real-space modeling of the exchange-correlation hole. We are able to recover, for the first time, correct fractional-charge and fractional-spin behaviour for atoms of groups 1 and 2. Based on Becke's non-dynamical correlation functional [A. D. Becke, J. Chem. Phys. 119, 2972 (2003)] and explicitly accounting for core-valence separation and pairing effects, this method is able to accurately describe dissociation and strong correlation in s-shell many-electron systems. © 2011 American Institute of Physics

Uncertainty in spatially explicit animal dispersal models

USGS Publications Warehouse

Mooij, Wolf M.; DeAngelis, Donald L.

2003-01-01

Uncertainty in estimates of survival of dispersing animals is a vexing difficulty in conservation biology. The current notion is that this uncertainty decreases the usefulness of spatially explicit population models in particular. We examined this problem by comparing dispersal models of three levels of complexity: (1) an event-based binomial model that considers only the occurrence of mortality or arrival, (2) a temporally explicit exponential model that employs mortality and arrival rates, and (3) a spatially explicit grid-walk model that simulates the movement of animals through an artificial landscape. Each model was fitted to the same set of field data. A first objective of the paper is to illustrate how the maximum-likelihood method can be used in all three cases to estimate the means and confidence limits for the relevant model parameters, given a particular set of data on dispersal survival. Using this framework we show that the structure of the uncertainty for all three models is strikingly similar. In fact, the results of our unified approach imply that spatially explicit dispersal models, which take advantage of information on landscape details, suffer less from uncertainly than do simpler models. Moreover, we show that the proposed strategy of model development safeguards one from error propagation in these more complex models. Finally, our approach shows that all models related to animal dispersal, ranging from simple to complex, can be related in a hierarchical fashion, so that the various approaches to modeling such dispersal can be viewed from a unified perspective.

Effective Reading and Writing Instruction: A Focus on Modeling

ERIC Educational Resources Information Center

Regan, Kelley; Berkeley, Sheri

2012-01-01

When providing effective reading and writing instruction, teachers need to provide explicit modeling. Modeling is particularly important when teaching students to use cognitive learning strategies. Examples of how teachers can provide specific, explicit, and flexible instructional modeling is presented in the context of two evidence-based…

The relative importance of physical erosion and soil water dynamics on chemical weathering and soil formation: learning from field and model results

NASA Astrophysics Data System (ADS)

Vanwalleghem, T.; Román, A.; Giraldez, J. V.

2015-12-01

A new model is presented that integrates the effect of landscape evolution and soil formation. This model is based on a daily spatially-explicit soil water balance. Average soil water content, temperature and deep percolation fluxes are linked to weathering and soil formation processes. Model input (temperature and precipitation) for the last 25 000 years was generated on a daily time by combining palaeoclimate data and the WXGEN weather generator. The soil-landscape model was applied to a 48 km2 semi-natural catchment in Southern Spain, with soils developed on granite. Model-generated runoff was used for a first validation against discharge observations. Next, soil formation output was contrasted against experimental data from 10 soil profiles along two catenas. Field data showed an important variation in mobile regolith thickness, between 0,44 and 1,10m, and in chemical weathering along the catena. Southern slopes were characterized by shallower, stonier and carbon-poor soils, while soils on north-facing slopes were deeper, more fine-textured and had a higher carbon content. Chemical depletion fraction was found to vary between 0,41 and 0,72. The lowest overall weathering intensity was found on plateau positions. South facing slopes revealed slightly lower weathering compared to north facing slopes. We attribute this to higher runoff generation and physical erosion rates on north facing slopes, transporting weathered material downslope. Model results corroborate these findings and show continuously wet soils on north-facing slopes with more runoff generation and a steady deep percolation flux during the wet winter season. On south-facing slopes, infiltration is higher and percolation is more erratic over time. Soils on the footslopes then were shown to be significantly impacted by deposition of sediment through lateral erosion fluxes.

Simulating chemical reactions in ionic liquids using QM/MM methodology.

PubMed

Acevedo, Orlando

2014-12-18

The use of ionic liquids as a reaction medium for chemical reactions has dramatically increased in recent years due in large part to the numerous reported advances in catalysis and organic synthesis. In some extreme cases, ionic liquids have been shown to induce mechanistic changes relative to conventional solvents. Despite the large interest in the solvents, a clear understanding of the molecular factors behind their chemical impact is largely unknown. This feature article reviews our efforts developing and applying mixed quantum and molecular mechanical (QM/MM) methodology to elucidate the microscopic details of how these solvents operate to enhance rates and alter mechanisms for industrially and academically important reactions, e.g., Diels-Alder, Kemp eliminations, nucleophilic aromatic substitutions, and β-eliminations. Explicit solvent representation provided the medium dependence of the activation barriers and atomic-level characterization of the solute-solvent interactions responsible for the experimentally observed "ionic liquid effects". Technical advances are also discussed, including a linear-scaling pairwise electrostatic interaction alternative to Ewald sums, an efficient polynomial fitting method for modeling proton transfers, and the development of a custom ionic liquid OPLS-AA force field.

Explicit continuous charge-based compact model for long channel heavily doped surrounding-gate MOSFETs incorporating interface traps and quantum effects

NASA Astrophysics Data System (ADS)

Hamzah, Afiq; Hamid, Fatimah A.; Ismail, Razali

2016-12-01

An explicit solution for long-channel surrounding-gate (SRG) MOSFETs is presented from intrinsic to heavily doped body including the effects of interface traps and fixed oxide charges. The solution is based on the core SRGMOSFETs model of the Unified Charge Control Model (UCCM) for heavily doped conditions. The UCCM model of highly doped SRGMOSFETs is derived to obtain the exact equivalent expression as in the undoped case. Taking advantage of the undoped explicit charge-based expression, the asymptotic limits for below threshold and above threshold have been redefined to include the effect of trap states for heavily doped cases. After solving the asymptotic limits, an explicit mobile charge expression is obtained which includes the trap state effects. The explicit mobile charge model shows very good agreement with respect to numerical simulation over practical terminal voltages, doping concentration, geometry effects, and trap state effects due to the fixed oxide charges and interface traps. Then, the drain current is obtained using the Pao-Sah's dual integral, which is expressed as a function of inversion charge densities at the source/drain ends. The drain current agreed well with the implicit solution and numerical simulation for all regions of operation without employing any empirical parameters. A comparison with previous explicit models has been conducted to verify the competency of the proposed model with the doping concentration of 1× {10}19 {{cm}}-3, as the proposed model has better advantages in terms of its simplicity and accuracy at a higher doping concentration.

From Cycle Rooted Spanning Forests to the Critical Ising Model: an Explicit Construction

NASA Astrophysics Data System (ADS)

de Tilière, Béatrice

2013-04-01

Fisher established an explicit correspondence between the 2-dimensional Ising model defined on a graph G and the dimer model defined on a decorated version {{G}} of this graph (Fisher in J Math Phys 7:1776-1781, 1966). In this paper we explicitly relate the dimer model associated to the critical Ising model and critical cycle rooted spanning forests (CRSFs). This relation is established through characteristic polynomials, whose definition only depends on the respective fundamental domains, and which encode the combinatorics of the model. We first show a matrix-tree type theorem establishing that the dimer characteristic polynomial counts CRSFs of the decorated fundamental domain {{G}_1}. Our main result consists in explicitly constructing CRSFs of {{G}_1} counted by the dimer characteristic polynomial, from CRSFs of G 1, where edges are assigned Kenyon's critical weight function (Kenyon in Invent Math 150(2):409-439, 2002); thus proving a relation on the level of configurations between two well known 2-dimensional critical models.

An explicit microphysics thunderstorm model.

Treesearch

R. Solomon; C.M. Medaglia; C. Adamo; S. Dietrick; A. Mugnai; U. Biader Ceipidor

2005-01-01

The authors present a brief description of a 1.5-dimensional thunderstorm model with a lightning parameterization that utilizes an explicit microphysical scheme to model lightning-producing clouds. The main intent of this work is to describe the basic microphysical and electrical properties of the model, with a small illustrative section to show how the model may be...

Atmospheric Ionizing Radiation (AIR) ER-2 Preflight Analysis

NASA Technical Reports Server (NTRS)

Tai, Hsiang; Wilson, John W.; Maiden, D. L.

1998-01-01

Atmospheric ionizing radiation (AIR) produces chemically active radicals in biological tissues that alter the cell function or result in cell death. The AIR ER-2 flight measurements will enable scientists to study the radiation risk associated with the high-altitude operation of a commercial supersonic transport. The ER-2 radiation measurement flights will follow predetermined, carefully chosen courses to provide an appropriate database matrix which will enable the evaluation of predictive modeling techniques. Explicit scientific results such as dose rate, dose equivalent rate, magnetic cutoff, neutron flux, and air ionization rate associated with those flights are predicted by using the AIR model. Through these flight experiments, we will further increase our knowledge and understanding of the AIR environment and our ability to assess the risk from the associated hazard.

Heterogeneous propellant internal ballistics: criticism and regeneration

NASA Astrophysics Data System (ADS)

Glick, R. L.

2011-10-01

Although heterogeneous propellant and its innately nondeterministic, chemically discrete morphology dominates applications, ballisticcharacterization deterministic time-mean burning rate and acoustic admittance measures' absence of explicit, nondeterministic information requires homogeneous propellant with a smooth, uniformly regressing burning surface: inadequate boundary conditions for heterogeneous propellant grained applications. The past age overcame this dichotomy with one-dimensional (1D) models and empirical knowledge from numerous, adequately supported motor developments and supplementary experiments. However, current cost and risk constraints inhibit this approach. Moreover, its fundamental science approach is more sensitive to incomplete boundary condition information (garbage-in still equals garbage-out) and more is expected. This work critiques this situation and sketches a path forward based on enhanced ballistic and motor characterizations in the workplace and approximate model and apparatus developments mentored by CSAR DNS capabilities (or equivalent).

Multi-dimensional multi-species modeling of transient electrodeposition in LIGA microfabrication.

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

Evans, Gregory Herbert; Chen, Ken Shuang

2004-06-01

This report documents the efforts and accomplishments of the LIGA electrodeposition modeling project which was headed by the ASCI Materials and Physics Modeling Program. A multi-dimensional framework based on GOMA was developed for modeling time-dependent diffusion and migration of multiple charged species in a dilute electrolyte solution with reduction electro-chemical reactions on moving deposition surfaces. By combining the species mass conservation equations with the electroneutrality constraint, a Poisson equation that explicitly describes the electrolyte potential was derived. The set of coupled, nonlinear equations governing species transport, electric potential, velocity, hydrodynamic pressure, and mesh motion were solved in GOMA, using themore » finite-element method and a fully-coupled implicit solution scheme via Newton's method. By treating the finite-element mesh as a pseudo solid with an arbitrary Lagrangian-Eulerian formulation and by repeatedly performing re-meshing with CUBIT and re-mapping with MAPVAR, the moving deposition surfaces were tracked explicitly from start of deposition until the trenches were filled with metal, thus enabling the computation of local current densities that potentially influence the microstructure and frictional/mechanical properties of the deposit. The multi-dimensional, multi-species, transient computational framework was demonstrated in case studies of two-dimensional nickel electrodeposition in single and multiple trenches, without and with bath stirring or forced flow. Effects of buoyancy-induced convection on deposition were also investigated. To further illustrate its utility, the framework was employed to simulate deposition in microscreen-based LIGA molds. Lastly, future needs for modeling LIGA electrodeposition are discussed.« less

Gaseous Chemistry and Aerosol Mechanism Developments for Version 3.5.1 of the Online Regional Model, WRF-Chem

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

Archer-Nicholls, Scott; Lowe, Douglas; Utembe, Steve

We have made a number of developments in the regional coupled model WRF-Chem, with the aim of making the model more suitable for prediction of atmospheric composition and of interactions between air quality and weather. We have worked on the European domain, with a particular focus on making the model suitable for the study of night time chemistry and oxidation by the nitrate radical in the UK atmosphere. A reduced form of the Common Reactive Intermediates gas-phase chemical mechanism (CRIv2-R5) has been implemented to enable more explicit simulation of VOC degradation. N2O5 heterogeneous chemistry has been added to the existingmore » sectional MOSAIC aerosol module, and coupled to both the CRIv2-R5 and existing CBM-Z gas phase scheme. Modifications have also been made to the sea-spray aerosol emission representation, allowing the inclusion of primary organic material in sea-spray aerosol. Driven by appropriate emissions, wind fields and chemical boundary conditions, implementation of the different developments is illustrated in order to demonstrate the impact that these changes have in the North-West European domain. These developments are now part of the freely available WRF-Chem distribution.« less

Quantum mechanics/molecular mechanics modeling of photoelectron spectra: the carbon 1s core-electron binding energies of ethanol-water solutions.

PubMed

Löytynoja, T; Niskanen, J; Jänkälä, K; Vahtras, O; Rinkevicius, Z; Ågren, H

2014-11-20

Using ethanol-water solutions as illustration, we demonstrate the capability of the hybrid quantum mechanics/molecular mechanics (QM/MM) paradigm to simulate core photoelectron spectroscopy: the binding energies and the chemical shifts. An integrated approach with QM/MM binding energy calculations coupled to preceding molecular dynamics sampling is adopted to generate binding energies averaged over the solute-solvent configurations available at a particular temperature and pressure and thus allowing for a statistical assessment with confidence levels for the final binding energies. The results are analyzed in terms of the contributions in the molecular mechanics model-electrostatic, polarization, and van der Waals-with atom or bond granulation of the corresponding MM charge and polarizability force-fields. The role of extramolecular charge transfer screening of the core-hole and explicit hydrogen bonding is studied by extending the QM core to cover the first solvation shell. The results are compared to those obtained from pure electrostatic and polarizable continuum models. Particularly, the dependence of the carbon 1s binding energies with respect to the ethanol concentration is studied. Our results indicate that QM/MM can be used as an all-encompassing model to study photoelectron binding energies and chemical shifts in solvent environments.

Graph-based analysis of connectivity in spatially-explicit population models: HexSim and the Connectivity Analysis Toolkit

EPA Science Inventory

Background / Question / Methods Planning for the recovery of threatened species is increasingly informed by spatially-explicit population models. However, using simulation model results to guide land management decisions can be difficult due to the volume and complexity of model...

Quantum mechanical force field for water with explicit electronic polarization.

PubMed

Han, Jaebeom; Mazack, Michael J M; Zhang, Peng; Truhlar, Donald G; Gao, Jiali

2013-08-07

A quantum mechanical force field (QMFF) for water is described. Unlike traditional approaches that use quantum mechanical results and experimental data to parameterize empirical potential energy functions, the present QMFF uses a quantum mechanical framework to represent intramolecular and intermolecular interactions in an entire condensed-phase system. In particular, the internal energy terms used in molecular mechanics are replaced by a quantum mechanical formalism that naturally includes electronic polarization due to intermolecular interactions and its effects on the force constants of the intramolecular force field. As a quantum mechanical force field, both intermolecular interactions and the Hamiltonian describing the individual molecular fragments can be parameterized to strive for accuracy and computational efficiency. In this work, we introduce a polarizable molecular orbital model Hamiltonian for water and for oxygen- and hydrogen-containing compounds, whereas the electrostatic potential responsible for intermolecular interactions in the liquid and in solution is modeled by a three-point charge representation that realistically reproduces the total molecular dipole moment and the local hybridization contributions. The present QMFF for water, which is called the XP3P (explicit polarization with three-point-charge potential) model, is suitable for modeling both gas-phase clusters and liquid water. The paper demonstrates the performance of the XP3P model for water and proton clusters and the properties of the pure liquid from about 900 × 10(6) self-consistent-field calculations on a periodic system consisting of 267 water molecules. The unusual dipole derivative behavior of water, which is incorrectly modeled in molecular mechanics, is naturally reproduced as a result of an electronic structural treatment of chemical bonding by XP3P. We anticipate that the XP3P model will be useful for studying proton transport in solution and solid phases as well as across biological ion channels through membranes.

Computational neural networks in chemistry: Model free mapping devices for predicting chemical reactivity from molecular structure

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

Elrod, D.W.

1992-01-01

Computational neural networks (CNNs) are a computational paradigm inspired by the brain's massively parallel network of highly interconnected neurons. The power of computational neural networks derives not so much from their ability to model the brain as from their ability to learn by example and to map highly complex, nonlinear functions, without the need to explicitly specify the functional relationship. Two central questions about CNNs were investigated in the context of predicting chemical reactions: (1) the mapping properties of neural networks and (2) the representation of chemical information for use in CNNs. Chemical reactivity is here considered an example ofmore » a complex, nonlinear function of molecular structure. CNN's were trained using modifications of the back propagation learning rule to map a three dimensional response surface similar to those typically observed in quantitative structure-activity and structure-property relationships. The computational neural network's mapping of the response surface was found to be robust to the effects of training sample size, noisy data and intercorrelated input variables. The investigation of chemical structure representation led to the development of a molecular structure-based connection-table representation suitable for neural network training. An extension of this work led to a BE-matrix structure representation that was found to be general for several classes of reactions. The CNN prediction of chemical reactivity and regiochemistry was investigated for electrophilic aromatic substitution reactions, Markovnikov addition to alkenes, Saytzeff elimination from haloalkanes, Diels-Alder cycloaddition, and retro Diels-Alder ring opening reactions using these connectivity-matrix derived representations. The reaction predictions made by the CNNs were more accurate than those of an expert system and were comparable to predictions made by chemists.« less

Mapping Asian anthropogenic emissions of non-methane volatile organic compounds to multiple chemical mechanisms

NASA Astrophysics Data System (ADS)

Li, M.; Zhang, Q.; Streets, D. G.; He, K. B.; Cheng, Y. F.; Emmons, L. K.; Huo, H.; Kang, S. C.; Lu, Z.; Shao, M.; Su, H.; Yu, X.; Zhang, Y.

2014-06-01

An accurate speciation mapping of non-methane volatile organic compounds (NMVOC) emissions has an important impact on the performance of chemical transport models (CTMs) in simulating ozone mixing ratios and secondary organic aerosols. Taking the INTEX-B Asian NMVOC emission inventory as the case, we developed an improved speciation framework to generate model-ready anthropogenic NMVOC emissions for various gas-phase chemical mechanisms commonly used in CTMs in this work, by using an explicit assignment approach and updated NMVOC profiles. NMVOC profiles were selected and aggregated from a wide range of new measurements and the SPECIATE database v.4.2. To reduce potential uncertainty from individual measurements, composite profiles were developed by grouping and averaging source profiles from the same category. The fractions of oxygenated volatile organic compounds (OVOC) were corrected during the compositing process for those profiles which used improper sampling and analyzing methods. Emissions of individual species were then lumped into species in different chemical mechanisms used in CTMs by applying mechanism-dependent species mapping tables, which overcomes the weakness of inaccurate mapping in previous studies. Emission estimates for individual NMVOC species differ between one and three orders of magnitude for some species when different sets of profiles are used, indicating that source profile is the most important source of uncertainties of individual species emissions. However, those differences are diminished in lumped species as a result of the lumping in the chemical mechanisms. Gridded emissions for eight chemical mechanisms at 30 min × 30 min resolution as well as the auxiliary data are available at http://mic.greenresource.cn/intex-b2006. The framework proposed in this work can be also used to develop speciated NMVOC emissions for other regions.

Mapping Asian anthropogenic emissions of non-methane volatile organic compounds to multiple chemical mechanisms

NASA Astrophysics Data System (ADS)

Li, M.; Zhang, Q.; Streets, D. G.; He, K. B.; Cheng, Y. F.; Emmons, L. K.; Huo, H.; Kang, S. C.; Lu, Z.; Shao, M.; Su, H.; Yu, X.; Zhang, Y.

2013-12-01

An accurate speciation mapping of non-methane volatile organic compounds (NMVOC) emissions has an important impact on the performance of chemical transport models (CTMs) in simulating ozone mixing ratios and secondary organic aerosols. In this work, we developed an improved speciation framework to generate model-ready anthropogenic Asian NMVOC emissions for various gas-phase chemical mechanisms commonly used in CTMs by using an explicit assignment approach and updated NMVOC profiles, based on the total NMVOC emissions in the INTEX-B Asian inventory for the year 2006. NMVOC profiles were selected and aggregated from a wide range of new measurements and the SPECIATE database. To reduce potential uncertainty from individual measurements, composite profiles were developed by grouping and averaging source profiles from the same category. The fractions of oxygenated volatile organic compounds (OVOC) were corrected during the compositing process for those profiles which used improper sampling and analyzing methods. Emissions of individual species were then lumped into species in different chemical mechanisms used in CTMs by applying mechanism-dependent species mapping tables, which overcomes the weakness of inaccurate mapping in previous studies. Gridded emissions for eight chemical mechanisms are developed at 30 min × 30 min resolution using various spatial proxies and are provided through the website: http://mic.greenresource.cn/intex-b2006. Emission estimates for individual NMVOC species differ between one and three orders of magnitude for some species when different sets of profiles are used, indicating that source profile is the most important source of uncertainties of individual species emissions. However, those differences are diminished in lumped species as a result of the lumping in the chemical mechanisms.

CONSTRUCTING, PERTURBATION ANALYSIIS AND TESTING OF A MULTI-HABITAT PERIODIC MATRIX POPULATION MODEL

EPA Science Inventory

We present a matrix model that explicitly incorporates spatial habitat structure and seasonality and discuss preliminary results from a landscape level experimental test. Ecological risk to populations is often modeled without explicit treatment of spatially or temporally distri...

Green-Ampt approximations: A comprehensive analysis

NASA Astrophysics Data System (ADS)

Ali, Shakir; Islam, Adlul; Mishra, P. K.; Sikka, Alok K.

2016-04-01

Green-Ampt (GA) model and its modifications are widely used for simulating infiltration process. Several explicit approximate solutions to the implicit GA model have been developed with varying degree of accuracy. In this study, performance of nine explicit approximations to the GA model is compared with the implicit GA model using the published data for broad range of soil classes and infiltration time. The explicit GA models considered are Li et al. (1976) (LI), Stone et al. (1994) (ST), Salvucci and Entekhabi (1994) (SE), Parlange et al. (2002) (PA), Barry et al. (2005) (BA), Swamee et al. (2012) (SW), Ali et al. (2013) (AL), Almedeij and Esen (2014) (AE), and Vatankhah (2015) (VA). Six statistical indicators (e.g., percent relative error, maximum absolute percent relative error, average absolute percent relative errors, percent bias, index of agreement, and Nash-Sutcliffe efficiency) and relative computer computation time are used for assessing the model performance. Models are ranked based on the overall performance index (OPI). The BA model is found to be the most accurate followed by the PA and VA models for variety of soil classes and infiltration periods. The AE, SW, SE, and LI model also performed comparatively better. Based on the overall performance index, the explicit models are ranked as BA > PA > VA > LI > AE > SE > SW > ST > AL. Results of this study will be helpful in selection of accurate and simple explicit approximate GA models for solving variety of hydrological problems.

Direct versus Indirect Explicit Methods of Enhancing EFL Students' English Grammatical Competence: A Concept Checking-Based Consciousness-Raising Tasks Model

ERIC Educational Resources Information Center

Dang, Trang Thi Doan; Nguyen, Huong Thu

2013-01-01

Two approaches to grammar instruction are often discussed in the ESL literature: direct explicit grammar instruction (DEGI) (deduction) and indirect explicit grammar instruction (IEGI) (induction). This study aims to explore the effects of indirect explicit grammar instruction on EFL learners' mastery of English tenses. Ninety-four…

DEFINING RECOVERY GOALS AND STRATEGIES FOR ENDANGERED SPECIES USING SPATIALLY-EXPLICIT POPULATION MODELS

EPA Science Inventory

We used a spatially explicit population model of wolves (Canis lupus) to propose a framework for defining rangewide recovery priorities and finer-scale strategies for regional reintroductions. The model predicts that Yellowstone and central Idaho, where wolves have recently been ...

Conformational free energy modeling of druglike molecules by metadynamics in the WHIM space.

PubMed

Spiwok, Vojtěch; Hlat-Glembová, Katarína; Tvaroška, Igor; Králová, Blanka

2012-03-26

Protein-ligand affinities can be significantly influenced not only by the interaction itself but also by conformational equilibrium of both binding partners, free ligand and free protein. Identification of important conformational families of a ligand and prediction of their thermodynamics is important for efficient ligand design. Here we report conformational free energy modeling of nine small-molecule drugs in explicitly modeled water by metadynamics with a bias potential applied in the space of weighted holistic invariant molecular (WHIM) descriptors. Application of metadynamics enhances conformational sampling compared to unbiased molecular dynamics simulation and allows to predict relative free energies of key conformations. Selected free energy minima and one example of transition state were tested by a series of unbiased molecular dynamics simulation. Comparison of free energy surfaces of free and target-bound Imatinib provides an estimate of free energy penalty of conformational change induced by its binding to the target. © 2012 American Chemical Society

On the explicit versus family solution of the fully diurnal photochemical equations of the stratosphere

NASA Technical Reports Server (NTRS)

Austin, John

1991-01-01

The family approach used to solve chemical equations is examined by integrating a heirarchy of versions of a 2D model of stratospheric chemistry and transport on an isentropic surface. Errors of up to 20 percent in radical concentrations can result from the use of a small number of families; the use of more families increases the accuracy of the solutions. The minimum number of families which can be used to provide an accurate solution is discussed, and the parameterization of long-time-scale species is recommended for making the model more efficient. The most pervasive errors are found in calculations of the concentrations of radical species, a problem which can lead to errors in predicting O3 over the long run. Methods for improving the schemes are presented, emphasizing the possibility of producing an improved 3D model.

LEAP into the Pfizer Global Virtual Library (PGVL) space: creation of readily synthesizable design ideas automatically.

PubMed

Hu, Qiyue; Peng, Zhengwei; Kostrowicki, Jaroslav; Kuki, Atsuo

2011-01-01

Pfizer Global Virtual Library (PGVL) of 10(13) readily synthesizable molecules offers a tremendous opportunity for lead optimization and scaffold hopping in drug discovery projects. However, mining into a chemical space of this size presents a challenge for the concomitant design informatics due to the fact that standard molecular similarity searches against a collection of explicit molecules cannot be utilized, since no chemical information system could create and manage more than 10(8) explicit molecules. Nevertheless, by accepting a tolerable level of false negatives in search results, we were able to bypass the need for full 10(13) enumeration and enabled the efficient similarity search and retrieval into this huge chemical space for practical usage by medicinal chemists. In this report, two search methods (LEAP1 and LEAP2) are presented. The first method uses PGVL reaction knowledge to disassemble the incoming search query molecule into a set of reactants and then uses reactant-level similarities into actual available starting materials to focus on a much smaller sub-region of the full virtual library compound space. This sub-region is then explicitly enumerated and searched via a standard similarity method using the original query molecule. The second method uses a fuzzy mapping onto candidate reactions and does not require exact disassembly of the incoming query molecule. Instead Basis Products (or capped reactants) are mapped into the query molecule and the resultant asymmetric similarity scores are used to prioritize the corresponding reactions and reactant sets. All sets of Basis Products are inherently indexed to specific reactions and specific starting materials. This again allows focusing on a much smaller sub-region for explicit enumeration and subsequent standard product-level similarity search. A set of validation studies were conducted. The results have shown that the level of false negatives for the disassembly-based method is acceptable when the query molecule can be recognized for exact disassembly, and the fuzzy reaction mapping method based on Basis Products has an even better performance in terms of lower false-negative rate because it is not limited by the requirement that the query molecule needs to be recognized by any disassembly algorithm. Both search methods have been implemented and accessed through a powerful desktop molecular design tool (see ref. (33) for details). The chapter will end with a comparison of published search methods against large virtual chemical space.

On Spatially Explicit Models of Cholera Epidemics: Hydrologic controls, environmental drivers, human-mediated transmissions (Invited)

NASA Astrophysics Data System (ADS)

Rinaldo, A.; Bertuzzo, E.; Mari, L.; Righetto, L.; Gatto, M.; Casagrandi, R.; Rodriguez-Iturbe, I.

2010-12-01

A recently proposed model for cholera epidemics is examined. The model accounts for local communities of susceptibles and infectives in a spatially explicit arrangement of nodes linked by networks having different topologies. The vehicle of infection (Vibrio cholerae) is transported through the network links which are thought of as hydrological connections among susceptible communities. The mathematical tools used are borrowed from general schemes of reactive transport on river networks acting as the environmental matrix for the circulation and mixing of water-borne pathogens. The results of a large-scale application to the Kwa Zulu (Natal) epidemics of 2001-2002 will be discussed. Useful theoretical results derived in the spatially-explicit context will also be reviewed (like e.g. the exact derivation of the speed of propagation for traveling fronts of epidemics on regular lattices endowed with uniform population density). Network effects will be discussed. The analysis of the limit case of uniformly distributed population density proves instrumental in establishing the overall conditions for the relevance of spatially explicit models. To that extent, it is shown that the ratio between spreading and disease outbreak timescales proves the crucial parameter. The relevance of our results lies in the major differences potentially arising between the predictions of spatially explicit models and traditional compartmental models of the SIR-like type. Our results suggest that in many cases of real-life epidemiological interest timescales of disease dynamics may trigger outbreaks that significantly depart from the predictions of compartmental models. Finally, a view on further developments includes: hydrologically improved aquatic reservoir models for pathogens; human mobility patterns affecting disease propagation; double-peak emergence and seasonality in the spatially explicit epidemic context.

Spatially explicit watershed modeling: tracking water, mercury and nitrogen in multiple systems under diverse conditions

EPA Science Inventory

Environmental decision-making and the influences of various stressors, such as landscape and climate changes on water quantity and quality, requires the application of environmental modeling. Spatially explicit environmental and watershed-scale models using GIS as a base framewor...

HexSim - A general purpose framework for spatially-explicit, individual-based modeling

EPA Science Inventory

HexSim is a framework for constructing spatially-explicit, individual-based computer models designed for simulating terrestrial wildlife population dynamics and interactions. HexSim is useful for a broad set of modeling applications. This talk will focus on a subset of those ap...

Studies of implicit and explicit solution techniques in transient thermal analysis of structures

NASA Technical Reports Server (NTRS)

Adelman, H. M.; Haftka, R. T.; Robinson, J. C.

1982-01-01

Studies aimed at an increase in the efficiency of calculating transient temperature fields in complex aerospace vehicle structures are reported. The advantages and disadvantages of explicit and implicit algorithms are discussed and a promising set of implicit algorithms with variable time steps, known as GEARIB, is described. Test problems, used for evaluating and comparing various algorithms, are discussed and finite element models of the configurations are described. These problems include a coarse model of the Space Shuttle wing, an insulated frame tst article, a metallic panel for a thermal protection system, and detailed models of sections of the Space Shuttle wing. Results generally indicate a preference for implicit over explicit algorithms for transient structural heat transfer problems when the governing equations are stiff (typical of many practical problems such as insulated metal structures). The effects on algorithm performance of different models of an insulated cylinder are demonstrated. The stiffness of the problem is highly sensitive to modeling details and careful modeling can reduce the stiffness of the equations to the extent that explicit methods may become the best choice. Preliminary applications of a mixed implicit-explicit algorithm and operator splitting techniques for speeding up the solution of the algebraic equations are also described.

Studies of implicit and explicit solution techniques in transient thermal analysis of structures

NASA Astrophysics Data System (ADS)

Adelman, H. M.; Haftka, R. T.; Robinson, J. C.

1982-08-01

Studies aimed at an increase in the efficiency of calculating transient temperature fields in complex aerospace vehicle structures are reported. The advantages and disadvantages of explicit and implicit algorithms are discussed and a promising set of implicit algorithms with variable time steps, known as GEARIB, is described. Test problems, used for evaluating and comparing various algorithms, are discussed and finite element models of the configurations are described. These problems include a coarse model of the Space Shuttle wing, an insulated frame tst article, a metallic panel for a thermal protection system, and detailed models of sections of the Space Shuttle wing. Results generally indicate a preference for implicit over explicit algorithms for transient structural heat transfer problems when the governing equations are stiff (typical of many practical problems such as insulated metal structures). The effects on algorithm performance of different models of an insulated cylinder are demonstrated. The stiffness of the problem is highly sensitive to modeling details and careful modeling can reduce the stiffness of the equations to the extent that explicit methods may become the best choice. Preliminary applications of a mixed implicit-explicit algorithm and operator splitting techniques for speeding up the solution of the algebraic equations are also described.

One-dimensional turbulence modeling of a turbulent counterflow flame with comparison to DNS

DOE PAGES

Jozefik, Zoltan; Kerstein, Alan R.; Schmidt, Heiko; ...

2015-06-01

The one-dimensional turbulence (ODT) model is applied to a reactant-to-product counterflow configuration and results are compared with DNS data. The model employed herein solves conservation equations for momentum, energy, and species on a one dimensional (1D) domain corresponding to the line spanning the domain between nozzle orifice centers. The effects of turbulent mixing are modeled via a stochastic process, while the Kolmogorov and reactive length and time scales are explicitly resolved and a detailed chemical kinetic mechanism is used. Comparisons between model and DNS results for spatial mean and root-mean-square (RMS) velocity, temperature, and major and minor species profiles aremore » shown. The ODT approach shows qualitatively and quantitatively reasonable agreement with the DNS data. Scatter plots and statistics conditioned on temperature are also compared for heat release rate and all species. ODT is able to capture the range of results depicted by DNS. As a result, conditional statistics show signs of underignition.« less

An algorithm for modeling entrainment and naturally and chemically dispersed oil droplet size distribution under surface breaking wave conditions.

PubMed

Li, Zhengkai; Spaulding, Malcolm L; French-McCay, Deborah

2017-06-15

A surface oil entrainment model and droplet size model have been developed to estimate the flux of oil under surface breaking waves. Both equations are expressed in dimensionless Weber number (We) and Ohnesorge number (Oh, which explicitly accounts for the oil viscosity, density, and oil-water interfacial tension). Data from controlled lab studies, large-scale wave tank tests, and field observations have been used to calibrate the constants of the two independent equations. Predictions using the new algorithm compared well with the observed amount of oil removed from the surface and the sizes of the oil droplets entrained in the water column. Simulations with the new algorithm, implemented in a comprehensive spill model, show that entrainment rates increase more rapidly with wind speed than previously predicted based on the existing Delvigne and Sweeney's (1988) model, and a quasi-stable droplet size distribution (d<~50μm) is developed in the near surface water. Copyright © 2017 Elsevier Ltd. All rights reserved.

Diffusion-controlled reactions modeling in Geant4-DNA

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

Karamitros, M., E-mail: matkara@gmail.com; CNRS, INCIA, UMR 5287, F-33400 Talence; Luan, S.

2014-10-01

Context Under irradiation, a biological system undergoes a cascade of chemical reactions that can lead to an alteration of its normal operation. There are different types of radiation and many competing reactions. As a result the kinetics of chemical species is extremely complex. The simulation becomes then a powerful tool which, by describing the basic principles of chemical reactions, can reveal the dynamics of the macroscopic system. To understand the dynamics of biological systems under radiation, since the 80s there have been on-going efforts carried out by several research groups to establish a mechanistic model that consists in describing allmore » the physical, chemical and biological phenomena following the irradiation of single cells. This approach is generally divided into a succession of stages that follow each other in time: (1) the physical stage, where the ionizing particles interact directly with the biological material; (2) the physico-chemical stage, where the targeted molecules release their energy by dissociating, creating new chemical species; (3) the chemical stage, where the new chemical species interact with each other or with the biomolecules; (4) the biological stage, where the repairing mechanisms of the cell come into play. This article focuses on the modeling of the chemical stage. Method This article presents a general method of speeding-up chemical reaction simulations in fluids based on the Smoluchowski equation and Monte-Carlo methods, where all molecules are explicitly simulated and the solvent is treated as a continuum. The model describes diffusion-controlled reactions. This method has been implemented in Geant4-DNA. The keys to the new algorithm include: (1) the combination of a method to compute time steps dynamically with a Brownian bridge process to account for chemical reactions, which avoids costly fixed time step simulations; (2) a k–d tree data structure for quickly locating, for a given molecule, its closest reactants. The performance advantage is presented in terms of complexity, and the accuracy of the new algorithm is demonstrated by simulating radiation chemistry in the context of the Geant4-DNA project. Application The time-dependent radiolytic yields of the main chemical species formed after irradiation are computed for incident protons at different energies (from 50 MeV to 500 keV). Both the time-evolution and energy dependency of the yields are discussed. The evolution, at one microsecond, of the yields of hydroxyls and solvated electrons with respect to the linear energy transfer is compared to theoretical and experimental data. According to our results, at high linear energy transfer, modeling radiation chemistry in the trading compartment representation might be adopted.« less

On explicit algebraic stress models for complex turbulent flows

NASA Technical Reports Server (NTRS)

Gatski, T. B.; Speziale, C. G.

1992-01-01

Explicit algebraic stress models that are valid for three-dimensional turbulent flows in noninertial frames are systematically derived from a hierarchy of second-order closure models. This represents a generalization of the model derived by Pope who based his analysis on the Launder, Reece, and Rodi model restricted to two-dimensional turbulent flows in an inertial frame. The relationship between the new models and traditional algebraic stress models -- as well as anistropic eddy visosity models -- is theoretically established. The need for regularization is demonstrated in an effort to explain why traditional algebraic stress models have failed in complex flows. It is also shown that these explicit algebraic stress models can shed new light on what second-order closure models predict for the equilibrium states of homogeneous turbulent flows and can serve as a useful alternative in practical computations.

Georeferenced model simulations efficiently support targeted monitoring

NASA Astrophysics Data System (ADS)

Berlekamp, Jürgen; Klasmeier, Jörg

2010-05-01

The European Water Framework Directive (WFD) demands the good ecological and chemical status of surface waters. To meet the definition of good chemical status of the WFD surface water concentrations of priority pollutants must not exceed established environmental quality standards (EQS). Surveillance of the concentrations of numerous chemical pollutants in whole river basins by monitoring is laborious and time-consuming. Moreover, measured data do often not allow for immediate source apportionment which is a prerequisite for defining promising reduction strategies to be implemented within the programme of measures. In this context, spatially explicit model approaches are highly advantageous because they provide a direct link between local point emissions (e.g. treated wastewater) or diffuse non-point emissions (e.g. agricultural runoff) and resulting surface water concentrations. Scenario analyses with such models allow for a priori investigation of potential positive effects of reduction measures such as optimization of wastewater treatment. The geo-referenced model GREAT-ER (Geography-referenced Regional Exposure Assessment Tool for European Rivers) has been designed to calculate spatially resolved averaged concentrations for different flow conditions (e.g. mean or low flow) based on emission estimations for local point source emissions such as treated effluents from wastewater treatment plants. The methodology was applied to selected pharmaceuticals (diclofenac, sotalol, metoprolol, carbamazepin) in the Main river basin in Germany (approx. 27,290 km²). Average concentrations of the compounds were calculated for each river reach in the whole catchment. Simulation results were evaluated by comparison with available data from orienting monitoring and used to develop an optimal monitoring strategy for the assessment of water quality regarding micropollutants at the catchment scale.

Organic photolysis reactions in tropospheric aerosols: effect on secondary organic aerosol formation and lifetime

DOE PAGES

Hodzic, A.; Madronich, S.; Kasibhatla, P. S.; ...

2015-08-20

This paper presents the first modeling estimates of the potential effect of gas- and particle-phase organic photolysis reactions on the formation and lifetime of secondary organic aerosols (SOAs). Typically only photolysis of smaller organic molecules (e.g., formaldehyde) for which explicit data exist is included in chemistry–climate models. Here, we specifically examine the photolysis of larger molecules that actively partition between the gas and particle phases. The chemical mechanism generator GECKO-A is used to explicitly model SOA formation from α-pinene, toluene, and C 12 and C 16 n-alkane reactions with OH at low and high NO x. Simulations are conducted formore » typical mid-latitude conditions and a solar zenith angle of 45° (permanent daylight). The results show that after 4 days of chemical aging under those conditions (equivalent to 8 days in the summer mid-latitudes), gas-phase photolysis leads to a moderate decrease in SOA yields, i.e., ~15 % (low NO x) to ~45 % (high NO x) for α-pinene, ~15 % for toluene, ~25 % for C 12 n-alkane, and ~10 % for C 16 n-alkane. The small effect of gas-phase photolysis on low-volatility n-alkanes such as C 16 n-alkane is due to the rapid partitioning of early-generation products to the particle phase, where they are protected from gas-phase photolysis. Minor changes are found in the volatility distribution of organic products and in oxygen to carbon ratios. The decrease in SOA mass is increasingly more important after a day of chemical processing, suggesting that most laboratory experiments are likely too short to quantify the effect of gas-phase photolysis on SOA yields. Our results also suggest that many molecules containing chromophores are preferentially partitioned into the particle phase before they can be photolyzed in the gas phase. Given the growing experimental evidence that these molecules can undergo in-particle photolysis, we performed sensitivity simulations using an empirically estimated SOA photolysis rate of J SOA = 4 × 10 −4 J NO2. Modeling results indicate that this photolytic loss rate would decrease SOA mass by 40–60 % for most species after 10 days of equivalent atmospheric aging at mid-latitudes in the summer. It should be noted that in our simulations we do not consider in-particle or aqueous-phase reactions which could modify the chemical composition of the particle and thus the quantity of photolabile species. The atmospheric implications of our results are significant for both the SOA global distribution and lifetime. GEOS-Chem global model results suggest that particle-phase photolytic reactions could be an important loss process for SOA in the atmosphere, removing aerosols from the troposphere on timescales of less than 7 days that are comparable to wet deposition.« less

Communication: Relaxation-limited electronic currents in extended reservoir simulations

NASA Astrophysics Data System (ADS)

Gruss, Daniel; Smolyanitsky, Alex; Zwolak, Michael

2017-10-01

Open-system approaches are gaining traction in the simulation of charge transport in nanoscale and molecular electronic devices. In particular, "extended reservoir" simulations, where explicit reservoir degrees of freedom are present, allow for the computation of both real-time and steady-state properties but require relaxation of the extended reservoirs. The strength of this relaxation, γ, influences the conductance, giving rise to a "turnover" behavior analogous to Kramers turnover in chemical reaction rates. We derive explicit, general expressions for the weak and strong relaxation limits. For weak relaxation, the conductance increases linearly with γ and every electronic state of the total explicit system contributes to the electronic current according to its "reduced" weight in the two extended reservoir regions. Essentially, this represents two conductors in series—one at each interface with the implicit reservoirs that provide the relaxation. For strong relaxation, a "dual" expression-one with the same functional form-results, except now proportional to 1/γ and dependent on the system of interest's electronic states, reflecting that the strong relaxation is localizing electrons in the extended reservoirs. Higher order behavior (e.g., γ2 or 1/γ2) can occur when there is a gap in the frequency spectrum. Moreover, inhomogeneity in the frequency spacing can give rise to a pseudo-plateau regime. These findings yield a physically motivated approach to diagnosing numerical simulations and understanding the influence of relaxation, and we examine their occurrence in both simple models and a realistic, fluctuating graphene nanoribbon.

Molecular simulations of self-assembly processes in metal-organic frameworks: Model dependence

NASA Astrophysics Data System (ADS)

Biswal, Debasmita; Kusalik, Peter G.

2017-07-01

Molecular simulation is a powerful tool for investigating microscopic behavior in various chemical systems, where the use of suitable models is critical to successfully reproduce the structural and dynamic properties of the real systems of interest. In this context, molecular dynamics simulation studies of self-assembly processes in metal-organic frameworks (MOFs), a well-known class of porous materials with interesting chemical and physical properties, are relatively challenging, where a reasonably accurate representation of metal-ligand interactions is anticipated to play an important role. In the current study, we both investigate the performance of some existing models and introduce and test new models to help explore the self-assembly in an archetypal Zn-carboxylate MOF system. To this end, the behavior of six different Zn-ion models, three solvent models, and two ligand models was examined and validated against key experimental structural parameters. To explore longer time scale ordering events during MOF self-assembly via explicit solvent simulations, it is necessary to identify a suitable combination of simplified model components representing metal ions, organic ligands, and solvent molecules. It was observed that an extended cationic dummy atom (ECDA) Zn-ion model combined with an all-atom carboxylate ligand model and a simple dipolar solvent model can reproduce characteristic experimental structures for the archetypal MOF system. The successful use of these models in extensive sets of molecular simulations, which provide key insights into the self-assembly mechanism of this archetypal MOF system occurring during the early stages of this process, has been very recently reported.

Flexible explicit but rigid implicit learning in a visuomotor adaptation task

PubMed Central

Bond, Krista M.

2015-01-01

There is mounting evidence for the idea that performance in a visuomotor rotation task can be supported by both implicit and explicit forms of learning. The implicit component of learning has been well characterized in previous experiments and is thought to arise from the adaptation of an internal model driven by sensorimotor prediction errors. However, the role of explicit learning is less clear, and previous investigations aimed at characterizing the explicit component have relied on indirect measures such as dual-task manipulations, posttests, and descriptive computational models. To address this problem, we developed a new method for directly assaying explicit learning by having participants verbally report their intended aiming direction on each trial. While our previous research employing this method has demonstrated the possibility of measuring explicit learning over the course of training, it was only tested over a limited scope of manipulations common to visuomotor rotation tasks. In the present study, we sought to better characterize explicit and implicit learning over a wider range of task conditions. We tested how explicit and implicit learning change as a function of the specific visual landmarks used to probe explicit learning, the number of training targets, and the size of the rotation. We found that explicit learning was remarkably flexible, responding appropriately to task demands. In contrast, implicit learning was strikingly rigid, with each task condition producing a similar degree of implicit learning. These results suggest that explicit learning is a fundamental component of motor learning and has been overlooked or conflated in previous visuomotor tasks. PMID:25855690

EPR parameters of L-α-alanine radicals in aqueous solution: a first-principles study

NASA Astrophysics Data System (ADS)

Janbazi, Mehdi; T. Azar, Yavar; Ziaie, Farhood

2018-07-01

EPR (electron paramagnetic resonance) response for a wide range of possible alanine radicals has been analysed employing quantum chemical methods. The strong correlation between geometry and EPR parameter structure of these radicals has been shown in this research work. Significant solvent effect on EPR parameters has been shown employing both explicit and implicit solvent models. In a relatively good agreement with the experiment, stable conformation of these radicals in acidic and basic conditions was determined, and a new conformation was suggested based on possible proton transfer in the intermediate pH range. The employed methodology along with experimental results may be used for the characterisation of different radiation-induced amino acid radicals.

Geothermometric evaluation of geothermal resources in southeastern Idaho

NASA Astrophysics Data System (ADS)

Neupane, G.; Mattson, E. D.; McLing, T. L.; Palmer, C. D.; Smith, R. W.; Wood, T. R.; Podgorney, R. K.

2016-01-01

Southeastern Idaho exhibits numerous warm springs, warm water from shallow wells, and hot water from oil and gas test wells that indicate a potential for geothermal development in the area. We have estimated reservoir temperatures from chemical composition of thermal waters in southeastern Idaho using an inverse geochemical modeling technique (Reservoir Temperature Estimator, RTEst) that calculates the temperature at which multiple minerals are simultaneously at equilibrium while explicitly accounting for the possible loss of volatile constituents (e.g., CO2), boiling and/or water mixing. The temperature estimates in the region varied from moderately warm (59 °C) to over 175 °C. Specifically, hot springs near Preston, Idaho, resulted in the highest reservoir temperature estimates in the region.

Modeling Interactions Among Turbulence, Gas-Phase Chemistry, Soot and Radiation Using Transported PDF Methods

NASA Astrophysics Data System (ADS)

Haworth, Daniel

2013-11-01

The importance of explicitly accounting for the effects of unresolved turbulent fluctuations in Reynolds-averaged and large-eddy simulations of chemically reacting turbulent flows is increasingly recognized. Transported probability density function (PDF) methods have emerged as one of the most promising modeling approaches for this purpose. In particular, PDF methods provide an elegant and effective resolution to the closure problems that arise from averaging or filtering terms that correspond to nonlinear point processes, including chemical reaction source terms and radiative emission. PDF methods traditionally have been associated with studies of turbulence-chemistry interactions in laboratory-scale, atmospheric-pressure, nonluminous, statistically stationary nonpremixed turbulent flames; and Lagrangian particle-based Monte Carlo numerical algorithms have been the predominant method for solving modeled PDF transport equations. Recent advances and trends in PDF methods are reviewed and discussed. These include advances in particle-based algorithms, alternatives to particle-based algorithms (e.g., Eulerian field methods), treatment of combustion regimes beyond low-to-moderate-Damköhler-number nonpremixed systems (e.g., premixed flamelets), extensions to include radiation heat transfer and multiphase systems (e.g., soot and fuel sprays), and the use of PDF methods as the basis for subfilter-scale modeling in large-eddy simulation. Examples are provided that illustrate the utility and effectiveness of PDF methods for physics discovery and for applications to practical combustion systems. These include comparisons of results obtained using the PDF method with those from models that neglect unresolved turbulent fluctuations in composition and temperature in the averaged or filtered chemical source terms and/or the radiation heat transfer source terms. In this way, the effects of turbulence-chemistry-radiation interactions can be isolated and quantified.

Development of a reactive burn model based on an explicit viscoplastic pore collapse model

NASA Astrophysics Data System (ADS)

Bouton, E.; Lefrançois, A.; Belmas, R.

2017-01-01

The aim of this study is to develop a reactive burn model based upon a microscopic hot spot model to compute the shock-initiation of pressed TATB high explosives. Such a model has been implemented in a lagrangian hydrodynamic code. In our calculations, 8 pore radii, ranging from 40 nm to 0.63 μm, have been taken into account and the porosity fraction associated to each void radius has been deduced from the Ultra-Small-Angle X-ray Scattering measurements (USAXS) for PBX-9502. The last parameter of our model is a burn rate that depends on three variables. The first two are the reaction progress variable and the lead shock pressure, the last one is the chemical reaction site number produced in the flow and calculated by the microscopic model. This burn rate has been calibrated by fitting pressure, velocity profiles and run distances to detonation. As the computed results are in close agreement with the measured ones, this model is able to perform a wide variety of numerical simulations including single, double shock waves and the desensitization phenomenon.

Electric Double-Layer Structure in Primitive Model Electrolytes. Comparing Molecular Dynamics with Local-Density Approximations

DOE PAGES

Giera, Brian; Lawrence Livermore National Lab.; Henson, Neil; ...

2015-02-27

We evaluate the accuracy of local-density approximations (LDAs) using explicit molecular dynamics simulations of binary electrolytes comprised of equisized ions in an implicit solvent. The Bikerman LDA, which considers ions to occupy a lattice, poorly captures excluded volume interactions between primitive model ions. Instead, LDAs based on the Carnahan–Starling (CS) hard-sphere equation of state capture simulated values of ideal and excess chemical potential profiles extremely well, as is the relationship between surface charge density and electrostatic potential. Excellent agreement between the EDL capacitances predicted by CS-LDAs and computed in molecular simulations is found even in systems where ion correlations drivemore » strong density and free charge oscillations within the EDL, despite the inability of LDAs to capture the oscillations in the detailed EDL profiles.« less

Solvent Reaction Field Potential inside an Uncharged Globular Protein: A Bridge between Implicit and Explicit Solvent Models?

PubMed Central

Baker, Nathan A.; McCammon, J. Andrew

2008-01-01

The solvent reaction field potential of an uncharged protein immersed in Simple Point Charge/Extended (SPC/E) explicit solvent was computed over a series of molecular dynamics trajectories, intotal 1560 ns of simulation time. A finite, positive potential of 13 to 24 kbTec−1 (where T = 300K), dependent on the geometry of the solvent-accessible surface, was observed inside the biomolecule. The primary contribution to this potential arose from a layer of positive charge density 1.0 Å from the solute surface, on average 0.008 ec/Å3, which we found to be the product of a highly ordered first solvation shell. Significant second solvation shell effects, including additional layers of charge density and a slight decrease in the short-range solvent-solvent interaction strength, were also observed. The impact of these findings on implicit solvent models was assessed by running similar explicit-solvent simulations on the fully charged protein system. When the energy due to the solvent reaction field in the uncharged system is accounted for, correlation between per-atom electrostatic energies for the explicit solvent model and a simple implicit (Poisson) calculation is 0.97, and correlation between per-atom energies for the explicit solvent model and a previously published, optimized Poisson model is 0.99. PMID:17949217

Solvent reaction field potential inside an uncharged globular protein: A bridge between implicit and explicit solvent models?

NASA Astrophysics Data System (ADS)

Cerutti, David S.; Baker, Nathan A.; McCammon, J. Andrew

2007-10-01

The solvent reaction field potential of an uncharged protein immersed in simple point charge/extended explicit solvent was computed over a series of molecular dynamics trajectories, in total 1560ns of simulation time. A finite, positive potential of 13-24 kbTec-1 (where T =300K), dependent on the geometry of the solvent-accessible surface, was observed inside the biomolecule. The primary contribution to this potential arose from a layer of positive charge density 1.0Å from the solute surface, on average 0.008ec/Å3, which we found to be the product of a highly ordered first solvation shell. Significant second solvation shell effects, including additional layers of charge density and a slight decrease in the short-range solvent-solvent interaction strength, were also observed. The impact of these findings on implicit solvent models was assessed by running similar explicit solvent simulations on the fully charged protein system. When the energy due to the solvent reaction field in the uncharged system is accounted for, correlation between per-atom electrostatic energies for the explicit solvent model and a simple implicit (Poisson) calculation is 0.97, and correlation between per-atom energies for the explicit solvent model and a previously published, optimized Poisson model is 0.99.

Ancient numerical daemons of conceptual hydrological modeling: 1. Fidelity and efficiency of time stepping schemes

NASA Astrophysics Data System (ADS)

Clark, Martyn P.; Kavetski, Dmitri

2010-10-01

A major neglected weakness of many current hydrological models is the numerical method used to solve the governing model equations. This paper thoroughly evaluates several classes of time stepping schemes in terms of numerical reliability and computational efficiency in the context of conceptual hydrological modeling. Numerical experiments are carried out using 8 distinct time stepping algorithms and 6 different conceptual rainfall-runoff models, applied in a densely gauged experimental catchment, as well as in 12 basins with diverse physical and hydroclimatic characteristics. Results show that, over vast regions of the parameter space, the numerical errors of fixed-step explicit schemes commonly used in hydrology routinely dwarf the structural errors of the model conceptualization. This substantially degrades model predictions, but also, disturbingly, generates fortuitously adequate performance for parameter sets where numerical errors compensate for model structural errors. Simply running fixed-step explicit schemes with shorter time steps provides a poor balance between accuracy and efficiency: in some cases daily-step adaptive explicit schemes with moderate error tolerances achieved comparable or higher accuracy than 15 min fixed-step explicit approximations but were nearly 10 times more efficient. From the range of simple time stepping schemes investigated in this work, the fixed-step implicit Euler method and the adaptive explicit Heun method emerge as good practical choices for the majority of simulation scenarios. In combination with the companion paper, where impacts on model analysis, interpretation, and prediction are assessed, this two-part study vividly highlights the impact of numerical errors on critical performance aspects of conceptual hydrological models and provides practical guidelines for robust numerical implementation.

Kinetic freeze-out conditions for the production of resonances, hadronic molecules, and light nuclei

NASA Astrophysics Data System (ADS)

Cho, Sungtae; Song, Taesoo; Lee, Su Houng

2018-02-01

We investigate the freeze-out conditions of a particle in an expanding system of interacting particles in order to understand the productions of resonances, hadronic molecules, and light nuclei in heavy-ion collisions. Applying the kinetic freeze-out condition with explicit hydrodynamic calculations for the expanding hadronic phase to the daughter particles of K* mesons, we find that the larger suppression of the yield ratio of K*/K at the Large Hadron Collider (LHC) than at the Relativisitic Heavy Ion Collider (RHIC) compared to the expectations from the statistical hadronization model based on chemical freeze-out parameters reflects the lower kinetic freeze-out temperature at LHC than at RHIC. Furthermore, we point out that for the light nuclei or hadronic molecules that are bound, the freeze-out condition should be applied to the respective particle in the hadronic matter. It is then shown through the rate equation that when the nucleon and pion numbers are kept constant at the chemical freeze-out value during the hadronic phase, the deuteron number quickly approaches an asymptotic value that is close to the statistical model prediction at the chemical freeze-out point. We argue that the reduction seen in K* numbers is a typical result for a particle that has a large natural decay width decaying into daughter particles, while that for deuteron is typical for a stable hadronic bound state.

Real-time monitoring of steady-state pulsed chemical beam epitaxy by p-polarized reflectance

NASA Astrophysics Data System (ADS)

Bachmann, K. J.; Sukidi, N.; Höpfner, C.; Harris, C.; Dietz, N.; Tran, H. T.; Beeler, S.; Ito, K.; Banks, H. T.

1998-01-01

The structure in the p-polarized reflectance (PR) intensity Rp4( t) - observed under conditions of pulsed chemical beam epitaxy (PCBE) - is modeled on the basis of the four-layer stack: ambient/surface reaction layer (SRL)/epilayer/substrate. Linearization of the PR intensity with regard to the phase factor associated with the SRL results in a good approximation that can be expressed as Rp4 = Rp3 + ΔRp. Rp3 is the reflectivity of the three-layer stack ambient-epilayer-substrate. ΔRp describes the properties of the SRL. An explicit relation is derived between ΔRp( t) and the time-dependent surface concentrations ch( t) ( h = 1, 2, …, N) of the constituents of the SRL, which holds for conditions of submonolayer coverage of the surface by source vapor molecules. Under conditions of low temperature PCBE at high flux, the SRL is expected to exhibit nonideal behavior, mandating replacement of the surface concentrations by activities. Also, in this case, the thickness of the SRL must be represented in terms of partial molar volumina Vh. Since the relation between ΔRp( t) and the activities of reactants, intermediates and products of the chemical reactions driving heteroepitaxial growth is non-linear, the extraction of kinetic parameters from the measured time dependence of the PR signal generally requires numerical modeling.

Empirical methods for modeling landscape change, ecosystem services, and biodiversity

Treesearch

David Lewis; Ralph Alig

2009-01-01

The purpose of this paper is to synthesize recent economics research aimed at integrating discrete-choice econometric models of land-use change with spatially-explicit landscape simulations and quantitative ecology. This research explicitly models changes in the spatial pattern of landscapes in two steps: 1) econometric estimation of parcel-scale transition...

SPATIALLY EXPLICIT MICRO-LEVEL MODELLING OF LAND USE CHANGE AT THE RURAL-URBAN INTERFACE. (R828012)

EPA Science Inventory

This paper describes micro-economic models of land use change applicable to the rural–urban interface in the US. Use of a spatially explicit micro-level modelling approach permits the analysis of regional patterns of land use as the aggregate outcomes of many, disparate...

Studying Activity Series of Metals.

ERIC Educational Resources Information Center

Hoon, Tien-Ghun; And Others

1995-01-01

Presents teaching strategies that illustrate the linking together of numerous chemical concepts involving the activity of metals (quantitative analysis, corrosion, and electrolysis) through the use of deep-level processing strategies. Concludes that making explicit links in the process of teaching chemistry can lead effectively to meaningful…

A Galilean Invariant Explicit Algebraic Reynolds Stress Model for Curved Flows

NASA Technical Reports Server (NTRS)

Girimaji, Sharath

1996-01-01

A Galilean invariant weak-equilbrium hypothesis that is sensitive to streamline curvature is proposed. The hypothesis leads to an algebraic Reynolds stress model for curved flows that is fully explicit and self-consistent. The model is tested in curved homogeneous shear flow: the agreement is excellent with Reynolds stress closure model and adequate with available experimental data.

A functional-dynamic reflection on participatory processes in modeling projects.

PubMed

Seidl, Roman

2015-12-01

The participation of nonscientists in modeling projects/studies is increasingly employed to fulfill different functions. However, it is not well investigated if and how explicitly these functions and the dynamics of a participatory process are reflected by modeling projects in particular. In this review study, I explore participatory modeling projects from a functional-dynamic process perspective. The main differences among projects relate to the functions of participation-most often, more than one per project can be identified, along with the degree of explicit reflection (i.e., awareness and anticipation) on the dynamic process perspective. Moreover, two main approaches are revealed: participatory modeling covering diverse approaches and companion modeling. It becomes apparent that the degree of reflection on the participatory process itself is not always explicit and perfectly visible in the descriptions of the modeling projects. Thus, the use of common protocols or templates is discussed to facilitate project planning, as well as the publication of project results. A generic template may help, not in providing details of a project or model development, but in explicitly reflecting on the participatory process. It can serve to systematize the particular project's approach to stakeholder collaboration, and thus quality management.

A numerical code for the simulation of non-equilibrium chemically reacting flows on hybrid CPU-GPU clusters

NASA Astrophysics Data System (ADS)

Kudryavtsev, Alexey N.; Kashkovsky, Alexander V.; Borisov, Semyon P.; Shershnev, Anton A.

2017-10-01

In the present work a computer code RCFS for numerical simulation of chemically reacting compressible flows on hybrid CPU/GPU supercomputers is developed. It solves 3D unsteady Euler equations for multispecies chemically reacting flows in general curvilinear coordinates using shock-capturing TVD schemes. Time advancement is carried out using the explicit Runge-Kutta TVD schemes. Program implementation uses CUDA application programming interface to perform GPU computations. Data between GPUs is distributed via domain decomposition technique. The developed code is verified on the number of test cases including supersonic flow over a cylinder.

Algorithm For Hypersonic Flow In Chemical Equilibrium

NASA Technical Reports Server (NTRS)

Palmer, Grant

1989-01-01

Implicit, finite-difference, shock-capturing algorithm calculates inviscid, hypersonic flows in chemical equilibrium. Implicit formulation chosen because overcomes limitation on mathematical stability encountered in explicit formulations. For dynamical portion of problem, Euler equations written in conservation-law form in Cartesian coordinate system for two-dimensional or axisymmetric flow. For chemical portion of problem, equilibrium state of gas at each point in computational grid determined by minimizing local Gibbs free energy, subject to local conservation of molecules, atoms, ions, and total enthalpy. Major advantage: resulting algorithm naturally stable and captures strong shocks without help of artificial-dissipation terms to damp out spurious numerical oscillations.

De Novo Design of Bioactive Small Molecules by Artificial Intelligence.

PubMed

Merk, Daniel; Friedrich, Lukas; Grisoni, Francesca; Schneider, Gisbert

2018-01-01

Generative artificial intelligence offers a fresh view on molecular design. We present the first-time prospective application of a deep learning model for designing new druglike compounds with desired activities. For this purpose, we trained a recurrent neural network to capture the constitution of a large set of known bioactive compounds represented as SMILES strings. By transfer learning, this general model was fine-tuned on recognizing retinoid X and peroxisome proliferator-activated receptor agonists. We synthesized five top-ranking compounds designed by the generative model. Four of the compounds revealed nanomolar to low-micromolar receptor modulatory activity in cell-based assays. Apparently, the computational model intrinsically captured relevant chemical and biological knowledge without the need for explicit rules. The results of this study advocate generative artificial intelligence for prospective de novo molecular design, and demonstrate the potential of these methods for future medicinal chemistry. © 2018 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Radiative interactions in chemically reacting supersonic internal flows

NASA Technical Reports Server (NTRS)

Tiwari, S. N.; Chandrasekhar, R.

1991-01-01

The two-dimensional, elliptic Navier-Stokes equations are used to investigate supersonic flows with finite-rate chemistry and radiation for hydrogen-air systems. The chemistry source terms in the species equation is treated implicitly to alleviate the stiffness associated with fast reactions. The explicit, unsplit MacCormack finite-difference scheme is used to advance the governing equations in time, until convergence is achieved. The specific problem considered is the premixed flow in a channel with a ten-degree compression ramp. Three different chemistry models are used, accounting for increasing number of reactions and participating species. Two chemistry models assure nitrogen as inert, while the third model accounts for nitrogen reactions and NO(x) formation. The tangent slab approximation is used in the radiative flux formulation. A pseudo-gray model is used to represent the absorption-emission characteristics of the participating species. Results obtained for specific conditions indicate that the radiative interactions vary substantially, depending on reactions involving HO2 and NO species and that this can have a significant influence on the flowfield.

High Performance Programming Using Explicit Shared Memory Model on Cray T3D1

NASA Technical Reports Server (NTRS)

Simon, Horst D.; Saini, Subhash; Grassi, Charles

1994-01-01

The Cray T3D system is the first-phase system in Cray Research, Inc.'s (CRI) three-phase massively parallel processing (MPP) program. This system features a heterogeneous architecture that closely couples DEC's Alpha microprocessors and CRI's parallel-vector technology, i.e., the Cray Y-MP and Cray C90. An overview of the Cray T3D hardware and available programming models is presented. Under Cray Research adaptive Fortran (CRAFT) model four programming methods (data parallel, work sharing, message-passing using PVM, and explicit shared memory model) are available to the users. However, at this time data parallel and work sharing programming models are not available to the user community. The differences between standard PVM and CRI's PVM are highlighted with performance measurements such as latencies and communication bandwidths. We have found that the performance of neither standard PVM nor CRI s PVM exploits the hardware capabilities of the T3D. The reasons for the bad performance of PVM as a native message-passing library are presented. This is illustrated by the performance of NAS Parallel Benchmarks (NPB) programmed in explicit shared memory model on Cray T3D. In general, the performance of standard PVM is about 4 to 5 times less than obtained by using explicit shared memory model. This degradation in performance is also seen on CM-5 where the performance of applications using native message-passing library CMMD on CM-5 is also about 4 to 5 times less than using data parallel methods. The issues involved (such as barriers, synchronization, invalidating data cache, aligning data cache etc.) while programming in explicit shared memory model are discussed. Comparative performance of NPB using explicit shared memory programming model on the Cray T3D and other highly parallel systems such as the TMC CM-5, Intel Paragon, Cray C90, IBM-SP1, etc. is presented.

Translational Science for Energy and Beyond.

PubMed

McKone, James R; Crans, Debbie C; Martin, Cheryl; Turner, John; Duggal, Anil R; Gray, Harry B

2016-09-19

A clear challenge for the coming decades is decreasing the carbon intensity of the global energy supply while simultaneously accommodating a rapid worldwide increase in power demand. Meeting this challenge of providing abundant, clean energy undoubtedly requires synergistic efforts between basic and applied researchers in the chemical sciences to develop and deploy new technologies. Among the available options, solar energy is one of the promising targets because of the high abundance of solar photons over much of the globe. Similarly, decarbonization of the global energy supply will require clean sources of hydrogen to use as reducing equivalents for fuel and chemical feedstocks. In this report, we discuss the importance of translational research-defined as work that explicitly targets basic discovery as well as technology development-in the context of photovoltaics and solar fuels. We focus on three representative research programs encompassing translational research in government, industry, and academia. We then discuss more broadly the benefits and challenges of translational research models and offer recommendations for research programs that address societal challenges in the energy sector and beyond.

Multi-GPU unsteady 2D flow simulation coupled with a state-to-state chemical kinetics

NASA Astrophysics Data System (ADS)

Tuttafesta, Michele; Pascazio, Giuseppe; Colonna, Gianpiero

2016-10-01

In this work we are presenting a GPU version of a CFD code for high enthalpy reacting flow, using the state-to-state approach. In supersonic and hypersonic flows, thermal and chemical non-equilibrium is one of the fundamental aspects that must be taken into account for the accurate characterization of the plasma and state-to-state kinetics is the most accurate approach used for this kind of problems. This model consists in writing a continuity equation for the population of each vibrational level of the molecules in the mixture, determining at the same time the species densities and the distribution of the population in internal levels. An explicit scheme is employed here to integrate the governing equations, so as to exploit the GPU structure and obtain an efficient algorithm. The best performances are obtained for reacting flows in state-to-state approach, reaching speedups of the order of 100, thanks to the use of an operator splitting scheme for the kinetics equations.

Exchange repulsive potential adaptable for electronic structure changes during chemical reactions

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

Yokogawa, D., E-mail: d.yokogawa@chem.nagoya-u.ac.jp

2015-04-28

Hybrid methods combining quantum mechanical (QM) and classical calculations are becoming important tools in chemistry. The popular approach to calculate the interaction between QM and classical calculations employs interatomic potentials. In most cases, the interatomic potential is constructed of an electrostatic (ES) potential and a non-ES potential. Because QM treatment is employed in the calculation of the ES potential, the electronic change can be considered in this ES potential. However, QM treatment of the non-ES potential is difficult because of high computational cost. To overcome this difficulty of evaluating the non-ES potential, we proposed an exchange repulsive potential as themore » main part of the non-ES potential on the basis of a QM approach. This potential is independent of empirical parameters and adaptable for electronic structure. We combined this potential with the reference interaction site model self-consistent field explicitly including spatial electron density distribution and successfully applied it to the chemical reactions in aqueous phase.« less

Chemical dynamics of the first proton-coupled electron transfer of water oxidation on TiO2 anatase.

PubMed

Chen, Jia; Li, Ye-Fei; Sit, Patrick; Selloni, Annabella

2013-12-18

Titanium dioxide (TiO2) is a prototype, water-splitting (photo)catalyst, but its performance is limited by the large overpotential for the oxygen evolution reaction (OER). We report here a first-principles density functional theory study of the chemical dynamics of the first proton-coupled electron transfer (PCET), which is considered responsible for the large OER overpotential on TiO2. We use a periodic model of the TiO2/water interface that includes a slab of anatase TiO2 and explicit water molecules, sample the solvent configurations by first principles molecular dynamics, and determine the energy profiles of the two electronic states involved in the electron transfer (ET) by hybrid functional calculations. Our results suggest that the first PCET is sequential, with the ET following the proton transfer. The ET occurs via an inner sphere process, which is facilitated by a state in which one electronic hole is shared by the two oxygen ions involved in the transfer.

Accelerating moderately stiff chemical kinetics in reactive-flow simulations using GPUs

NASA Astrophysics Data System (ADS)

Niemeyer, Kyle E.; Sung, Chih-Jen

2014-01-01

The chemical kinetics ODEs arising from operator-split reactive-flow simulations were solved on GPUs using explicit integration algorithms. Nonstiff chemical kinetics of a hydrogen oxidation mechanism (9 species and 38 irreversible reactions) were computed using the explicit fifth-order Runge-Kutta-Cash-Karp method, and the GPU-accelerated version performed faster than single- and six-core CPU versions by factors of 126 and 25, respectively, for 524,288 ODEs. Moderately stiff kinetics, represented with mechanisms for hydrogen/carbon-monoxide (13 species and 54 irreversible reactions) and methane (53 species and 634 irreversible reactions) oxidation, were computed using the stabilized explicit second-order Runge-Kutta-Chebyshev (RKC) algorithm. The GPU-based RKC implementation demonstrated an increase in performance of nearly 59 and 10 times, for problem sizes consisting of 262,144 ODEs and larger, than the single- and six-core CPU-based RKC algorithms using the hydrogen/carbon-monoxide mechanism. With the methane mechanism, RKC-GPU performed more than 65 and 11 times faster, for problem sizes consisting of 131,072 ODEs and larger, than the single- and six-core RKC-CPU versions, and up to 57 times faster than the six-core CPU-based implicit VODE algorithm on 65,536 ODEs. In the presence of more severe stiffness, such as ethylene oxidation (111 species and 1566 irreversible reactions), RKC-GPU performed more than 17 times faster than RKC-CPU on six cores for 32,768 ODEs and larger, and at best 4.5 times faster than VODE on six CPU cores for 65,536 ODEs. With a larger time step size, RKC-GPU performed at best 2.5 times slower than six-core VODE for 8192 ODEs and larger. Therefore, the need for developing new strategies for integrating stiff chemistry on GPUs was discussed.

An Empirical Polarizable Force Field Based on the Classical Drude Oscillator Model: Development History and Recent Applications

PubMed Central

2016-01-01

Molecular mechanics force fields that explicitly account for induced polarization represent the next generation of physical models for molecular dynamics simulations. Several methods exist for modeling induced polarization, and here we review the classical Drude oscillator model, in which electronic degrees of freedom are modeled by charged particles attached to the nuclei of their core atoms by harmonic springs. We describe the latest developments in Drude force field parametrization and application, primarily in the last 15 years. Emphasis is placed on the Drude-2013 polarizable force field for proteins, DNA, lipids, and carbohydrates. We discuss its parametrization protocol, development history, and recent simulations of biologically interesting systems, highlighting specific studies in which induced polarization plays a critical role in reproducing experimental observables and understanding physical behavior. As the Drude oscillator model is computationally tractable and available in a wide range of simulation packages, it is anticipated that use of these more complex physical models will lead to new and important discoveries of the physical forces driving a range of chemical and biological phenomena. PMID:26815602

Measures of Microbial Biomass for Soil Carbon Decomposition Models

NASA Astrophysics Data System (ADS)

Mayes, M. A.; Dabbs, J.; Steinweg, J. M.; Schadt, C. W.; Kluber, L. A.; Wang, G.; Jagadamma, S.

2014-12-01

Explicit parameterization of the decomposition of plant inputs and soil organic matter by microbes is becoming more widely accepted in models of various complexity, ranging from detailed process models to global-scale earth system models. While there are multiple ways to measure microbial biomass, chloroform fumigation-extraction (CFE) is commonly used to parameterize models.. However CFE is labor- and time-intensive, requires toxic chemicals, and it provides no specific information about the composition or function of the microbial community. We investigated correlations between measures of: CFE; DNA extraction yield; QPCR base-gene copy numbers for Bacteria, Fungi and Archaea; phospholipid fatty acid analysis; and direct cell counts to determine the potential for use as proxies for microbial biomass. As our ultimate goal is to develop a reliable, more informative, and faster methods to predict microbial biomass for use in models, we also examined basic soil physiochemical characteristics including texture, organic matter content, pH, etc. to identify multi-factor predictive correlations with one or more measures of the microbial community. Our work will have application to both microbial ecology studies and the next generation of process and earth system models.

Simulating ectomycorrhiza in boreal forests: implementing ectomycorrhizal fungi model MYCOFON in CoupModel (v5)

NASA Astrophysics Data System (ADS)

He, Hongxing; Meyer, Astrid; Jansson, Per-Erik; Svensson, Magnus; Rütting, Tobias; Klemedtsson, Leif

2018-02-01

The symbiosis between plants and Ectomycorrhizal fungi (ECM) is shown to considerably influence the carbon (C) and nitrogen (N) fluxes between the soil, rhizosphere, and plants in boreal forest ecosystems. However, ECM are either neglected or presented as an implicit, undynamic term in most ecosystem models, which can potentially reduce the predictive power of models.

In order to investigate the necessity of an explicit consideration of ECM in ecosystem models, we implement the previously developed MYCOFON model into a detailed process-based, soil-plant-atmosphere model, Coup-MYCOFON, which explicitly describes the C and N fluxes between ECM and roots. This new Coup-MYCOFON model approach (ECM explicit) is compared with two simpler model approaches: one containing ECM implicitly as a dynamic uptake of organic N considering the plant roots to represent the ECM (ECM implicit), and the other a static N approach in which plant growth is limited to a fixed N level (nonlim). Parameter uncertainties are quantified using Bayesian calibration in which the model outputs are constrained to current forest growth and soil C / N ratio for four forest sites along a climate and N deposition gradient in Sweden and simulated over a 100-year period.

The nonlim approach could not describe the soil C / N ratio due to large overestimation of soil N sequestration but simulate the forest growth reasonably well. The ECM implicit and explicit approaches both describe the soil C / N ratio well but slightly underestimate the forest growth. The implicit approach simulated lower litter production and soil respiration than the explicit approach. The ECM explicit Coup-MYCOFON model provides a more detailed description of internal ecosystem fluxes and feedbacks of C and N between plants, soil, and ECM. Our modeling highlights the need to incorporate ECM and organic N uptake into ecosystem models, and the nonlim approach is not recommended for future long-term soil C and N predictions. We also provide a key set of posterior fungal parameters that can be further investigated and evaluated in future ECM studies.

An approach to modeling coupled thermal-hydraulic-chemical processes in geothermal systems

USGS Publications Warehouse

Palguta, Jennifer; Williams, Colin F.; Ingebritsen, Steven E.; Hickman, Stephen H.; Sonnenthal, Eric

2011-01-01

Interactions between hydrothermal fluids and rock alter mineralogy, leading to the formation of secondary minerals and potentially significant physical and chemical property changes. Reactive transport simulations are essential for evaluating the coupled processes controlling the geochemical, thermal and hydrological evolution of geothermal systems. The objective of this preliminary investigation is to successfully replicate observations from a series of hydrothermal laboratory experiments [Morrow et al., 2001] using the code TOUGHREACT. The laboratory experiments carried out by Morrow et al. [2001] measure permeability reduction in fractured and intact Westerly granite due to high-temperature fluid flow through core samples. Initial permeability and temperature values used in our simulations reflect these experimental conditions and range from 6.13 × 10−20 to 1.5 × 10−17 m2 and 150 to 300 °C, respectively. The primary mineralogy of the model rock is plagioclase (40 vol.%), K-feldspar (20 vol.%), quartz (30 vol.%), and biotite (10 vol.%). The simulations are constrained by the requirement that permeability, relative mineral abundances, and fluid chemistry agree with experimental observations. In the models, the granite core samples are represented as one-dimensional reaction domains. We find that the mineral abundances, solute concentrations, and permeability evolutions predicted by the models are consistent with those observed in the experiments carried out by Morrow et al. [2001] only if the mineral reactive surface areas decrease with increasing clay mineral abundance. This modeling approach suggests the importance of explicitly incorporating changing mineral surface areas into reactive transport models.

The importance of explicitly mapping instructional analogies in science education

NASA Astrophysics Data System (ADS)

Asay, Loretta Johnson

Analogies are ubiquitous during instruction in science classrooms, yet research about the effectiveness of using analogies has produced mixed results. An aspect seldom studied is a model of instruction when using analogies. The few existing models for instruction with analogies have not often been examined quantitatively. The Teaching With Analogies (TWA) model (Glynn, 1991) is one of the models frequently cited in the variety of research about analogies. The TWA model outlines steps for instruction, including the step of explicitly mapping the features of the source to the target. An experimental study was conducted to examine the effects of explicitly mapping the features of the source and target in an analogy during computer-based instruction about electrical circuits. Explicit mapping was compared to no mapping and to a control with no analogy. Participants were ninth- and tenth-grade biology students who were each randomly assigned to one of three conditions (no analogy module, analogy module, or explicitly mapped analogy module) for computer-based instruction. Subjects took a pre-test before the instruction, which was used to assign them to a level of previous knowledge about electrical circuits for analysis of any differential effects. After the instruction modules, students took a post-test about electrical circuits. Two weeks later, they took a delayed post-test. No advantage was found for explicitly mapping the analogy. Learning patterns were the same, regardless of the type of instruction. Those who knew the least about electrical circuits, based on the pre-test, made the most gains. After the two-week delay, this group maintained the largest amount of their gain. Implications exist for science education classrooms, as analogy use should be based on research about effective practices. Further studies are suggested to foster the building of research-based models for classroom instruction with analogies.

The effects of rotation on the surface composition and yields of low mass AGB stars.

NASA Astrophysics Data System (ADS)

Cristallo, S.; Piersanti, L.; Straniero, O.

Over the past 20 years, stellar evolutionary models have been strongly improved in order to reproduce with reasonable accuracy both photometric and spectroscopic observations. Notwithstanding, the majority of these models do not take into account macroscopic phenomena, like rotation and/or magnetic fields. Their explicit treatment could modify stellar physical and chemical properties. One of the most interesting problems related to stellar nucleosynthesis is the behavior of the s-process spectroscopic indexes ([hs/ls] and [Pb/hs]) in Asymptotic Giant Branch (AGB) stars. In this contribution we show that, for a fixed metallicity, rotation can lead to a spread in the [hs/ls] and [Pb/hs] in low-mass AGB stars. In particular, we demonstrate that the Eddington-Sweet and the Goldreich-Schubert-Fricke instabilities may have enough time to smear the 13C-pocket (the major neutron source) and the 14N-pocket (the major neutron poison). In fact, a different overlap between these pockets leads to a different neutrons-to-seeds ratio, with important consequences on the corresponding s-process distributions. Possible consequences on the chemical evolution of Galactic globular clusters are discussed.

Modeling Engineered Nanomaterials (ENMs) Fate and ...

EPA Pesticide Factsheets

Under the Toxic Substances Control Act (TSCA), the Environmental Protection Agency (EPA) is required to perform new chemical reviews of engineered nanomaterials (ENMs) identified in pre-manufacture notices. However, environmental fate models developed for traditional contaminants are limited in their ability to simulate the environmental behavior of nanomaterials due to incomplete understanding and representation of the processes governing nanomaterial distribution in the environment and by scarce empirical data quantifying the interaction of nanomaterials with environmental surfaces. We have updated the Water Quality Analysis Simulation Program (WASP), version S, to incorporate nanomaterials as an explicitly simulated state variable. WASPS now has the capability to simulate nanomaterial fate and transport in surface waters and sediments using heteroaggregation, the kinetic process governing the attachment of nanomaterials to particles and subsequently ENM distribution in the aqueous and sediment phases. Unlike dissolved chemicals which use equilibrium partition coefficients, heteroaggregation consists of a particle collision rate and an attachment efficiency ( lXhet) that generally acts as a one direction process. To demonstrate, we used a derived a het value from sediment attachment studies to parameterize WASP for simulation of multi walled carbon nanotube (MWCNT) transport in Brier Creek, a coastal plain river located in central eastern Georgia, USA and a tr

CLEPS 1.0: A new protocol for cloud aqueous phase oxidation of VOC mechanisms

NASA Astrophysics Data System (ADS)

Mouchel-Vallon, Camille; Deguillaume, Laurent; Monod, Anne; Perroux, Hélène; Rose, Clémence; Ghigo, Giovanni; Long, Yoann; Leriche, Maud; Aumont, Bernard; Patryl, Luc; Armand, Patrick; Chaumerliac, Nadine

2017-03-01

A new detailed aqueous phase mechanism named the Cloud Explicit Physico-chemical Scheme (CLEPS 1.0) is proposed to describe the oxidation of water soluble organic compounds resulting from isoprene oxidation. It is based on structure activity relationships (SARs) which provide global rate constants together with branching ratios for HOṡ abstraction and addition on atmospheric organic compounds. The GROMHE SAR allows the evaluation of Henry's law constants for undocumented organic compounds. This new aqueous phase mechanism is coupled with the MCM v3.3.1 gas phase mechanism through a mass transfer scheme between gas phase and aqueous phase. The resulting multiphase mechanism has then been implemented in a model based on the Dynamically Simple Model for Atmospheric Chemical Complexity (DSMACC) using the Kinetic PreProcessor (KPP) that can serve to analyze data from cloud chamber experiments and field campaigns. The simulation of permanent cloud under low-NOx conditions describes the formation of oxidized monoacids and diacids in the aqueous phase as well as a significant influence on the gas phase chemistry and composition and shows that the aqueous phase reactivity leads to an efficient fragmentation and functionalization of organic compounds.

Combining Model-driven and Schema-based Program Synthesis

NASA Technical Reports Server (NTRS)

Denney, Ewen; Whittle, John

2004-01-01

We describe ongoing work which aims to extend the schema-based program synthesis paradigm with explicit models. In this context, schemas can be considered as model-to-model transformations. The combination of schemas with explicit models offers a number of advantages, namely, that building synthesis systems becomes much easier since the models can be used in verification and in adaptation of the synthesis systems. We illustrate our approach using an example from signal processing.

Cohen's Kappa and classification table metrics 2.0: An ArcView 3.x extension for accuracy assessment of spatially explicit models

Treesearch

Jeff Jenness; J. Judson Wynne

2005-01-01

In the field of spatially explicit modeling, well-developed accuracy assessment methodologies are often poorly applied. Deriving model accuracy metrics have been possible for decades, but these calculations were made by hand or with the use of a spreadsheet application. Accuracy assessments may be useful for: (1) ascertaining the quality of a model; (2) improving model...

Students' use of atomic and molecular models in learning chemistry

NASA Astrophysics Data System (ADS)

O'Connor, Eileen Ann

1997-09-01

The objective of this study was to investigate the development of introductory college chemistry students' use of atomic and molecular models to explain physical and chemical phenomena. The study was conducted during the first semester of the course at a University and College II. Public institution (Carnegie Commission of Higher Education, 1973). Students' use of models was observed during one-on-one interviews conducted over the course of the semester. The approach to introductory chemistry emphasized models. Students were exposed to over two-hundred and fifty atomic and molecular models during lectures, were assigned text readings that used over a thousand models, and worked interactively with dozens of models on the computer. These models illustrated various features of the spatial organization of valence electrons and nuclei in atoms and molecules. Despite extensive exposure to models in lectures, in textbook, and in computer-based activities, the students in the study based their explanation in large part on a simple Bohr model (electrons arranged in concentric circles around the nuclei)--a model that had not been introduced in the course. Students used visual information from their models to construct their explanation, while overlooking inter-atomic and intra-molecular forces which are not represented explicitly in the models. In addition, students often explained phenomena by adding separate information about the topic without either integrating or logically relating this information into a cohesive explanation. The results of the study demonstrate that despite the extensive use of models in chemistry instruction, students do not necessarily apply them appropriately in explaining chemical and physical phenomena. The results of this study suggest that for the power of models as aids to learning to be more fully realized, chemistry professors must give more attention to the selection, use, integration, and limitations of models in their instruction.

Moderators of the Relationship between Implicit and Explicit Evaluation

PubMed Central

Nosek, Brian A.

2005-01-01

Automatic and controlled modes of evaluation sometimes provide conflicting reports of the quality of social objects. This paper presents evidence for four moderators of the relationship between automatic (implicit) and controlled (explicit) evaluations. Implicit and explicit preferences were measured for a variety of object pairs using a large sample. The average correlation was r = .36, and 52 of the 57 object pairs showed a significant positive correlation. Results of multilevel modeling analyses suggested that: (a) implicit and explicit preferences are related, (b) the relationship varies as a function of the objects assessed, and (c) at least four variables moderate the relationship – self-presentation, evaluative strength, dimensionality, and distinctiveness. The variables moderated implicit-explicit correspondence across individuals and accounted for much of the observed variation across content domains. The resulting model of the relationship between automatic and controlled evaluative processes is grounded in personal experience with the targets of evaluation. PMID:16316292

Electronically excited and ionized states in condensed phase: Theory and applications

NASA Astrophysics Data System (ADS)

Sadybekov, Arman

Predictive modeling of chemical processes in silico is a goal of XXI century. While robust and accurate methods exist for ground-state properties, reliable methods for excited states are still lacking and require further development. Electronically exited states are formed by interactions of matter with light and are responsible for key processes in solar energy harvesting, vision, artificial sensors, and photovoltaic applications. The greatest challenge to overcome on our way to a quantitative description of light-induced processes is accurate inclusion of the effect of the environment on excited states. All above mentioned processes occur in solution or solid state. Yet, there are few methodologies to study excited states in condensed phase. Application of highly accurate and robust methods, such as equation-of-motion coupled-cluster theory EOM-CC, is limited by a high computational cost and scaling precluding full quantum mechanical treatment of the entire system. In this thesis we present successful application of the EOM-CC family of methods to studies of excited states in liquid phase and build hierarchy of models for inclusion of the solvent effects. In the first part of the thesis we show that a simple gasphase model is sufficient to quantitatively analyze excited states in liquid benzene, while the latter part emphasizes the importance of explicit treatment of the solvent molecules in the case of glycine in water solution. In chapter 2, we use a simple dimer model to describe exciton formation in liquid and solid benzene. We show that sampling of dimer structures extracted from the liquid benzene is sufficient to correctly predict exited-state properties of the liquid. Our calculations explain experimentally observed features, which helped to understand the mechanism of the excimer formation in liquid benzene. Furthermore, we shed light on the difference between dimer configurations in the first solvation shell of liquid benzene and in unit cell of solid benzene and discussed the impact of these differences on the formation of the excimer state. In chapter 3, we present a theoretical approach for calculating core-level states in condensed phase. The approach is based on EOM-CC and effective fragment potential (EFP) method. By introducing an approximate treatment of double excitations in the EOM-CCSD (EOM-CC with single and double substitutions) ansatz, we addressed poor convergence issues that are encountered for the core-level states and significantly reduced computational costs. While the approximations introduce relatively large errors in the absolute values of transition energies, the errors are systematic. Consequently, chemical shifts, changes in ionization energies relative to the reference systems, are reproduced reasonably well. By using different protonation forms of solvated glycine as a benchmark system, we showed that our protocol is capable of reproducing the experimental chemical shifts with a quantitative accuracy. The results demonstrate that chemical shifts are very sensitive to the solvent interactions and that explicit treatment of solvent, such as EFP, is essential for achieving quantitative accuracy. In chapter 4, we outline future directions and discuss possible applications of the developed computational protocol for prediction of core chemical shifts in larger systems.

Transport of reacting solutes subject to a moving dissolution boundary: Numerical methods and solutions

USGS Publications Warehouse

Willis, Catherine; Rubin, Jacob

1987-01-01

A moving boundary problem which arises during transport with precipitation-dissolution reactions is solved by three different numerical methods. Two of these methods (one explicit and one implicit) are based on an integral formulation of mass balance and lead to an approximation of a weak solution. These methods are compared to a front-tracking scheme. Although the two approaches are conceptually different, the numerical solutions showed good agreement. As the ratio of dispersion to convection decreases, the methods based on the integral formulation become computationally more efficient. Specific reactions were modeled to examine the dependence of the system on the physical and chemical parameters. Although the water flow rate does not explicitly appear in the equation for the velocity of the moving boundary, the speed of the boundary depends more on the flux rate than on the dispersion coefficient. The discontinuity in the gradient of the solute concentration profile at the boundary increases with convection and with the initial concentration of the mineral. Our implicit method is extended to allow participation of the solutes in complexation reactions as well as the precipitation-dissolution reaction. This extension is easily made and does not change the basic method.

Characterization factors for thermal pollution in freshwater aquatic environments.

PubMed

Verones, Francesca; Hanafiah, Marlia Mohd; Pfister, Stephan; Huijbregts, Mark A J; Pelletier, Gregory J; Koehler, Annette

2010-12-15

To date the impact of thermal emissions has not been addressed in life cycle assessment despite the narrow thermal tolerance of most aquatic species. A method to derive characterization factors for the impact of cooling water discharges on aquatic ecosystems was developed which uses space and time explicit integration of fate and effects of water temperature changes. The fate factor is calculated with a 1-dimensional steady-state model and reflects the residence time of heat emissions in the river. The effect factor specifies the loss of species diversity per unit of temperature increase and is based on a species sensitivity distribution of temperature tolerance intervals for various aquatic species. As an example, time explicit characterization factors were calculated for the cooling water discharge of a nuclear power plant in Switzerland, quantifying the impact on aquatic ecosystems of the rivers Aare and Rhine. The relative importance of the impact of these cooling water discharges was compared with other impacts in life cycle assessment. We found that thermal emissions are relevant for aquatic ecosystems compared to other stressors, such as chemicals and nutrients. For the case of nuclear electricity investigated, thermal emissions contribute between 3% and over 90% to Ecosystem Quality damage.

Latin hypercube sampling and geostatistical modeling of spatial uncertainty in a spatially explicit forest landscape model simulation

Treesearch

Chonggang Xu; Hong S. He; Yuanman Hu; Yu Chang; Xiuzhen Li; Rencang Bu

2005-01-01

Geostatistical stochastic simulation is always combined with Monte Carlo method to quantify the uncertainty in spatial model simulations. However, due to the relatively long running time of spatially explicit forest models as a result of their complexity, it is always infeasible to generate hundreds or thousands of Monte Carlo simulations. Thus, it is of great...

Exponential-fitted methods for integrating stiff systems of ordinary differential equations: Applications to homogeneous gas-phase chemical kinetics

NASA Technical Reports Server (NTRS)

Pratt, D. T.

1984-01-01

Conventional algorithms for the numerical integration of ordinary differential equations (ODEs) are based on the use of polynomial functions as interpolants. However, the exact solutions of stiff ODEs behave like decaying exponential functions, which are poorly approximated by polynomials. An obvious choice of interpolant are the exponential functions themselves, or their low-order diagonal Pade (rational function) approximants. A number of explicit, A-stable, integration algorithms were derived from the use of a three-parameter exponential function as interpolant, and their relationship to low-order, polynomial-based and rational-function-based implicit and explicit methods were shown by examining their low-order diagonal Pade approximants. A robust implicit formula was derived by exponential fitting the trapezoidal rule. Application of these algorithms to integration of the ODEs governing homogenous, gas-phase chemical kinetics was demonstrated in a developmental code CREK1D, which compares favorably with the Gear-Hindmarsh code LSODE in spite of the use of a primitive stepsize control strategy.

Implicit and explicit ethnocentrism: revisiting the ideologies of prejudice.

PubMed

Cunningham, William A; Nezlek, John B; Banaji, Mahzarin R

2004-10-01

Two studies investigated relationships among individual differences in implicit and explicit prejudice, right-wing ideology, and rigidity in thinking. The first study examined these relationships focusing on White Americans' prejudice toward Black Americans. The second study provided the first test of implicit ethnocentrism and its relationship to explicit ethnocentrism by studying the relationship between attitudes toward five social groups. Factor analyses found support for both implicit and explicit ethnocentrism. In both studies, mean explicit attitudes toward out groups were positive, whereas implicit attitudes were negative, suggesting that implicit and explicit prejudices are distinct; however, in both studies, implicit and explicit attitudes were related (r = .37, .47). Latent variable modeling indicates a simple structure within this ethnocentric system, with variables organized in order of specificity. These results lead to the conclusion that (a) implicit ethnocentrism exists and (b) it is related to and distinct from explicit ethnocentrism.

Pre-Service Teachers' Implicit and Explicit Attitudes toward Obesity Influence Their Judgments of Students

ERIC Educational Resources Information Center

Glock, Sabine; Beverborg, Arnoud Oude Groote; Müller, Barbara C. N.

2016-01-01

Obese children experience disadvantages in school and discrimination from their teachers. Teachers' implicit and explicit attitudes have been identified as contributing to these disadvantages. Drawing on dual process models, we investigated the nature of pre-service teachers' implicit and explicit attitudes, their motivation to respond without…

Explicit and Implicit Stigma of Mental Illness as Predictors of the Recovery Attitudes of Assertive Community Treatment Practitioners.

PubMed

Stull, Laura G; McConnell, Haley; McGrew, John; Salyers, Michelle P

2017-01-01

While explicit negative stereotypes of mental illness are well established as barriers to recovery, implicit attitudes also may negatively impact outcomes. The current study is unique in its focus on both explicit and implicit stigma as predictors of recovery attitudes of mental health practitioners. Assertive Community Treatment practitioners (n = 154) from 55 teams completed online measures of stigma, recovery attitudes, and an Implicit Association Test (IAT). Three of four explicit stigma variables (perceptions of blameworthiness, helplessness, and dangerousness) and all three implicit stigma variables were associated with lower recovery attitudes. In a multivariate, hierarchical model, however, implicit stigma did not explain additional variance in recovery attitudes. In the overall model, perceptions of dangerousness and implicitly associating mental illness with "bad" were significant individual predictors of lower recovery attitudes. The current study demonstrates a need for interventions to lower explicit stigma, particularly perceptions of dangerousness, to increase mental health providers' expectations for recovery. The extent to which implicit and explicit stigma differentially predict outcomes, including recovery attitudes, needs further research.

Regulatory T cell effects in antitumor laser immunotherapy: a mathematical model and analysis

NASA Astrophysics Data System (ADS)

Dawkins, Bryan A.; Laverty, Sean M.

2016-03-01

Regulatory T cells (Tregs) have tremendous influence on treatment outcomes in patients receiving immunotherapy for cancerous tumors. We present a mathematical model incorporating the primary cellular and molecular components of antitumor laser immunotherapy. We explicitly model developmental classes of dendritic cells (DCs), cytotoxic T cells (CTLs), primary and metastatic tumor cells, and tumor antigen. Regulatory T cells have been shown to kill antigen presenting cells, to influence dendritic cell maturation and migration, to kill activated killer CTLs in the tumor microenvironment, and to influence CTL proliferation. Since Tregs affect explicitly modeled cells, but we do not explicitly model dynamics of Treg themselves, we use model parameters to analyze effects of Treg immunosuppressive activity. We will outline a systematic method for assigning clinical outcomes to model simulations and use this condition to associate simulated patient treatment outcome with Treg activity.

A Unified Framework for Monetary Theory and Policy Analysis.

ERIC Educational Resources Information Center

Lagos, Ricardo; Wright, Randall

2005-01-01

Search-theoretic models of monetary exchange are based on explicit descriptions of the frictions that make money essential. However, tractable versions of these models typically make strong assumptions that render them ill suited for monetary policy analysis. We propose a new framework, based on explicit micro foundations, within which macro…

A Naturalistic Inquiry into Praxis When Education Instructors Use Explicit Metacognitive Modeling

ERIC Educational Resources Information Center

Shannon, Nancy Gayle

2014-01-01

This naturalistic inquiry brought together six education instructors in one small teacher preparation program to explore what happens to educational instructors' praxis when the education instructors use explicit metacognitive modeling to reveal their thinking behind their pedagogical decision-making. The participants, while teaching an…

Modeling trends from North American Breeding Bird Survey data: a spatially explicit approach

USGS Publications Warehouse

Bled, Florent; Sauer, John R.; Pardieck, Keith L.; Doherty, Paul; Royle, J. Andy

2013-01-01

Population trends, defined as interval-specific proportional changes in population size, are often used to help identify species of conservation interest. Efficient modeling of such trends depends on the consideration of the correlation of population changes with key spatial and environmental covariates. This can provide insights into causal mechanisms and allow spatially explicit summaries at scales that are of interest to management agencies. We expand the hierarchical modeling framework used in the North American Breeding Bird Survey (BBS) by developing a spatially explicit model of temporal trend using a conditional autoregressive (CAR) model. By adopting a formal spatial model for abundance, we produce spatially explicit abundance and trend estimates. Analyses based on large-scale geographic strata such as Bird Conservation Regions (BCR) can suffer from basic imbalances in spatial sampling. Our approach addresses this issue by providing an explicit weighting based on the fundamental sample allocation unit of the BBS. We applied the spatial model to three species from the BBS. Species have been chosen based upon their well-known population change patterns, which allows us to evaluate the quality of our model and the biological meaning of our estimates. We also compare our results with the ones obtained for BCRs using a nonspatial hierarchical model (Sauer and Link 2011). Globally, estimates for mean trends are consistent between the two approaches but spatial estimates provide much more precise trend estimates in regions on the edges of species ranges that were poorly estimated in non-spatial analyses. Incorporating a spatial component in the analysis not only allows us to obtain relevant and biologically meaningful estimates for population trends, but also enables us to provide a flexible framework in order to obtain trend estimates for any area.

Can a continuum solvent model reproduce the free energy landscape of a -hairpin folding in water?

NASA Astrophysics Data System (ADS)

Zhou, Ruhong; Berne, Bruce J.

2002-10-01

The folding free energy landscape of the C-terminal -hairpin of protein G is explored using the surface-generalized Born (SGB) implicit solvent model, and the results are compared with the landscape from an earlier study with explicit solvent model. The OPLSAA force field is used for the -hairpin in both implicit and explicit solvent simulations, and the conformational space sampling is carried out with a highly parallel replica-exchange method. Surprisingly, we find from exhaustive conformation space sampling that the free energy landscape from the implicit solvent model is quite different from that of the explicit solvent model. In the implicit solvent model some nonnative states are heavily overweighted, and more importantly, the lowest free energy state is no longer the native -strand structure. An overly strong salt-bridge effect between charged residues (E42, D46, D47, E56, and K50) is found to be responsible for this behavior in the implicit solvent model. Despite this, we find that the OPLSAA/SGB energies of all the nonnative structures are higher than that of the native structure; thus the OPLSAA/SGB energy is still a good scoring function for structure prediction for this -hairpin. Furthermore, the -hairpin population at 282 K is found to be less than 40% from the implicit solvent model, which is much smaller than the 72% from the explicit solvent model and 80% from experiment. On the other hand, both implicit and explicit solvent simulations with the OPLSAA force field exhibit no meaningful helical content during the folding process, which is in contrast to some very recent studies using other force fields.

Can a continuum solvent model reproduce the free energy landscape of a β-hairpin folding in water?

PubMed Central

Zhou, Ruhong; Berne, Bruce J.

2002-01-01

The folding free energy landscape of the C-terminal β-hairpin of protein G is explored using the surface-generalized Born (SGB) implicit solvent model, and the results are compared with the landscape from an earlier study with explicit solvent model. The OPLSAA force field is used for the β-hairpin in both implicit and explicit solvent simulations, and the conformational space sampling is carried out with a highly parallel replica-exchange method. Surprisingly, we find from exhaustive conformation space sampling that the free energy landscape from the implicit solvent model is quite different from that of the explicit solvent model. In the implicit solvent model some nonnative states are heavily overweighted, and more importantly, the lowest free energy state is no longer the native β-strand structure. An overly strong salt-bridge effect between charged residues (E42, D46, D47, E56, and K50) is found to be responsible for this behavior in the implicit solvent model. Despite this, we find that the OPLSAA/SGB energies of all the nonnative structures are higher than that of the native structure; thus the OPLSAA/SGB energy is still a good scoring function for structure prediction for this β-hairpin. Furthermore, the β-hairpin population at 282 K is found to be less than 40% from the implicit solvent model, which is much smaller than the 72% from the explicit solvent model and ≈80% from experiment. On the other hand, both implicit and explicit solvent simulations with the OPLSAA force field exhibit no meaningful helical content during the folding process, which is in contrast to some very recent studies using other force fields. PMID:12242327

Can a continuum solvent model reproduce the free energy landscape of a beta -hairpin folding in water?

PubMed

Zhou, Ruhong; Berne, Bruce J

2002-10-01

The folding free energy landscape of the C-terminal beta-hairpin of protein G is explored using the surface-generalized Born (SGB) implicit solvent model, and the results are compared with the landscape from an earlier study with explicit solvent model. The OPLSAA force field is used for the beta-hairpin in both implicit and explicit solvent simulations, and the conformational space sampling is carried out with a highly parallel replica-exchange method. Surprisingly, we find from exhaustive conformation space sampling that the free energy landscape from the implicit solvent model is quite different from that of the explicit solvent model. In the implicit solvent model some nonnative states are heavily overweighted, and more importantly, the lowest free energy state is no longer the native beta-strand structure. An overly strong salt-bridge effect between charged residues (E42, D46, D47, E56, and K50) is found to be responsible for this behavior in the implicit solvent model. Despite this, we find that the OPLSAA/SGB energies of all the nonnative structures are higher than that of the native structure; thus the OPLSAA/SGB energy is still a good scoring function for structure prediction for this beta-hairpin. Furthermore, the beta-hairpin population at 282 K is found to be less than 40% from the implicit solvent model, which is much smaller than the 72% from the explicit solvent model and approximately equal 80% from experiment. On the other hand, both implicit and explicit solvent simulations with the OPLSAA force field exhibit no meaningful helical content during the folding process, which is in contrast to some very recent studies using other force fields.

[Research on quality regionalization of cultivated Pseudostellaria heterophylla based on climate factors].

PubMed

Kang, Chuan-Zhi; Zhou, Tao; Jiang, Wei-Ke; Guo, Lan-Ping; Zhang, Xiao-Bo; Xiao, Cheng-Hong; Zhao, Dan

2016-07-01

Maxent model was applied in the study to filtering the climate factors layer by layer. Polysaccharides and pseudostellarin B the two internal quality evaluation index were combined to analyse the interlinkages between climate factors and chemical constituents in order to search for the critical climate factors of Pseudostellaria heterophylla. Then based on the key climate factors to explicit the quality spatial distribution of P. heterophylla. The results showed that polysaccharides and climatic factors had no significant correlation, suggesting that the indicator was not climate-driven metabolites. Pseudostellarin B could construct regression model with the precipitation. And quality regionalization results showed that pseudostellarin B content presented firstly increased and then decreased trend from southeast to northwest, which was the consistent change with precipitation. It clearly proposed that precipitation was the key climate factor, which affected the accumulation of cyclopeptide compound for Pseudostellariae Radix. Copyright© by the Chinese Pharmaceutical Association.

Computing the Absorption and Emission Spectra of 5-Methylcytidine in Different Solvents: A Test-Case for Different Solvation Models.

PubMed

Martínez-Fernández, L; Pepino, A J; Segarra-Martí, J; Banyasz, A; Garavelli, M; Improta, R

2016-09-13

The optical spectra of 5-methylcytidine in three different solvents (tetrahydrofuran, acetonitrile, and water) is measured, showing that both the absorption and the emission maximum in water are significantly blue-shifted (0.08 eV). The absorption spectra are simulated based on CAM-B3LYP/TD-DFT calculations but including solvent effects with three different approaches: (i) a hybrid implicit/explicit full quantum mechanical approach, (ii) a mixed QM/MM static approach, and (iii) a QM/MM method exploiting the structures issuing from molecular dynamics classical simulations. Ab-initio Molecular dynamics simulations based on CAM-B3LYP functionals have also been performed. The adopted approaches all reproduce the main features of the experimental spectra, giving insights on the chemical-physical effects responsible for the solvent shifts in the spectra of 5-methylcytidine and providing the basis for discussing advantages and limitations of the adopted solvation models.

Modeling Task Switching without Switching Tasks: A Short-Term Priming Account of Explicitly Cued Performance

ERIC Educational Resources Information Center

Schneider, Darryl W.; Logan, Gordon D.

2005-01-01

Switch costs in task switching are commonly attributed to an executive control process of task-set reconfiguration, particularly in studies involving the explicit task-cuing procedure. The authors propose an alternative account of explicitly cued performance that is based on 2 mechanisms: priming of cue encoding from residual activation of cues in…

The Things You Do: Internal Models of Others’ Expected Behaviour Guide Action Observation

PubMed Central

Schenke, Kimberley C.; Wyer, Natalie A.; Bach, Patric

2016-01-01

Predictions allow humans to manage uncertainties within social interactions. Here, we investigate how explicit and implicit person models–how different people behave in different situations–shape these predictions. In a novel action identification task, participants judged whether actors interacted with or withdrew from objects. In two experiments, we manipulated, unbeknownst to participants, the two actors action likelihoods across situations, such that one actor typically interacted with one object and withdrew from the other, while the other actor showed the opposite behaviour. In Experiment 2, participants additionally received explicit information about the two individuals that either matched or mismatched their actual behaviours. The data revealed direct but dissociable effects of both kinds of person information on action identification. Implicit action likelihoods affected response times, speeding up the identification of typical relative to atypical actions, irrespective of the explicit knowledge about the individual’s behaviour. Explicit person knowledge, in contrast, affected error rates, causing participants to respond according to expectations instead of observed behaviour, even when they were aware that the explicit information might not be valid. Together, the data show that internal models of others’ behaviour are routinely re-activated during action observation. They provide first evidence of a person-specific social anticipation system, which predicts forthcoming actions from both explicit information and an individuals’ prior behaviour in a situation. These data link action observation to recent models of predictive coding in the non-social domain where similar dissociations between implicit effects on stimulus identification and explicit behavioural wagers have been reported. PMID:27434265

Alcohol-Approach Inclinations and Drinking Identity as Predictors of Behavioral Economic Demand for Alcohol

PubMed Central

Ramirez, Jason J.; Dennhardt, Ashley A.; Baldwin, Scott A.; Murphy, James G.; Lindgren, Kristen P.

2016-01-01

Behavioral economic demand curve indices of alcohol consumption reflect decisions to consume alcohol at varying costs. Although these indices predict alcohol-related problems beyond established predictors, little is known about the determinants of elevated demand. Two cognitive constructs that may underlie alcohol demand are alcohol-approach inclinations and drinking identity. The aim of this study was to evaluate implicit and explicit measures of these constructs as predictors of alcohol demand curve indices. College student drinkers (N = 223, 59% female) completed implicit and explicit measures of drinking identity and alcohol-approach inclinations at three timepoints separated by three-month intervals, and completed the Alcohol Purchase Task to assess demand at Time 3. Given no change in our alcohol-approach inclinations and drinking identity measures over time, random intercept-only models were used to predict two demand indices: Amplitude, which represents maximum hypothetical alcohol consumption and expenditures, and Persistence, which represents sensitivity to increasing prices. When modeled separately, implicit and explicit measures of drinking identity and alcohol-approach inclinations positively predicted demand indices. When implicit and explicit measures were included in the same model, both measures of drinking identity predicted Amplitude, but only explicit drinking identity predicted Persistence. In contrast, explicit measures of alcohol-approach inclinations, but not implicit measures, predicted both demand indices. Therefore, there was more support for explicit, versus implicit, measures as unique predictors of alcohol demand. Overall, drinking identity and alcohol-approach inclinations both exhibit positive associations with alcohol demand and represent potentially modifiable cognitive constructs that may underlie elevated demand in college student drinkers. PMID:27379444

40 CFR 791.3 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... been required to develop that data or after 5 years, whichever is later. (i) Small business refers to a...) DATA REIMBURSEMENT General Provisions § 791.3 Definitions. Terms defined in the Act, and not explicitly... reimbursement for the cost of developing health and environmental data on the test chemical. (e) Exemption...

40 CFR 791.3 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... been required to develop that data or after 5 years, whichever is later. (i) Small business refers to a...) DATA REIMBURSEMENT General Provisions § 791.3 Definitions. Terms defined in the Act, and not explicitly... reimbursement for the cost of developing health and environmental data on the test chemical. (e) Exemption...

Modeling the absorption spectrum of the permanganate ion in vacuum and in aqueous solution

NASA Astrophysics Data System (ADS)

Olsen, Jógvan Magnus Haugaard; Hedegård, Erik Donovan

The absorption spectrum of the MnO$_{4}$$^{-}$ ion has been a test-bed for quantum-chemical methods over the last decades. Its correct description requires highly-correlated multiconfigurational methods, which are incompatible with the inclusion of finite-temperature and solvent effects due to their high computational demands. Therefore, implicit solvent models are usually employed. Here we show that implicit solvent models are not sufficiently accurate to model the solvent shift of MnO$_{4}$$^{-}$, and we analyze the origins of their failure. We obtain the correct solvent shift for MnO$_{4}$$^{-}$ in aqueous solution by employing the polarizable embedding (PE) model combined with a range-separated complete active space short-range density functional theory method (CAS-srDFT). Finite-temperature effects are taken into account by averaging over structures obtained from ab initio molecular dynamics simulations. The explicit treatment of finite-temperature and solvent effects facilitates the interpretation of the bands in the low-energy region of the MnO$_{4}$$^{-}$ absorption spectrum, whose assignment has been elusive.

Modeling the mechanism of glycosylation reactions between ethanol, 1,2-ethanediol and methoxymethanol.

PubMed

Azofra, Luis Miguel; Alkorta, Ibon; Toro-Labbé, Alejandro; Elguero, José

2013-09-07

The mechanism of the S(N)2 model glycosylation reaction between ethanol, 1,2-ethanediol and methoxymethanol has been studied theoretically at the B3LYP/6-311+G(d,p) computational level. Three different types of reactions have been explored: (i) the exchange of hydroxyl groups between these model systems; (ii) the basic catalysis reactions by combination of the substrates as glycosyl donors (neutral species) and acceptors (enolate species); and (iii) the effect on the reaction profile of an explicit H2O molecule in the reactions considered in (ii). The reaction force, the electronic chemical potential and the reaction electronic flux have been characterized for the reaction path in each case. Energy calculations show that methoxymethanol is the worst glycosyl donor model among the ones studied here, while 1,2-ethanediol is the best, having the lowest activation barrier of 74.7 kJ mol(-1) for the reaction between this one and the ethanolate as the glycosyl acceptor model. In general, the presence of direct interactions between the atoms involved in the penta-coordinated TS increases the activation energies of the processes.

Molecular dynamics simulation of potentiometric sensor response: the effect of biomolecules, surface morphology and surface charge.

PubMed

Lowe, B M; Skylaris, C-K; Green, N G; Shibuta, Y; Sakata, T

2018-05-10

The silica-water interface is critical to many modern technologies in chemical engineering and biosensing. One technology used commonly in biosensors, the potentiometric sensor, operates by measuring the changes in electric potential due to changes in the interfacial electric field. Predictive modelling of this response caused by surface binding of biomolecules remains highly challenging. In this work, through the most extensive molecular dynamics simulation of the silica-water interfacial potential and electric field to date, we report a novel prediction and explanation of the effects of nano-morphology on sensor response. Amorphous silica demonstrated a larger potentiometric response than an equivalent crystalline silica model due to increased sodium adsorption, in agreement with experiments showing improved sensor response with nano-texturing. We provide proof-of-concept that molecular dynamics can be used as a complementary tool for potentiometric biosensor response prediction. Effects that are conventionally neglected, such as surface morphology, water polarisation, biomolecule dynamics and finite-size effects, are explicitly modelled.

Fundamental Scaling of Microplasmas and Tunable UV Light Generation.

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

Manginell, Ronald P.; Sillerud, Colin Halliday; Hopkins, Matthew M.

2016-11-01

The temporal evolution of spectral lines from microplasma devices (MD) was studied, including impurity transitions. Long-wavelength emission diminishes more rapidly than deep UV with decreasing pulse width and RF operation. Thus, switching from DC to short pulsed or RF operation, UV emissions can be suppressed, allowing for real-time tuning of the ionization energy of a microplasma photo-ionization source, which is useful for chemical and atomic physics. Scaling allows MD to operate near atmospheric pressure where excimer states are efficiently created and emit down to 65 nm; laser emissions fall off below 200 nm, making MD light sources attractive for deepmore » UV use. A first fully-kinetic three-dimensional model was developed that explicitly calculates electron-energy distribution function. This, and non-continuum effects, were studied with the model and how they are impacted by geometry and transient or DC operation. Finally, a global non-dimensional model was developed to help explain general trends MD physics.« less

Troublesome toxins: Time to re-think plant-herbivore interactions in vertebrate ecology

USGS Publications Warehouse

Swihart, R.K.; DeAngelis, D.L.; Feng, Z.; Bryant, J.P.

2009-01-01

Earlier models of plant-herbivore interactions relied on forms of functional response that related rates of ingestion by herbivores to mechanical or physical attributes such as bite size and rate. These models fail to predict a growing number of findings that implicate chemical toxins as important determinants of plant-herbivore dynamics. Specifically, considerable evidence suggests that toxins set upper limits on food intake for many species of herbivorous vertebrates. Herbivores feeding on toxin-containing plants must avoid saturating their detoxification systems, which often occurs before ingestion rates are limited by mechanical handling of food items. In light of the importance of plant toxins, a new approach is needed to link herbivores to their food base. We discuss necessary features of such an approach, note recent advances in herbivore functional response models that incorporate effects of plant toxins, and mention predictions that are consistent with observations in natural systems. Future ecological studies will need to address explicitly the importance of plant toxins in shaping plant and herbivore communities.

A Three-Stage Model of Housing Search,

DTIC Science & Technology

1980-05-01

Hanushek and Quigley, 1978) that recognize housing search as a transaction cost but rarely - .. examine search behavior; and descriptive studies of search...explicit mobility models that have recently appeared in the liter- ature (Speare et al., 1975; Hanushek and Quigley, 1978; Brummell, 1979). Although...1978; Hanushek and Quigley, 1978; Cronin, 1978). By explicitly assigning dollar values, the economic models attempt to obtain an objective measure of

DoD Product Line Practice Workshop Report

DTIC Science & Technology

1998-05-01

capability. The essential enterprise management practices include ensuring sound business goals providing an appropriate funding model performing...business. This way requires vision and explicit support at the organizational level. There must be an explicit funding model to support the development...the same group seems to work best in smaller organizations. A funding model for core asset development also needs to be developed because the core

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

Wieder, William R.; Allison, Steven D.; Davidson, Eric A.

Microbes influence soil organic matter (SOM) decomposition and the long-term stabilization of carbon (C) in soils. We contend that by revising the representation of microbial processes and their interactions with the physicochemical soil environment, Earth system models (ESMs) may make more realistic global C cycle projections. Explicit representation of microbial processes presents considerable challenges due to the scale at which these processes occur. Thus, applying microbial theory in ESMs requires a framework to link micro-scale process-level understanding and measurements to macro-scale models used to make decadal- to century-long projections. Here, we review the diversity, advantages, and pitfalls of simulating soilmore » biogeochemical cycles using microbial-explicit modeling approaches. We present a roadmap for how to begin building, applying, and evaluating reliable microbial-explicit model formulations that can be applied in ESMs. Drawing from experience with traditional decomposition models we suggest: (1) guidelines for common model parameters and output that can facilitate future model intercomparisons; (2) development of benchmarking and model-data integration frameworks that can be used to effectively guide, inform, and evaluate model parameterizations with data from well-curated repositories; and (3) the application of scaling methods to integrate microbial-explicit soil biogeochemistry modules within ESMs. With contributions across scientific disciplines, we feel this roadmap can advance our fundamental understanding of soil biogeochemical dynamics and more realistically project likely soil C response to environmental change at global scales.« less

Self-Love or Other-Love? Explicit Other-Preference but Implicit Self-Preference

PubMed Central

Gebauer, Jochen E.; Göritz, Anja S.; Hofmann, Wilhelm; Sedikides, Constantine

2012-01-01

Do humans prefer the self even over their favorite other person? This question has pervaded philosophy and social-behavioral sciences. Psychology’s distinction between explicit and implicit preferences calls for a two-tiered solution. Our evolutionarily-based Dissociative Self-Preference Model offers two hypotheses. Other-preferences prevail at an explicit level, because they convey caring for others, which strengthens interpersonal bonds–a major evolutionary advantage. Self-preferences, however, prevail at an implicit level, because they facilitate self-serving automatic behavior, which favors the self in life-or-die situations–also a major evolutionary advantage. We examined the data of 1,519 participants, who completed an explicit measure and one of five implicit measures of preferences for self versus favorite other. The results were consistent with the Dissociative Self-Preference Model. Explicitly, participants preferred their favorite other over the self. Implicitly, however, they preferred the self over their favorite other (be it their child, romantic partner, or best friend). Results are discussed in relation to evolutionary theorizing on self-deception. PMID:22848605

A Metacognitive Approach to "Implicit" and "Explicit" Evaluations: Comment on Gawronski and Bodenhausen (2006)

ERIC Educational Resources Information Center

Petty, Richard E.; Brinol, Pablo

2006-01-01

Comments on the article by B. Gawronski and G. V. Bodenhausen (see record 2006-10465-003). A metacognitive model (MCM) is presented to describe how automatic (implicit) and deliberative (explicit) measures of attitudes respond to change attempts. The model assumes that contemporary implicit measures tap quick evaluative associations, whereas…

A Watershed-based spatially-explicit demonstration of an Integrated Environmental Modeling Framework for Ecosystem Services in the Coal River Basin (WV, USA)

EPA Science Inventory

We demonstrate a spatially-explicit regional assessment of current condition of aquatic ecoservices in the Coal River Basin (CRB), with limited sensitivity analysis for the atmospheric contaminant mercury. The integrated modeling framework (IMF) forecasts water quality and quant...

USING THE ECLPSS SOFTWARE ENVIRONMENT TO BUILD A SPATIALLY EXPLICIT COMPONENT-BASED MODEL OF OZONE EFFECTS ON FOREST ECOSYSTEMS. (R827958)

EPA Science Inventory

We have developed a modeling framework to support grid-based simulation of ecosystems at multiple spatial scales, the Ecological Component Library for Parallel Spatial Simulation (ECLPSS). ECLPSS helps ecologists to build robust spatially explicit simulations of ...

A masked negative self-esteem? Implicit and explicit self-esteem in patients with Narcissistic Personality Disorder.

PubMed

Marissen, Marlies A E; Brouwer, Marlies E; Hiemstra, Annemarie M F; Deen, Mathijs L; Franken, Ingmar H A

2016-08-30

The mask model of narcissism states that the narcissistic traits of patients with NPD are the result of a compensatory reaction to underlying ego fragility. This model assumes that high explicit self-esteem masks low implicit self-esteem. However, research on narcissism has predominantly focused on non-clinical participants and data derived from patients diagnosed with Narcissistic Personality Disorder (NPD) remain scarce. Therefore, the goal of the present study was to test the mask model hypothesis of narcissism among patients with NPD. Male patients with NPD were compared to patients with other PD's and healthy participants on implicit and explicit self-esteem. NPD patients did not differ in levels of explicit and implicit self-esteem compared to both the psychiatric and the healthy control group. Overall, the current study found no evidence in support of the mask model of narcissism among a clinical group. This implicates that it might not be relevant for clinicians to focus treatment of NPD on an underlying negative self-esteem. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Aerosol processing in stratiform clouds in ECHAM6-HAM

NASA Astrophysics Data System (ADS)

Neubauer, David; Lohmann, Ulrike; Hoose, Corinna

2013-04-01

Aerosol processing in stratiform clouds by uptake into cloud particles, collision-coalescence, chemical processing inside the cloud particles and release back into the atmosphere has important effects on aerosol concentration, size distribution, chemical composition and mixing state. Aerosol particles can act as cloud condensation nuclei. Cloud droplets can take up further aerosol particles by collisions. Atmospheric gases may also be transferred into the cloud droplets and undergo chemical reactions, e.g. the production of atmospheric sulphate. Aerosol particles are also processed in ice crystals. They may be taken up by homogeneous freezing of cloud droplets below -38° C or by heterogeneous freezing above -38° C. This includes immersion freezing of already immersed aerosol particles in the droplets and contact freezing of particles colliding with a droplet. Many clouds do not form precipitation and also much of the precipitation evaporates before it reaches the ground. The water soluble part of the aerosol particles concentrates in the hydrometeors and together with the insoluble part forms a single, mixed, larger particle, which is released. We have implemented aerosol processing into the current version of the general circulation model ECHAM6 (Stevens et al., 2013) coupled to the aerosol module HAM (Stier et al., 2005). ECHAM6-HAM solves prognostic equations for the cloud droplet number and ice crystal number concentrations. In the standard version of HAM, seven modes are used to describe the total aerosol. The modes are divided into soluble/mixed and insoluble modes and the number concentrations and masses of different chemical components (sulphate, black carbon, organic carbon, sea salt and mineral dust) are prognostic variables. We extended this by an explicit representation of aerosol particles in cloud droplets and ice crystals in stratiform clouds similar to Hoose et al. (2008a,b). Aerosol particles in cloud droplets are represented by 5 tracers for the chemical components as well as 5 tracers for aerosol particles in ice crystals. This allows simulations of aerosol processing in warm, mixed-phase (e.g. through the Bergeron-Findeisen process) and ice clouds. The fixed scavenging ratios used for wet deposition in clouds in standard HAM are replaced by an explicit treatment of collision of cloud droplets/ice crystals with interstitial aerosol particles. Nucleation scavenging of aerosol particles by acting as cloud condensation nuclei or ice nuclei, freezing and evaporation of cloud droplets and melting and sublimation of ice crystals are treated explicitly. In extension to previous studies, aerosol particles from evaporating precipitation are released to modes which correspond to their size. Cloud processing of aerosol particles changes their size distribution and hence influences cloud droplet and ice crystal number concentrations as well as precipitation rate, which in turn affects aerosol concentrations. Results will be presented at the conference. Hoose et al., JGR, 2008a, doi: 10.1029/2007JD009251 Hoose et al., ACP, 2008b, doi: 10.5194/acp-8-6939-2008 Stevens et al., 2013, submitted Stier et al., ACP, 2005, doi: 10.5194/acp-5-1125-2005

Kinetic multi-layer model of aerosol surface and bulk chemistry (KM-SUB): the influence of interfacial transport and bulk diffusion on the oxidation of oleic acid by ozone

NASA Astrophysics Data System (ADS)

Shiraiwa, Manabu; Pfrang, Christian; Pöschl, Ulrich

2010-05-01

Aerosols are ubiquitous in the atmosphere and have strong effects on climate and public health. Gas-particle interactions can significantly change the physical and chemical properties of aerosols such as toxicity, reactivity, hygroscopicity and radiative properties. Chemical reactions and mass transport lead to continuous transformation and changes in the composition of atmospheric aerosols ("chemical aging"). Resistor model formulations are widely used to describe and investigate heterogeneous reactions and multiphase processes in laboratory, field and model studies of atmospheric chemistry. The traditional resistor models, however, are usually based on simplifying assumptions such as steady state conditions, homogeneous mixing, and limited numbers of non-interacting species and processes. In order to overcome these limitations, Pöschl, Rudich and Ammann have developed a kinetic model framework (PRA framework) with a double-layer surface concept and universally applicable rate equations and parameters for mass transport and chemical reactions at the gas-particle interface of aerosols and clouds [1]. Based on the PRA framework, we present a novel kinetic multi-layer model that explicitly resolves mass transport and chemical reaction at the surface and in the bulk of aerosol particles (KM-SUB) [2]. The model includes reversible adsorption, surface reactions and surface-bulk exchange as well as bulk diffusion and reaction. Unlike earlier models, KM-SUB does not require simplifying assumptions about steady-state conditions and radial mixing. The temporal evolution and concentration profiles of volatile and non-volatile species at the gas-particle interface and in the particle bulk can be modeled along with surface concentrations and gas uptake coefficients. In this study we explore and exemplify the effects of bulk diffusion on the rate of reactive gas uptake for a simple reference system, the ozonolysis of oleic acid particles, in comparison to experimental data and earlier model studies. We demonstrate how KM-SUB can be used to interpret and analyze experimental data from laboratory studies, and how the results can be extrapolated to atmospheric conditions. In particular, we show how interfacial transport and bulk transport, i.e., surface accommodation, bulk accommodation and bulk diffusion, influence the kinetics of the chemical reaction. Sensitivity studies suggest that in fine air particulate matter oleic acid and compounds with similar reactivity against ozone (C=C double bonds) can reach chemical life-times of multiple hours only if they are embedded in a (semi-)solid matrix with very low diffusion coefficients (~10-10 cm2 s-1). Depending on the complexity of the investigated system, unlimited numbers of volatile and non-volatile species and chemical reactions can be flexibly added and treated with KM-SUB. We propose and intend to pursue the application of KM-SUB as a basis for the development of a detailed master mechanism of aerosol chemistry as well as for the derivation of simplified but realistic parameterizations for large-scale atmospheric and climate models. References [1] Pöschl et al., Atmos. Chem. and Phys., 7, 5989-6023 (2007). [2] Shiraiwa et al., Atmos. Chem. Phys. Discuss., 10, 281-326 (2010).

In silico designing of power conversion efficient organic lead dyes for solar cells using todays innovative approaches to assure renewable energy for future

NASA Astrophysics Data System (ADS)

Kar, Supratik; Roy, Juganta K.; Leszczynski, Jerzy

2017-06-01

Advances in solar cell technology require designing of new organic dye sensitizers for dye-sensitized solar cells with high power conversion efficiency to circumvent the disadvantages of silicon-based solar cells. In silico studies including quantitative structure-property relationship analysis combined with quantum chemical analysis were employed to understand the primary electron transfer mechanism and photo-physical properties of 273 arylamine organic dyes from 11 diverse chemical families explicit to iodine electrolyte. The direct quantitative structure-property relationship models enable identification of the essential electronic and structural attributes necessary for quantifying the molecular prerequisites of 11 classes of arylamine organic dyes, responsible for high power conversion efficiency of dye-sensitized solar cells. Tetrahydroquinoline, N,N'-dialkylaniline and indoline have been least explored classes under arylamine organic dyes for dye-sensitized solar cells. Therefore, the identified properties from the corresponding quantitative structure-property relationship models of the mentioned classes were employed in designing of "lead dyes". Followed by, a series of electrochemical and photo-physical parameters were computed for designed dyes to check the required variables for electron flow of dye-sensitized solar cells. The combined computational techniques yielded seven promising lead dyes each for all three chemical classes considered. Significant (130, 183, and 46%) increment in predicted %power conversion efficiency was observed comparing with the existing dye with highest experimental %power conversion efficiency value for tetrahydroquinoline, N,N'-dialkylaniline and indoline, respectively maintaining required electrochemical parameters.

Examining the impacts of ethanol (E85) versus gasoline photochemical production of smog in a fog using near-explicit gas- and aqueous-chemistry mechanisms

NASA Astrophysics Data System (ADS)

Ginnebaugh, Diana L.; Jacobson, Mark Z.

2012-12-01

This study investigates the air quality impacts of using a high-blend ethanol fuel (E85) instead of gasoline in vehicles in an urban setting when a morning fog is present under summer and winter conditions. The model couples the near-explicit gas-phase Master Chemical Mechanism (MCM v. 3.1) with the extensive aqueous-phase Chemical Aqueous Phase Radical Mechanism (CAPRAM 3.0i) in SMVGEAR II, a fast and accurate ordinary differential equation solver. Summer and winter scenarios are investigated during a two day period in the South Coast Air Basin (SCAB) with all gasoline vehicles replaced by flex-fuel vehicles running on E85 in 2020. We find that E85 slightly increases ozone compared with gasoline in the presence or absence of a fog under summer conditions but increases ozone significantly relative to gasoline during winter conditions, although winter ozone is always lower than summer ozone. A new finding here is that a fog during summer may increase ozone after the fog disappears, due to chemistry alone. Temperatures were high enough in the summer to increase peroxy radical (RO2) production with the morning fog, which led to the higher ozone after fog dissipation. A fog on a winter day decreases ozone after the fog. Within a fog, ozone is always lower than if no fog occurs. The sensitivity of the results to fog parameters like droplet size, liquid water content, fog duration and photolysis are investigated and discussed. The results support previous work suggesting that E85 and gasoline both enhance pollution with E85 enhancing pollution significantly more at low temperatures. Thus, neither E85 nor gasoline is a ‘clean-burning’ fuel.

The Effects of Explicit Teaching of Strategies, Second-Order Concepts, and Epistemological Underpinnings on Students' Ability to Reason Causally in History

ERIC Educational Resources Information Center

Stoel, Gerhard L.; van Drie, Jannet P.; van Boxtel, Carla A. M.

2017-01-01

This article reports an experimental study on the effects of explicit teaching on 11th grade students' ability to reason causally in history. Underpinned by the model of domain learning, explicit teaching is conceptualized as multidimensional, focusing on strategies and second-order concepts to generate and verbalize causal explanations and…

Investigating the predictive validity of implicit and explicit measures of motivation on condom use, physical activity and healthy eating.

PubMed

Keatley, David; Clarke, David D; Hagger, Martin S

2012-01-01

The literature on health-related behaviours and motivation is replete with research involving explicit processes and their relations with intentions and behaviour. Recently, interest has been focused on the impact of implicit processes and measures on health-related behaviours. Dual-systems models have been proposed to provide a framework for understanding the effects of explicit or deliberative and implicit or impulsive processes on health behaviours. Informed by a dual-systems approach and self-determination theory, the aim of this study was to test the effects of implicit and explicit motivation on three health-related behaviours in a sample of undergraduate students (N = 162). Implicit motives were hypothesised to predict behaviour independent of intentions while explicit motives would be mediated by intentions. Regression analyses indicated that implicit motivation predicted physical activity behaviour only. Across all behaviours, intention mediated the effects of explicit motivational variables from self-determination theory. This study provides limited support for dual-systems models and the role of implicit motivation in the prediction of health-related behaviour. Suggestions for future research into the role of implicit processes in motivation are outlined.

An explicit asymptotic model for the surface wave in a viscoelastic half-space based on applying Rabotnov's fractional exponential integral operators

NASA Astrophysics Data System (ADS)

Wilde, M. V.; Sergeeva, N. V.

2018-05-01

An explicit asymptotic model extracting the contribution of a surface wave to the dynamic response of a viscoelastic half-space is derived. Fractional exponential Rabotnov's integral operators are used for describing of material properties. The model is derived by extracting the principal part of the poles corresponding to the surface waves after applying Laplace and Fourier transforms. The simplified equations for the originals are written by using power series expansions. Padè approximation is constructed to unite short-time and long-time models. The form of this approximation allows to formulate the explicit model using a fractional exponential Rabotnov's integral operator with parameters depending on the properties of surface wave. The applicability of derived models is studied by comparing with the exact solutions of a model problem. It is revealed that the model based on Padè approximation is highly effective for all the possible time domains.

Vertically aligned single-walled carbon nanotubes by chemical assembly--methodology, properties, and applications.

PubMed

Diao, Peng; Liu, Zhongfan

2010-04-06

Single-walled carbon nanotubes (SWNTs), as one of the most promising one-dimension nanomaterials due to its unique structure, peculiar chemical, mechanical, thermal, and electronic properties, have long been considered as an important building block to construct ordered alignments. Vertically aligned SWNTs (v-SWNTs) have been successfully prepared by using direct growth and chemical assembly strategies. In this review, we focus explicitly on the v-SWNTs fabricated via chemical assembly strategy. We provide the readers with a full and systematic summary covering the advances in all aspects of this area, including various approaches for the preparation of v-SWNTs using chemical assembly techniques, characterization, assembly kinetics, and electrochemical properties of v-SWNTs. We also review the applications of v-SWNTs in electrochemical and bioelectrochemical sensors, photoelectric conversion, and scanning probe microscopy.

Precondensed matter - Key to the early solar system

NASA Technical Reports Server (NTRS)

Clayton, D. D.

1978-01-01

Explicit astrophysical details are developed for the hypothesis that chemical and isotopic anomalies in primitive solar-system samples reflect routine initial chemical conditions within precondensed matter. The central feature of this theory concerns the chemical state of presolar dust, which is regarded as never having been vaporized in the region where the most chemically primitive samples (carbonaceous meteorites) accumulated. It is suggested that the initial chemical state of heavy atoms during meteorite and planetary accumulation was distributed between a refractory-mineral component from high-temperature condensation and a volatile component resulting from cold matter adhering to preexisting grains. Thermal conditions in the solar nebula are considered along with the existence of supernova condensates and other thermal condensates in the interstellar dust. Fractionation into volatile and refractory elements is idealized in terms of four distinct interstellar components, and the fractionated precondensed matter is described.

Evaluation of the Physical and Chemical Properties of Eyjafjallajökull Volcanic Plume Using a Cloud-Resolving Model

NASA Astrophysics Data System (ADS)

Spiridonov, Vlado; Curic, Mladjen

2013-11-01

The Eyjafjallajökull volcanic eruption, which occurred on April 14, 2010, caused many environmental, air traffic and health problems. An attempt has been made to demonstrate for the first time that certain improvements could be made in the quantitative prediction of the volcanic ash parameters, and in the accounting of the processes in the immediate vicinity of the volcano, using a cloud-resolving model. This type of explicit modeling by treatment of volcanic ash and sulfate chemistry parameterization, with input of a number parameters describing the volcanic source, is the way forward for understanding the complex processes in plumes and in the future plume dispersion modeling. Results imply that the most significant microphysical processes are those related to accretion of cloud water, cloud ice and rainwater by snow, and accretion of rain and snow by hail. The dominant chemical conversion rates that give a great contribution to the sulfate budget are nucleation and dynamic scavenging and oxidation processes. A three-dimensional numerical experiment has shown a very realistic simulation of volcanic ash and other chemical compounds evolution, with a sloping structure strongly influenced by the meteorological conditions. In-cloud oxidation by H2O2 is the dominant pathway for SO2 oxidation and allows sulfate to be produced within the SO2 source region. The averaged cloud water pH of about 5.8 and rainwater pH of 4.5 over simulation time show quantitatively how the oxidation may strongly influence the sulfate budget and acidity of volcanic cloud. Compared to observations, model results are close in many aspects. Information on the near field volcanic plume behavior is essential for early preparedness and evacuation. This approach demonstrates a potential improvement in quantitative predictions regarding the volcanic plume distribution at different altitudes. It could be a useful tool for modeling volcanic plumes for better emergency measures planning.

Age effects on explicit and implicit memory

PubMed Central

Ward, Emma V.; Berry, Christopher J.; Shanks, David R.

2013-01-01

It is well-documented that explicit memory (e.g., recognition) declines with age. In contrast, many argue that implicit memory (e.g., priming) is preserved in healthy aging. For example, priming on tasks such as perceptual identification is often not statistically different in groups of young and older adults. Such observations are commonly taken as evidence for distinct explicit and implicit learning/memory systems. In this article we discuss several lines of evidence that challenge this view. We describe how patterns of differential age-related decline may arise from differences in the ways in which the two forms of memory are commonly measured, and review recent research suggesting that under improved measurement methods, implicit memory is not age-invariant. Formal computational models are of considerable utility in revealing the nature of underlying systems. We report the results of applying single and multiple-systems models to data on age effects in implicit and explicit memory. Model comparison clearly favors the single-system view. Implications for the memory systems debate are discussed. PMID:24065942

High-Order/Low-Order methods for ocean modeling

DOE PAGES

Newman, Christopher; Womeldorff, Geoff; Chacón, Luis; ...

2015-06-01

In this study, we examine a High Order/Low Order (HOLO) approach for a z-level ocean model and show that the traditional semi-implicit and split-explicit methods, as well as a recent preconditioning strategy, can easily be cast in the framework of HOLO methods. The HOLO formulation admits an implicit-explicit method that is algorithmically scalable and second-order accurate, allowing timesteps much larger than the barotropic time scale. We show how HOLO approaches, in particular the implicit-explicit method, can provide a solid route for ocean simulation to heterogeneous computing and exascale environments.

Explicit robust schemes for implementation of a class of principal value-based constitutive models: Symbolic and numeric implementation

NASA Technical Reports Server (NTRS)

Arnold, S. M.; Saleeb, A. F.; Tan, H. Q.; Zhang, Y.

1993-01-01

The issue of developing effective and robust schemes to implement a class of the Ogden-type hyperelastic constitutive models is addressed. To this end, special purpose functions (running under MACSYMA) are developed for the symbolic derivation, evaluation, and automatic FORTRAN code generation of explicit expressions for the corresponding stress function and material tangent stiffness tensors. These explicit forms are valid over the entire deformation range, since the singularities resulting from repeated principal-stretch values have been theoretically removed. The required computational algorithms are outlined, and the resulting FORTRAN computer code is presented.

Dynamic modelling of solids in a full-scale activated sludge plant preceded by CEPT as a preliminary step for micropollutant removal modelling.

PubMed

Baalbaki, Zeina; Torfs, Elena; Maere, Thomas; Yargeau, Viviane; Vanrolleghem, Peter A

2017-04-01

The presence of micropollutants in the environment has triggered research on quantifying and predicting their fate in wastewater treatment plants (WWTPs). Since the removal of micropollutants is highly related to conventional pollutant removal and affected by hydraulics, aeration, biomass composition and solids concentration, the fate of these conventional pollutants and characteristics must be well predicted before tackling models to predict the fate of micropollutants. In light of this, the current paper presents the dynamic modelling of conventional pollutants undergoing activated sludge treatment using a limited set of additional daily composite data besides the routine data collected at a WWTP over one year. Results showed that as a basis for modelling, the removal of micropollutants, the Bürger-Diehl settler model was found to capture the actual effluent total suspended solids (TSS) concentrations more efficiently than the Takács model by explicitly modelling the overflow boundary. Results also demonstrated that particular attention must be given to characterizing incoming TSS to obtain a representative solids balance in the presence of a chemically enhanced primary treatment, which is key to predict the fate of micropollutants.

A new numerical model of the middle atmosphere. 2: Ozone and related species

NASA Technical Reports Server (NTRS)

Garcia, Rolando R.; Solomon, Susan

1994-01-01

A new two-dimensional model with detailed photochemistry is presented. The model includes descriptions of planetary wave and gravity wave propagation and dissipation to characterize the wave forcing and associated mixing in the stratosphere and mesosphere. Such a representation allows for explicit calculation of the regions of strong mixing in the middle atmosphere required for accurate simulation of trace gas transport. The new model also includes a detailed description of photochemical processes in the stratosphere and mesosphere. The downward transport of H2, H2O, and NO(y) from the mesosphere to the stratosphere is examined, and it is shown that mesospheric processes can influence the distributions of these chemical species in polar regions. For HNO3 we also find that small concentrations of liquid aerosols above 30 km could play a major role in determining the abundance in polar winter at high latitudes. The model is also used to examine the chemical budget of ozone in the midlatitude stratosphere and to set constraints on the effectiveness of bromine relative to chlorine for ozone loss and the role of the HO2 + BrO reaction. Recent laboratory data used in this modeling study suggest that this process greatly enhances the effectiveness of bromine for ozone destruction, making bromine-catalyzed chemistry second only to HO(x)-catalyzed ozone destruction in the contemporary stratosphere at midlatitudes below about 18 km. The calculated vertical distribution of ozone in the lower stratosphere agrees well with observations, as does the total column ozone during most seasons and latitudes, with the important exception of southern hemisphere winter and spring.

Class of self-limiting growth models in the presence of nonlinear diffusion

NASA Astrophysics Data System (ADS)

Kar, Sandip; Banik, Suman Kumar; Ray, Deb Shankar

2002-06-01

The source term in a reaction-diffusion system, in general, does not involve explicit time dependence. A class of self-limiting growth models dealing with animal and tumor growth and bacterial population in a culture, on the other hand, are described by kinetics with explicit functions of time. We analyze a reaction-diffusion system to study the propagation of spatial front for these models.

Continuous time Boolean modeling for biological signaling: application of Gillespie algorithm.

PubMed

Stoll, Gautier; Viara, Eric; Barillot, Emmanuel; Calzone, Laurence

2012-08-29

Mathematical modeling is used as a Systems Biology tool to answer biological questions, and more precisely, to validate a network that describes biological observations and predict the effect of perturbations. This article presents an algorithm for modeling biological networks in a discrete framework with continuous time. There exist two major types of mathematical modeling approaches: (1) quantitative modeling, representing various chemical species concentrations by real numbers, mainly based on differential equations and chemical kinetics formalism; (2) and qualitative modeling, representing chemical species concentrations or activities by a finite set of discrete values. Both approaches answer particular (and often different) biological questions. Qualitative modeling approach permits a simple and less detailed description of the biological systems, efficiently describes stable state identification but remains inconvenient in describing the transient kinetics leading to these states. In this context, time is represented by discrete steps. Quantitative modeling, on the other hand, can describe more accurately the dynamical behavior of biological processes as it follows the evolution of concentration or activities of chemical species as a function of time, but requires an important amount of information on the parameters difficult to find in the literature. Here, we propose a modeling framework based on a qualitative approach that is intrinsically continuous in time. The algorithm presented in this article fills the gap between qualitative and quantitative modeling. It is based on continuous time Markov process applied on a Boolean state space. In order to describe the temporal evolution of the biological process we wish to model, we explicitly specify the transition rates for each node. For that purpose, we built a language that can be seen as a generalization of Boolean equations. Mathematically, this approach can be translated in a set of ordinary differential equations on probability distributions. We developed a C++ software, MaBoSS, that is able to simulate such a system by applying Kinetic Monte-Carlo (or Gillespie algorithm) on the Boolean state space. This software, parallelized and optimized, computes the temporal evolution of probability distributions and estimates stationary distributions. Applications of the Boolean Kinetic Monte-Carlo are demonstrated for three qualitative models: a toy model, a published model of p53/Mdm2 interaction and a published model of the mammalian cell cycle. Our approach allows to describe kinetic phenomena which were difficult to handle in the original models. In particular, transient effects are represented by time dependent probability distributions, interpretable in terms of cell populations.

Innovations in individual feature history management - The significance of feature-based temporal model

USGS Publications Warehouse

Choi, J.; Seong, J.C.; Kim, B.; Usery, E.L.

2008-01-01

A feature relies on three dimensions (space, theme, and time) for its representation. Even though spatiotemporal models have been proposed, they have principally focused on the spatial changes of a feature. In this paper, a feature-based temporal model is proposed to represent the changes of both space and theme independently. The proposed model modifies the ISO's temporal schema and adds new explicit temporal relationship structure that stores temporal topological relationship with the ISO's temporal primitives of a feature in order to keep track feature history. The explicit temporal relationship can enhance query performance on feature history by removing topological comparison during query process. Further, a prototype system has been developed to test a proposed feature-based temporal model by querying land parcel history in Athens, Georgia. The result of temporal query on individual feature history shows the efficiency of the explicit temporal relationship structure. ?? Springer Science+Business Media, LLC 2007.

Labeling and Knowing: A Reconciliation of Implicit Theory and Explicit Theory among Students with Exceptionalities

ERIC Educational Resources Information Center

lo, C. Owen

2014-01-01

Using a realist grounded theory method, this study resulted in a theoretical model and 4 propositions. As displayed in the LINK model, the labeling practice is situated in and endorsed by a social context that carries explicit theory about and educational policies regarding the labels. Taking a developmental perspective, the labeling practice…

Fire emissions constrained by the synergistic use of formaldehyde and glyoxal SCIAMACHY columns in a two-compound inverse modelling framework

NASA Astrophysics Data System (ADS)

Stavrakou, T.; Muller, J.; de Smedt, I.; van Roozendael, M.; Vrekoussis, M.; Wittrock, F.; Richter, A.; Burrows, J.

2008-12-01

Formaldehyde (HCHO) and glyoxal (CHOCHO) are carbonyls formed in the oxidation of volatile organic compounds (VOCs) emitted by plants, anthropogenic activities, and biomass burning. They are also directly emitted by fires. Although this primary production represents only a small part of the global source for both species, yet it can be locally important during intense fire events. Simultaneous observations of formaldehyde and glyoxal retrieved from the SCIAMACHY satellite instrument in 2005 and provided by the BIRA/IASB and the Bremen group, respectively, are compared with the corresponding columns simulated with the IMAGESv2 global CTM. The chemical mechanism has been optimized with respect to HCHO and CHOCHO production from pyrogenically emitted NMVOCs, based on the Master Chemical Mechanism (MCM) and on an explicit profile for biomass burning emissions. Gas-to-particle conversion of glyoxal in clouds and in aqueous aerosols is considered in the model. In this study we provide top-down estimates for fire emissions of HCHO and CHOCHO precursors by performing a two- compound inversion of emissions using the adjoint of the IMAGES model. The pyrogenic fluxes are optimized at the model resolution. The two-compound inversion offers the advantage that the information gained from measurements of one species constrains the sources of both compounds, due to the existence of common precursors. In a first inversion, only the burnt biomass amounts are optimized. In subsequent simulations, the emission factors for key individual NMVOC compounds are also varied.

Probabilistic cross-link analysis and experiment planning for high-throughput elucidation of protein structure.

PubMed

Ye, Xiaoduan; O'Neil, Patrick K; Foster, Adrienne N; Gajda, Michal J; Kosinski, Jan; Kurowski, Michal A; Bujnicki, Janusz M; Friedman, Alan M; Bailey-Kellogg, Chris

2004-12-01

Emerging high-throughput techniques for the characterization of protein and protein-complex structures yield noisy data with sparse information content, placing a significant burden on computation to properly interpret the experimental data. One such technique uses cross-linking (chemical or by cysteine oxidation) to confirm or select among proposed structural models (e.g., from fold recognition, ab initio prediction, or docking) by testing the consistency between cross-linking data and model geometry. This paper develops a probabilistic framework for analyzing the information content in cross-linking experiments, accounting for anticipated experimental error. This framework supports a mechanism for planning experiments to optimize the information gained. We evaluate potential experiment plans using explicit trade-offs among key properties of practical importance: discriminability, coverage, balance, ambiguity, and cost. We devise a greedy algorithm that considers those properties and, from a large number of combinatorial possibilities, rapidly selects sets of experiments expected to discriminate pairs of models efficiently. In an application to residue-specific chemical cross-linking, we demonstrate the ability of our approach to plan experiments effectively involving combinations of cross-linkers and introduced mutations. We also describe an experiment plan for the bacteriophage lambda Tfa chaperone protein in which we plan dicysteine mutants for discriminating threading models by disulfide formation. Preliminary results from a subset of the planned experiments are consistent and demonstrate the practicality of planning. Our methods provide the experimenter with a valuable tool (available from the authors) for understanding and optimizing cross-linking experiments.

Experimental design matters for statistical analysis: how to handle blocking.

PubMed

Jensen, Signe M; Schaarschmidt, Frank; Onofri, Andrea; Ritz, Christian

2018-03-01

Nowadays, evaluation of the effects of pesticides often relies on experimental designs that involve multiple concentrations of the pesticide of interest or multiple pesticides at specific comparable concentrations and, possibly, secondary factors of interest. Unfortunately, the experimental design is often more or less neglected when analysing data. Two data examples were analysed using different modelling strategies. First, in a randomized complete block design, mean heights of maize treated with a herbicide and one of several adjuvants were compared. Second, translocation of an insecticide applied to maize as a seed treatment was evaluated using incomplete data from an unbalanced design with several layers of hierarchical sampling. Extensive simulations were carried out to further substantiate the effects of different modelling strategies. It was shown that results from suboptimal approaches (two-sample t-tests and ordinary ANOVA assuming independent observations) may be both quantitatively and qualitatively different from the results obtained using an appropriate linear mixed model. The simulations demonstrated that the different approaches may lead to differences in coverage percentages of confidence intervals and type 1 error rates, confirming that misleading conclusions can easily happen when an inappropriate statistical approach is chosen. To ensure that experimental data are summarized appropriately, avoiding misleading conclusions, the experimental design should duly be reflected in the choice of statistical approaches and models. We recommend that author guidelines should explicitly point out that authors need to indicate how the statistical analysis reflects the experimental design. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Pesticides.

PubMed

Cabrera, Laura Y

2017-10-01

There is growing evidence about the influence of chemical exposures on specific molecular systems and mechanisms involved in cognitive and mental function. Evidence is also emerging about the negative impact of these chemical exposures on mental health, including depression, suicide, and other risks. Despite the growing appreciation of these factors, however, little attention has been paid to the ethical and social implications of their interactions. Drawing on recent work that argues for an environmental neuroethics approach that explicitly brings together ethics, environment, and conditions of the central nervous system, this article focuses on these critical issues for pesticides specifically.

Upwind differencing and LU factorization for chemical non-equilibrium Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Shuen, Jian-Shun

1992-01-01

By means of either the Roe or the Van Leer flux-splittings for inviscid terms, in conjunction with central differencing for viscous terms in the explicit operator and the Steger-Warming splitting and lower-upper approximate factorization for the implicit operator, the present, robust upwind method for solving the chemical nonequilibrium Navier-Stokes equations yields formulas for finite-volume discretization in general coordinates. Numerical tests in the illustrative cases of a hypersonic blunt body, a ramped duct, divergent nozzle flows, and shock wave/boundary layer interactions, establish the method's efficiency.

The mixed impact of medical school on medical students' implicit and explicit weight bias.

PubMed

Phelan, Sean M; Puhl, Rebecca M; Burke, Sara E; Hardeman, Rachel; Dovidio, John F; Nelson, David B; Przedworski, Julia; Burgess, Diana J; Perry, Sylvia; Yeazel, Mark W; van Ryn, Michelle

2015-10-01

Health care trainees demonstrate implicit (automatic, unconscious) and explicit (conscious) bias against people from stigmatised and marginalised social groups, which can negatively influence communication and decision making. Medical schools are well positioned to intervene and reduce bias in new physicians. This study was designed to assess medical school factors that influence change in implicit and explicit bias against individuals from one stigmatised group: people with obesity. This was a prospective cohort study of medical students enrolled at 49 US medical schools randomly selected from all US medical schools within the strata of public and private schools and region. Participants were 1795 medical students surveyed at the beginning of their first year and end of their fourth year. Web-based surveys included measures of weight bias, and medical school experiences and climate. Bias change was compared with changes in bias in the general public over the same period. Linear mixed models were used to assess the impact of curriculum, contact with people with obesity, and faculty role modelling on weight bias change. Increased implicit and explicit biases were associated with less positive contact with patients with obesity and more exposure to faculty role modelling of discriminatory behaviour or negative comments about patients with obesity. Increased implicit bias was associated with training in how to deal with difficult patients. On average, implicit weight bias decreased and explicit bias increased during medical school, over a period of time in which implicit weight bias in the general public increased and explicit bias remained stable. Medical schools may reduce students' weight biases by increasing positive contact between students and patients with obesity, eliminating unprofessional role modelling by faculty members and residents, and altering curricula focused on treating difficult patients. © 2015 John Wiley & Sons Ltd.

Explicit and implicit learning: The case of computer programming

NASA Astrophysics Data System (ADS)

Mancy, Rebecca

The central question of this thesis concerns the role of explicit and implicit learning in the acquisition of a complex skill, namely computer programming. This issue is explored with reference to information processing models of memory drawn from cognitive science. These models indicate that conscious information processing occurs in working memory where information is stored and manipulated online, but that this mode of processing shows serious limitations in terms of capacity or resources. Some information processing models also indicate information processing in the absence of conscious awareness through automation and implicit learning. It was hypothesised that students would demonstrate implicit and explicit knowledge and that both would contribute to their performance in programming. This hypothesis was investigated via two empirical studies. The first concentrated on temporary storage and online processing in working memory and the second on implicit and explicit knowledge. Storage and processing were tested using two tools: temporary storage capacity was measured using a digit span test; processing was investigated with a disembedding test. The results were used to calculate correlation coefficients with performance on programming examinations. Individual differences in temporary storage had only a small role in predicting programming performance and this factor was not a major determinant of success. Individual differences in disembedding were more strongly related to programming achievement. The second study used interviews to investigate the use of implicit and explicit knowledge. Data were analysed according to a grounded theory paradigm. The results indicated that students possessed implicit and explicit knowledge, but that the balance between the two varied between students and that the most successful students did not necessarily possess greater explicit knowledge. The ways in which students described their knowledge led to the development of a framework which extends beyond the implicit-explicit dichotomy to four descriptive categories of knowledge along this dimension. Overall, the results demonstrated that explicit and implicit knowledge both contribute to the acquisition ofprogramming skills. Suggestions are made for further research, and the results are discussed in the context of their implications for education.

Assessing bioenergy harvest risks: Geospatially explicit tools for maintaining soil productivity in western US forests

Treesearch

Mark Kimsey; Deborah Page-Dumroese; Mark Coleman

2011-01-01

Biomass harvesting for energy production and forest health can impact the soil resource by altering inherent chemical, physical and biological properties. These impacts raise concern about damaging sensitive forest soils, even with the prospect of maintaining vigorous forest growth through biomass harvesting operations. Current forest biomass harvesting research...

Methods Development for a Spatially Explicit Population-Level Risk Assessment, Uncertainty Analysis, and Comparison with Risk Quotient Approaches

EPA Science Inventory

The standard framework of Ecological Risk Assessment (ERA) uses organism-level assessment endpoints to qualitatively determine the risk to populations. While organism-level toxicity data provide the pathway by which a species may be affected by a chemical stressor, they neither i...

Cloud Modeling

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Moncrieff, Mitchell; Einaud, Franco (Technical Monitor)

2001-01-01

Numerical cloud models have been developed and applied extensively to study cloud-scale and mesoscale processes during the past four decades. The distinctive aspect of these cloud models is their ability to treat explicitly (or resolve) cloud-scale dynamics. This requires the cloud models to be formulated from the non-hydrostatic equations of motion that explicitly include the vertical acceleration terms since the vertical and horizontal scales of convection are similar. Such models are also necessary in order to allow gravity waves, such as those triggered by clouds, to be resolved explicitly. In contrast, the hydrostatic approximation, usually applied in global or regional models, does allow the presence of gravity waves. In addition, the availability of exponentially increasing computer capabilities has resulted in time integrations increasing from hours to days, domain grids boxes (points) increasing from less than 2000 to more than 2,500,000 grid points with 500 to 1000 m resolution, and 3-D models becoming increasingly prevalent. The cloud resolving model is now at a stage where it can provide reasonably accurate statistical information of the sub-grid, cloud-resolving processes poorly parameterized in climate models and numerical prediction models.

Communication and re-use of chemical information in bioscience

PubMed Central

Murray-Rust, Peter; Mitchell, John BO; Rzepa, Henry S

2005-01-01

The current methods of publishing chemical information in bioscience articles are analysed. Using 3 papers as use-cases, it is shown that conventional methods using human procedures, including cut-and-paste are time-consuming and introduce errors. The meaning of chemical terms and the identity of compounds is often ambiguous. valuable experimental data such as spectra and computational results are almost always omitted. We describe an Open XML architecture at proof-of-concept which addresses these concerns. Compounds are identified through explicit connection tables or links to persistent Open resources such as PubChem. It is argued that if publishers adopt these tools and protocols, then the quality and quantity of chemical information available to bioscientists will increase and the authors, publishers and readers will find the process cost-effective. PMID:16026614

Numerical study of hydrogen-air supersonic combustion by using elliptic and parabolized equations

NASA Technical Reports Server (NTRS)

Chitsomboon, T.; Tiwari, S. N.

1986-01-01

The two-dimensional Navier-Stokes and species continuity equations are used to investigate supersonic chemically reacting flow problems which are related to scramjet-engine configurations. A global two-step finite-rate chemistry model is employed to represent the hydrogen-air combustion in the flow. An algebraic turbulent model is adopted for turbulent flow calculations. The explicit unsplit MacCormack finite-difference algorithm is used to develop a computer program suitable for a vector processing computer. The computer program developed is then used to integrate the system of the governing equations in time until convergence is attained. The chemistry source terms in the species continuity equations are evaluated implicitly to alleviate stiffness associated with fast chemical reactions. The problems solved by the elliptic code are re-investigated by using a set of two-dimensional parabolized Navier-Stokes and species equations. A linearized fully-coupled fully-implicit finite difference algorithm is used to develop a second computer code which solves the governing equations by marching in spce rather than time, resulting in a considerable saving in computer resources. Results obtained by using the parabolized formulation are compared with the results obtained by using the fully-elliptic equations. The comparisons indicate fairly good agreement of the results of the two formulations.

Separating the optical contributions to line-edge roughness in EUV lithography using stochastic simulations

NASA Astrophysics Data System (ADS)

Chunder, Anindarupa; Latypov, Azat; Chen, Yulu; Biafore, John J.; Levinson, Harry J.; Bailey, Todd

2017-03-01

Minimization and control of line-edge roughness (LER) and contact-edge roughness (CER) is one of the current challenges limiting EUV line-space and contact hole printability. One significant contributor to feature roughness and CD variability in EUV is photon shot noise (PSN); others are the physical and chemical processes in photoresists, known as resist stochastic effect. Different approaches are available to mitigate each of these contributions. In order to facilitate this mitigation, it is important to assess the magnitude of each of these contributions separately from others. In this paper, we present and test a computational approach based on the concept of an `ideal resist'. An ideal resist is assumed to be devoid of all resist stochastic effects. Hence, such an ideal resist can only be simulated as an `ideal resist model' (IRM) through explicit utilization of the Poisson statistics of PSN2 or direct Monte Carlo simulation of photon absorption in resist. LER estimated using IRM, thus quantifies the exclusive contribution of PSN to LER. The result of the simulation study done using IRM indicates higher magnitude of contribution (60%) from PSN to LER with respect to total or final LER for a sufficiently optimized high dose `state of the art' EUV chemically amplified resist (CAR) model.

Modeling and Assimilating Ocean Color Radiances

NASA Technical Reports Server (NTRS)

Gregg, Watson

2012-01-01

Radiances are the source of information from ocean color sensors to produce estimates of biological and geochemical constituents. They potentially provide information on various other aspects of global biological and chemical systems, and there is considerable work involved in deriving new information from these signals. Each derived product, however, contains errors that are derived from the application of the radiances, above and beyond the radiance errors. A global biogeochemical model with an explicit spectral radiative transfer model is used to investigate the potential of assimilating radiances. The results indicate gaps in our understanding of radiative processes in the oceans and their relationships with biogeochemical variables. Most important, detritus optical properties are not well characterized and produce important effects of the simulated radiances. Specifically, there does not appear to be a relationship between detrital biomass and its optical properties, as there is for chlorophyll. Approximations are necessary to get beyond this problem. In this reprt we will discuss the challenges in modeling and assimilation water-leaving radiances and the prospects for improving our understanding of biogeochemical process by utilizing these signals.

Testing the cognitive catalyst model of rumination with explicit and implicit cognitive content.

PubMed

Sova, Christopher C; Roberts, John E

2018-06-01

The cognitive catalyst model posits that rumination and negative cognitive content, such as negative schema, interact to predict depressive affect. Past research has found support for this model using explicit measures of negative cognitive content such as self-report measures of trait self-esteem and dysfunctional attitudes. The present study tested whether these findings would extend to implicit measures of negative cognitive content such as implicit self-esteem, and whether effects would depend on initial mood state and history of depression. Sixty-one undergraduate students selected on the basis of depression history (27 previously depressed; 34 never depressed) completed explicit and implicit measures of negative cognitive content prior to random assignment to a rumination induction followed by a distraction induction or vice versa. Dysphoric affect was measured both before and after these inductions. Analyses revealed that explicit measures, but not implicit measures, interacted with rumination to predict change in dysphoric affect, and these interactions were further moderated by baseline levels of dysphoria. Limitations include the small nonclinical sample and use of a self-report measure of depression history. These findings suggest that rumination amplifies the association between explicit negative cognitive content and depressive affect primarily among people who are already experiencing sad mood. Copyright © 2018 Elsevier Ltd. All rights reserved.

Effect of explicit dimension instruction on speech category learning

PubMed Central

Chandrasekaran, Bharath; Yi, Han-Gyol; Smayda, Kirsten E.; Maddox, W. Todd

2015-01-01

Learning non-native speech categories is often considered a challenging task in adulthood. This difficulty is driven by cross-language differences in weighting critical auditory dimensions that differentiate speech categories. For example, previous studies have shown that differentiating Mandarin tonal categories requires attending to dimensions related to pitch height and direction. Relative to native speakers of Mandarin, the pitch direction dimension is under-weighted by native English speakers. In the current study, we examined the effect of explicit instructions (dimension instruction) on native English speakers' Mandarin tone category learning within the framework of a dual-learning systems (DLS) model. This model predicts that successful speech category learning is initially mediated by an explicit, reflective learning system that frequently utilizes unidimensional rules, with an eventual switch to a more implicit, reflexive learning system that utilizes multidimensional rules. Participants were explicitly instructed to focus and/or ignore the pitch height dimension, the pitch direction dimension, or were given no explicit prime. Our results show that instruction instructing participants to focus on pitch direction, and instruction diverting attention away from pitch height resulted in enhanced tone categorization. Computational modeling of participant responses suggested that instruction related to pitch direction led to faster and more frequent use of multidimensional reflexive strategies, and enhanced perceptual selectivity along the previously underweighted pitch direction dimension. PMID:26542400

The explicit and implicit dance in psychoanalytic change.

PubMed

Fosshage, James L

2004-02-01

How the implicit/non-declarative and explicit/declarative cognitive domains interact is centrally important in the consideration of effecting change within the psychoanalytic arena. Stern et al. (1998) declare that long-lasting change occurs in the domain of implicit relational knowledge. In the view of this author, the implicit and explicit domains are intricately intertwined in an interactive dance within a psychoanalytic process. The author views that a spirit of inquiry (Lichtenberg, Lachmann & Fosshage 2002) serves as the foundation of the psychoanalytic process. Analyst and patient strive to explore, understand and communicate and, thereby, create a 'spirit' of interaction that contributes, through gradual incremental learning, to new implicit relational knowledge. This spirit, as part of the implicit relational interaction, is a cornerstone of the analytic relationship. The 'inquiry' more directly brings explicit/declarative processing to the foreground in the joint attempt to explore and understand. The spirit of inquiry in the psychoanalytic arena highlights both the autobiographical scenarios of the explicit memory system and the mental models of the implicit memory system as each contributes to a sense of self, other, and self with other. This process facilitates the extrication and suspension of the old models, so that new models based on current relational experience can be gradually integrated into both memory systems for lasting change.

Integrating remote sensing and spatially explicit epidemiological modeling

NASA Astrophysics Data System (ADS)

Finger, Flavio; Knox, Allyn; Bertuzzo, Enrico; Mari, Lorenzo; Bompangue, Didier; Gatto, Marino; Rinaldo, Andrea

2015-04-01

Spatially explicit epidemiological models are a crucial tool for the prediction of epidemiological patterns in time and space as well as for the allocation of health care resources. In addition they can provide valuable information about epidemiological processes and allow for the identification of environmental drivers of the disease spread. Most epidemiological models rely on environmental data as inputs. They can either be measured in the field by the means of conventional instruments or using remote sensing techniques to measure suitable proxies of the variables of interest. The later benefit from several advantages over conventional methods, including data availability, which can be an issue especially in developing, and spatial as well as temporal resolution of the data, which is particularly crucial for spatially explicit models. Here we present the case study of a spatially explicit, semi-mechanistic model applied to recurring cholera outbreaks in the Lake Kivu area (Democratic Republic of the Congo). The model describes the cholera incidence in eight health zones on the shore of the lake. Remotely sensed datasets of chlorophyll a concentration in the lake, precipitation and indices of global climate anomalies are used as environmental drivers. Human mobility and its effect on the disease spread is also taken into account. Several model configurations are tested on a data set of reported cases. The best models, accounting for different environmental drivers, and selected using the Akaike information criterion, are formally compared via cross validation. The best performing model accounts for seasonality, El Niño Southern Oscillation, precipitation and human mobility.

Modeling the Explicit Chemistry of Anthropogenic and Biogenic Organic Aerosols

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

Madronich, Sasha

2015-12-09

The atmospheric burden of Secondary Organic Aerosols (SOA) remains one of the most important yet uncertain aspects of the radiative forcing of climate. This grant focused on improving our quantitative understanding of SOA formation and evolution, by developing, applying, and improving a highly detailed model of atmospheric organic chemistry, the Generation of Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) model. Eleven (11) publications have resulted from this grant.

Advantages of soft subdural implants for the delivery of electrochemical neuromodulation therapies to the spinal cord

NASA Astrophysics Data System (ADS)

Capogrosso, Marco; Gandar, Jerome; Greiner, Nathan; Moraud, Eduardo Martin; Wenger, Nikolaus; Shkorbatova, Polina; Musienko, Pavel; Minev, Ivan; Lacour, Stephanie; Courtine, Grégoire

2018-04-01

Objective. We recently developed soft neural interfaces enabling the delivery of electrical and chemical stimulation to the spinal cord. These stimulations restored locomotion in animal models of paralysis. Soft interfaces can be placed either below or above the dura mater. Theoretically, the subdural location combines many advantages, including increased selectivity of electrical stimulation, lower stimulation thresholds, and targeted chemical stimulation through local drug delivery. However, these advantages have not been documented, nor have their functional impact been studied in silico or in a relevant animal model of neurological disorders using a multimodal neural interface. Approach. We characterized the recruitment properties of subdural interfaces using a realistic computational model of the rat spinal cord that included explicit representation of the spinal roots. We then validated and complemented computer simulations with electrophysiological experiments in rats. We additionally performed behavioral experiments in rats that received a lateral spinal cord hemisection and were implanted with a soft interface. Main results. In silico and in vivo experiments showed that the subdural location decreased stimulation thresholds compared to the epidural location while retaining high specificity. This feature reduces power consumption and risks of long-term damage in the tissues, thus increasing the clinical safety profile of this approach. The hemisection induced a transient paralysis of the leg ipsilateral to the injury. During this period, the delivery of electrical stimulation restricted to the injured side combined with local chemical modulation enabled coordinated locomotor movements of the paralyzed leg without affecting the non-impaired leg in all tested rats. Electrode properties remained stable over time, while anatomical examinations revealed excellent bio-integration properties. Significance. Soft neural interfaces inserted subdurally provide the opportunity to deliver electrical and chemical neuromodulation therapies using a single, bio-compatible and mechanically compliant device that effectively alleviates locomotor deficits after spinal cord injury.

A Scheme for the Integrated Assessment of Mitigation Options

NASA Astrophysics Data System (ADS)

Held, H.; Edenhofer, O.

2003-04-01

After some consensus has been achieved that the global mean temperature will have increased by 1.4 to 5.8^oC at the end of this century in case of continued ``business as usual'' greenhouse gas emissions, society has to decide if or which mitigation measures should be taken. A new integrated assessment project on this very issue will be started at PIK in spring 2003. The assessment will cover economic aspects as well as potential side effects of various measures. In the economic module, the effects of investment decisions on technological innovation will be explicitly taken into account. Special emphasize will be put on the issue of uncertainty. Hereby we distinguish the uncertainty related to the Integrated Assessment modules, including the economic module, from the fact that no over-complex system can be fully captured by a model. Therefore, a scheme for the assessment of the ``residual'', the non-modelled part of the system, needs to be worked out. The scheme must be truly interdisciplinary, i.e. must be applicable to at least the natural science and the economic aspects. A scheme based on meta-principles like minimum persistence, ubiquity, or irreversibility of potential measures appears to be a promising candidate. An implementation of ubiquity as at present successfully operated in environmental chemistry may serve as a guideline [1]. Here, the best-known mechanism within a complex impact chain of potentially harmful chemicals, their transport, is captured by a reaction-diffusion mechanism [2]. begin{thebibliography}{0} bibitem{s} M. Scheringer, Persistence and spatial range as endpoints of an exposure-based assessment of organic chemicals. Environ. Sci. Technol. 30: 1652-1659 (1996). bibitem{h} H. Held, Robustness of spatial ranges of environmental chemicals with respect to model dimension, accepted for publication in Stoch. Environ. Res. Risk Assessment.

Development of a chlorine chemistry module for the Master Chemical Mechanism

NASA Astrophysics Data System (ADS)

Xue, L. K.; Saunders, S. M.; Wang, T.; Gao, R.; Wang, X. F.; Zhang, Q. Z.; Wang, W. X.

2015-06-01

The chlorine atom (Cl·) has a high potential to perturb atmospheric photochemistry by oxidizing volatile organic compounds (VOCs), but the exact role it plays in the polluted troposphere remains unclear. The Master Chemical Mechanism (MCM) is a near explicit mechanism that has been widely applied in the atmospheric chemistry research. While it addresses comprehensively the chemistry initiated by the OH, O3 and NO3 radicals, its representation of the Cl· chemistry is incomplete as it only considers the reactions for alkanes. In this paper, we develop a more comprehensive Cl· chemistry module that can be directly incorporated within the MCM framework. A suite of 199 chemical reactions describes the Cl·-initiated degradation of alkenes, aromatics, aldehydes, ketones, alcohols, and some organic acids and nitrates, along with the inorganic chemistry involving Cl· and its precursors. To demonstrate the potential influence of the new chemistry module, it was incorporated into a MCM box model to evaluate the impacts of nitryl chloride (ClNO2), a product of nocturnal halogen activation by nitrogen oxides (NOx), on the following-day's atmospheric photochemistry. With constraints of recent observations collected at a coastal site in Hong Kong, southern China, the modeling analyses suggest that the Cl· produced from ClNO2 photolysis may substantially enhance the atmospheric oxidative capacity, VOC oxidation, and O3 formation, particularly in the early morning period. The results demonstrate the critical need for photochemical models to include more fully chlorine chemistry in order to better understand the atmospheric photochemistry in polluted environments subject to intense emissions of NOx, VOCs and chlorine-containing constituents.

Development of a chlorine chemistry module for the Master Chemical Mechanism

NASA Astrophysics Data System (ADS)

Xue, L. K.; Saunders, S. M.; Wang, T.; Gao, R.; Wang, X. F.; Zhang, Q. Z.; Wang, W. X.

2015-10-01

The chlorine atom (Cl·) has a high potential to perturb atmospheric photochemistry by oxidizing volatile organic compounds (VOCs), but the exact role it plays in the polluted troposphere remains unclear. The Master Chemical Mechanism (MCM) is a near-explicit mechanism that has been widely applied in the atmospheric chemistry research. While it addresses comprehensively the chemistry initiated by the OH, O3 and NO3 radicals, its representation of the Cl· chemistry is incomplete as it only considers the reactions for alkanes. In this paper, we develop a more comprehensive Cl· chemistry module that can be directly incorporated within the MCM framework. A suite of 205 chemical reactions describes the Cl·-initiated degradation of alkenes, aromatics, alkynes, aldehydes, ketones, alcohols, and some organic acids and nitrates, along with the inorganic chemistry involving Cl· and its precursors. To demonstrate the potential influence of the new chemistry module, it was incorporated into a MCM box model to evaluate the impacts of nitryl chloride (ClNO2), a product of nocturnal halogen activation by nitrogen oxides (NOX), on the following day's atmospheric photochemistry. With constraints of recent observations collected at a coastal site in Hong Kong, southern China, the modeling analyses suggest that the Cl· produced from ClNO2 photolysis may substantially enhance the atmospheric oxidative capacity, VOC oxidation and O3 formation, particularly in the early morning period. The results demonstrate the critical need for photochemical models to include more detailed chlorine chemistry in order to better understand the atmospheric photochemistry in polluted environments subject to intense emissions of NOX, VOCs and chlorine-containing constituents.

Simulation of the M13 life cycle I: Assembly of a genetically-structured deterministic chemical kinetic simulation.

PubMed

Smeal, Steven W; Schmitt, Margaret A; Pereira, Ronnie Rodrigues; Prasad, Ashok; Fisk, John D

2017-01-01

To expand the quantitative, systems level understanding and foster the expansion of the biotechnological applications of the filamentous bacteriophage M13, we have unified the accumulated quantitative information on M13 biology into a genetically-structured, experimentally-based computational simulation of the entire phage life cycle. The deterministic chemical kinetic simulation explicitly includes the molecular details of DNA replication, mRNA transcription, protein translation and particle assembly, as well as the competing protein-protein and protein-nucleic acid interactions that control the timing and extent of phage production. The simulation reproduces the holistic behavior of M13, closely matching experimentally reported values of the intracellular levels of phage species and the timing of events in the M13 life cycle. The computational model provides a quantitative description of phage biology, highlights gaps in the present understanding of M13, and offers a framework for exploring alternative mechanisms of regulation in the context of the complete M13 life cycle. Copyright © 2016 Elsevier Inc. All rights reserved.

Translational Science for Energy and Beyond

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

McKone, James R.; Crans, Debbie C.; Martin, Cheryl

A clear challenge for the coming decades is decreasing the carbon intensity of the global energy supply while simultaneously accommodating a rapid worldwide increase in power demand. Meeting this challenge of providing abundant, clean energy undoubtedly requires synergistic efforts between basic and applied researchers in the chemical sciences to develop and deploy new technologies. Among the available options, solar energy is one of the promising targets because of the high abundance of solar photons over much of the globe. Similarly, decarbonization of the global energy supply will require clean sources of hydrogen to use as reducing equivalents for fuel andmore » chemical feedstocks. In this report, we discuss the importance of translational research -- defined as work that explicitly targets basic discovery as well as technology development -- in the context of photovoltaics and solar fuels. We focus on three representative research programs encompassing translational research in government, industry, and academia. We then discuss more broadly the benefits and challenges of translational research models and offer recommendations for research programs that address societal challenges in the energy sector and beyond.« less

Approach to equilibrium of a quantum system and generalization of the Montroll-Shuler equation for vibrational relaxation of a molecular oscillator

NASA Astrophysics Data System (ADS)

Kenkre, V. M.; Chase, M.

2017-08-01

The approach to equilibrium of a quantum mechanical system in interaction with a bath is studied from a practical as well as a conceptual point of view. Explicit memory functions are derived for given models of bath couplings. If the system is a harmonic oscillator representing a molecule in interaction with a reservoir, the generalized master equation derived becomes an extension into the coherent domain of the well-known Montroll-Shuler equation for vibrational relaxation and unimolecular dissociation. A generalization of the Bethe-Teller result regarding energy relaxation is found for short times. The theory has obvious applications to relaxation dynamics at ultra-short times as in observations on the femtosecond time scale and to the investigation of quantum coherence at those short times. While vibrational relaxation in chemical physics is a primary target of the study, another system of interest in condensed matter physics, an electron or hole in a lattice subjected to a strong DC electric field that gives rise to well-known Wannier-Stark ladders, is naturally addressed with the theory. Specific system-bath interactions are explored to obtain explicit details of the dynamics. General phenomenological descriptions of the reservoir are considered rather than specific microscopic realizations.

Including resonances in the multiperipheral model

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

Pinsky, S.S.; Snider, D.R.; Thomas, G.H.

1973-10-01

A simple generalization of the multiperipheral model (MPM) and the Mueller--Regge Model (MRM) is given which has improved phenomenological capabilities by explicitly incorporating resonance phenomena, and still is simple enough to be an important theoretical laboratory. The model is discussed both with and without charge. In addition, the one channel, two channel, three channel and N channel cases are explicitly treated. Particular attention is paid to the constraints of charge conservation and positivity in the MRM. The recently proven equivalence between the MRM and MPM is extended to this model, and is used extensively. (auth)

Explicit Pore Pressure Material Model in Carbon-Cloth Phenolic

NASA Technical Reports Server (NTRS)

Gutierrez-Lemini, Danton; Ehle, Curt

2003-01-01

An explicit material model that uses predicted pressure in the pores of a carbon-cloth phenolic (CCP) composite has been developed. This model is intended to be used within a finite-element model to predict phenomena specific to CCP components of solid-fuel-rocket nozzles subjected to high operating temperatures and to mechanical stresses that can be great enough to cause structural failures. Phenomena that can be predicted with the help of this model include failures of specimens in restrained-thermal-growth (RTG) tests, pocketing erosion, and ply lifting

Effects of prompting and reinforcement of one response pattern upon imitation of a different modeled pattern

PubMed Central

Bondy, Andrew S.

1982-01-01

Twelve preschool children participated in a study of the effects of explicit training on the imitation of modeled behavior. The responses trained involved a marble-dropping pattern that differed from the modeled pattern. Training consisted of physical prompts and verbal praise during a single session. No prompts or praise were used during test periods. After operant levels of the experimental responses were measured, training either preceded or was interposed within a series of exposures to modeled behavior that differed from the trained behavior. Children who were initially exposed to a modeling session immediately imitated, whereas those children who were initially trained immediately performed the appropriate response. Children initially trained on one pattern generally continued to exhibit that pattern even after many modeling sessions. Children who first viewed the modeled response and then were exposed to explicit training of a different response reversed their response pattern from the trained response to the modeled response within a few sessions. The results suggest that under certain conditions explicit training will exert greater control over responding than immediate modeling stimuli. PMID:16812260

Transient modeling/analysis of hyperbolic heat conduction problems employing mixed implicit-explicit alpha method

NASA Technical Reports Server (NTRS)

Tamma, Kumar K.; D'Costa, Joseph F.

1991-01-01

This paper describes the evaluation of mixed implicit-explicit finite element formulations for hyperbolic heat conduction problems involving non-Fourier effects. In particular, mixed implicit-explicit formulations employing the alpha method proposed by Hughes et al. (1987, 1990) are described for the numerical simulation of hyperbolic heat conduction models, which involves time-dependent relaxation effects. Existing analytical approaches for modeling/analysis of such models involve complex mathematical formulations for obtaining closed-form solutions, while in certain numerical formulations the difficulties include severe oscillatory solution behavior (which often disguises the true response) in the vicinity of the thermal disturbances, which propagate with finite velocities. In view of these factors, the alpha method is evaluated to assess the control of the amount of numerical dissipation for predicting the transient propagating thermal disturbances. Numerical test models are presented, and pertinent conclusions are drawn for the mixed-time integration simulation of hyperbolic heat conduction models involving non-Fourier effects.

Testing the Use of Implicit Solvent in the Molecular Dynamics Modelling of DNA Flexibility

NASA Astrophysics Data System (ADS)

Mitchell, J.; Harris, S.

DNA flexibility controls packaging, looping and in some cases sequence specific protein binding. Molecular dynamics simulations carried out with a computationally efficient implicit solvent model are potentially a powerful tool for studying larger DNA molecules than can be currently simulated when water and counterions are represented explicitly. In this work we compare DNA flexibility at the base pair step level modelled using an implicit solvent model to that previously determined from explicit solvent simulations and database analysis. Although much of the sequence dependent behaviour is preserved in implicit solvent, the DNA is considerably more flexible when the approximate model is used. In addition we test the ability of the implicit solvent to model stress induced DNA disruptions by simulating a series of DNA minicircle topoisomers which vary in size and superhelical density. When compared with previously run explicit solvent simulations, we find that while the levels of DNA denaturation are similar using both computational methodologies, the specific structural form of the disruptions is different.

Spatially explicit modelling of cholera epidemics

NASA Astrophysics Data System (ADS)

Finger, F.; Bertuzzo, E.; Mari, L.; Knox, A. C.; Gatto, M.; Rinaldo, A.

2013-12-01

Epidemiological models can provide crucial understanding about the dynamics of infectious diseases. Possible applications range from real-time forecasting and allocation of health care resources to testing alternative intervention mechanisms such as vaccines, antibiotics or the improvement of sanitary conditions. We apply a spatially explicit model to the cholera epidemic that struck Haiti in October 2010 and is still ongoing. The dynamics of susceptibles as well as symptomatic and asymptomatic infectives are modelled at the scale of local human communities. Dissemination of Vibrio cholerae through hydrological transport and human mobility along the road network is explicitly taken into account, as well as the effect of rainfall as a driver of increasing disease incidence. The model is calibrated using a dataset of reported cholera cases. We further model the long term impact of several types of interventions on the disease dynamics by varying parameters appropriately. Key epidemiological mechanisms and parameters which affect the efficiency of treatments such as antibiotics are identified. Our results lead to conclusions about the influence of different intervention strategies on the overall epidemiological dynamics.

Assessing implicit models for nonpolar mean solvation forces: The importance of dispersion and volume terms

PubMed Central

Wagoner, Jason A.; Baker, Nathan A.

2006-01-01

Continuum solvation models provide appealing alternatives to explicit solvent methods because of their ability to reproduce solvation effects while alleviating the need for expensive sampling. Our previous work has demonstrated that Poisson-Boltzmann methods are capable of faithfully reproducing polar explicit solvent forces for dilute protein systems; however, the popular solvent-accessible surface area model was shown to be incapable of accurately describing nonpolar solvation forces at atomic-length scales. Therefore, alternate continuum methods are needed to reproduce nonpolar interactions at the atomic scale. In the present work, we address this issue by supplementing the solvent-accessible surface area model with additional volume and dispersion integral terms suggested by scaled particle models and Weeks–Chandler–Andersen theory, respectively. This more complete nonpolar implicit solvent model shows very good agreement with explicit solvent results and suggests that, although often overlooked, the inclusion of appropriate dispersion and volume terms are essential for an accurate implicit solvent description of atomic-scale nonpolar forces. PMID:16709675

Development and assessment of 30-meter pine density maps for landscape-level modeling of mountain pine beetle dynamics

Treesearch

Benjamin A. Crabb; James A. Powell; Barbara J. Bentz

2012-01-01

Forecasting spatial patterns of mountain pine beetle (MPB) population success requires spatially explicit information on host pine distribution. We developed a means of producing spatially explicit datasets of pine density at 30-m resolution using existing geospatial datasets of vegetation composition and structure. Because our ultimate goal is to model MPB population...

Emergence of a coherent and cohesive swarm based on mutual anticipation

PubMed Central

Murakami, Hisashi; Niizato, Takayuki; Gunji, Yukio-Pegio

2017-01-01

Collective behavior emerging out of self-organization is one of the most striking properties of an animal group. Typically, it is hypothesized that each individual in an animal group tends to align its direction of motion with those of its neighbors. Most previous models for collective behavior assume an explicit alignment rule, by which an agent matches its velocity with that of neighbors in a certain neighborhood, to reproduce a collective order pattern by simple interactions. Recent empirical studies, however, suggest that there is no evidence for explicit matching of velocity, and that collective polarization arises from interactions other than those that follow the explicit alignment rule. We here propose a new lattice-based computational model that does not incorporate the explicit alignment rule but is based instead on mutual anticipation and asynchronous updating. Moreover, we show that this model can realize densely collective motion with high polarity. Furthermore, we focus on the behavior of a pair of individuals, and find that the turning response is drastically changed depending on the distance between two individuals rather than the relative heading, and is consistent with the empirical observations. Therefore, the present results suggest that our approach provides an alternative model for collective behavior. PMID:28406173

Flory-type theories of polymer chains under different external stimuli

NASA Astrophysics Data System (ADS)

Budkov, Yu A.; Kiselev, M. G.

2018-01-01

In this Review, we present a critical analysis of various applications of the Flory-type theories to a theoretical description of the conformational behavior of single polymer chains in dilute polymer solutions under a few external stimuli. Different theoretical models of flexible polymer chains in the supercritical fluid are discussed and analysed. Different points of view on the conformational behavior of the polymer chain near the liquid-gas transition critical point of the solvent are presented. A theoretical description of the co-solvent-induced coil-globule transitions within the implicit-solvent-explicit-co-solvent models is discussed. Several explicit-solvent-explicit-co-solvent theoretical models of the coil-to-globule-to-coil transition of the polymer chain in a mixture of good solvents (co-nonsolvency) are analysed and compared with each other. Finally, a new theoretical model of the conformational behavior of the dielectric polymer chain under the external constant electric field in the dilute polymer solution with an explicit account for the many-body dipole correlations is discussed. The polymer chain collapse induced by many-body dipole correlations of monomers in the context of statistical thermodynamics of dielectric polymers is analysed.

Implicit-Explicit Time Integration Methods for Non-hydrostatic Atmospheric Models

NASA Astrophysics Data System (ADS)

Gardner, D. J.; Guerra, J. E.; Hamon, F. P.; Reynolds, D. R.; Ullrich, P. A.; Woodward, C. S.

2016-12-01

The Accelerated Climate Modeling for Energy (ACME) project is developing a non-hydrostatic atmospheric dynamical core for high-resolution coupled climate simulations on Department of Energy leadership class supercomputers. An important factor in computational efficiency is avoiding the overly restrictive time step size limitations of fully explicit time integration methods due to the stiffest modes present in the model (acoustic waves). In this work we compare the accuracy and performance of different Implicit-Explicit (IMEX) splittings of the non-hydrostatic equations and various Additive Runge-Kutta (ARK) time integration methods. Results utilizing the Tempest non-hydrostatic atmospheric model and the ARKode package show that the choice of IMEX splitting and ARK scheme has a significant impact on the maximum stable time step size as well as solution quality. Horizontally Explicit Vertically Implicit (HEVI) approaches paired with certain ARK methods lead to greatly improved runtimes. With effective preconditioning IMEX splittings that incorporate some implicit horizontal dynamics can be competitive with HEVI results. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-699187

The Construction of Visual-spatial Situation Models in Children's Reading and Their Relation to Reading Comprehension

PubMed Central

Barnes, Marcia A.; Raghubar, Kimberly P.; Faulkner, Heather; Denton, Carolyn A.

2014-01-01

Readers construct mental models of situations described by text to comprehend what they read, updating these situation models based on explicitly described and inferred information about causal, temporal, and spatial relations. Fluent adult readers update their situation models while reading narrative text based in part on spatial location information that is consistent with the perspective of the protagonist. The current study investigates whether children update spatial situation models in a similar way, whether there are age-related changes in children's formation of spatial situation models during reading, and whether measures of the ability to construct and update spatial situation models are predictive of reading comprehension. Typically-developing children from ages 9 through 16 years (n=81) were familiarized with a physical model of a marketplace. Then the model was covered, and children read stories that described the movement of a protagonist through the marketplace and were administered items requiring memory for both explicitly stated and inferred information about the character's movements. Accuracy of responses and response times were evaluated. Results indicated that: (a) location and object information during reading appeared to be activated and updated not simply from explicit text-based information but from a mental model of the real world situation described by the text; (b) this pattern showed no age-related differences; and (c) the ability to update the situation model of the text based on inferred information, but not explicitly stated information, was uniquely predictive of reading comprehension after accounting for word decoding. PMID:24315376

The molecular structure and absorption spectrum of hydroxy substituted dibenzoylmethanatoboron difluoride in solution: A theoretical and experimental study

NASA Astrophysics Data System (ADS)

Gelfand, Natalia; Freidzon, Alexandra; Fedorenko, Elena

2018-01-01

Electronic spectroscopy and quantum chemistry are used to study the structure and absorption spectra of the hydroxy substituted dibenzoylmethanatoboron difluoride (OHDBMBF2) in solutions. Introducing a hydroxy group in the diketonate moiety allows the dye to form intermolecular complexes with proton acceptors, such as solvents or analytes, thus making it a promising chemical sensor. Our calculations show that donor oxygen-containing solvents break the intramolecular hydrogen bond Osbnd H···Odik and form an intermolecular Osbnd H···Osolv bond thus disrupting the coplanarity of the dye and affecting the position and shape of its absorption bands. The spectra calculated with explicit solvent combined with polarizable continuum model (PCM) better agree with the experiment than those calculated only within PCM.

Interactions in charged colloidal suspensions: A molecular dynamics simulation study

NASA Astrophysics Data System (ADS)

Padidela, Uday Kumar; Behera, Raghu Nath

2017-07-01

Colloidal suspensions are extensively used in everyday life and find several applications in the pharmaceutical, chemical, food industries, etc. We present the classical molecular dynamics simulation results of the structural and transport properties of charged colloidal suspensions as a function of its size, charge and concentration. The system is viewed as a two-component (colloids and counterions) primitive model consisting of spherical colloid particle (macroion) and the counterions (micro-particles), which are treated explicitly. The solvent is treated as dielectric continuum. A systematic trend in the radial distribution functions g(r), potential of mean force W(r), different thermodynamic properties and diffusion coefficients is obtained as a function of colloid charge, size and concentration. An attractive minimum in W(r) is obtained at short interparticle distance.

Rapid Response Tools and Datasets for Post-fire Erosion Modeling: Lessons Learned from the Rock House and High Park Fires

NASA Astrophysics Data System (ADS)

Miller, Mary Ellen; Elliot, William E.; MacDonald, Lee H.

2013-04-01

Once the danger posed by an active wildfire has passed, land managers must rapidly assess the threat from post-fire runoff and erosion due to the loss of surface cover and fire-induced changes in soil properties. Increased runoff and sediment delivery are of great concern to both the pubic and resource managers. Post-fire assessments and proposals to mitigate these threats are typically undertaken by interdisciplinary Burned Area Emergency Response (BAER) teams. These teams are under very tight deadlines, so they often begin their analysis while the fire is still burning and typically must complete their plans within a couple of weeks. Many modeling tools and datasets have been developed over the years to assist BAER teams, but process-based, spatially explicit models are currently under-utilized relative to simpler, lumped models because they are more difficult to set up and require the preparation of spatially-explicit data layers such as digital elevation models, soils, and land cover. The difficulty of acquiring and utilizing these data layers in spatially-explicit models increases with increasing fire size. Spatially-explicit post-fire erosion modeling was attempted for a small watershed in the 1270 km2 Rock House fire in Texas, but the erosion modeling work could not be completed in time. The biggest limitation was the time required to extract the spatially explicit soils data needed to run the preferred post-fire erosion model (GeoWEPP with Disturbed WEPP parameters). The solution is to have the spatial soil, land cover, and DEM data layers prepared ahead of time, and to have a clear methodology for the BAER teams to incorporate these layers in spatially-explicit modeling interfaces like GeoWEPP. After a fire occurs the data layers can quickly be clipped to the fire perimeter. The soil and land cover parameters can then be adjusted according to the burn severity map, which is one of the first products generated for the BAER teams. Under a previous project for the U.S. Environmental Protection Agency this preparatory work was done for much of Colorado, and in June 2012 the High Park wildfire in north central Colorado burned over 340 km2. The data layers for the entire burn area were quickly assembled and the spatially explicit runoff and erosion modeling was completed in less than three days. The resulting predictions were then used by the BAER team to quantify downstream risks and delineate priority areas for different post-fire treatments. These two contrasting case studies demonstrate the feasibility and the value of preparing datasets and modeling tools ahead of time. In recognition of this, the U.S. National Aeronautic and Space Administration has agreed to fund a pilot project to demonstrate the utility of acquiring and preparing the necessary data layers for fire-prone wildlands across the western U.S. A similar modeling and data acquisition approach could be followed

Explicit and implicit cognition: a preliminary test of a dual-process theory of cognitive vulnerability to depression.

PubMed

Haeffel, Gerald J; Abramson, Lyn Y; Brazy, Paige C; Shah, James Y; Teachman, Bethany A; Nosek, Brian A

2007-06-01

Two studies were conducted to test a dual-process theory of cognitive vulnerability to depression. According to this theory, implicit and explicit cognitive processes have differential effects on depressive reactions to stressful life events. Implicit processes are hypothesized to be critical in determining an individual's immediate affective reaction to stress whereas explicit cognitions are thought to be more involved in long-term depressive reactions. Consistent with hypotheses, the results of study 1 (cross-sectional; N=237) showed that implicit, but not explicit, cognitions predicted immediate affective reactions to a lab stressor. Study 2 (longitudinal; N=251) also supported the dual-process model of cognitive vulnerability to depression. Results showed that both the implicit and explicit measures interacted with life stress to predict prospective changes in depressive symptoms, respectively. However, when both implicit and explicit predictors were entered into a regression equation simultaneously, only the explicit measure interacted with stress to remain a unique predictor of depressive symptoms over the five-week prospective interval.

Improved pKa Prediction of Substituted Alcohols, Phenols, and Hydroperoxides in Aqueous Medium Using Density Functional Theory and a Cluster-Continuum Solvation Model.

PubMed

Thapa, Bishnu; Schlegel, H Bernhard

2017-06-22

Acid dissociation constants (pK a 's) are key physicochemical properties that are needed to understand the structure and reactivity of molecules in solution. Theoretical pK a 's have been calculated for a set of 72 organic compounds with -OH and -OOH groups (48 with known experimental pK a 's). This test set includes 17 aliphatic alcohols, 25 substituted phenols, and 30 hydroperoxides. Calculations in aqueous medium have been carried out with SMD implicit solvation and three hybrid DFT functionals (B3LYP, ωB97XD, and M06-2X) with two basis sets (6-31+G(d,p) and 6-311++G(d,p)). The effect of explicit water molecules on calculated pK a 's was assessed by including up to three water molecules. pK a 's calculated with only SMD implicit solvation are found to have average errors greater than 6 pK a units. Including one explicit water reduces the error by about 3 pK a units, but the error is still far from chemical accuracy. With B3LYP/6-311++G(d,p) and three explicit water molecules in SMD solvation, the mean signed error and standard deviation are only -0.02 ± 0.55; a linear fit with zero intercept has a slope of 1.005 and R 2 = 0.97. Thus, this level of theory can be used to calculate pK a 's directly without the need for linear correlations or thermodynamic cycles. Estimated pK a values are reported for 24 hydroperoxides that have not yet been determined experimentally.

Solvent effect in implicit/explicit model on FT-IR, 1H, 13C and 19F NMR, UV-vis and fluorescence spectra, linear, second- and third-nonlinear optical parameters of 2-(trifluoromethyl)benzoic acid: Experimental and computational study

NASA Astrophysics Data System (ADS)

Avcı, Davut; Altürk, Sümeyye; Tamer, Ömer; Kuşbazoğlu, Mustafa; Atalay, Yusuf

2017-09-01

FT-IR, 1H, 13C and 19F NMR, UV-vis and fluorescence spectra for 2-(trifluoromethyl)benzoic acid (2-TFMBA) were recorded. DFT//B3LYP/6-31++G(d,p) calculations were used to determine the optimized molecular geometry, vibrational frequencies, 1H, 13C and 19F GIAO-NMR chemical shifts of 2-TFMBA. The detailed assignments of vibrational frequencies were carried out on the basis of potential energy distribution (PED) by using VEDA program. TD-DFT/B3LYP/6-31++G(d,p) calculations with the PCM (polarizable continuum model) in ethanol and DMSO solvents based on implicit/explicit model and gas phase in the excited state were employed to investigate UV-vis absorption and fluorescence emission wavelengths. The UV-vis and emission spectra were given in ethanol and DMSO solvents, and the major contributions to the electronic transitions were obtained. In addition, the NLO parameters (β, γ and χ(3)) and frontier molecular orbital energies of 2-TFMBA were calculated by using B3LYP/6-31++G(d,p) level. The NLO parameters of 2-TFMBA were compared with that of para-Nitroaniline (pNA) and urea which are the typical NLO materials. The refractive index (n) is calculated by using the Lorentz-Lorenz equation to observe polarization behavior of 2-TFMBA in DMSO and ethanol solvents. In order to investigate intramolecular and hydrogen bonding interactions, NBO calculations were also performed by the same level. To sum up, considering the well-known biological role, photochemical properties of 2-TFMBA were discussed.

Comparison of Damage Path Predictions for Composite Laminates by Explicit and Standard Finite Element Analysis Tools

NASA Technical Reports Server (NTRS)

Bogert, Philip B.; Satyanarayana, Arunkumar; Chunchu, Prasad B.

2006-01-01

Splitting, ultimate failure load and the damage path in center notched composite specimens subjected to in-plane tension loading are predicted using progressive failure analysis methodology. A 2-D Hashin-Rotem failure criterion is used in determining intra-laminar fiber and matrix failures. This progressive failure methodology has been implemented in the Abaqus/Explicit and Abaqus/Standard finite element codes through user written subroutines "VUMAT" and "USDFLD" respectively. A 2-D finite element model is used for predicting the intra-laminar damages. Analysis results obtained from the Abaqus/Explicit and Abaqus/Standard code show good agreement with experimental results. The importance of modeling delamination in progressive failure analysis methodology is recognized for future studies. The use of an explicit integration dynamics code for simple specimen geometry and static loading establishes a foundation for future analyses where complex loading and nonlinear dynamic interactions of damage and structure will necessitate it.

Group-based differences in anti-aging bias among medical students.

PubMed

Ruiz, Jorge G; Andrade, Allen D; Anam, Ramanakumar; Taldone, Sabrina; Karanam, Chandana; Hogue, Christie; Mintzer, Michael J

2015-01-01

Medical students (MS) may develop ageist attitudes early in their training that may predict their future avoidance of caring for the elderly. This study sought to determine MS' patterns of explicit and implicit anti-aging bias, intent to practice with older people and using the quad model, the role of gender, race, and motivation-based differences. One hundred and three MS completed an online survey that included explicit and implicit measures. Explicit measures revealed a moderately positive perception of older people. Female medical students and those high in internal motivation showed lower anti-aging bias, and both were more likely to intend to practice with older people. Although the implicit measure revealed more negativity toward the elderly than the explicit measures, there were no group differences. However, using the quad model the authors identified gender, race, and motivation-based differences in controlled and automatic processes involved in anti-aging bias.

A Tractable Disequilbrium Framework for Integrating Computational Thermodynamics and Geodynamics

NASA Astrophysics Data System (ADS)

Spiegelman, M. W.; Tweed, L. E. L.; Evans, O.; Kelemen, P. B.; Wilson, C. R.

2017-12-01

The consistent integration of computational thermodynamics and geodynamics is essential for exploring and understanding a wide range of processes from high-PT magma dynamics in the convecting mantle to low-PT reactive alteration of the brittle crust. Nevertheless, considerable challenges remain for coupling thermodynamics and fluid-solid mechanics within computationally tractable and insightful models. Here we report on a new effort, part of the ENKI project, that provides a roadmap for developing flexible geodynamic models of varying complexity that are thermodynamically consistent with established thermodynamic models. The basic theory is derived from the disequilibrium thermodynamics of De Groot and Mazur (1984), similar to Rudge et. al (2011, GJI), but extends that theory to include more general rheologies, multiple solid (and liquid) phases and explicit chemical reactions to describe interphase exchange. Specifying stoichiometric reactions clearly defines the compositions of reactants and products and allows the affinity of each reaction (A = -Δ/Gr) to be used as a scalar measure of disequilibrium. This approach only requires thermodynamic models to return chemical potentials of all components and phases (as well as thermodynamic quantities for each phase e.g. densities, heat capacity, entropies), but is not constrained to be in thermodynamic equilibrium. Allowing meta-stable phases mitigates some of the computational issues involved with the introduction and exhaustion of phases. Nevertheless, for closed systems, these problems are guaranteed to evolve to the same equilibria predicted by equilibrium thermodynamics. Here we illustrate the behavior of this theory for a range of simple problems (constructed with our open-source model builder TerraFERMA) that model poro-viscous behavior in the well understood Fo-Fa binary phase loop. Other contributions in this session will explore a range of models with more petrologically interesting phase diagrams as well as other rheologies.

A different time and place test of ArcHSI: A spatially explicit habitat model for elk in the Black Hills

Treesearch

Mark A. Rumble; Lakhdar Benkobi; R. Scott Gamo

2007-01-01

We tested predictions of the spatially explicit ArcHSI habitat model for elk. The distribution of elk relative to proximity of forage and cover differed from that predicted. Elk used areas near primary roads similar to that predicted by the model, but elk were farther from secondary roads. Elk used areas categorized as good (> 0.7), fair (> 0.42 to 0.7), and poor...

Pulsar distances and the galactic distribution of free electrons

NASA Technical Reports Server (NTRS)

Taylor, J. H.; Cordes, J. M.

1993-01-01

The present quantitative model for Galactic free electron distribution abandons the assumption of axisymmetry and explicitly incorporates spiral arms; their shapes and locations are derived from existing radio and optical observations of H II regions. The Gum Nebula's dispersion-measure contributions are also explicitly modeled. Adjustable quantities are calibrated by reference to three different types of data. The new model is estimated to furnish distance estimates to known pulsars that are accurate to about 25 percent.

Continuum Fatigue Damage Modeling for Use in Life Extending Control

NASA Technical Reports Server (NTRS)

Lorenzo, Carl F.

1994-01-01

This paper develops a simplified continuum (continuous wrp to time, stress, etc.) fatigue damage model for use in Life Extending Controls (LEC) studies. The work is based on zero mean stress local strain cyclic damage modeling. New nonlinear explicit equation forms of cyclic damage in terms of stress amplitude are derived to facilitate the continuum modeling. Stress based continuum models are derived. Extension to plastic strain-strain rate models are also presented. Application of these models to LEC applications is considered. Progress toward a nonzero mean stress based continuum model is presented. Also, new nonlinear explicit equation forms in terms of stress amplitude are also derived for this case.

Importance of spatial autocorrelation in modeling bird distributions at a continental scale

USGS Publications Warehouse

Bahn, V.; O'Connor, R.J.; Krohn, W.B.

2006-01-01

Spatial autocorrelation in species' distributions has been recognized as inflating the probability of a type I error in hypotheses tests, causing biases in variable selection, and violating the assumption of independence of error terms in models such as correlation or regression. However, it remains unclear whether these problems occur at all spatial resolutions and extents, and under which conditions spatially explicit modeling techniques are superior. Our goal was to determine whether spatial models were superior at large extents and across many different species. In addition, we investigated the importance of purely spatial effects in distribution patterns relative to the variation that could be explained through environmental conditions. We studied distribution patterns of 108 bird species in the conterminous United States using ten years of data from the Breeding Bird Survey. We compared the performance of spatially explicit regression models with non-spatial regression models using Akaike's information criterion. In addition, we partitioned the variance in species distributions into an environmental, a pure spatial and a shared component. The spatially-explicit conditional autoregressive regression models strongly outperformed the ordinary least squares regression models. In addition, partialling out the spatial component underlying the species' distributions showed that an average of 17% of the explained variation could be attributed to purely spatial effects independent of the spatial autocorrelation induced by the underlying environmental variables. We concluded that location in the range and neighborhood play an important role in the distribution of species. Spatially explicit models are expected to yield better predictions especially for mobile species such as birds, even in coarse-grained models with a large extent. ?? Ecography.

LES with and without explicit filtering: comparison and assessment of various models

NASA Astrophysics Data System (ADS)

Winckelmans, Gregoire S.; Jeanmart, Herve; Wray, Alan A.; Carati, Daniele

2000-11-01

The proper mathematical formalism for large eddy simulation (LES) of turbulent flows assumes that a regular ``explicit" filter (i.e., a filter with a well-defined second moment, such as the gaussian, the top hat, etc.) is applied to the equations of fluid motion. This filter is then responsible for a ``filtered-scale" stress. Because of the discretization of the filtered equations, using the LES grid, there is also a ``subgrid-scale" stress. The global effective stress is found to be the discretization of a filtered-scale stress plus a subgrid-scale stress. The former can be partially reconstructed from an exact, infinite, series, the first term of which is the ``tensor-diffusivity" model of Leonard and is found, in practice, to be sufficient for modeling. Alternatively, sufficient reconstruction can also be achieved using the ``scale-similarity" model of Bardina. The latter corresponds to loss of information: it cannot be reconstructed; its effect (essentially dissipation) must be modeled using ad hoc modeling strategies (such as the dynamic version of the ``effective viscosity" model of Smagorinsky). Practitionners also often assume LES without explicit filtering: the effective stress is then only a subgrid-scale stress. We here compare the performance of various LES models for both approaches (with and without explicit filtering), and for cases without solid boundaries: (1) decay of isotropic turbulence; (2) decay of aircraft wake vortices in a turbulent atmosphere. One main conclusion is that better subgrid-scale models are still needed, the effective viscosity models being too active at the large scales.

On the performance of explicit and implicit algorithms for transient thermal analysis

NASA Astrophysics Data System (ADS)

Adelman, H. M.; Haftka, R. T.

1980-09-01

The status of an effort to increase the efficiency of calculating transient temperature fields in complex aerospace vehicle structures is described. The advantages and disadvantages of explicit and implicit algorithms are discussed. A promising set of implicit algorithms, known as the GEAR package is described. Four test problems, used for evaluating and comparing various algorithms, have been selected and finite element models of the configurations are discribed. These problems include a space shuttle frame component, an insulated cylinder, a metallic panel for a thermal protection system and a model of the space shuttle orbiter wing. Calculations were carried out using the SPAR finite element program, the MITAS lumped parameter program and a special purpose finite element program incorporating the GEAR algorithms. Results generally indicate a preference for implicit over explicit algorithms for solution of transient structural heat transfer problems when the governing equations are stiff. Careful attention to modeling detail such as avoiding thin or short high-conducting elements can sometimes reduce the stiffness to the extent that explicit methods become advantageous.

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

Tsigabu Gebrehiwet; James R. Henriksen; Luanjing Guo

Multi-component mineral precipitation in porous, subsurface environments is challenging to simulate or engineer when in situ reactant mixing is controlled by diffusion. In contrast to well-mixed systems, the conditions that favor mineral precipitation in porous media are distributed along chemical gradients, which evolve spatially due to concurrent mineral precipitation and modification of solute transport in the media. The resulting physical and chemical characteristics of a mixing/precipitation zone are a consequence of coupling between transport and chemical processes, and the distinctive properties of individual chemical systems. We examined the spatial distribution of precipitates formed in “double diffusion” columns for two chemicalmore » systems, calcium carbonate and calcium phosphate. Polyacrylamide hydrogel was used as a low permeability, high porosity medium to maximize diffusive mixing and minimize pressure- and density-driven flow between reactant solutions. In the calcium phosphate system, multiple, visually dense and narrow bands of precipitates were observed that were reminiscent of previously reported Liesegang patterns. In the calcium carbonate system, wider precipitation zones characterized by more sparse distributions of precipitates and a more open channel structure were observed. In both cases, formation of precipitates inhibited, but did not necessarily eliminate, continued transport and mixing of the reactants. A reactive transport model with fully implicit coupling between diffusion, chemical speciation and precipitation kinetics, but where explicit details of nucleation processes were neglected, was able to qualitatively simulate properties of the precipitation zones. The results help to illustrate how changes in the physical properties of a precipitation zone depend on coupling between diffusion-controlled reactant mixing and chemistry-specific details of precipitation kinetics.« less

Problem formulation for risk assessment of combined exposures to chemicals and other stressors in humans.

PubMed

Solomon, Keith R; Wilks, Martin F; Bachman, Ammie; Boobis, Alan; Moretto, Angelo; Pastoor, Timothy P; Phillips, Richard; Embry, Michelle R

2016-11-01

When the human health risk assessment/risk management paradigm was developed, it did not explicitly include a "problem formulation" phase. The concept of problem formulation was first introduced in the context of ecological risk assessment (ERA) for the pragmatic reason to constrain and focus ERAs on the key questions. However, this need also exists for human health risk assessment, particularly for cumulative risk assessment (CRA), because of its complexity. CRA encompasses the combined threats to health from exposure via all relevant routes to multiple stressors, including biological, chemical, physical and psychosocial stressors. As part of the HESI Risk Assessment in the 21st Century (RISK21) Project, a framework for CRA was developed in which problem formulation plays a critical role. The focus of this effort is primarily on a chemical CRA (i.e., two or more chemicals) with subsequent consideration of non-chemical stressors, defined as "modulating factors" (ModFs). Problem formulation is a systematic approach that identifies all factors critical to a specific risk assessment and considers the purpose of the assessment, scope and depth of the necessary analysis, analytical approach, available resources and outcomes, and overall risk management goal. There are numerous considerations that are specific to multiple stressors, and proper problem formulation can help to focus a CRA to the key factors in order to optimize resources. As part of the problem formulation, conceptual models for exposures and responses can be developed that address these factors, such as temporal relationships between stressors and consideration of the appropriate ModFs.

The Importance of Explicitly Representing Soil Carbon with Depth over the Permafrost Region in Earth System Models: Implications for Atmospheric Carbon Dynamics at Multiple Temporal Scales between 1960 and 2300.

NASA Astrophysics Data System (ADS)

McGuire, A. D.

2014-12-01

We conducted an assessment of changes in permafrost area and carbon storage simulated by process-based models between 1960 and 2300. The models participating in this comparison were those that had joined the model integration team of the Vulnerability of Permafrost Carbon Research Coordination Network (see http://www.biology.ufl.edu/permafrostcarbon/). Each of the models in this comparison conducted simulations over the permafrost land region in the Northern Hemisphere driven by CCSM4-simulated climate for RCP 4.5 and 8.5 scenarios. Among the models, the area of permafrost (defined as the area for which active layer thickness was less than 3 m) ranged between 13.2 and 20.0 million km2. Between 1960 and 2300, models indicated the loss of permafrost area between 5.1 to 6.0 million km2 for RCP 4.5 and between 7.1 and 15.2 million km2 for RCP 8.5. Among the models, the density of soil carbon storage in 1960 ranged between 13 and 42 thousand g C m-2; models that explicitly represented carbon with depth had estimates greater than 27 thousand g C m-2. For the RCP 4.5 scenario, changes in soil carbon between 1960 and 2300 ranged between losses of 32 Pg C to gains of 58 Pg C, in which models that explicitly represent soil carbon with depth simulated losses or lower gains of soil carbon in comparison with those that did not. For the RCP 8.5 scenario, changes in soil carbon between 1960 and 2300 ranged between losses of 642 Pg C to gains of 66 Pg C, in which those models that represent soil carbon explicitly with depth all simulated losses, while those that do not all simulated gains. These results indicate that there are substantial differences in responses of carbon dynamics between model that do and do not explicitly represent soil carbon with depth in the permafrost region. We present analyses of the implications of the differences for atmospheric carbon dynamics at multiple temporal scales between 1960 and 2300.

Digital soil classification and elemental mapping using imaging Vis-NIR spectroscopy: How to explicitly quantify stagnic properties of a Luvisol under Norway spruce

NASA Astrophysics Data System (ADS)

Kriegs, Stefanie; Buddenbaum, Henning; Rogge, Derek; Steffens, Markus

2015-04-01

Laboratory imaging Vis-NIR spectroscopy of soil profiles is a novel technique in soil science that can determine quantity and quality of various chemical soil properties with a hitherto unreached spatial resolution in undisturbed soil profiles. We have applied this technique to soil cores in order to get quantitative proof of redoximorphic processes under two different tree species and to proof tree-soil interactions at microscale. Due to the imaging capabilities of Vis-NIR spectroscopy a spatially explicit understanding of soil processes and properties can be achieved. Spatial heterogeneity of the soil profile can be taken into account. We took six 30 cm long rectangular soil columns of adjacent Luvisols derived from quaternary aeolian sediments (Loess) in a forest soil near Freising/Bavaria using stainless steel boxes (100×100×300 mm). Three profiles were sampled under Norway spruce and three under European beech. A hyperspectral camera (VNIR, 400-1000 nm in 160 spectral bands) with spatial resolution of 63×63 µm² per pixel was used for data acquisition. Reference samples were taken at representative spots and analysed for organic carbon (OC) quantity and quality with a CN elemental analyser and for iron oxides (Fe) content using dithionite extraction followed by ICP-OES measurement. We compared two supervised classification algorithms, Spectral Angle Mapper and Maximum Likelihood, using different sets of training areas and spectral libraries. As established in chemometrics we used multivariate analysis such as partial least-squares regression (PLSR) in addition to multivariate adaptive regression splines (MARS) to correlate chemical data with Vis-NIR spectra. As a result elemental mapping of Fe and OC within the soil core at high spatial resolution has been achieved. The regression model was validated by a new set of reference samples for chemical analysis. Digital soil classification easily visualizes soil properties within the soil profiles. By combining both techniques, detailed soil maps, elemental balances and a deeper understanding of soil forming processes at the microscale become feasible for complete soil profiles.

Chemical Transport in a Fissured Rock: Verification of a Numerical Model

NASA Astrophysics Data System (ADS)

Rasmuson, A.; Narasimhan, T. N.; Neretnieks, I.

1982-10-01

Numerical models for simulating chemical transport in fissured rocks constitute powerful tools for evaluating the acceptability of geological nuclear waste repositories. Due to the very long-term, high toxicity of some nuclear waste products, the models are required to predict, in certain cases, the spatial and temporal distribution of chemical concentration less than 0.001% of the concentration released from the repository. Whether numerical models can provide such accuracies is a major question addressed in the present work. To this end we have verified a numerical model, TRUMP, which solves the advective diffusion equation in general three dimensions, with or without decay and source terms. The method is based on an integrated finite difference approach. The model was verified against known analytic solution of the one-dimensional advection-diffusion problem, as well as the problem of advection-diffusion in a system of parallel fractures separated by spherical particles. The studies show that as long as the magnitude of advectance is equal to or less than that of conductance for the closed surface bounding any volume element in the region (that is, numerical Peclet number <2), the numerical method can indeed match the analytic solution within errors of ±10-3% or less. The realistic input parameters used in the sample calculations suggest that such a range of Peclet numbers is indeed likely to characterize deep groundwater systems in granitic and ancient argillaceous systems. Thus TRUMP in its present form does provide a viable tool for use in nuclear waste evaluation studies. A sensitivity analysis based on the analytic solution suggests that the errors in prediction introduced due to uncertainties in input parameters are likely to be larger than the computational inaccuracies introduced by the numerical model. Currently, a disadvantage in the TRUMP model is that the iterative method of solving the set of simultaneous equations is rather slow when time constants vary widely over the flow region. Although the iterative solution may be very desirable for large three-dimensional problems in order to minimize computer storage, it seems desirable to use a direct solver technique in conjunction with the mixed explicit-implicit approach whenever possible. Work in this direction is in progress.

A Modeling Framework for Predicting the Size of Sediments Produced on Hillslopes and Supplied to Channels

NASA Astrophysics Data System (ADS)

Sklar, L. S.; Mahmoudi, M.

2016-12-01

Landscape evolution models rarely represent sediment size explicitly, despite the importance of sediment size in regulating rates of bedload sediment transport, river incision into bedrock, and many other processes in channels and on hillslopes. A key limitation has been the lack of a general model for predicting the size of sediments produced on hillslopes and supplied to channels. Here we present a framework for such a model, as a first step toward building a `geomorphic transport law' that balances mechanistic realism with computational simplicity and is widely applicable across diverse landscapes. The goal is to take as inputs landscape-scale boundary conditions such as lithology, climate and tectonics, and predict the spatial variation in the size distribution of sediments supplied to channels across catchments. The model framework has two components. The first predicts the initial size distribution of particles produced by erosion of bedrock underlying hillslopes, while the second accounts for the effects of physical and chemical weathering during transport down slopes and delivery to channels. The initial size distribution can be related to the spacing and orientation of fractures within bedrock, which depend on the stresses and deformation experienced during exhumation and on rock resistance to fracture propagation. Other controls on initial size include the sizes of mineral grains in crystalline rocks, the sizes of cemented particles in clastic sedimentary rocks, and the potential for characteristic size distributions produced by tree throw, frost cracking, and other erosional processes. To model how weathering processes transform the initial size distribution we consider the effects of erosion rate and the thickness of soil and weathered bedrock on hillslope residence time. Residence time determines the extent of size reduction, for given values of model terms that represent the potential for chemical and physical weathering. Chemical weathering potential is parameterized in terms of mean annual precipitation and temperature, and the fraction of soluble minerals. Physical weathering potential can be parameterized in terms of topographic attributes, including slope, curvature and aspect. Finally, we compare model predictions with field data from Inyo Creek in the Sierra Nevada Mtns, USA.

Using the PyMOL Application to Reinforce Visual Understanding of Protein Structure

ERIC Educational Resources Information Center

Rigsby, Rachel E.; Parker, Alison B.

2016-01-01

Visualization of chemical concepts can be challenging for many students. This is arguably a critical skill for beginning students of biochemistry to develop, since new information is often presented visually in the form of textbook figures. It is recommended that visual literacy be explicitly taught in the classroom rather than assuming that…

A Dual-Process Approach to the Role of Mother's Implicit and Explicit Attitudes toward Their Child in Parenting Models

ERIC Educational Resources Information Center

Sturge-Apple, Melissa L.; Rogge, Ronald D.; Skibo, Michael A.; Peltz, Jack S.; Suor, Jennifer H.

2015-01-01

Extending dual process frameworks of cognition to a novel domain, the present study examined how mothers' explicit and implicit attitudes about her child may operate in models of parenting. To assess implicit attitudes, two separate studies were conducted using the same child-focused Go/No-go Association Task (GNAT-Child). In Study 1, model…

Calabi-Yau structures on categories of matrix factorizations

NASA Astrophysics Data System (ADS)

Shklyarov, Dmytro

2017-09-01

Using tools of complex geometry, we construct explicit proper Calabi-Yau structures, that is, non-degenerate cyclic cocycles on differential graded categories of matrix factorizations of regular functions with isolated critical points. The formulas involve the Kapustin-Li trace and its higher corrections. From the physics perspective, our result yields explicit 'off-shell' models for categories of topological D-branes in B-twisted Landau-Ginzburg models.

Does Teaching Students How to Explicitly Model the Causal Structure of Systems Improve Their Understanding of These Systems?

ERIC Educational Resources Information Center

Jensen, Eva

2014-01-01

If students really understand the systems they study, they would be able to tell how changes in the system would affect a result. This demands that the students understand the mechanisms that drive its behaviour. The study investigates potential merits of learning how to explicitly model the causal structure of systems. The approach and…

An Explicit Algorithm for the Simulation of Fluid Flow through Porous Media

NASA Astrophysics Data System (ADS)

Trapeznikova, Marina; Churbanova, Natalia; Lyupa, Anastasiya

2018-02-01

The work deals with the development of an original mathematical model of porous medium flow constructed by analogy with the quasigasdynamic system of equations and allowing implementation via explicit numerical methods. The model is generalized to the case of multiphase multicomponent fluid and takes into account possible heat sources. The proposed approach is verified by a number of test predictions.

Development and Validation of Spatially Explicit Habitat Models for Cavity-nesting Birds in Fishlake National Forest, Utah

Treesearch

Randall A., Jr. Schultz; Thomas C., Jr. Edwards; Gretchen G. Moisen; Tracey S. Frescino

2005-01-01

The ability of USDA Forest Service Forest Inventory and Analysis (FIA) generated spatial products to increase the predictive accuracy of spatially explicit, macroscale habitat models was examined for nest-site selection by cavity-nesting birds in Fishlake National Forest, Utah. One FIA-derived variable (percent basal area of aspen trees) was significant in the habitat...

MOST: most-similar ligand based approach to target prediction.

PubMed

Huang, Tao; Mi, Hong; Lin, Cheng-Yuan; Zhao, Ling; Zhong, Linda L D; Liu, Feng-Bin; Zhang, Ge; Lu, Ai-Ping; Bian, Zhao-Xiang

2017-03-11

Many computational approaches have been used for target prediction, including machine learning, reverse docking, bioactivity spectra analysis, and chemical similarity searching. Recent studies have suggested that chemical similarity searching may be driven by the most-similar ligand. However, the extent of bioactivity of most-similar ligands has been oversimplified or even neglected in these studies, and this has impaired the prediction power. Here we propose the MOst-Similar ligand-based Target inference approach, namely MOST, which uses fingerprint similarity and explicit bioactivity of the most-similar ligands to predict targets of the query compound. Performance of MOST was evaluated by using combinations of different fingerprint schemes, machine learning methods, and bioactivity representations. In sevenfold cross-validation with a benchmark Ki dataset from CHEMBL release 19 containing 61,937 bioactivity data of 173 human targets, MOST achieved high average prediction accuracy (0.95 for pKi ≥ 5, and 0.87 for pKi ≥ 6). Morgan fingerprint was shown to be slightly better than FP2. Logistic Regression and Random Forest methods performed better than Naïve Bayes. In a temporal validation, the Ki dataset from CHEMBL19 were used to train models and predict the bioactivity of newly deposited ligands in CHEMBL20. MOST also performed well with high accuracy (0.90 for pKi ≥ 5, and 0.76 for pKi ≥ 6), when Logistic Regression and Morgan fingerprint were employed. Furthermore, the p values associated with explicit bioactivity were found be a robust index for removing false positive predictions. Implicit bioactivity did not offer this capability. Finally, p values generated with Logistic Regression, Morgan fingerprint and explicit activity were integrated with a false discovery rate (FDR) control procedure to reduce false positives in multiple-target prediction scenario, and the success of this strategy it was demonstrated with a case of fluanisone. In the case of aloe-emodin's laxative effect, MOST predicted that acetylcholinesterase was the mechanism-of-action target; in vivo studies validated this prediction. Using the MOST approach can result in highly accurate and robust target prediction. Integrated with a FDR control procedure, MOST provides a reliable framework for multiple-target inference. It has prospective applications in drug repurposing and mechanism-of-action target prediction.

Combining Distributed and Shared Memory Models: Approach and Evolution of the Global Arrays Toolkit

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

Nieplocha, Jarek; Harrison, Robert J.; Kumar, Mukul

2002-07-29

Both shared memory and distributed memory models have advantages and shortcomings. Shared memory model is much easier to use but it ignores data locality/placement. Given the hierarchical nature of the memory subsystems in the modern computers this characteristic might have a negative impact on performance and scalability. Various techniques, such as code restructuring to increase data reuse and introducing blocking in data accesses, can address the problem and yield performance competitive with message passing[Singh], however at the cost of compromising the ease of use feature. Distributed memory models such as message passing or one-sided communication offer performance and scalability butmore » they compromise the ease-of-use. In this context, the message-passing model is sometimes referred to as?assembly programming for the scientific computing?. The Global Arrays toolkit[GA1, GA2] attempts to offer the best features of both models. It implements a shared-memory programming model in which data locality is managed explicitly by the programmer. This management is achieved by explicit calls to functions that transfer data between a global address space (a distributed array) and local storage. In this respect, the GA model has similarities to the distributed shared-memory models that provide an explicit acquire/release protocol. However, the GA model acknowledges that remote data is slower to access than local data and allows data locality to be explicitly specified and hence managed. The GA model exposes to the programmer the hierarchical memory of modern high-performance computer systems, and by recognizing the communication overhead for remote data transfer, it promotes data reuse and locality of reference. This paper describes the characteristics of the Global Arrays programming model, capabilities of the toolkit, and discusses its evolution.« less

Sum over Histories Representation for Kinetic Sensitivity Analysis: How Chemical Pathways Change When Reaction Rate Coefficients Are Varied

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

Bai, Shirong; Davis, Michael J.; Skodje, Rex T.

2015-11-12

The sensitivity of kinetic observables is analyzed using a newly developed sum over histories representation of chemical kinetics. In the sum over histories representation, the concentrations of the chemical species are decomposed into the sum of probabilities for chemical pathways that follow molecules from reactants to products or intermediates. Unlike static flux methods for reaction path analysis, the sum over histories approach includes the explicit time dependence of the pathway probabilities. Using the sum over histories representation, the sensitivity of an observable with respect to a kinetic parameter such as a rate coefficient is then analyzed in terms of howmore » that parameter affects the chemical pathway probabilities. The method is illustrated for species concentration target functions in H-2 combustion where the rate coefficients are allowed to vary over their associated uncertainty ranges. It is found that large sensitivities are often associated with rate limiting steps along important chemical pathways or by reactions that control the branching of reactive flux« less

Parameter and uncertainty estimation for mechanistic, spatially explicit epidemiological models

NASA Astrophysics Data System (ADS)

Finger, Flavio; Schaefli, Bettina; Bertuzzo, Enrico; Mari, Lorenzo; Rinaldo, Andrea

2014-05-01

Epidemiological models can be a crucially important tool for decision-making during disease outbreaks. The range of possible applications spans from real-time forecasting and allocation of health-care resources to testing alternative intervention mechanisms such as vaccines, antibiotics or the improvement of sanitary conditions. Our spatially explicit, mechanistic models for cholera epidemics have been successfully applied to several epidemics including, the one that struck Haiti in late 2010 and is still ongoing. Calibration and parameter estimation of such models represents a major challenge because of properties unusual in traditional geoscientific domains such as hydrology. Firstly, the epidemiological data available might be subject to high uncertainties due to error-prone diagnosis as well as manual (and possibly incomplete) data collection. Secondly, long-term time-series of epidemiological data are often unavailable. Finally, the spatially explicit character of the models requires the comparison of several time-series of model outputs with their real-world counterparts, which calls for an appropriate weighting scheme. It follows that the usual assumption of a homoscedastic Gaussian error distribution, used in combination with classical calibration techniques based on Markov chain Monte Carlo algorithms, is likely to be violated, whereas the construction of an appropriate formal likelihood function seems close to impossible. Alternative calibration methods, which allow for accurate estimation of total model uncertainty, particularly regarding the envisaged use of the models for decision-making, are thus needed. Here we present the most recent developments regarding methods for parameter and uncertainty estimation to be used with our mechanistic, spatially explicit models for cholera epidemics, based on informal measures of goodness of fit.

Principle considerations for the risk assessment of sprayed consumer products.

PubMed

Steiling, W; Bascompta, M; Carthew, P; Catalano, G; Corea, N; D'Haese, A; Jackson, P; Kromidas, L; Meurice, P; Rothe, H; Singal, M

2014-05-16

In recent years, the official regulation of chemicals and chemical products has been intensified. Explicitly for spray products enhanced requirements to assess the consumers'/professionals' exposure to such product type have been introduced. In this regard the Aerosol-Dispensers-Directive (75/324/EEC) with obligation for marketing aerosol dispensers, and the Cosmetic-Products-Regulation (1223/2009/EC) which obliges the insurance of a safety assessment, have to be mentioned. Both enactments, similar to the REACH regulation (1907/2006/EC), require a robust chemical safety assessment. From such assessment, appropriate risk management measures may be identified to adequately control the risk of these chemicals/products to human health and the environment when used. Currently, the above-mentioned regulations lack the guidance on which data are needed for preparing a proper hazard analysis and safety assessment of spray products. Mandatory in the process of inhalation risk and safety assessment is the determination and quantification of the actual exposure to the spray product and more specifically, its ingredients. In this respect the current article, prepared by the European Aerosol Federation (FEA, Brussels) task force "Inhalation Toxicology", intends to introduce toxicological principles and the state of the art in currently available exposure models adapted for typical application scenarios. This review on current methodologies is intended to guide safety assessors to better estimate inhalation exposure by using the most relevant data. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Parameterization of Highly Charged Metal Ions Using the 12-6-4 LJ-Type Nonbonded Model in Explicit Water

PubMed Central

2015-01-01

Highly charged metal ions act as catalytic centers and structural elements in a broad range of chemical complexes. The nonbonded model for metal ions is extensively used in molecular simulations due to its simple form, computational speed, and transferability. We have proposed and parametrized a 12-6-4 LJ (Lennard-Jones)-type nonbonded model for divalent metal ions in previous work, which showed a marked improvement over the 12-6 LJ nonbonded model. In the present study, by treating the experimental hydration free energies and ion–oxygen distances of the first solvation shell as targets for our parametrization, we evaluated 12-6 LJ parameters for 18 M(III) and 6 M(IV) metal ions for three widely used water models (TIP3P, SPC/E, and TIP4PEW). As expected, the interaction energy underestimation of the 12-6 LJ nonbonded model increases dramatically for the highly charged metal ions. We then parametrized the 12-6-4 LJ-type nonbonded model for these metal ions with the three water models. The final parameters reproduced the target values with good accuracy, which is consistent with our previous experience using this potential. Finally, tests were performed on a protein system, and the obtained results validate the transferability of these nonbonded model parameters. PMID:25145273

Rigorous evaluation of chemical measurement uncertainty: liquid chromatographic analysis methods using detector response factor calibration

NASA Astrophysics Data System (ADS)

Toman, Blaza; Nelson, Michael A.; Bedner, Mary

2017-06-01

Chemical measurement methods are designed to promote accurate knowledge of a measurand or system. As such, these methods often allow elicitation of latent sources of variability and correlation in experimental data. They typically implement measurement equations that support quantification of effects associated with calibration standards and other known or observed parametric variables. Additionally, multiple samples and calibrants are usually analyzed to assess accuracy of the measurement procedure and repeatability by the analyst. Thus, a realistic assessment of uncertainty for most chemical measurement methods is not purely bottom-up (based on the measurement equation) or top-down (based on the experimental design), but inherently contains elements of both. Confidence in results must be rigorously evaluated for the sources of variability in all of the bottom-up and top-down elements. This type of analysis presents unique challenges due to various statistical correlations among the outputs of measurement equations. One approach is to use a Bayesian hierarchical (BH) model which is intrinsically rigorous, thus making it a straightforward method for use with complex experimental designs, particularly when correlations among data are numerous and difficult to elucidate or explicitly quantify. In simpler cases, careful analysis using GUM Supplement 1 (MC) methods augmented with random effects meta analysis yields similar results to a full BH model analysis. In this article we describe both approaches to rigorous uncertainty evaluation using as examples measurements of 25-hydroxyvitamin D3 in solution reference materials via liquid chromatography with UV absorbance detection (LC-UV) and liquid chromatography mass spectrometric detection using isotope dilution (LC-IDMS).

Non-covalent interactions across organic and biological subsets of chemical space: Physics-based potentials parametrized from machine learning

NASA Astrophysics Data System (ADS)

Bereau, Tristan; DiStasio, Robert A.; Tkatchenko, Alexandre; von Lilienfeld, O. Anatole

2018-06-01

Classical intermolecular potentials typically require an extensive parametrization procedure for any new compound considered. To do away with prior parametrization, we propose a combination of physics-based potentials with machine learning (ML), coined IPML, which is transferable across small neutral organic and biologically relevant molecules. ML models provide on-the-fly predictions for environment-dependent local atomic properties: electrostatic multipole coefficients (significant error reduction compared to previously reported), the population and decay rate of valence atomic densities, and polarizabilities across conformations and chemical compositions of H, C, N, and O atoms. These parameters enable accurate calculations of intermolecular contributions—electrostatics, charge penetration, repulsion, induction/polarization, and many-body dispersion. Unlike other potentials, this model is transferable in its ability to handle new molecules and conformations without explicit prior parametrization: All local atomic properties are predicted from ML, leaving only eight global parameters—optimized once and for all across compounds. We validate IPML on various gas-phase dimers at and away from equilibrium separation, where we obtain mean absolute errors between 0.4 and 0.7 kcal/mol for several chemically and conformationally diverse datasets representative of non-covalent interactions in biologically relevant molecules. We further focus on hydrogen-bonded complexes—essential but challenging due to their directional nature—where datasets of DNA base pairs and amino acids yield an extremely encouraging 1.4 kcal/mol error. Finally, and as a first look, we consider IPML for denser systems: water clusters, supramolecular host-guest complexes, and the benzene crystal.

Methods used to parameterize the spatially-explicit components of a state-and-transition simulation model

USGS Publications Warehouse

Sleeter, Rachel; Acevedo, William; Soulard, Christopher E.; Sleeter, Benjamin M.

2015-01-01

Spatially-explicit state-and-transition simulation models of land use and land cover (LULC) increase our ability to assess regional landscape characteristics and associated carbon dynamics across multiple scenarios. By characterizing appropriate spatial attributes such as forest age and land-use distribution, a state-and-transition model can more effectively simulate the pattern and spread of LULC changes. This manuscript describes the methods and input parameters of the Land Use and Carbon Scenario Simulator (LUCAS), a customized state-and-transition simulation model utilized to assess the relative impacts of LULC on carbon stocks for the conterminous U.S. The methods and input parameters are spatially explicit and describe initial conditions (strata, state classes and forest age), spatial multipliers, and carbon stock density. Initial conditions were derived from harmonization of multi-temporal data characterizing changes in land use as well as land cover. Harmonization combines numerous national-level datasets through a cell-based data fusion process to generate maps of primary LULC categories. Forest age was parameterized using data from the North American Carbon Program and spatially-explicit maps showing the locations of past disturbances (i.e. wildfire and harvest). Spatial multipliers were developed to spatially constrain the location of future LULC transitions. Based on distance-decay theory, maps were generated to guide the placement of changes related to forest harvest, agricultural intensification/extensification, and urbanization. We analyze the spatially-explicit input parameters with a sensitivity analysis, by showing how LUCAS responds to variations in the model input. This manuscript uses Mediterranean California as a regional subset to highlight local to regional aspects of land change, which demonstrates the utility of LUCAS at many scales and applications.

Corruption of accuracy and efficiency of Markov chain Monte Carlo simulation by inaccurate numerical implementation of conceptual hydrologic models

NASA Astrophysics Data System (ADS)

Schoups, G.; Vrugt, J. A.; Fenicia, F.; van de Giesen, N. C.

2010-10-01

Conceptual rainfall-runoff models have traditionally been applied without paying much attention to numerical errors induced by temporal integration of water balance dynamics. Reliance on first-order, explicit, fixed-step integration methods leads to computationally cheap simulation models that are easy to implement. Computational speed is especially desirable for estimating parameter and predictive uncertainty using Markov chain Monte Carlo (MCMC) methods. Confirming earlier work of Kavetski et al. (2003), we show here that the computational speed of first-order, explicit, fixed-step integration methods comes at a cost: for a case study with a spatially lumped conceptual rainfall-runoff model, it introduces artificial bimodality in the marginal posterior parameter distributions, which is not present in numerically accurate implementations of the same model. The resulting effects on MCMC simulation include (1) inconsistent estimates of posterior parameter and predictive distributions, (2) poor performance and slow convergence of the MCMC algorithm, and (3) unreliable convergence diagnosis using the Gelman-Rubin statistic. We studied several alternative numerical implementations to remedy these problems, including various adaptive-step finite difference schemes and an operator splitting method. Our results show that adaptive-step, second-order methods, based on either explicit finite differencing or operator splitting with analytical integration, provide the best alternative for accurate and efficient MCMC simulation. Fixed-step or adaptive-step implicit methods may also be used for increased accuracy, but they cannot match the efficiency of adaptive-step explicit finite differencing or operator splitting. Of the latter two, explicit finite differencing is more generally applicable and is preferred if the individual hydrologic flux laws cannot be integrated analytically, as the splitting method then loses its advantage.

Explicit Instruction Elements in Core Reading Programs

ERIC Educational Resources Information Center

Child, Angela R.

2012-01-01

Classroom teachers are provided instructional recommendations for teaching reading from their adopted core reading programs (CRPs). Explicit instruction elements or what is also called instructional moves, including direct explanation, modeling, guided practice, independent practice, discussion, feedback, and monitoring, were examined within CRP…

Late positive potential to explicit sexual images associated with the number of sexual intercourse partners

PubMed Central

Steele, Vaughn R.; Staley, Cameron; Sabatinelli, Dean

2015-01-01

Risky sexual behaviors typically occur when a person is sexually motivated by potent, sexual reward cues. Yet, individual differences in sensitivity to sexual cues have not been examined with respect to sexual risk behaviors. A greater responsiveness to sexual cues might provide greater motivation for a person to act sexually; a lower responsiveness to sexual cues might lead a person to seek more intense, novel, possibly risky, sexual acts. In this study, event-related potentials were recorded in 64 men and women while they viewed a series of emotional, including explicit sexual, photographs. The motivational salience of the sexual cues was varied by including more and less explicit sexual images. Indeed, the more explicit sexual stimuli resulted in enhanced late positive potentials (LPP) relative to the less explicit sexual images. Participants with fewer sexual intercourse partners in the last year had reduced LPP amplitude to the less explicit sexual images than the more explicit sexual images, whereas participants with more partners responded similarly to the more and less explicit sexual images. This pattern of results is consistent with a greater responsivity model. Those who engage in more sexual behaviors consistent with risk are also more responsive to less explicit sexual cues. PMID:24526189

Assessment of implicit health attitudes: a multitrait-multimethod approach and a comparison between patients with hypochondriasis and patients with anxiety disorders.

PubMed

Weck, Florian; Höfling, Volkmar

2015-01-01

Two adaptations of the Implicit Association Task were used to assess implicit anxiety (IAT-Anxiety) and implicit health attitudes (IAT-Hypochondriasis) in patients with hypochondriasis (n = 58) and anxiety patients (n = 71). Explicit anxieties and health attitudes were assessed using questionnaires. The analysis of several multitrait-multimethod models indicated that the low correlation between explicit and implicit measures of health attitudes is due to the substantial methodological differences between the IAT and the self-report questionnaire. Patients with hypochondriasis displayed significantly more dysfunctional explicit and implicit health attitudes than anxiety patients, but no differences were found regarding explicit and implicit anxieties. The study demonstrates the specificity of explicit and implicit dysfunctional health attitudes among patients with hypochondriasis.

A Combined Kinetic and Volatility Basis Set Approach to Model Secondary Organic Aerosol from Toluene and Diesel Exhaust/Meat Cooking Mixtures

NASA Astrophysics Data System (ADS)

Parikh, H. M.; Carlton, A. G.; Zhang, H.; Kamens, R.; Vizuete, W.

2011-12-01

Secondary organic aerosol (SOA) is simulated for 6 outdoor smog chamber experiments using a SOA model based on a kinetic chemical mechanism in conjunction with a volatility basis set (VBS) approach. The experiments include toluene, a non-SOA-forming hydrocarbon mixture, diesel exhaust or meat cooking emissions and NOx, and are performed under varying conditions of relative humidity. SOA formation from toluene is modeled using a condensed kinetic aromatic mechanism that includes partitioning of lumped semi-volatile products in particle organic-phase and incorporates particle aqueous-phase chemistry to describe uptake of glyoxal and methylglyoxal. Modeling using the kinetic mechanism alone, along with primary organic aerosol (POA) from diesel exhaust (DE) /meat cooking (MC) fails to simulate the rapid SOA formation at the beginning hours of the experiments. Inclusion of a VBS approach with the kinetic mechanism to characterize the emissions and chemistry of complex mixture of intermediate volatility organic compounds (IVOCs) from DE/MC, substantially improves SOA predictions when compared with observed data. The VBS model includes photochemical aging of IVOCs and evaporation of POA after dilution. The relative contribution of SOA mass from DE/MC is as high as 95% in the morning, but substantially decreases after mid-afternoon. For high humidity experiments, aqueous-phase SOA fraction dominates the total SOA mass at the end of the day (approximately 50%). In summary, the combined kinetic and VBS approach provides a new and improved framework to semi-explicitly model SOA from VOC precursors in conjunction with a VBS approach that can be used on complex emission mixtures comprised with hundreds of individual chemical species.

Generalized background error covariance matrix model (GEN_BE v2.0)

NASA Astrophysics Data System (ADS)

Descombes, G.; Auligné, T.; Vandenberghe, F.; Barker, D. M.; Barré, J.

2015-03-01

The specification of state background error statistics is a key component of data assimilation since it affects the impact observations will have on the analysis. In the variational data assimilation approach, applied in geophysical sciences, the dimensions of the background error covariance matrix (B) are usually too large to be explicitly determined and B needs to be modeled. Recent efforts to include new variables in the analysis such as cloud parameters and chemical species have required the development of the code to GENerate the Background Errors (GEN_BE) version 2.0 for the Weather Research and Forecasting (WRF) community model. GEN_BE allows for a simpler, flexible, robust, and community-oriented framework that gathers methods used by some meteorological operational centers and researchers. We present the advantages of this new design for the data assimilation community by performing benchmarks of different modeling of B and showing some of the new features in data assimilation test cases. As data assimilation for clouds remains a challenge, we present a multivariate approach that includes hydrometeors in the control variables and new correlated errors. In addition, the GEN_BE v2.0 code is employed to diagnose error parameter statistics for chemical species, which shows that it is a tool flexible enough to implement new control variables. While the generation of the background errors statistics code was first developed for atmospheric research, the new version (GEN_BE v2.0) can be easily applied to other domains of science and chosen to diagnose and model B. Initially developed for variational data assimilation, the model of the B matrix may be useful for variational ensemble hybrid methods as well.

Effect of fuel concentration on cargo transport by a team of Kinesin motors

NASA Astrophysics Data System (ADS)

Takshak, Anjneya; Mishra, Nirvantosh; Kulkarni, Aditi; Kunwar, Ambarish

2017-02-01

Eukaryotic cells employ specialized proteins called molecular motors for transporting organelles and vesicles from one location to another in a regulated and directed manner. These molecular motors often work collectively in a team while transporting cargos. Molecular motors use cytoplasmic ATP as fuel, which is hydrolyzed to generate mechanical force. While the effect of ATP concentration on cargo transport by single Kinesin motor function is well understood, it is still unexplored, both theoretically and experimentally, how ATP concentration would affect cargo transport by a team of Kinesin motors. For instance, how does fuel concentration affect the travel distances and travel velocities of cargo? How cooperativity of Kinesin motors engaged on a cargo is affected by ATP concentration? To answer these questions, here we develop mechano-chemical models of cargo transport by a team of Kinesin motors. To develop these models we use experimentally-constrained mechano-chemical model of a single Kinesin motor as well as earlier developed mean-field and stochastic models of load sharing for cargo transport. Thus, our new models for cargo transport by a team of Kinesin motors include fuel concentration explicitly, which was not considered in earlier models. We make several interesting predictions which can be tested experimentally. For instance, the travel distances of cargos are very large at limited ATP concentrations in spite of very small travel velocity. Velocities of cargos driven by multiple Kinesin have a Michaelis-Menten dependence on ATP concentration. Similarly, cooperativity among the engaged Kinesin motors on the cargo shows a Michaelis-Menten type dependence, which attains a maximum value near physiological ATP concentrations. Our new results can be potentially useful in controlling artificial nano-molecular shuttles precisely for targeted delivery in various nano-technological applications.

Free energy landscape of protein folding in water: explicit vs. implicit solvent.

PubMed

Zhou, Ruhong

2003-11-01

The Generalized Born (GB) continuum solvent model is arguably the most widely used implicit solvent model in protein folding and protein structure prediction simulations; however, it still remains an open question on how well the model behaves in these large-scale simulations. The current study uses the beta-hairpin from C-terminus of protein G as an example to explore the folding free energy landscape with various GB models, and the results are compared to the explicit solvent simulations and experiments. All free energy landscapes are obtained from extensive conformation space sampling with a highly parallel replica exchange method. Because solvation model parameters are strongly coupled with force fields, five different force field/solvation model combinations are examined and compared in this study, namely the explicit solvent model: OPLSAA/SPC model, and the implicit solvent models: OPLSAA/SGB (Surface GB), AMBER94/GBSA (GB with Solvent Accessible Surface Area), AMBER96/GBSA, and AMBER99/GBSA. Surprisingly, we find that the free energy landscapes from implicit solvent models are quite different from that of the explicit solvent model. Except for AMBER96/GBSA, all other implicit solvent models find the lowest free energy state not the native state. All implicit solvent models show erroneous salt-bridge effects between charged residues, particularly in OPLSAA/SGB model, where the overly strong salt-bridge effect results in an overweighting of a non-native structure with one hydrophobic residue F52 expelled from the hydrophobic core in order to make better salt bridges. On the other hand, both AMBER94/GBSA and AMBER99/GBSA models turn the beta-hairpin in to an alpha-helix, and the alpha-helical content is much higher than the previously reported alpha-helices in an explicit solvent simulation with AMBER94 (AMBER94/TIP3P). Only AMBER96/GBSA shows a reasonable free energy landscape with the lowest free energy structure the native one despite an erroneous salt-bridge between D47 and K50. Detailed results on free energy contour maps, lowest free energy structures, distribution of native contacts, alpha-helical content during the folding process, NOE comparison with NMR, and temperature dependences are reported and discussed for all five models. Copyright 2003 Wiley-Liss, Inc.

Reduced product yield in chemical processes by second law effects

NASA Technical Reports Server (NTRS)

England, C.; Funk, J. E.

1980-01-01

An analysis of second law effects in chemical processes, where product yield is explicitly related to the individual irreversibilities within the process to indicate a maximum theoretical yield, is presented. Examples are given that indicate differences between first and second law approaches toward process efficiency and process yield. This analysis also expresses production capacity in terms of the heating value of a product. As a result, it is particularly convenient in analyzing fuel conversion plants and their potential for improvement. Relationships are also given for the effects of irreversibilities on requirements for process heat and for feedstocks.

Microphysics-based black carbon aging in a global CTM: constraints from HIPPO observations and implications for global black carbon budget

NASA Astrophysics Data System (ADS)

He, Cenlin; Li, Qinbin; Liou, Kuo-Nan; Qi, Ling; Tao, Shu; Schwarz, Joshua P.

2016-03-01

We develop and examine a microphysics-based black carbon (BC) aerosol aging scheme that accounts for condensation, coagulation, and heterogeneous chemical oxidation processes in a global 3-D chemical transport model (GEOS-Chem) by interpreting the BC measurements from the HIAPER Pole-to-Pole Observations (HIPPO, 2009-2011) using the model. We convert aerosol mass in the model to number concentration by assuming lognormal aerosol size distributions and compute the microphysical BC aging rate (excluding chemical oxidation aging) explicitly from the condensation of soluble materials onto hydrophobic BC and the coagulation between hydrophobic BC and preexisting soluble particles. The chemical oxidation aging is tested in the sensitivity simulation. The microphysical aging rate is ˜ 4 times higher in the lower troposphere over source regions than that from a fixed aging scheme with an e-folding time of 1.2 days. The higher aging rate reflects the large emissions of sulfate-nitrate and secondary organic aerosol precursors hence faster BC aging through condensation and coagulation. In contrast, the microphysical aging is more than 5-fold slower than the fixed aging in remote regions, where condensation and coagulation are weak. Globally, BC microphysical aging is dominated by condensation, while coagulation contribution is largest over eastern China, India, and central Africa. The fixed aging scheme results in an overestimate of HIPPO BC throughout the troposphere by a factor of 6 on average. The microphysical scheme reduces this discrepancy by a factor of ˜ 3, particularly in the middle and upper troposphere. It also leads to a 3-fold reduction in model bias in the latitudinal BC column burden averaged along the HIPPO flight tracks, with largest improvements in the tropics. The resulting global annual mean BC lifetime is 4.2 days and BC burden is 0.25 mg m-2, with 7.3 % of the burden at high altitudes (above 5 km). Wet scavenging accounts for 80.3 % of global BC deposition. We find that, in source regions, the microphysical aging rate is insensitive to aerosol size distribution, condensation threshold, and chemical oxidation aging, while it is the opposite in remote regions, where the aging rate is orders of magnitude smaller. As a result, global BC burden and lifetime show little sensitivity (< 5 % change) to these three factors.

Modeling biochemical transformation processes and information processing with Narrator.

PubMed

Mandel, Johannes J; Fuss, Hendrik; Palfreyman, Niall M; Dubitzky, Werner

2007-03-27

Software tools that model and simulate the dynamics of biological processes and systems are becoming increasingly important. Some of these tools offer sophisticated graphical user interfaces (GUIs), which greatly enhance their acceptance by users. Such GUIs are based on symbolic or graphical notations used to describe, interact and communicate the developed models. Typically, these graphical notations are geared towards conventional biochemical pathway diagrams. They permit the user to represent the transport and transformation of chemical species and to define inhibitory and stimulatory dependencies. A critical weakness of existing tools is their lack of supporting an integrative representation of transport, transformation as well as biological information processing. Narrator is a software tool facilitating the development and simulation of biological systems as Co-dependence models. The Co-dependence Methodology complements the representation of species transport and transformation together with an explicit mechanism to express biological information processing. Thus, Co-dependence models explicitly capture, for instance, signal processing structures and the influence of exogenous factors or events affecting certain parts of a biological system or process. This combined set of features provides the system biologist with a powerful tool to describe and explore the dynamics of life phenomena. Narrator's GUI is based on an expressive graphical notation which forms an integral part of the Co-dependence Methodology. Behind the user-friendly GUI, Narrator hides a flexible feature which makes it relatively easy to map models defined via the graphical notation to mathematical formalisms and languages such as ordinary differential equations, the Systems Biology Markup Language or Gillespie's direct method. This powerful feature facilitates reuse, interoperability and conceptual model development. Narrator is a flexible and intuitive systems biology tool. It is specifically intended for users aiming to construct and simulate dynamic models of biology without recourse to extensive mathematical detail. Its design facilitates mappings to different formal languages and frameworks. The combined set of features makes Narrator unique among tools of its kind. Narrator is implemented as Java software program and available as open-source from http://www.narrator-tool.org.

Modeling biochemical transformation processes and information processing with Narrator

PubMed Central

Mandel, Johannes J; Fuß, Hendrik; Palfreyman, Niall M; Dubitzky, Werner

2007-01-01

Background Software tools that model and simulate the dynamics of biological processes and systems are becoming increasingly important. Some of these tools offer sophisticated graphical user interfaces (GUIs), which greatly enhance their acceptance by users. Such GUIs are based on symbolic or graphical notations used to describe, interact and communicate the developed models. Typically, these graphical notations are geared towards conventional biochemical pathway diagrams. They permit the user to represent the transport and transformation of chemical species and to define inhibitory and stimulatory dependencies. A critical weakness of existing tools is their lack of supporting an integrative representation of transport, transformation as well as biological information processing. Results Narrator is a software tool facilitating the development and simulation of biological systems as Co-dependence models. The Co-dependence Methodology complements the representation of species transport and transformation together with an explicit mechanism to express biological information processing. Thus, Co-dependence models explicitly capture, for instance, signal processing structures and the influence of exogenous factors or events affecting certain parts of a biological system or process. This combined set of features provides the system biologist with a powerful tool to describe and explore the dynamics of life phenomena. Narrator's GUI is based on an expressive graphical notation which forms an integral part of the Co-dependence Methodology. Behind the user-friendly GUI, Narrator hides a flexible feature which makes it relatively easy to map models defined via the graphical notation to mathematical formalisms and languages such as ordinary differential equations, the Systems Biology Markup Language or Gillespie's direct method. This powerful feature facilitates reuse, interoperability and conceptual model development. Conclusion Narrator is a flexible and intuitive systems biology tool. It is specifically intended for users aiming to construct and simulate dynamic models of biology without recourse to extensive mathematical detail. Its design facilitates mappings to different formal languages and frameworks. The combined set of features makes Narrator unique among tools of its kind. Narrator is implemented as Java software program and available as open-source from . PMID:17389034

Accounting for the Decreasing Reaction Potential of Heterogeneous Aquifers in a Stochastic Framework of Aquifer-Scale Reactive Transport

NASA Astrophysics Data System (ADS)

Loschko, Matthias; Wöhling, Thomas; Rudolph, David L.; Cirpka, Olaf A.

2018-01-01

Many groundwater contaminants react with components of the aquifer matrix, causing a depletion of the aquifer's reactivity with time. We discuss conceptual simplifications of reactive transport that allow the implementation of a decreasing reaction potential in reactive-transport simulations in chemically and hydraulically heterogeneous aquifers without relying on a fully explicit description. We replace spatial coordinates by travel-times and use the concept of relative reactivity, which represents the reaction-partner supply from the matrix relative to a reference. Microorganisms facilitating the reactions are not explicitly modeled. Solute mixing is neglected. Streamlines, obtained by particle tracking, are discretized in travel-time increments with variable content of reaction partners in the matrix. As exemplary reactive system, we consider aerobic respiration and denitrification with simplified reaction equations: Dissolved oxygen undergoes conditional zero-order decay, nitrate follows first-order decay, which is inhibited in the presence of dissolved oxygen. Both reactions deplete the bioavailable organic carbon of the matrix, which in turn determines the relative reactivity. These simplifications reduce the computational effort, facilitating stochastic simulations of reactive transport on the aquifer scale. In a one-dimensional test case with a more detailed description of the reactions, we derive a potential relationship between the bioavailable organic-carbon content and the relative reactivity. In a three-dimensional steady-state test case, we use the simplified model to calculate the decreasing denitrification potential of an artificial aquifer over 200 years in an ensemble of 200 members. We demonstrate that the uncertainty in predicting the nitrate breakthrough in a heterogeneous aquifer decreases with increasing scale of observation.

Explicit and implicit springback simulation in sheet metal forming using fully coupled ductile damage and distortional hardening model

NASA Astrophysics Data System (ADS)

Yetna n'jock, M.; Houssem, B.; Labergere, C.; Saanouni, K.; Zhenming, Y.

2018-05-01

The springback is an important phenomenon which accompanies the forming of metallic sheets especially for high strength materials. A quantitative prediction of springback becomes very important for newly developed material with high mechanical characteristics. In this work, a numerical methodology is developed to quantify this undesirable phenomenon. This methodoly is based on the use of both explicit and implicit finite element solvers of Abaqus®. The most important ingredient of this methodology consists on the use of highly predictive mechanical model. A thermodynamically-consistent, non-associative and fully anisotropic elastoplastic constitutive model strongly coupled with isotropic ductile damage and accounting for distortional hardening is then used. An algorithm for local integration of the complete set of the constitutive equations is developed. This algorithm considers the rotated frame formulation (RFF) to ensure the incremental objectivity of the model in the framework of finite strains. This algorithm is implemented in both explicit (Abaqus/Explicit®) and implicit (Abaqus/Standard®) solvers of Abaqus® through the users routine VUMAT and UMAT respectively. The implicit solver of Abaqus® has been used to study spingback as it is generally a quasi-static unloading. In order to compare the methods `efficiency, the explicit method (Dynamic Relaxation Method) proposed by Rayleigh has been also used for springback prediction. The results obtained within U draw/bending benchmark are studied, discussed and compared with experimental results as reference. Finally, the purpose of this work is to evaluate the reliability of different methods predict efficiently springback in sheet metal forming.

Free energy landscapes of small peptides in an implicit solvent model determined by force-biased multicanonical molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Watanabe, Yukihisa S.; Kim, Jae Gil; Fukunishi, Yoshifumi; Nakamura, Haruki

2004-12-01

In order to investigate whether the implicit solvent (GB/SA) model could reproduce the free energy landscapes of peptides, the potential of mean forces (PMFs) of eight tripeptides was examined and compared with the PMFs of the explicit water model. The force-biased multicanonical molecular dynamics method was used for the enhanced conformational sampling. Consequently, the GB/SA model reproduced almost all the global and local minima in the PMFs observed with the explicit water model. However, the GB/SA model overestimated frequencies of the structures that are stabilized by intra-peptide hydrogen bonds.

Fragment virtual screening based on Bayesian categorization for discovering novel VEGFR-2 scaffolds.

PubMed

Zhang, Yanmin; Jiao, Yu; Xiong, Xiao; Liu, Haichun; Ran, Ting; Xu, Jinxing; Lu, Shuai; Xu, Anyang; Pan, Jing; Qiao, Xin; Shi, Zhihao; Lu, Tao; Chen, Yadong

2015-11-01

The discovery of novel scaffolds against a specific target has long been one of the most significant but challengeable goals in discovering lead compounds. A scaffold that binds in important regions of the active pocket is more favorable as a starting point because scaffolds generally possess greater optimization possibilities. However, due to the lack of sufficient chemical space diversity of the databases and the ineffectiveness of the screening methods, it still remains a great challenge to discover novel active scaffolds. Since the strengths and weaknesses of both fragment-based drug design and traditional virtual screening (VS), we proposed a fragment VS concept based on Bayesian categorization for the discovery of novel scaffolds. This work investigated the proposal through an application on VEGFR-2 target. Firstly, scaffold and structural diversity of chemical space for 10 compound databases were explicitly evaluated. Simultaneously, a robust Bayesian classification model was constructed for screening not only compound databases but also their corresponding fragment databases. Although analysis of the scaffold diversity demonstrated a very unevenly distribution of scaffolds over molecules, results showed that our Bayesian model behaved better in screening fragments than molecules. Through a literature retrospective research, several generated fragments with relatively high Bayesian scores indeed exhibit VEGFR-2 biological activity, which strongly proved the effectiveness of fragment VS based on Bayesian categorization models. This investigation of Bayesian-based fragment VS can further emphasize the necessity for enrichment of compound databases employed in lead discovery by amplifying the diversity of databases with novel structures.

A neurocomputational theory of how explicit learning bootstraps early procedural learning.

PubMed

Paul, Erick J; Ashby, F Gregory

2013-01-01

It is widely accepted that human learning and memory is mediated by multiple memory systems that are each best suited to different requirements and demands. Within the domain of categorization, at least two systems are thought to facilitate learning: an explicit (declarative) system depending largely on the prefrontal cortex, and a procedural (non-declarative) system depending on the basal ganglia. Substantial evidence suggests that each system is optimally suited to learn particular categorization tasks. However, it remains unknown precisely how these systems interact to produce optimal learning and behavior. In order to investigate this issue, the present research evaluated the progression of learning through simulation of categorization tasks using COVIS, a well-known model of human category learning that includes both explicit and procedural learning systems. Specifically, the model's parameter space was thoroughly explored in procedurally learned categorization tasks across a variety of conditions and architectures to identify plausible interaction architectures. The simulation results support the hypothesis that one-way interaction between the systems occurs such that the explicit system "bootstraps" learning early on in the procedural system. Thus, the procedural system initially learns a suboptimal strategy employed by the explicit system and later refines its strategy. This bootstrapping could be from cortical-striatal projections that originate in premotor or motor regions of cortex, or possibly by the explicit system's control of motor responses through basal ganglia-mediated loops.

Designing Anticancer Peptides by Constructive Machine Learning.

PubMed

Grisoni, Francesca; Neuhaus, Claudia S; Gabernet, Gisela; Müller, Alex T; Hiss, Jan A; Schneider, Gisbert

2018-04-21

Constructive (generative) machine learning enables the automated generation of novel chemical structures without the need for explicit molecular design rules. This study presents the experimental application of such a deep machine learning model to design membranolytic anticancer peptides (ACPs) de novo. A recurrent neural network with long short-term memory cells was trained on α-helical cationic amphipathic peptide sequences and then fine-tuned with 26 known ACPs by transfer learning. This optimized model was used to generate unique and novel amino acid sequences. Twelve of the peptides were synthesized and tested for their activity on MCF7 human breast adenocarcinoma cells and selectivity against human erythrocytes. Ten of these peptides were active against cancer cells. Six of the active peptides killed MCF7 cancer cells without affecting human erythrocytes with at least threefold selectivity. These results advocate constructive machine learning for the automated design of peptides with desired biological activities. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

A new numerical model of the middle atmosphere. I - Dynamics and transport of tropospheric source gases

NASA Technical Reports Server (NTRS)

Garcia, Rolando R.; Stordal, Frode; Solomon, Susan; Kiehl, Jeffrey T.

1992-01-01

Attention is given to a new model of the middle atmosphere which includes, in addition to the equations governing the zonal mean state, a potential vorticity equation for a single planetary-scale Rossby wave, and an IR radiative transfer code for the stratosphere and lower mesosphere, which replaces the Newtonian cooling parameterization used previously. It is shown that explicit computation of the planetary-scale wave field yields a more realistic representation of the zonal mean dynamics and the distribution of trace chemical species. Wave breaking produces a well-mixed 'surf zone' equatorward of the polar night vortex and drives a meridional circulation with downwelling on the poleward side of the vortex. This combination of mixing and downwelling produces shallow meridional gradients of trace gases in the subtropics and middle latitudes, and very steep gradients at the edge of the polar vortex. Computed distributions of methane and nitrous oxide are shown to agree well with observations.

A watershed-based spatially-explicit demonstration of an integrated environmental modeling framework for ecosystem services in the Coal River Basin (WV, USA)

Treesearch

John M. Johnston; Mahion C. Barber; Kurt Wolfe; Mike Galvin; Mike Cyterski; Rajbir Parmar; Luis Suarez

2016-01-01

We demonstrate a spatially-explicit regional assessment of current condition of aquatic ecoservices in the Coal River Basin (CRB), with limited sensitivity analysis for the atmospheric contaminant mercury. The integrated modeling framework (IMF) forecasts water quality and quantity, habitat suitability for aquatic biota, fish biomasses, population densities, ...

Finite Element Modeling of Coupled Flexible Multibody Dynamics and Liquid Sloshing

DTIC Science & Technology

2006-09-01

tanks is presented. The semi-discrete combined solid and fluid equations of motions are integrated using a time- accurate parallel explicit solver...Incompressible fluid flow in a moving/deforming container including accurate modeling of the free-surface, turbulence, and viscous effects ...paper, a single computational code which uses a time- accurate explicit solution procedure is used to solve both the solid and fluid equations of

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

DOE PAGES

Broddrick, Jared T.; Rubin, Benjamin E.; Welkie, David G.; ...

2016-12-20

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. In this paper, 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 inmore » 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. Finally, 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.« less

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

PubMed Central

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

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

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

Broddrick, Jared T.; Rubin, Benjamin E.; Welkie, David G.

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. In this paper, 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 inmore » 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. Finally, 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.« less

Integrated carbon and chlorine isotope modeling: applications to chlorinated aliphatic hydrocarbons dechlorination.

PubMed

Jin, Biao; Haderlein, Stefan B; Rolle, Massimo

2013-02-05

We propose a self-consistent method to predict the evolution of carbon and chlorine isotope ratios during degradation of chlorinated hydrocarbons. The method treats explicitly the cleavage of isotopically different C-Cl bonds and thus considers, simultaneously, combined carbon-chlorine isotopologues. To illustrate the proposed modeling approach we focus on the reductive dehalogenation of chlorinated ethenes. We compare our method with the currently available approach, in which carbon and chlorine isotopologues are treated separately. The new approach provides an accurate description of dual-isotope effects regardless of the extent of the isotope fractionation and physical characteristics of the experimental system. We successfully applied the new approach to published experimental results on dehalogenation of chlorinated ethenes both in well-mixed systems and in situations where mass-transfer limitations control the overall rate of biodegradation. The advantages of our self-consistent dual isotope modeling approach proved to be most evident when isotope fractionation factors of carbon and chlorine differed significantly and for systems with mass-transfer limitations, where both physical and (bio)chemical transformation processes affect the observed isotopic values.

Resilience landscapes for Congo basin rainforests vs. climate and management impacts

NASA Astrophysics Data System (ADS)

Pietsch, Stephan Alexander; Gautam, Sishir; Elias Bednar, Johannes; Stanzl, Patrick; Mosnier, Aline; Obersteiner, Michael

2015-04-01

Past climate change caused severe disturbances of the Central African rainforest belt, with forest fragmentation and re-expansion due to drier and wetter climate conditions. Besides climate, human induced forest degradation affected biodiversity, structure and carbon storage of Congo basin rainforests. Information on climatically stable, mature rainforest, unaffected by human induced disturbances, provides means of assessing the impact of forest degradation and may serve as benchmarks of carbon carrying capacity over regions with similar site and climate conditions. BioGeoChemical (BGC) ecosystem models explicitly consider the impacts of site and climate conditions and may assess benchmark levels over regions devoid of undisturbed conditions. We will present a BGC-model validation for the Western Congolian Lowland Rainforest (WCLRF) using field data from a recently confirmed forest refuge, show model - data comparisons for disturbed und undisturbed forests under different site and climate conditions as well as for sites with repeated assessment of biodiversity and standing biomass during recovery from intensive exploitation. We will present climatic thresholds for WCLRF stability, and construct resilience landscapes for current day conditions vs. climate and management impacts.

Hysteresis in the Central African Rainforest

NASA Astrophysics Data System (ADS)

Pietsch, Stephan Alexander; Elias Bednar, Johannes; Gautam, Sishir; Petritsch, Richard; Schier, Franziska; Stanzl, Patrick

2014-05-01

Past climate change caused severe disturbances of the Central African rainforest belt, with forest fragmentation and re-expansion due to drier and wetter climate conditions. Besides climate, human induced forest degradation affected biodiversity, structure and carbon storage of Congo basin rainforests. Information on climatically stable, mature rainforest, unaffected by human induced disturbances, provides means of assessing the impact of forest degradation and may serve as benchmarks of carbon carrying capacity over regions with similar site and climate conditions. BioGeoChemical (BGC) ecosystem models explicitly consider the impacts of site and climate conditions and may assess benchmark levels over regions devoid of undisturbed conditions. We will present a BGC-model validation for the Western Congolian Lowland Rainforest (WCLRF) using field data from a recently confirmed forest refuge, show model - data comparisons for disturbed und undisturbed forests under different site and climate conditions as well as for sites with repeated assessment of biodiversity and standing biomass during recovery from intensive exploitation. We will present climatic thresholds for WCLRF stability, analyse the relationship between resilience, standing C-stocks and change in climate and finally provide evidence of hysteresis.

Integrated presentation of ecological risk from multiple stressors

NASA Astrophysics Data System (ADS)

Goussen, Benoit; Price, Oliver R.; Rendal, Cecilie; Ashauer, Roman

2016-10-01

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic.

Osmotic Pressure in Ionic Microgel Dispersions

NASA Astrophysics Data System (ADS)

Denton, Alan R.; Tang, Qiyun

2015-03-01

Microgels are microscopic gel particles, typically 10-1000 nm in size, that are swollen by a solvent. Hollow microgels (microcapsules) can encapsulate cargo, such as dye molecules or drugs, in their solvent-filled cavities. Their sensitive response to environmental conditions (e.g., temperature, pH) and influence on flow properties suit microgels to widespread applications in the chemical, pharmaceutical, food, and consumer care industries. When dispersed in water, polyelectrolyte gels become charged through dissociation of counterions. The electrostatic contribution to the osmotic pressure inside and outside of ionic microgels influences particle swelling and bulk materials properties, including thermodynamic, structural, optical, and rheological properties. Within the primitive and cell models of polyelectrolyte solutions, we derive an exact statistical mechanical formula for the contribution of mobile microions to the osmotic pressure within ionic microgels. Using Poisson-Boltzmann theory, we validate this result by explicitly calculating ion distributions across the surface of an ionic microgel and the electrostatic contribution to the osmotic pressure. Within a coarse-grained one-component model, we further chart the limits of the cell model for salty dispersions. This work was supported by the National Science Foundation under Grant No. DMR-1106331.

Integrated presentation of ecological risk from multiple stressors.

PubMed

Goussen, Benoit; Price, Oliver R; Rendal, Cecilie; Ashauer, Roman

2016-10-26

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic.

Generalized binomial τ-leap method for biochemical kinetics incorporating both delay and intrinsic noise

NASA Astrophysics Data System (ADS)

Leier, André; Marquez-Lago, Tatiana T.; Burrage, Kevin

2008-05-01

The delay stochastic simulation algorithm (DSSA) by Barrio et al. [Plos Comput. Biol. 2, 117(E) (2006)] was developed to simulate delayed processes in cell biology in the presence of intrinsic noise, that is, when there are small-to-moderate numbers of certain key molecules present in a chemical reaction system. These delayed processes can faithfully represent complex interactions and mechanisms that imply a number of spatiotemporal processes often not explicitly modeled such as transcription and translation, basic in the modeling of cell signaling pathways. However, for systems with widely varying reaction rate constants or large numbers of molecules, the simulation time steps of both the stochastic simulation algorithm (SSA) and the DSSA can become very small causing considerable computational overheads. In order to overcome the limit of small step sizes, various τ-leap strategies have been suggested for improving computational performance of the SSA. In this paper, we present a binomial τ-DSSA method that extends the τ-leap idea to the delay setting and avoids drawing insufficient numbers of reactions, a common shortcoming of existing binomial τ-leap methods that becomes evident when dealing with complex chemical interactions. The resulting inaccuracies are most evident in the delayed case, even when considering reaction products as potential reactants within the same time step in which they are produced. Moreover, we extend the framework to account for multicellular systems with different degrees of intercellular communication. We apply these ideas to two important genetic regulatory models, namely, the hes1 gene, implicated as a molecular clock, and a Her1/Her 7 model for coupled oscillating cells.

Cell Patterns Emerge from Coupled Chemical and Physical Fields with Cell Proliferation Dynamics: The Arabidopsis thaliana Root as a Study System

PubMed Central

Barrio, Rafael A.; Romero-Arias, José Roberto; Noguez, Marco A.; Azpeitia, Eugenio; Ortiz-Gutiérrez, Elizabeth; Hernández-Hernández, Valeria; Cortes-Poza, Yuriria; Álvarez-Buylla, Elena R.

2013-01-01

A central issue in developmental biology is to uncover the mechanisms by which stem cells maintain their capacity to regenerate, yet at the same time produce daughter cells that differentiate and attain their ultimate fate as a functional part of a tissue or an organ. In this paper we propose that, during development, cells within growing organs obtain positional information from a macroscopic physical field that is produced in space while cells are proliferating. This dynamical interaction triggers and responds to chemical and genetic processes that are specific to each biological system. We chose the root apical meristem of Arabidopsis thaliana to develop our dynamical model because this system is well studied at the molecular, genetic and cellular levels and has the key traits of multicellular stem-cell niches. We built a dynamical model that couples fundamental molecular mechanisms of the cell cycle to a tension physical field and to auxin dynamics, both of which are known to play a role in root development. We perform extensive numerical calculations that allow for quantitative comparison with experimental measurements that consider the cellular patterns at the root tip. Our model recovers, as an emergent pattern, the transition from proliferative to transition and elongation domains, characteristic of stem-cell niches in multicellular organisms. In addition, we successfully predict altered cellular patterns that are expected under various applied auxin treatments or modified physical growth conditions. Our modeling platform may be extended to explicitly consider gene regulatory networks or to treat other developmental systems. PMID:23658505

A spatially explicit hydro-ecological modeling framework (BEPS-TerrainLab V2.0): Model description and test in a boreal ecosystem in Eastern North America

NASA Astrophysics Data System (ADS)

Govind, Ajit; Chen, Jing Ming; Margolis, Hank; Ju, Weimin; Sonnentag, Oliver; Giasson, Marc-André

2009-04-01

SummaryA spatially explicit, process-based hydro-ecological model, BEPS-TerrainLab V2.0, was developed to improve the representation of ecophysiological, hydro-ecological and biogeochemical processes of boreal ecosystems in a tightly coupled manner. Several processes unique to boreal ecosystems were implemented including the sub-surface lateral water fluxes, stratification of vegetation into distinct layers for explicit ecophysiological representation, inclusion of novel spatial upscaling strategies and biogeochemical processes. To account for preferential water fluxes common in humid boreal ecosystems, a novel scheme was introduced based on laboratory analyses. Leaf-scale ecophysiological processes were upscaled to canopy-scale by explicitly considering leaf physiological conditions as affected by light and water stress. The modified model was tested with 2 years of continuous measurements taken at the Eastern Old Black Spruce Site of the Fluxnet-Canada Research Network located in a humid boreal watershed in eastern Canada. Comparison of the simulated and measured ET, water-table depth (WTD), volumetric soil water content (VSWC) and gross primary productivity (GPP) revealed that BEPS-TerrainLab V2.0 simulates hydro-ecological processes with reasonable accuracy. The model was able to explain 83% of the ET, 92% of the GPP variability and 72% of the WTD dynamics. The model suggests that in humid ecosystems such as eastern North American boreal watersheds, topographically driven sub-surface baseflow is the main mechanism of soil water partitioning which significantly affects the local-scale hydrological conditions.

Analytical validation of an explicit finite element model of a rolling element bearing with a localised line spall

NASA Astrophysics Data System (ADS)

Singh, Sarabjeet; Howard, Carl Q.; Hansen, Colin H.; Köpke, Uwe G.

2018-03-01

In this paper, numerically modelled vibration response of a rolling element bearing with a localised outer raceway line spall is presented. The results were obtained from a finite element (FE) model of the defective bearing solved using an explicit dynamics FE software package, LS-DYNA. Time domain vibration signals of the bearing obtained directly from the FE modelling were processed further to estimate time-frequency and frequency domain results, such as spectrogram and power spectrum, using standard signal processing techniques pertinent to the vibration-based monitoring of rolling element bearings. A logical approach to analyses of the numerically modelled results was developed with an aim to presenting the analytical validation of the modelled results. While the time and frequency domain analyses of the results show that the FE model generates accurate bearing kinematics and defect frequencies, the time-frequency analysis highlights the simulation of distinct low- and high-frequency characteristic vibration signals associated with the unloading and reloading of the rolling elements as they move in and out of the defect, respectively. Favourable agreement of the numerical and analytical results demonstrates the validation of the results from the explicit FE modelling of the bearing.

Increasing the sampling efficiency of protein conformational transition using velocity-scaling optimized hybrid explicit/implicit solvent REMD simulation

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

Yu, Yuqi; Wang, Jinan; Shao, Qiang, E-mail: qshao@mail.shcnc.ac.cn, E-mail: Jiye.Shi@ucb.com, E-mail: wlzhu@mail.shcnc.ac.cn

2015-03-28

The application of temperature replica exchange molecular dynamics (REMD) simulation on protein motion is limited by its huge requirement of computational resource, particularly when explicit solvent model is implemented. In the previous study, we developed a velocity-scaling optimized hybrid explicit/implicit solvent REMD method with the hope to reduce the temperature (replica) number on the premise of maintaining high sampling efficiency. In this study, we utilized this method to characterize and energetically identify the conformational transition pathway of a protein model, the N-terminal domain of calmodulin. In comparison to the standard explicit solvent REMD simulation, the hybrid REMD is much lessmore » computationally expensive but, meanwhile, gives accurate evaluation of the structural and thermodynamic properties of the conformational transition which are in well agreement with the standard REMD simulation. Therefore, the hybrid REMD could highly increase the computational efficiency and thus expand the application of REMD simulation to larger-size protein systems.« less

Predictive Validity of Explicit and Implicit Threat Overestimation in Contamination Fear

PubMed Central

Green, Jennifer S.; Teachman, Bethany A.

2012-01-01

We examined the predictive validity of explicit and implicit measures of threat overestimation in relation to contamination-fear outcomes using structural equation modeling. Undergraduate students high in contamination fear (N = 56) completed explicit measures of contamination threat likelihood and severity, as well as looming vulnerability cognitions, in addition to an implicit measure of danger associations with potential contaminants. Participants also completed measures of contamination-fear symptoms, as well as subjective distress and avoidance during a behavioral avoidance task, and state looming vulnerability cognitions during an exposure task. The latent explicit (but not implicit) threat overestimation variable was a significant and unique predictor of contamination fear symptoms and self-reported affective and cognitive facets of contamination fear. On the contrary, the implicit (but not explicit) latent measure predicted behavioral avoidance (at the level of a trend). Results are discussed in terms of differential predictive validity of implicit versus explicit markers of threat processing and multiple fear response systems. PMID:24073390

Explicit and Implicit Processes Constitute the Fast and Slow Processes of Sensorimotor Learning.

PubMed

McDougle, Samuel D; Bond, Krista M; Taylor, Jordan A

2015-07-01

A popular model of human sensorimotor learning suggests that a fast process and a slow process work in parallel to produce the canonical learning curve (Smith et al., 2006). Recent evidence supports the subdivision of sensorimotor learning into explicit and implicit processes that simultaneously subserve task performance (Taylor et al., 2014). We set out to test whether these two accounts of learning processes are homologous. Using a recently developed method to assay explicit and implicit learning directly in a sensorimotor task, along with a computational modeling analysis, we show that the fast process closely resembles explicit learning and the slow process approximates implicit learning. In addition, we provide evidence for a subdivision of the slow/implicit process into distinct manifestations of motor memory. We conclude that the two-state model of motor learning is a close approximation of sensorimotor learning, but it is unable to describe adequately the various implicit learning operations that forge the learning curve. Our results suggest that a wider net be cast in the search for the putative psychological mechanisms and neural substrates underlying the multiplicity of processes involved in motor learning. Copyright © 2015 the authors 0270-6474/15/359568-12$15.00/0.

Investigating the predictive validity of implicit and explicit measures of motivation in problem-solving behavioural tasks.

PubMed

Keatley, David; Clarke, David D; Hagger, Martin S

2013-09-01

Research into the effects of individuals'autonomous motivation on behaviour has traditionally adopted explicit measures and self-reported outcome assessment. Recently, there has been increased interest in the effects of implicit motivational processes underlying behaviour from a self-determination theory (SDT) perspective. The aim of the present research was to provide support for the predictive validity of an implicit measure of autonomous motivation on behavioural persistence on two objectively measurable tasks. SDT and a dual-systems model were adopted as frameworks to explain the unique effects offered by explicit and implicit autonomous motivational constructs on behavioural persistence. In both studies, implicit autonomous motivation significantly predicted unique variance in time spent on each task. Several explicit measures of autonomous motivation also significantly predicted persistence. Results provide support for the proposed model and the inclusion of implicit measures in research on motivated behaviour. In addition, implicit measures of autonomous motivation appear to be better suited to explaining variance in behaviours that are more spontaneous or unplanned. Future implications for research examining implicit motivation from dual-systems models and SDT approaches are outlined. © 2012 The British Psychological Society.

Modeling Active Aging and Explicit Memory: An Empirical Study.

PubMed

Ponce de León, Laura Ponce; Lévy, Jean Pierre; Fernández, Tomás; Ballesteros, Soledad

2015-08-01

The rapid growth of the population of older adults and their concomitant psychological status and health needs have captured the attention of researchers and health professionals. To help fill the void of literature available to social workers interested in mental health promotion and aging, the authors provide a model for active aging that uses psychosocial variables. Structural equation modeling was used to examine the relationships among the latent variables of the state of explicit memory, the perception of social resources, depression, and the perception of quality of life in a sample of 184 older adults. The results suggest that explicit memory is not a direct indicator of the perception of quality of life, but it could be considered an indirect indicator as it is positively correlated with perception of social resources and negatively correlated with depression. These last two variables influenced the perception of quality of life directly, the former positively and the latter negatively. The main outcome suggests that the perception of social support improves explicit memory and quality of life and reduces depression in active older adults. The findings also suggest that gerontological professionals should design memory training programs, improve available social resources, and offer environments with opportunities to exercise memory.

Explicit and Implicit Processes Constitute the Fast and Slow Processes of Sensorimotor Learning

PubMed Central

Bond, Krista M.; Taylor, Jordan A.

2015-01-01

A popular model of human sensorimotor learning suggests that a fast process and a slow process work in parallel to produce the canonical learning curve (Smith et al., 2006). Recent evidence supports the subdivision of sensorimotor learning into explicit and implicit processes that simultaneously subserve task performance (Taylor et al., 2014). We set out to test whether these two accounts of learning processes are homologous. Using a recently developed method to assay explicit and implicit learning directly in a sensorimotor task, along with a computational modeling analysis, we show that the fast process closely resembles explicit learning and the slow process approximates implicit learning. In addition, we provide evidence for a subdivision of the slow/implicit process into distinct manifestations of motor memory. We conclude that the two-state model of motor learning is a close approximation of sensorimotor learning, but it is unable to describe adequately the various implicit learning operations that forge the learning curve. Our results suggest that a wider net be cast in the search for the putative psychological mechanisms and neural substrates underlying the multiplicity of processes involved in motor learning. PMID:26134640

Independence polynomial and matching polynomial of the Koch network

NASA Astrophysics Data System (ADS)

Liao, Yunhua; Xie, Xiaoliang

2015-11-01

The lattice gas model and the monomer-dimer model are two classical models in statistical mechanics. It is well known that the partition functions of these two models are associated with the independence polynomial and the matching polynomial in graph theory, respectively. Both polynomials have been shown to belong to the “#P-complete” class, which indicate the problems are computationally “intractable”. We consider these two polynomials of the Koch networks which are scale-free with small-world effects. Explicit recurrences are derived, and explicit formulae are presented for the number of independent sets of a certain type.

Computational chemical analysis of unconjugated bilirubin anions and insights into pKa values clarification

NASA Astrophysics Data System (ADS)

Vega-Hissi, Esteban G.; Estrada, Mario R.; Lavecchia, Martín J.; Pis Diez, Reinaldo

2013-01-01

The pKa, the negative logarithm of the acid dissociation equilibrium constant, of the carboxylic acid groups of unconjugated bilirubin in water is a discussed issue because there are quite different experimental values reported. Using quantum mechanical calculations we have studied the conformational behavior of unconjugated bilirubin species (in gas phase and in solution modeled implicitly and explicitly) to provide evidence that may clarify pKa values because of its pathophysiological relevance. Our results show that rotation of carboxylate group, which is not restricted, settles it in a suitable place to establish stronger interactions that stabilizes the monoanion and the dianion to be properly solvated, demonstrating that the rationalization used to justify the high pKa values of unconjugated bilirubin is inappropriate. Furthermore, low unconjugated bilirubin (UCB) pKa values were estimated from a linear regression analysis.

Pharmacokinetics and PBPK Models

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

Corley, Richard A.

2010-07-01

Since the landmark report Pesticides in the Diets of Infants and Children (NRC 1993), children at all stages of development, from fertilization through postnatal maturation, have explicitly been identified as an area of emphasis in human health risk assessments. Exposure to drugs or chemicals at any point in development has the potential for causing irreversible changes that can be unique to each stage of development (Grabowski and Daston 1983; Rodier 1978; Wilson 1973). While exposures of a developing embryo or fetus are mediated by the mother, postnatal exposures consist of maternal influences via breastfeeding as well as environmental factors (Figuremore » 1). As a result, risk assessments for developmental toxicity must consider the sources as well as timing of potential exposures to adequately protect children when they may be the most exposed or the most sensitive to adverse consequences (NRC 1993).« less

Assessment of an Explicit Algebraic Reynolds Stress Model

NASA Technical Reports Server (NTRS)

Carlson, Jan-Renee

2005-01-01

This study assesses an explicit algebraic Reynolds stress turbulence model in the in the three-dimensional Reynolds averaged Navier-Stokes (RANS) solver, ISAAC (Integrated Solution Algorithm for Arbitrary Con gurations). Additionally, it compares solutions for two select configurations between ISAAC and the RANS solver PAB3D. This study compares with either direct numerical simulation data, experimental data, or empirical models for several different geometries with compressible, separated, and high Reynolds number flows. In general, the turbulence model matched data or followed experimental trends well, and for the selected configurations, the computational results of ISAAC closely matched those of PAB3D using the same turbulence model.

Logistic Mixed Models to Investigate Implicit and Explicit Belief Tracking.

PubMed

Lages, Martin; Scheel, Anne

2016-01-01

We investigated the proposition of a two-systems Theory of Mind in adults' belief tracking. A sample of N = 45 participants predicted the choice of one of two opponent players after observing several rounds in an animated card game. Three matches of this card game were played and initial gaze direction on target and subsequent choice predictions were recorded for each belief task and participant. We conducted logistic regressions with mixed effects on the binary data and developed Bayesian logistic mixed models to infer implicit and explicit mentalizing in true belief and false belief tasks. Although logistic regressions with mixed effects predicted the data well a Bayesian logistic mixed model with latent task- and subject-specific parameters gave a better account of the data. As expected explicit choice predictions suggested a clear understanding of true and false beliefs (TB/FB). Surprisingly, however, model parameters for initial gaze direction also indicated belief tracking. We discuss why task-specific parameters for initial gaze directions are different from choice predictions yet reflect second-order perspective taking.

Characterizing Aeroelastic Systems Using Eigenanalysis, Explicitly Retaining The Aerodynamic Degrees of Freedom

NASA Technical Reports Server (NTRS)

Heeg, Jennifer; Dowell, Earl H.

2001-01-01

Discrete time aeroelastic models with explicitly retained aerodynamic modes have been generated employing a time marching vortex lattice aerodynamic model. This paper presents analytical results from eigenanalysis of these models. The potential of these models to calculate the behavior of modes that represent damped system motion (noncritical modes) in addition to the simple harmonic modes is explored. A typical section with only structural freedom in pitch is examined. The eigenvalues are examined and compared to experimental data. Issues regarding the convergence of the solution with regard to refining the aerodynamic discretization are investigated. Eigenvector behavior is examined; the eigenvector associated with a particular eigenvalue can be viewed as the set of modal participation factors for that particular mode. For the present formulation of the equations of motion, the vorticity for each aerodynamic element appears explicitly as an element of each eigenvector in addition to the structural dynamic generalized coordinates. Thus, modal participation of the aerodynamic degrees of freedom can be assessed in M addition to participation of structural degrees of freedom.

Blast and the Consequences on Traumatic Brain Injury-Multiscale Mechanical Modeling of Brain

DTIC Science & Technology

2011-02-17

blast simulation. LS-DYNA as an explicit FE code has been employed to simulate this multi- material fluid –structure interaction problem. The 3-D head...formulation is implemented to model the air-blast simulation. LS-DYNA as an explicit FE code has been employed to simulate this multi-material fluid ...Biomechanics Study of Influencing Parameters for brain under Impact ............................... 12 5.1 The Impact of Cerebrospinal Fluid

Traveling waves in a spring-block chain sliding down a slope

NASA Astrophysics Data System (ADS)

Morales, J. E.; James, G.; Tonnelier, A.

2017-07-01

Traveling waves are studied in a spring slider-block model. We explicitly construct front waves (kinks) for a piecewise-linear spinodal friction force. Pulse waves are obtained as the matching of two traveling fronts with identical speeds. Explicit formulas are obtained for the wavespeed and the wave form in the anticontinuum limit. The link with localized waves in a Burridge-Knopoff model of an earthquake fault is briefly discussed.

Biomass and fire dynamics in a temperate forest-grassland mosaic: Integrating multi-species herbivory, climate, and fire with the FireBGCv2/GrazeBGC system

Treesearch

Robert A. Riggs; Robert E. Keane; Norm Cimon; Rachel Cook; Lisa Holsinger; John Cook; Timothy DelCurto; L.Scott Baggett; Donald Justice; David Powell; Martin Vavra; Bridgett Naylor

2015-01-01

Landscape fire succession models (LFSMs) predict spatially-explicit interactions between vegetation succession and disturbance, but these models have yet to fully integrate ungulate herbivory as a driver of their processes. We modified a complex LFSM, FireBGCv2, to include a multi-species herbivory module, GrazeBGC. The system is novel in that it explicitly...

Traveling waves in a spring-block chain sliding down a slope.

PubMed

Morales, J E; James, G; Tonnelier, A

2017-07-01

Traveling waves are studied in a spring slider-block model. We explicitly construct front waves (kinks) for a piecewise-linear spinodal friction force. Pulse waves are obtained as the matching of two traveling fronts with identical speeds. Explicit formulas are obtained for the wavespeed and the wave form in the anticontinuum limit. The link with localized waves in a Burridge-Knopoff model of an earthquake fault is briefly discussed.

One-dimensional numerical modeling of Blue Jet and its impact on stratospheric chemistry

NASA Astrophysics Data System (ADS)

Duruisseau, F.; Thiéblemont, R.; Huret, N.

2011-12-01

In the stratosphere the ozone layer is very sensitive to the NOx abundance. The ionisation of N2 and O2 molecules by TLE's (Transient Luminous Events) is a source of NOx which is currently not well quantified and could act as a loss of ozone. In this study a one dimensional explicit parameterization of a Blue-Jet propagation based on that proposed by Raizer et al. (2006 and 2007) has been developed. This parameterization considers Blue-Jet as a streamer initiated by a bidirectional leader discharge, emerging from the anvil and sustained by moderate cloud charge. The streamer growth varies with the electrical field induced by initial cloud charge and the initial altitude. This electrical parameterization and the chemical mechanisms associated with the discharge have been implemented into a detailed chemical model of stratospheric ozone including evolution of nitrogen, chlorine and bromine species. We will present several tests performed to validate the electrical code and evaluate the propagation velocity and the maximum altitude attains by the blue jet as a function of electrical parameters. The results obtained giving the spatiotemporal evolution of the electron density are then used to initiate the specific chemistry associated with the Blue Jet. Preliminary results on the impact of such discharge on the ozone content and the whole stratospheric system will be presented.

Generalized Background Error covariance matrix model (GEN_BE v2.0)

NASA Astrophysics Data System (ADS)

Descombes, G.; Auligné, T.; Vandenberghe, F.; Barker, D. M.

2014-07-01

The specification of state background error statistics is a key component of data assimilation since it affects the impact observations will have on the analysis. In the variational data assimilation approach, applied in geophysical sciences, the dimensions of the background error covariance matrix (B) are usually too large to be explicitly determined and B needs to be modeled. Recent efforts to include new variables in the analysis such as cloud parameters and chemical species have required the development of the code to GENerate the Background Errors (GEN_BE) version 2.0 for the Weather Research and Forecasting (WRF) community model to allow for a simpler, flexible, robust, and community-oriented framework that gathers methods used by meteorological operational centers and researchers. We present the advantages of this new design for the data assimilation community by performing benchmarks and showing some of the new features on data assimilation test cases. As data assimilation for clouds remains a challenge, we present a multivariate approach that includes hydrometeors in the control variables and new correlated errors. In addition, the GEN_BE v2.0 code is employed to diagnose error parameter statistics for chemical species, which shows that it is a tool flexible enough to involve new control variables. While the generation of the background errors statistics code has been first developed for atmospheric research, the new version (GEN_BE v2.0) can be easily extended to other domains of science and be chosen as a testbed for diagnostic and new modeling of B. Initially developed for variational data assimilation, the model of the B matrix may be useful for variational ensemble hybrid methods as well.

Cyto-Sim: a formal language model and stochastic simulator of membrane-enclosed biochemical processes.

PubMed

Sedwards, Sean; Mazza, Tommaso

2007-10-15

Compartments and membranes are the basis of cell topology and more than 30% of the human genome codes for membrane proteins. While it is possible to represent compartments and membrane proteins in a nominal way with many mathematical formalisms used in systems biology, few, if any, explicitly model the topology of the membranes themselves. Discrete stochastic simulation potentially offers the most accurate representation of cell dynamics. Since the details of every molecular interaction in a pathway are often not known, the relationship between chemical species in not necessarily best described at the lowest level, i.e. by mass action. Simulation is a form of computer-aided analysis, relying on human interpretation to derive meaning. To improve efficiency and gain meaning in an automatic way, it is necessary to have a formalism based on a model which has decidable properties. We present Cyto-Sim, a stochastic simulator of membrane-enclosed hierarchies of biochemical processes, where the membranes comprise an inner, outer and integral layer. The underlying model is based on formal language theory and has been shown to have decidable properties (Cavaliere and Sedwards, 2006), allowing formal analysis in addition to simulation. The simulator provides variable levels of abstraction via arbitrary chemical kinetics which link to ordinary differential equations. In addition to its compact native syntax, Cyto-Sim currently supports models described as Petri nets, can import all versions of SBML and can export SBML and MATLAB m-files. Cyto-Sim is available free, either as an applet or a stand-alone Java program via the web page (http://www.cosbi.eu/Rpty_Soft_CytoSim.php). Other versions can be made available upon request.

Spin-orbit splitted excited states using explicitly-correlated equation-of-motion coupled-cluster singles and doubles eigenvectors

NASA Astrophysics Data System (ADS)

Bokhan, Denis; Trubnikov, Dmitrii N.; Perera, Ajith; Bartlett, Rodney J.

2018-04-01

An explicitly-correlated method of calculation of excited states with spin-orbit couplings, has been formulated and implemented. Developed approach utilizes left and right eigenvectors of equation-of-motion coupled-cluster model, which is based on the linearly approximated explicitly correlated coupled-cluster singles and doubles [CCSD(F12)] method. The spin-orbit interactions are introduced by using the spin-orbit mean field (SOMF) approximation of the Breit-Pauli Hamiltonian. Numerical tests for several atoms and molecules show good agreement between explicitly-correlated results and the corresponding values, calculated in complete basis set limit (CBS); the highly-accurate excitation energies can be obtained already at triple- ζ level.

Heavy-light mesons in chiral AdS/QCD

NASA Astrophysics Data System (ADS)

Liu, Yizhuang; Zahed, Ismail

2017-06-01

We discuss a minimal holographic model for the description of heavy-light and light mesons with chiral symmetry, defined in a slab of AdS space. The model consists of a pair of chiral Yang-Mills and tachyon fields with specific boundary conditions that break spontaneously chiral symmetry in the infrared. The heavy-light spectrum and decay constants are evaluated explicitly. In the heavy mass limit the model exhibits both heavy-quark and chiral symmetry and allows for the explicit derivation of the one-pion axial couplings to the heavy-light mesons.

Nonminimally coupled massive scalar field in a 2D black hole: Exactly solvable model

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

Frolov, V.; Zelnikov, A.

2001-06-15

We study a nonminimal massive scalar field in the background of a two-dimensional black hole spacetime. We consider the black hole which is the solution of the 2D dilaton gravity derived from string-theoretical models. We find an explicit solution in a closed form for all modes and the Green function of the scalar field with an arbitrary mass and a nonminimal coupling to the curvature. Greybody factors, the Hawking radiation, and 2>{sup ren} are calculated explicitly for this exactly solvable model.

Test-Case Generation using an Explicit State Model Checker Final Report

NASA Technical Reports Server (NTRS)

Heimdahl, Mats P. E.; Gao, Jimin

2003-01-01

In the project 'Test-Case Generation using an Explicit State Model Checker' we have extended an existing tools infrastructure for formal modeling to export Java code so that we can use the NASA Ames tool Java Pathfinder (JPF) for test case generation. We have completed a translator from our source language RSML(exp -e) to Java and conducted initial studies of how JPF can be used as a testing tool. In this final report, we provide a detailed description of the translation approach as implemented in our tools.

Inductive electronegativity scale. Iterative calculation of inductive partial charges.

PubMed

Cherkasov, Artem

2003-01-01

A number of novel QSAR descriptors have been introduced on the basis of the previously elaborated models for steric and inductive effects. The developed "inductive" parameters include absolute and effective electronegativity, atomic partial charges, and local and global chemical hardness and softness. Being based on traditional inductive and steric substituent constants these 3D descriptors provide a valuable insight into intramolecular steric and electronic interactions and can find broad application in structure-activity studies. Possible interpretation of physical meaning of the inductive descriptors has been suggested by considering a neutral molecule as an electrical capacitor formed by charged atomic spheres. This approximation relates inductive chemical softness and hardness of bound atom(s) with the total area of the facings of electrical capacitor formed by the atom(s) and the rest of the molecule. The derived full electronegativity equalization scheme allows iterative calculation of inductive partial charges on the basis of atomic electronegativities, covalent radii, and intramolecular distances. A range of inductive descriptors has been computed for a variety of organic compounds. The calculated inductive charges in the studied molecules have been validated by experimental C-1s Electron Core Binding Energies and molecular dipole moments. Several semiempirical chemical rules, such as equalized electronegativity's arithmetic mean, principle of maximum hardness, and principle of hardness borrowing could be explicitly illustrated in the framework of the developed approach.

Implicit and explicit weight bias in a national sample of 4,732 medical students: the medical student CHANGES study.

PubMed

Phelan, Sean M; Dovidio, John F; Puhl, Rebecca M; Burgess, Diana J; Nelson, David B; Yeazel, Mark W; Hardeman, Rachel; Perry, Sylvia; van Ryn, Michelle

2014-04-01

To examine the magnitude of explicit and implicit weight biases compared to biases against other groups; and identify student factors predicting bias in a large national sample of medical students. A web-based survey was completed by 4,732 1st year medical students from 49 medical schools as part of a longitudinal study of medical education. The survey included a validated measure of implicit weight bias, the implicit association test, and 2 measures of explicit bias: a feeling thermometer and the anti-fat attitudes test. A majority of students exhibited implicit (74%) and explicit (67%) weight bias. Implicit weight bias scores were comparable to reported bias against racial minorities. Explicit attitudes were more negative toward obese people than toward racial minorities, gays, lesbians, and poor people. In multivariate regression models, implicit and explicit weight bias was predicted by lower BMI, male sex, and non-Black race. Either implicit or explicit bias was also predicted by age, SES, country of birth, and specialty choice. Implicit and explicit weight bias is common among 1st year medical students, and varies across student factors. Future research should assess implications of biases and test interventions to reduce their impact. Copyright © 2013 The Obesity Society.

Different Mechanisms of Soil Microbial Response to Global Change Result in Different Outcomes in the MIMICS-CN Model

NASA Astrophysics Data System (ADS)

Kyker-Snowman, E.; Wieder, W. R.; Grandy, S.

2017-12-01

Microbial-explicit models of soil carbon (C) and nitrogen (N) cycling have improved upon simulations of C and N stocks and flows at site-to-global scales relative to traditional first-order linear models. However, the response of microbial-explicit soil models to global change factors depends upon which parameters and processes in a model are altered by those factors. We used the MIcrobial-MIneral Carbon Stabilization Model with coupled N cycling (MIMICS-CN) to compare modeled responses to changes in temperature and plant inputs at two previously-modeled sites (Harvard Forest and Kellogg Biological Station). We spun the model up to equilibrium, applied each perturbation, and evaluated 15 years of post-perturbation C and N pools and fluxes. To model the effect of increasing temperatures, we independently examined the impact of decreasing microbial C use efficiency (CUE), increasing the rate of microbial turnover, and increasing Michaelis-Menten kinetic rates of litter decomposition, plus several combinations of the three. For plant inputs, we ran simulations with stepwise increases in metabolic litter, structural litter, whole litter (structural and metabolic), or labile soil C. The cumulative change in soil C or N varied in both sign and magnitude across simulations. For example, increasing kinetic rates of litter decomposition resulted in net releases of both C and N from soil pools, while decreasing CUE produced short-term increases in respiration but long-term accumulation of C in litter pools and shifts in soil C:N as microbial demand for C increased and biomass declined. Given that soil N cycling constrains the response of plant productivity to global change and that soils generate a large amount of uncertainty in current earth system models, microbial-explicit models are a critical opportunity to advance the modeled representation of soils. However, microbial-explicit models must be improved by experiments to isolate the physiological and stoichiometric parameters of soil microbes that shift under global change.

Modelling explicit fracture of nuclear fuel pellets using peridynamics

NASA Astrophysics Data System (ADS)

Mella, R.; Wenman, M. R.

2015-12-01

Three dimensional models of explicit cracking of nuclear fuel pellets for a variety of power ratings have been explored with peridynamics, a non-local, mesh free, fracture mechanics method. These models were implemented in the explicitly integrated molecular dynamics code LAMMPS, which was modified to include thermal strains in solid bodies. The models of fuel fracture, during initial power transients, are shown to correlate with the mean number of cracks observed on the inner and outer edges of the pellet, by experimental post irradiation examination of fuel, for power ratings of 10 and 15 W g-1 UO2. The models of the pellet show the ability to predict expected features such as the mid-height pellet crack, the correct number of radial cracks and initiation and coalescence of radial cracks. This work presents a modelling alternative to empirical fracture data found in many fuel performance codes and requires just one parameter of fracture strain. Weibull distributions of crack numbers were fitted to both numerical and experimental data using maximum likelihood estimation so that statistical comparison could be made. The findings show P-values of less than 0.5% suggesting an excellent agreement between model and experimental distributions.

Aerosol-cloud interactions in a multi-scale modeling framework

NASA Astrophysics Data System (ADS)

Lin, G.; Ghan, S. J.

2017-12-01

Atmospheric aerosols play an important role in changing the Earth's climate through scattering/absorbing solar and terrestrial radiation and interacting with clouds. However, quantification of the aerosol effects remains one of the most uncertain aspects of current and future climate projection. Much of the uncertainty results from the multi-scale nature of aerosol-cloud interactions, which is very challenging to represent in traditional global climate models (GCMs). In contrast, the multi-scale modeling framework (MMF) provides a viable solution, which explicitly resolves the cloud/precipitation in the cloud resolved model (CRM) embedded in the GCM grid column. In the MMF version of community atmospheric model version 5 (CAM5), aerosol processes are treated with a parameterization, called the Explicit Clouds Parameterized Pollutants (ECPP). It uses the cloud/precipitation statistics derived from the CRM to treat the cloud processing of aerosols on the GCM grid. However, this treatment treats clouds on the CRM grid but aerosols on the GCM grid, which is inconsistent with the reality that cloud-aerosol interactions occur on the cloud scale. To overcome the limitation, here, we propose a new aerosol treatment in the MMF: Explicit Clouds Explicit Aerosols (ECEP), in which we resolve both clouds and aerosols explicitly on the CRM grid. We first applied the MMF with ECPP to the Accelerated Climate Modeling for Energy (ACME) model to have an MMF version of ACME. Further, we also developed an alternative version of ACME-MMF with ECEP. Based on these two models, we have conducted two simulations: one with the ECPP and the other with ECEP. Preliminary results showed that the ECEP simulations tend to predict higher aerosol concentrations than ECPP simulations, because of the more efficient vertical transport from the surface to the higher atmosphere but the less efficient wet removal. We also found that the cloud droplet number concentrations are also different between the two simulations due to the difference in the cloud droplet lifetime. Next, we will explore how the ECEP treatment affects the anthropogenic aerosol forcing, particularly the aerosol indirect forcing, by comparing present-day and pre-industrial simulations.

Phase-space reaction network on a multisaddle energy landscape: HCN isomerization.

PubMed

Li, Chun-Biu; Matsunaga, Yasuhiro; Toda, Mikito; Komatsuzaki, Tamiki

2005-11-08

By using the HCN/CNH isomerization reaction as an illustrative vehicle of chemical reactions on multisaddle energy landscapes, we give explicit visualizations of molecular motions associated with a straight-through reaction tube in the phase space inside which all reactive trajectories pass from one basin to another, with eliminating recrossing trajectories in the configuration space. This visualization provides us with a chemical intuition of how chemical species "walk along" the reaction-rate slope in the multidimensional phase space compared with the intrinsic reaction path in the configuration space. The distinct nonergodic features in the two different HCN and CNH wells can be easily demonstrated by a section of Poincare surface of section in those potential minima, which predicts in a priori the pattern of trajectories residing in the potential well. We elucidate the global phase-space structure which gives rise to the non-Markovian dynamics or the dynamical correlation of sequential multisaddle chemical reactions. The phase-space structure relevant to the controllability of the product state in chemical reactions is also discussed.

Effective equations governing an active poroelastic medium

PubMed Central

2017-01-01

In this work, we consider the spatial homogenization of a coupled transport and fluid–structure interaction model, to the end of deriving a system of effective equations describing the flow, elastic deformation and transport in an active poroelastic medium. The ‘active’ nature of the material results from a morphoelastic response to a chemical stimulant, in which the growth time scale is strongly separated from other elastic time scales. The resulting effective model is broadly relevant to the study of biological tissue growth, geophysical flows (e.g. swelling in coals and clays) and a wide range of industrial applications (e.g. absorbant hygiene products). The key contribution of this work is the derivation of a system of homogenized partial differential equations describing macroscale growth, coupled to transport of solute, that explicitly incorporates details of the structure and dynamics of the microscopic system, and, moreover, admits finite growth and deformation at the pore scale. The resulting macroscale model comprises a Biot-type system, augmented with additional terms pertaining to growth, coupled to an advection–reaction–diffusion equation. The resultant system of effective equations is then compared with other recent models under a selection of appropriate simplifying asymptotic limits. PMID:28293138

Characterizing model uncertainties in the life cycle of lignocellulose-based ethanol fuels.

PubMed

Spatari, Sabrina; MacLean, Heather L

2010-11-15

Renewable and low carbon fuel standards being developed at federal and state levels require an estimation of the life cycle carbon intensity (LCCI) of candidate fuels that can substitute for gasoline, such as second generation bioethanol. Estimating the LCCI of such fuels with a high degree of confidence requires the use of probabilistic methods to account for known sources of uncertainty. We construct life cycle models for the bioconversion of agricultural residue (corn stover) and energy crops (switchgrass) and explicitly examine uncertainty using Monte Carlo simulation. Using statistical methods to identify significant model variables from public data sets and Aspen Plus chemical process models,we estimate stochastic life cycle greenhouse gas (GHG) emissions for the two feedstocks combined with two promising fuel conversion technologies. The approach can be generalized to other biofuel systems. Our results show potentially high and uncertain GHG emissions for switchgrass-ethanol due to uncertain CO₂ flux from land use change and N₂O flux from N fertilizer. However, corn stover-ethanol,with its low-in-magnitude, tight-in-spread LCCI distribution, shows considerable promise for reducing life cycle GHG emissions relative to gasoline and corn-ethanol. Coproducts are important for reducing the LCCI of all ethanol fuels we examine.

Development of a modified in vitro skin absorption method to study the epidermal/dermal disposition of a contact allergen in human skin.

PubMed

Pendlington, Ruth U; Minter, Helen J; Stupart, Leanne; MacKay, Cameron; Roper, Clive S; Sanders, David J; Pease, Camilla K

2008-01-01

In vitro skin absorption methods exist in Organisation for Economic Co-operation and Development (OECD) guideline form (No. 428) and are used to estimate the degree of systemic penetration of chemicals through skin. More detailed kinetics of permeation through skin compartments are not described well by existing methods. This study was designed to assess the practical feasibility of generating compartmental (stratum corneum/epidermal/dermal) disposition and kinetic data of topically applied chemicals. For chemically induced effects initiated in the skin (e.g., skin allergy), the delivery of tissue concentrations of chemical will impact the incidence and severity of biological effect. Explicit data on the kinetics of chemical disposition in skin have not traditionally been needed for skin allergy risk assessment: current in vivo assays embody delivery implicitly. Under the 7th Amendment to the European Cosmetics Directive, in vivo assays (such as the local lymph node assay for skin sensitization) will not be permitted to assess cosmetic ingredients. New in vitro and in silico alternative approaches and ways of predicting risk of adverse effects in humans need to be developed, and new methods such as that described here provide a way of estimating delivered concentrations and the effect of formulation changes on that delivery. As we continue to deconstruct the contributing factors of skin allergy in humans, it will be useful to have methods available that can measure skin tissue compartment exposure levels delivered from different exposure use scenarios. Here we provide such a method. The method could also be used to generate useful data for developing in silico kinetic models of compartmental skin delivery and for refining data for skin delivery in relation to the evaluation of systemic toxicity.

The chemical formula of a magnetotactic bacterium.

PubMed

Naresh, Mohit; Das, Sayoni; Mishra, Prashant; Mittal, Aditya

2012-05-01

Elucidation of the chemical logic of life is one of the grand challenges in biology, and essential to the progress of the upcoming field of synthetic biology. Treatment of microbial cells explicitly as a "chemical" species in controlled reaction (growth) environments has allowed fascinating discoveries of elemental formulae of a few species that have guided the modern views on compositions of a living cell. Application of mass and energy balances on living cells has proved to be useful in modeling of bioengineering systems, particularly in deriving optimized media compositions for growing microorganisms to maximize yields of desired bio-derived products by regulating intra-cellular metabolic networks. In this work, application of elemental mass balance during growth of Magnetospirillum gryphiswaldense in bioreactors has resulted in the discovery of the chemical formula of the magnetotactic bacterium. By developing a stoichiometric equation characterizing the formation of a magnetotactic bacterial cell, coupled with rigorous experimental measurements and robust calculations, we report the elemental formula of M. gryphiswaldense cell as CH(2.06)O(0.13)N(0.28)Fe(1.74×10(-3)). Remarkably, we find that iron metabolism during growth of this magnetotactic bacterium is much more correlated individually with carbon and nitrogen, compared to carbon and nitrogen with each other, indicating that iron serves more as a nutrient during bacterial growth rather than just a mineral. Magnetotactic bacteria have not only invoked some interest in the field of astrobiology for the last two decades, but are also prokaryotes having the unique ability of synthesizing membrane bound intracellular organelles. Our findings on these unique prokaryotes are a strong addition to the limited repertoire, of elemental compositions of living cells, aimed at exploring the chemical logic of life. Copyright © 2011 Wiley Periodicals, Inc.

ORILAM, a three-moment lognormal aerosol scheme for mesoscale atmospheric model: Online coupling into the Meso-NH-C model and validation on the Escompte campaign

NASA Astrophysics Data System (ADS)

Tulet, Pierre; Crassier, Vincent; Cousin, Frederic; Suhre, Karsten; Rosset, Robert

2005-09-01

Classical aerosol schemes use either a sectional (bin) or lognormal approach. Both approaches have particular capabilities and interests: the sectional approach is able to describe every kind of distribution, whereas the lognormal one makes assumption of the distribution form with a fewer number of explicit variables. For this last reason we developed a three-moment lognormal aerosol scheme named ORILAM to be coupled in three-dimensional mesoscale or CTM models. This paper presents the concept and hypothesis of a range of aerosol processes such as nucleation, coagulation, condensation, sedimentation, and dry deposition. One particular interest of ORILAM is to keep explicit the aerosol composition and distribution (mass of each constituent, mean radius, and standard deviation of the distribution are explicit) using the prediction of three-moment (m0, m3, and m6). The new model was evaluated by comparing simulations to measurements from the Escompte campaign and to a previously published aerosol model. The numerical cost of the lognormal mode is lower than two bins of the sectional one.

Moving forward socio-economically focused models of deforestation.

PubMed

Dezécache, Camille; Salles, Jean-Michel; Vieilledent, Ghislain; Hérault, Bruno

2017-09-01

Whilst high-resolution spatial variables contribute to a good fit of spatially explicit deforestation models, socio-economic processes are often beyond the scope of these models. Such a low level of interest in the socio-economic dimension of deforestation limits the relevancy of these models for decision-making and may be the cause of their failure to accurately predict observed deforestation trends in the medium term. This study aims to propose a flexible methodology for taking into account multiple drivers of deforestation in tropical forested areas, where the intensity of deforestation is explicitly predicted based on socio-economic variables. By coupling a model of deforestation location based on spatial environmental variables with several sub-models of deforestation intensity based on socio-economic variables, we were able to create a map of predicted deforestation over the period 2001-2014 in French Guiana. This map was compared to a reference map for accuracy assessment, not only at the pixel scale but also over cells ranging from 1 to approximately 600 sq. km. Highly significant relationships were explicitly established between deforestation intensity and several socio-economic variables: population growth, the amount of agricultural subsidies, gold and wood production. Such a precise characterization of socio-economic processes allows to avoid overestimation biases in high deforestation areas, suggesting a better integration of socio-economic processes in the models. Whilst considering deforestation as a purely geographical process contributes to the creation of conservative models unable to effectively assess changes in the socio-economic and political contexts influencing deforestation trends, this explicit characterization of the socio-economic dimension of deforestation is critical for the creation of deforestation scenarios in REDD+ projects. © 2017 John Wiley & Sons Ltd.

Higher measured than modeled ozone production at increased NOx levels in the Colorado Front Range

NASA Astrophysics Data System (ADS)

Baier, Bianca C.; Brune, William H.; Miller, David O.; Blake, Donald; Long, Russell; Wisthaler, Armin; Cantrell, Christopher; Fried, Alan; Heikes, Brian; Brown, Steven; McDuffie, Erin; Flocke, Frank; Apel, Eric; Kaser, Lisa; Weinheimer, Andrew

2017-09-01

Chemical models must correctly calculate the ozone formation rate, P(O3), to accurately predict ozone levels and to test mitigation strategies. However, air quality models can have large uncertainties in P(O3) calculations, which can create uncertainties in ozone forecasts, especially during the summertime when P(O3) is high. One way to test mechanisms is to compare modeled P(O3) to direct measurements. During summer 2014, the Measurement of Ozone Production Sensor (MOPS) directly measured net P(O3) in Golden, CO, approximately 25 km west of Denver along the Colorado Front Range. Net P(O3) was compared to rates calculated by a photochemical box model that was constrained by measurements of other chemical species and that used a lumped chemical mechanism and a more explicit one. Median observed P(O3) was up to a factor of 2 higher than that modeled during early morning hours when nitric oxide (NO) levels were high and was similar to modeled P(O3) for the rest of the day. While all interferences and offsets in this new method are not fully understood, simulations of these possible uncertainties cannot explain the observed P(O3) behavior. Modeled and measured P(O3) and peroxy radical (HO2 and RO2) discrepancies observed here are similar to those presented in prior studies. While a missing atmospheric organic peroxy radical source from volatile organic compounds co-emitted with NO could be one plausible solution to the P(O3) discrepancy, such a source has not been identified and does not fully explain the peroxy radical model-data mismatch. If the MOPS accurately depicts atmospheric P(O3), then these results would imply that P(O3) in Golden, CO, would be NOx-sensitive for more of the day than what is calculated by models, extending the NOx-sensitive P(O3) regime from the afternoon further into the morning. These results could affect ozone reduction strategies for the region surrounding Golden and possibly other areas that do not comply with national ozone regulations. Thus, it is important to continue the development of this direct ozone measurement technique to understand P(O3), especially under high-NOx regimes.

A MULTIPLE GRID APPROACH FOR OPEN CHANNEL FLOWS WITH STRONG SHOCKS. (R825200)

EPA Science Inventory

Abstract

Explicit finite difference schemes are being widely used for modeling open channel flows accompanied with shocks. A characteristic feature of explicit schemes is the small time step, which is limited by the CFL stability condition. To overcome this limitation,...

New explicit global asymptotic stability criteria for higher order difference equations

NASA Astrophysics Data System (ADS)

El-Morshedy, Hassan A.

2007-12-01

New explicit sufficient conditions for the asymptotic stability of the zero solution of higher order difference equations are obtained. These criteria can be applied to autonomous and nonautonomous equations. The celebrated Clark asymptotic stability criterion is improved. Also, applications to models from mathematical biology and macroeconomics are given.

Explicit Processing Demands Reveal Language Modality-Specific Organization of Working Memory

ERIC Educational Resources Information Center

Rudner, Mary; Ronnberg, Jerker

2008-01-01

The working memory model for Ease of Language Understanding (ELU) predicts that processing differences between language modalities emerge when cognitive demands are explicit. This prediction was tested in three working memory experiments with participants who were Deaf Signers (DS), Hearing Signers (HS), or Hearing Nonsigners (HN). Easily nameable…

Feasibility of Explicit Instruction in Adult Basic Education: Instructor-Learner Interaction Patterns

ERIC Educational Resources Information Center

Mellard, Daryl; Scanlon, David

2006-01-01

A strategic instruction model introduced into adult basic education classrooms yields insight into the feasibility of using direct and explicit instruction with adults with learning disabilities or other cognitive barriers to learning. Ecobehavioral assessment was used to describe and compare instructor-learner interaction patterns during learning…

Multiday production of condensing organic aerosol mass in urban and forest outflow

DOE PAGES

Lee-Taylor, J.; Hodzic, A.; Madronich, S.; ...

2014-07-03

Secondary organic aerosol (SOA) production in air masses containing either anthropogenic or biogenic (terpene-dominated) emissions is investigated using the explicit gas-phase chemical mechanism generator GECKO-A. Simulations show several-fold increases in SOA mass continuing for several days in the urban outflow, even as the initial air parcel is diluted into the regional atmosphere. The SOA mass increase in the forest outflow is more modest (∼50%) and of shorter duration (1–2 days). The production in the urban outflow stems from continuing oxidation of gas-phase precursors which persist in equilibrium with the particle phase, and can be attributed to multigenerational reaction products ofmore » both aromatics and alkanes. In particular we find large contributions from substituted maleic anhydrides and multi-substituted peroxide-bicyclic alkenes. The results show that the predicted production is a robust feature of our model even under changing atmospheric conditions, and contradict the notion that SOA undergoes little mass production beyond a short initial formation period. The results imply that anthropogenic aerosol precursors could influence the chemical and radiative characteristics of the atmosphere over an extremely wide region, and that SOA measurements near precursor sources may routinely underestimate this influence.« less

Explicit polarization: a quantum mechanical framework for developing next generation force fields.

PubMed

Gao, Jiali; Truhlar, Donald G; Wang, Yingjie; Mazack, Michael J M; Löffler, Patrick; Provorse, Makenzie R; Rehak, Pavel

2014-09-16

Conspectus Molecular mechanical force fields have been successfully used to model condensed-phase and biological systems for a half century. By means of careful parametrization, such classical force fields can be used to provide useful interpretations of experimental findings and predictions of certain properties. Yet, there is a need to further improve computational accuracy for the quantitative prediction of biomolecular interactions and to model properties that depend on the wave functions and not just the energy terms. A new strategy called explicit polarization (X-Pol) has been developed to construct the potential energy surface and wave functions for macromolecular and liquid-phase simulations on the basis of quantum mechanics rather than only using quantum mechanical results to fit analytic force fields. In this spirit, this approach is called a quantum mechanical force field (QMFF). X-Pol is a general fragment method for electronic structure calculations based on the partition of a condensed-phase or macromolecular system into subsystems ("fragments") to achieve computational efficiency. Here, intrafragment energy and the mutual electronic polarization of interfragment interactions are treated explicitly using quantum mechanics. X-Pol can be used as a general, multilevel electronic structure model for macromolecular systems, and it can also serve as a new-generation force field. As a quantum chemical model, a variational many-body (VMB) expansion approach is used to systematically improve interfragment interactions, including exchange repulsion, charge delocalization, dispersion, and other correlation energies. As a quantum mechanical force field, these energy terms are approximated by empirical functions in the spirit of conventional molecular mechanics. This Account first reviews the formulation of X-Pol, in the full variationally correct version, in the faster embedded version, and with systematic many-body improvements. We discuss illustrative examples involving water clusters (which show the power of two-body corrections), ethylmethylimidazolium acetate ionic liquids (which reveal that the amount of charge transfer between anion and cation is much smaller than what has been assumed in some classical simulations), and a solvated protein in aqueous solution (which shows that the average charge distribution of carbonyl groups along the polypeptide chain depends strongly on their position in the sequence, whereas they are fixed in most classical force fields). The development of QMFFs also offers an opportunity to extend the accuracy of biochemical simulations to areas where classical force fields are often insufficient, especially in the areas of spectroscopy, reactivity, and enzyme catalysis.

Three-Dimensional Modeling of Flow and Thermochemical Behavior in a Blast Furnace

NASA Astrophysics Data System (ADS)

Shen, Yansong; Guo, Baoyu; Chew, Sheng; Austin, Peter; Yu, Aibing

2015-02-01

An ironmaking blast furnace (BF) is a complex high-temperature moving bed reactor involving counter-, co- and cross-current flows of gas, liquid and solid, coupled with heat and mass exchange and chemical reactions. Two-dimensional (2D) models were widely used for understanding its internal state in the past. In this paper, a three-dimensional (3D) CFX-based mathematical model is developed for describing the internal state of a BF in terms of multiphase flow and the related thermochemical behavior, as well as process indicators. This model considers the intense interactions between gas, solid and liquid phases, and also their competition for the space. The model is applied to a BF covering from the burden surface at the top to the liquid surface in the hearth, where the raceway cavity is considered explicitly. The results show that the key in-furnace phenomena such as flow/temperature patterns and component distributions of solid, gas and liquid phases can be described and characterized in different regions inside the BF, including the gas and liquids flow circumferentially over the 3D raceway surface. The in-furnace distributions of key performance indicators such as reduction degree and gas utilization can also be predicted. This model offers a cost-effective tool to understand and control the complex BF flow and performance.

Through the Immune Looking Glass: A Model for Brain Memory Strategies

PubMed Central

Sánchez-Ramón, Silvia; Faure, Florence

2016-01-01

The immune system (IS) and the central nervous system (CNS) are complex cognitive networks involved in defining the identity (self) of the individual through recognition and memory processes that enable one to anticipate responses to stimuli. Brain memory has traditionally been classified as either implicit or explicit on psychological and anatomical grounds, with reminiscences of the evolutionarily-based innate-adaptive IS responses. Beyond the multineuronal networks of the CNS, we propose a theoretical model of brain memory integrating the CNS as a whole. This is achieved by analogical reasoning between the operational rules of recognition and memory processes in both systems, coupled to an evolutionary analysis. In this new model, the hippocampus is no longer specifically ascribed to explicit memory but rather it both becomes part of the innate (implicit) memory system and tightly controls the explicit memory system. Alike the antigen presenting cells for the IS, the hippocampus would integrate transient and pseudo-specific (i.e., danger-fear) memories and would drive the formation of long-term and highly specific or explicit memories (i.e., the taste of the Proust’s madeleine cake) by the more complex and recent, evolutionarily speaking, neocortex. Experimental and clinical evidence is provided to support the model. We believe that the singularity of this model’s approximation could help to gain a better understanding of the mechanisms operating in brain memory strategies from a large-scale network perspective. PMID:26869886

Deriving predicted no-effect concentrations (PNECs) for emerging contaminants in the river Po, Italy, using three approaches: Assessment factor, species sensitivity distribution and AQUATOX ecosystem modelling.

PubMed

Gredelj, Andrea; Barausse, Alberto; Grechi, Laura; Palmeri, Luca

2018-06-20

Over the past decades, per- and polyfluoroalkyl substances (PFASs) found in environmental matrices worldwide have raised concerns due to their toxicity, ubiquity and persistence. A widespread pollution of groundwater and surface waters caused by PFASs in Northern Italy has been recently discovered, becoming a major environmental issue, also because the exact risk for humans and nature posed by this contamination is unclear. Here, the Po River in Northern Italy was selected as a study area to assess the ecological risk posed by perfluoroalkyl acids (PFAAs), a class of PFASs, considering the noticeable concentration of various PFAAs detected in the Po waters over the past years. Moreover, the Po has a large environmental and socio-economic importance: it is the largest Italian river and drains a densely inhabited, intensely cultivated and heavily industrialized watershed. Predicted no-effect concentrations (PNECs) were derived using two regulated methodologies, assessment factors (AFs) and species sensitivity distribution (SSD), which rely on published ecotoxicological laboratory tests. Results were compared to those of a novel methodology using the mechanistic ecosystem model AQUATOX to compute PNECs in an ecologically-sound manner, i.e. considering physical, chemical, biological and ecological processes in the river. The model was used to quantify how the biomasses of the modelled taxa in the river food web deviated from natural conditions due to varying inputs of the chemicals. PNEC for each chemical was defined as the lowest chemical concentration causing a non-negligible yearly biomass loss for a simulated taxon with respect to a control simulation. The investigated PFAAs were Perfluorooctanoic acid (PFOA) and Perfluorooctanesulfonic acid (PFOS) as long-chained compounds, and Perfluorobutanoic acid (PFBA) and Perfluorobutanesulfonic acid (PFBS) as short-chained homologues. Two emerging contaminants, Linear Alkylbenzene Sulfonate (LAS) and triclosan, were also studied to assess the performance of the three methodologies for chemicals whose ecotoxicology and environmental fate are well-studied. The most precautionary approach was the use of AFs generally followed by SSD and then AQUATOX, except for PFOS, for which AQUATOX yielded a much lower PNEC compared to the other approaches since, unlike the other two methodologies, it explicitly simulates sublethal toxicity and indirect ecological effects. Our findings highlight that neglecting the role of ecological processes when extrapolating from laboratory tests to ecosystems can result in under-protective threshold concentrations for chemicals. Ecosystem models can complement existing laboratory-based methodologies, and the use of multiple methods for deriving PNECs can help to clarify uncertainty in ecological risk estimates. Copyright © 2018 Elsevier Ltd. All rights reserved.

Constant pH Molecular Dynamics of Proteins in Explicit Solvent with Proton Tautomerism

PubMed Central

Goh, Garrett B.; Hulbert, Benjamin S.; Zhou, Huiqing; Brooks, Charles L.

2015-01-01

pH is a ubiquitous regulator of biological activity, including protein-folding, protein-protein interactions and enzymatic activity. Existing constant pH molecular dynamics (CPHMD) models that were developed to address questions related to the pH-dependent properties of proteins are largely based on implicit solvent models. However, implicit solvent models are known to underestimate the desolvation energy of buried charged residues, increasing the error associated with predictions that involve internal ionizable residue that are important in processes like hydrogen transport and electron transfer. Furthermore, discrete water and ions cannot be modeled in implicit solvent, which are important in systems like membrane proteins and ion channels. We report on an explicit solvent constant pH molecular dynamics framework based on multi-site λ-dynamics (CPHMDMSλD). In the CPHMDMSλD framework, we performed seamless alchemical transitions between protonation and tautomeric states using multi-site λ-dynamics, and designed novel biasing potentials to ensure that the physical end-states are predominantly sampled. We show that explicit solvent CPHMDMSλD simulations model realistic pH-dependent properties of proteins such as the Hen-Egg White Lysozyme (HEWL), binding domain of 2-oxoglutarate dehydrogenase (BBL) and N-terminal domain of ribosomal L9 (NTL9), and the pKa predictions are in excellent agreement with experimental values, with a RMSE ranging from 0.72 to 0.84 pKa units. With the recent development of the explicit solvent CPHMDMSλD framework for nucleic acids, accurate modeling of pH-dependent properties of both major class of biomolecules – proteins and nucleic acids is now possible. PMID:24375620

On the application of multilevel modeling in environmental and ecological studies

USGS Publications Warehouse

Qian, Song S.; Cuffney, Thomas F.; Alameddine, Ibrahim; McMahon, Gerard; Reckhow, Kenneth H.

2010-01-01

This paper illustrates the advantages of a multilevel/hierarchical approach for predictive modeling, including flexibility of model formulation, explicitly accounting for hierarchical structure in the data, and the ability to predict the outcome of new cases. As a generalization of the classical approach, the multilevel modeling approach explicitly models the hierarchical structure in the data by considering both the within- and between-group variances leading to a partial pooling of data across all levels in the hierarchy. The modeling framework provides means for incorporating variables at different spatiotemporal scales. The examples used in this paper illustrate the iterative process of model fitting and evaluation, a process that can lead to improved understanding of the system being studied.

Explicit-Reflective Teaching Nature of Science as Embedded within the Science Topic: Interactive Historical Vignettes Technique

ERIC Educational Resources Information Center

Nur, Erdogan Melek; Fitnat, Koseoglu

2015-01-01

It is obvious that more extensive work is needed in developing historical materials that address nature of science (NOS) concepts that will be implemented by teachers. Owing to the importance of meeting this need, research problem of this study is to design historical vignettes focused on the concept of chemical equilibrium which lies at the heart…

Sensitivity of single column model simulations of Arctic springtime clouds to different cloud cover and mixed phase cloud parameterizations

NASA Astrophysics Data System (ADS)

Zhang, Junhua; Lohmann, Ulrike

2003-08-01

The single column model of the Canadian Centre for Climate Modeling and Analysis (CCCma) climate model is used to simulate Arctic spring cloud properties observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment. The model is driven by the rawinsonde observations constrained European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis data. Five cloud parameterizations, including three statistical and two explicit schemes, are compared and the sensitivity to mixed phase cloud parameterizations is studied. Using the original mixed phase cloud parameterization of the model, the statistical cloud schemes produce more cloud cover, cloud water, and precipitation than the explicit schemes and in general agree better with observations. The mixed phase cloud parameterization from ECMWF decreases the initial saturation specific humidity threshold of cloud formation. This improves the simulated cloud cover in the explicit schemes and reduces the difference between the different cloud schemes. On the other hand, because the ECMWF mixed phase cloud scheme does not consider the Bergeron-Findeisen process, less ice crystals are formed. This leads to a higher liquid water path and less precipitation than what was observed.

Modeling Complex Chemical Systems: Problems and Solutions

NASA Astrophysics Data System (ADS)

van Dijk, Jan

2016-09-01

Non-equilibrium plasmas in complex gas mixtures are at the heart of numerous contemporary technologies. They typically contain dozens to hundreds of species, involved in hundreds to thousands of reactions. Chemists and physicists have always been interested in what are now called chemical reduction techniques (CRT's). The idea of such CRT's is that they reduce the number of species that need to be considered explicitly without compromising the validity of the model. This is usually achieved on the basis of an analysis of the reaction time scales of the system under study, which identifies species that are in partial equilibrium after a given time span. The first such CRT that has been widely used in plasma physics was developed in the 1960's and resulted in the concept of effective ionization and recombination rates. It was later generalized to systems in which multiple levels are effected by transport. In recent years there has been a renewed interest in tools for chemical reduction and reaction pathway analysis. An example of the latter is the PumpKin tool. Another trend is that techniques that have previously been developed in other fields of science are adapted as to be able to handle the plasma state of matter. Examples are the Intrinsic Low Dimension Manifold (ILDM) method and its derivatives, which originate from combustion engineering, and the general-purpose Principle Component Analysis (PCA) technique. In this contribution we will provide an overview of the most common reduction techniques, then critically assess the pros and cons of the methods that have gained most popularity in recent years. Examples will be provided for plasmas in argon and carbon dioxide.

Current Challenges in Geothermal Reservoir Simulation

NASA Astrophysics Data System (ADS)

Driesner, T.

2016-12-01

Geothermal reservoir simulation has long been introduced as a valuable tool for geothermal reservoir management and research. Yet, the current generation of simulation tools faces a number of severe challenges, in particular in the application for novel types of geothermal resources such as supercritical reservoirs or hydraulic stimulation. This contribution reviews a number of key problems: Representing the magmatic heat source of high enthalpy resources in simulations. Current practice is representing the deeper parts of a high enthalpy reservoir by a heat flux or temperature boundary condition. While this is sufficient for many reservoir management purposes it precludes exploring the chances of very high enthalpy resources in the deepest parts of such systems as well as the development of reliable conceptual models. Recent 2D simulations with the CSMP++ simulation platform demonstrate the potential of explicitly including the heat source, namely for understanding supercritical resources. Geometrically realistic incorporation of discrete fracture networks in simulation. A growing number of simulation tools can, in principle, handle flow and heat transport in discrete fracture networks. However, solving the governing equations and representing the physical properties are often biased by introducing strongly simplifying assumptions. Including proper fracture mechanics in complex fracture network simulations remains an open challenge. Improvements of the simulating chemical fluid-rock interaction in geothermal reservoirs. Major improvements have been made towards more stable and faster numerical solvers for multicomponent chemical fluid rock interaction. However, the underlying thermodynamic models and databases are unable to correctly address a number of important regions in temperature-pressure-composition parameter space. Namely, there is currently no thermodynamic formalism to describe relevant chemical reactions in supercritical reservoirs. Overcoming this unsatisfactory situation requires fundamental research in high temperature physical chemistry rather than further numerical development.

Medical School Factors Associated with Changes in Implicit and Explicit Bias Against Gay and Lesbian People among 3492 Graduating Medical Students.

PubMed

Phelan, Sean M; Burke, Sara E; Hardeman, Rachel R; White, Richard O; Przedworski, Julia; Dovidio, John F; Perry, Sylvia P; Plankey, Michael; A Cunningham, Brooke; Finstad, Deborah; W Yeazel, Mark; van Ryn, Michelle

2017-11-01

Implicit and explicit bias among providers can influence the quality of healthcare. Efforts to address sexual orientation bias in new physicians are hampered by a lack of knowledge of school factors that influence bias among students. To determine whether medical school curriculum, role modeling, diversity climate, and contact with sexual minorities predict bias among graduating students against gay and lesbian people. Prospective cohort study. A sample of 4732 first-year medical students was recruited from a stratified random sample of 49 US medical schools in the fall of 2010 (81% response; 55% of eligible), of which 94.5% (4473) identified as heterosexual. Seventy-eight percent of baseline respondents (3492) completed a follow-up survey in their final semester (spring 2014). Medical school predictors included formal curriculum, role modeling, diversity climate, and contact with sexual minorities. Outcomes were year 4 implicit and explicit bias against gay men and lesbian women, adjusted for bias at year 1. In multivariate models, lower explicit bias against gay men and lesbian women was associated with more favorable contact with LGBT faculty, residents, students, and patients, and perceived skill and preparedness for providing care to LGBT patients. Greater explicit bias against lesbian women was associated with discrimination reported by sexual minority students (b = 1.43 [0.16, 2.71]; p = 0.03). Lower implicit sexual orientation bias was associated with more frequent contact with LGBT faculty, residents, students, and patients (b = -0.04 [-0.07, -0.01); p = 0.008). Greater implicit bias was associated with more faculty role modeling of discriminatory behavior (b = 0.34 [0.11, 0.57); p = 0.004). Medical schools may reduce bias against sexual minority patients by reducing negative role modeling, improving the diversity climate, and improving student preparedness to care for this population.

An image-based reaction field method for electrostatic interactions in molecular dynamics simulations of aqueous solutions

NASA Astrophysics Data System (ADS)

Lin, Yuchun; Baumketner, Andrij; Deng, Shaozhong; Xu, Zhenli; Jacobs, Donald; Cai, Wei

2009-10-01

In this paper, a new solvation model is proposed for simulations of biomolecules in aqueous solutions that combines the strengths of explicit and implicit solvent representations. Solute molecules are placed in a spherical cavity filled with explicit water, thus providing microscopic detail where it is most needed. Solvent outside of the cavity is modeled as a dielectric continuum whose effect on the solute is treated through the reaction field corrections. With this explicit/implicit model, the electrostatic potential represents a solute molecule in an infinite bath of solvent, thus avoiding unphysical interactions between periodic images of the solute commonly used in the lattice-sum explicit solvent simulations. For improved computational efficiency, our model employs an accurate and efficient multiple-image charge method to compute reaction fields together with the fast multipole method for the direct Coulomb interactions. To minimize the surface effects, periodic boundary conditions are employed for nonelectrostatic interactions. The proposed model is applied to study liquid water. The effect of model parameters, which include the size of the cavity, the number of image charges used to compute reaction field, and the thickness of the buffer layer, is investigated in comparison with the particle-mesh Ewald simulations as a reference. An optimal set of parameters is obtained that allows for a faithful representation of many structural, dielectric, and dynamic properties of the simulated water, while maintaining manageable computational cost. With controlled and adjustable accuracy of the multiple-image charge representation of the reaction field, it is concluded that the employed model achieves convergence with only one image charge in the case of pure water. Future applications to pKa calculations, conformational sampling of solvated biomolecules and electrolyte solutions are briefly discussed.

Boreal forest BVOC exchange: emissions versus in-canopy sinks

NASA Astrophysics Data System (ADS)

Zhou, Putian; Ganzeveld, Laurens; Taipale, Ditte; Rannik, Üllar; Rantala, Pekka; Petteri Rissanen, Matti; Chen, Dean; Boy, Michael

2017-12-01

A multilayer gas dry deposition model has been developed and implemented into a one-dimensional chemical transport model SOSAA (model to Simulate the concentrations of Organic vapours, Sulphuric Acid and Aerosols) to calculate the dry deposition velocities for all the gas species included in the chemistry scheme. The new model was used to analyse in-canopy sources and sinks, including gas emissions, chemical production and loss, dry deposition, and turbulent transport of 12 featured biogenic volatile organic compounds (BVOCs) or groups of BVOCs (e.g. monoterpenes, isoprene+2-methyl-3-buten-2-ol (MBO), sesquiterpenes, and oxidation products of mono- and sesquiterpenes) in July 2010 at the boreal forest site SMEAR II (Station for Measuring Ecosystem-Atmosphere Relations). According to the significance of modelled monthly-averaged individual source and sink terms inside the canopy, the selected BVOCs were classified into five categories: 1. Most of emitted gases are transported out of the canopy (monoterpenes, isoprene + MBO). 2. Chemical reactions remove a significant portion of emitted gases (sesquiterpenes). 3. Bidirectional fluxes occur since both emission and dry deposition are crucial for the in-canopy concentration tendency (acetaldehyde, methanol, acetone, formaldehyde). 4. Gases removed by deposition inside the canopy are compensated for by the gases transported from above the canopy (acetol, pinic acid, β-caryophyllene's oxidation product BCSOZOH). 5. The chemical production is comparable to the sink by deposition (isoprene's oxidation products ISOP34OOH and ISOP34NO3). Most of the simulated sources and sinks were located above about 0.2 hc (canopy height) for oxidation products and above about 0.4 hc for emitted species except formaldehyde. In addition, soil deposition (including deposition onto understorey vegetation) contributed 11-61 % to the overall in-canopy deposition. The emission sources peaked at about 0.8-0.9 hc, which was higher than 0.6 hc where the maximum of dry deposition onto overstorey vegetation was located. This study provided a method to enable the quantification of the exchange between atmosphere and biosphere for numerous BVOCs, which could be applied in large-scale models in future. With this more explicit canopy exchange modelling system, this study analysed both the temporal and spatial variations in individual in-canopy sources and sinks, as well as their combined effects on driving BVOC exchange. In this study 12 featured BVOCs or BVOC groups were analysed. Other compounds could also be investigated similarly by being classified into these five categories.

Assessing the Role of Shape and Label in the Misleading Packaging of Food Imitating Products: From Empirical Evidence to Policy Recommendation

PubMed Central

Basso, Frédéric; Bouillé, Julien; Le Goff, Kévin; Robert-Demontrond, Philippe; Oullier, Olivier

2016-01-01

Food imitating products are chemical consumer items used frequently in the household for cleaning and personal hygiene (e.g., bleach, soap, and shampoo), which resemble food products. Their containers replicate elements of food package design such as possessing a shape close in style to drinking product containers or bearing labels that depict colorful fruits. In marketing, these incongruent forms are designed to increase the appeal of functional products, leading to chemical consumer product embellishment. However, due to the resulting visual ambiguity, food imitating products may expose consumers to the risk of being poisoned from ingestion. Thus, from a public health perspective, food imitating products are considered dangerous chemical products that should not be sold, and may merit being recalled for the safety of consumers. To help policymakers address the hazardous presence of food imitating products, the purpose of this article is to identify the specific design features that generate most ambiguity for the consumer, and therefore increase the likelihood of confusion with foodstuffs. Among the visual elements of food packaging, the two most important features (shape and label) are manipulated in a series of three lab studies combining six Implicit Association Tests (IATs) and two explicit measures on products' drinkability and safety. IATs were administered to assess consumers' implicit association of liquid products with tastiness in a within-subject design in which the participants (N = 122) were presented with two kinds of food imitating products with a drink shape or drink label compared with drinks (experiential products with congruent form) and classic chemical products (hygiene products) (functional products with congruent form). Results show that chemical consumer products with incongruent drink shapes (but not drink labels) as an element of food package design are both implicitly associated with tastiness and explicitly judged as safe and drinkable. These results require confirmation in other studies involving different shapes and labels. Notwithstanding, due to the misleading effect of this ambiguity, public health authorities are thus well advised to focus their market surveillance on chemical products emulating a food or drink shape. PMID:27065919

A fragment-based approach to the SAMPL3 Challenge

NASA Astrophysics Data System (ADS)

Kulp, John L.; Blumenthal, Seth N.; Wang, Qiang; Bryan, Richard L.; Guarnieri, Frank

2012-05-01

The success of molecular fragment-based design depends critically on the ability to make predictions of binding poses and of affinity ranking for compounds assembled by linking fragments. The SAMPL3 Challenge provides a unique opportunity to evaluate the performance of a state-of-the-art fragment-based design methodology with respect to these requirements. In this article, we present results derived from linking fragments to predict affinity and pose in the SAMPL3 Challenge. The goal is to demonstrate how incorporating different aspects of modeling protein-ligand interactions impact the accuracy of the predictions, including protein dielectric models, charged versus neutral ligands, ΔΔGs solvation energies, and induced conformational stress. The core method is based on annealing of chemical potential in a Grand Canonical Monte Carlo (GC/MC) simulation. By imposing an initially very high chemical potential and then automatically running a sequence of simulations at successively decreasing chemical potentials, the GC/MC simulation efficiently discovers statistical distributions of bound fragment locations and orientations not found reliably without the annealing. This method accounts for configurational entropy, the role of bound water molecules, and results in a prediction of all the locations on the protein that have any affinity for the fragment. Disregarding any of these factors in affinity-rank prediction leads to significantly worse correlation with experimentally-determined free energies of binding. We relate three important conclusions from this challenge as applied to GC/MC: (1) modeling neutral ligands—regardless of the charged state in the active site—produced better affinity ranking than using charged ligands, although, in both cases, the poses were almost exactly overlaid; (2) simulating explicit water molecules in the GC/MC gave better affinity and pose predictions; and (3) applying a ΔΔGs solvation correction further improved the ranking of the neutral ligands. Using the GC/MC method under a variety of parameters in the blinded SAMPL3 Challenge provided important insights to the relevant parameters and boundaries in predicting binding affinities using simulated annealing of chemical potential calculations.

Evaluation and Validation of a TCAT Model to Describe Non-Dilute Flow and Species Transport in Porous Media

NASA Astrophysics Data System (ADS)

Weigand, T. M.; Harrison, E.; Miller, C. T.

2017-12-01

A thermodynamically constrained averaging theory (TCAT) model has been developed to simulate non-dilute flow and species transport in porous media. This model has the advantages of a firm connection between the microscale, or pore scale, and the macroscale; a thermodynamically consistent basis; the explicit inclusion of dissipative terms that arise from spatial gradients in pressure and chemical activity; and the ability to describe both high and low concentration displacement. The TCAT model has previously been shown to provide excellent agreement for a set of laboratory data and outperformed existing macroscale models that have been used for non-dilute flow and transport. The examined experimental dataset consisted of stable brine displacements for a large range of fluid properties. This dataset however only examined one type of porous media and had a fixed flow rate for all experiments. In this work, the TCAT model is applied to a dataset that consists of two different porous media types, constant head and flow rate conditions, varying resident fluid concentrations, and internal probes that measured the pressure and salt mass fraction. Parameter estimation is performed on a subset of the experimental data for the TCAT model as well as other existing non-dilute flow and transport models. The optimized parameters are then used for forward simulations and the accuracy of the models is compared.

Age-related differences in brain activity during implicit and explicit processing of fearful facial expressions.

PubMed

Zsoldos, Isabella; Cousin, Emilie; Klein-Koerkamp, Yanica; Pichat, Cédric; Hot, Pascal

2016-11-01

Age-related differences in neural correlates underlying implicit and explicit emotion processing are unclear. Within the framework of the Frontoamygdalar Age-related Differences in Emotion model (St Jacques et al., 2009), our objectives were to examine the behavioral and neural modifications that occur with age for both processes. During explicit and implicit processing of fearful faces, we expected to observe less amygdala activity in older adults (OA) than in younger adults (YA), associated with poorer recognition performance in the explicit task, and more frontal activity during implicit processing, suggesting compensation. At a behavioral level, explicit recognition of fearful faces was impaired in OA compared with YA. We did not observe any cerebral differences between OA and YA during the implicit task, whereas in the explicit task, OA recruited more frontal, parietal, temporal, occipital, and cingulate areas. Our findings suggest that automatic processing of emotion may be preserved during aging, whereas deliberate processing is impaired. Additional neural recruitment in OA did not appear to compensate for their behavioral deficits. Copyright © 2016 Elsevier B.V. All rights reserved.

Simulation of large-scale rule-based models

PubMed Central

Colvin, Joshua; Monine, Michael I.; Faeder, James R.; Hlavacek, William S.; Von Hoff, Daniel D.; Posner, Richard G.

2009-01-01

Motivation: Interactions of molecules, such as signaling proteins, with multiple binding sites and/or multiple sites of post-translational covalent modification can be modeled using reaction rules. Rules comprehensively, but implicitly, define the individual chemical species and reactions that molecular interactions can potentially generate. Although rules can be automatically processed to define a biochemical reaction network, the network implied by a set of rules is often too large to generate completely or to simulate using conventional procedures. To address this problem, we present DYNSTOC, a general-purpose tool for simulating rule-based models. Results: DYNSTOC implements a null-event algorithm for simulating chemical reactions in a homogenous reaction compartment. The simulation method does not require that a reaction network be specified explicitly in advance, but rather takes advantage of the availability of the reaction rules in a rule-based specification of a network to determine if a randomly selected set of molecular components participates in a reaction during a time step. DYNSTOC reads reaction rules written in the BioNetGen language which is useful for modeling protein–protein interactions involved in signal transduction. The method of DYNSTOC is closely related to that of StochSim. DYNSTOC differs from StochSim by allowing for model specification in terms of BNGL, which extends the range of protein complexes that can be considered in a model. DYNSTOC enables the simulation of rule-based models that cannot be simulated by conventional methods. We demonstrate the ability of DYNSTOC to simulate models accounting for multisite phosphorylation and multivalent binding processes that are characterized by large numbers of reactions. Availability: DYNSTOC is free for non-commercial use. The C source code, supporting documentation and example input files are available at http://public.tgen.org/dynstoc/. Contact: dynstoc@tgen.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19213740

Multiscale Multiphysics and Multidomain Models I: Basic Theory

PubMed Central

Wei, Guo-Wei

2013-01-01

This work extends our earlier two-domain formulation of a differential geometry based multiscale paradigm into a multidomain theory, which endows us the ability to simultaneously accommodate multiphysical descriptions of aqueous chemical, physical and biological systems, such as fuel cells, solar cells, nanofluidics, ion channels, viruses, RNA polymerases, molecular motors and large macromolecular complexes. The essential idea is to make use of the differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain of solvent from the microscopic domain of solute, and dynamically couple continuum and discrete descriptions. Our main strategy is to construct energy functionals to put on an equal footing of multiphysics, including polar (i.e., electrostatic) solvation, nonpolar solvation, chemical potential, quantum mechanics, fluid mechanics, molecular mechanics, coarse grained dynamics and elastic dynamics. The variational principle is applied to the energy functionals to derive desirable governing equations, such as multidomain Laplace-Beltrami (LB) equations for macromolecular morphologies, multidomain Poisson-Boltzmann (PB) equation or Poisson equation for electrostatic potential, generalized Nernst-Planck (NP) equations for the dynamics of charged solvent species, generalized Navier-Stokes (NS) equation for fluid dynamics, generalized Newton's equations for molecular dynamics (MD) or coarse-grained dynamics and equation of motion for elastic dynamics. Unlike the classical PB equation, our PB equation is an integral-differential equation due to solvent-solute interactions. To illustrate the proposed formalism, we have explicitly constructed three models, a multidomain solvation model, a multidomain charge transport model and a multidomain chemo-electro-fluid-MD-elastic model. Each solute domain is equipped with distinct surface tension, pressure, dielectric function, and charge density distribution. In addition to long-range Coulombic interactions, various non-electrostatic solvent-solute interactions are considered in the present modeling. We demonstrate the consistency between the non-equilibrium charge transport model and the equilibrium solvation model by showing the systematical reduction of the former to the latter at equilibrium. This paper also offers a brief review of the field. PMID:25382892

Multiscale Multiphysics and Multidomain Models I: Basic Theory.

PubMed

Wei, Guo-Wei

2013-12-01

This work extends our earlier two-domain formulation of a differential geometry based multiscale paradigm into a multidomain theory, which endows us the ability to simultaneously accommodate multiphysical descriptions of aqueous chemical, physical and biological systems, such as fuel cells, solar cells, nanofluidics, ion channels, viruses, RNA polymerases, molecular motors and large macromolecular complexes. The essential idea is to make use of the differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain of solvent from the microscopic domain of solute, and dynamically couple continuum and discrete descriptions. Our main strategy is to construct energy functionals to put on an equal footing of multiphysics, including polar (i.e., electrostatic) solvation, nonpolar solvation, chemical potential, quantum mechanics, fluid mechanics, molecular mechanics, coarse grained dynamics and elastic dynamics. The variational principle is applied to the energy functionals to derive desirable governing equations, such as multidomain Laplace-Beltrami (LB) equations for macromolecular morphologies, multidomain Poisson-Boltzmann (PB) equation or Poisson equation for electrostatic potential, generalized Nernst-Planck (NP) equations for the dynamics of charged solvent species, generalized Navier-Stokes (NS) equation for fluid dynamics, generalized Newton's equations for molecular dynamics (MD) or coarse-grained dynamics and equation of motion for elastic dynamics. Unlike the classical PB equation, our PB equation is an integral-differential equation due to solvent-solute interactions. To illustrate the proposed formalism, we have explicitly constructed three models, a multidomain solvation model, a multidomain charge transport model and a multidomain chemo-electro-fluid-MD-elastic model. Each solute domain is equipped with distinct surface tension, pressure, dielectric function, and charge density distribution. In addition to long-range Coulombic interactions, various non-electrostatic solvent-solute interactions are considered in the present modeling. We demonstrate the consistency between the non-equilibrium charge transport model and the equilibrium solvation model by showing the systematical reduction of the former to the latter at equilibrium. This paper also offers a brief review of the field.

An SOA model for toluene oxidation in the presence of inorganic aerosols.

PubMed

Cao, Gang; Jang, Myoseon

2010-01-15

A predictive model for secondary organic aerosol (SOA) formation including both partitioning and heterogeneous reactions is explored for the SOA produced from the oxidation of toluene in the presence of inorganic seed aerosols. The predictive SOA model comprises the explicit gas-phase chemistry of toluene, gas-particle partitioning, and heterogeneous chemistry. The resulting products from the explicit gas phase chemistry are lumped into several classes of chemical species based on their vapor pressure and reactivity for heterogeneous reactions. Both the gas-particle partitioning coefficient and the heterogeneous reaction rate constant of each lumped gas-phase product are theoretically determined using group contribution and molecular structure-reactivity. In the SOA model, the predictive SOA mass is decoupled into partitioning (OM(P)) and heterogeneous aerosol production (OM(H)). OM(P) is estimated from the SOA partitioning model developed by Schell et al. (J. Geophys. Res. 2001, 106, 28275-28293 ) that has been used in a regional air quality model (CMAQ 4.7). OM(H) is predicted from the heterogeneous SOA model developed by Jang et al. (Environ. Sci. Technol. 2006, 40, 3013-3022 ). The SOA model is evaluated using a number of the experimental SOA data that are generated in a 2 m(3) indoor Teflon film chamber under various experimental conditions (e.g., humidity, inorganic seed compositions, NO(x) concentrations). The SOA model reasonably predicts not only the gas-phase chemistry, such as the ozone formation, the conversion of NO to NO(2), and the toluene decay, but also the SOA production. The model predicted that the OM(H) fraction of the total toluene SOA mass increases as NO(x) concentrations decrease: 0.73-0.83 at low NO(x) levels and 0.17-0.47 at middle and high NO(x) levels for SOA experiments with high initial toluene concentrations. Our study also finds a significant increase in the OM(H) mass fraction in the SOA generated with low initial toluene concentrations, compared to those with high initial toluene concentrations. On average, more than a 1-fold increase in OM(H) fraction is observed when the comparison is made between SOA experiments with 40 ppb toluene to those with 630 ppb toluene. Such an observation implies that heterogeneous reactions of the second-generation products of toluene oxidation can contribute considerably to the total SOA mass under atmospheric relevant conditions.

An explicit mixed numerical method for mesoscale model

NASA Technical Reports Server (NTRS)

Hsu, H.-M.

1981-01-01

A mixed numerical method has been developed for mesoscale models. The technique consists of a forward difference scheme for time tendency terms, an upstream scheme for advective terms, and a central scheme for the other terms in a physical system. It is shown that the mixed method is conditionally stable and highly accurate for approximating the system of either shallow-water equations in one dimension or primitive equations in three dimensions. Since the technique is explicit and two time level, it conserves computer and programming resources.

Initialization and assimilation of cloud and rainwater in a regional model

NASA Technical Reports Server (NTRS)

Raymond, William H.; Olson, William S.

1990-01-01

The initialization and assimilation of cloud and rainwater quantities in a mesoscale regional model was examined. Forecasts of explicit cloud and rainwater are made using conservation equations. The physical processes include condensation, evaporation, autoconversion, accretion, and the removal of rainwater by fallout. These physical processes, some of which are parameterized, represent source and sink in terms in the conservation equations. The question of how to initialize the explicit liquid water calculations in numerical models and how to retain information about precipitation processes during the 4-D assimilation cycle are important issues that are addressed.

Automation based on knowledge modeling theory and its applications in engine diagnostic systems using Space Shuttle Main Engine vibrational data. M.S. Thesis

NASA Technical Reports Server (NTRS)

Kim, Jonnathan H.

1995-01-01

Humans can perform many complicated tasks without explicit rules. This inherent and advantageous capability becomes a hurdle when a task is to be automated. Modern computers and numerical calculations require explicit rules and discrete numerical values. In order to bridge the gap between human knowledge and automating tools, a knowledge model is proposed. Knowledge modeling techniques are discussed and utilized to automate a labor and time intensive task of detecting anomalous bearing wear patterns in the Space Shuttle Main Engine (SSME) High Pressure Oxygen Turbopump (HPOTP).

Effect of the explicit flexibility of the InhA enzyme from Mycobacterium tuberculosis in molecular docking simulations.

PubMed

Cohen, Elisangela M L; Machado, Karina S; Cohen, Marcelo; de Souza, Osmar Norberto

2011-12-22

Protein/receptor explicit flexibility has recently become an important feature of molecular docking simulations. Taking the flexibility into account brings the docking simulation closer to the receptors' real behaviour in its natural environment. Several approaches have been developed to address this problem. Among them, modelling the full flexibility as an ensemble of snapshots derived from a molecular dynamics simulation (MD) of the receptor has proved very promising. Despite its potential, however, only a few studies have employed this method to probe its effect in molecular docking simulations. We hereby use ensembles of snapshots obtained from three different MD simulations of the InhA enzyme from M. tuberculosis (Mtb), the wild-type (InhA_wt), InhA_I16T, and InhA_I21V mutants to model their explicit flexibility, and to systematically explore their effect in docking simulations with three different InhA inhibitors, namely, ethionamide (ETH), triclosan (TCL), and pentacyano(isoniazid)ferrate(II) (PIF). The use of fully-flexible receptor (FFR) models of InhA_wt, InhA_I16T, and InhA_I21V mutants in docking simulation with the inhibitors ETH, TCL, and PIF revealed significant differences in the way they interact as compared to the rigid, InhA crystal structure (PDB ID: 1ENY). In the latter, only up to five receptor residues interact with the three different ligands. Conversely, in the FFR models this number grows up to an astonishing 80 different residues. The comparison between the rigid crystal structure and the FFR models showed that the inclusion of explicit flexibility, despite the limitations of the FFR models employed in this study, accounts in a substantial manner to the induced fit expected when a protein/receptor and ligand approach each other to interact in the most favourable manner. Protein/receptor explicit flexibility, or FFR models, represented as an ensemble of MD simulation snapshots, can lead to a more realistic representation of the induced fit effect expected in the encounter and proper docking of receptors to ligands. The FFR models of InhA explicitly characterizes the overall movements of the amino acid residues in helices, strands, loops, and turns, allowing the ligand to properly accommodate itself in the receptor's binding site. Utilization of the intrinsic flexibility of Mtb's InhA enzyme and its mutants in virtual screening via molecular docking simulation may provide a novel platform to guide the rational or dynamical-structure-based drug design of novel inhibitors for Mtb's InhA. We have produced a short video sequence of each ligand (ETH, TCL and PIF) docked to the FFR models of InhA_wt. These videos are available at http://www.inf.pucrs.br/~osmarns/LABIO/Videos_Cohen_et_al_19_07_2011.htm.

Toward an Optimal Pedagogy for Teamwork.

PubMed

Earnest, Mark A; Williams, Jason; Aagaard, Eva M

2017-10-01

Teamwork and collaboration are increasingly listed as core competencies for undergraduate health professions education. Despite the clear mandate for teamwork training, the optimal method for providing that training is much less certain. In this Perspective, the authors propose a three-level classification of pedagogical approaches to teamwork training based on the presence of two key learning factors: interdependent work and explicit training in teamwork. In this classification framework, level 1-minimal team learning-is where learners work in small groups but neither of the key learning factors is present. Level 2-implicit team learning-engages learners in interdependent learning activities but does not include an explicit focus on teamwork. Level 3-explicit team learning-creates environments where teams work interdependently toward common goals and are given explicit instruction and practice in teamwork. The authors provide examples that demonstrate each level. They then propose that the third level of team learning, explicit team learning, represents a best practice approach in teaching teamwork, highlighting their experience with an explicit team learning course at the University of Colorado Anschutz Medical Campus. Finally, they discuss several challenges to implementing explicit team-learning-based curricula: the lack of a common teamwork model on which to anchor such a curriculum; the question of whether the knowledge, skills, and attitudes acquired during training would be transferable to the authentic clinical environment; and effectively evaluating the impact of explicit team learning.

Spatially explicit shallow landslide susceptibility mapping over large areas

Treesearch

Dino Bellugi; William E. Dietrich; Jonathan Stock; Jim McKean; Brian Kazian; Paul Hargrove

2011-01-01

Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so...

Evaluating spatially explicit burn probabilities for strategic fire management planning

Treesearch

C. Miller; M.-A. Parisien; A. A. Ager; M. A. Finney

2008-01-01

Spatially explicit information on the probability of burning is necessary for virtually all strategic fire and fuels management planning activities, including conducting wildland fire risk assessments, optimizing fuel treatments, and prevention planning. Predictive models providing a reliable estimate of the annual likelihood of fire at each point on the landscape have...

Beyond the Sponge Model: Encouraging Students' Questioning Skills in Abnormal Psychology.

ERIC Educational Resources Information Center

Keeley, Stuart M.; Ali, Rahan; Gebing, Tracy

1998-01-01

Argues that educators should provide students with explicit training in asking critical questions. Describes a training strategy taught in abnormal psychology courses at Bowling Green State University (Ohio). Based on a pre- and post-test, results support the promise of using explicit questioning training in promoting the evaluative aspects of…

A Conceptual Model for the Design and Delivery of Explicit Thinking Skills Instruction

ERIC Educational Resources Information Center

Kassem, Cherrie L.

2005-01-01

Developing student thinking skills is an important goal for most educators. However, due to time constraints and weighty content standards, thinking skills instruction is often embedded in subject matter, implicit and incidental. For best results, thinking skills instruction requires a systematic design and explicit teaching strategies. The…

Fully implicit Particle-in-cell algorithms for multiscale plasma simulation

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

Chacon, Luis

The outline of the paper is as follows: Particle-in-cell (PIC) methods for fully ionized collisionless plasmas, explicit vs. implicit PIC, 1D ES implicit PIC (charge and energy conservation, moment-based acceleration), and generalization to Multi-D EM PIC: Vlasov-Darwin model (review and motivation for Darwin model, conservation properties (energy, charge, and canonical momenta), and numerical benchmarks). The author demonstrates a fully implicit, fully nonlinear, multidimensional PIC formulation that features exact local charge conservation (via a novel particle mover strategy), exact global energy conservation (no particle self-heating or self-cooling), adaptive particle orbit integrator to control errors in momentum conservation, and canonical momenta (EM-PICmore » only, reduced dimensionality). The approach is free of numerical instabilities: ω peΔt >> 1, and Δx >> λ D. It requires many fewer dofs (vs. explicit PIC) for comparable accuracy in challenging problems. Significant CPU gains (vs explicit PIC) have been demonstrated. The method has much potential for efficiency gains vs. explicit in long-time-scale applications. Moment-based acceleration is effective in minimizing N FE, leading to an optimal algorithm.« less

Application of a flexible lattice Boltzmann method based simulation tool for modelling physico-chemical processes at different scales

NASA Astrophysics Data System (ADS)

Patel, Ravi A.; Perko, Janez; Jacques, Diederik

2017-04-01

Often, especially in the disciplines related to natural porous media, such as for example vadoze zone or aquifer hydrology or contaminant transport, the relevant spatial and temporal scales on which we need to provide information is larger than the scale where the processes actually occur. Usual techniques used to deal with these problems assume the existence of a REV. However, in order to understand the behavior on larger scales it is important to downscale the problem onto the relevant scale of the processes. Due to the limitations of resources (time, memory) the downscaling can only be made up to the certain lower scale. At this lower scale still several scales may co-exist - the scale which can be explicitly described and a scale which needs to be conceptualized by effective properties. Hence, models which are supposed to provide effective properties on relevant scales should therefor be flexible enough to represent complex pore-structure by explicit geometry on one side, and differently defined processes (e.g. by the effective properties) which emerge on lower scale. In this work we present the state-of-the-art lattice Boltzmann method based simulation tool applicable to advection-diffusion equation coupled to geochemical processes. The lattice Boltzmann transport solver can be coupled with an external geochemical solver which allows to account for a wide range of geochemical reaction networks through thermodynamic databases. The applicability to multiphase systems is ongoing. We provide several examples related to the calculation of an effective diffusion properties, permeability and effective reaction rate based on a continuum scale based on the pore scale geometry.

Quantifying the Impact of BOReal Forest Fires on Tropospheric Oxidants Over the Atlantic Using Aircraft and Satellites (BORTAS) Experiment: Design, Execution, and Science Overview

NASA Technical Reports Server (NTRS)

Palmer, Paul I.; Parrington, Mark; Lee, James D.; Lewis, Alistair C.; Richard, Andrew R.; Bernath, Peter F.; Pawson, Steven; daSilva, Arlindo M.; Duck, Thomas J.; Waugh, David L.;

Structure and dynamics of human vimentin intermediate filament dimer and tetramer in explicit and implicit solvent models.

PubMed

Qin, Zhao; Buehler, Markus J

2011-01-01

Intermediate filaments, in addition to microtubules and microfilaments, are one of the three major components of the cytoskeleton in eukaryotic cells, and play an important role in mechanotransduction as well as in providing mechanical stability to cells at large stretch. The molecular structures, mechanical and dynamical properties of the intermediate filament basic building blocks, the dimer and the tetramer, however, have remained elusive due to persistent experimental challenges owing to the large size and fibrillar geometry of this protein. We have recently reported an atomistic-level model of the human vimentin dimer and tetramer, obtained through a bottom-up approach based on structural optimization via molecular simulation based on an implicit solvent model (Qin et al. in PLoS ONE 2009 4(10):e7294, 9). Here we present extensive simulations and structural analyses of the model based on ultra large-scale atomistic-level simulations in an explicit solvent model, with system sizes exceeding 500,000 atoms and simulations carried out at 20 ns time-scales. We report a detailed comparison of the structural and dynamical behavior of this large biomolecular model with implicit and explicit solvent models. Our simulations confirm the stability of the molecular model and provide insight into the dynamical properties of the dimer and tetramer. Specifically, our simulations reveal a heterogeneous distribution of the bending stiffness along the molecular axis with the formation of rather soft and highly flexible hinge-like regions defined by non-alpha-helical linker domains. We report a comparison of Ramachandran maps and the solvent accessible surface area between implicit and explicit solvent models, and compute the persistence length of the dimer and tetramer structure of vimentin intermediate filaments for various subdomains of the protein. Our simulations provide detailed insight into the dynamical properties of the vimentin dimer and tetramer intermediate filament building blocks, which may guide the development of novel coarse-grained models of intermediate filaments, and could also help in understanding assembly mechanisms.

Rapid Response Tools and Datasets for Post-fire Hydrological Modeling

NASA Astrophysics Data System (ADS)

Miller, Mary Ellen; MacDonald, Lee H.; Billmire, Michael; Elliot, William J.; Robichaud, Pete R.

2016-04-01

Rapid response is critical following natural disasters. Flooding, erosion, and debris flows are a major threat to life, property and municipal water supplies after moderate and high severity wildfires. The problem is that mitigation measures must be rapidly implemented if they are to be effective, but they are expensive and cannot be applied everywhere. Fires, runoff, and erosion risks also are highly heterogeneous in space, so there is an urgent need for a rapid, spatially-explicit assessment. Past post-fire modeling efforts have usually relied on lumped, conceptual models because of the lack of readily available, spatially-explicit data layers on the key controls of topography, vegetation type, climate, and soil characteristics. The purpose of this project is to develop a set of spatially-explicit data layers for use in process-based models such as WEPP, and to make these data layers freely available. The resulting interactive online modeling database (http://geodjango.mtri.org/geowepp/) is now operational and publically available for 17 western states in the USA. After a fire, users only need to upload a soil burn severity map, and this is combined with the pre-existing data layers to generate the model inputs needed for spatially explicit models such as GeoWEPP (Renschler, 2003). The development of this online database has allowed us to predict post-fire erosion and various remediation scenarios in just 1-7 days for six fires ranging in size from 4-540 km2. These initial successes have stimulated efforts to further improve the spatial extent and amount of data, and add functionality to support the USGS debris flow model, batch processing for Disturbed WEPP (Elliot et al., 2004) and ERMiT (Robichaud et al., 2007), and to support erosion modeling for other land uses, such as agriculture or mining. The design and techniques used to create the database and the modeling interface are readily repeatable for any area or country that has the necessary topography, climate, soil, and land cover datasets.

The national stream quality accounting network: A flux-basedapproach to monitoring the water quality of large rivers

USGS Publications Warehouse

Hooper, R.P.; Aulenbach, Brent T.; Kelly, V.J.

2001-01-01

Estimating the annual mass flux at a network of fixed stations is one approach to characterizing water quality of large rivers. The interpretive context provided by annual flux includes identifying source and sink areas for constituents and estimating the loadings to receiving waters, such as reservoirs or the ocean. Since 1995, the US Geological Survey's National Stream Quality Accounting Network (NASQAN) has employed this approach at a network of 39 stations in four of the largest river basins of the USA: The Mississippi, the Columbia, the Colorado and the Rio Grande. In this paper, the design of NASQAN is described and its effectiveness at characterizing the water quality of these rivers is evaluated using data from the first 3 years of operation. A broad range of constituents was measured by NASQAN, including trace organic and inorganic chemicals, major ions, sediment and nutrients. Where possible, a regression model relating concentration to discharge and season was used to interpolate between chemical observations for flux estimation. For water-quality network design, the most important finding from NASQAN was the importance of having a specific objective (that is, estimating annual mass flux) and, from that, an explicitly stated data analysis strategy, namely the use of regression models to interpolate between observations. The use of such models aided in the design of sampling strategy and provided a context for data review. The regression models essentially form null hypotheses for concentration variation that can be evaluated by the observed data. The feedback between network operation and data collection established by the hypothesis tests places the water-quality network on a firm scientific footing.