Agent-based modeling as a tool for program design and evaluation.

PubMed

Lawlor, Jennifer A; McGirr, Sara

2017-12-01

Recently, systems thinking and systems science approaches have gained popularity in the field of evaluation; however, there has been relatively little exploration of how evaluators could use quantitative tools to assist in the implementation of systems approaches therein. The purpose of this paper is to explore potential uses of one such quantitative tool, agent-based modeling, in evaluation practice. To this end, we define agent-based modeling and offer potential uses for it in typical evaluation activities, including: engaging stakeholders, selecting an intervention, modeling program theory, setting performance targets, and interpreting evaluation results. We provide demonstrative examples from published agent-based modeling efforts both inside and outside the field of evaluation for each of the evaluative activities discussed. We further describe potential pitfalls of this tool and offer cautions for evaluators who may chose to implement it in their practice. Finally, the article concludes with a discussion of the future of agent-based modeling in evaluation practice and a call for more formal exploration of this tool as well as other approaches to simulation modeling in the field. Copyright © 2017 Elsevier Ltd. All rights reserved.

Potential formulation of sleep dynamics

NASA Astrophysics Data System (ADS)

Phillips, A. J. K.; Robinson, P. A.

2009-02-01

A physiologically based model of the mechanisms that control the human sleep-wake cycle is formulated in terms of an equivalent nonconservative mechanical potential. The potential is analytically simplified and reduced to a quartic two-well potential, matching the bifurcation structure of the original model. This yields a dynamics-based model that is analytically simpler and has fewer parameters than the original model, allowing easier fitting to experimental data. This model is first demonstrated to semiquantitatively match the dynamics of the physiologically based model from which it is derived, and is then fitted directly to a set of experimentally derived criteria. These criteria place rigorous constraints on the parameter values, and within these constraints the model is shown to reproduce normal sleep-wake dynamics and recovery from sleep deprivation. Furthermore, this approach enables insights into the dynamics by direct analogies to phenomena in well studied mechanical systems. These include the relation between friction in the mechanical system and the timecourse of neurotransmitter action, and the possible relation between stochastic resonance and napping behavior. The model derived here also serves as a platform for future investigations of sleep-wake phenomena from a dynamical perspective.

Fully Associative, Nonisothermal, Potential-Based Unified Viscoplastic Model for Titanium-Based Matrices

NASA Technical Reports Server (NTRS)

2005-01-01

A number of titanium matrix composite (TMC) systems are currently being investigated for high-temperature air frame and propulsion system applications. As a result, numerous computational methodologies for predicting both deformation and life for this class of materials are under development. An integral part of these methodologies is an accurate and computationally efficient constitutive model for the metallic matrix constituent. Furthermore, because these systems are designed to operate at elevated temperatures, the required constitutive models must account for both time-dependent and time-independent deformations. To accomplish this, the NASA Lewis Research Center is employing a recently developed, complete, potential-based framework. This framework, which utilizes internal state variables, was put forth for the derivation of reversible and irreversible constitutive equations. The framework, and consequently the resulting constitutive model, is termed complete because the existence of the total (integrated) form of the Gibbs complementary free energy and complementary dissipation potentials are assumed a priori. The specific forms selected here for both the Gibbs and complementary dissipation potentials result in a fully associative, multiaxial, nonisothermal, unified viscoplastic model with nonlinear kinematic hardening. This model constitutes one of many models in the Generalized Viscoplasticity with Potential Structure (GVIPS) class of inelastic constitutive equations.

A Nonlinear Multigrid Solver for an Atmospheric General Circulation Model Based on Semi-Implicit Semi-Lagrangian Advection of Potential Vorticity

NASA Technical Reports Server (NTRS)

McCormick, S.; Ruge, John W.

1998-01-01

This work represents a part of a project to develop an atmospheric general circulation model based on the semi-Lagrangian advection of potential vorticity (PC) with divergence as the companion prognostic variable.

Models-Based Practice: Great White Hope or White Elephant?

ERIC Educational Resources Information Center

Casey, Ashley

2014-01-01

Background: Many critical curriculum theorists in physical education have advocated a model- or models-based approach to teaching in the subject. This paper explores the literature base around models-based practice (MBP) and asks if this multi-models approach to curriculum planning has the potential to be the great white hope of pedagogical change…

3D reconstruction of the magnetic vector potential using model based iterative reconstruction

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

Prabhat, K. C.; Aditya Mohan, K.; Phatak, Charudatta

Lorentz transmission electron microscopy (TEM) observations of magnetic nanoparticles contain information on the magnetic and electrostatic potentials. Vector field electron tomography (VFET) can be used to reconstruct electromagnetic potentials of the nanoparticles from their corresponding LTEM images. The VFET approach is based on the conventional filtered back projection approach to tomographic reconstructions and the availability of an incomplete set of measurements due to experimental limitations means that the reconstructed vector fields exhibit significant artifacts. In this paper, we outline a model-based iterative reconstruction (MBIR) algorithm to reconstruct the magnetic vector potential of magnetic nanoparticles. We combine a forward model formore » image formation in TEM experiments with a prior model to formulate the tomographic problem as a maximum a-posteriori probability estimation problem (MAP). The MAP cost function is minimized iteratively to determine the vector potential. Here, a comparative reconstruction study of simulated as well as experimental data sets show that the MBIR approach yields quantifiably better reconstructions than the VFET approach.« less

Transcranial Magnetic Stimulation: An Automated Procedure to Obtain Coil-specific Models for Field Calculations.

PubMed

Madsen, Kristoffer H; Ewald, Lars; Siebner, Hartwig R; Thielscher, Axel

2015-01-01

Field calculations for transcranial magnetic stimulation (TMS) are increasingly implemented online in neuronavigation systems and in more realistic offline approaches based on finite-element methods. They are often based on simplified and/or non-validated models of the magnetic vector potential of the TMS coils. To develop an approach to reconstruct the magnetic vector potential based on automated measurements. We implemented a setup that simultaneously measures the three components of the magnetic field with high spatial resolution. This is complemented by a novel approach to determine the magnetic vector potential via volume integration of the measured field. The integration approach reproduces the vector potential with very good accuracy. The vector potential distribution of a standard figure-of-eight shaped coil determined with our setup corresponds well with that calculated using a model reconstructed from x-ray images. The setup can supply validated models for existing and newly appearing TMS coils. Copyright © 2015 Elsevier Inc. All rights reserved.

3D reconstruction of the magnetic vector potential using model based iterative reconstruction.

PubMed

Prabhat, K C; Aditya Mohan, K; Phatak, Charudatta; Bouman, Charles; De Graef, Marc

2017-11-01

Lorentz transmission electron microscopy (TEM) observations of magnetic nanoparticles contain information on the magnetic and electrostatic potentials. Vector field electron tomography (VFET) can be used to reconstruct electromagnetic potentials of the nanoparticles from their corresponding LTEM images. The VFET approach is based on the conventional filtered back projection approach to tomographic reconstructions and the availability of an incomplete set of measurements due to experimental limitations means that the reconstructed vector fields exhibit significant artifacts. In this paper, we outline a model-based iterative reconstruction (MBIR) algorithm to reconstruct the magnetic vector potential of magnetic nanoparticles. We combine a forward model for image formation in TEM experiments with a prior model to formulate the tomographic problem as a maximum a-posteriori probability estimation problem (MAP). The MAP cost function is minimized iteratively to determine the vector potential. A comparative reconstruction study of simulated as well as experimental data sets show that the MBIR approach yields quantifiably better reconstructions than the VFET approach. Copyright © 2017 Elsevier B.V. All rights reserved.

3D reconstruction of the magnetic vector potential using model based iterative reconstruction

DOE PAGES

Prabhat, K. C.; Aditya Mohan, K.; Phatak, Charudatta; ...

2017-07-03

Lorentz transmission electron microscopy (TEM) observations of magnetic nanoparticles contain information on the magnetic and electrostatic potentials. Vector field electron tomography (VFET) can be used to reconstruct electromagnetic potentials of the nanoparticles from their corresponding LTEM images. The VFET approach is based on the conventional filtered back projection approach to tomographic reconstructions and the availability of an incomplete set of measurements due to experimental limitations means that the reconstructed vector fields exhibit significant artifacts. In this paper, we outline a model-based iterative reconstruction (MBIR) algorithm to reconstruct the magnetic vector potential of magnetic nanoparticles. We combine a forward model formore » image formation in TEM experiments with a prior model to formulate the tomographic problem as a maximum a-posteriori probability estimation problem (MAP). The MAP cost function is minimized iteratively to determine the vector potential. Here, a comparative reconstruction study of simulated as well as experimental data sets show that the MBIR approach yields quantifiably better reconstructions than the VFET approach.« less

A Resource-Based Modelling Framework to Assess Habitat Suitability for Steppe Birds in Semiarid Mediterranean Agricultural Systems

PubMed Central

Cardador, Laura; De Cáceres, Miquel; Bota, Gerard; Giralt, David; Casas, Fabián; Arroyo, Beatriz; Mougeot, François; Cantero-Martínez, Carlos; Moncunill, Judit; Butler, Simon J.; Brotons, Lluís

2014-01-01

European agriculture is undergoing widespread changes that are likely to have profound impacts on farmland biodiversity. The development of tools that allow an assessment of the potential biodiversity effects of different land-use alternatives before changes occur is fundamental to guiding management decisions. In this study, we develop a resource-based model framework to estimate habitat suitability for target species, according to simple information on species’ key resource requirements (diet, foraging habitat and nesting site), and examine whether it can be used to link land-use and local species’ distribution. We take as a study case four steppe bird species in a lowland area of the north-eastern Iberian Peninsula. We also compare the performance of our resource-based approach to that obtained through habitat-based models relating species’ occurrence and land-cover variables. Further, we use our resource-based approach to predict the effects that change in farming systems can have on farmland bird habitat suitability and compare these predictions with those obtained using the habitat-based models. Habitat suitability estimates generated by our resource-based models performed similarly (and better for one study species) than habitat based-models when predicting current species distribution. Moderate prediction success was achieved for three out of four species considered by resource-based models and for two of four by habitat-based models. Although, there is potential for improving the performance of resource-based models, they provide a structure for using available knowledge of the functional links between agricultural practices, provision of key resources and the response of organisms to predict potential effects of changing land-uses in a variety of context or the impacts of changes such as altered management practices that are not easily incorporated into habitat-based models. PMID:24667825

ESTIMATION OF GROUNDWATER POLLUTION POTENTIAL BY PESTICIDES IN MID-ATLANTIC COASTAL PLAIN WATERSHEDS

EPA Science Inventory

A simple GIS-based transport model to estimate the potential for groundwater pollution by pesticides has been developed within the ArcView GIS environment. The pesticide leaching analytical model, which is based on one-dimensional advective-dispersive-reactive (ADR) transport, ha...

Estimating the potential of energy saving and carbon emission mitigation of cassava-based fuel ethanol using life cycle assessment coupled with a biogeochemical process model.

PubMed

Jiang, Dong; Hao, Mengmeng; Fu, Jingying; Tian, Guangjin; Ding, Fangyu

2017-09-14

Global warming and increasing concentration of atmospheric greenhouse gas (GHG) have prompted considerable interest in the potential role of energy plant biomass. Cassava-based fuel ethanol is one of the most important bioenergy and has attracted much attention in both developed and developing countries. However, the development of cassava-based fuel ethanol is still faced with many uncertainties, including raw material supply, net energy potential, and carbon emission mitigation potential. Thus, an accurate estimation of these issues is urgently needed. This study provides an approach to estimate energy saving and carbon emission mitigation potentials of cassava-based fuel ethanol through LCA (life cycle assessment) coupled with a biogeochemical process model-GEPIC (GIS-based environmental policy integrated climate) model. The results indicate that the total potential of cassava yield on marginal land in China is 52.51 million t; the energy ratio value varies from 0.07 to 1.44, and the net energy surplus of cassava-based fuel ethanol in China is 92,920.58 million MJ. The total carbon emission mitigation from cassava-based fuel ethanol in China is 4593.89 million kgC. Guangxi, Guangdong, and Fujian are identified as target regions for large-scale development of cassava-based fuel ethanol industry. These results can provide an operational approach and fundamental data for scientific research and energy planning.

About the choice of Gibbs' potential for modelling of FCC ↔ HCP transformation in FeMnSi-based shape memory alloys

NASA Astrophysics Data System (ADS)

Evard, Margarita E.; Volkov, Aleksandr E.; Belyaev, Fedor S.; Ignatova, Anna D.

2018-05-01

The choice of Gibbs' potential for microstructural modeling of FCC ↔ HCP martensitic transformation in FeMn-based shape memory alloys is discussed. Threefold symmetry of the HCP phase is taken into account on specifying internal variables characterizing volume fractions of martensite variants. Constraints imposed on model constants by thermodynamic equilibrium conditions are formulated.

A landscape model for predicting potential natural vegetation of the Olympic Peninsula USA using boundary equations and newly developed environmental variables.

Treesearch

Jan A. Henderson; Robin D. Lesher; David H. Peter; Chris D. Ringo

2011-01-01

A gradient-analysis-based model and grid-based map are presented that use the potential vegetation zone as the object of the model. Several new variables are presented that describe the environmental gradients of the landscape at different scales. Boundary algorithms are conceptualized, and then defined, that describe the environmental boundaries between vegetation...

Theoretical determination of one-electron redox potentials for DNA bases, base pairs, and stacks.

PubMed

Paukku, Y; Hill, G

2011-05-12

Electron affinities, ionization potentials, and redox potentials for DNA bases, base pairs, and N-methylated derivatives are computed at the DFT/M06-2X/6-31++G(d,p) level of theory. Redox properties of a guanine-guanine stack model are explored as well. Reduction and oxidation potentials are in good agreement with the experimental ones. Electron affinities of base pairs were found to be negative. Methylation of canonical bases affects the ionization potentials the most. Base pair formation and base stacking lower ionization potentials by 0.3 eV. Pairing of guanine with the 5-methylcytosine does not seem to influence the redox properties of this base pair much.

An analytical drain current model for symmetric double-gate MOSFETs

NASA Astrophysics Data System (ADS)

Yu, Fei; Huang, Gongyi; Lin, Wei; Xu, Chuanzhong

2018-04-01

An analytical surface-potential-based drain current model of symmetric double-gate (sDG) MOSFETs is described as a SPICE compatible model in this paper. The continuous surface and central potentials from the accumulation to the strong inversion regions are solved from the 1-D Poisson's equation in sDG MOSFETs. Furthermore, the drain current is derived from the charge sheet model as a function of the surface potential. Over a wide range of terminal voltages, doping concentrations, and device geometries, the surface potential calculation scheme and drain current model are verified by solving the 1-D Poisson's equation based on the least square method and using the Silvaco Atlas simulation results and experimental data, respectively. Such a model can be adopted as a useful platform to develop the circuit simulator and provide the clear understanding of sDG MOSFET device physics.

ISS Plasma Interaction: Measurements and Modeling

NASA Technical Reports Server (NTRS)

Barsamian, H.; Mikatarian, R.; Alred, J.; Minow, J.; Koontz, S.

2004-01-01

Ionospheric plasma interaction effects on the International Space Station are discussed in the following paper. The large structure and high voltage arrays of the ISS represent a complex system interacting with LEO plasma. Discharge current measurements made by the Plasma Contactor Units and potential measurements made by the Floating Potential Probe delineate charging and magnetic induction effects on the ISS. Based on theoretical and physical understanding of the interaction phenomena, a model of ISS plasma interaction has been developed. The model includes magnetic induction effects, interaction of the high voltage solar arrays with ionospheric plasma, and accounts for other conductive areas on the ISS. Based on these phenomena, the Plasma Interaction Model has been developed. Limited verification of the model has been performed by comparison of Floating Potential Probe measurement data to simulations. The ISS plasma interaction model will be further tested and verified as measurements from the Floating Potential Measurement Unit become available, and construction of the ISS continues.

A GIS-based approach for comparative analysis of potential fire risk assessment

NASA Astrophysics Data System (ADS)

Sun, Ying; Hu, Lieqiu; Liu, Huiping

2007-06-01

Urban fires are one of the most important sources of property loss and human casualty and therefore it is necessary to assess the potential fire risk with consideration of urban community safety. Two evaluation models are proposed, both of which are integrated with GIS. One is the single factor model concerning the accessibility of fire passage and the other is grey clustering approach based on the multifactor system. In the latter model, fourteen factors are introduced and divided into four categories involving security management, evacuation facility, construction resistance and fire fighting capability. A case study on campus of Beijing Normal University is presented to express the potential risk assessment models in details. A comparative analysis of the two models is carried out to validate the accuracy. The results are approximately consistent with each other. Moreover, modeling with GIS promotes the efficiency the potential risk assessment.

Potential usefulness of a topic model-based categorization of lung cancers as quantitative CT biomarkers for predicting the recurrence risk after curative resection

NASA Astrophysics Data System (ADS)

Kawata, Y.; Niki, N.; Ohmatsu, H.; Satake, M.; Kusumoto, M.; Tsuchida, T.; Aokage, K.; Eguchi, K.; Kaneko, M.; Moriyama, N.

2014-03-01

In this work, we investigate a potential usefulness of a topic model-based categorization of lung cancers as quantitative CT biomarkers for predicting the recurrence risk after curative resection. The elucidation of the subcategorization of a pulmonary nodule type in CT images is an important preliminary step towards developing the nodule managements that are specific to each patient. We categorize lung cancers by analyzing volumetric distributions of CT values within lung cancers via a topic model such as latent Dirichlet allocation. Through applying our scheme to 3D CT images of nonsmall- cell lung cancer (maximum lesion size of 3 cm) , we demonstrate the potential usefulness of the topic model-based categorization of lung cancers as quantitative CT biomarkers.

Macroscopic neural mass model constructed from a current-based network model of spiking neurons.

PubMed

Umehara, Hiroaki; Okada, Masato; Teramae, Jun-Nosuke; Naruse, Yasushi

2017-02-01

Neural mass models (NMMs) are efficient frameworks for describing macroscopic cortical dynamics including electroencephalogram and magnetoencephalogram signals. Originally, these models were formulated on an empirical basis of synaptic dynamics with relatively long time constants. By clarifying the relations between NMMs and the dynamics of microscopic structures such as neurons and synapses, we can better understand cortical and neural mechanisms from a multi-scale perspective. In a previous study, the NMMs were analytically derived by averaging the equations of synaptic dynamics over the neurons in the population and further averaging the equations of the membrane-potential dynamics. However, the averaging of synaptic current assumes that the neuron membrane potentials are nearly time invariant and that they remain at sub-threshold levels to retain the conductance-based model. This approximation limits the NMM to the non-firing state. In the present study, we newly propose a derivation of a NMM by alternatively approximating the synaptic current which is assumed to be independent of the membrane potential, thus adopting a current-based model. Our proposed model releases the constraint of the nearly constant membrane potential. We confirm that the obtained model is reducible to the previous model in the non-firing situation and that it reproduces the temporal mean values and relative power spectrum densities of the average membrane potentials for the spiking neurons. It is further ensured that the existing NMM properly models the averaged dynamics over individual neurons even if they are spiking in the populations.

WORKSHOP ON APPLICATION OF STATISTICAL METHODS TO BIOLOGICALLY-BASED PHARMACOKINETIC MODELING FOR RISK ASSESSMENT

EPA Science Inventory

Biologically-based pharmacokinetic models are being increasingly used in the risk assessment of environmental chemicals. These models are based on biological, mathematical, statistical and engineering principles. Their potential uses in risk assessment include extrapolation betwe...

Potential-based and non-potential-based cohesive zone formulations under mixed-mode separation and over-closure-Part II: Finite element applications

NASA Astrophysics Data System (ADS)

Máirtín, Éamonn Ó.; Parry, Guillaume; Beltz, Glenn E.; McGarry, J. Patrick

2014-02-01

This paper, the second of two parts, presents three novel finite element case studies to demonstrate the importance of normal-tangential coupling in cohesive zone models (CZMs) for the prediction of mixed-mode interface debonding. Specifically, four new CZMs proposed in Part I of this study are implemented, namely the potential-based MP model and the non-potential-based NP1, NP2 and SMC models. For comparison, simulations are also performed for the well established potential-based Xu-Needleman (XN) model and the non-potential-based model of van den Bosch, Schreurs and Geers (BSG model). Case study 1: Debonding and rebonding of a biological cell from a cyclically deforming silicone substrate is simulated when the mode II work of separation is higher than the mode I work of separation at the cell-substrate interface. An active formulation for the contractility and remodelling of the cell cytoskeleton is implemented. It is demonstrated that when the XN potential function is used at the cell-substrate interface repulsive normal tractions are computed, preventing rebonding of significant regions of the cell to the substrate. In contrast, the proposed MP potential function at the cell-substrate interface results in negligible repulsive normal tractions, allowing for the prediction of experimentally observed patterns of cell cytoskeletal remodelling. Case study 2: Buckling of a coating from the compressive surface of a stent is simulated. It is demonstrated that during expansion of the stent the coating is initially compressed into the stent surface, while simultaneously undergoing tangential (shear) tractions at the coating-stent interface. It is demonstrated that when either the proposed NP1 or NP2 model is implemented at the stent-coating interface mixed-mode over-closure is correctly penalised. Further expansion of the stent results in the prediction of significant buckling of the coating from the stent surface, as observed experimentally. In contrast, the BSG model does not correctly penalise mixed-mode over-closure at the stent-coating interface, significantly altering the stress state in the coating and preventing the prediction of buckling. Case study 3: Application of a displacement to the base of a bi-layered composite arch results in a symmetric sinusoidal distribution of normal and tangential traction at the arch interface. The traction defined mode mixity at the interface ranges from pure mode II at the base of the arch to pure mode I at the top of the arch. It is demonstrated that predicted debonding patterns are highly sensitive to normal-tangential coupling terms in a CZM. The NP2, XN, and BSG models exhibit a strong bias towards mode I separation at the top of the arch, while the NP1 model exhibits a bias towards mode II debonding at the base of the arch. Only the SMC model provides mode-independent behaviour in the early stages of debonding. This case study provides a practical example of the importance of the behaviour of CZMs under conditions of traction controlled mode mixity, following from the theoretical analysis presented in Part I of this study.

Spatial analysis of plague in California: niche modeling predictions of the current distribution and potential response to climate change

PubMed Central

Holt, Ashley C; Salkeld, Daniel J; Fritz, Curtis L; Tucker, James R; Gong, Peng

2009-01-01

Background Plague, caused by the bacterium Yersinia pestis, is a public and wildlife health concern in California and the western United States. This study explores the spatial characteristics of positive plague samples in California and tests Maxent, a machine-learning method that can be used to develop niche-based models from presence-only data, for mapping the potential distribution of plague foci. Maxent models were constructed using geocoded seroprevalence data from surveillance of California ground squirrels (Spermophilus beecheyi) as case points and Worldclim bioclimatic data as predictor variables, and compared and validated using area under the receiver operating curve (AUC) statistics. Additionally, model results were compared to locations of positive and negative coyote (Canis latrans) samples, in order to determine the correlation between Maxent model predictions and areas of plague risk as determined via wild carnivore surveillance. Results Models of plague activity in California ground squirrels, based on recent climate conditions, accurately identified case locations (AUC of 0.913 to 0.948) and were significantly correlated with coyote samples. The final models were used to identify potential plague risk areas based on an ensemble of six future climate scenarios. These models suggest that by 2050, climate conditions may reduce plague risk in the southern parts of California and increase risk along the northern coast and Sierras. Conclusion Because different modeling approaches can yield substantially different results, care should be taken when interpreting future model predictions. Nonetheless, niche modeling can be a useful tool for exploring and mapping the potential response of plague activity to climate change. The final models in this study were used to identify potential plague risk areas based on an ensemble of six future climate scenarios, which can help public managers decide where to allocate surveillance resources. In addition, Maxent model results were significantly correlated with coyote samples, indicating that carnivore surveillance programs will continue to be important for tracking the response of plague to future climate conditions. PMID:19558717

Extension of landscape-based population viability models to ecoregional scales for conservation planning

Treesearch

Thomas W. Bonnot; Frank R. III Thompson; Joshua Millspaugh

2011-01-01

Landscape-based population models are potentially valuable tools in facilitating conservation planning and actions at large scales. However, such models have rarely been applied at ecoregional scales. We extended landscape-based population models to ecoregional scales for three species of concern in the Central Hardwoods Bird Conservation Region and compared model...

Analytical Debye-Huckel model for electrostatic potentials around dissolved DNA.

PubMed

Wagner, K; Keyes, E; Kephart, T W; Edwards, G

1997-07-01

We present an analytical, Green-function-based model for the electric potential of DNA in solution, treating the surrounding solvent with the Debye-Huckel approximation. The partial charge of each atom is accounted for by modeling DNA as linear distributions of atoms on concentric cylindrical surfaces. The condensed ions of the solvent are treated with the Debye-Huckel approximation. The resultant leading term of the potential is that of a continuous shielded line charge, and the higher order terms account for the helical structure. Within several angstroms of the surface there is sufficient information in the electric potential to distinguish features and symmetries of DNA. Plots of the potential and equipotential surfaces, dominated by the phosphate charges, reflect the structural differences between the A, B, and Z conformations and, to a smaller extent, the difference between base sequences. As the distances from the helices increase, the magnitudes of the potentials decrease. However, the bases and sugars account for a larger fraction of the double helix potential with increasing distance. We have found that when the solvent is treated with the Debye-Huckel approximation, the potential decays more rapidly in every direction from the surface than it did in the concentric dielectric cylinder approximation.

SCS-CN based time-distributed sediment yield model

NASA Astrophysics Data System (ADS)

Tyagi, J. V.; Mishra, S. K.; Singh, Ranvir; Singh, V. P.

2008-05-01

SummaryA sediment yield model is developed to estimate the temporal rates of sediment yield from rainfall events on natural watersheds. The model utilizes the SCS-CN based infiltration model for computation of rainfall-excess rate, and the SCS-CN-inspired proportionality concept for computation of sediment-excess. For computation of sedimentographs, the sediment-excess is routed to the watershed outlet using a single linear reservoir technique. Analytical development of the model shows the ratio of the potential maximum erosion (A) to the potential maximum retention (S) of the SCS-CN method is constant for a watershed. The model is calibrated and validated on a number of events using the data of seven watersheds from India and the USA. Representative values of the A/S ratio computed for the watersheds from calibration are used for the validation of the model. The encouraging results of the proposed simple four parameter model exhibit its potential in field application.

Predicting cerulean warbler habitat use in the Cumberland Mountains of Tennessee

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

Buehler, D.A.; Welton, M.J.; Beachy, T.A.

2006-12-15

We developed a habitat model to predict cerulean warbler (Dendroica cerulea) habitat availability in the Cumberland Mountains of eastern Tennessee. We used 7 remotely sensed vegetation and topographic landform explanatory variables and known locations of territorial male cerulean warblers mapped in 2003 as the response variable to develop a Mahalanobis distance statistic model of potential habitat. We evaluated the accuracy of the model based on field surveys for ceruleans during the 2004 breeding season. The model performed well with an 80% correct classification of cerulean presence based on the validation data, although prediction of absence was only 54% correct. Wemore » extrapolated from potential habitat to cerulean abundance based on density estimates from territory mapping on 8 20-ha plots in 2005. Over the 200,000-ha study area, we estimated there were 80,584 ha of potential habitat, capable of supporting about 36,500 breeding pairs. We applied the model to the 21,609-ha state-owned Royal Blue Wildlife Management Area to evaluate the potential effects of coal surface mining as one example of a potential conflict between land use and cerulean warbler conservation. Our models suggest coal surface mining could remove 2,954 ha of cerulean habitat on Royal Blue Wildlife Management Area and could displace 2,540 breeding pairs (23% of the Royal Blue population). A comprehensive conservation strategy is needed to address potential and realized habitat loss and degradation on the breeding grounds, during migration, and on the wintering grounds.« less

Physiologically Based Pharmacokinetic Modeling Suggests Limited Drug–Drug Interaction Between Clopidogrel and Dasabuvir

PubMed Central

Fu, W; Badri, P; Bow, DAJ; Fischer, V

2017-01-01

Dasabuvir, a nonnucleoside NS5B polymerase inhibitor, is a sensitive substrate of cytochrome P450 (CYP) 2C8 with a potential for drug–drug interaction (DDI) with clopidogrel. A physiologically based pharmacokinetic (PBPK) model was developed for dasabuvir to evaluate the DDI potential with clopidogrel, the acyl‐β‐D glucuronide metabolite of which has been reported as a strong mechanism‐based inhibitor of CYP2C8 based on an interaction with repaglinide. In addition, the PBPK model for clopidogrel and its metabolite were updated with additional in vitro data. Sensitivity analyses using these PBPK models suggested that CYP2C8 inhibition by clopidogrel acyl‐β‐D glucuronide may not be as potent as previously suggested. The dasabuvir and updated clopidogrel PBPK models predict a moderate increase of 1.5–1.9‐fold for Cmax and 1.9–2.8‐fold for AUC of dasabuvir when coadministered with clopidogrel. While the PBPK results suggest there is a potential for DDI between dasabuvir and clopidogrel, the magnitude is not expected to be clinically relevant. PMID:28411400

Black hole algorithm for determining model parameter in self-potential data

NASA Astrophysics Data System (ADS)

Sungkono; Warnana, Dwa Desa

2018-01-01

Analysis of self-potential (SP) data is increasingly popular in geophysical method due to its relevance in many cases. However, the inversion of SP data is often highly nonlinear. Consequently, local search algorithms commonly based on gradient approaches have often failed to find the global optimum solution in nonlinear problems. Black hole algorithm (BHA) was proposed as a solution to such problems. As the name suggests, the algorithm was constructed based on the black hole phenomena. This paper investigates the application of BHA to solve inversions of field and synthetic self-potential (SP) data. The inversion results show that BHA accurately determines model parameters and model uncertainty. This indicates that BHA is highly potential as an innovative approach for SP data inversion.

Adaptive regularization network based neural modeling paradigm for nonlinear adaptive estimation of cerebral evoked potentials.

PubMed

Zhang, Jian-Hua; Böhme, Johann F

2007-11-01

In this paper we report an adaptive regularization network (ARN) approach to realizing fast blind separation of cerebral evoked potentials (EPs) from background electroencephalogram (EEG) activity with no need to make any explicit assumption on the statistical (or deterministic) signal model. The ARNs are proposed to construct nonlinear EEG and EP signal models. A novel adaptive regularization training (ART) algorithm is proposed to improve the generalization performance of the ARN. Two adaptive neural modeling methods based on the ARN are developed and their implementation and performance analysis are also presented. The computer experiments using simulated and measured visual evoked potential (VEP) data have shown that the proposed ARN modeling paradigm yields computationally efficient and more accurate VEP signal estimation owing to its intrinsic model-free and nonlinear processing characteristics.

Potential Teachers' Appropriate and Inappropriate Application of Pedagogical Resources in a Model-Based Physics Course: A "Knowledge in Pieces" Perspective on Teacher Learning

ERIC Educational Resources Information Center

Harlow, Danielle B.; Bianchini, Julie A.; Swanson, Lauren H.; Dwyer, Hilary A.

2013-01-01

We used a "knowledge in pieces" perspective on teacher learning to document undergraduates' pedagogical resources in a model-based physics course for potential teachers. We defined pedagogical resources as small, discrete ideas about teaching science that are applied appropriately or inappropriately in specific contexts. Neither…

Objectively Determining the Educational Potential of Computer and Video-Based Courseware; or, Producing Reliable Evaluations Despite the Dog and Pony Show.

ERIC Educational Resources Information Center

Barrett, Andrew J.; And Others

The Center for Interactive Technology, Applications, and Research at the College of Engineering of the University of South Florida (Tampa) has developed objective and descriptive evaluation models to assist in determining the educational potential of computer and video courseware. The computer-based courseware evaluation model and the video-based…

TOWARDS REFINED USE OF TOXICITY DATA IN ...

EPA Pesticide Factsheets

In 2003, an International Life Sciences Institute (ILSI) Working Group examined the potential of statistically based structure-activity relationship (SAR) models for use in screening environmental contaminants for possible developmental toxicants. In 2003, an International Life Sciences Institute (ILSI) Working Group examined the potential of statistically based structure-activity relationship (SAR) models for use in screening environmental contaminants for possible developmental toxicants.

A Physically Based Analytical Model to Describe Effective Excess Charge for Streaming Potential Generation in Water Saturated Porous Media

NASA Astrophysics Data System (ADS)

Guarracino, L.; Jougnot, D.

2018-01-01

Among the different contributions generating self-potential, the streaming potential is of particular interest in hydrogeology for its sensitivity to water flow. Estimating water flux in porous media using streaming potential data relies on our capacity to understand, model, and upscale the electrokinetic coupling at the mineral-solution interface. Different approaches have been proposed to predict streaming potential generation in porous media. One of these approaches is the flux averaging which is based on determining the excess charge which is effectively dragged in the medium by water flow. In this study, we develop a physically based analytical model to predict the effective excess charge in saturated porous media using a flux-averaging approach in a bundle of capillary tubes with a fractal pore size distribution. The proposed model allows the determination of the effective excess charge as a function of pore water ionic concentration and hydrogeological parameters like porosity, permeability, and tortuosity. The new model has been successfully tested against different set of experimental data from the literature. One of the main findings of this study is the mechanistic explanation to the empirical dependence between the effective excess charge and the permeability that has been found by several researchers. The proposed model also highlights the link to other lithological properties, and it is able to reproduce the evolution of effective excess charge with electrolyte concentrations.

OWL: A code for the two-center shell model with spherical Woods-Saxon potentials

NASA Astrophysics Data System (ADS)

Diaz-Torres, Alexis

2018-03-01

A Fortran-90 code for solving the two-center nuclear shell model problem is presented. The model is based on two spherical Woods-Saxon potentials and the potential separable expansion method. It describes the single-particle motion in low-energy nuclear collisions, and is useful for characterizing a broad range of phenomena from fusion to nuclear molecular structures.

Action-based Dynamical Modeling for the Milky Way Disk: The Influence of Spiral Arms

NASA Astrophysics Data System (ADS)

Trick, Wilma H.; Bovy, Jo; D'Onghia, Elena; Rix, Hans-Walter

2017-04-01

RoadMapping is a dynamical modeling machinery developed to constrain the Milky Way’s (MW) gravitational potential by simultaneously fitting an axisymmetric parametrized potential and an action-based orbit distribution function (DF) to discrete 6D phase-space measurements of stars in the Galactic disk. In this work, we demonstrate RoadMapping's robustness in the presence of spiral arms by modeling data drawn from an N-body simulation snapshot of a disk-dominated galaxy of MW mass with strong spiral arms (but no bar), exploring survey volumes with radii 500 {pc}≤slant {r}\\max ≤slant 5 {kpc}. The potential constraints are very robust, even though we use a simple action-based DF, the quasi-isothermal DF. The best-fit RoadMapping model always recovers the correct gravitational forces where most of the stars that entered the analysis are located, even for small volumes. For data from large survey volumes, RoadMapping finds axisymmetric models that average well over the spiral arms. Unsurprisingly, the models are slightly biased by the excess of stars in the spiral arms. Gravitational potential models derived from survey volumes with at least {r}\\max =3 {kpc} can be reliably extrapolated to larger volumes. However, a large radial survey extent, {r}\\max ˜ 5 {kpc}, is needed to correctly recover the halo scale length. In general, the recovery and extrapolability of potentials inferred from data sets that were drawn from inter-arm regions appear to be better than those of data sets drawn from spiral arms. Our analysis implies that building axisymmetric models for the Galaxy with upcoming Gaia data will lead to sensible and robust approximations of the MW’s potential.

Teacher Evaluation Models: Compliance or Growth Oriented?

ERIC Educational Resources Information Center

Clenchy, Kelly R.

2017-01-01

This research study reviewed literature specific to the evolution of teacher evaluation models and explored the effectiveness of standards-based evaluation models' potential to facilitate professional growth. The researcher employed descriptive phenomenology to conduct a study of teachers' perceptions of a standard-based evaluation model's…

Integrating Near-Real Time Hydrologic-Response Monitoring and Modeling for Improved Assessments of Slope Stability Along the Coastal Bluffs of the Puget Sound Rail Corridor, Washington State

NASA Astrophysics Data System (ADS)

Mirus, B. B.; Baum, R. L.; Stark, B.; Smith, J. B.; Michel, A.

2015-12-01

Previous USGS research on landslide potential in hillside areas and coastal bluffs around Puget Sound, WA, has identified rainfall thresholds and antecedent moisture conditions that correlate with heightened probability of shallow landslides. However, physically based assessments of temporal and spatial variability in landslide potential require improved quantitative characterization of the hydrologic controls on landslide initiation in heterogeneous geologic materials. Here we present preliminary steps towards integrating monitoring of hydrologic response with physically based numerical modeling to inform the development of a landslide warning system for a railway corridor along the eastern shore of Puget Sound. We instrumented two sites along the steep coastal bluffs - one active landslide and one currently stable slope with the potential for failure - to monitor rainfall, soil-moisture, and pore-pressure dynamics in near-real time. We applied a distributed model of variably saturated subsurface flow for each site, with heterogeneous hydraulic-property distributions based on our detailed site characterization of the surficial colluvium and the underlying glacial-lacustrine deposits that form the bluffs. We calibrated the model with observed volumetric water content and matric potential time series, then used simulated pore pressures from the calibrated model to calculate the suction stress and the corresponding distribution of the factor of safety against landsliding with the infinite slope approximation. Although the utility of the model is limited by uncertainty in the deeper groundwater flow system, the continuous simulation of near-surface hydrologic response can help to quantify the temporal variations in the potential for shallow slope failures at the two sites. Thus the integration of near-real time monitoring and physically based modeling contributes a useful tool towards mitigating hazards along the Puget Sound railway corridor.

Modeling startle eyeblink electromyogram to assess fear learning.

PubMed

Khemka, Saurabh; Tzovara, Athina; Gerster, Samuel; Quednow, Boris B; Bach, Dominik R

2017-02-01

Pavlovian fear conditioning is widely used as a laboratory model of associative learning in human and nonhuman species. In this model, an organism is trained to predict an aversive unconditioned stimulus from initially neutral events (conditioned stimuli, CS). In humans, fear memory is typically measured via conditioned autonomic responses or fear-potentiated startle. For the latter, various analysis approaches have been developed, but a systematic comparison of competing methodologies is lacking. Here, we investigate the suitability of a model-based approach to startle eyeblink analysis for assessment of fear memory, and compare this to extant analysis strategies. First, we build a psychophysiological model (PsPM) on a generic startle response. Then, we optimize and validate this PsPM on three independent fear-conditioning data sets. We demonstrate that our model can robustly distinguish aversive (CS+) from nonaversive stimuli (CS-, i.e., has high predictive validity). Importantly, our model-based approach captures fear-potentiated startle during fear retention as well as fear acquisition. Our results establish a PsPM-based approach to assessment of fear-potentiated startle, and qualify previous peak-scoring methods. Our proposed model represents a generic startle response and can potentially be used beyond fear conditioning, for example, to quantify affective startle modulation or prepulse inhibition of the acoustic startle response. © 2016 The Authors. Psychophysiology published by Wiley Periodicals, Inc. on behalf of Society for Psychophysiological Research.

A knowledge-based potential with an accurate description of local interactions improves discrimination between native and near-native protein conformations.

PubMed

Ferrada, Evandro; Vergara, Ismael A; Melo, Francisco

2007-01-01

The correct discrimination between native and near-native protein conformations is essential for achieving accurate computer-based protein structure prediction. However, this has proven to be a difficult task, since currently available physical energy functions, empirical potentials and statistical scoring functions are still limited in achieving this goal consistently. In this work, we assess and compare the ability of different full atom knowledge-based potentials to discriminate between native protein structures and near-native protein conformations generated by comparative modeling. Using a benchmark of 152 near-native protein models and their corresponding native structures that encompass several different folds, we demonstrate that the incorporation of close non-bonded pairwise atom terms improves the discriminating power of the empirical potentials. Since the direct and unbiased derivation of close non-bonded terms from current experimental data is not possible, we obtained and used those terms from the corresponding pseudo-energy functions of a non-local knowledge-based potential. It is shown that this methodology significantly improves the discrimination between native and near-native protein conformations, suggesting that a proper description of close non-bonded terms is important to achieve a more complete and accurate description of native protein conformations. Some external knowledge-based energy functions that are widely used in model assessment performed poorly, indicating that the benchmark of models and the specific discrimination task tested in this work constitutes a difficult challenge.

Molecular dynamics simulations for mechanical properties of borophene: parameterization of valence force field model and Stillinger-Weber potential

PubMed Central

Zhou, Yu-Ping; Jiang, Jin-Wu

2017-01-01

While most existing theoretical studies on the borophene are based on first-principles calculations, the present work presents molecular dynamics simulations for the lattice dynamical and mechanical properties in borophene. The obtained mechanical quantities are in good agreement with previous first-principles calculations. The key ingredients for these molecular dynamics simulations are the two efficient empirical potentials developed in the present work for the interaction of borophene with low-energy triangular structure. The first one is the valence force field model, which is developed with the assistance of the phonon dispersion of borophene. The valence force field model is a linear potential, so it is rather efficient for the calculation of linear quantities in borophene. The second one is the Stillinger-Weber potential, whose parameters are derived based on the valence force field model. The Stillinger-Weber potential is applicable in molecular dynamics simulations of nonlinear physical or mechanical quantities in borophene. PMID:28349983

Surface-Potential-Based Metal-Oxide-Silicon-Varactor Model for RF Applications

NASA Astrophysics Data System (ADS)

Miyake, Masataka; Sadachika, Norio; Navarro, Dondee; Mizukane, Yoshio; Matsumoto, Kenji; Ezaki, Tatsuya; Miura-Mattausch, Mitiko; Mattausch, Hans Juergen; Ohguro, Tatsuya; Iizuka, Takahiro; Taguchi, Masahiko; Kumashiro, Shigetaka; Miyamoto, Shunsuke

2007-04-01

We have developed a surface-potential-based metal-oxide-silicon (MOS)-varactor model valid for RF applications up to 200 GHz. The model enables the calculation of the MOS-varactor capacitance seamlessly from the depletion region to the accumulation region and explicitly considers the carrier-response delay causing a non-quasi-static (NQS) effect. It has been observed that capacitance reduction due to this non-quasi-static effect limits the MOS-varactor application to an RF regime.

Analytical Debye-Huckel model for electrostatic potentials around dissolved DNA.

PubMed Central

Wagner, K; Keyes, E; Kephart, T W; Edwards, G

1997-01-01

We present an analytical, Green-function-based model for the electric potential of DNA in solution, treating the surrounding solvent with the Debye-Huckel approximation. The partial charge of each atom is accounted for by modeling DNA as linear distributions of atoms on concentric cylindrical surfaces. The condensed ions of the solvent are treated with the Debye-Huckel approximation. The resultant leading term of the potential is that of a continuous shielded line charge, and the higher order terms account for the helical structure. Within several angstroms of the surface there is sufficient information in the electric potential to distinguish features and symmetries of DNA. Plots of the potential and equipotential surfaces, dominated by the phosphate charges, reflect the structural differences between the A, B, and Z conformations and, to a smaller extent, the difference between base sequences. As the distances from the helices increase, the magnitudes of the potentials decrease. However, the bases and sugars account for a larger fraction of the double helix potential with increasing distance. We have found that when the solvent is treated with the Debye-Huckel approximation, the potential decays more rapidly in every direction from the surface than it did in the concentric dielectric cylinder approximation. Images FIGURE 1 FIGURE 2 FIGURE 3 FIGURE 4 FIGURE 5 FIGURE 7 PMID:9199767

Advances in visual representation of molecular potentials.

PubMed

Du, Qi-Shi; Huang, Ri-Bo; Chou, Kuo-Chen

2010-06-01

The recent advances in visual representations of molecular properties in 3D space are summarized, and their applications in molecular modeling study and rational drug design are introduced. The visual representation methods provide us with detailed insights into protein-ligand interactions, and hence can play a major role in elucidating the structure or reactivity of a biomolecular system. Three newly developed computation and visualization methods for studying the physical and chemical properties of molecules are introduced, including their electrostatic potential, lipophilicity potential and excess chemical potential. The newest application examples of visual representations in structure-based rational drug are presented. The 3D electrostatic potentials, calculated using the empirical method (EM-ESP), in which the classical Coulomb equation and traditional atomic partial changes are discarded, are highly consistent with the results by the higher level quantum chemical method. The 3D lipophilicity potentials, computed by the heuristic molecular lipophilicity potential method based on the principles of quantum mechanics and statistical mechanics, are more accurate and reliable than those by using the traditional empirical methods. The 3D excess chemical potentials, derived by the reference interaction site model-hypernetted chain theory, provide a new tool for computational chemistry and molecular modeling. For structure-based drug design, the visual representations of molecular properties will play a significant role in practical applications. It is anticipated that the new advances in computational chemistry will stimulate the development of molecular modeling methods, further enriching the visual representation techniques for rational drug design, as well as other relevant fields in life science.

Bond Graph Modeling of Chemiosmotic Biomolecular Energy Transduction.

PubMed

Gawthrop, Peter J

2017-04-01

Engineering systems modeling and analysis based on the bond graph approach has been applied to biomolecular systems. In this context, the notion of a Faraday-equivalent chemical potential is introduced which allows chemical potential to be expressed in an analogous manner to electrical volts thus allowing engineering intuition to be applied to biomolecular systems. Redox reactions, and their representation by half-reactions, are key components of biological systems which involve both electrical and chemical domains. A bond graph interpretation of redox reactions is given which combines bond graphs with the Faraday-equivalent chemical potential. This approach is particularly relevant when the biomolecular system implements chemoelectrical transduction - for example chemiosmosis within the key metabolic pathway of mitochondria: oxidative phosphorylation. An alternative way of implementing computational modularity using bond graphs is introduced and used to give a physically based model of the mitochondrial electron transport chain To illustrate the overall approach, this model is analyzed using the Faraday-equivalent chemical potential approach and engineering intuition is used to guide affinity equalisation: a energy based analysis of the mitochondrial electron transport chain.

Simulated western spruce budworm defoliation reduces torching and crowning potential: A sensitivity analysis using a physics-based fire model

Treesearch

Gregory M. Cohn; Russell A. Parsons; Emily K. Heyerdahl; Daniel G. Gavin; Aquila Flower

2014-01-01

The widespread, native defoliator western spruce budworm (Choristoneura occidentalis Freeman) reduces canopy fuels, which might affect the potential for surface fires to torch (ignite the crowns of individual trees) or crown (spread between tree crowns). However, the effects of defoliation on fire behaviour are poorly understood. We used a physics-based fire model to...

Automatic Parametrization of Somatosensory Evoked Potentials With Chirp Modeling.

PubMed

Vayrynen, Eero; Noponen, Kai; Vipin, Ashwati; Thow, X Y; Al-Nashash, Hasan; Kortelainen, Jukka; All, Angelo

2016-09-01

In this paper, an approach using polynomial phase chirp signals to model somatosensory evoked potentials (SEPs) is proposed. SEP waveforms are assumed as impulses undergoing group velocity dispersion while propagating along a multipath neural connection. Mathematical analysis of pulse dispersion resulting in chirp signals is performed. An automatic parameterization of SEPs is proposed using chirp models. A Particle Swarm Optimization algorithm is used to optimize the model parameters. Features describing the latencies and amplitudes of SEPs are automatically derived. A rat model is then used to evaluate the automatic parameterization of SEPs in two experimental cases, i.e., anesthesia level and spinal cord injury (SCI). Experimental results show that chirp-based model parameters and the derived SEP features are significant in describing both anesthesia level and SCI changes. The proposed automatic optimization based approach for extracting chirp parameters offers potential for detailed SEP analysis in future studies. The method implementation in Matlab technical computing language is provided online.

Numerical solution of a multi-ion one-potential model for electroosmotic flow in two-dimensional rectangular microchannels.

PubMed

Van Theemsche, Achim; Deconinck, Johan; Van den Bossche, Bart; Bortels, Leslie

2002-10-01

A new more general numerical model for the simulation of electrokinetic flow in rectangular microchannels is presented. The model is based on the dilute solution model and the Navier-Stokes equations and has been implemented in a finite-element-based C++ code. The model includes the ion distribution in the Helmholtz double layer and considers only one single electrical' potential field variable throughout the domain. On a charged surface(s) the surface charge density, which is proportional to the local electrical field, is imposed. The zeta potential results, then, from this boundary condition and depends on concentrations, temperature, ion valence, molecular diffusion coefficients, and geometric conditions. Validation cases show that the model predicts accurately known analytical results, also for geometries having dimensions comparable to the Debye length. As a final study, the electro-osmotic flow in a controlled cross channel is investigated.

Evaluation of liquefaction potential of soil based on standard penetration test using multi-gene genetic programming model

NASA Astrophysics Data System (ADS)

Muduli, Pradyut; Das, Sarat

2014-06-01

This paper discusses the evaluation of liquefaction potential of soil based on standard penetration test (SPT) dataset using evolutionary artificial intelligence technique, multi-gene genetic programming (MGGP). The liquefaction classification accuracy (94.19%) of the developed liquefaction index (LI) model is found to be better than that of available artificial neural network (ANN) model (88.37%) and at par with the available support vector machine (SVM) model (94.19%) on the basis of the testing data. Further, an empirical equation is presented using MGGP to approximate the unknown limit state function representing the cyclic resistance ratio (CRR) of soil based on developed LI model. Using an independent database of 227 cases, the overall rates of successful prediction of occurrence of liquefaction and non-liquefaction are found to be 87, 86, and 84% by the developed MGGP based model, available ANN and the statistical models, respectively, on the basis of calculated factor of safety (F s) against the liquefaction occurrence.

Proteins QSAR with Markov average electrostatic potentials.

PubMed

González-Díaz, Humberto; Uriarte, Eugenio

2005-11-15

Classic physicochemical and topological indices have been largely used in small molecules QSAR but less in proteins QSAR. In this study, a Markov model is used to calculate, for the first time, average electrostatic potentials xik for an indirect interaction between aminoacids placed at topologic distances k within a given protein backbone. The short-term average stochastic potential xi1 for 53 Arc repressor mutants was used to model the effect of Alanine scanning on thermal stability. The Arc repressor is a model protein of relevance for biochemical studies on bioorganics and medicinal chemistry. A linear discriminant analysis model developed correctly classified 43 out of 53, 81.1% of proteins according to their thermal stability. More specifically, the model classified 20/28, 71.4% of proteins with near wild-type stability and 23/25, 92.0% of proteins with reduced stability. Moreover, predictability in cross-validation procedures was of 81.0%. Expansion of the electrostatic potential in the series xi0, xi1, xi2, and xi3, justified the use of the abrupt truncation approach, being the overall accuracy >70.0% for xi0 but equal for xi1, xi2, and xi3. The xi1 model compared favorably with respect to others based on D-Fire potential, surface area, volume, partition coefficient, and molar refractivity, with less than 77.0% of accuracy [Ramos de Armas, R.; González-Díaz, H.; Molina, R.; Uriarte, E. Protein Struct. Func. Bioinf.2004, 56, 715]. The xi1 model also has more tractable interpretation than others based on Markovian negentropies and stochastic moments. Finally, the model is notably simpler than the two models based on quadratic and linear indices. Both models, reported by Marrero-Ponce et al., use four-to-five time more descriptors. Introduction of average stochastic potentials may be useful for QSAR applications; having xik amenable physical interpretation and being very effective.

Transgenic animal models of neurodegeneration based on human genetic studies

PubMed Central

Richie, Christopher T.; Hoffer, Barry J.; Airavaara, Mikko

2011-01-01

The identification of genes linked to neurodegenerative diseases such as Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), Huntington's disease (HD) and Parkinson's disease (PD) has led to the development of animal models for studying mechanism and evaluating potential therapies. None of the transgenic models developed based on disease-associated genes have been able to fully recapitulate the behavioral and pathological features of the corresponding disease. However, there has been enormous progress made in identifying potential therapeutic targets and understanding some of the common mechanisms of neurodegeneration. In this review, we will discuss transgenic animal models for AD, ALS, HD and PD that are based on human genetic studies. All of the diseases discussed have active or complete clinical trials for experimental treatments that benefited from transgenic models of the disease. PMID:20931247

Development of AHPDST Vulnerability Indexing Model for Groundwater Vulnerability Assessment Using Hydrogeophysical Derived Parameters and GIS Application

NASA Astrophysics Data System (ADS)

Mogaji, K. A.

2017-04-01

Producing a bias-free vulnerability assessment map model is significantly needed for planning a scheme of groundwater quality protection. This study developed a GIS-based AHPDST vulnerability index model for producing groundwater vulnerability model map in the hard rock terrain, Nigeria by exploiting the potentials of analytic hierarchy process (AHP) and Dempster-Shafer theory (DST) data mining models. The acquired borehole and geophysical data in the study area were processed to derive five groundwater vulnerability conditioning factors (GVCFs), namely recharge rate, aquifer transmissivity, hydraulic conductivity, transverse resistance and longitudinal conductance. The produced GVCFs' thematic maps were multi-criterially analyzed by employing the mechanisms of AHP and DST models to determine the normalized weight ( W) parameter for the GVCFs and mass function factors (MFFs) parameter for the GVCFs' thematic maps' class boundaries, respectively. Based on the application of the weighted linear average technique, the determined W and MFFs parameters were synthesized to develop groundwater vulnerability potential index (GVPI)-based AHPDST model algorithm. The developed model was applied to establish four GVPI mass/belief function indices. The estimates based on the applied GVPI belief function indices were processed in GIS environment to create prospective groundwater vulnerability potential index maps. The most representative of the resulting vulnerability maps (the GVPIBel map) was considered for producing the groundwater vulnerability potential zones (GVPZ) map for the area. The produced GVPZ map established 48 and 52% of the areal extent to be covered by the lows/moderate and highs vulnerable zones, respectively. The success and the prediction rates of the produced GVPZ map were determined using the relative operating characteristics technique to give 82.3 and 77.7%, respectively. The analyzed results reveal that the developed GVPI-based AHPDST model algorithm is capable of producing efficient groundwater vulnerability potential zones prediction map and characterizing the predicted zones uncertainty via the DST mechanism processes in the area. The produced GVPZ map in this study can be used by decision makers to formulate appropriate groundwater management strategies and the approach may be well opted in other hard rock regions of the world, especially in economically poor nations.

Meta-modeling soil organic carbon sequestration potential and its application at regional scale.

PubMed

Luo, Zhongkui; Wang, Enli; Bryan, Brett A; King, Darran; Zhao, Gang; Pan, Xubin; Bende-Michl, Ulrike

2013-03-01

Upscaling the results from process-based soil-plant models to assess regional soil organic carbon (SOC) change and sequestration potential is a great challenge due to the lack of detailed spatial information, particularly soil properties. Meta-modeling can be used to simplify and summarize process-based models and significantly reduce the demand for input data and thus could be easily applied on regional scales. We used the pre-validated Agricultural Production Systems sIMulator (APSIM) to simulate the impact of climate, soil, and management on SOC at 613 reference sites across Australia's cereal-growing regions under a continuous wheat system. We then developed a simple meta-model to link the APSIM-modeled SOC change to primary drivers, i.e., the amount of recalcitrant SOC, plant available water capacity of soil, soil pH, and solar radiation, temperature, and rainfall in the growing season. Based on high-resolution soil texture data and 8165 climate data points across the study area, we used the meta-model to assess SOC sequestration potential and the uncertainty associated with the variability of soil characteristics. The meta-model explained 74% of the variation of final SOC content as simulated by APSIM. Applying the meta-model to Australia's cereal-growing regions reveals regional patterns in SOC, with higher SOC stock in cool, wet regions. Overall, the potential SOC stock ranged from 21.14 to 152.71 Mg/ha with a mean of 52.18 Mg/ha. Variation of soil properties induced uncertainty ranging from 12% to 117% with higher uncertainty in warm, wet regions. In general, soils in Australia's cereal-growing regions under continuous wheat production were simulated as a sink of atmospheric carbon dioxide with a mean sequestration potential of 8.17 Mg/ha.

Palaeomagnetic dating method accounting for post-depositional remanence and its application to geomagnetic field modelling

NASA Astrophysics Data System (ADS)

Nilsson, A.; Suttie, N.

2016-12-01

Sedimentary palaeomagnetic data may exhibit some degree of smoothing of the recorded field due to the gradual processes by which the magnetic signal is `locked-in' over time. Here we present a new Bayesian method to construct age-depth models based on palaeomagnetic data, taking into account and correcting for potential lock-in delay. The age-depth model is built on the widely used "Bacon" dating software by Blaauw and Christen (2011, Bayesian Analysis 6, 457-474) and is designed to combine both radiocarbon and palaeomagnetic measurements. To our knowledge, this is the first palaeomagnetic dating method that addresses the potential problems related post-depositional remanent magnetisation acquisition in age-depth modelling. Age-depth models, including site specific lock-in depth and lock-in filter function, produced with this method are shown to be consistent with independent results based on radiocarbon wiggle match dated sediment sections. Besides its primary use as a dating tool, our new method can also be used specifically to identify the most likely lock-in parameters for a specific record. We explore the potential to use these results to construct high-resolution geomagnetic field models based on sedimentary palaeomagnetic data, adjusting for smoothing induced by post-depositional remanent magnetisation acquisition. Potentially, this technique could enable reconstructions of Holocene geomagnetic field with the same amplitude of variability observed in archaeomagnetic field models for the past three millennia.

Deep Potential Molecular Dynamics: A Scalable Model with the Accuracy of Quantum Mechanics

NASA Astrophysics Data System (ADS)

Zhang, Linfeng; Han, Jiequn; Wang, Han; Car, Roberto; E, Weinan

2018-04-01

We introduce a scheme for molecular simulations, the deep potential molecular dynamics (DPMD) method, based on a many-body potential and interatomic forces generated by a carefully crafted deep neural network trained with ab initio data. The neural network model preserves all the natural symmetries in the problem. It is first-principles based in the sense that there are no ad hoc components aside from the network model. We show that the proposed scheme provides an efficient and accurate protocol in a variety of systems, including bulk materials and molecules. In all these cases, DPMD gives results that are essentially indistinguishable from the original data, at a cost that scales linearly with system size.

Atomistic simulations of TeO₂-based glasses: interatomic potentials and molecular dynamics.

PubMed

Gulenko, Anastasia; Masson, Olivier; Berghout, Abid; Hamani, David; Thomas, Philippe

2014-07-21

In this work we present for the first time empirical interatomic potentials that are able to reproduce TeO2-based systems. Using these potentials in classical molecular dynamics simulations, we obtained first results for the pure TeO2 glass structure model. The calculated pair distribution function is in good agreement with the experimental one, which indicates a realistic glass structure model. We investigated the short- and medium-range TeO2 glass structures. The local environment of the Te atom strongly varies, so that the glass structure model has a broad Q polyhedral distribution. The glass network is described as weakly connected with a large number of terminal oxygen atoms.

Parametrization of Stillinger-Weber potential based on valence force field model: application to single-layer MoS2 and black phosphorus

NASA Astrophysics Data System (ADS)

Jiang, Jin-Wu

2015-08-01

We propose parametrizing the Stillinger-Weber potential for covalent materials starting from the valence force-field model. All geometrical parameters in the Stillinger-Weber potential are determined analytically according to the equilibrium condition for each individual potential term, while the energy parameters are derived from the valence force-field model. This parametrization approach transfers the accuracy of the valence force field model to the Stillinger-Weber potential. Furthermore, the resulting Stilliinger-Weber potential supports stable molecular dynamics simulations, as each potential term is at an energy-minimum state separately at the equilibrium configuration. We employ this procedure to parametrize Stillinger-Weber potentials for single-layer MoS2 and black phosphorous. The obtained Stillinger-Weber potentials predict an accurate phonon spectrum and mechanical behaviors. We also provide input scripts of these Stillinger-Weber potentials used by publicly available simulation packages including GULP and LAMMPS.

Parametrization of Stillinger-Weber potential based on valence force field model: application to single-layer MoS2 and black phosphorus.

PubMed

Jiang, Jin-Wu

2015-08-07

We propose parametrizing the Stillinger-Weber potential for covalent materials starting from the valence force-field model. All geometrical parameters in the Stillinger-Weber potential are determined analytically according to the equilibrium condition for each individual potential term, while the energy parameters are derived from the valence force-field model. This parametrization approach transfers the accuracy of the valence force field model to the Stillinger-Weber potential. Furthermore, the resulting Stilliinger-Weber potential supports stable molecular dynamics simulations, as each potential term is at an energy-minimum state separately at the equilibrium configuration. We employ this procedure to parametrize Stillinger-Weber potentials for single-layer MoS2 and black phosphorous. The obtained Stillinger-Weber potentials predict an accurate phonon spectrum and mechanical behaviors. We also provide input scripts of these Stillinger-Weber potentials used by publicly available simulation packages including GULP and LAMMPS.

Global evaluation of biofuel potential from microalgae

PubMed Central

Moody, Jeffrey W.; McGinty, Christopher M.; Quinn, Jason C.

2014-01-01

In the current literature, the life cycle, technoeconomic, and resource assessments of microalgae-based biofuel production systems have relied on growth models extrapolated from laboratory-scale data, leading to a large uncertainty in results. This type of simplistic growth modeling overestimates productivity potential and fails to incorporate biological effects, geographical location, or cultivation architecture. This study uses a large-scale, validated, outdoor photobioreactor microalgae growth model based on 21 reactor- and species-specific inputs to model the growth of Nannochloropsis. This model accurately accounts for biological effects such as nutrient uptake, respiration, and temperature and uses hourly historical meteorological data to determine the current global productivity potential. Global maps of the current near-term microalgae lipid and biomass productivity were generated based on the results of annual simulations at 4,388 global locations. Maximum annual average lipid yields between 24 and 27 m3·ha−1·y−1, corresponding to biomass yields of 13 to 15 g·m−2·d−1, are possible in Australia, Brazil, Colombia, Egypt, Ethiopia, India, Kenya, and Saudi Arabia. The microalgae lipid productivity results of this study were integrated with geography-specific fuel consumption and land availability data to perform a scalability assessment. Results highlight the promising potential of microalgae-based biofuels compared with traditional terrestrial feedstocks. When water, nutrients, and CO2 are not limiting, many regions can potentially meet significant fractions of their transportation fuel requirements through microalgae production, without land resource restriction. Discussion focuses on sensitivity of monthly variability in lipid production compared with annual average yields, effects of temperature on productivity, and a comparison of results with previous published modeling assumptions. PMID:24912176

Biophysically based mathematical modeling of interstitial cells of Cajal slow wave activity generated from a discrete unitary potential basis.

PubMed

Faville, R A; Pullan, A J; Sanders, K M; Koh, S D; Lloyd, C M; Smith, N P

2009-06-17

Spontaneously rhythmic pacemaker activity produced by interstitial cells of Cajal (ICC) is the result of the entrainment of unitary potential depolarizations generated at intracellular sites termed pacemaker units. In this study, we present a mathematical modeling framework that quantitatively represents the transmembrane ion flows and intracellular Ca2+ dynamics from a single ICC operating over the physiological membrane potential range. The mathematical model presented here extends our recently developed biophysically based pacemaker unit modeling framework by including mechanisms necessary for coordinating unitary potential events, such as a T-Type Ca2+ current, Vm-dependent K+ currents, and global Ca2+ diffusion. Model simulations produce spontaneously rhythmic slow wave depolarizations with an amplitude of 65 mV at a frequency of 17.4 cpm. Our model predicts that activity at the spatial scale of the pacemaker unit is fundamental for ICC slow wave generation, and Ca2+ influx from activation of the T-Type Ca2+ current is required for unitary potential entrainment. These results suggest that intracellular Ca2+ levels, particularly in the region local to the mitochondria and endoplasmic reticulum, significantly influence pacing frequency and synchronization of pacemaker unit discharge. Moreover, numerical investigations show that our ICC model is capable of qualitatively replicating a wide range of experimental observations.

New statistical potential for quality assessment of protein models and a survey of energy functions

PubMed Central

2010-01-01

Background Scoring functions, such as molecular mechanic forcefields and statistical potentials are fundamentally important tools in protein structure modeling and quality assessment. Results The performances of a number of publicly available scoring functions are compared with a statistical rigor, with an emphasis on knowledge-based potentials. We explored the effect on accuracy of alternative choices for representing interaction center types and other features of scoring functions, such as using information on solvent accessibility, on torsion angles, accounting for secondary structure preferences and side chain orientation. Partially based on the observations made, we present a novel residue based statistical potential, which employs a shuffled reference state definition and takes into account the mutual orientation of residue side chains. Atom- and residue-level statistical potentials and Linux executables to calculate the energy of a given protein proposed in this work can be downloaded from http://www.fiserlab.org/potentials. Conclusions Among the most influential terms we observed a critical role of a proper reference state definition and the benefits of including information about the microenvironment of interaction centers. Molecular mechanical potentials were also tested and found to be over-sensitive to small local imperfections in a structure, requiring unfeasible long energy relaxation before energy scores started to correlate with model quality. PMID:20226048

Estimating the potential of energy saving and carbon emission mitigation of cassava-based fuel ethanol using life cycle assessment coupled with a biogeochemical process model

NASA Astrophysics Data System (ADS)

Jiang, Dong; Hao, Mengmeng; Fu, Jingying; Tian, Guangjin; Ding, Fangyu

2017-09-01

Global warming and increasing concentration of atmospheric greenhouse gas (GHG) have prompted considerable interest in the potential role of energy plant biomass. Cassava-based fuel ethanol is one of the most important bioenergy and has attracted much attention in both developed and developing countries. However, the development of cassava-based fuel ethanol is still faced with many uncertainties, including raw material supply, net energy potential, and carbon emission mitigation potential. Thus, an accurate estimation of these issues is urgently needed. This study provides an approach to estimate energy saving and carbon emission mitigation potentials of cassava-based fuel ethanol through LCA (life cycle assessment) coupled with a biogeochemical process model—GEPIC (GIS-based environmental policy integrated climate) model. The results indicate that the total potential of cassava yield on marginal land in China is 52.51 million t; the energy ratio value varies from 0.07 to 1.44, and the net energy surplus of cassava-based fuel ethanol in China is 92,920.58 million MJ. The total carbon emission mitigation from cassava-based fuel ethanol in China is 4593.89 million kgC. Guangxi, Guangdong, and Fujian are identified as target regions for large-scale development of cassava-based fuel ethanol industry. These results can provide an operational approach and fundamental data for scientific research and energy planning.

Study of a risk-based piping inspection guideline system.

PubMed

Tien, Shiaw-Wen; Hwang, Wen-Tsung; Tsai, Chih-Hung

2007-02-01

A risk-based inspection system and a piping inspection guideline model were developed in this study. The research procedure consists of two parts--the building of a risk-based inspection model for piping and the construction of a risk-based piping inspection guideline model. Field visits at the plant were conducted to develop the risk-based inspection and strategic analysis system. A knowledge-based model had been built in accordance with international standards and local government regulations, and the rational unified process was applied for reducing the discrepancy in the development of the models. The models had been designed to analyze damage factors, damage models, and potential damage positions of piping in the petrochemical plants. The purpose of this study was to provide inspection-related personnel with the optimal planning tools for piping inspections, hence, to enable effective predictions of potential piping risks and to enhance the better degree of safety in plant operations that the petrochemical industries can be expected to achieve. A risk analysis was conducted on the piping system of a petrochemical plant. The outcome indicated that most of the risks resulted from a small number of pipelines.

Inside The Zone of Proximal Development: Validating A Multifactor Model Of Learning Potential With Gifted Students And Their Peers

ERIC Educational Resources Information Center

Kanevsky, Lannie; Geake, John

2004-01-01

Kanevsky (1995b) proposed a model of learning potential based on Vygotsky?s notions of "good learning" and the zone of proximal development. This study investigated the contributions of general knowledge, information processing efficiency, and metacognition to differences in the learning potential of 5 gifted nongifted students.…

Emergence of cytotoxic resistance in cancer cell populations: Single-cell mechanisms and population-level consequences

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

Lorenzi, Tommaso; Chisholm, Rebecca H.; Lorz, Alexander

We formulate an individual-based model and a population model of phenotypic evolution, under cytotoxic drugs, in a cancer cell population structured by the expression levels of survival-potential and proliferation-potential. We apply these models to a recently studied experimental system. Our results suggest that mechanisms based on fundamental laws of biology can reversibly push an actively-proliferating, and drug-sensitive, cell population to transition into a weakly-proliferative and drug-tolerant state, which will eventually facilitate the emergence of more potent, proliferating and drug-tolerant cells.

[Hardware Implementation of Numerical Simulation Function of Hodgkin-Huxley Model Neurons Action Potential Based on Field Programmable Gate Array].

PubMed

Wang, Jinlong; Lu, Mai; Hu, Yanwen; Chen, Xiaoqiang; Pan, Qiangqiang

2015-12-01

Neuron is the basic unit of the biological neural system. The Hodgkin-Huxley (HH) model is one of the most realistic neuron models on the electrophysiological characteristic description of neuron. Hardware implementation of neuron could provide new research ideas to clinical treatment of spinal cord injury, bionics and artificial intelligence. Based on the HH model neuron and the DSP Builder technology, in the present study, a single HH model neuron hardware implementation was completed in Field Programmable Gate Array (FPGA). The neuron implemented in FPGA was stimulated by different types of current, the action potential response characteristics were analyzed, and the correlation coefficient between numerical simulation result and hardware implementation result were calculated. The results showed that neuronal action potential response of FPGA was highly consistent with numerical simulation result. This work lays the foundation for hardware implementation of neural network.

HYSOGs250m, global gridded hydrologic soil groups for curve-number-based runoff modeling.

PubMed

Ross, C Wade; Prihodko, Lara; Anchang, Julius; Kumar, Sanath; Ji, Wenjie; Hanan, Niall P

2018-05-15

Hydrologic soil groups (HSGs) are a fundamental component of the USDA curve-number (CN) method for estimation of rainfall runoff; yet these data are not readily available in a format or spatial-resolution suitable for regional- and global-scale modeling applications. We developed a globally consistent, gridded dataset defining HSGs from soil texture, bedrock depth, and groundwater. The resulting data product-HYSOGs250m-represents runoff potential at 250 m spatial resolution. Our analysis indicates that the global distribution of soil is dominated by moderately high runoff potential, followed by moderately low, high, and low runoff potential. Low runoff potential, sandy soils are found primarily in parts of the Sahara and Arabian Deserts. High runoff potential soils occur predominantly within tropical and sub-tropical regions. No clear pattern could be discerned for moderately low runoff potential soils, as they occur in arid and humid environments and at both high and low elevations. Potential applications of this data include CN-based runoff modeling, flood risk assessment, and as a covariate for biogeographical analysis of vegetation distributions.

Creep fatigue life prediction for engine hot section materials (ISOTROPIC)

NASA Technical Reports Server (NTRS)

Nelson, R. S.; Schoendorf, J. F.; Lin, L. S.

1986-01-01

The specific activities summarized include: verification experiments (base program); thermomechanical cycling model; multiaxial stress state model; cumulative loading model; screening of potential environmental and protective coating models; and environmental attack model.

Unscented Kalman filter assimilation of time-lapse self-potential data for monitoring solute transport

NASA Astrophysics Data System (ADS)

Cui, Yi-an; Liu, Lanbo; Zhu, Xiaoxiong

2017-08-01

Monitoring the extent and evolution of contaminant plumes in local and regional groundwater systems from existing landfills is critical in contamination control and remediation. The self-potential survey is an efficient and economical nondestructive geophysical technique that can be used to investigate underground contaminant plumes. Based on the unscented transform, we have built a Kalman filtering cycle to conduct time-lapse data assimilation for monitoring the transport of solute based on the solute transport experiment using a bench-scale physical model. The data assimilation was formed by modeling the evolution based on the random walk model and observation correcting based on the self-potential forward. Thus, monitoring self-potential data can be inverted by the data assimilation technique. As a result, we can reconstruct the dynamic process of the contaminant plume instead of using traditional frame-to-frame static inversion, which may cause inversion artifacts. The data assimilation inversion algorithm was evaluated through noise-added synthetic time-lapse self-potential data. The result of the numerical experiment shows validity, accuracy and tolerance to the noise of the dynamic inversion. To validate the proposed algorithm, we conducted a scaled-down sandbox self-potential observation experiment to generate time-lapse data that closely mimics the real-world contaminant monitoring setup. The results of physical experiments support the idea that the data assimilation method is a potentially useful approach for characterizing the transport of contamination plumes using the unscented Kalman filter (UKF) data assimilation technique applied to field time-lapse self-potential data.

Protein requirements for long term missions

NASA Technical Reports Server (NTRS)

Stein, T. P.

1994-01-01

A key component of the diet for a space mission is protein. This first part of this paper reviews the reasons for emphasizing protein nurtition and then discusses what the requirements are likely to be. The second part discusses potential advantages of modifying these requirements and describes potential potential approaches to effecting these modificatons based on well established ground based models.

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

PubMed

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

2008-01-15

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

Physiologically-based pharmacokinetic (PBPK) modeling to explore potential metabolic pathways of bromochloromethane in rats.

EPA Science Inventory

Bromochloromethane (BCM) is a volatile organic compound and a by-product of disinfection of water by chlorination. Physiologically based pharmacokinetic (PBPK) models are used in risk assessment applications and a PBPK model for BCM, Updated with F-344 specific input parameters,...

Approaches for Increasing Acceptance of Physiologically Based Pharmacokinetic Models in Public Health Risk Assessment

EPA Science Inventory

Physiologically based pharmacokinetic (PBPK) models have great potential for application in regulatory and non-regulatory public health risk assessment. The development and application of PBPK models in chemical toxicology has grown steadily since their emergence in the 1980s. Ho...

Model of Rescue Units Control in Event of Potential Emergency

NASA Astrophysics Data System (ADS)

Kalach, A. V.; Kravchenko, A. S.; Soloviev, A. S.; Nesterov, A. A.

2018-05-01

A problem of organization and efficiency improvement of the system controlling the rescue units of the Ministry of Civil Defense and Emergency Response of the Russian Federation considered using the example of potential hydrological emergency, a model of a system for controlling rescue units in the event of potential hydrological emergency. The problem solution is based on mathematical models of operational control of rescue units and assessment of a hydrological situation of area flooding.

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

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

Kerisit, Sebastien N.; Liu, Chongxuan

2013-08-20

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

Potential distribution of the viral haemorrhagic septicaemia virus in the Great Lakes region

USGS Publications Warehouse

Escobar, Luis E.; Kurath, Gael; Escobar-Dodero, Joaquim; Craft, Meggan E.; Phelps, Nicholas B.D.

2017-01-01

Viral haemorrhagic septicaemia virus (VHSV) genotype IVb has been responsible for large-scale fish mortality events in the Great Lakes of North America. Anticipating the areas of potential VHSV occurrence is key to designing epidemiological surveillance and disease prevention strategies in the Great Lakes basin. We explored the environmental features that could shape the distribution of VHSV, based on remote sensing and climate data via ecological niche modelling. Variables included temperature measured during the day and night, precipitation, vegetation, bathymetry, solar radiation and topographic wetness. VHSV occurrences were obtained from available reports of virus confirmation in laboratory facilities. We fit a Maxent model using VHSV-IVb reports and environmental variables under different parameterizations to identify the best model to determine potential VHSV occurrence based on environmental suitability. VHSV reports were generated from both passive and active surveillance. VHSV occurrences were most abundant near shore sites. We were, however, able to capture the environmental signature of VHSV based on the environmental variables employed in our model, allowing us to identify patterns of VHSV potential occurrence. Our findings suggest that VHSV is not at an ecological equilibrium and more areas could be affected, including areas not in close geographic proximity to past VHSV reports.

Analyses on hydrophobicity and attractiveness of all-atom distance-dependent potentials

PubMed Central

Shirota, Matsuyuki; Ishida, Takashi; Kinoshita, Kengo

2009-01-01

Accurate model evaluation is a crucial step in protein structure prediction. For this purpose, statistical potentials, which evaluate a model structure based on the observed atomic distance frequencies in comparison with those in reference states, have been widely used. The reference state is a virtual state where all of the atomic interactions are turned off, and it provides a standard to measure the observed frequencies. In this study, we examined seven all-atom distance-dependent potentials with different reference states. As results, we observed that the variations of atom pair composition and those of distance distributions in the reference states produced systematic changes in the hydrophobic and attractive characteristics of the potentials. The performance evaluations with the CASP7 structures indicated that the preference of hydrophobic interactions improved the correlation between the energy and the GDT-TS score, but decreased the Z-score of the native structure. The attractiveness of potential improved both the correlation and Z-score for template-based modeling targets, but the benefit was smaller in free modeling targets. These results indicated that the performances of the potentials were more strongly influenced by their characteristics than by the accuracy of the definitions of the reference states. PMID:19588493

Targeting Dengue Virus NS-3 Helicase by Ligand based Pharmacophore Modeling and Structure based Virtual Screening

NASA Astrophysics Data System (ADS)

Halim, Sobia A.; Khan, Shanza; Khan, Ajmal; Wadood, Abdul; Mabood, Fazal; Hussain, Javid; Al-Harrasi, Ahmed

2017-10-01

Dengue fever is an emerging public health concern, with several million viral infections occur annually, for which no effective therapy currently exist. Non-structural protein 3 (NS-3) Helicase encoded by the dengue virus (DENV) is considered as a potential drug target to design new and effective drugs against dengue. Helicase is involved in unwinding of dengue RNA. This study was conducted to design new NS-3 Helicase inhibitor by in silico ligand- and structure based approaches. Initially ligand-based pharmacophore model was generated that was used to screen a set of 1201474 compounds collected from ZINC Database. The compounds matched with the pharmacophore model were docked into the active site of NS-3 helicase. Based on docking scores and binding interactions, twenty five compounds are suggested to be potential inhibitors of NS3 Helicase. The pharmacokinetic properties of these hits were predicted. The selected hits revealed acceptable ADMET properties. This study identified potential inhibitors of NS-3 Helicase in silico, and can be helpful in the treatment of Dengue.

Soft tissue deformation modelling through neural dynamics-based reaction-diffusion mechanics.

PubMed

Zhang, Jinao; Zhong, Yongmin; Gu, Chengfan

2018-05-30

Soft tissue deformation modelling forms the basis of development of surgical simulation, surgical planning and robotic-assisted minimally invasive surgery. This paper presents a new methodology for modelling of soft tissue deformation based on reaction-diffusion mechanics via neural dynamics. The potential energy stored in soft tissues due to a mechanical load to deform tissues away from their rest state is treated as the equivalent transmembrane potential energy, and it is distributed in the tissue masses in the manner of reaction-diffusion propagation of nonlinear electrical waves. The reaction-diffusion propagation of mechanical potential energy and nonrigid mechanics of motion are combined to model soft tissue deformation and its dynamics, both of which are further formulated as the dynamics of cellular neural networks to achieve real-time computational performance. The proposed methodology is implemented with a haptic device for interactive soft tissue deformation with force feedback. Experimental results demonstrate that the proposed methodology exhibits nonlinear force-displacement relationship for nonlinear soft tissue deformation. Homogeneous, anisotropic and heterogeneous soft tissue material properties can be modelled through the inherent physical properties of mass points. Graphical abstract Soft tissue deformation modelling with haptic feedback via neural dynamics-based reaction-diffusion mechanics.

Application of discriminant analysis-based model for prediction of risk of low back disorders due to workplace design in industrial jobs.

PubMed

Ganga, G M D; Esposto, K F; Braatz, D

2012-01-01

The occupational exposure limits of different risk factors for development of low back disorders (LBDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors for LBDs interact in causing injury, since the nature and mechanism of these disorders are relatively unknown phenomena. Industrial ergonomists' role becomes further complicated because the potential risk factors that may contribute towards the onset of LBDs interact in a complex manner, which makes it difficult to discriminate in detail among the jobs that place workers at high or low risk of LBDs. The purpose of this paper was to develop a comparative study between predictions based on the neural network-based model proposed by Zurada, Karwowski & Marras (1997) and a linear discriminant analysis model, for making predictions about industrial jobs according to their potential risk of low back disorders due to workplace design. The results obtained through applying the discriminant analysis-based model proved that it is as effective as the neural network-based model. Moreover, the discriminant analysis-based model proved to be more advantageous regarding cost and time savings for future data gathering.

Application of Dempster-Shafer theory of evidence model to geoelectric and hydraulic parameters for groundwater potential zonation

NASA Astrophysics Data System (ADS)

Mogaji, Kehinde Anthony; Lim, Hwee San

2018-06-01

The application of a GIS - based Dempster - Shafer data driven model named as evidential belief function EBF- methodology to groundwater potential conditioning factors (GPCFs) derived from geophysical and hydrogeological data sets for assessing groundwater potentiality was presented in this study. The proposed method's efficacy in managing degree of uncertainty in spatial predictive models motivated this research. The method procedural approaches entail firstly, the database containing groundwater data records (bore wells location inventory, hydrogeological data record, etc.) and geophysical measurement data construction. From the database, different influencing groundwater occurrence factors, namely aquifer layer thickness, aquifer layer resistivity, overburden material resistivity, overburden material thickness, aquifer hydraulic conductivity and aquifer transmissivity were extracted and prepared. Further, the bore well location inventories were partitioned randomly into a ratio of 70% (19 wells) for model training and 30% (9 wells) for model testing. The synthesized of the GPCFs via applying the DS - EBF model algorithms produced the groundwater productivity potential index (GPPI) map which demarcated the area into low - medium, medium, medium - high and high potential zones. The analyzed percentage degree of uncertainty for the predicted lows potential zones classes and mediums/highs potential zones classes are >10% and <10%, respectively. The DS theory model-based GPPI map's validation through ROC approach established prediction rate accuracy of 88.8%. Successively, the determined transverse resistance (TR) values in the range of 1280 and 30,000 Ω my for the area geoelectrically delineated aquifer units of the predicted potential zones through Dar - Zarrouk Parameter analysis quantitatively confirm the DS theory modeling prediction results. This research results have expand the capability of DS - EBF model in predictive modeling by effective uncertainty management. Thus, the produced map could form part of decision support system reliable to be used by local authorities for groundwater exploitation and management in the area.

Screening a repurposing library for potentiators of antibiotics against Staphylococcus aureus biofilms.

PubMed

Van den Driessche, Freija; Brackman, Gilles; Swimberghe, Rosalie; Rigole, Petra; Coenye, Tom

2017-03-01

Staphylococcus aureus biofilms are involved in a wide range of infections that are extremely difficult to treat with conventional antibiotic therapy. We aimed to identify potentiators of antibiotics against mature biofilms of S. aureus Mu50, a methicillin-resistant and vancomycin-intermediate-resistant strain. Over 700 off-patent drugs from a repurposing library were screened in combination with vancomycin in a microtitre plate (MTP)-based biofilm model system. This led to the identification of 25 hit compounds, including four phenothiazines among which thioridazine was the most potent. Their activity was evaluated in combination with other antibiotics both against planktonic and biofilm-grown S. aureus cells. The most promising combinations were subsequently tested in an in vitro chronic wound biofilm infection model. Although no synergistic activity was observed against planktonic cells, thioridazine potentiated the activity of tobramycin, linezolid and flucloxacillin against S. aureus biofilm cells. However, this effect was only observed in a general biofilm model and not in a chronic wound model of biofilm infection. Several drug compounds were identified that potentiated the activity of vancomycin against biofilms formed in a MTP-based biofilm model. A selected hit compound lost its potentiating activity in a model that mimics specific aspects of wound biofilms. This study provides a platform for discovering and evaluating potentiators against bacterial biofilms and highlights the necessity of using relevant in vitro biofilm model systems. Copyright © 2017 Elsevier B.V. and International Society of Chemotherapy. All rights reserved.

TOWARDS REFINED USE OF TOXICITY DATA IN STATISTICALLY BASED SAR MODELS FOR DEVELOPMENTAL TOXICITY.

EPA Science Inventory

In 2003, an International Life Sciences Institute (ILSI) Working Group examined the potential of statistically based structure-activity relationship (SAR) models for use in screening environmental contaminants for possible developmental toxicants.

Sustainable High-Potential Career Development: A Resource-Based View.

ERIC Educational Resources Information Center

Iles, Paul

1997-01-01

In the current economic climate, fast-track career models pose problems for individuals and organizations. An alternative model uses a resource-based view of the company and principles of sustainable development borrowed from environmentalism. (SK)

In Silico Neuro-Oncology: Brownian Motion-Based Mathematical Treatment as a Potential Platform for Modeling the Infiltration of Glioma Cells into Normal Brain Tissue.

PubMed

Antonopoulos, Markos; Stamatakos, Georgios

2015-01-01

Intensive glioma tumor infiltration into the surrounding normal brain tissues is one of the most critical causes of glioma treatment failure. To quantitatively understand and mathematically simulate this phenomenon, several diffusion-based mathematical models have appeared in the literature. The majority of them ignore the anisotropic character of diffusion of glioma cells since availability of pertinent truly exploitable tomographic imaging data is limited. Aiming at enriching the anisotropy-enhanced glioma model weaponry so as to increase the potential of exploiting available tomographic imaging data, we propose a Brownian motion-based mathematical analysis that could serve as the basis for a simulation model estimating the infiltration of glioblastoma cells into the surrounding brain tissue. The analysis is based on clinical observations and exploits diffusion tensor imaging (DTI) data. Numerical simulations and suggestions for further elaboration are provided.

A neuro-inspired model-based closed-loop neuroprosthesis for the substitution of a cerebellar learning function in anesthetized rats

NASA Astrophysics Data System (ADS)

Hogri, Roni; Bamford, Simeon A.; Taub, Aryeh H.; Magal, Ari; Giudice, Paolo Del; Mintz, Matti

2015-02-01

Neuroprostheses could potentially recover functions lost due to neural damage. Typical neuroprostheses connect an intact brain with the external environment, thus replacing damaged sensory or motor pathways. Recently, closed-loop neuroprostheses, bidirectionally interfaced with the brain, have begun to emerge, offering an opportunity to substitute malfunctioning brain structures. In this proof-of-concept study, we demonstrate a neuro-inspired model-based approach to neuroprostheses. A VLSI chip was designed to implement essential cerebellar synaptic plasticity rules, and was interfaced with cerebellar input and output nuclei in real time, thus reproducing cerebellum-dependent learning in anesthetized rats. Such a model-based approach does not require prior system identification, allowing for de novo experience-based learning in the brain-chip hybrid, with potential clinical advantages and limitations when compared to existing parametric ``black box'' models.

An Accurate Temperature Correction Model for Thermocouple Hygrometers 1

PubMed Central

Savage, Michael J.; Cass, Alfred; de Jager, James M.

1982-01-01

Numerous water relation studies have used thermocouple hygrometers routinely. However, the accurate temperature correction of hygrometer calibration curve slopes seems to have been largely neglected in both psychrometric and dewpoint techniques. In the case of thermocouple psychrometers, two temperature correction models are proposed, each based on measurement of the thermojunction radius and calculation of the theoretical voltage sensitivity to changes in water potential. The first model relies on calibration at a single temperature and the second at two temperatures. Both these models were more accurate than the temperature correction models currently in use for four psychrometers calibrated over a range of temperatures (15-38°C). The model based on calibration at two temperatures is superior to that based on only one calibration. The model proposed for dewpoint hygrometers is similar to that for psychrometers. It is based on the theoretical voltage sensitivity to changes in water potential. Comparison with empirical data from three dewpoint hygrometers calibrated at four different temperatures indicates that these instruments need only be calibrated at, e.g. 25°C, if the calibration slopes are corrected for temperature. PMID:16662241

Application of multimedia models for screening assessment of long-range transport potential and overall persistence.

PubMed

Klasmeier, Jörg; Matthies, Michael; Macleod, Matthew; Fenner, Kathrin; Scheringer, Martin; Stroebe, Maximilian; Le Gall, Anne Christine; Mckone, Thomas; Van De Meent, Dik; Wania, Frank

2006-01-01

We propose a multimedia model-based methodology to evaluate whether a chemical substance qualifies as POP-like based on overall persistence (Pov) and potential for long-range transport (LRTP). It relies upon screening chemicals against the Pov and LRTP characteristics of selected reference chemicals with well-established environmental fates. Results indicate that chemicals of high and low concern in terms of persistence and long-range transport can be consistently identified by eight contemporary multimedia models using the proposed methodology. Model results for three hypothetical chemicals illustrate that the model-based classification of chemicals according to Pov and LRTP is not always consistent with the single-media half-life approach proposed by the UNEP Stockholm Convention and thatthe models provide additional insight into the likely long-term hazards associated with chemicals in the environment. We suggest this model-based classification method be adopted as a complement to screening against defined half-life criteria at the initial stages of tiered assessments designed to identify POP-like chemicals and to prioritize further environmental fate studies for new and existing chemicals.

Potential for the dynamics of pedestrians in a socially interacting group

NASA Astrophysics Data System (ADS)

Zanlungo, Francesco; Ikeda, Tetsushi; Kanda, Takayuki

2014-01-01

We introduce a simple potential to describe the dynamics of the relative motion of two pedestrians socially interacting in a walking group. We show that the proposed potential, based on basic empirical observations and theoretical considerations, can qualitatively describe the statistical properties of pedestrian behavior. In detail, we show that the two-dimensional probability distribution of the relative distance is determined by the proposed potential through a Boltzmann distribution. After calibrating the parameters of the model on the two-pedestrian group data, we apply the model to three-pedestrian groups, showing that it describes qualitatively and quantitatively well their behavior. In particular, the model predicts that three-pedestrian groups walk in a V-shaped formation and provides accurate values for the position of the three pedestrians. Furthermore, the model correctly predicts the average walking velocity of three-person groups based on the velocity of two-person ones. Possible extensions to larger groups, along with alternative explanations of the social dynamics that may be implied by our model, are discussed at the end of the paper.

A threshold-based weather model for predicting stripe rust infection in winter wheat

USDA-ARS?s Scientific Manuscript database

Wheat stripe rust (WSR) (caused by Puccinia striiformis sp. tritici) is a major threat in most wheat growing regions worldwide, with potential to inflict regular yield losses when environmental conditions are favorable. We propose a threshold-based disease-forecasting model using a stepwise modeling...

Integrating distributional, spatial prioritization, and individual-based models to evaluate potential critical habitat networks: A case study using the Northern Spotted Owl

EPA Science Inventory

As part of the northern spotted owl recovery planning effort, we evaluated a series of alternative critical habitat scenarios using a species-distribution model (MaxEnt), a conservation-planning model (Zonation), and an individual-based population model (HexSim). With this suite ...

EVALUATING REGIONAL PREDICTIVE CAPACITY OF A PROCESS-BASED MERCURY EXPOSURE MODEL, REGIONAL-MERCURY CYCLING MODEL (R-MCM), APPLIED TO 91 VERMONT AND NEW HAMPSHIRE LAKES AND PONDS, USA

EPA Science Inventory

Regulatory agencies must develop fish consumption advisories for many lakes and rivers with limited resources. Process-based mathematical models are potentially valuable tools for developing regional fish advisories. The Regional Mercury Cycling model (R-MCM) was specifically d...

Limited view angle iterative CT reconstruction

NASA Astrophysics Data System (ADS)

Kisner, Sherman J.; Haneda, Eri; Bouman, Charles A.; Skatter, Sondre; Kourinny, Mikhail; Bedford, Simon

2012-03-01

Computed Tomography (CT) is widely used for transportation security to screen baggage for potential threats. For example, many airports use X-ray CT to scan the checked baggage of airline passengers. The resulting reconstructions are then used for both automated and human detection of threats. Recently, there has been growing interest in the use of model-based reconstruction techniques for application in CT security systems. Model-based reconstruction offers a number of potential advantages over more traditional direct reconstruction such as filtered backprojection (FBP). Perhaps one of the greatest advantages is the potential to reduce reconstruction artifacts when non-traditional scan geometries are used. For example, FBP tends to produce very severe streaking artifacts when applied to limited view data, which can adversely affect subsequent processing such as segmentation and detection. In this paper, we investigate the use of model-based reconstruction in conjunction with limited-view scanning architectures, and we illustrate the value of these methods using transportation security examples. The advantage of limited view architectures is that it has the potential to reduce the cost and complexity of a scanning system, but its disadvantage is that limited-view data can result in structured artifacts in reconstructed images. Our method of reconstruction depends on the formulation of both a forward projection model for the system, and a prior model that accounts for the contents and densities of typical baggage. In order to evaluate our new method, we use realistic models of baggage with randomly inserted simple simulated objects. Using this approach, we show that model-based reconstruction can substantially reduce artifacts and improve important metrics of image quality such as the accuracy of the estimated CT numbers.

A Methodology for Calculating EGS Electricity Generation Potential Based on the Gringarten Model for Heat Extraction From Fractured Rock

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

Augustine, Chad

Existing methodologies for estimating the electricity generation potential of Enhanced Geothermal Systems (EGS) assume thermal recovery factors of 5% or less, resulting in relatively low volumetric electricity generation potentials for EGS reservoirs. This study proposes and develops a methodology for calculating EGS electricity generation potential based on the Gringarten conceptual model and analytical solution for heat extraction from fractured rock. The electricity generation potential of a cubic kilometer of rock as a function of temperature is calculated assuming limits on the allowed produced water temperature decline and reservoir lifetime based on surface power plant constraints. The resulting estimates of EGSmore » electricity generation potential can be one to nearly two-orders of magnitude larger than those from existing methodologies. The flow per unit fracture surface area from the Gringarten solution is found to be a key term in describing the conceptual reservoir behavior. The methodology can be applied to aid in the design of EGS reservoirs by giving minimum reservoir volume, fracture spacing, number of fractures, and flow requirements for a target reservoir power output. Limitations of the idealized model compared to actual reservoir performance and the implications on reservoir design are discussed.« less

Reverse engineering model structures for soil and ecosystem respiration: the potential of gene expression programming

NASA Astrophysics Data System (ADS)

Ilie, Iulia; Dittrich, Peter; Carvalhais, Nuno; Jung, Martin; Heinemeyer, Andreas; Migliavacca, Mirco; Morison, James I. L.; Sippel, Sebastian; Subke, Jens-Arne; Wilkinson, Matthew; Mahecha, Miguel D.

2017-09-01

Accurate model representation of land-atmosphere carbon fluxes is essential for climate projections. However, the exact responses of carbon cycle processes to climatic drivers often remain uncertain. Presently, knowledge derived from experiments, complemented by a steadily evolving body of mechanistic theory, provides the main basis for developing such models. The strongly increasing availability of measurements may facilitate new ways of identifying suitable model structures using machine learning. Here, we explore the potential of gene expression programming (GEP) to derive relevant model formulations based solely on the signals present in data by automatically applying various mathematical transformations to potential predictors and repeatedly evolving the resulting model structures. In contrast to most other machine learning regression techniques, the GEP approach generates readable models that allow for prediction and possibly for interpretation. Our study is based on two cases: artificially generated data and real observations. Simulations based on artificial data show that GEP is successful in identifying prescribed functions, with the prediction capacity of the models comparable to four state-of-the-art machine learning methods (random forests, support vector machines, artificial neural networks, and kernel ridge regressions). Based on real observations we explore the responses of the different components of terrestrial respiration at an oak forest in south-eastern England. We find that the GEP-retrieved models are often better in prediction than some established respiration models. Based on their structures, we find previously unconsidered exponential dependencies of respiration on seasonal ecosystem carbon assimilation and water dynamics. We noticed that the GEP models are only partly portable across respiration components, the identification of a general terrestrial respiration model possibly prevented by equifinality issues. Overall, GEP is a promising tool for uncovering new model structures for terrestrial ecology in the data-rich era, complementing more traditional modelling approaches.

Support vector machines-based modelling of seismic liquefaction potential

NASA Astrophysics Data System (ADS)

Pal, Mahesh

2006-08-01

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

Biophysically Based Mathematical Modeling of Interstitial Cells of Cajal Slow Wave Activity Generated from a Discrete Unitary Potential Basis

PubMed Central

Faville, R.A.; Pullan, A.J.; Sanders, K.M.; Koh, S.D.; Lloyd, C.M.; Smith, N.P.

2009-01-01

Abstract Spontaneously rhythmic pacemaker activity produced by interstitial cells of Cajal (ICC) is the result of the entrainment of unitary potential depolarizations generated at intracellular sites termed pacemaker units. In this study, we present a mathematical modeling framework that quantitatively represents the transmembrane ion flows and intracellular Ca2+ dynamics from a single ICC operating over the physiological membrane potential range. The mathematical model presented here extends our recently developed biophysically based pacemaker unit modeling framework by including mechanisms necessary for coordinating unitary potential events, such as a T-Type Ca2+ current, Vm-dependent K+ currents, and global Ca2+ diffusion. Model simulations produce spontaneously rhythmic slow wave depolarizations with an amplitude of 65 mV at a frequency of 17.4 cpm. Our model predicts that activity at the spatial scale of the pacemaker unit is fundamental for ICC slow wave generation, and Ca2+ influx from activation of the T-Type Ca2+ current is required for unitary potential entrainment. These results suggest that intracellular Ca2+ levels, particularly in the region local to the mitochondria and endoplasmic reticulum, significantly influence pacing frequency and synchronization of pacemaker unit discharge. Moreover, numerical investigations show that our ICC model is capable of qualitatively replicating a wide range of experimental observations. PMID:19527643

Computational fluid dynamics-habitat suitability index (CFD-HSI) modelling as an exploratory tool for assessing passability of riverine migratory challenge zones for fish

USGS Publications Warehouse

Haro, Alexander J.; Chelminski, Michael; Dudley, Robert W.

2015-01-01

We developed two-dimensional computational fluid hydraulics-habitat suitability index (CFD-HSI) models to identify and qualitatively assess potential zones of shallow water depth and high water velocity that may present passage challenges for five major anadromous fish species in a 2.63-km reach of the main stem Penobscot River, Maine, as a result of a dam removal downstream of the reach. Suitability parameters were based on distribution of fish lengths and body depths and transformed to cruising, maximum sustained and sprint swimming speeds. Zones of potential depth and velocity challenges were calculated based on the hydraulic models; ability of fish to pass a challenge zone was based on the percent of river channel that the contiguous zone spanned and its maximum along-current length. Three river flows (low: 99.1 m3 sec-1; normal: 344.9 m3 sec-1; and high: 792.9 m3 sec-1) were modelled to simulate existing hydraulic conditions and hydraulic conditions simulating removal of a dam at the downstream boundary of the reach. Potential depth challenge zones were nonexistent for all low-flow simulations of existing conditions for deeper-bodied fishes. Increasing flows for existing conditions and removal of the dam under all flow conditions increased the number and size of potential velocity challenge zones, with the effects of zones being more pronounced for smaller species. The two-dimensional CFD-HSI model has utility in demonstrating gross effects of flow and hydraulic alteration, but may not be as precise a predictive tool as a three-dimensional model. Passability of the potential challenge zones cannot be precisely quantified for two-dimensional or three-dimensional models due to untested assumptions and incomplete data on fish swimming performance and behaviours.

Developing a probability-based model of aquifer vulnerability in an agricultural region

NASA Astrophysics Data System (ADS)

Chen, Shih-Kai; Jang, Cheng-Shin; Peng, Yi-Huei

2013-04-01

SummaryHydrogeological settings of aquifers strongly influence the regional groundwater movement and pollution processes. Establishing a map of aquifer vulnerability is considerably critical for planning a scheme of groundwater quality protection. This study developed a novel probability-based DRASTIC model of aquifer vulnerability in the Choushui River alluvial fan, Taiwan, using indicator kriging and to determine various risk categories of contamination potentials based on estimated vulnerability indexes. Categories and ratings of six parameters in the probability-based DRASTIC model were probabilistically characterized according to the parameter classification methods of selecting a maximum estimation probability and calculating an expected value. Moreover, the probability-based estimation and assessment gave us an excellent insight into propagating the uncertainty of parameters due to limited observation data. To examine the prediction capacity of pollutants for the developed probability-based DRASTIC model, medium, high, and very high risk categories of contamination potentials were compared with observed nitrate-N exceeding 0.5 mg/L indicating the anthropogenic groundwater pollution. The analyzed results reveal that the developed probability-based DRASTIC model is capable of predicting high nitrate-N groundwater pollution and characterizing the parameter uncertainty via the probability estimation processes.

Computation of Incompressible Potential Flow over an Airfoil Using a High Order Aerodynamic Panel Method Based on Circular Arc Panels.

DTIC Science & Technology

1982-08-01

Vortex Sheet Figure 4 - Properties of Singularity Sheets they may be used to model different types of flow. Transfer of boundary... Vortex Sheet Equivalence Singularity Behavior Using Green’s theorem it is clear that the problem of potential flow over a body can be modeled using ...that source, doublet, or vortex singularities can be used to model potential flow problems, and that the doublet and vortex singularities are

Saddle point localization of molecular wavefunctions.

PubMed

Mellau, Georg Ch; Kyuberis, Alexandra A; Polyansky, Oleg L; Zobov, Nikolai; Field, Robert W

2016-09-15

The quantum mechanical description of isomerization is based on bound eigenstates of the molecular potential energy surface. For the near-minimum regions there is a textbook-based relationship between the potential and eigenenergies. Here we show how the saddle point region that connects the two minima is encoded in the eigenstates of the model quartic potential and in the energy levels of the [H, C, N] potential energy surface. We model the spacing of the eigenenergies with the energy dependent classical oscillation frequency decreasing to zero at the saddle point. The eigenstates with the smallest spacing are localized at the saddle point. The analysis of the HCN ↔ HNC isomerization states shows that the eigenstates with small energy spacing relative to the effective (v1, v3, ℓ) bending potentials are highly localized in the bending coordinate at the transition state. These spectroscopically detectable states represent a chemical marker of the transition state in the eigenenergy spectrum. The method developed here provides a basis for modeling characteristic patterns in the eigenenergy spectrum of bound states.

Perspectives on Non-Animal Alternatives for Assessing Sensitization Potential in Allergic Contact Dermatitis

PubMed Central

Sharma, Nripen S.; Jindal, Rohit; Mitra, Bhaskar; Lee, Serom; Li, Lulu; Maguire, Tim J.; Schloss, Rene; Yarmush, Martin L.

2014-01-01

Skin sensitization remains a major environmental and occupational health hazard. Animal models have been used as the gold standard method of choice for estimating chemical sensitization potential. However, a growing international drive and consensus for minimizing animal usage have prompted the development of in vitro methods to assess chemical sensitivity. In this paper, we examine existing approaches including in silico models, cell and tissue based assays for distinguishing between sensitizers and irritants. The in silico approaches that have been discussed include Quantitative Structure Activity Relationships (QSAR) and QSAR based expert models that correlate chemical molecular structure with biological activity and mechanism based read-across models that incorporate compound electrophilicity. The cell and tissue based assays rely on an assortment of mono and co-culture cell systems in conjunction with 3D skin models. Given the complexity of allergen induced immune responses, and the limited ability of existing systems to capture the entire gamut of cellular and molecular events associated with these responses, we also introduce a microfabricated platform that can capture all the key steps involved in allergic contact sensitivity. Finally, we describe the development of an integrated testing strategy comprised of two or three tier systems for evaluating sensitization potential of chemicals. PMID:24741377

Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

NASA Astrophysics Data System (ADS)

Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran

2014-09-01

Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.

Ascertaining Validity in the Abstract Realm of PMESII Simulation Models: An Analysis of the Peace Support Operations Model (PSOM)

DTIC Science & Technology

2009-06-01

simulation is the campaign-level Peace Support Operations Model (PSOM). This thesis provides a quantitative analysis of PSOM. The results are based ...multiple potential outcomes , further development and analysis is required before the model is used for large scale analysis . 15. NUMBER OF PAGES 159...multiple potential outcomes , further development and analysis is required before the model is used for large scale analysis . vi THIS PAGE

Predictive Structure-Based Toxicology Approaches To Assess the Androgenic Potential of Chemicals.

PubMed

Trisciuzzi, Daniela; Alberga, Domenico; Mansouri, Kamel; Judson, Richard; Novellino, Ettore; Mangiatordi, Giuseppe Felice; Nicolotti, Orazio

2017-11-27

We present a practical and easy-to-run in silico workflow exploiting a structure-based strategy making use of docking simulations to derive highly predictive classification models of the androgenic potential of chemicals. Models were trained on a high-quality chemical collection comprising 1689 curated compounds made available within the CoMPARA consortium from the US Environmental Protection Agency and were integrated with a two-step applicability domain whose implementation had the effect of improving both the confidence in prediction and statistics by reducing the number of false negatives. Among the nine androgen receptor X-ray solved structures, the crystal 2PNU (entry code from the Protein Data Bank) was associated with the best performing structure-based classification model. Three validation sets comprising each 2590 compounds extracted by the DUD-E collection were used to challenge model performance and the effectiveness of Applicability Domain implementation. Next, the 2PNU model was applied to screen and prioritize two collections of chemicals. The first is a small pool of 12 representative androgenic compounds that were accurately classified based on outstanding rationale at the molecular level. The second is a large external blind set of 55450 chemicals with potential for human exposure. We show how the use of molecular docking provides highly interpretable models and can represent a real-life option as an alternative nontesting method for predictive toxicology.

Place-Based Investment Model of Talent Development: A Proposed Model for Developing and Reinvesting Talents within the Community

ERIC Educational Resources Information Center

Paul, Kristina Ayers; Seward, Kristen K.

2016-01-01

The place-based investment model (PBIM) of talent development is a programming model for developing talents of high-potential youth in ways that could serve as an investment in the community. In this article, we discuss the PBIM within rural contexts. The model is grounded in three theories--Moon's personal talent development theory, Sternberg's…

Modeling of the Through-the-Thickness Electric Potentials of a Piezoelectric Bimorph Using the Spectral Element Method

PubMed Central

Dong, Xingjian; Peng, Zhike; Hua, Hongxing; Meng, Guang

2014-01-01

An efficient spectral element (SE) with electric potential degrees of freedom (DOF) is proposed to investigate the static electromechanical responses of a piezoelectric bimorph for its actuator and sensor functions. A sublayer model based on the piecewise linear approximation for the electric potential is used to describe the nonlinear distribution of electric potential through the thickness of the piezoelectric layers. An equivalent single layer (ESL) model based on first-order shear deformation theory (FSDT) is used to describe the displacement field. The Legendre orthogonal polynomials of order 5 are used in the element interpolation functions. The validity and the capability of the present SE model for investigation of global and local responses of the piezoelectric bimorph are confirmed by comparing the present solutions with those obtained from coupled 3-D finite element (FE) analysis. It is shown that, without introducing any higher-order electric potential assumptions, the current method can accurately describe the distribution of the electric potential across the thickness even for a rather thick bimorph. It is revealed that the effect of electric potential is significant when the bimorph is used as sensor while the effect is insignificant when the bimorph is used as actuator, and therefore, the present study may provide a better understanding of the nonlinear induced electric potential for bimorph sensor and actuator. PMID:24561399

In defense of compilation: A response to Davis' form and content in model-based reasoning

NASA Technical Reports Server (NTRS)

Keller, Richard

1990-01-01

In a recent paper entitled 'Form and Content in Model Based Reasoning', Randy Davis argues that model based reasoning research aimed at compiling task specific rules from underlying device models is mislabeled, misguided, and diversionary. Some of Davis' claims are examined and his basic conclusions are challenged about the value of compilation research to the model based reasoning community. In particular, Davis' claim is refuted that model based reasoning is exempt from the efficiency benefits provided by knowledge compilation techniques. In addition, several misconceptions are clarified about the role of representational form in compilation. It is concluded that techniques have the potential to make a substantial contribution to solving tractability problems in model based reasoning.

Logic-Based Models for the Analysis of Cell Signaling Networks†

PubMed Central

2010-01-01

Computational models are increasingly used to analyze the operation of complex biochemical networks, including those involved in cell signaling networks. Here we review recent advances in applying logic-based modeling to mammalian cell biology. Logic-based models represent biomolecular networks in a simple and intuitive manner without describing the detailed biochemistry of each interaction. A brief description of several logic-based modeling methods is followed by six case studies that demonstrate biological questions recently addressed using logic-based models and point to potential advances in model formalisms and training procedures that promise to enhance the utility of logic-based methods for studying the relationship between environmental inputs and phenotypic or signaling state outputs of complex signaling networks. PMID:20225868

Predicting the regeneration of Appalachian hardwoods: adapting the REGEN model for the Appalachian Plateau

Treesearch

Lance A. Vickers; Thomas R. Fox; David L. Loftis; David A. Boucugnani

2013-01-01

The difficulty of achieving reliable oak (Quercus spp.) regeneration is well documented. Application of silvicultural techniques to facilitate oak regeneration largely depends on current regeneration potential. A computer model to assess regeneration potential based on existing advanced reproduction in Appalachian hardwoods was developed by David...

A Qualitative Approach to Portfolios: The Early Assessment for Exceptional Potential Model.

ERIC Educational Resources Information Center

Shaklee, Beverly D.; Viechnicki, Karen J.

1995-01-01

The Early Assessment for Exceptional Potential portfolio assessment model assesses children as exceptional learners, users, generators, and pursuers of knowledge. It is based on use of authentic learning opportunities; interaction of assessment, curriculum, and instruction; multiple criteria derived from multiple sources; and systematic teacher…

Surface potential based modeling of charge, current, and capacitances in DGTFET including mobile channel charge and ambipolar behaviour

NASA Astrophysics Data System (ADS)

Jain, Prateek; Yadav, Chandan; Agarwal, Amit; Chauhan, Yogesh Singh

2017-08-01

We present a surface potential based analytical model for double gate tunnel field effect transistor (DGTFET) for the current, terminal charges, and terminal capacitances. The model accounts for the effect of the mobile charge in the channel and captures the device physics in depletion as well as in the strong inversion regime. The narrowing of the tunnel barrier in the presence of mobile charges in the channel is incorporated via modeling of the inverse decay length, which is constant under channel depletion condition and bias dependent under inversion condition. To capture the ambipolar current behavior in the model, tunneling at the drain junction is also included. The proposed model is validated against TCAD simulation data and it shows close match with the simulation data.

Numerical Predictions of Damage and Failure in Carbon Fiber Reinforced Laminates Using a Thermodynamically-Based Work Potential Theory

NASA Technical Reports Server (NTRS)

Pineda, Evan Jorge; Waas, Anthony M.

2013-01-01

A thermodynamically-based work potential theory for modeling progressive damage and failure in fiber-reinforced laminates is presented. The current, multiple-internal state variable (ISV) formulation, referred to as enhanced Schapery theory (EST), utilizes separate ISVs for modeling the effects of damage and failure. Consistent characteristic lengths are introduced into the formulation to govern the evolution of the failure ISVs. Using the stationarity of the total work potential with respect to each ISV, a set of thermodynamically consistent evolution equations for the ISVs are derived. The theory is implemented into a commercial finite element code. The model is verified against experimental results from two laminated, T800/3900-2 panels containing a central notch and different fiber-orientation stacking sequences. Global load versus displacement, global load versus local strain gage data, and macroscopic failure paths obtained from the models are compared against the experimental results.

A Toda lattice model of DNA

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

Christiansen, P.L.; Scott, A.C.; Muto, V.

In recent years the possibility that anharmonic excitations could play a role in the dynamics of SNA has been considered by several authors. It has been suggested that solitons may be generated thermally at biological temperatures. The denaturation of the DNA double helix has been investigated by statistical mechanics methods and by dynamical simulations. Here the potential for the hydrogen bond in each base pair is approximated by a Morse potential. In the present paper we describe the Toda lattice model of DNA. Temperature enters via the initial conditions and through a perturbation of the dynamical equations. The model ismore » refined by introduction of transversal motion of the Toda lattice and by transversal coupling of two lattices in the hydrogen bonds present in the base pairs. Using Lennard-Jones potentials to model these bonds we are able to obtain results concerning the open states of DNA at biological temperatures. 39 refs., 7 figs.« less

Potential of 3D City Models to assess flood vulnerability

NASA Astrophysics Data System (ADS)

Schröter, Kai; Bochow, Mathias; Schüttig, Martin; Nagel, Claus; Ross, Lutz; Kreibich, Heidi

2016-04-01

Vulnerability, as the product of exposure and susceptibility, is a key factor of the flood risk equation. Furthermore, the estimation of flood loss is very sensitive to the choice of the vulnerability model. Still, in contrast to elaborate hazard simulations, vulnerability is often considered in a simplified manner concerning the spatial resolution and geo-location of exposed objects as well as the susceptibility of these objects at risk. Usually, area specific potential flood loss is quantified on the level of aggregated land-use classes, and both hazard intensity and resistance characteristics of affected objects are represented in highly simplified terms. We investigate the potential of 3D City Models and spatial features derived from remote sensing data to improve the differentiation of vulnerability in flood risk assessment. 3D City Models are based on CityGML, an application scheme of the Geography Markup Language (GML), which represents the 3D geometry, 3D topology, semantics and appearance of objects on different levels of detail. As such, 3D City Models offer detailed spatial information which is useful to describe the exposure and to characterize the susceptibility of residential buildings at risk. This information is further consolidated with spatial features of the building stock derived from remote sensing data. Using this database a spatially detailed flood vulnerability model is developed by means of data-mining. Empirical flood damage data are used to derive and to validate flood susceptibility models for individual objects. We present first results from a prototype application in the city of Dresden, Germany. The vulnerability modeling based on 3D City Models and remote sensing data is compared i) to the generally accepted good engineering practice based on area specific loss potential and ii) to a highly detailed representation of flood vulnerability based on a building typology using urban structure types. Comparisons are drawn in terms of affected building area and estimated loss for a selection of inundation scenarios.

Forecasting the effects of land use scenarios on farmland birds reveal a potential mitigation of climate change impacts.

PubMed

Princé, Karine; Lorrillière, Romain; Barbet-Massin, Morgane; Léger, François; Jiguet, Frédéric

2015-01-01

Climate and land use changes are key drivers of current biodiversity trends, but interactions between these drivers are poorly modeled, even though they could amplify or mitigate negative impacts of climate change. Here, we attempt to predict the impacts of different agricultural change scenarios on common breeding birds within farmland included in the potential future climatic suitable areas for these species. We used the Special Report on Emissions Scenarios (SRES) to integrate likely changes in species climatic suitability, based on species distribution models, and changes in area of farmland, based on the IMAGE model, inside future climatic suitable areas. We also developed six farmland cover scenarios, based on expert opinion, which cover a wide spectrum of potential changes in livestock farming and cropping patterns by 2050. We ran generalized linear mixed models to calibrate the effects of farmland cover and climate change on bird specific abundance within 386 small agricultural regions. We used model outputs to predict potential changes in bird populations on the basis of predicted changes in regional farmland cover, in area of farmland and in species climatic suitability. We then examined the species sensitivity according to their habitat requirements. A scenario based on extensification of agricultural systems (i.e., low-intensity agriculture) showed the greatest potential to reduce reverse current declines in breeding birds. To meet ecological requirements of a larger number of species, agricultural policies accounting for regional disparities and landscape structure appear more efficient than global policies uniformly implemented at national scale. Interestingly, we also found evidence that farmland cover changes can mitigate the negative effect of climate change. Here, we confirm that there is a potential for countering negative effects of climate change by adaptive management of landscape. We argue that such studies will help inform sustainable agricultural policies for the future.

Antibacterial Activity of Imidazolium-Based Ionic Liquids Investigated by QSAR Modeling and Experimental Studies.

PubMed

Hodyna, Diana; Kovalishyn, Vasyl; Rogalsky, Sergiy; Blagodatnyi, Volodymyr; Petko, Kirill; Metelytsia, Larisa

2016-09-01

Predictive QSAR models for the inhibitors of B. subtilis and Ps. aeruginosa among imidazolium-based ionic liquids were developed using literary data. The regression QSAR models were created through Artificial Neural Network and k-nearest neighbor procedures. The classification QSAR models were constructed using WEKA-RF (random forest) method. The predictive ability of the models was tested by fivefold cross-validation; giving q(2) = 0.77-0.92 for regression models and accuracy 83-88% for classification models. Twenty synthesized samples of 1,3-dialkylimidazolium ionic liquids with predictive value of activity level of antimicrobial potential were evaluated. For all asymmetric 1,3-dialkylimidazolium ionic liquids, only compounds containing at least one radical with alkyl chain length of 12 carbon atoms showed high antibacterial activity. However, the activity of symmetric 1,3-dialkylimidazolium salts was found to have opposite relationship with the length of aliphatic radical being maximum for compounds based on 1,3-dioctylimidazolium cation. The obtained experimental results suggested that the application of classification QSAR models is more accurate for the prediction of activity of new imidazolium-based ILs as potential antibacterials. © 2016 John Wiley & Sons A/S.

Efficient Band-to-Trap Tunneling Model Including Heterojunction Band Offset

DOE PAGES

Gao, Xujiao; Huang, Andy; Kerr, Bert

2017-10-25

In this paper, we present an efficient band-to-trap tunneling model based on the Schenk approach, in which an analytic density-of-states (DOS) model is developed based on the open boundary scattering method. The new model explicitly includes the effect of heterojunction band offset, in addition to the well-known field effect. Its analytic form enables straightforward implementation into TCAD device simulators. It is applicable to all one-dimensional potentials, which can be approximated to a good degree such that the approximated potentials lead to piecewise analytic wave functions with open boundary conditions. The model allows for simulating both the electric-field-enhanced and band-offset-enhanced carriermore » recombination due to the band-to-trap tunneling near the heterojunction in a heterojunction bipolar transistor (HBT). Simulation results of an InGaP/GaAs/GaAs NPN HBT show that the proposed model predicts significantly increased base currents, due to the hole-to-trap tunneling enhanced by the emitter-base junction band offset. Finally, the results compare favorably with experimental observation.« less

Efficient Band-to-Trap Tunneling Model Including Heterojunction Band Offset

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

Gao, Xujiao; Huang, Andy; Kerr, Bert

In this paper, we present an efficient band-to-trap tunneling model based on the Schenk approach, in which an analytic density-of-states (DOS) model is developed based on the open boundary scattering method. The new model explicitly includes the effect of heterojunction band offset, in addition to the well-known field effect. Its analytic form enables straightforward implementation into TCAD device simulators. It is applicable to all one-dimensional potentials, which can be approximated to a good degree such that the approximated potentials lead to piecewise analytic wave functions with open boundary conditions. The model allows for simulating both the electric-field-enhanced and band-offset-enhanced carriermore » recombination due to the band-to-trap tunneling near the heterojunction in a heterojunction bipolar transistor (HBT). Simulation results of an InGaP/GaAs/GaAs NPN HBT show that the proposed model predicts significantly increased base currents, due to the hole-to-trap tunneling enhanced by the emitter-base junction band offset. Finally, the results compare favorably with experimental observation.« less

Hypoglycemia early alarm systems based on recursive autoregressive partial least squares models.

PubMed

Bayrak, Elif Seyma; Turksoy, Kamuran; Cinar, Ali; Quinn, Lauretta; Littlejohn, Elizabeth; Rollins, Derrick

2013-01-01

Hypoglycemia caused by intensive insulin therapy is a major challenge for artificial pancreas systems. Early detection and prevention of potential hypoglycemia are essential for the acceptance of fully automated artificial pancreas systems. Many of the proposed alarm systems are based on interpretation of recent values or trends in glucose values. In the present study, subject-specific linear models are introduced to capture glucose variations and predict future blood glucose concentrations. These models can be used in early alarm systems of potential hypoglycemia. A recursive autoregressive partial least squares (RARPLS) algorithm is used to model the continuous glucose monitoring sensor data and predict future glucose concentrations for use in hypoglycemia alarm systems. The partial least squares models constructed are updated recursively at each sampling step with a moving window. An early hypoglycemia alarm algorithm using these models is proposed and evaluated. Glucose prediction models based on real-time filtered data has a root mean squared error of 7.79 and a sum of squares of glucose prediction error of 7.35% for six-step-ahead (30 min) glucose predictions. The early alarm systems based on RARPLS shows good performance. A sensitivity of 86% and a false alarm rate of 0.42 false positive/day are obtained for the early alarm system based on six-step-ahead predicted glucose values with an average early detection time of 25.25 min. The RARPLS models developed provide satisfactory glucose prediction with relatively smaller error than other proposed algorithms and are good candidates to forecast and warn about potential hypoglycemia unless preventive action is taken far in advance. © 2012 Diabetes Technology Society.

Hypoglycemia Early Alarm Systems Based on Recursive Autoregressive Partial Least Squares Models

PubMed Central

Bayrak, Elif Seyma; Turksoy, Kamuran; Cinar, Ali; Quinn, Lauretta; Littlejohn, Elizabeth; Rollins, Derrick

2013-01-01

Background Hypoglycemia caused by intensive insulin therapy is a major challenge for artificial pancreas systems. Early detection and prevention of potential hypoglycemia are essential for the acceptance of fully automated artificial pancreas systems. Many of the proposed alarm systems are based on interpretation of recent values or trends in glucose values. In the present study, subject-specific linear models are introduced to capture glucose variations and predict future blood glucose concentrations. These models can be used in early alarm systems of potential hypoglycemia. Methods A recursive autoregressive partial least squares (RARPLS) algorithm is used to model the continuous glucose monitoring sensor data and predict future glucose concentrations for use in hypoglycemia alarm systems. The partial least squares models constructed are updated recursively at each sampling step with a moving window. An early hypoglycemia alarm algorithm using these models is proposed and evaluated. Results Glucose prediction models based on real-time filtered data has a root mean squared error of 7.79 and a sum of squares of glucose prediction error of 7.35% for six-step-ahead (30 min) glucose predictions. The early alarm systems based on RARPLS shows good performance. A sensitivity of 86% and a false alarm rate of 0.42 false positive/day are obtained for the early alarm system based on six-step-ahead predicted glucose values with an average early detection time of 25.25 min. Conclusions The RARPLS models developed provide satisfactory glucose prediction with relatively smaller error than other proposed algorithms and are good candidates to forecast and warn about potential hypoglycemia unless preventive action is taken far in advance. PMID:23439179

Finite element model for MOI applications using A-V formulation

NASA Astrophysics Data System (ADS)

Xuan, L.; Shanker, B.; Udpa, L.; Shih, W.; Fitzpatrick, G.

2001-04-01

Magneto-optic imaging (MOI) is a relatively new sensor application of an extension of bubble memory technology to NDT and produce easy-to-interpret, real time analog images. MOI systems use a magneto-optic (MO) sensor to produce analog images of magnetic flux leakage from surface and subsurface defects. The instrument's capability in detecting the relatively weak magnetic fields associated with subsurface defects depends on the sensitivity of the magneto-optic sensor. The availability of a theoretical model that can simulate the MOI system performance is extremely important for optimization of the MOI sensor and hardware system. A nodal finite element model based on magnetic vector potential formulation has been developed for simulating MOI phenomenon. This model has been used for predicting the magnetic fields in simple test geometry with corrosion dome defects. In the case of test samples with multiple discontinuities, a more robust model using the magnetic vector potential Ā and electrical scalar potential V is required. In this paper, a finite element model based on A-V formulation is developed to model complex circumferential crack under aluminum rivets in dimpled countersink.

A prognostic pollen emissions model for climate models (PECM1.0)

NASA Astrophysics Data System (ADS)

Wozniak, Matthew C.; Steiner, Allison L.

2017-11-01

We develop a prognostic model called Pollen Emissions for Climate Models (PECM) for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type, and meteorological parameters. Using modern surface pollen count data, empirical relationships between prior-year annual average temperature and pollen season start dates and end dates are developed for deciduous broadleaf trees (Acer, Alnus, Betula, Fraxinus, Morus, Platanus, Populus, Quercus, Ulmus), evergreen needleleaf trees (Cupressaceae, Pinaceae), grasses (Poaceae; C3, C4), and ragweed (Ambrosia). This regression model explains as much as 57 % of the variance in pollen phenological dates, and it is used to create a climate-flexible phenology that can be used to study the response of wind-driven pollen emissions to climate change. The emissions model is evaluated in the Regional Climate Model version 4 (RegCM4) over the continental United States by prescribing an emission potential from PECM and transporting pollen as aerosol tracers. We evaluate two different pollen emissions scenarios in the model using (1) a taxa-specific land cover database, phenology, and emission potential, and (2) a plant functional type (PFT) land cover, phenology, and emission potential. The simulated surface pollen concentrations for both simulations are evaluated against observed surface pollen counts in five climatic subregions. Given prescribed pollen emissions, the RegCM4 simulates observed concentrations within an order of magnitude, although the performance of the simulations in any subregion is strongly related to the land cover representation and the number of observation sites used to create the empirical phenological relationship. The taxa-based model provides a better representation of the phenology of tree-based pollen counts than the PFT-based model; however, we note that the PFT-based version provides a useful and climate-flexible emissions model for the general representation of the pollen phenology over the United States.

Finite-element time-domain algorithms for modeling linear Debye and Lorentz dielectric dispersions at low frequencies.

PubMed

Stoykov, Nikolay S; Kuiken, Todd A; Lowery, Madeleine M; Taflove, Allen

2003-09-01

We present what we believe to be the first algorithms that use a simple scalar-potential formulation to model linear Debye and Lorentz dielectric dispersions at low frequencies in the context of finite-element time-domain (FETD) numerical solutions of electric potential. The new algorithms, which permit treatment of multiple-pole dielectric relaxations, are based on the auxiliary differential equation method and are unconditionally stable. We validate the algorithms by comparison with the results of a previously reported method based on the Fourier transform. The new algorithms should be useful in calculating the transient response of biological materials subject to impulsive excitation. Potential applications include FETD modeling of electromyography, functional electrical stimulation, defibrillation, and effects of lightning and impulsive electric shock.

Model-based analyses: Promises, pitfalls, and example applications to the study of cognitive control

PubMed Central

Mars, Rogier B.; Shea, Nicholas J.; Kolling, Nils; Rushworth, Matthew F. S.

2011-01-01

We discuss a recent approach to investigating cognitive control, which has the potential to deal with some of the challenges inherent in this endeavour. In a model-based approach, the researcher defines a formal, computational model that performs the task at hand and whose performance matches that of a research participant. The internal variables in such a model might then be taken as proxies for latent variables computed in the brain. We discuss the potential advantages of such an approach for the study of the neural underpinnings of cognitive control and its pitfalls, and we make explicit the assumptions underlying the interpretation of data obtained using this approach. PMID:20437297

Tidal current energy potential of Nalón river estuary assessment using a high precision flow model

NASA Astrophysics Data System (ADS)

Badano, Nicolás; Valdés, Rodolfo Espina; Álvarez, Eduardo Álvarez

2018-05-01

Obtaining energy from tide currents in onshore locations is of great interest due to the proximity to the points of consumption. This opens the door to the feasibility of new installations based on hydrokinetic microturbines even in zones of moderate speed. In this context, the accuracy of energy predictions based on hydrodynamic models is of paramount importance. This research presents a high precision methodology based on a multidimensional hydrodynamic model that is used to study the energetic potential in estuaries. Moreover, it is able to estimate the flow variations caused by microturbine installations. The paper also shows the results obtained from the application of the methodology in a study of the Nalón river mouth (Asturias, Spain).

Geothermal Play-Fairway Analysis of the Tatun Volcano Group, Taiwan

NASA Astrophysics Data System (ADS)

Chen, Yan-Ru; Song, Sheng-Rong

2017-04-01

Geothermal energy is a sustainable and low-emission energy resource. It has the advantage of low-cost and withstanding nature hazards. Taiwan is located on the western Ring of Fire and characteristic of widespread hot spring and high surface heat flows, especially on the north of Taiwan. Many previous studies reveal that the Tatun Volcano Group (TVG) has great potential to develop the geothermal energy. However, investment in geothermal development has inherent risk and how to reduce the exploration risk is the most important. The exploration risk can be lowered by using the play-fairway analysis (PFA) that integrates existing data representing the composite risk segments in the region in order to define the exploration strategy. As a result, this study has adapted this logic for geothermal exploration in TVG. There are two necessary factors in geothermal energy, heat and permeability. They are the composite risk segments for geothermal play-fairway analysis. This study analyzes existing geologic, geophysical and geochemical data to construct the heat and permeability potential models. Heat potential model is based on temperature gradient, temperature of hot spring, proximity to hot spring, hydrothermal alteration zones, helium isotope ratios, and magnetics. Permeability potential model is based on fault zone, minor fault, and micro-earthquake activities. Then, these two potential models are weighted by using the Analytical Hierarchy Process (AHP) and combined to rank geothermal favorability. Uncertainty model is occurred by the quality of data and spatial accuracy of data. The goal is to combine the potential model with the uncertainty model as a risk map to find the best drilling site for geothermal exploration in TVG. Integrated results indicate where geothermal potential is the highest and provide the best information for those who want to develop the geothermal exploration in TVG.

Novel approach for computing photosynthetically active radiation for productivity modeling using remotely sensed images in the Great Plains, United States

USGS Publications Warehouse

Singh, Ramesh K.; Liu, Shu-Guang; Tieszen, Larry L.; Suyker, Andrew E.; Verma, Shashi B.

2012-01-01

Gross primary production (GPP) is a key indicator of ecosystem performance, and helps in many decision-making processes related to environment. We used the Eddy covariancelight use efficiency (EC-LUE) model for estimating GPP in the Great Plains, United States in order to evaluate the performance of this model. We developed a novel algorithm for computing the photosynthetically active radiation (PAR) based on net radiation. A strong correlation (R2=0.94,N=24) was found between daily PAR and Landsat-based mid-day instantaneous net radiation. Though the Moderate Resolution Spectroradiometer (MODIS) based instantaneous net radiation was in better agreement (R2=0.98,N=24) with the daily measured PAR, there was no statistical significant difference between Landsat based PAR and MODIS based PAR. The EC-LUE model validation also confirms the need to consider biological attributes (C3 versus C4 plants) for potential light use efficiency. A universal potential light use efficiency is unable to capture the spatial variation of GPP. It is necessary to use C3 versus C4 based land use/land cover map for using EC-LUE model for estimating spatiotemporal distribution of GPP.

Evaluation of Smoking Prevention Television Messages Based on the Elaboration Likelihood Model

ERIC Educational Resources Information Center

Flynn, Brian S.; Worden, John K.; Bunn, Janice Yanushka; Connolly, Scott W.; Dorwaldt, Anne L.

2011-01-01

Progress in reducing youth smoking may depend on developing improved methods to communicate with higher risk youth. This study explored the potential of smoking prevention messages based on the Elaboration Likelihood Model (ELM) to address these needs. Structured evaluations of 12 smoking prevention messages based on three strategies derived from…

Pred-Skin: A Fast and Reliable Web Application to Assess Skin Sensitization Effect of Chemicals.

PubMed

Braga, Rodolpho C; Alves, Vinicius M; Muratov, Eugene N; Strickland, Judy; Kleinstreuer, Nicole; Trospsha, Alexander; Andrade, Carolina Horta

2017-05-22

Chemically induced skin sensitization is a complex immunological disease with a profound impact on quality of life and working ability. Despite some progress in developing alternative methods for assessing the skin sensitization potential of chemical substances, there is no in vitro test that correlates well with human data. Computational QSAR models provide a rapid screening approach and contribute valuable information for the assessment of chemical toxicity. We describe the development of a freely accessible web-based and mobile application for the identification of potential skin sensitizers. The application is based on previously developed binary QSAR models of skin sensitization potential from human (109 compounds) and murine local lymph node assay (LLNA, 515 compounds) data with good external correct classification rate (0.70-0.81 and 0.72-0.84, respectively). We also included a multiclass skin sensitization potency model based on LLNA data (accuracy ranging between 0.73 and 0.76). When a user evaluates a compound in the web app, the outputs are (i) binary predictions of human and murine skin sensitization potential; (ii) multiclass prediction of murine skin sensitization; and (iii) probability maps illustrating the predicted contribution of chemical fragments. The app is the first tool available that incorporates quantitative structure-activity relationship (QSAR) models based on human data as well as multiclass models for LLNA. The Pred-Skin web app version 1.0 is freely available for the web, iOS, and Android (in development) at the LabMol web portal ( http://labmol.com.br/predskin/ ), in the Apple Store, and on Google Play, respectively. We will continuously update the app as new skin sensitization data and respective models become available.

Evaluating simplistic methods to understand current distributions and forecast distribution changes under climate change scenarios: An example with coypu (Myocastor coypus)

USGS Publications Warehouse

Jarnevich, Catherine S.; Young, Nicholas E; Sheffels, Trevor R.; Carter, Jacoby; Systma, Mark D.; Talbert, Colin

2017-01-01

Invasive species provide a unique opportunity to evaluate factors controlling biogeographic distributions; we can consider introduction success as an experiment testing suitability of environmental conditions. Predicting potential distributions of spreading species is not easy, and forecasting potential distributions with changing climate is even more difficult. Using the globally invasive coypu (Myocastor coypus [Molina, 1782]), we evaluate and compare the utility of a simplistic ecophysiological based model and a correlative model to predict current and future distribution. The ecophysiological model was based on winter temperature relationships with nutria survival. We developed correlative statistical models using the Software for Assisted Habitat Modeling and biologically relevant climate data with a global extent. We applied the ecophysiological based model to several global circulation model (GCM) predictions for mid-century. We used global coypu introduction data to evaluate these models and to explore a hypothesized physiological limitation, finding general agreement with known coypu distribution locally and globally and support for an upper thermal tolerance threshold. Global circulation model based model results showed variability in coypu predicted distribution among GCMs, but had general agreement of increasing suitable area in the USA. Our methods highlighted the dynamic nature of the edges of the coypu distribution due to climate non-equilibrium, and uncertainty associated with forecasting future distributions. Areas deemed suitable habitat, especially those on the edge of the current known range, could be used for early detection of the spread of coypu populations for management purposes. Combining approaches can be beneficial to predicting potential distributions of invasive species now and in the future and in exploring hypotheses of factors controlling distributions.

Community-based benchmarking of the CMIP DECK experiments

NASA Astrophysics Data System (ADS)

Gleckler, P. J.

2015-12-01

A diversity of community-based efforts are independently developing "diagnostic packages" with little or no coordination between them. A short list of examples include NCAR's Climate Variability Diagnostics Package (CVDP), ORNL's International Land Model Benchmarking (ILAMB), LBNL's Toolkit for Extreme Climate Analysis (TECA), PCMDI's Metrics Package (PMP), the EU EMBRACE ESMValTool, the WGNE MJO diagnostics package, and CFMIP diagnostics. The full value of these efforts cannot be realized without some coordination. As a first step, a WCRP effort has initiated a catalog to document candidate packages that could potentially be applied in a "repeat-use" fashion to all simulations contributed to the CMIP DECK (Diagnostic, Evaluation and Characterization of Klima) experiments. Some coordination of community-based diagnostics has the additional potential to improve how CMIP modeling groups analyze their simulations during model-development. The fact that most modeling groups now maintain a "CMIP compliant" data stream means that in principal without much effort they could readily adopt a set of well organized diagnostic capabilities specifically designed to operate on CMIP DECK experiments. Ultimately, a detailed listing of and access to analysis codes that are demonstrated to work "out of the box" with CMIP data could enable model developers (and others) to select those codes they wish to implement in-house, potentially enabling more systematic evaluation during the model development process.

Assessing rear-end crash potential in urban locations based on vehicle-by-vehicle interactions, geometric characteristics and operational conditions.

PubMed

Dimitriou, Loukas; Stylianou, Katerina; Abdel-Aty, Mohamed A

2018-03-01

Rear-end crashes are one of the most frequently occurring crash types, especially in urban networks. An understanding of the contributing factors and their significant association with rear-end crashes is of practical importance and will help in the development of effective countermeasures. The objective of this study is to assess rear-end crash potential at a microscopic level in an urban environment, by investigating vehicle-by-vehicle interactions. To do so, several traffic parameters at the individual vehicle level have been taken into consideration, for capturing car-following characteristics and vehicle interactions, and to investigate their effect on potential rear-end crashes. In this study rear-end crash potential was estimated based on stopping distance between two consecutive vehicles, and four rear-end crash potential cases were developed. The results indicated that 66.4% of the observations were estimated as rear-end crash potentials. It was also shown that rear-end crash potential was presented when traffic flow and speed standard deviation were higher. Also, locational characteristics such as lane of travel and location in the network were found to affect drivers' car following decisions and additionally, it was shown that speeds were lower and headways higher when Heavy Goods Vehicles lead. Finally, a model-based behavioral analysis based on Multinomial Logit regression was conducted to systematically identify the statistically significant variables in explaining rear-end risk potential. The modeling results highlighted the significance of the explanatory variables associated with rear-end crash potential, however it was shown that their effect varied among different model configurations. The outcome of the results can be of significant value for several purposes, such as real-time monitoring of risk potential, allocating enforcement units in urban networks and designing targeted proactive safety policies. Copyright © 2018 Elsevier Ltd. All rights reserved.

Modeling spatial patterns of wildfire susceptibility in southern California: Applications of MODIS remote sensing data and mesoscale numerical weather models

NASA Astrophysics Data System (ADS)

Schneider, Philipp

This dissertation investigates the potential of Moderate Resolution Imaging Spectroradiometer (MODIS) imagery and mesoscale numerical weather models for mapping wildfire susceptibility in general and for improving the Fire Potential Index (FPI) in southern California in particular. The dissertation explores the use of the Visible Atmospherically Resistant Index (VARI) from MODIS data for mapping relative greenness (RG) of vegetation and subsequently for computing the FPI. VARI-based RG was validated against in situ observations of live fuel moisture. The results indicate that VARI is superior to the previously used Normalized Difference Vegetation Index (NDVI) for computing RG. FPI computed using VARI-based RG was found to outperform the traditional FPI when validated against historical fire detections using logistic regression. The study further investigates the potential of using Multiple Endmember Spectral Mixture Analysis (MESMA) on MODIS data for estimating live and dead fractions of vegetation. MESMA fractions were compared against in situ measurements and fractions derived from data of a high-resolution, hyperspectral sensor. The results show that live and dead fractions obtained from MODIS using MESMA are well correlated with the reference data. Further, FPI computed using MESMA-based green vegetation fraction in lieu of RG was validated against historical fire occurrence data. MESMA-based FPI performs at a comparable level to the traditional NDVI-based FPI, but can do so using a single MODIS image rather than an extensive remote sensing time series as required for the RG approach. Finally this dissertation explores the potential of integrating gridded wind speed data obtained from the MM5 mesoscale numerical weather model in the FPI. A new fire susceptibility index, the Wind-Adjusted Fire Potential Index (WAFPI), was introduced. It modifies the FPI algorithm by integrating normalized wind speed. Validating WAFPI against historical wildfire events using logistic regression indicates that gridded data sets of wind speed are a valuable addition to the FPI as they can significantly increase the probability range of the fitted model and can further increase the model's discriminatory power over that of the traditional FPI.

Improving Learning for All Students through Equity-Based Inclusive Reform Practices: Effectiveness of a Fully Integrated Schoolwide Model on Student Reading and Math Achievement

ERIC Educational Resources Information Center

Choi, Jeong Hoon; Meisenheimer, Jessica M.; McCart, Amy B.; Sailor, Wayne

2017-01-01

The present investigation examines the schoolwide applications model (SAM) as a potentially effective school reform model for increasing equity-based inclusive education practices while enhancing student reading and math achievement for all students. A 3-year quasi-experimental comparison group analysis using latent growth modeling (LGM) was used…

Virtual Transgenics: Using a Molecular Biology Simulation to Impact Student Academic Achievement and Attitudes

ERIC Educational Resources Information Center

Shegog, Ross; Lazarus, Melanie M.; Murray, Nancy G.; Diamond, Pamela M.; Sessions, Nathalie; Zsigmond, Eva

2012-01-01

The transgenic mouse model is useful for studying the causes and potential cures for human genetic diseases. Exposing high school biology students to laboratory experience in developing transgenic animal models is logistically prohibitive. Computer-based simulation, however, offers this potential in addition to advantages of fidelity and reach.…

Whole Protein Native Fitness Potentials

NASA Astrophysics Data System (ADS)

Faraggi, Eshel; Kloczkowski, Andrzej

2013-03-01

Protein structure prediction can be separated into two tasks: sample the configuration space of the protein chain, and assign a fitness between these hypothetical models and the native structure of the protein. One of the more promising developments in this area is that of knowledge based energy functions. However, standard approaches using pair-wise interactions have shown shortcomings demonstrated by the superiority of multi-body-potentials. These shortcomings are due to residue pair-wise interaction being dependent on other residues along the chain. We developed a method that uses whole protein information filtered through machine learners to score protein models based on their likeness to native structures. For all models we calculated parameters associated with the distance to the solvent and with distances between residues. These parameters, in addition to energy estimates obtained by using a four-body-potential, DFIRE, and RWPlus were used as training for machine learners to predict the fitness of the models. Testing on CASP 9 targets showed that our method is superior to DFIRE, RWPlus, and the four-body potential, which are considered standards in the field.

An accurate potential model for the a3Σu+ state of the alkali dimers Na2, K2, Rb2, and Cs2

NASA Astrophysics Data System (ADS)

Lau, Jascha A.; Toennies, J. Peter; Tang, K. T.

2016-11-01

A modified semi-empirical Tang-Toennies potential model is used to describe the a3Σu+ potentials of the alkali dimers. These potentials are currently of interest in connection with the laser manipulation of the ultracold alkali gases. The fully analytical model is based on three experimental parameters, the well depth De, well location Re, and the harmonic vibrational frequency ωe of which the latter is only slightly optimized within the range of the literature values. Comparison with the latest spectroscopic data shows good agreement for Na2, K2, Rb2, and Cs2, comparable to that found with published potential models with up to 55 parameters. The differences between the reduced potential of Li2 and the conformal reduced potentials of the heavier dimers are analyzed together with why the model describes Li2 less accurately. The new model potential provides a test of the principle of corresponding states and an excellent first order approximation for further optimization to improve the fits to the spectroscopic data and describe the scattering lengths and Feshbach resonances at ultra-low temperatures.

Predicted phototoxicities of carbon nano-material by quantum mechanical calculations

EPA Science Inventory

The purpose of this research is to develop a predictive model for the phototoxicity potential of carbon nanomaterials (fullerenols and single-walled carbon nanotubes). This model is based on the quantum mechanical (ab initio) calculations on these carbon-based materials and compa...

Copula-based nonlinear modeling of the law of one price for lumber products

Treesearch

Barry K. Goodwin; Matthew T. Holt; Gülcan Önel; Jeffrey P. Prestemon

2018-01-01

This paper proposes an alternative and potentially novel approach to analyzing the law of one price in a nonlinear fashion. Copula-based models that consider the joint distribution of prices separated by space are developed and applied to weekly...

Fuzzy logic-based assessment for mapping potential infiltration areas in low-gradient watersheds.

PubMed

Quiroz Londoño, Orlando Mauricio; Romanelli, Asunción; Lima, María Lourdes; Massone, Héctor Enrique; Martínez, Daniel Emilio

2016-07-01

This paper gives an account of the design a logic-based approach for identifying potential infiltration areas in low-gradient watersheds based on remote sensing data. This methodological framework is applied in a sector of the Pampa Plain, Argentina, which has high level of agricultural activities and large demands for groundwater supplies. Potential infiltration sites are assessed as a function of two primary topics: hydrologic and soil conditions. This model shows the state of each evaluated subwatershed respecting to its potential contribution to infiltration mainly based on easily measurable and commonly used parameters: drainage density, geomorphologic units, soil media, land-cover, slope and aspect (slope orientation). Mapped outputs from the logic model displayed 42% very low-low, 16% moderate, 41% high-very high contribution to potential infiltration in the whole watershed. Subwatersheds in the upper and lower section were identified as areas with high to very high potential infiltration according to the following media features: low drainage density (<1.5 km/km(2)), arable land and pastures as the main land-cover categories, sandy clay loam to loam - clay loam soils and with the geomorphological units named poorly drained plain, channelized drainage plain and, dunes and beaches. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modelling strategies to predict the multi-scale effects of rural land management change

NASA Astrophysics Data System (ADS)

Bulygina, N.; Ballard, C. E.; Jackson, B. M.; McIntyre, N.; Marshall, M.; Reynolds, B.; Wheater, H. S.

2011-12-01

Changes to the rural landscape due to agricultural land management are ubiquitous, yet predicting the multi-scale effects of land management change on hydrological response remains an important scientific challenge. Much empirical research has been of little generic value due to inadequate design and funding of monitoring programmes, while the modelling issues challenge the capability of data-based, conceptual and physics-based modelling approaches. In this paper we report on a major UK research programme, motivated by a national need to quantify effects of agricultural intensification on flood risk. Working with a consortium of farmers in upland Wales, a multi-scale experimental programme (from experimental plots to 2nd order catchments) was developed to address issues of upland agricultural intensification. This provided data support for a multi-scale modelling programme, in which highly detailed physics-based models were conditioned on the experimental data and used to explore effects of potential field-scale interventions. A meta-modelling strategy was developed to represent detailed modelling in a computationally-efficient manner for catchment-scale simulation; this allowed catchment-scale quantification of potential management options. For more general application to data-sparse areas, alternative approaches were needed. Physics-based models were developed for a range of upland management problems, including the restoration of drained peatlands, afforestation, and changing grazing practices. Their performance was explored using literature and surrogate data; although subject to high levels of uncertainty, important insights were obtained, of practical relevance to management decisions. In parallel, regionalised conceptual modelling was used to explore the potential of indices of catchment response, conditioned on readily-available catchment characteristics, to represent ungauged catchments subject to land management change. Although based in part on speculative relationships, significant predictive power was derived from this approach. Finally, using a formal Bayesian procedure, these different sources of information were combined with local flow data in a catchment-scale conceptual model application , i.e. using small-scale physical properties, regionalised signatures of flow and available flow measurements.

Construction of dynamic stochastic simulation models using knowledge-based techniques

NASA Technical Reports Server (NTRS)

Williams, M. Douglas; Shiva, Sajjan G.

1990-01-01

Over the past three decades, computer-based simulation models have proven themselves to be cost-effective alternatives to the more structured deterministic methods of systems analysis. During this time, many techniques, tools and languages for constructing computer-based simulation models have been developed. More recently, advances in knowledge-based system technology have led many researchers to note the similarities between knowledge-based programming and simulation technologies and to investigate the potential application of knowledge-based programming techniques to simulation modeling. The integration of conventional simulation techniques with knowledge-based programming techniques is discussed to provide a development environment for constructing knowledge-based simulation models. A comparison of the techniques used in the construction of dynamic stochastic simulation models and those used in the construction of knowledge-based systems provides the requirements for the environment. This leads to the design and implementation of a knowledge-based simulation development environment. These techniques were used in the construction of several knowledge-based simulation models including the Advanced Launch System Model (ALSYM).

Respiratory nanoparticle-based vaccines and challenges associated with animal models and translation.

PubMed

Renukaradhya, Gourapura J; Narasimhan, Balaji; Mallapragada, Surya K

2015-12-10

Vaccine development has had a huge impact on human health. However, there is a significant need to develop efficacious vaccines for several existing as well as emerging respiratory infectious diseases. Several challenges need to be overcome to develop efficacious vaccines with translational potential. This review focuses on two aspects to overcome some barriers - 1) the development of nanoparticle-based vaccines, and 2) the choice of suitable animal models for respiratory infectious diseases that will allow for translation. Nanoparticle-based vaccines, including subunit vaccines involving synthetic and/or natural polymeric adjuvants and carriers, as well as those based on virus-like particles offer several key advantages to help overcome the barriers to effective vaccine development. These include the ability to deliver combinations of antigens, target the vaccine formulation to specific immune cells, enable cross-protection against divergent strains, act as adjuvants or immunomodulators, allow for sustained release of antigen, enable single dose delivery, and potentially obviate the cold chain. While mouse models have provided several important insights into the mechanisms of infectious diseases, they are often a limiting step in translation of new vaccines to the clinic. An overview of different animal models involved in vaccine research for respiratory infections, with advantages and disadvantages of each model, is discussed. Taken together, advances in nanotechnology, combined with the right animal models for evaluating vaccine efficacy, has the potential to revolutionize vaccine development for respiratory infections. Copyright © 2015 Elsevier B.V. All rights reserved.

New Theoretical Model of Nerve Conduction in Unmyelinated Nerves

PubMed Central

Akaishi, Tetsuya

2017-01-01

Nerve conduction in unmyelinated fibers has long been described based on the equivalent circuit model and cable theory. However, without the change in ionic concentration gradient across the membrane, there would be no generation or propagation of the action potential. Based on this concept, we employ a new conductive model focusing on the distribution of voltage-gated sodium ion channels and Coulomb force between electrolytes. Based on this new model, the propagation of the nerve conduction was suggested to take place far before the generation of action potential at each channel. We theoretically showed that propagation of action potential, which is enabled by the increasing Coulomb force produced by inflowing sodium ions, from one sodium ion channel to the next sodium channel would be inversely proportionate to the density of sodium channels on the axon membrane. Because the longitudinal number of sodium ion channel would be proportionate to the square root of channel density, the conduction velocity of unmyelinated nerves is theoretically shown to be proportionate to the square root of channel density. Also, from a viewpoint of equilibrium state of channel importation and degeneration, channel density was suggested to be proportionate to axonal diameter. Based on these simple basis, conduction velocity in unmyelinated nerves was theoretically shown to be proportionate to the square root of axonal diameter. This new model would also enable us to acquire more accurate and understandable vision on the phenomena in unmyelinated nerves in addition to the conventional electric circuit model and cable theory. PMID:29081751

Satellite-derived potential evapotranspiration for distributed hydrologic runoff modeling

NASA Astrophysics Data System (ADS)

Spies, R. R.; Franz, K. J.; Bowman, A.; Hogue, T. S.; Kim, J.

2012-12-01

Distributed models have the ability of incorporating spatially variable data, especially high resolution forcing inputs such as precipitation, temperature and evapotranspiration in hydrologic modeling. Use of distributed hydrologic models for operational streamflow prediction has been partially hindered by a lack of readily available, spatially explicit input observations. Potential evapotranspiration (PET), for example, is currently accounted for through PET input grids that are based on monthly climatological values. The goal of this study is to assess the use of satellite-based PET estimates that represent the temporal and spatial variability, as input to the National Weather Service (NWS) Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM). Daily PET grids are generated for six watersheds in the upper Mississippi River basin using a method that applies only MODIS satellite-based observations and the Priestly Taylor formula (MODIS-PET). The use of MODIS-PET grids will be tested against the use of the current climatological PET grids for simulating basin discharge. Gridded surface temperature forcing data are derived by applying the inverse distance weighting spatial prediction method to point-based station observations from the Automated Surface Observing System (ASOS) and Automated Weather Observing System (AWOS). Precipitation data are obtained from the Climate Prediction Center's (CPC) Climatology-Calibrated Precipitation Analysis (CCPA). A-priori gridded parameters for the Sacramento Soil Moisture Accounting Model (SAC-SMA), Snow-17 model, and routing model are initially obtained from the Office of Hydrologic Development and further calibrated using an automated approach. The potential of the MODIS-PET to be used in an operational distributed modeling system will be assessed with the long-term goal of promoting research to operations transfers and advancing the science of hydrologic forecasting.

Modelling and simulation of complex sociotechnical systems: envisioning and analysing work environments

PubMed Central

Hettinger, Lawrence J.; Kirlik, Alex; Goh, Yang Miang; Buckle, Peter

2015-01-01

Accurate comprehension and analysis of complex sociotechnical systems is a daunting task. Empirically examining, or simply envisioning the structure and behaviour of such systems challenges traditional analytic and experimental approaches as well as our everyday cognitive capabilities. Computer-based models and simulations afford potentially useful means of accomplishing sociotechnical system design and analysis objectives. From a design perspective, they can provide a basis for a common mental model among stakeholders, thereby facilitating accurate comprehension of factors impacting system performance and potential effects of system modifications. From a research perspective, models and simulations afford the means to study aspects of sociotechnical system design and operation, including the potential impact of modifications to structural and dynamic system properties, in ways not feasible with traditional experimental approaches. This paper describes issues involved in the design and use of such models and simulations and describes a proposed path forward to their development and implementation. Practitioner Summary: The size and complexity of real-world sociotechnical systems can present significant barriers to their design, comprehension and empirical analysis. This article describes the potential advantages of computer-based models and simulations for understanding factors that impact sociotechnical system design and operation, particularly with respect to process and occupational safety. PMID:25761227

Temporal validation for landsat-based volume estimation model

Treesearch

Renaldo J. Arroyo; Emily B. Schultz; Thomas G. Matney; David L. Evans; Zhaofei Fan

2015-01-01

Satellite imagery can potentially reduce the costs and time associated with ground-based forest inventories; however, for satellite imagery to provide reliable forest inventory data, it must produce consistent results from one time period to the next. The objective of this study was to temporally validate a Landsat-based volume estimation model in a four county study...

LEAKAGE CHARACTERISTICS OF BASE OF RIVERBANK BY SELF POTENTIAL METHOD AND EXAMINATION OF EFFECTIVENESS OF SELF POTENTIAL METHOD TO HEALTH MONITORING OF BASE OF RIVERBANK

NASA Astrophysics Data System (ADS)

Matsumoto, Kensaku; Okada, Takashi; Takeuchi, Atsuo; Yazawa, Masato; Uchibori, Sumio; Shimizu, Yoshihiko

Field Measurement of Self Potential Method using Copper Sulfate Electrode was performed in base of riverbank in WATARASE River, where has leakage problem to examine leakage characteristics. Measurement results showed typical S-shape what indicates existence of flow groundwater. The results agreed with measurement results by Ministry of Land, Infrastructure and Transport with good accuracy. Results of 1m depth ground temperature detection and Chain-Array detection showed good agreement with results of the Self Potential Method. Correlation between Self Potential value and groundwater velocity was examined model experiment. The result showed apparent correlation. These results indicate that the Self Potential Method was effective method to examine the characteristics of ground water of base of riverbank in leakage problem.

Efficient generation of mouse models of human diseases via ABE- and BE-mediated base editing.

PubMed

Liu, Zhen; Lu, Zongyang; Yang, Guang; Huang, Shisheng; Li, Guanglei; Feng, Songjie; Liu, Yajing; Li, Jianan; Yu, Wenxia; Zhang, Yu; Chen, Jia; Sun, Qiang; Huang, Xingxu

2018-06-14

A recently developed adenine base editor (ABE) efficiently converts A to G and is potentially useful for clinical applications. However, its precision and efficiency in vivo remains to be addressed. Here we achieve A-to-G conversion in vivo at frequencies up to 100% by microinjection of ABE mRNA together with sgRNAs. We then generate mouse models harboring clinically relevant mutations at Ar and Hoxd13, which recapitulates respective clinical defects. Furthermore, we achieve both C-to-T and A-to-G base editing by using a combination of ABE and SaBE3, thus creating mouse model harboring multiple mutations. We also demonstrate the specificity of ABE by deep sequencing and whole-genome sequencing (WGS). Taken together, ABE is highly efficient and precise in vivo, making it feasible to model and potentially cure relevant genetic diseases.

Spatial modelling of landscape aesthetic potential in urban-rural fringes.

PubMed

Sahraoui, Yohan; Clauzel, Céline; Foltête, Jean-Christophe

2016-10-01

The aesthetic potential of landscape has to be modelled to provide tools for land-use planning. This involves identifying landscape attributes and revealing individuals' landscape preferences. Landscape aesthetic judgments of individuals (n = 1420) were studied by means of a photo-based survey. A set of landscape visibility metrics was created to measure landscape composition and configuration in each photograph using spatial data. These metrics were used as explanatory variables in multiple linear regressions to explain aesthetic judgments. We demonstrate that landscape aesthetic judgments may be synthesized in three consensus groups. The statistical results obtained show that landscape visibility metrics have good explanatory power. Ultimately, we propose a spatial modelling of landscape aesthetic potential based on these results combined with systematic computation of visibility metrics. Copyright © 2016 Elsevier Ltd. All rights reserved.

Equivalent magnetic vector potential model for low-frequency magnetic exposure assessment

NASA Astrophysics Data System (ADS)

Diao, Y. L.; Sun, W. N.; He, Y. Q.; Leung, S. W.; Siu, Y. M.

2017-10-01

In this paper, a novel source model based on a magnetic vector potential for the assessment of induced electric field strength in a human body exposed to the low-frequency (LF) magnetic field of an electrical appliance is presented. The construction of the vector potential model requires only a single-component magnetic field to be measured close to the appliance under test, hence relieving considerable practical measurement effort—the radial basis functions (RBFs) are adopted for the interpolation of discrete measurements; the magnetic vector potential model can then be directly constructed by summing a set of simple algebraic functions of RBF parameters. The vector potentials are then incorporated into numerical calculations as the equivalent source for evaluations of the induced electric field in the human body model. The accuracy and effectiveness of the proposed model are demonstrated by comparing the induced electric field in a human model to that of the full-wave simulation. This study presents a simple and effective approach for modelling the LF magnetic source. The result of this study could simplify the compliance test procedure for assessing an electrical appliance regarding LF magnetic exposure.

Equivalent magnetic vector potential model for low-frequency magnetic exposure assessment.

PubMed

Diao, Y L; Sun, W N; He, Y Q; Leung, S W; Siu, Y M

2017-09-21

In this paper, a novel source model based on a magnetic vector potential for the assessment of induced electric field strength in a human body exposed to the low-frequency (LF) magnetic field of an electrical appliance is presented. The construction of the vector potential model requires only a single-component magnetic field to be measured close to the appliance under test, hence relieving considerable practical measurement effort-the radial basis functions (RBFs) are adopted for the interpolation of discrete measurements; the magnetic vector potential model can then be directly constructed by summing a set of simple algebraic functions of RBF parameters. The vector potentials are then incorporated into numerical calculations as the equivalent source for evaluations of the induced electric field in the human body model. The accuracy and effectiveness of the proposed model are demonstrated by comparing the induced electric field in a human model to that of the full-wave simulation. This study presents a simple and effective approach for modelling the LF magnetic source. The result of this study could simplify the compliance test procedure for assessing an electrical appliance regarding LF magnetic exposure.

Constructing high-accuracy intermolecular potential energy surface with multi-dimension Morse/Long-Range model

NASA Astrophysics Data System (ADS)

Zhai, Yu; Li, Hui; Le Roy, Robert J.

2018-04-01

Spectroscopically accurate Potential Energy Surfaces (PESs) are fundamental for explaining and making predictions of the infrared and microwave spectra of van der Waals (vdW) complexes, and the model used for the potential energy function is critically important for providing accurate, robust and portable analytical PESs. The Morse/Long-Range (MLR) model has proved to be one of the most general, flexible and accurate one-dimensional (1D) model potentials, as it has physically meaningful parameters, is flexible, smooth and differentiable everywhere, to all orders and extrapolates sensibly at both long and short ranges. The Multi-Dimensional Morse/Long-Range (mdMLR) potential energy model described herein is based on that 1D MLR model, and has proved to be effective and accurate in the potentiology of various types of vdW complexes. In this paper, we review the current status of development of the mdMLR model and its application to vdW complexes. The future of the mdMLR model is also discussed. This review can serve as a tutorial for the construction of an mdMLR PES.

Structured prediction models for RNN based sequence labeling in clinical text.

PubMed

Jagannatha, Abhyuday N; Yu, Hong

2016-11-01

Sequence labeling is a widely used method for named entity recognition and information extraction from unstructured natural language data. In clinical domain one major application of sequence labeling involves extraction of medical entities such as medication, indication, and side-effects from Electronic Health Record narratives. Sequence labeling in this domain, presents its own set of challenges and objectives. In this work we experimented with various CRF based structured learning models with Recurrent Neural Networks. We extend the previously studied LSTM-CRF models with explicit modeling of pairwise potentials. We also propose an approximate version of skip-chain CRF inference with RNN potentials. We use these methodologies for structured prediction in order to improve the exact phrase detection of various medical entities.

Structured prediction models for RNN based sequence labeling in clinical text

PubMed Central

Jagannatha, Abhyuday N; Yu, Hong

2016-01-01

Sequence labeling is a widely used method for named entity recognition and information extraction from unstructured natural language data. In clinical domain one major application of sequence labeling involves extraction of medical entities such as medication, indication, and side-effects from Electronic Health Record narratives. Sequence labeling in this domain, presents its own set of challenges and objectives. In this work we experimented with various CRF based structured learning models with Recurrent Neural Networks. We extend the previously studied LSTM-CRF models with explicit modeling of pairwise potentials. We also propose an approximate version of skip-chain CRF inference with RNN potentials. We use these methodologies1 for structured prediction in order to improve the exact phrase detection of various medical entities. PMID:28004040

Using Avatars to Model Weight Loss Behaviors: Participant Attitudes and Technology Development

PubMed Central

Napolitano, Melissa A.; Hayes, Sharon; Russo, Giuseppe; Muresu, Debora; Giordano, Antonio; Foster, Gary D.

2013-01-01

Background: Virtual reality and other avatar-based technologies are potential methods for demonstrating and modeling weight loss behaviors. This study examined avatar-based technology as a tool for modeling weight loss behaviors. Methods: This study consisted of two phases: (1) an online survey to obtain feedback about using avatars for modeling weight loss behaviors and (2) technology development and usability testing to create an avatar-based technology program for modeling weight loss behaviors. Results: Results of phase 1 (n = 128) revealed that interest was high, with 88.3% stating that they would participate in a program that used an avatar to help practice weight loss skills in a virtual environment. In phase 2, avatars and modules to model weight loss skills were developed. Eight women were recruited to participate in a 4-week usability test, with 100% reporting they would recommend the program and that it influenced their diet/exercise behavior. Most women (87.5%) indicated that the virtual models were helpful. After 4 weeks, average weight loss was 1.6 kg (standard deviation = 1.7). Conclusion: This investigation revealed a high level of interest in an avatar-based program, with formative work indicating promise. Given the high costs associated with in vivo exposure and practice, this study demonstrates the potential use of avatar-based technology as a tool for modeling weight loss behaviors. PMID:23911189

Human Pluripotent Stem Cell-Based Assay Predicts Developmental Toxicity Potential of ToxCast Chemicals (ACT meeting)

EPA Science Inventory

Worldwide initiatives to screen for toxicity potential among the thousands of chemicals currently in use require inexpensive and high-throughput in vitro models to meet their goals. The devTOX quickPredict platform is an in vitro human pluripotent stem cell-based assay used to as...

Charged Particle Detection: Potential of Love Wave Acoustic Devices

NASA Astrophysics Data System (ADS)

Pedrick, Michael; Tittmann, Bernhard

2006-03-01

An investigation of the dependence of film density on group and phase velocities in a Love Wave Device shows potential for acoustic-based charged particle detection (CPD). Exposure of an ion sensitive photoresist to charged particles causes localized changes in density through either scission or cross-linking. A theoretical model was developed to study ion fluence effects on Love Wave sensitivity based on: ion energy, effective density changes, layer thickness and mode selection. The model is based on a Poly(Methyl Methacralate) (PMMA) film deposited on a Quartz substrate. The effect of Helium ion fluence on the properties of PMMA has previously been studied. These guidelines were used as an initial basis for the prediction of helium ion detection in a PMMA layer. Procedures for experimental characterization of ion effects on the material properties of PMMA are reviewed. Techniques for experimental validation of the predicted velocity shifts are discussed. A Love Wave Device for CPD could potentially provide a cost-effective alternative to semiconductor or photo-based counterparts. The potential for monitoring ion implantation effects on material properties is also discussed.

Transport properties and efficiency of elastically coupled particles in asymmetric periodic potentials

NASA Astrophysics Data System (ADS)

Igarashi, Akito; Tsukamoto, Shinji

2000-02-01

Biological molecular motors drive unidirectional transport and transduce chemical energy to mechanical work. In order to identify this energy conversion which is a common feature of molecular motors, many workers have studied various physical models, which consist of Brownian particles in spatially periodic potentials. Most of the models are, however, based on "single-particle" dynamics and too simple as models for biological motors, especially for actin-myosin motors, which cause muscle contraction. In this paper, particles coupled by elastic strings in an asymmetric periodic potential are considered as a model for the motors. We investigate the dynamics of the model and calculate the efficiency of energy conversion with the use of molecular dynamical method. In particular, we find that the velocity and efficiency of the elastically coupled particles where the natural length of the springs is incommensurable with the period of the periodic potential are larger than those of the corresponding single particle model.

Alternans promotion in cardiac electrophysiology models by delay differential equations.

PubMed

Gomes, Johnny M; Dos Santos, Rodrigo Weber; Cherry, Elizabeth M

2017-09-01

Cardiac electrical alternans is a state of alternation between long and short action potentials and is frequently associated with harmful cardiac conditions. Different dynamic mechanisms can give rise to alternans; however, many cardiac models based on ordinary differential equations are not able to reproduce this phenomenon. A previous study showed that alternans can be induced by the introduction of delay differential equations (DDEs) in the formulations of the ion channel gating variables of a canine myocyte model. The present work demonstrates that this technique is not model-specific by successfully promoting alternans using DDEs for five cardiac electrophysiology models that describe different types of myocytes, with varying degrees of complexity. By analyzing results across the different models, we observe two potential requirements for alternans promotion via DDEs for ionic gates: (i) the gate must have a significant influence on the action potential duration and (ii) a delay must significantly impair the gate's recovery between consecutive action potentials.

Towards a feminist empowerment model of forgiveness psychotherapy.

PubMed

McKay, Kevin M; Hill, Melanie S; Freedman, Suzanne R; Enright, Robert D

2007-03-01

In recent years Enright and Fitzgibbon's (2000) process model of forgiveness therapy has received substantial theoretical and empirical attention. However, both the process model of forgiveness therapy and the social-cognitive developmental model on which it is based have received criticism from feminist theorists. The current paper considers feminist criticisms of forgiveness therapy and uses a feminist lens to identify potential areas for growth. Specifically, Worell and Remer's (2003) model of synthesizing feminist ideals into existing theory was consulted, areas of bias within the forgiveness model of psychotherapy were identified, and strategies for restructuring areas of potential bias were introduced. Further, the authors consider unique aspects of forgiveness therapy that can potentially strengthen existing models of feminist therapy. (PsycINFO Database Record (c) 2010 APA, all rights reserved).

SHEDS-HT: An Integrated Probabilistic Exposure Model for Prioritizing Exposures to Chemicals with Near-Field and Dietary Sources

EPA Science Inventory

United States Environmental Protection Agency (USEPA) researchers are developing a strategy for highthroughput (HT) exposure-based prioritization of chemicals under the ExpoCast program. These novel modeling approaches for evaluating chemicals based on their potential for biologi...

Physiologically-based pharmacokinetic (PBPK) modeling to explore potential metabolic pathways of bromochloromethane in rats

EPA Science Inventory

Bromochloromethane (BCM) is a volatile compound and a by-product of disinfection of water by ofchlorination. Physiologically based pharmacokinetic (PBPK) models are used in risk assessment applications. An updated PBPKmodel for BCM is generated and applied to hypotheses testing c...

Anharmonic Normal Mode Analysis of Elastic Network Model Improves the Modeling of Atomic Fluctuations in Protein Crystal Structures

PubMed Central

Zheng, Wenjun

2010-01-01

Abstract Protein conformational dynamics, despite its significant anharmonicity, has been widely explored by normal mode analysis (NMA) based on atomic or coarse-grained potential functions. To account for the anharmonic aspects of protein dynamics, this study proposes, and has performed, an anharmonic NMA (ANMA) based on the Cα-only elastic network models, which assume elastic interactions between pairs of residues whose Cα atoms or heavy atoms are within a cutoff distance. The key step of ANMA is to sample an anharmonic potential function along the directions of eigenvectors of the lowest normal modes to determine the mean-squared fluctuations along these directions. ANMA was evaluated based on the modeling of anisotropic displacement parameters (ADPs) from a list of 83 high-resolution protein crystal structures. Significant improvement was found in the modeling of ADPs by ANMA compared with standard NMA. Further improvement in the modeling of ADPs is attained if the interactions between a protein and its crystalline environment are taken into account. In addition, this study has determined the optimal cutoff distances for ADP modeling based on elastic network models, and these agree well with the peaks of the statistical distributions of distances between Cα atoms or heavy atoms derived from a large set of protein crystal structures. PMID:20550915

The use and QA of biologically related models for treatment planning: short report of the TG-166 of the therapy physics committee of the AAPM.

PubMed

Allen Li, X; Alber, Markus; Deasy, Joseph O; Jackson, Andrew; Ken Jee, Kyung-Wook; Marks, Lawrence B; Martel, Mary K; Mayo, Charles; Moiseenko, Vitali; Nahum, Alan E; Niemierko, Andrzej; Semenenko, Vladimir A; Yorke, Ellen D

2012-03-01

Treatment planning tools that use biologically related models for plan optimization and/or evaluation are being introduced for clinical use. A variety of dose-response models and quantities along with a series of organ-specific model parameters are included in these tools. However, due to various limitations, such as the limitations of models and available model parameters, the incomplete understanding of dose responses, and the inadequate clinical data, the use of biologically based treatment planning system (BBTPS) represents a paradigm shift and can be potentially dangerous. There will be a steep learning curve for most planners. The purpose of this task group is to address some of these relevant issues before the use of BBTPS becomes widely spread. In this report, the authors (1) discuss strategies, limitations, conditions, and cautions for using biologically based models and parameters in clinical treatment planning; (2) demonstrate the practical use of the three most commonly used commercially available BBTPS and potential dosimetric differences between biologically model based and dose-volume based treatment plan optimization and evaluation; (3) identify the desirable features and future directions in developing BBTPS; and (4) provide general guidelines and methodology for the acceptance testing, commissioning, and routine quality assurance (QA) of BBTPS.

Feature Extraction of Event-Related Potentials Using Wavelets: An Application to Human Performance Monitoring

NASA Technical Reports Server (NTRS)

Trejo, Leonard J.; Shensa, Mark J.; Remington, Roger W. (Technical Monitor)

1998-01-01

This report describes the development and evaluation of mathematical models for predicting human performance from discrete wavelet transforms (DWT) of event-related potentials (ERP) elicited by task-relevant stimuli. The DWT was compared to principal components analysis (PCA) for representation of ERPs in linear regression and neural network models developed to predict a composite measure of human signal detection performance. Linear regression models based on coefficients of the decimated DWT predicted signal detection performance with half as many f ree parameters as comparable models based on PCA scores. In addition, the DWT-based models were more resistant to model degradation due to over-fitting than PCA-based models. Feed-forward neural networks were trained using the backpropagation,-, algorithm to predict signal detection performance based on raw ERPs, PCA scores, or high-power coefficients of the DWT. Neural networks based on high-power DWT coefficients trained with fewer iterations, generalized to new data better, and were more resistant to overfitting than networks based on raw ERPs. Networks based on PCA scores did not generalize to new data as well as either the DWT network or the raw ERP network. The results show that wavelet expansions represent the ERP efficiently and extract behaviorally important features for use in linear regression or neural network models of human performance. The efficiency of the DWT is discussed in terms of its decorrelation and energy compaction properties. In addition, the DWT models provided evidence that a pattern of low-frequency activity (1 to 3.5 Hz) occurring at specific times and scalp locations is a reliable correlate of human signal detection performance.

Feature extraction of event-related potentials using wavelets: an application to human performance monitoring

NASA Technical Reports Server (NTRS)

Trejo, L. J.; Shensa, M. J.

1999-01-01

This report describes the development and evaluation of mathematical models for predicting human performance from discrete wavelet transforms (DWT) of event-related potentials (ERP) elicited by task-relevant stimuli. The DWT was compared to principal components analysis (PCA) for representation of ERPs in linear regression and neural network models developed to predict a composite measure of human signal detection performance. Linear regression models based on coefficients of the decimated DWT predicted signal detection performance with half as many free parameters as comparable models based on PCA scores. In addition, the DWT-based models were more resistant to model degradation due to over-fitting than PCA-based models. Feed-forward neural networks were trained using the backpropagation algorithm to predict signal detection performance based on raw ERPs, PCA scores, or high-power coefficients of the DWT. Neural networks based on high-power DWT coefficients trained with fewer iterations, generalized to new data better, and were more resistant to overfitting than networks based on raw ERPs. Networks based on PCA scores did not generalize to new data as well as either the DWT network or the raw ERP network. The results show that wavelet expansions represent the ERP efficiently and extract behaviorally important features for use in linear regression or neural network models of human performance. The efficiency of the DWT is discussed in terms of its decorrelation and energy compaction properties. In addition, the DWT models provided evidence that a pattern of low-frequency activity (1 to 3.5 Hz) occurring at specific times and scalp locations is a reliable correlate of human signal detection performance. Copyright 1999 Academic Press.

Modeling potential evapotranspiration of two forested watersheds in the southern Appalachians

Treesearch

L.Y. Rao; G. Sun; C.R. Ford; J.M. Vose

2011-01-01

Global climate change has direct impacts on watershed hydrology through altering evapotranspiration (ET) processes at multiple scales. There are many methods to estimate forest ET with models, but the most practical and the most popular one is the potential ET (PET) based method. However, the choice of PET methods for AET estimation remains challenging. This study...

Representing the effects of stratosphere–troposphere exchange on 3-D O3 distributions in chemistry transport models using a potential vorticity-based parameterization

EPA Science Inventory

Downward transport of ozone (O3) from the stratosphere can be a significant contributor to tropospheric O3 background levels. However, this process often is not well represented in current regional models. In this study, we develop a seasonally and spatially varying potential vor...

Assessing the prospective resource base for enhanced geothermal systems in Europe

NASA Astrophysics Data System (ADS)

Limberger, J.; Calcagno, P.; Manzella, A.; Trumpy, E.; Boxem, T.; Pluymaekers, M. P. D.; van Wees, J.-D.

2014-12-01

In this study the resource base for EGS (enhanced geothermal systems) in Europe was quantified and economically constrained, applying a discounted cash-flow model to different techno-economic scenarios for future EGS in 2020, 2030, and 2050. Temperature is a critical parameter that controls the amount of thermal energy available in the subsurface. Therefore, the first step in assessing the European resource base for EGS is the construction of a subsurface temperature model of onshore Europe. Subsurface temperatures were computed to a depth of 10 km below ground level for a regular 3-D hexahedral grid with a horizontal resolution of 10 km and a vertical resolution of 250 m. Vertical conductive heat transport was considered as the main heat transfer mechanism. Surface temperature and basal heat flow were used as boundary conditions for the top and bottom of the model, respectively. If publicly available, the most recent and comprehensive regional temperature models, based on data from wells, were incorporated. With the modeled subsurface temperatures and future technical and economic scenarios, the technical potential and minimum levelized cost of energy (LCOE) were calculated for each grid cell of the temperature model. Calculations for a typical EGS scenario yield costs of EUR 215 MWh-1 in 2020, EUR 127 MWh-1 in 2030, and EUR 70 MWh-1 in 2050. Cutoff values of EUR 200 MWh-1 in 2020, EUR 150 MWh-1 in 2030, and EUR 100 MWh-1 in 2050 are imposed to the calculated LCOE values in each grid cell to limit the technical potential, resulting in an economic potential for Europe of 19 GWe in 2020, 22 GWe in 2030, and 522 GWe in 2050. The results of our approach do not only provide an indication of prospective areas for future EGS in Europe, but also show a more realistic cost determined and depth-dependent distribution of the technical potential by applying different well cost models for 2020, 2030, and 2050.

Climate-based species distribution models for Armillaria solidipes in Wyoming: A preliminary assessment

Treesearch

John W. Hanna; James T. Blodgett; Eric W. I. Pitman; Sarah M. Ashiglar; John E. Lundquist; Mee-Sook Kim; Amy L. Ross-Davis; Ned B. Klopfenstein

2014-01-01

As part of an ongoing project to predict Armillaria root disease in the Rocky Mountain zone, this project predicts suitable climate space (potential distribution) for A. solidipes in Wyoming and associated forest areas at risk to disease caused by this pathogen. Two bioclimatic models are being developed. One model is based solely on verified locations of A. solidipes...

Hybrid forecasting of chaotic processes: Using machine learning in conjunction with a knowledge-based model

NASA Astrophysics Data System (ADS)

Pathak, Jaideep; Wikner, Alexander; Fussell, Rebeckah; Chandra, Sarthak; Hunt, Brian R.; Girvan, Michelle; Ott, Edward

2018-04-01

A model-based approach to forecasting chaotic dynamical systems utilizes knowledge of the mechanistic processes governing the dynamics to build an approximate mathematical model of the system. In contrast, machine learning techniques have demonstrated promising results for forecasting chaotic systems purely from past time series measurements of system state variables (training data), without prior knowledge of the system dynamics. The motivation for this paper is the potential of machine learning for filling in the gaps in our underlying mechanistic knowledge that cause widely-used knowledge-based models to be inaccurate. Thus, we here propose a general method that leverages the advantages of these two approaches by combining a knowledge-based model and a machine learning technique to build a hybrid forecasting scheme. Potential applications for such an approach are numerous (e.g., improving weather forecasting). We demonstrate and test the utility of this approach using a particular illustrative version of a machine learning known as reservoir computing, and we apply the resulting hybrid forecaster to a low-dimensional chaotic system, as well as to a high-dimensional spatiotemporal chaotic system. These tests yield extremely promising results in that our hybrid technique is able to accurately predict for a much longer period of time than either its machine-learning component or its model-based component alone.

Making the most of MBSE: pragmatic model-based engineering for the SKA Telescope Manager

NASA Astrophysics Data System (ADS)

Le Roux, Gerhard; Bridger, Alan; MacIntosh, Mike; Nicol, Mark; Schnetler, Hermine; Williams, Stewart

2016-08-01

Many large projects including major astronomy projects are adopting a Model Based Systems Engineering approach. How far is it possible to get value for the effort involved in developing a model that accurately represents a significant project such as SKA? Is it possible for such a large project to ensure that high-level requirements are traceable through the various system-engineering artifacts? Is it possible to utilize the tools available to produce meaningful measures for the impact of change? This paper shares one aspect of the experience gained on the SKA project. It explores some of the recommended and pragmatic approaches developed, to get the maximum value from the modeling activity while designing the Telescope Manager for the SKA. While it is too early to provide specific measures of success, certain areas are proving to be the most helpful and offering significant potential over the lifetime of the project. The experience described here has been on the 'Cameo Systems Modeler' tool-set, supporting a SysML based System Engineering approach; however the concepts and ideas covered would potentially be of value to any large project considering a Model based approach to their Systems Engineering.

Systematic and simulation-free coarse graining of homopolymer melts: a relative-entropy-based study.

PubMed

Yang, Delian; Wang, Qiang

2015-09-28

We applied the systematic and simulation-free strategy proposed in our previous work (D. Yang and Q. Wang, J. Chem. Phys., 2015, 142, 054905) to the relative-entropy-based (RE-based) coarse graining of homopolymer melts. RE-based coarse graining provides a quantitative measure of the coarse-graining performance and can be used to select the appropriate analytic functional forms of the pair potentials between coarse-grained (CG) segments, which are more convenient to use than the tabulated (numerical) CG potentials obtained from structure-based coarse graining. In our general coarse-graining strategy for homopolymer melts using the RE framework proposed here, the bonding and non-bonded CG potentials are coupled and need to be solved simultaneously. Taking the hard-core Gaussian thread model (K. S. Schweizer and J. G. Curro, Chem. Phys., 1990, 149, 105) as the original system, we performed RE-based coarse graining using the polymer reference interaction site model theory under the assumption that the intrachain segment pair correlation functions of CG systems are the same as those in the original system, which de-couples the bonding and non-bonded CG potentials and simplifies our calculations (that is, we only calculated the latter). We compared the performance of various analytic functional forms of non-bonded CG pair potential and closures for CG systems in RE-based coarse graining, as well as the structural and thermodynamic properties of original and CG systems at various coarse-graining levels. Our results obtained from RE-based coarse graining are also compared with those from structure-based coarse graining.

Languages, communication potential and generalized trust in Sub-Saharan Africa: evidence based on the Afrobarometer Survey.

PubMed

Buzasi, Katalin

2015-01-01

The goal of this study is to investigate whether speaking other than home languages in Sub-Saharan Africa promotes generalized trust. Based on various psychological and economic theories, a simple model is provided to illustrate how languages might shape trust through various channels. Relying on data from the Afrobarometer Project, which provides information on home and additional languages, the Index of Communication Potential (ICP) is introduced to capture the linguistic situation in the 20 sample countries. The ICP, which can be computed at any desired level of aggregation, refers to the probability that an individual can communicate with a randomly selected person in the society based on common languages. The estimated two-level hierarchical models show that, however, individual level communication potential does not seem to impact trust formation, but living in an area with higher average communication potential increases the chance of exhibiting higher trust toward unknown people. Copyright © 2014 Elsevier Inc. All rights reserved.

Biofilm formation by Listeria monocytogenes on stainless steel surface and biotransfer potential.

PubMed

de Oliveira, Maíra Maciel Mattos; Brugnera, Danilo Florisvaldo; Alves, Eduardo; Piccoli, Roberta Hilsdorf

2010-01-01

An experimental model was proposed to study biofilm formation by Listeria monocytogenes ATCC 19117 on AISI 304 (#4) stainless steel surface and biotransfer potential during this process. In this model, biofilm formation was conducted on the surface of stainless steel coupons, set on a stainless steel base with 4 divisions, each one supporting 21 coupons. Trypic Soy Broth was used as bacterial growth substrate, with incubation at 37 °C and stirring of 50 rpm. The number of adhered cells was determined after 3, 48, 96, 144, 192 and 240 hours of biofilm formation and biotransfer potential from 96 hours. Stainless steel coupons were submitted to Scanning Electron Microscopy (SEM) after 3, 144 and 240 hours. Based on the number of adhered cells and SEM, it was observed that L. monocytogenes adhered rapidly to the stainless steel surface, with mature biofilm being formed after 240 hours. The biotransfer potential of bacterium to substrate occurred at all the stages analyzed. The rapid capacity of adhesion to surface, combined with biotransfer potential throughout the biofilm formation stages, make L. monocytogenes a potential risk to the food industry. Both the experimental model developed and the methodology used were efficient in the study of biofilm formation by L. monocytogenes on stainless steel surface and biotransfer potential.

Model-based estimators of density and connectivity to inform conservation of spatially structured populations

USGS Publications Warehouse

Morin, Dana J.; Fuller, Angela K.; Royle, J. Andrew; Sutherland, Chris

2017-01-01

Conservation and management of spatially structured populations is challenging because solutions must consider where individuals are located, but also differential individual space use as a result of landscape heterogeneity. A recent extension of spatial capture–recapture (SCR) models, the ecological distance model, uses spatial encounter histories of individuals (e.g., a record of where individuals are detected across space, often sequenced over multiple sampling occasions), to estimate the relationship between space use and characteristics of a landscape, allowing simultaneous estimation of both local densities of individuals across space and connectivity at the scale of individual movement. We developed two model-based estimators derived from the SCR ecological distance model to quantify connectivity over a continuous surface: (1) potential connectivity—a metric of the connectivity of areas based on resistance to individual movement; and (2) density-weighted connectivity (DWC)—potential connectivity weighted by estimated density. Estimates of potential connectivity and DWC can provide spatial representations of areas that are most important for the conservation of threatened species, or management of abundant populations (i.e., areas with high density and landscape connectivity), and thus generate predictions that have great potential to inform conservation and management actions. We used a simulation study with a stationary trap design across a range of landscape resistance scenarios to evaluate how well our model estimates resistance, potential connectivity, and DWC. Correlation between true and estimated potential connectivity was high, and there was positive correlation and high spatial accuracy between estimated DWC and true DWC. We applied our approach to data collected from a population of black bears in New York, and found that forested areas represented low levels of resistance for black bears. We demonstrate that formal inference about measures of landscape connectivity can be achieved from standard methods of studying animal populations which yield individual encounter history data such as camera trapping. Resulting biological parameters including resistance, potential connectivity, and DWC estimate the spatial distribution and connectivity of the population within a statistical framework, and we outline applications to many possible conservation and management problems.

Comparing niche- and process-based models to reduce prediction uncertainty in species range shifts under climate change.

PubMed

Morin, Xavier; Thuiller, Wilfried

2009-05-01

Obtaining reliable predictions of species range shifts under climate change is a crucial challenge for ecologists and stakeholders. At the continental scale, niche-based models have been widely used in the last 10 years to predict the potential impacts of climate change on species distributions all over the world, although these models do not include any mechanistic relationships. In contrast, species-specific, process-based predictions remain scarce at the continental scale. This is regrettable because to secure relevant and accurate predictions it is always desirable to compare predictions derived from different kinds of models applied independently to the same set of species and using the same raw data. Here we compare predictions of range shifts under climate change scenarios for 2100 derived from niche-based models with those of a process-based model for 15 North American boreal and temperate tree species. A general pattern emerged from our comparisons: niche-based models tend to predict a stronger level of extinction and a greater proportion of colonization than the process-based model. This result likely arises because niche-based models do not take phenotypic plasticity and local adaptation into account. Nevertheless, as the two kinds of models rely on different assumptions, their complementarity is revealed by common findings. Both modeling approaches highlight a major potential limitation on species tracking their climatic niche because of migration constraints and identify similar zones where species extirpation is likely. Such convergent predictions from models built on very different principles provide a useful way to offset uncertainties at the continental scale. This study shows that the use in concert of both approaches with their own caveats and advantages is crucial to obtain more robust results and that comparisons among models are needed in the near future to gain accuracy regarding predictions of range shifts under climate change.

Analysis of energy-saving potential in residential buildings in Xiamen City and its policy implications for southern China

NASA Astrophysics Data System (ADS)

Guo, Fei

The buildings sector is the largest energy-consuming sector in the world. Residential buildings consume about three-quarters of the final energy in the buildings sector. Promoting residential energy savings is in consequence critical for addressing many energy-use-related environmental challenges, such as climate change and air pollution. Given China's robust economic growth and fast urbanization, it is now a critical time to develop policy interventions on residential energy use in the nation. With this as a background, this dissertation explores effective policy intervention opportunities in southern China through analyzing the residential energy-saving potential, using the city of Xiamen as a case study. Four types of residential energy-saving potential are analyzed: technical potential, economic potential, maximum achievable potential (MAP), and possible achievable potential (PAP). Of these, the first two types are characterized as static theoretical evaluation, while the last two represent dynamic evaluation within a certain time horizon. The achievable potential analyses are rarely seen in existing literature. The analytical results reveal that there exists a significant technical potential for residential energy savings of about 20.9-24.9% in the city of Xiamen. Of the technical potential, about two-thirds to four-fifths are cost-effective from the government or society perspective. The cost-effectiveness is evaluated by comparing the "Levelized Cost of Conserved Energy (LCOCE)" of available advanced technical measures with the "Actual Cost" of conserved energy. The "Actual Cost" of energy is defined by adding the environmental externalities costs and hidden government subsidies over the retail prices of energy. The achievable potential analyses are particularly based on two key realistic factors: 1) the gradual ramping-up adoption process of advanced technical measures; and 2) individuals' adoption-decision making on them. For implementing the achievable potential analyses in Xiamen, a residential energy consumption (REC) projection model specifically tailored for southern China is developed. This computational model builds on the Kastovich (1982) adoption-decision theory and the general logic used in the U.S. EIA's (2003) National Energy Modeling System (NEMS). Base on this projection model, Xiamen's REC from the base year 2011 to 2020 is projected. This model can be used as a policy analysis tool to quantitatively evaluate the real-world impact of diverse policy incentives on residential energy use in southern China. The projection results show that the MAP of residential energy savings in Xiamen will be about only 8.3-8.4% in 2020 from a business-as-usual projection. Ten current appropriate and feasible policy interventions are evaluated for analyzing the PAP in Xiamen, which reveals that only about one-fourth to one-half of Xiamen's MAP will possibly be achieved in 2020. Based on the potential analysis for the Xiamen case, a discussion on promoting energy-saving incentive policies for the residential buildings in southern China is given. It suggests that more new, innovative and market-based policies need to be introduced in China in order to realize larger achievable potential for residential energy savings.

Biochemical methane potential prediction of plant biomasses: Comparing chemical composition versus near infrared methods and linear versus non-linear models.

PubMed

Godin, Bruno; Mayer, Frédéric; Agneessens, Richard; Gerin, Patrick; Dardenne, Pierre; Delfosse, Philippe; Delcarte, Jérôme

2015-01-01

The reliability of different models to predict the biochemical methane potential (BMP) of various plant biomasses using a multispecies dataset was compared. The most reliable prediction models of the BMP were those based on the near infrared (NIR) spectrum compared to those based on the chemical composition. The NIR predictions of local (specific regression and non-linear) models were able to estimate quantitatively, rapidly, cheaply and easily the BMP. Such a model could be further used for biomethanation plant management and optimization. The predictions of non-linear models were more reliable compared to those of linear models. The presentation form (green-dried, silage-dried and silage-wet form) of biomasses to the NIR spectrometer did not influence the performances of the NIR prediction models. The accuracy of the BMP method should be improved to enhance further the BMP prediction models. Copyright © 2014 Elsevier Ltd. All rights reserved.

Identification of promising DNA GyrB inhibitors for Tuberculosis using pharmacophore-based virtual screening, molecular docking and molecular dynamics studies.

PubMed

Islam, Md Ataul; Pillay, Tahir S

2017-08-01

In this study, we searched for potential DNA GyrB inhibitors using pharmacophore-based virtual screening followed by molecular docking and molecular dynamics simulation approaches. For this purpose, a set of 248 DNA GyrB inhibitors was collected from the literature and a well-validated pharmacophore model was generated. The best pharmacophore model explained that two each of hydrogen bond acceptors and hydrophobicity regions were critical for inhibition of DNA GyrB. Good statistical results of the pharmacophore model indicated that the model was robust in nature. Virtual screening of molecular databases revealed three molecules as potential antimycobacterial agents. The final screened promising compounds were evaluated in molecular docking and molecular dynamics simulation studies. In the molecular dynamics studies, RMSD and RMSF values undoubtedly explained that the screened compounds formed stable complexes with DNA GyrB. Therefore, it can be concluded that the compounds identified may have potential for the treatment of TB. © 2017 John Wiley & Sons A/S.

Cotton growth modeling and assessment using UAS visual-band imagery

USDA-ARS?s Scientific Manuscript database

This paper explores the potential of using unmanned aircraft system (UAS)-based visible-band images to assess cotton growth. By applying the structure-from-motion algorithm, cotton plant height (ph) and canopy cover (cc) were retrieved from the point cloud-based digital surface models (DSMs) and ort...

Designing Corporate Databases to Support Technology Innovation

ERIC Educational Resources Information Center

Gultz, Michael Jarett

2012-01-01

Based on a review of the existing literature on database design, this study proposed a unified database model to support corporate technology innovation. This study assessed potential support for the model based on the opinions of 200 technology industry executives, including Chief Information Officers, Chief Knowledge Officers and Chief Learning…

Thermodynamics-based models of transcriptional regulation with gene sequence.

PubMed

Wang, Shuqiang; Shen, Yanyan; Hu, Jinxing

2015-12-01

Quantitative models of gene regulatory activity have the potential to improve our mechanistic understanding of transcriptional regulation. However, the few models available today have been based on simplistic assumptions about the sequences being modeled or heuristic approximations of the underlying regulatory mechanisms. In this work, we have developed a thermodynamics-based model to predict gene expression driven by any DNA sequence. The proposed model relies on a continuous time, differential equation description of transcriptional dynamics. The sequence features of the promoter are exploited to derive the binding affinity which is derived based on statistical molecular thermodynamics. Experimental results show that the proposed model can effectively identify the activity levels of transcription factors and the regulatory parameters. Comparing with the previous models, the proposed model can reveal more biological sense.

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

PubMed

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

2015-06-01

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

Internet-based crowdsourcing and research ethics: the case for IRB review.

PubMed

Graber, Mark A; Graber, Abraham

2013-02-01

The recent success of Foldit in determining the structure of the Mason-Pfizer monkey virus (M-PMV) retroviral protease is suggestive of the power-solving potential of internet-facilitated game-like crowdsourcing. This research model is highly novel, however, and thus, deserves careful consideration of potential ethical issues. In this paper, we will demonstrate that the crowdsourcing model of research has the potential to cause harm to participants, manipulates the participant into continued participation, and uses participants as experimental subjects. We conclude that protocols relying on this model require institutional review board (IRB) scrutiny.

Multi-Agent-Based Simulation of a Complex Ecosystem of Mental Health Care.

PubMed

Kalton, Alan; Falconer, Erin; Docherty, John; Alevras, Dimitris; Brann, David; Johnson, Kyle

2016-02-01

This paper discusses the creation of an Agent-Based Simulation that modeled the introduction of care coordination capabilities into a complex system of care for patients with Serious and Persistent Mental Illness. The model describes the engagement between patients and the medical, social and criminal justice services they interact with in a complex ecosystem of care. We outline the challenges involved in developing the model, including process mapping and the collection and synthesis of data to support parametric estimates, and describe the controls built into the model to support analysis of potential changes to the system. We also describe the approach taken to calibrate the model to an observable level of system performance. Preliminary results from application of the simulation are provided to demonstrate how it can provide insights into potential improvements deriving from introduction of care coordination technology.

A vector space model approach to identify genetically related diseases.

PubMed

Sarkar, Indra Neil

2012-01-01

The relationship between diseases and their causative genes can be complex, especially in the case of polygenic diseases. Further exacerbating the challenges in their study is that many genes may be causally related to multiple diseases. This study explored the relationship between diseases through the adaptation of an approach pioneered in the context of information retrieval: vector space models. A vector space model approach was developed that bridges gene disease knowledge inferred across three knowledge bases: Online Mendelian Inheritance in Man, GenBank, and Medline. The approach was then used to identify potentially related diseases for two target diseases: Alzheimer disease and Prader-Willi Syndrome. In the case of both Alzheimer Disease and Prader-Willi Syndrome, a set of plausible diseases were identified that may warrant further exploration. This study furthers seminal work by Swanson, et al. that demonstrated the potential for mining literature for putative correlations. Using a vector space modeling approach, information from both biomedical literature and genomic resources (like GenBank) can be combined towards identification of putative correlations of interest. To this end, the relevance of the predicted diseases of interest in this study using the vector space modeling approach were validated based on supporting literature. The results of this study suggest that a vector space model approach may be a useful means to identify potential relationships between complex diseases, and thereby enable the coordination of gene-based findings across multiple complex diseases.

Sexual attraction to others: a comparison of two models of alloerotic responding in men.

PubMed

Blanchard, Ray; Kuban, Michael E; Blak, Thomas; Klassen, Philip E; Dickey, Robert; Cantor, James M

2012-02-01

The penile response profiles of homosexual and heterosexual pedophiles, hebephiles, and teleiophiles to laboratory stimuli depicting male and female children and adults may be conceptualized as a series of overlapping stimulus generalization gradients. This study used such profile data to compare two models of alloerotic responding (sexual responding to other people) in men. The first model was based on the notion that men respond to a potential sexual object as a compound stimulus made up of an age component and a gender component. The second model was based on the notion that men respond to a potential sexual object as a gestalt, which they evaluate in terms of global similarity to other potential sexual objects. The analytic strategy was to compare the accuracy of these models in predicting a man's penile response to each of his less arousing (nonpreferred) stimulus categories from his response to his most arousing (preferred) stimulus category. Both models based their predictions on the degree of dissimilarity between the preferred stimulus category and a given nonpreferred stimulus category, but each model used its own measure of dissimilarity. According to the first model ("summation model"), penile response should vary inversely as the sum of stimulus differences on separate dimensions of age and gender. According to the second model ("bipolar model"), penile response should vary inversely as the distance between stimulus categories on a single, bipolar dimension of morphological similarity-a dimension on which children are located near the middle, and adult men and women are located at opposite ends. The subjects were 2,278 male patients referred to a specialty clinic for phallometric assessment of their erotic preferences. Comparisons of goodness of fit to the observed data favored the unidimensional bipolar model.

Human iPSC-derived cardiomyocytes and tissue engineering strategies for disease modeling and drug screening

PubMed Central

Smith, Alec S.T.; Macadangdang, Jesse; Leung, Winnie; Laflamme, Michael A.; Kim, Deok-Ho

2016-01-01

Improved methodologies for modeling cardiac disease phenotypes and accurately screening the efficacy and toxicity of potential therapeutic compounds are actively being sought to advance drug development and improve disease modeling capabilities. To that end, much recent effort has been devoted to the development of novel engineered biomimetic cardiac tissue platforms that accurately recapitulate the structure and function of the human myocardium. Within the field of cardiac engineering, induced pluripotent stem cells (iPSCs) are an exciting tool that offer the potential to advance the current state of the art, as they are derived from somatic cells, enabling the development of personalized medical strategies and patient specific disease models. Here we review different aspects of iPSC-based cardiac engineering technologies. We highlight methods for producing iPSC-derived cardiomyocytes (iPSC-CMs) and discuss their application to compound efficacy/toxicity screening and in vitro modeling of prevalent cardiac diseases. Special attention is paid to the application of micro- and nano-engineering techniques for the development of novel iPSC-CM based platforms and their potential to advance current preclinical screening modalities. PMID:28007615

Generalized large-scale semigeostrophic approximations for the f-plane primitive equations

NASA Astrophysics Data System (ADS)

Oliver, Marcel; Vasylkevych, Sergiy

2016-05-01

We derive a family of balance models for rotating stratified flow in the primitive equation (PE) setting. By construction, the models possess conservation laws for energy and potential vorticity and are formally of the same order of accuracy as Hoskins’ semigeostrophic equations. Our construction is based on choosing a new coordinate frame for the PE variational principle in such a way that the consistently truncated Lagrangian degenerates. We show that the balance relations so obtained are elliptic when the fluid is stably stratified and certain smallness assumptions are satisfied. Moreover, the potential temperature can be recovered from the potential vorticity via inversion of a non-standard Monge-Ampère problem which is subject to the same ellipticity condition. While the present work is entirely formal, we conjecture, based on a careful rewriting of the equations of motion and a straightforward derivative count, that the Cauchy problem for the balance models is well posed subject to conditions on the initial data. Our family of models includes, in particular, the stratified analog of the L 1 balance model of Salmon.

GVIPS Models and Software

NASA Technical Reports Server (NTRS)

Arnold, Steven M.; Gendy, Atef; Saleeb, Atef F.; Mark, John; Wilt, Thomas E.

2007-01-01

Two reports discuss, respectively, (1) the generalized viscoplasticity with potential structure (GVIPS) class of mathematical models and (2) the Constitutive Material Parameter Estimator (COMPARE) computer program. GVIPS models are constructed within a thermodynamics- and potential-based theoretical framework, wherein one uses internal state variables and derives constitutive equations for both the reversible (elastic) and the irreversible (viscoplastic) behaviors of materials. Because of the underlying potential structure, GVIPS models not only capture a variety of material behaviors but also are very computationally efficient. COMPARE comprises (1) an analysis core and (2) a C++-language subprogram that implements a Windows-based graphical user interface (GUI) for controlling the core. The GUI relieves the user of the sometimes tedious task of preparing data for the analysis core, freeing the user to concentrate on the task of fitting experimental data and ultimately obtaining a set of material parameters. The analysis core consists of three modules: one for GVIPS material models, an analysis module containing a specialized finite-element solution algorithm, and an optimization module. COMPARE solves the problem of finding GVIPS material parameters in the manner of a design-optimization problem in which the parameters are the design variables.

Objective quantification of the tinnitus decompensation by synchronization measures of auditory evoked single sweeps.

PubMed

Strauss, Daniel J; Delb, Wolfgang; D'Amelio, Roberto; Low, Yin Fen; Falkai, Peter

2008-02-01

Large-scale neural correlates of the tinnitus decompensation might be used for an objective evaluation of therapies and neurofeedback based therapeutic approaches. In this study, we try to identify large-scale neural correlates of the tinnitus decompensation using wavelet phase stability criteria of single sweep sequences of late auditory evoked potentials as synchronization stability measure. The extracted measure provided an objective quantification of the tinnitus decompensation and allowed for a reliable discrimination between a group of compensated and decompensated tinnitus patients. We provide an interpretation for our results by a neural model of top-down projections based on the Jastreboff tinnitus model combined with the adaptive resonance theory which has not been applied to model tinnitus so far. Using this model, our stability measure of evoked potentials can be linked to the focus of attention on the tinnitus signal. It is concluded that the wavelet phase stability of late auditory evoked potential single sweeps might be used as objective tinnitus decompensation measure and can be interpreted in the framework of the Jastreboff tinnitus model and adaptive resonance theory.

Interdisciplinary modeling and analysis to reduce loss of life from tsunamis

NASA Astrophysics Data System (ADS)

Wood, N. J.

2016-12-01

Recent disasters have demonstrated the significant loss of life and community impacts that can occur from tsunamis. Minimizing future losses requires an integrated understanding of the range of potential tsunami threats, how individuals are specifically vulnerable to these threats, what is currently in place to improve their chances of survival, and what risk-reduction efforts could be implemented. This presentation will provide a holistic perspective of USGS research enabled by recent advances in geospatial modeling to assess and communicate population vulnerability to tsunamis and the range of possible interventions to reduce it. Integrated research includes efforts to characterize the magnitude and demography of at-risk individuals in tsunami-hazard zones, their evacuation potential based on landscape conditions, nature-based mitigation to improve evacuation potential, evacuation pathways and population demand at assembly areas, siting considerations for vertical-evacuation refuges, community implications of multiple evacuation zones, car-based evacuation modeling for distant tsunamis, and projected changes in population exposure to tsunamis over time. Collectively, this interdisciplinary research supports emergency managers in their efforts to implement targeted risk-reduction efforts based on local conditions and needs, instead of generic regional strategies that only focus on hazard attributes.

Test Platforms for Model-Based Flight Research

NASA Astrophysics Data System (ADS)

Dorobantu, Andrei

Demonstrating the reliability of flight control algorithms is critical to integrating unmanned aircraft systems into the civilian airspace. For many potential applications, design and certification of these algorithms will rely heavily on mathematical models of the aircraft dynamics. Therefore, the aerospace community must develop flight test platforms to support the advancement of model-based techniques. The University of Minnesota has developed a test platform dedicated to model-based flight research for unmanned aircraft systems. This thesis provides an overview of the test platform and its research activities in the areas of system identification, model validation, and closed-loop control for small unmanned aircraft.

SU-G-TeP4-14: Quality Control of Treatment Planning Using Knowledge-Based Planning Across a System of Radiation Oncology Practices

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

Masi, K; Ditman, M; Marsh, R

Purpose: There is potentially a wide variation in plan quality for a certain disease site, even for clinics located in the same system of hospitals. We have used a prostate-specific knowledge-based planning (KBP) model as a quality control tool to investigate the variation in prostate treatment planning across a network of affiliated radiation oncology departments. Methods: A previously created KBP model was applied to 10 patients each from 4 community-based clinics (Clinics A, B, C, and D). The KBP model was developed using RapidPlan (Eclipse v13.5, Varian Medical Systems) from 60 prostate/prostate bed IMRT plans that were originally planned usingmore » an in-house treatment planning system at the central institution of the community-based clinics. The dosimetric plan quality (target coverage and normal-tissue sparing) of each model-generated plan was compared to the respective clinically-used plan. Each community-based clinic utilized the same planning goals to develop the clinically-used plans that were used at the main institution. Results: Across all 4 clinics, the model-generated plans decreased the mean dose to the rectum by varying amounts (on average, 12.5, 2.6, 4.5, and 2.7 Gy for Clinics A, B, C, and D, respectively). The mean dose to the bladder also decreased with the model-generated plans (5.4, 2.3, 3.0, and 4.1 Gy, respectively). The KBP model also identified that target coverage (D95%) improvements were possible for for Clinics A, B, and D (0.12, 1.65, and 2.75%) while target coverage decreased by 0.72% for Clinic C, demonstrating potentially different trade-offs made in clinical plans at different institutions. Conclusion: Quality control of dosimetric plan quality across a system of radiation oncology practices is possible with knowledge-based planning. By using a quality KBP model, smaller community-based clinics can potentially identify the areas of their treatment plans that may be improved, whether it be in normal-tissue sparing or improved target coverage. M. Matuszak has research funding for KBP from Varian Medical Systems.« less

Agent based modeling in tactical wargaming

NASA Astrophysics Data System (ADS)

James, Alex; Hanratty, Timothy P.; Tuttle, Daniel C.; Coles, John B.

2016-05-01

Army staffs at division, brigade, and battalion levels often plan for contingency operations. As such, analysts consider the impact and potential consequences of actions taken. The Army Military Decision-Making Process (MDMP) dictates identification and evaluation of possible enemy courses of action; however, non-state actors often do not exhibit the same level and consistency of planned actions that the MDMP was originally designed to anticipate. The fourth MDMP step is a particular challenge, wargaming courses of action within the context of complex social-cultural behaviors. Agent-based Modeling (ABM) and its resulting emergent behavior is a potential solution to model terrain in terms of the human domain and improve the results and rigor of the traditional wargaming process.

Protein requirements for long term missions

NASA Astrophysics Data System (ADS)

Stein, T. P.

1994-11-01

A key component of the diet for a space mission is protein. This first part of this paper reviews the reasons for emphasizing protein nutrition and then discusses what the requirements are likely to be. The second part discusses potential advantages of modifying these requirements and describes potential approaches to effecting these modifications based on well established ground based models.

New Coarse-Grained Model and Its Implementation in Simulations of Graphene Assemblies.

PubMed

Shang, Jun-Jun; Yang, Qing-Sheng; Liu, Xia

2017-08-08

Graphene is a one-atom thick layer of carbon atoms arranged in a hexagonal pattern, which makes it the strongest material in the world. The Tersoff potential is a suitable potential for simulating the mechanical behavior of the complex covalently bonded system of graphene. In this paper, we describe a new coarse-grained (CG) potential, TersoffCG, which is based on the function form of the Tersoff potential. The TersoffCG applies to a CG model of graphene that uses the same hexagonal pattern as the atomistic model. The parameters of the TersoffCG potential are determined using structural feature and potential-energy fitting between the CG model and the atomic model. The modeling process of graphene is highly simplified using the present CG model as it avoids the necessity to define bonds/angles/dihedrals connectivity. What is more, the present CG model provides a new perspective of coarse-graining scheme for crystal structures of nanomaterials. The structural changes and mechanical properties of multilayer graphene were calculated using the new potential. Furthermore, a CG model of a graphene aerogel was built in a specific form of assembly. The chemical bonding in the joints of graphene-aerogel forms automatically during the energy relaxation process. The compressive and recover test of the graphene aerogel was reproduced to study its high elasticity. Our computational examples show that the TersoffCG potential can be used for simulations of graphene and its assemblies, which have many applications in areas of environmental protection, aerospace engineering, and others.

A simple, mass balance model of carbon flow in a controlled ecological life support system

NASA Technical Reports Server (NTRS)

Garland, Jay L.

1989-01-01

Internal cycling of chemical elements is a fundamental aspect of a Controlled Ecological Life Support System (CELSS). Mathematical models are useful tools for evaluating fluxes and reservoirs of elements associated with potential CELSS configurations. A simple mass balance model of carbon flow in CELSS was developed based on data from the CELSS Breadboard project at Kennedy Space Center. All carbon reservoirs and fluxes were calculated based on steady state conditions and modelled using linear, donor-controlled transfer coefficients. The linear expression of photosynthetic flux was replaced with Michaelis-Menten kinetics based on dynamical analysis of the model which found that the latter produced more adequate model output. Sensitivity analysis of the model indicated that accurate determination of the maximum rate of gross primary production is critical to the development of an accurate model of carbon flow. Atmospheric carbon dioxide was particularly sensitive to changes in photosynthetic rate. The small reservoir of CO2 relative to large CO2 fluxes increases the potential for volatility in CO2 concentration. Feedback control mechanisms regulating CO2 concentration will probably be necessary in a CELSS to reduce this system instability.

Principal Dynamic Mode Analysis of the Hodgkin–Huxley Equations

PubMed Central

Eikenberry, Steffen E.; Marmarelis, Vasilis Z.

2015-01-01

We develop an autoregressive model framework based on the concept of Principal Dynamic Modes (PDMs) for the process of action potential (AP) generation in the excitable neuronal membrane described by the Hodgkin–Huxley (H–H) equations. The model's exogenous input is injected current, and whenever the membrane potential output exceeds a specified threshold, it is fed back as a second input. The PDMs are estimated from the previously developed Nonlinear Autoregressive Volterra (NARV) model, and represent an efficient functional basis for Volterra kernel expansion. The PDM-based model admits a modular representation, consisting of the forward and feedback PDM bases as linear filterbanks for the exogenous and autoregressive inputs, respectively, whose outputs are then fed to a static nonlinearity composed of polynomials operating on the PDM outputs and cross-terms of pair-products of PDM outputs. A two-step procedure for model reduction is performed: first, influential subsets of the forward and feedback PDM bases are identified and selected as the reduced PDM bases. Second, the terms of the static nonlinearity are pruned. The first step reduces model complexity from a total of 65 coefficients to 27, while the second further reduces the model coefficients to only eight. It is demonstrated that the performance cost of model reduction in terms of out-of-sample prediction accuracy is minimal. Unlike the full model, the eight coefficient pruned model can be easily visualized to reveal the essential system components, and thus the data-derived PDM model can yield insight into the underlying system structure and function. PMID:25630480

Modeling regeneration responses of big sagebrush (Artemisia tridentata) to abiotic conditions

USGS Publications Warehouse

Schlaepfer, Daniel R.; Lauenroth, William K.; Bradford, John B.

2014-01-01

Ecosystems dominated by big sagebrush, Artemisia tridentata Nuttall (Asteraceae), which are the most widespread ecosystems in semiarid western North America, have been affected by land use practices and invasive species. Loss of big sagebrush and the decline of associated species, such as greater sage-grouse, are a concern to land managers and conservationists. However, big sagebrush regeneration remains difficult to achieve by restoration and reclamation efforts and there is no regeneration simulation model available. We present here the first process-based, daily time-step, simulation model to predict yearly big sagebrush regeneration including relevant germination and seedling responses to abiotic factors. We estimated values, uncertainty, and importance of 27 model parameters using a total of 1435 site-years of observation. Our model explained 74% of variability of number of years with successful regeneration at 46 sites. It also achieved 60% overall accuracy predicting yearly regeneration success/failure. Our results identify specific future research needed to improve our understanding of big sagebrush regeneration, including data at the subspecies level and improved parameter estimates for start of seed dispersal, modified wet thermal-time model of germination, and soil water potential influences. We found that relationships between big sagebrush regeneration and climate conditions were site specific, varying across the distribution of big sagebrush. This indicates that statistical models based on climate are unsuitable for understanding range-wide regeneration patterns or for assessing the potential consequences of changing climate on sagebrush regeneration and underscores the value of this process-based model. We used our model to predict potential regeneration across the range of sagebrush ecosystems in the western United States, which confirmed that seedling survival is a limiting factor, whereas germination is not. Our results also suggested that modeled regeneration suitability is necessary but not sufficient to explain sagebrush presence. We conclude that future assessment of big sagebrush responses to climate change will need to account for responses of regenerative stages using a process-based understanding, such as provided by our model.

An Australasian model license reassessment procedure for identifying potentially unsafe drivers.

PubMed

Fildes, Brian N; Charlton, Judith; Pronk, Nicola; Langford, Jim; Oxley, Jennie; Koppel, Sjaanie

2008-08-01

Most licensing jurisdictions in Australia currently employ age-based assessment programs as a means to manage older driver safety, yet available evidence suggests that these programs have no safety benefits. This paper describes a community referral-based model license re assessment procedure for identifying and assessing potentially unsafe drivers. While the model was primarily developed for assessing older driver fitness to drive, it could be applicable to other forms of driver impairment associated with increased crash risk. It includes a three-tier process of assessment, involving the use of validated and relevant assessment instruments. A case is argued that this process is a more systematic, transparent and effective process for managing older driver safety and thus more likely to be widely acceptable to the target community and licensing authorities than age-based practices.

Fuel models and fire potential from satellite and surface observations

USGS Publications Warehouse

Burgan, R.E.; Klaver, R.W.; Klarer, J.M.

1998-01-01

A national 1-km resolution fire danger fuel model map was derived through use of previously mapped land cover classes and ecoregions, and extensive ground sample data, then refined through review by fire managers familiar with various portions of the U.S. The fuel model map will be used in the next generation fire danger rating system for the U.S., but it also made possible immediate development of a satellite and ground based fire potential index map. The inputs and algorithm of the fire potential index are presented, along with a case study of the correlation between the fire potential index and fire occurrence in California and Nevada. Application of the fire potential index in the Mediterranean ecosystems of Spain, Chile, and Mexico will be tested.

Root growth, water uptake, and sap flow of winter wheat in response to different soil water conditions

NASA Astrophysics Data System (ADS)

Cai, Gaochao; Vanderborght, Jan; Langensiepen, Matthias; Schnepf, Andrea; Hüging, Hubert; Vereecken, Harry

2018-04-01

How much water can be taken up by roots and how this depends on the root and water distributions in the root zone are important questions that need to be answered to describe water fluxes in the soil-plant-atmosphere system. Physically based root water uptake (RWU) models that relate RWU to transpiration, root density, and water potential distributions have been developed but used or tested far less. This study aims at evaluating the simulated RWU of winter wheat using the empirical Feddes-Jarvis (FJ) model and the physically based Couvreur (C) model for different soil water conditions and soil textures compared to sap flow measurements. Soil water content (SWC), water potential, and root development were monitored noninvasively at six soil depths in two rhizotron facilities that were constructed in two soil textures: stony vs. silty, with each of three water treatments: sheltered, rainfed, and irrigated. Soil and root parameters of the two models were derived from inverse modeling and simulated RWU was compared with sap flow measurements for validation. The different soil types and water treatments resulted in different crop biomass, root densities, and root distributions with depth. The two models simulated the lowest RWU in the sheltered plot of the stony soil where RWU was also lower than the potential RWU. In the silty soil, simulated RWU was equal to the potential uptake for all treatments. The variation of simulated RWU among the different plots agreed well with measured sap flow but the C model predicted the ratios of the transpiration fluxes in the two soil types slightly better than the FJ model. The root hydraulic parameters of the C model could be constrained by the field data but not the water stress parameters of the FJ model. This was attributed to differences in root densities between the different soils and treatments which are accounted for by the C model, whereas the FJ model only considers normalized root densities. The impact of differences in root density on RWU could be accounted for directly by the physically based RWU model but not by empirical models that use normalized root density functions.

A habitat assessment for Florida panther population expansion into central Florida

USGS Publications Warehouse

Thatcher, C.A.; Van Manen, F.T.; Clark, J.D.

2009-01-01

One of the goals of the Florida panther (Puma concolor coryi) recovery plan is to expand panther range north of the Caloosahatchee River in central Florida. Our objective was to evaluate the potential of that region to support panthers. We used a geographic information system and the Mahalanobis distance statistic to develop a habitat model based on landscape characteristics associated with panther home ranges. We used cross-validation and an independent telemetry data set to test the habitat model. We also conducted a least-cost path analysis to identify potential habitat linkages and to provide a relative measure of connectivity among habitat patches. Variables in our model were paved road density, major highways, human population density, percentage of the area permanently or semipermanently flooded, and percentage of the area in natural land cover. Our model clearly identified habitat typical of that found within panther home ranges based on model testing with recent telemetry data. We identified 4 potential translocation sites that may support a total of approximately 36 panthers. Although we identified potential habitat linkages, our least-cost path analyses highlighted the extreme isolation of panther habitat in portions of the study area. Human intervention will likely be required if the goal is to establish female panthers north of the Caloosahatchee in the near term.

A Modeling Investigation of Thermal and Strain Induced Recovery and Nonlinear Hardening in Potential Based Viscoplasticity

NASA Technical Reports Server (NTRS)

Arnold, S. M.; Saleeb, A. F.; Wilt, T. E.

1993-01-01

Specific forms for both the Gibb's and the complementary dissipation potentials were chosen such that a complete potential based multiaxial, isothermal, viscoplastic model was obtained. This model in general possesses three internal state variables (two scalars associated with dislocation density and one tensor associated with dislocation motion) both thermal and dynamic recovery mechanisms, and nonlinear kinematic hardening. This general model, although possessing associated flow and evolutionary laws, is shown to emulate three distinct classes of theories found in the literature, by modification of the driving threshold function F. A parametric study was performed on a specialized nondimensional multiaxial form containing only a single tensorial internal state variable (i.e., internal stress). The study was conducted with the idea of examining the impact of including a strain-induced recovery mechanism and the compliance operator, derived from the Gibb's potential, on the uniaxial and multiaxial response. One important finding was that inclusion of strain recovery provided the needed flexibility in modeling stress-strain and creep response of metals at low homologous temperatures, without adversely affecting the high temperature response. Furthermore, for nonproportional loading paths, the inclusion of the compliance operator had a significant influence on the multiaxial response, but had no influence on either uniaxial or proportional load histories.

Modeling of nanoscale liquid mixture transport by density functional hydrodynamics

NASA Astrophysics Data System (ADS)

Dinariev, Oleg Yu.; Evseev, Nikolay V.

2017-06-01

Modeling of multiphase compositional hydrodynamics at nanoscale is performed by means of density functional hydrodynamics (DFH). DFH is the method based on density functional theory and continuum mechanics. This method has been developed by the authors over 20 years and used for modeling in various multiphase hydrodynamic applications. In this paper, DFH was further extended to encompass phenomena inherent in liquids at nanoscale. The new DFH extension is based on the introduction of external potentials for chemical components. These potentials are localized in the vicinity of solid surfaces and take account of the van der Waals forces. A set of numerical examples, including disjoining pressure, film precursors, anomalous rheology, liquid in contact with heterogeneous surface, capillary condensation, and forward and reverse osmosis, is presented to demonstrate modeling capabilities.

Ephaptic conduction in a cardiac strand model with 3D electrodiffusion

PubMed Central

Mori, Yoichiro; Fishman, Glenn I.; Peskin, Charles S.

2008-01-01

We study cardiac action potential propagation under severe reduction in gap junction conductance. We use a mathematical model of cellular electrical activity that takes into account both three-dimensional geometry and ionic concentration effects. Certain anatomical and biophysical parameters are varied to see their impact on cardiac action potential conduction velocity. This study uncovers quantitative features of ephaptic propagation that differ from previous studies based on one-dimensional models. We also identify a mode of cardiac action potential propagation in which the ephaptic and gap-junction-mediated mechanisms alternate. Our study demonstrates the usefulness of this modeling approach for electrophysiological systems especially when detailed membrane geometry plays an important role. PMID:18434544

Web based collaborative decision making in flood risk management

NASA Astrophysics Data System (ADS)

Evers, Mariele; Almoradie, Adrian; Jonoski, Andreja

2014-05-01

Stakeholder participation in the development of flood risk management (FRM) plans is essential since stakeholders often have a better understanding or knowledge of the potentials and limitation of their local area. Moreover, a participatory approach also creates trust amongst stakeholders, leading to a successful implementation of measures. Stakeholder participation however has its challenges and potential pitfalls that could lead to its premature termination. Such challenges and pitfalls are the limitation of financial resources, stakeholders' spatial distribution and their interest to participate. Different type of participation in FRM may encounter diverse challenges. These types of participation in FRM can be classified into (1) Information and knowledge sharing (IKS), (2) Consultative participation (CP) or (3) Collaborative decision making (CDM)- the most challenging type of participation. An innovative approach to address these challenges and potential pitfalls is a web-based mobile or computer-aided environment for stakeholder participation. This enhances the remote interaction between participating entities such as stakeholders. This paper presents a developed framework and an implementation of CDM web based environment for the Alster catchment (Hamburg, Germany) and Cranbrook catchment (London, UK). The CDM framework consists of two main stages: (1) Collaborative modelling and (2) Participatory decision making. This paper also highlights the stakeholder analyses, modelling approach and application of General Public License (GPL) technologies in developing the web-based environments. Actual test and evaluation of the environments was through series of stakeholders workshops. The overall results based from stakeholders' evaluation shows that web-based environments can address the challenges and potential pitfalls in stakeholder participation and it enhances participation in flood risk management. The web-based environment was developed within the DIANE-CM project (Decentralised Integrated Analysis and Enhancement of Awareness through Collaborative Modelling and Management of Flood Risk) of the 2nd ERANET CRUE funding initiative.

Where to Dig for Fossils: Combining Climate-Envelope, Taphonomy and Discovery Models

PubMed Central

Block, Sebastián; Saltré, Frédérik; Rodríguez-Rey, Marta; Fordham, Damien A.; Unkel, Ingmar; Bradshaw, Corey J. A.

2016-01-01

Fossils represent invaluable data to reconstruct the past history of life, yet fossil-rich sites are often rare and difficult to find. The traditional fossil-hunting approach focuses on small areas and has not yet taken advantage of modelling techniques commonly used in ecology to account for an organism’s past distributions. We propose a new method to assist finding fossils at continental scales based on modelling the past distribution of species, the geological suitability of fossil preservation and the likelihood of fossil discovery in the field, and apply it to several genera of Australian megafauna that went extinct in the Late Quaternary. Our models predicted higher fossil potentials for independent sites than for randomly selected locations (mean Kolmogorov-Smirnov statistic = 0.66). We demonstrate the utility of accounting for the distribution history of fossil taxa when trying to find the most suitable areas to look for fossils. For some genera, the probability of finding fossils based on simple climate-envelope models was higher than the probability based on models incorporating current conditions associated with fossil preservation and discovery as predictors. However, combining the outputs from climate-envelope, preservation, and discovery models resulted in the most accurate predictions of potential fossil sites at a continental scale. We proposed potential areas to discover new fossils of Diprotodon, Zygomaturus, Protemnodon, Thylacoleo, and Genyornis, and provide guidelines on how to apply our approach to assist fossil hunting in other continents and geological settings. PMID:27027874

Where to Dig for Fossils: Combining Climate-Envelope, Taphonomy and Discovery Models.

PubMed

Block, Sebastián; Saltré, Frédérik; Rodríguez-Rey, Marta; Fordham, Damien A; Unkel, Ingmar; Bradshaw, Corey J A

2016-01-01

Fossils represent invaluable data to reconstruct the past history of life, yet fossil-rich sites are often rare and difficult to find. The traditional fossil-hunting approach focuses on small areas and has not yet taken advantage of modelling techniques commonly used in ecology to account for an organism's past distributions. We propose a new method to assist finding fossils at continental scales based on modelling the past distribution of species, the geological suitability of fossil preservation and the likelihood of fossil discovery in the field, and apply it to several genera of Australian megafauna that went extinct in the Late Quaternary. Our models predicted higher fossil potentials for independent sites than for randomly selected locations (mean Kolmogorov-Smirnov statistic = 0.66). We demonstrate the utility of accounting for the distribution history of fossil taxa when trying to find the most suitable areas to look for fossils. For some genera, the probability of finding fossils based on simple climate-envelope models was higher than the probability based on models incorporating current conditions associated with fossil preservation and discovery as predictors. However, combining the outputs from climate-envelope, preservation, and discovery models resulted in the most accurate predictions of potential fossil sites at a continental scale. We proposed potential areas to discover new fossils of Diprotodon, Zygomaturus, Protemnodon, Thylacoleo, and Genyornis, and provide guidelines on how to apply our approach to assist fossil hunting in other continents and geological settings.

Simulation of ridesourcing using agent-based demand and supply regional models : potential market demand for first-mile transit travel and reduction in vehicle miles traveled in the San Francisco Bay Area.

DOT National Transportation Integrated Search

2016-01-01

In this study, we use existing modeling tools and data from the San Francisco Bay Area : (California) to understand the potential market demand for a first mile transit access service : and possible reductions in vehicle miles traveled (VMT) (a...

Long-term potential and actual evapotranspiration of two different forests on the Atlantic Coastal Plain

Treesearch

Devendra Amatya; S. Tian; Z. Dai; Ge Sun

2016-01-01

A reliable estimate of potential evapotranspiration (PET) for a forest ecosystem is critical in ecohydrologic modeling related with water supply, vegetation dynamics, and climate change and yet is a challenging task due to its complexity. Based on long-term on-site measured hydro-climatic data and predictions from earlier validated hydrologic modeling studies...

Phenomenological and molecular-level Petri net modeling and simulation of long-term potentiation.

PubMed

Hardy, S; Robillard, P N

2005-10-01

Petri net-based modeling methods have been used in many research projects to represent biological systems. Among these, the hybrid functional Petri net (HFPN) was developed especially for biological modeling in order to provide biologists with a more intuitive Petri net-based method. In the literature, HFPNs are used to represent kinetic models at the molecular level. We present two models of long-term potentiation previously represented by differential equations which we have transformed into HFPN models: a phenomenological synapse model and a molecular-level model of the CaMKII regulation pathway. Through simulation, we obtained results similar to those of previous studies using these models. Our results open the way to a new type of modeling for systems biology where HFPNs are used to combine different levels of abstraction within one model. This approach can be useful in fully modeling a system at the molecular level when kinetic data is missing or when a full study of a system at the molecular level it is not within the scope of the research.

A systematic approach to prioritize drug targets using machine learning, a molecular descriptor-based classification model, and high-throughput screening of plant derived molecules: a case study in oral cancer.

PubMed

Randhawa, Vinay; Kumar Singh, Anil; Acharya, Vishal

2015-12-01

Systems-biology inspired identification of drug targets and machine learning-based screening of small molecules which modulate their activity have the potential to revolutionize modern drug discovery by complementing conventional methods. To utilize the effectiveness of such pipelines, we first analyzed the dysregulated gene pairs between control and tumor samples and then implemented an ensemble-based feature selection approach to prioritize targets in oral squamous cell carcinoma (OSCC) for therapeutic exploration. Based on the structural information of known inhibitors of CXCR4-one of the best targets identified in this study-a feature selection was implemented for the identification of optimal structural features (molecular descriptor) based on which a classification model was generated. Furthermore, the CXCR4-centered descriptor-based classification model was finally utilized to screen a repository of plant derived small-molecules to obtain potential inhibitors. The application of our methodology may assist effective selection of the best targets which may have previously been overlooked, that in turn will lead to the development of new oral cancer medications. The small molecules identified in this study can be ideal candidates for trials as potential novel anti-oral cancer agents. Importantly, distinct steps of this whole study may provide reference for the analysis of other complex human diseases.

A Fully Associative, Non-Linear Kinematic, Unified Viscoplastic Model for Titanium Based Matrices

NASA Technical Reports Server (NTRS)

Arnold, S. M.; Saleeb, A. F.; Castelli, M. G.

1994-01-01

Specific forms for both the Gibb's and complementary dissipation potentials are chosen such that a complete (i.e., fully associative) potential based multiaxial unified viscoplastic model is obtained. This model possesses one tensorial internal state variable that is associated with dislocation substructure, with an evolutionary law that has nonlinear kinematic hardening and both thermal and strain induced recovery mechanisms. A unique aspect of the present model is the inclusion of non-linear hardening through the use of a compliance operator, derived from the Gibb's potential, in the evolution law for the back stress. This non-linear tensorial operator is significant in that it allows both the flow and evolutionary laws to be fully associative (and therefore easily integrated) and greatly influences the multiaxial response under non-proportional loading paths. In addition to this nonlinear compliance operator, a new consistent, potential preserving, internal strain unloading criterion has been introduced to prevent abnormalities in the predicted stress-strain curves, which are present with nonlinear hardening formulations, during unloading and reversed loading of the external variables. Specification of an experimental program for the complete determination of the material functions and parameters for characterizing a metallic matrix, e.g., TIMETAL 21S, is given. The experiments utilized are tensile, creep, and step creep tests. Finally, a comparison of this model and a commonly used Bodner-Partom model is made on the basis of predictive accuracy and numerical efficiency.

Simulations and field observations of root water uptake in plots with different soil water availability.

NASA Astrophysics Data System (ADS)

Cai, Gaochao; Vanderborght, Jan; Couvreur, Valentin; Javaux, Mathieu; Vereecken, Harry

2015-04-01

Root water uptake is a main process in the hydrological cycle and vital for water management in agronomy. In most models of root water uptake, the spatial and temporal soil water status and plant root distributions are required for water flow simulations. However, dynamic root growth and root distributions are not easy and time consuming to measure by normal approaches. Furthermore, root water uptake cannot be measured directly in the field. Therefore, it is necessary to incorporate monitoring data of soil water content and potential and root distributions within a modeling framework to explore the interaction between soil water availability and root water uptake. But, most models are lacking a physically based concept to describe water uptake from soil profiles with vertical variations in soil water availability. In this contribution, we present an experimental setup in which root development, soil water content and soil water potential are monitored non-invasively in two field plots with different soil texture and for three treatments with different soil water availability: natural rain, sheltered and irrigated treatment. Root development is monitored using 7-m long horizontally installed minirhizotubes at six depths with three replicates per treatment. The monitoring data are interpreted using a model that is a one-dimensional upscaled version of root water uptake model that describes flow in the coupled soil-root architecture considering water potential gradients in the system and hydraulic conductances of the soil and root system (Couvreur et al., 2012). This model approach links the total root water uptake to an effective soil water potential in the root zone. The local root water uptake is a function of the difference between the local soil water potential and effective root zone water potential so that compensatory uptake in heterogeneous soil water potential profiles is simulated. The root system conductance is derived from inverse modelling using measurements of soil water potentials, water contents, and root distributions. The results showed that this modelling approach reproduced soil water dynamics well in the different plots and treatments. Root water uptake reduced when the effective soil water potential decreased to around -70 to -100 kPa in the root zone. Couvreur, V., Vanderborght, J., and Javaux, M.: A simple three dimensional macroscopic root water uptake model based on the hydraulic architecture approach, Hydrol. Earth Syst. Sci., 16, 2957-2971, doi:10.5194/hess-16-2957-2012, 2012.

Parameterizing the Morse Potential for Coarse-Grained Modeling of Blood Plasma

PubMed Central

Zhang, Na; Zhang, Peng; Kang, Wei; Bluestein, Danny; Deng, Yuefan

2014-01-01

Multiscale simulations of fluids such as blood represent a major computational challenge of coupling the disparate spatiotemporal scales between molecular and macroscopic transport phenomena characterizing such complex fluids. In this paper, a coarse-grained (CG) particle model is developed for simulating blood flow by modifying the Morse potential, traditionally used in Molecular Dynamics for modeling vibrating structures. The modified Morse potential is parameterized with effective mass scales for reproducing blood viscous flow properties, including density, pressure, viscosity, compressibility and characteristic flow dynamics of human blood plasma fluid. The parameterization follows a standard inverse-problem approach in which the optimal micro parameters are systematically searched, by gradually decoupling loosely correlated parameter spaces, to match the macro physical quantities of viscous blood flow. The predictions of this particle based multiscale model compare favorably to classic viscous flow solutions such as Counter-Poiseuille and Couette flows. It demonstrates that such coarse grained particle model can be applied to replicate the dynamics of viscous blood flow, with the advantage of bridging the gap between macroscopic flow scales and the cellular scales characterizing blood flow that continuum based models fail to handle adequately. PMID:24910470

From creatures of habit to goal-directed learners: Tracking the developmental emergence of model-based reinforcement learning

PubMed Central

Decker, Johannes H.; Otto, A. Ross; Daw, Nathaniel D.; Hartley, Catherine A.

2016-01-01

Theoretical models distinguish two decision-making strategies that have been formalized in reinforcement-learning theory. A model-based strategy leverages a cognitive model of potential actions and their consequences to make goal-directed choices, whereas a model-free strategy evaluates actions based solely on their reward history. Research in adults has begun to elucidate the psychological mechanisms and neural substrates underlying these learning processes and factors that influence their relative recruitment. However, the developmental trajectory of these evaluative strategies has not been well characterized. In this study, children, adolescents, and adults, performed a sequential reinforcement-learning task that enables estimation of model-based and model-free contributions to choice. Whereas a model-free strategy was evident in choice behavior across all age groups, evidence of a model-based strategy only emerged during adolescence and continued to increase into adulthood. These results suggest that recruitment of model-based valuation systems represents a critical cognitive component underlying the gradual maturation of goal-directed behavior. PMID:27084852

The relation between degree-2160 spectral models of Earth's gravitational and topographic potential: a guide on global correlation measures and their dependency on approximation effects

NASA Astrophysics Data System (ADS)

Hirt, Christian; Rexer, Moritz; Claessens, Sten; Rummel, Reiner

2017-10-01

Comparisons between high-degree models of the Earth's topographic and gravitational potential may give insight into the quality and resolution of the source data sets, provide feedback on the modelling techniques and help to better understand the gravity field composition. Degree correlations (cross-correlation coefficients) or reduction rates (quantifying the amount of topographic signal contained in the gravitational potential) are indicators used in a number of contemporary studies. However, depending on the modelling techniques and underlying levels of approximation, the correlation at high degrees may vary significantly, as do the conclusions drawn. The present paper addresses this problem by attempting to provide a guide on global correlation measures with particular emphasis on approximation effects and variants of topographic potential modelling. We investigate and discuss the impact of different effects (e.g., truncation of series expansions of the topographic potential, mass compression, ellipsoidal versus spherical approximation, ellipsoidal harmonic coefficient versus spherical harmonic coefficient (SHC) representation) on correlation measures. Our study demonstrates that the correlation coefficients are realistic only when the model's harmonic coefficients of a given degree are largely independent of the coefficients of other degrees, permitting degree-wise evaluations. This is the case, e.g., when both models are represented in terms of SHCs and spherical approximation (i.e. spherical arrangement of field-generating masses). Alternatively, a representation in ellipsoidal harmonics can be combined with ellipsoidal approximation. The usual ellipsoidal approximation level (i.e. ellipsoidal mass arrangement) is shown to bias correlation coefficients when SHCs are used. Importantly, gravity models from the International Centre for Global Earth Models (ICGEM) are inherently based on this approximation level. A transformation is presented that enables a transformation of ICGEM geopotential models from ellipsoidal to spherical approximation. The transformation is applied to generate a spherical transform of EGM2008 (sphEGM2008) that can meaningfully be correlated degree-wise with the topographic potential. We exploit this new technique and compare a number of models of topographic potential constituents (e.g., potential implied by land topography, ocean water masses) based on the Earth2014 global relief model and a mass-layer forward modelling technique with sphEGM2008. Different to previous findings, our results show very significant short-scale correlation between Earth's gravitational potential and the potential generated by Earth's land topography (correlation +0.92, and 60% of EGM2008 signals are delivered through the forward modelling). Our tests reveal that the potential generated by Earth's oceans water masses is largely unrelated to the geopotential at short scales, suggesting that altimetry-derived gravity and/or bathymetric data sets are significantly underpowered at 5 arc-min scales. We further decompose the topographic potential into the Bouguer shell and terrain correction and show that they are responsible for about 20 and 25% of EGM2008 short-scale signals, respectively. As a general conclusion, the paper shows the importance of using compatible models in topographic/gravitational potential comparisons and recommends the use of SHCs together with spherical approximation or EHCs with ellipsoidal approximation in order to avoid biases in the correlation measures.

Forward and Inverse Modeling of Self-potential. A Tomography of Groundwater Flow and Comparison Between Deterministic and Stochastic Inversion Methods

NASA Astrophysics Data System (ADS)

Quintero-Chavarria, E.; Ochoa Gutierrez, L. H.

2016-12-01

Applications of the Self-potential Method in the fields of Hydrogeology and Environmental Sciences have had significant developments during the last two decades with a strong use on groundwater flows identification. Although only few authors deal with the forward problem's solution -especially in geophysics literature- different inversion procedures are currently being developed but in most cases they are compared with unconventional groundwater velocity fields and restricted to structured meshes. This research solves the forward problem based on the finite element method using the St. Venant's Principle to transform a point dipole, which is the field generated by a single vector, into a distribution of electrical monopoles. Then, two simple aquifer models were generated with specific boundary conditions and head potentials, velocity fields and electric potentials in the medium were computed. With the model's surface electric potential, the inverse problem is solved to retrieve the source of electric potential (vector field associated to groundwater flow) using deterministic and stochastic approaches. The first approach was carried out by implementing a Tikhonov regularization with a stabilized operator adapted to the finite element mesh while for the second a hierarchical Bayesian model based on Markov chain Monte Carlo (McMC) and Markov Random Fields (MRF) was constructed. For all implemented methods, the result between the direct and inverse models was contrasted in two ways: 1) shape and distribution of the vector field, and 2) magnitude's histogram. Finally, it was concluded that inversion procedures are improved when the velocity field's behavior is considered, thus, the deterministic method is more suitable for unconfined aquifers than confined ones. McMC has restricted applications and requires a lot of information (particularly in potentials fields) while MRF has a remarkable response especially when dealing with confined aquifers.

Comparison of Modeling Approaches to Prioritize Chemicals Based on Estimates of Exposure and Exposure Potential

EPA Science Inventory

While only limited data are available to characterize the potential toxicity of over 8 million commercially available chemical substances, there is even less information available on the exposure and use-scenarios that are required to link potential toxicity to human and ecologic...

Efficient computation of electrograms and ECGs in human whole heart simulations using a reaction-eikonal model.

PubMed

Neic, Aurel; Campos, Fernando O; Prassl, Anton J; Niederer, Steven A; Bishop, Martin J; Vigmond, Edward J; Plank, Gernot

2017-10-01

Anatomically accurate and biophysically detailed bidomain models of the human heart have proven a powerful tool for gaining quantitative insight into the links between electrical sources in the myocardium and the concomitant current flow in the surrounding medium as they represent their relationship mechanistically based on first principles. Such models are increasingly considered as a clinical research tool with the perspective of being used, ultimately, as a complementary diagnostic modality. An important prerequisite in many clinical modeling applications is the ability of models to faithfully replicate potential maps and electrograms recorded from a given patient. However, while the personalization of electrophysiology models based on the gold standard bidomain formulation is in principle feasible, the associated computational expenses are significant, rendering their use incompatible with clinical time frames. In this study we report on the development of a novel computationally efficient reaction-eikonal (R-E) model for modeling extracellular potential maps and electrograms. Using a biventricular human electrophysiology model, which incorporates a topologically realistic His-Purkinje system (HPS), we demonstrate by comparing against a high-resolution reaction-diffusion (R-D) bidomain model that the R-E model predicts extracellular potential fields, electrograms as well as ECGs at the body surface with high fidelity and offers vast computational savings greater than three orders of magnitude. Due to their efficiency R-E models are ideally suitable for forward simulations in clinical modeling studies which attempt to personalize electrophysiological model features.

Efficient computation of electrograms and ECGs in human whole heart simulations using a reaction-eikonal model

NASA Astrophysics Data System (ADS)

Neic, Aurel; Campos, Fernando O.; Prassl, Anton J.; Niederer, Steven A.; Bishop, Martin J.; Vigmond, Edward J.; Plank, Gernot

2017-10-01

Anatomically accurate and biophysically detailed bidomain models of the human heart have proven a powerful tool for gaining quantitative insight into the links between electrical sources in the myocardium and the concomitant current flow in the surrounding medium as they represent their relationship mechanistically based on first principles. Such models are increasingly considered as a clinical research tool with the perspective of being used, ultimately, as a complementary diagnostic modality. An important prerequisite in many clinical modeling applications is the ability of models to faithfully replicate potential maps and electrograms recorded from a given patient. However, while the personalization of electrophysiology models based on the gold standard bidomain formulation is in principle feasible, the associated computational expenses are significant, rendering their use incompatible with clinical time frames. In this study we report on the development of a novel computationally efficient reaction-eikonal (R-E) model for modeling extracellular potential maps and electrograms. Using a biventricular human electrophysiology model, which incorporates a topologically realistic His-Purkinje system (HPS), we demonstrate by comparing against a high-resolution reaction-diffusion (R-D) bidomain model that the R-E model predicts extracellular potential fields, electrograms as well as ECGs at the body surface with high fidelity and offers vast computational savings greater than three orders of magnitude. Due to their efficiency R-E models are ideally suitable for forward simulations in clinical modeling studies which attempt to personalize electrophysiological model features.

Factors Affecting Utilization of Information Output of Computer-Based Modeling Procedures in Local Government Organizations.

ERIC Educational Resources Information Center

Komsky, Susan

Fiscal Impact Budgeting Systems (FIBS) are sophisticated computer based modeling procedures used in local government organizations, whose results, however, are often overlooked or ignored by decision makers. A study attempted to discover the reasons for this situation by focusing on four factors: potential usefulness, faith in computers,…

A sediment graph model based on SCS-CN method

NASA Astrophysics Data System (ADS)

Singh, P. K.; Bhunya, P. K.; Mishra, S. K.; Chaube, U. C.

2008-01-01

SummaryThis paper proposes new conceptual sediment graph models based on coupling of popular and extensively used methods, viz., Nash model based instantaneous unit sediment graph (IUSG), soil conservation service curve number (SCS-CN) method, and Power law. These models vary in their complexity and this paper tests their performance using data of the Nagwan watershed (area = 92.46 km 2) (India). The sensitivity of total sediment yield and peak sediment flow rate computations to model parameterisation is analysed. The exponent of the Power law, β, is more sensitive than other model parameters. The models are found to have substantial potential for computing sediment graphs (temporal sediment flow rate distribution) as well as total sediment yield.

Estimation of inlet flow rates for image-based aneurysm CFD models: where and how to begin?

PubMed

Valen-Sendstad, Kristian; Piccinelli, Marina; KrishnankuttyRema, Resmi; Steinman, David A

2015-06-01

Patient-specific flow rates are rarely available for image-based computational fluid dynamics models. Instead, flow rates are often assumed to scale according to the diameters of the arteries of interest. Our goal was to determine how choice of inlet location and scaling law affect such model-based estimation of inflow rates. We focused on 37 internal carotid artery (ICA) aneurysm cases from the Aneurisk cohort. An average ICA flow rate of 245 mL min(-1) was assumed from the literature, and then rescaled for each case according to its inlet diameter squared (assuming a fixed velocity) or cubed (assuming a fixed wall shear stress). Scaling was based on diameters measured at various consistent anatomical locations along the models. Choice of location introduced a modest 17% average uncertainty in model-based flow rate, but within individual cases estimated flow rates could vary by >100 mL min(-1). A square law was found to be more consistent with physiological flow rates than a cube law. Although impact of parent artery truncation on downstream flow patterns is well studied, our study highlights a more insidious and potentially equal impact of truncation site and scaling law on the uncertainty of assumed inlet flow rates and thus, potentially, downstream flow patterns.

Strengthening community participation in reducing GHG emission from forest and peatland fire

NASA Astrophysics Data System (ADS)

Thoha, A. S.; Saharjo, B. H.; Boer, R.; Ardiansyah, M.

2018-02-01

Strengthening community participation is needed to find solutions to encourage community more participate in reducing Green House Gas (GHG) from forest and peatland fire. This research aimed to identify stakeholders that have the role in forest and peatland fire control and to formulate strengthening model of community participation through community-based early warning fire. Stakeholder mapping and action research were used to determine stakeholders that had potential influence and interest and to formulate strengthening model of community participation in reducing GHG from forest and peatland fire. There was found that position of key players in the mapping of stakeholders came from the government institution. The existence of community-based fire control group can strengthen government institution through collaborating with stakeholders having strong interest and influence. Moreover, it was found several local knowledge in Kapuas District about how communities predict drought that have potential value for developing the community-based early warning fire system. Formulated institutional model in this research also can be further developed as a model institution in the preservation of natural resources based on local knowledge. In conclusion, local knowledge and community-based fire groups can be integrated within strengthening model of community participation in reducing GHG from forest and peatland fire.

A stochastic bioenergetics model based approach to translating large river flow and temperature in to fish population responses: The pallid sturgeon example

USGS Publications Warehouse

Wildhaber, Mark L.; Dey, Rima; Wikle, Christopher K.; Moran, Edward H.; Anderson, Christopher J.; Franz, Kristie J.

2015-01-01

In managing fish populations, especially at-risk species, realistic mathematical models are needed to help predict population response to potential management actions in the context of environmental conditions and changing climate while effectively incorporating the stochastic nature of real world conditions. We provide a key component of such a model for the endangered pallid sturgeon (Scaphirhynchus albus) in the form of an individual-based bioenergetics model influenced not only by temperature but also by flow. This component is based on modification of a known individual-based bioenergetics model through incorporation of: the observed ontogenetic shift in pallid sturgeon diet from marcroinvertebrates to fish; the energetic costs of swimming under flowing-water conditions; and stochasticity. We provide an assessment of how differences in environmental conditions could potentially alter pallid sturgeon growth estimates, using observed temperature and velocity from channelized portions of the Lower Missouri River mainstem. We do this using separate relationships between the proportion of maximum consumption and fork length and swimming cost standard error estimates for fish captured above and below the Kansas River in the Lower Missouri River. Critical to our matching observed growth in the field with predicted growth based on observed environmental conditions was a two-step shift in diet from macroinvertebrates to fish.

Source-to-Outcome Microbial Exposure and Risk Modeling Framework

EPA Science Inventory

A Quantitative Microbial Risk Assessment (QMRA) is a computer-based data-delivery and modeling approach that integrates interdisciplinary fate/transport, exposure, and impact models and databases to characterize potential health impacts/risks due to pathogens. As such, a QMRA ex...

Language Model Applications to Spelling with Brain-Computer Interfaces

PubMed Central

Mora-Cortes, Anderson; Manyakov, Nikolay V.; Chumerin, Nikolay; Van Hulle, Marc M.

2014-01-01

Within the Ambient Assisted Living (AAL) community, Brain-Computer Interfaces (BCIs) have raised great hopes as they provide alternative communication means for persons with disabilities bypassing the need for speech and other motor activities. Although significant advancements have been realized in the last decade, applications of language models (e.g., word prediction, completion) have only recently started to appear in BCI systems. The main goal of this article is to review the language model applications that supplement non-invasive BCI-based communication systems by discussing their potential and limitations, and to discern future trends. First, a brief overview of the most prominent BCI spelling systems is given, followed by an in-depth discussion of the language models applied to them. These language models are classified according to their functionality in the context of BCI-based spelling: the static/dynamic nature of the user interface, the use of error correction and predictive spelling, and the potential to improve their classification performance by using language models. To conclude, the review offers an overview of the advantages and challenges when implementing language models in BCI-based communication systems when implemented in conjunction with other AAL technologies. PMID:24675760

Cheminformatics-aided pharmacovigilance: application to Stevens-Johnson Syndrome

PubMed Central

Low, Yen S; Caster, Ola; Bergvall, Tomas; Fourches, Denis; Zang, Xiaoling; Norén, G Niklas; Rusyn, Ivan; Edwards, Ralph

2016-01-01

Objective Quantitative Structure-Activity Relationship (QSAR) models can predict adverse drug reactions (ADRs), and thus provide early warnings of potential hazards. Timely identification of potential safety concerns could protect patients and aid early diagnosis of ADRs among the exposed. Our objective was to determine whether global spontaneous reporting patterns might allow chemical substructures associated with Stevens-Johnson Syndrome (SJS) to be identified and utilized for ADR prediction by QSAR models. Materials and Methods Using a reference set of 364 drugs having positive or negative reporting correlations with SJS in the VigiBase global repository of individual case safety reports (Uppsala Monitoring Center, Uppsala, Sweden), chemical descriptors were computed from drug molecular structures. Random Forest and Support Vector Machines methods were used to develop QSAR models, which were validated by external 5-fold cross validation. Models were employed for virtual screening of DrugBank to predict SJS actives and inactives, which were corroborated using knowledge bases like VigiBase, ChemoText, and MicroMedex (Truven Health Analytics Inc, Ann Arbor, Michigan). Results We developed QSAR models that could accurately predict if drugs were associated with SJS (area under the curve of 75%–81%). Our 10 most active and inactive predictions were substantiated by SJS reports (or lack thereof) in the literature. Discussion Interpretation of QSAR models in terms of significant chemical descriptors suggested novel SJS structural alerts. Conclusions We have demonstrated that QSAR models can accurately identify SJS active and inactive drugs. Requiring chemical structures only, QSAR models provide effective computational means to flag potentially harmful drugs for subsequent targeted surveillance and pharmacoepidemiologic investigations. PMID:26499102

Linking MODFLOW with an agent-based land-use model to support decision making

USGS Publications Warehouse

Reeves, H.W.; Zellner, M.L.

2010-01-01

The U.S. Geological Survey numerical groundwater flow model, MODFLOW, was integrated with an agent-based land-use model to yield a simulator for environmental planning studies. Ultimately, this integrated simulator will be used as a means to organize information, illustrate potential system responses, and facilitate communication within a participatory modeling framework. Initial results show the potential system response to different zoning policy scenarios in terms of the spatial patterns of development, which is referred to as urban form, and consequent impacts on groundwater levels. These results illustrate how the integrated simulator is capable of representing the complexity of the system. From a groundwater modeling perspective, the most important aspect of the integration is that the simulator generates stresses on the groundwater system within the simulation in contrast to the traditional approach that requires the user to specify the stresses through time. Copyright ?? 2010 The Author(s). Journal compilation ?? 2010 National Ground Water Association.

Modeling Human Exposure to Indoor Contaminants: External Source to Body Tissues.

PubMed

Webster, Eva M; Qian, Hua; Mackay, Donald; Christensen, Rebecca D; Tietjen, Britta; Zaleski, Rosemary

2016-08-16

Information on human indoor exposure is necessary to assess the potential risk to individuals from many chemicals of interest. Dynamic indoor and human physicologically based pharmacokinetic (PBPK) models of the distribution of nonionizing, organic chemical concentrations in indoor environments resulting in delivered tissue doses are developed, described and tested. The Indoor model successfully reproduced independently measured, reported time-dependent air concentrations of chloroform released during showering and of 2-butyoxyethanol following use of a volatile surface cleaner. The Indoor model predictions were also comparable to those from a higher tier consumer model (ConsExpo 4.1) for the surface cleaner scenario. The PBPK model successful reproduced observed chloroform exhaled air concentrations resulting from an inhalation exposure. Fugacity based modeling provided a seamless description of the partitioning, fluxes, accumulation and release of the chemical in indoor media and tissues of the exposed subject. This has the potential to assist in health risk assessments, provided that appropriate physical/chemical property, usage characteristics, and toxicological information are available.

Assessing the hydropower potential of ungauged watersheds in Iceland using hydrological modeling and satellite retrieved snow cover images

NASA Astrophysics Data System (ADS)

Finger, David

2015-04-01

About 80% of the domestic energy production in Iceland comes from renewable energies. Hydropower accounts for about 20% this production, representing about 75% of the total electricity production in Iceland. In 2008 total electricity production from hydropower was about 12.5 TWh a-1, making Iceland a worldwide leader in hydropower production per capita. Furthermore, the total potential of hydroelectricity in Iceland is estimated to amount up to 220 TWh a-1. In this regard, hydrological modelling is an essential tool to adapt a sustainable management of water resources and estimate the potential of possible new sites for hydropower production. We used the conceptual lumped Hydrologiska Byråns Vattenbalansavdelning model (HBV) to estimate the potential of hydropower production in two remote areas in north-eastern Iceland (Leirdalshraun, a 274 km2 area above 595 m asl and Hafralónsá, a 946 km2 area above 235 m asl). The model parameters were determined by calibrating the model with discharge data from gauged sub catchments. Satellite snow cover images were used to constrain melt parameters of the model and assure adequate modelling of snow melt in the ungauged areas. This was particularly valuable to adequately estimate the contribution of snow melt, rainfall runoff and groundwater intrusion from glaciers outside the topographic boundaries of the selected watersheds. Runoff from the entire area potentially used for hydropower exploitation was estimated using the parameter sets of the gauged sub-catchments. Additionally, snow melt from the ungauged areas was validated with satellite based snow cover images, revealing a robust simulation of snow melt in the entire area. Based on the hydrological modelling the total amount of snow melt and rainfall runoff available in Leirdalshraun and Hafralónsá amounts up to 700 M m3 a-1 and 1000 M m3 a-1, respectively. These results reveal that the total hydropower potential of the two sites amounts up to 1.2 TWh a-1 hydroelectricity, accounting for about 10% of the current production in Iceland. These result are of eminent importance to embed sustainable and resilient based water management in discussions concerning future plans of national energy production.

Relativistic optical model on the basis of the Moscow potential and lower phase shifts for nucleon-nucleon scattering at laboratory energies of up to 3 GeV

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

Knyr, V. A.; Neudatchin, V. G.; Khokhlov, N. A.

Data of a partial-wave analysis of nucleon-nucleon scattering at energies of up to E{sub lab} = 3 GeV (lower partial waves) and the properties of the deuteron are described within the relativistic optical model based on deep attractive quasipotentials involving forbidden states (as exemplified by the Moscow potential). Partial-wave potentials are derived by the inverse-scattering-problem method based on the Marchenko equation by using present-day data from the partial-wave analysis of nucleon-nucleon scattering at energies of up to 3 GeV. Channel coupling is taken into account. The imaginary parts of the potentials are deduced from the phase equation of the variable-phasemore » approach. The general situation around the manifestation of quark effects in nucleon-nucleon interaction is discussed.« less

Integrating geospatial and ground geophysical information as guidelines for groundwater potential zones in hard rock terrains of south India.

PubMed

Rashid, Mehnaz; Lone, Mahjoor Ahmad; Ahmed, Shakeel

2012-08-01

The increasing demand of water has brought tremendous pressure on groundwater resources in the regions were groundwater is prime source of water. The objective of this study was to explore groundwater potential zones in Maheshwaram watershed of Andhra Pradesh, India with semi-arid climatic condition and hard rock granitic terrain. GIS-based modelling was used to integrate remote sensing and geophysical data to delineate groundwater potential zones. In the present study, Indian Remote Sensing RESOURCESAT-1, Linear Imaging Self-Scanner (LISS-4) digital data, ASTER digital elevation model and vertical electrical sounding data along with other data sets were analysed to generate various thematic maps, viz., geomorphology, land use/land cover, geology, lineament density, soil, drainage density, slope, aquifer resistivity and aquifer thickness. Based on this integrated approach, the groundwater availability in the watershed was classified into four categories, viz. very good, good, moderate and poor. The results reveal that the modelling assessment method proposed in this study is an effective tool for deciphering groundwater potential zones for proper planning and management of groundwater resources in diverse hydrogeological terrains.

Computational Modeling of Single Neuron Extracellular Electric Potentials and Network Local Field Potentials using LFPsim.

PubMed

Parasuram, Harilal; Nair, Bipin; D'Angelo, Egidio; Hines, Michael; Naldi, Giovanni; Diwakar, Shyam

2016-01-01

Local Field Potentials (LFPs) are population signals generated by complex spatiotemporal interaction of current sources and dipoles. Mathematical computations of LFPs allow the study of circuit functions and dysfunctions via simulations. This paper introduces LFPsim, a NEURON-based tool for computing population LFP activity and single neuron extracellular potentials. LFPsim was developed to be used on existing cable compartmental neuron and network models. Point source, line source, and RC based filter approximations can be used to compute extracellular activity. As a demonstration of efficient implementation, we showcase LFPs from mathematical models of electrotonically compact cerebellum granule neurons and morphologically complex neurons of the neocortical column. LFPsim reproduced neocortical LFP at 8, 32, and 56 Hz via current injection, in vitro post-synaptic N2a, N2b waves and in vivo T-C waves in cerebellum granular layer. LFPsim also includes a simulation of multi-electrode array of LFPs in network populations to aid computational inference between biophysical activity in neural networks and corresponding multi-unit activity resulting in extracellular and evoked LFP signals.

Dietary Exposure Potential Model

EPA Science Inventory

Existing food consumption and contaminant residue databases, typically products of nutrition and regulatory monitoring, contain useful information to characterize dietary intake of environmental chemicals. A PC-based model with resident database system, termed the Die...

Graphic comparison of reserve-growth models for conventional oil and accumulation

USGS Publications Warehouse

Klett, T.R.

2003-01-01

The U.S. Geological Survey (USGS) periodically assesses crude oil, natural gas, and natural gas liquids resources of the world. The assessment procedure requires estimated recover-able oil and natural gas volumes (field size, cumulative production plus remaining reserves) in discovered fields. Because initial reserves are typically conservative, subsequent estimates increase through time as these fields are developed and produced. The USGS assessment of petroleum resources makes estimates, or forecasts, of the potential additions to reserves in discovered oil and gas fields resulting from field development, and it also estimates the potential fully developed sizes of undiscovered fields. The term ?reserve growth? refers to the commonly observed upward adjustment of reserve estimates. Because such additions are related to increases in the total size of a field, the USGS uses field sizes to model reserve growth. Future reserve growth in existing fields is a major component of remaining U.S. oil and natural gas resources and has therefore become a necessary element of U.S. petroleum resource assessments. Past and currently proposed reserve-growth models compared herein aid in the selection of a suitable set of forecast functions to provide an estimate of potential additions to reserves from reserve growth in the ongoing National Oil and Gas Assessment Project (NOGA). Reserve growth is modeled by construction of a curve that represents annual fractional changes of recoverable oil and natural gas volumes (for fields and reservoirs), which provides growth factors. Growth factors are used to calculate forecast functions, which are sets of field- or reservoir-size multipliers. Comparisons of forecast functions were made based on datasets used to construct the models, field type, modeling method, and length of forecast span. Comparisons were also made between forecast functions based on field-level and reservoir- level growth, and between forecast functions based on older and newer data. The reserve-growth model used in the 1995 USGS National Assessment and the model currently used in the NOGA project provide forecast functions that yield similar estimates of potential additions to reserves. Both models are based on the Oil and Gas Integrated Field File from the Energy Information Administration (EIA), but different vintages of data (from 1977 through 1991 and 1977 through 1996, respectively). The model based on newer data can be used in place of the previous model, providing similar estimates of potential additions to reserves. Fore-cast functions for oil fields vary little from those for gas fields in these models; therefore, a single function may be used for both oil and gas fields, like that used in the USGS World Petroleum Assessment 2000. Forecast functions based on the field-level reserve growth model derived from the NRG Associates databases (from 1982 through 1998) differ from those derived from EIA databases (from 1977 through 1996). However, the difference may not be enough to preclude the use of the forecast functions derived from NRG data in place of the forecast functions derived from EIA data. Should the model derived from NRG data be used, separate forecast functions for oil fields and gas fields must be employed. The forecast function for oil fields from the model derived from NRG data varies significantly from that for gas fields, and a single function for both oil and gas fields may not be appropriate.

Forecasting an invasive species’ distribution with global distribution data, local data, and physiological information

USGS Publications Warehouse

Jarnevich, Catherine S.; Young, Nicholas E.; Talbert, Marian; Talbert, Colin

2018-01-01

Understanding invasive species distributions and potential invasions often requires broad‐scale information on the environmental tolerances of the species. Further, resource managers are often faced with knowing these broad‐scale relationships as well as nuanced environmental factors related to their landscape that influence where an invasive species occurs and potentially could occur. Using invasive buffelgrass (Cenchrus ciliaris), we developed global models and local models for Saguaro National Park, Arizona, USA, based on location records and literature on physiological tolerances to environmental factors to investigate whether environmental relationships of a species at a global scale are also important at local scales. In addition to correlative models with five commonly used algorithms, we also developed a model using a priori user‐defined relationships between occurrence and environmental characteristics based on a literature review. All correlative models at both scales performed well based on statistical evaluations. The user‐defined curves closely matched those produced by the correlative models, indicating that the correlative models may be capturing mechanisms driving the distribution of buffelgrass. Given climate projections for the region, both global and local models indicate that conditions at Saguaro National Park may become more suitable for buffelgrass. Combining global and local data with correlative models and physiological information provided a holistic approach to forecasting invasive species distributions.

SHEDS-HT: An Integrated Probabilistic Exposure Model for ...

EPA Pesticide Factsheets

United States Environmental Protection Agency (USEPA) researchers are developing a strategy for highthroughput (HT) exposure-based prioritization of chemicals under the ExpoCast program. These novel modeling approaches for evaluating chemicals based on their potential for biologically relevant human exposures will inform toxicity testing and prioritization for chemical risk assessment. Based on probabilistic methods and algorithms developed for The Stochastic Human Exposure and Dose Simulation Model for Multimedia, Multipathway Chemicals (SHEDS-MM), a new mechanistic modeling approach has been developed to accommodate high-throughput (HT) assessment of exposure potential. In this SHEDS-HT model, the residential and dietary modules of SHEDS-MM have been operationally modified to reduce the user burden, input data demands, and run times of the higher-tier model, while maintaining critical features and inputs that influence exposure. The model has been implemented in R; the modeling framework links chemicals to consumer product categories or food groups (and thus exposure scenarios) to predict HT exposures and intake doses. Initially, SHEDS-HT has been applied to 2507 organic chemicals associated with consumer products and agricultural pesticides. These evaluations employ data from recent USEPA efforts to characterize usage (prevalence, frequency, and magnitude), chemical composition, and exposure scenarios for a wide range of consumer products. In modeling indirec

Chemical structure-based predictive model for methanogenic anaerobic biodegradation potential.

PubMed

Meylan, William; Boethling, Robert; Aronson, Dallas; Howard, Philip; Tunkel, Jay

2007-09-01

Many screening-level models exist for predicting aerobic biodegradation potential from chemical structure, but anaerobic biodegradation generally has been ignored by modelers. We used a fragment contribution approach to develop a model for predicting biodegradation potential under methanogenic anaerobic conditions. The new model has 37 fragments (substructures) and classifies a substance as either fast or slow, relative to the potential to be biodegraded in the "serum bottle" anaerobic biodegradation screening test (Organization for Economic Cooperation and Development Guideline 311). The model correctly classified 90, 77, and 91% of the chemicals in the training set (n = 169) and two independent validation sets (n = 35 and 23), respectively. Accuracy of predictions of fast and slow degradation was equal for training-set chemicals, but fast-degradation predictions were less accurate than slow-degradation predictions for the validation sets. Analysis of the signs of the fragment coefficients for this and the other (aerobic) Biowin models suggests that in the context of simple group contribution models, the majority of positive and negative structural influences on ultimate degradation are the same for aerobic and methanogenic anaerobic biodegradation.

A quantum perturbative pair distribution for determining interatomic potentials from extended x-ray absorption spectroscopy

NASA Astrophysics Data System (ADS)

Piazza, F.

2002-11-01

In this paper we develop a technique for determining interatomic potentials in materials in the quantum regime from single-shell extended x-ray absorption spectroscopy (EXAFS) spectra. We introduce a pair distribution function, based on ordinary quantum time-independent perturbation theory. In the proposed scheme, the model potential parameters enter the distribution through a fourth-order Taylor expansion of the potential, and are directly refined in the fit of the model signal to the experimental spectrum. We discuss in general the validity of our theoretical framework, namely the quantum regime and perturbative treatment, and work out a simple tool for monitoring the sensitivity of our theory in determining lattice anharmonicities based on the statistical F-test. As an example, we apply our formalism to an EXAFS spectrum at the Ag K edge of AgI at T = 77 K. We determine the Ag-I potential parameters and find good agreement with previous studies.

Linking sediment-charcoal records and ecological modeling to understand causes of fire-regime change in boreal forests

Treesearch

Linda B. Brubaker; Philip E. Higuera; T. Scott Rupp; Mark A. Olson; Patricia M. Anderson; Feng Sheng. Hu

2009-01-01

Interactions between vegetation and fire have the potential to overshadow direct effects of climate change on fire regimes in boreal forests of North America. We develop methods to compare sediment-charcoal records with fire regimes simulated by an ecological model, ALFRESCO (Alaskan Frame-based Ecosystem Code) and apply these methods to evaluate potential causes of a...

From Models to Measurements: Comparing Downed Dead Wood Carbon Stock Estimates in the U.S. Forest Inventory

PubMed Central

Domke, Grant M.; Woodall, Christopher W.; Walters, Brian F.; Smith, James E.

2013-01-01

The inventory and monitoring of coarse woody debris (CWD) carbon (C) stocks is an essential component of any comprehensive National Greenhouse Gas Inventory (NGHGI). Due to the expense and difficulty associated with conducting field inventories of CWD pools, CWD C stocks are often modeled as a function of more commonly measured stand attributes such as live tree C density. In order to assess potential benefits of adopting a field-based inventory of CWD C stocks in lieu of the current model-based approach, a national inventory of downed dead wood C across the U.S. was compared to estimates calculated from models associated with the U.S.’s NGHGI and used in the USDA Forest Service, Forest Inventory and Analysis program. The model-based population estimate of C stocks for CWD (i.e., pieces and slash piles) in the conterminous U.S. was 9 percent (145.1 Tg) greater than the field-based estimate. The relatively small absolute difference was driven by contrasting results for each CWD component. The model-based population estimate of C stocks from CWD pieces was 17 percent (230.3 Tg) greater than the field-based estimate, while the model-based estimate of C stocks from CWD slash piles was 27 percent (85.2 Tg) smaller than the field-based estimate. In general, models overestimated the C density per-unit-area from slash piles early in stand development and underestimated the C density from CWD pieces in young stands. This resulted in significant differences in CWD C stocks by region and ownership. The disparity in estimates across spatial scales illustrates the complexity in estimating CWD C in a NGHGI. Based on the results of this study, it is suggested that the U.S. adopt field-based estimates of CWD C stocks as a component of its NGHGI to both reduce the uncertainty within the inventory and improve the sensitivity to potential management and climate change events. PMID:23544112

From models to measurements: comparing downed dead wood carbon stock estimates in the U.S. forest inventory.

PubMed

Domke, Grant M; Woodall, Christopher W; Walters, Brian F; Smith, James E

2013-01-01

The inventory and monitoring of coarse woody debris (CWD) carbon (C) stocks is an essential component of any comprehensive National Greenhouse Gas Inventory (NGHGI). Due to the expense and difficulty associated with conducting field inventories of CWD pools, CWD C stocks are often modeled as a function of more commonly measured stand attributes such as live tree C density. In order to assess potential benefits of adopting a field-based inventory of CWD C stocks in lieu of the current model-based approach, a national inventory of downed dead wood C across the U.S. was compared to estimates calculated from models associated with the U.S.'s NGHGI and used in the USDA Forest Service, Forest Inventory and Analysis program. The model-based population estimate of C stocks for CWD (i.e., pieces and slash piles) in the conterminous U.S. was 9 percent (145.1 Tg) greater than the field-based estimate. The relatively small absolute difference was driven by contrasting results for each CWD component. The model-based population estimate of C stocks from CWD pieces was 17 percent (230.3 Tg) greater than the field-based estimate, while the model-based estimate of C stocks from CWD slash piles was 27 percent (85.2 Tg) smaller than the field-based estimate. In general, models overestimated the C density per-unit-area from slash piles early in stand development and underestimated the C density from CWD pieces in young stands. This resulted in significant differences in CWD C stocks by region and ownership. The disparity in estimates across spatial scales illustrates the complexity in estimating CWD C in a NGHGI. Based on the results of this study, it is suggested that the U.S. adopt field-based estimates of CWD C stocks as a component of its NGHGI to both reduce the uncertainty within the inventory and improve the sensitivity to potential management and climate change events.

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

Yu, Hong, E-mail: h-yu@seu.edu.cn; Chen, Hong-Bo

In this article, a new semi-continuum model is built to describe the fundamental vibration frequency of the silicon nanowires in <111> orientation. The Keating potential model and the discrete nature in the width and the thickness direction of the silicon nanowires in <111> orientation are applied in the new semi-continuum model. Based on the Keating model and the principle of conservation of energy, the vibration frequency of the silicon nanowires with the triangle, the rhombus, and the hexagon cross sections are derived. It is indicated that the calculation results based on this new model are accordant with the simulation resultsmore » of the software based on molecular dynamics (MD).« less

Smart grid initialization reduces the computational complexity of multi-objective image registration based on a dual-dynamic transformation model to account for large anatomical differences

NASA Astrophysics Data System (ADS)

Bosman, Peter A. N.; Alderliesten, Tanja

2016-03-01

We recently demonstrated the strong potential of using dual-dynamic transformation models when tackling deformable image registration problems involving large anatomical differences. Dual-dynamic transformation models employ two moving grids instead of the common single moving grid for the target image (and single fixed grid for the source image). We previously employed powerful optimization algorithms to make use of the additional flexibility offered by a dual-dynamic transformation model with good results, directly obtaining insight into the trade-off between important registration objectives as a result of taking a multi-objective approach to optimization. However, optimization has so far been initialized using two regular grids, which still leaves a great potential of dual-dynamic transformation models untapped: a-priori grid alignment with image structures/areas that are expected to deform more. This allows (far) less grid points to be used, compared to using a sufficiently refined regular grid, leading to (far) more efficient optimization, or, equivalently, more accurate results using the same number of grid points. We study the implications of exploiting this potential by experimenting with two new smart grid initialization procedures: one manual expert-based and one automated image-feature-based. We consider a CT test case with large differences in bladder volume with and without a multi-resolution scheme and find a substantial benefit of using smart grid initialization.

Two-body potential model based on cosine series expansion for ionic materials

DOE PAGES

Oda, Takuji; Weber, William J.; Tanigawa, Hisashi

2015-09-23

There is a method to construct a two-body potential model for ionic materials with a Fourier series basis and we examine it. For this method, the coefficients of cosine basis functions are uniquely determined by solving simultaneous linear equations to minimize the sum of weighted mean square errors in energy, force and stress, where first-principles calculation results are used as the reference data. As a validation test of the method, potential models for magnesium oxide are constructed. The mean square errors appropriately converge with respect to the truncation of the cosine series. This result mathematically indicates that the constructed potentialmore » model is sufficiently close to the one that is achieved with the non-truncated Fourier series and demonstrates that this potential virtually provides minimum error from the reference data within the two-body representation. The constructed potential models work appropriately in both molecular statics and dynamics simulations, especially if a two-step correction to revise errors expected in the reference data is performed, and the models clearly outperform two existing Buckingham potential models that were tested. Moreover, the good agreement over a broad range of energies and forces with first-principles calculations should enable the prediction of materials behavior away from equilibrium conditions, such as a system under irradiation.« less

Obesity prevention: Comparison of techniques and potential solution

NASA Astrophysics Data System (ADS)

Zulkepli, Jafri; Abidin, Norhaslinda Zainal; Zaibidi, Nerda Zura

2014-12-01

Over the years, obesity prevention has been a broadly studied subject by both academicians and practitioners. It is one of the most serious public health issue as it can cause numerous chronic health and psychosocial problems. Research is needed to suggest a population-based strategy for obesity prevention. In the academic environment, the importance of obesity prevention has triggered various problem solving approaches. A good obesity prevention model, should comprehend and cater all complex and dynamics issues. Hence, the main purpose of this paper is to discuss the qualitative and quantitative approaches on obesity prevention study and to provide an extensive literature review on various recent modelling techniques for obesity prevention. Based on these literatures, the comparison of both quantitative and qualitative approahes are highlighted and the justification on the used of system dynamics technique to solve the population of obesity is discussed. Lastly, a potential framework solution based on system dynamics modelling is proposed.

Risk estimates for CO exposure in man based on behavioral and physiological responses in rodents

NASA Technical Reports Server (NTRS)

Gross, M. K.

1983-01-01

An examination of animal response to CO is studied along with potential models for extrapolating animal test data to humans. The best models for extrapolating data were found to be the Probit and Weibull models.

GIS-Based Suitability Model for Assessment of Forest Biomass Energy Potential in a Region of Portugal

NASA Astrophysics Data System (ADS)

Quinta-Nova, Luis; Fernandez, Paulo; Pedro, Nuno

2017-12-01

This work focuses on developed a decision support system based on multicriteria spatial analysis to assess the potential for generation of biomass residues from forestry sources in a region of Portugal (Beira Baixa). A set of environmental, economic and social criteria was defined, evaluated and weighted in the context of Saaty’s analytic hierarchies. The best alternatives were obtained after applying Analytic Hierarchy Process (AHP). The model was applied to the central region of Portugal where forest and agriculture are the most representative land uses. Finally, sensitivity analysis of the set of factors and their associated weights was performed to test the robustness of the model. The proposed evaluation model provides a valuable reference for decision makers in establishing a standardized means of selecting the optimal location for new biomass plants.

Agent based modeling of the effects of potential treatments over the blood-brain barrier in multiple sclerosis.

PubMed

Pennisi, Marzio; Russo, Giulia; Motta, Santo; Pappalardo, Francesco

2015-12-01

Multiple sclerosis is a disease of the central nervous system that involves the destruction of the insulating sheath of axons, causing severe disabilities. Since the etiology of the disease is not yet fully understood, the use of novel techniques that may help to understand the disease, to suggest potential therapies and to test the effects of candidate treatments is highly advisable. To this end we developed an agent based model that demonstrated its ability to reproduce the typical oscillatory behavior observed in the most common form of multiple sclerosis, relapsing-remitting multiple sclerosis. The model has then been used to test the potential beneficial effects of vitamin D over the disease. Many scientific studies underlined the importance of the blood-brain barrier and of the mechanisms that influence its permeability on the development of the disease. In the present paper we further extend our previously developed model with a mechanism that mimics the blood-brain barrier behavior. The goal of our work is to suggest the best strategies to follow for developing new potential treatments that intervene in the blood-brain barrier. Results suggest that the best treatments should potentially prevent the opening of the blood-brain barrier, as treatments that help in recovering the blood-brain barrier functionality could be less effective. Copyright © 2015 Elsevier B.V. All rights reserved.

Properties of a Formal Method to Model Emergence in Swarm-Based Systems

NASA Technical Reports Server (NTRS)

Rouff, Christopher; Vanderbilt, Amy; Truszkowski, Walt; Rash, James; Hinchey, Mike

2004-01-01

Future space missions will require cooperation between multiple satellites and/or rovers. Developers are proposing intelligent autonomous swarms for these missions, but swarm-based systems are difficult or impossible to test with current techniques. This viewgraph presentation examines the use of formal methods in testing swarm-based systems. The potential usefulness of formal methods in modeling the ANTS asteroid encounter mission is also examined.

The impact of surface area, volume, curvature, and Lennard-Jones potential to solvation modeling.

PubMed

Nguyen, Duc D; Wei, Guo-Wei

2017-01-05

This article explores the impact of surface area, volume, curvature, and Lennard-Jones (LJ) potential on solvation free energy predictions. Rigidity surfaces are utilized to generate robust analytical expressions for maximum, minimum, mean, and Gaussian curvatures of solvent-solute interfaces, and define a generalized Poisson-Boltzmann (GPB) equation with a smooth dielectric profile. Extensive correlation analysis is performed to examine the linear dependence of surface area, surface enclosed volume, maximum curvature, minimum curvature, mean curvature, and Gaussian curvature for solvation modeling. It is found that surface area and surfaces enclosed volumes are highly correlated to each other's, and poorly correlated to various curvatures for six test sets of molecules. Different curvatures are weakly correlated to each other for six test sets of molecules, but are strongly correlated to each other within each test set of molecules. Based on correlation analysis, we construct twenty six nontrivial nonpolar solvation models. Our numerical results reveal that the LJ potential plays a vital role in nonpolar solvation modeling, especially for molecules involving strong van der Waals interactions. It is found that curvatures are at least as important as surface area or surface enclosed volume in nonpolar solvation modeling. In conjugation with the GPB model, various curvature-based nonpolar solvation models are shown to offer some of the best solvation free energy predictions for a wide range of test sets. For example, root mean square errors from a model constituting surface area, volume, mean curvature, and LJ potential are less than 0.42 kcal/mol for all test sets. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Global height datum unification: a new approach in gravity potential space

NASA Astrophysics Data System (ADS)

Ardalan, A. A.; Safari, A.

2005-12-01

The problem of “global height datum unification” is solved in the gravity potential space based on: (1) high-resolution local gravity field modeling, (2) geocentric coordinates of the reference benchmark, and (3) a known value of the geoid’s potential. The high-resolution local gravity field model is derived based on a solution of the fixed-free two-boundary-value problem of the Earth’s gravity field using (a) potential difference values (from precise leveling), (b) modulus of the gravity vector (from gravimetry), (c) astronomical longitude and latitude (from geodetic astronomy and/or combination of (GNSS) Global Navigation Satellite System observations with total station measurements), (d) and satellite altimetry. Knowing the height of the reference benchmark in the national height system and its geocentric GNSS coordinates, and using the derived high-resolution local gravity field model, the gravity potential value of the zero point of the height system is computed. The difference between the derived gravity potential value of the zero point of the height system and the geoid’s potential value is computed. This potential difference gives the offset of the zero point of the height system from geoid in the “potential space”, which is transferred into “geometry space” using the transformation formula derived in this paper. The method was applied to the computation of the offset of the zero point of the Iranian height datum from the geoid’s potential value W 0=62636855.8 m2/s2. According to the geometry space computations, the height datum of Iran is 0.09 m below the geoid.

New Estimates of Land Use Intensity of Potential Bioethanol Production in the U.S.A.

NASA Astrophysics Data System (ADS)

Kheshgi, H. S.; Song, Y.; Torkamani, S.; Jain, A. K.

2016-12-01

We estimate potential bioethanol land use intensity (the inverse of potential bioethanol yield per hectare) across the United States by modeling crop yields and conversion to bioethanol (via a fermentation pathway), based on crop field studies and conversion technology analyses. We apply the process-based land surface model, the Integrated Science Assessment model (ISAM), to estimate the potential yield of four crops - corn, Miscanthus, and two variants of switchgrass (Cave-in-Rock and Alamo) - across the U.S.A. landscape for the 14-year period from 1999 through 2012, for the case with fertilizer application but without irrigation. We estimate bioethanol yield based on recent experience for corn bioethanol production from corn kernel, and current cellulosic bioethanol process design specifications under the assumption of the maximum practical harvest fraction for the energy grasses (Miscanthus and switchgrasses) and a moderate (30%) harvest fraction of corn stover. We find that each of four crops included has regions where that crop is estimated to have the lowest land use intensity (highest potential bioethanol yield per hectare). We find that minimizing potential land use intensity by including both corn and the energy grasses only improves incrementally to that of corn (using both harvested kernel and stover for bioethanol). Bioethanol land use intensity is one fundamental factor influencing the desirability of biofuels, but is not the only one; others factors include economics, competition with food production and land use, water and climate, nitrogen runoff, life-cycle emissions, and the pace of crop and technology improvement into the future.

[GSH fermentation process modeling using entropy-criterion based RBF neural network model].

PubMed

Tan, Zuoping; Wang, Shitong; Deng, Zhaohong; Du, Guocheng

2008-05-01

The prediction accuracy and generalization of GSH fermentation process modeling are often deteriorated by noise existing in the corresponding experimental data. In order to avoid this problem, we present a novel RBF neural network modeling approach based on entropy criterion. It considers the whole distribution structure of the training data set in the parameter learning process compared with the traditional MSE-criterion based parameter learning, and thus effectively avoids the weak generalization and over-learning. Then the proposed approach is applied to the GSH fermentation process modeling. Our results demonstrate that this proposed method has better prediction accuracy, generalization and robustness such that it offers a potential application merit for the GSH fermentation process modeling.

Study of lithium cation in water clusters: based on atom-bond electronegativity equalization method fused into molecular mechanics.

PubMed

Li, Xin; Yang, Zhong-Zhi

2005-05-12

We present a potential model for Li(+)-water clusters based on a combination of the atom-bond electronegativity equalization and molecular mechanics (ABEEM/MM) that is to take ABEEM charges of the cation and all atoms, bonds, and lone pairs of water molecules into the intermolecular electrostatic interaction term in molecular mechanics. The model allows point charges on cationic site and seven sites of an ABEEM-7P water molecule to fluctuate responding to the cluster geometry. The water molecules in the first sphere of Li(+) are strongly structured and there is obvious charge transfer between the cation and the water molecules; therefore, the charge constraint on the ionic cluster includes the charged constraint on the Li(+) and the first-shell water molecules and the charge neutrality constraint on each water molecule in the external hydration shells. The newly constructed potential model based on ABEEM/MM is first applied to ionic clusters and reproduces gas-phase state properties of Li(+)(H(2)O)(n) (n = 1-6 and 8) including optimized geometries, ABEEM charges, binding energies, frequencies, and so on, which are in fair agreement with those measured by available experiments and calculated by ab initio methods. Prospects and benefits introduced by this potential model are pointed out.

Action-Based Dynamical Modelling For The Milky Way Disk

NASA Astrophysics Data System (ADS)

Trick, Wilma; Rix, Hans-Walter; Bovy, Jo

2016-09-01

We present Road Mapping, a full-likelihood dynamical modelling machinery, that aims to recover the Milky Way's (MW) gravitational potential from large samples of stars in the Galactic disk. Road Mapping models the observed positions and velocities of stars with a parameterized, action-based distribution function (DF) in a parameterized axisymmetric gravitational potential (Binney & McMillan 2011, Binney 2012, Bovy & Rix 2013).In anticipation of the Gaia data release in autumn, we have fully tested Road Mapping and demonstrated its robustness against the breakdown of its assumptions.Using large suites of mock data, we investigated in isolated test cases how the modelling would be affected if the data's true potential or DF was not included in the families of potentials and DFs assumed by Road Mapping, or if we misjudged measurement errors or the spatial selection function (SF) (Trick et al., submitted to ApJ). We found that the potential can be robustly recovered — given the limitations of the assumed potential model—, even for minor misjudgments in DF or SF, or for proper motion errors or distances known to within 10%.We were also able to demonstrate that Road Mapping is still successful if the strong assumption of axisymmetric breaks down (Trick et al., in preparation). Data drawn from a highresolution simulation (D'Onghia et al. 2013) of a MW-like galaxy with pronounced spiral arms does neither follow the assumed simple DF, nor does it come from an axisymmetric potential. We found that as long as the survey volume is large enough, Road Mapping gives good average constraints on the galaxy's potential.We are planning to apply Road Mapping to a real data set — the Tycho-2 catalogue (Hog et al. 2000) —very soon, and might be able to present some preliminary results already at the conference.

Modeled Changes in Potential Grassland Productivity and in Grass-Fed Ruminant Livestock Density in Europe over 1961-2010.

PubMed

Chang, Jinfeng; Viovy, Nicolas; Vuichard, Nicolas; Ciais, Philippe; Campioli, Matteo; Klumpp, Katja; Martin, Raphaël; Leip, Adrian; Soussana, Jean-François

2015-01-01

About 25% of European livestock intake is based on permanent and sown grasslands. To fulfill rising demand for animal products, an intensification of livestock production may lead to an increased consumption of crop and compound feeds. In order to preserve an economically and environmentally sustainable agriculture, a more forage based livestock alimentation may be an advantage. However, besides management, grassland productivity is highly vulnerable to climate (i.e., temperature, precipitation, CO2 concentration), and spatial information about European grassland productivity in response to climate change is scarce. The process-based vegetation model ORCHIDEE-GM, containing an explicit representation of grassland management (i.e., herbage mowing and grazing), is used here to estimate changes in potential productivity and potential grass-fed ruminant livestock density across European grasslands over the period 1961-2010. Here "potential grass-fed ruminant livestock density" denotes the maximum density of livestock that can be supported by grassland productivity in each 25 km × 25 km grid cell. In reality, livestock density could be higher than potential (e.g., if additional feed is supplied to animals) or lower (e.g., in response to economic factors, pedo-climatic and biotic conditions ignored by the model, or policy decisions that can for instance reduce livestock numbers). When compared to agricultural statistics (Eurostat and FAOstat), ORCHIDEE-GM gave a good reproduction of the regional gradients of annual grassland productivity and ruminant livestock density. The model however tends to systematically overestimate the absolute values of productivity in most regions, suggesting that most grid cells remain below their potential grassland productivity due to possible nutrient and biotic limitations on plant growth. When ORCHIDEE-GM was run for the period 1961-2010 with variable climate and rising CO2, an increase of potential annual production (over 3%) per decade was found: 97% of this increase was attributed to the rise in CO2, -3% to climate trends and 15% to trends in nitrogen fertilization and deposition. When compared with statistical data, ORCHIDEE-GM captures well the observed phase of climate-driven interannual variability in grassland production well, whereas the magnitude of the interannual variability in modeled productivity is larger than the statistical data. Regional grass-fed livestock numbers can be reproduced by ORCHIDEE-GM based on its simple assumptions and parameterization about productivity being the only limiting factor to define the sustainable number of animals per unit area. Causes for regional model-data misfits are discussed, including uncertainties in farming practices (e.g., nitrogen fertilizer application, and mowing and grazing intensity) and in ruminant diet composition, as well as uncertainties in the statistical data and in model parameter values.

Modeled Changes in Potential Grassland Productivity and in Grass-Fed Ruminant Livestock Density in Europe over 1961–2010

PubMed Central

Chang, Jinfeng; Viovy, Nicolas; Vuichard, Nicolas; Ciais, Philippe; Campioli, Matteo; Klumpp, Katja; Martin, Raphaël; Leip, Adrian; Soussana, Jean-François

2015-01-01

About 25% of European livestock intake is based on permanent and sown grasslands. To fulfill rising demand for animal products, an intensification of livestock production may lead to an increased consumption of crop and compound feeds. In order to preserve an economically and environmentally sustainable agriculture, a more forage based livestock alimentation may be an advantage. However, besides management, grassland productivity is highly vulnerable to climate (i.e., temperature, precipitation, CO2 concentration), and spatial information about European grassland productivity in response to climate change is scarce. The process-based vegetation model ORCHIDEE-GM, containing an explicit representation of grassland management (i.e., herbage mowing and grazing), is used here to estimate changes in potential productivity and potential grass-fed ruminant livestock density across European grasslands over the period 1961–2010. Here “potential grass-fed ruminant livestock density” denotes the maximum density of livestock that can be supported by grassland productivity in each 25 km × 25 km grid cell. In reality, livestock density could be higher than potential (e.g., if additional feed is supplied to animals) or lower (e.g., in response to economic factors, pedo-climatic and biotic conditions ignored by the model, or policy decisions that can for instance reduce livestock numbers). When compared to agricultural statistics (Eurostat and FAOstat), ORCHIDEE-GM gave a good reproduction of the regional gradients of annual grassland productivity and ruminant livestock density. The model however tends to systematically overestimate the absolute values of productivity in most regions, suggesting that most grid cells remain below their potential grassland productivity due to possible nutrient and biotic limitations on plant growth. When ORCHIDEE-GM was run for the period 1961–2010 with variable climate and rising CO2, an increase of potential annual production (over 3%) per decade was found: 97% of this increase was attributed to the rise in CO2, -3% to climate trends and 15% to trends in nitrogen fertilization and deposition. When compared with statistical data, ORCHIDEE-GM captures well the observed phase of climate-driven interannual variability in grassland production well, whereas the magnitude of the interannual variability in modeled productivity is larger than the statistical data. Regional grass-fed livestock numbers can be reproduced by ORCHIDEE-GM based on its simple assumptions and parameterization about productivity being the only limiting factor to define the sustainable number of animals per unit area. Causes for regional model-data misfits are discussed, including uncertainties in farming practices (e.g., nitrogen fertilizer application, and mowing and grazing intensity) and in ruminant diet composition, as well as uncertainties in the statistical data and in model parameter values. PMID:26018186

Wildfire potential mapping over the state of Mississippi: A land surface modeling approach

Treesearch

William H. Cooke; Georgy V. Mostovoy; Valentine G. Anantharaj; W. Matt Jolly

2012-01-01

A relationship between the likelihood of wildfires and various drought metrics (soil moisture-based fire potential indices) were examined over the southern part of Mississippi. The following three indices were tested and used to simulate spatial and temporal wildfire probability changes: (1) the accumulated difference between daily precipitation and potential...

First principles molecular dynamics of molten NaCl

NASA Astrophysics Data System (ADS)

Galamba, N.; Costa Cabral, B. J.

2007-03-01

First principles Hellmann-Feynman molecular dynamics (HFMD) results for molten NaCl at a single state point are reported. The effect of induction forces on the structure and dynamics of the system is studied by comparison of the partial radial distribution functions and the velocity and force autocorrelation functions with those calculated from classical MD based on rigid-ion and shell-model potentials. The first principles results reproduce the main structural features of the molten salt observed experimentally, whereas they are incorrectly described by both rigid-ion and shell-model potentials. Moreover, HFMD Green-Kubo self-diffusion coefficients are in closer agreement with experimental data than those predicted by classical MD. A comprehensive discussion of MD results for molten NaCl based on different ab initio parametrized polarizable interionic potentials is also given.

Neural Energy Supply-Consumption Properties Based on Hodgkin-Huxley Model

PubMed Central

2017-01-01

Electrical activity is the foundation of the neural system. Coding theories that describe neural electrical activity by the roles of action potential timing or frequency have been thoroughly studied. However, an alternative method to study coding questions is the energy method, which is more global and economical. In this study, we clearly defined and calculated neural energy supply and consumption based on the Hodgkin-Huxley model, during firing action potentials and subthreshold activities using ion-counting and power-integral model. Furthermore, we analyzed energy properties of each ion channel and found that, under the two circumstances, power synchronization of ion channels and energy utilization ratio have significant differences. This is particularly true of the energy utilization ratio, which can rise to above 100% during subthreshold activity, revealing an overdraft property of energy use. These findings demonstrate the distinct status of the energy properties during neuronal firings and subthreshold activities. Meanwhile, after introducing a synapse energy model, this research can be generalized to energy calculation of a neural network. This is potentially important for understanding the relationship between dynamical network activities and cognitive behaviors. PMID:28316842

Second virial coefficient of a generalized Lennard-Jones potential.

PubMed

González-Calderón, Alfredo; Rocha-Ichante, Adrián

2015-01-21

We present an exact analytical solution for the second virial coefficient of a generalized Lennard-Jones type of pair potential model. The potential can be reduced to the Lennard-Jones, hard-sphere, and sticky hard-sphere models by tuning the potential parameters corresponding to the width and depth of the well. Thus, the second virial solution can also regain the aforementioned cases. Moreover, the obtained expression strongly resembles the one corresponding to the Kihara potential. In fact, the Fk functions are the same. Furthermore, for these functions, the complete expansions at low and high temperature are given. Additionally, we propose an alternative stickiness parameter based on the obtained second virial coefficient.

A temperature-dependent physiologically based model for the invasive apple snail Pomacea canaliculata

NASA Astrophysics Data System (ADS)

Gilioli, Gianni; Pasquali, Sara; Martín, Pablo R.; Carlsson, Nils; Mariani, Luigi

2017-11-01

In order to set priorities in management of costly and ecosystem-damaging species, policymakers and managers need accurate predictions not only about where a specific invader may establish but also about its potential abundance at different geographical scales. This is because density or biomass per unit area of an invasive species is a key predictor of the magnitude of environmental and economic impact in the invaded habitat. Here, we present a physiologically based demographic model describing and explaining the population dynamics of a widespread freshwater invader, the golden apple snail Pomacea canaliculata, which is causing severe environmental and economic impacts in invaded wetlands and rice fields in Southeastern Asia and has also been introduced to North America and Europe . The model is based on bio-demographic functions for mortality, development and fecundity rates that are driven by water temperature for the aquatic stages (juveniles and adults) and by air temperature for the aerial egg masses. Our model has been validated against data on the current distribution in South America and Japan, and produced consistent and realistic patterns of reproduction, growth, maturation and mortality under different scenarios in accordance to what is known from real P. canaliculata populations in different regions and climates. The model further shows that P. canaliculata will use two different reproductive strategies (semelparity and iteroparity) within the potential area of establishment, a plasticity that may explain the high invasiveness of this species across a wide range of habitats with different climates. Our results also suggest that densities, and thus the magnitude of environmental and agricultural damage, will be largely different in locations with distinct climatic regimes within the potential area of establishment. We suggest that physiologically based demographic modelling of invasive species will become a valuable tool for invasive species managers.

A quantum wave based compact modeling approach for the current in ultra-short DG MOSFETs suitable for rapid multi-scale simulations

NASA Astrophysics Data System (ADS)

Hosenfeld, Fabian; Horst, Fabian; Iñíguez, Benjamín; Lime, François; Kloes, Alexander

2017-11-01

Source-to-drain (SD) tunneling decreases the device performance in MOSFETs falling below the 10 nm channel length. Modeling quantum mechanical effects including SD tunneling has gained more importance specially for compact model developers. The non-equilibrium Green's function (NEGF) has become a state-of-the-art method for nano-scaled device simulation in the past years. In the sense of a multi-scale simulation approach it is necessary to bridge the gap between compact models with their fast and efficient calculation of the device current, and numerical device models which consider quantum effects of nano-scaled devices. In this work, an NEGF based analytical model for nano-scaled double-gate (DG) MOSFETs is introduced. The model consists of a closed-form potential solution of a classical compact model and a 1D NEGF formalism for calculating the device current, taking into account quantum mechanical effects. The potential calculation omits the iterative coupling and allows the straightforward current calculation. The model is based on a ballistic NEGF approach whereby backscattering effects are considered as second order effect in a closed-form. The accuracy and scalability of the non-iterative DG MOSFET model is inspected in comparison with numerical NanoMOS TCAD data for various channel lengths. With the help of this model investigations on short-channel and temperature effects are performed.

Agent-based assessment of stormwater re-use potential of low-impact development control facilities at the site of Vlasina Lake, Serbia.

PubMed

Blagojević, Borislava; Milićević, Dragan; Potić, Olivera

2013-01-01

Vlasina Lake in south-east Serbia is classified as an Area of Distinct Land Use and, as such, is subject to high environmental protection standards applied in the Master Plan. Two open channels for stormwater and sediment transportation to two large detention basins with pumping stations for water evacuation into the lake were envisaged in the Master Plan. In the preliminary design, the stormwater system was quite different: wherever possible, on-site natural features were used for allocation of ponds, and drainage channels were led through existing road culverts. The applied design concept has been low impact development (LID), which led to potential blue-green corridors, recognized by project stakeholders. The paper studies the possibility of using ponds as a key element of both the LID concept and the blue-green corridors approach. For that purpose, an initial Vlasina Lake site agent-based simulation model has been created. A realistic physical model is included, and simulation results for two hypothetical climatic and socio-economic scenarios are presented. From the experience in creating the agent-based model, and based on the simulation results, recommendations are given for further work. It is shown that ponds have potential for the investigated water re-use purposes.

Nutrigenomics-based personalised nutritional advice: in search of a business model?

PubMed

Ronteltap, Amber; van Trijp, Hans; Berezowska, Aleksandra; Goossens, Jo

2013-03-01

Nutritional advice has mainly focused on population-level recommendations. Recent developments in nutrition, communication, and marketing sciences have enabled potential deviations from this dominant business model in the direction of personalisation of nutrition advice. Such personalisation efforts can take on many forms, but these have in common that they can only be effective if they are supported by a viable business model. The present paper takes an inventory of approaches to personalised nutrition currently available in the market place as its starting point to arrive at an identification of their underlying business models. This analysis is presented as a unifying framework against which the potential of nutrigenomics-based personalised advice can be assessed. It has uncovered nine archetypical approaches to personalised nutrition advice in terms of their dominant underlying business models. Differentiating features among such business models are the type of information that is used as a basis for personalisation, the definition of the target group, the communication channels that are being adopted, and the partnerships that are built as a part of the business model. Future research should explore the consumer responses to the diversity of "archetypical" business models for personalised nutrition advice as a source of market information on which the delivery of nutrigenomics-based personalised nutrition advice may further build.

Gay-Berne and electrostatic multipole based coarse-grain potential in implicit solvent

NASA Astrophysics Data System (ADS)

Wu, Johnny; Zhen, Xia; Shen, Hujun; Li, Guohui; Ren, Pengyu

2011-10-01

A general, transferable coarse-grain (CG) framework based on the Gay-Berne potential and electrostatic point multipole expansion is presented for polypeptide simulations. The solvent effect is described by the Generalized Kirkwood theory. The CG model is calibrated using the results of all-atom simulations of model compounds in solution. Instead of matching the overall effective forces produced by atomic models, the fundamental intermolecular forces such as electrostatic, repulsion-dispersion, and solvation are represented explicitly at a CG level. We demonstrate that the CG alanine dipeptide model is able to reproduce quantitatively the conformational energy of all-atom force fields in both gas and solution phases, including the electrostatic and solvation components. Replica exchange molecular dynamics and microsecond dynamic simulations of polyalanine of 5 and 12 residues reveal that the CG polyalanines fold into "alpha helix" and "beta sheet" structures. The 5-residue polyalanine displays a substantial increase in the "beta strand" fraction relative to the 12-residue polyalanine. The detailed conformational distribution is compared with those reported from recent all-atom simulations and experiments. The results suggest that the new coarse-graining approach presented in this study has the potential to offer both accuracy and efficiency for biomolecular modeling.

Human iPSC-derived cardiomyocytes and tissue engineering strategies for disease modeling and drug screening.

PubMed

Smith, Alec S T; Macadangdang, Jesse; Leung, Winnie; Laflamme, Michael A; Kim, Deok-Ho

Improved methodologies for modeling cardiac disease phenotypes and accurately screening the efficacy and toxicity of potential therapeutic compounds are actively being sought to advance drug development and improve disease modeling capabilities. To that end, much recent effort has been devoted to the development of novel engineered biomimetic cardiac tissue platforms that accurately recapitulate the structure and function of the human myocardium. Within the field of cardiac engineering, induced pluripotent stem cells (iPSCs) are an exciting tool that offer the potential to advance the current state of the art, as they are derived from somatic cells, enabling the development of personalized medical strategies and patient specific disease models. Here we review different aspects of iPSC-based cardiac engineering technologies. We highlight methods for producing iPSC-derived cardiomyocytes (iPSC-CMs) and discuss their application to compound efficacy/toxicity screening and in vitro modeling of prevalent cardiac diseases. Special attention is paid to the application of micro- and nano-engineering techniques for the development of novel iPSC-CM based platforms and their potential to advance current preclinical screening modalities. Published by Elsevier Inc.

Predictive models reduce talent development costs in female gymnastics.

PubMed

Pion, Johan; Hohmann, Andreas; Liu, Tianbiao; Lenoir, Matthieu; Segers, Veerle

2017-04-01

This retrospective study focuses on the comparison of different predictive models based on the results of a talent identification test battery for female gymnasts. We studied to what extent these models have the potential to optimise selection procedures, and at the same time reduce talent development costs in female artistic gymnastics. The dropout rate of 243 female elite gymnasts was investigated, 5 years past talent selection, using linear (discriminant analysis) and non-linear predictive models (Kohonen feature maps and multilayer perceptron). The coaches classified 51.9% of the participants correct. Discriminant analysis improved the correct classification to 71.6% while the non-linear technique of Kohonen feature maps reached 73.7% correctness. Application of the multilayer perceptron even classified 79.8% of the gymnasts correctly. The combination of different predictive models for talent selection can avoid deselection of high-potential female gymnasts. The selection procedure based upon the different statistical analyses results in decrease of 33.3% of cost because the pool of selected athletes can be reduced to 92 instead of 138 gymnasts (as selected by the coaches). Reduction of the costs allows the limited resources to be fully invested in the high-potential athletes.

Automated Decomposition of Model-based Learning Problems

NASA Technical Reports Server (NTRS)

Williams, Brian C.; Millar, Bill

1996-01-01

A new generation of sensor rich, massively distributed autonomous systems is being developed that has the potential for unprecedented performance, such as smart buildings, reconfigurable factories, adaptive traffic systems and remote earth ecosystem monitoring. To achieve high performance these massive systems will need to accurately model themselves and their environment from sensor information. Accomplishing this on a grand scale requires automating the art of large-scale modeling. This paper presents a formalization of [\\em decompositional model-based learning (DML)], a method developed by observing a modeler's expertise at decomposing large scale model estimation tasks. The method exploits a striking analogy between learning and consistency-based diagnosis. Moriarty, an implementation of DML, has been applied to thermal modeling of a smart building, demonstrating a significant improvement in learning rate.

High Throughput Exposure Prioritization of Chemicals Using a Screening-Level Probabilistic SHEDS-Lite Exposure Model

EPA Science Inventory

These novel modeling approaches for screening, evaluating and classifying chemicals based on the potential for biologically-relevant human exposures will inform toxicity testing and prioritization for chemical risk assessment. The new modeling approach is derived from the Stocha...

Simple agrometeorological models for estimating Guineagrass yield in Southeast Brazil.

PubMed

Pezzopane, José Ricardo Macedo; da Cruz, Pedro Gomes; Santos, Patricia Menezes; Bosi, Cristiam; de Araujo, Leandro Coelho

2014-09-01

The objective of this work was to develop and evaluate agrometeorological models to simulate the production of Guineagrass. For this purpose, we used forage yield from 54 growing periods between December 2004-January 2007 and April 2010-March 2012 in irrigated and non-irrigated pastures in São Carlos, São Paulo state, Brazil (latitude 21°57'42″ S, longitude 47°50'28″ W and altitude 860 m). Initially we performed linear regressions between the agrometeorological variables and the average dry matter accumulation rate for irrigated conditions. Then we determined the effect of soil water availability on the relative forage yield considering irrigated and non-irrigated pastures, by means of segmented linear regression among water balance and relative production variables (dry matter accumulation rates with and without irrigation). The models generated were evaluated with independent data related to 21 growing periods without irrigation in the same location, from eight growing periods in 2000 and 13 growing periods between December 2004-January 2007 and April 2010-March 2012. The results obtained show the satisfactory predictive capacity of the agrometeorological models under irrigated conditions based on univariate regression (mean temperature, minimum temperature and potential evapotranspiration or degreedays) or multivariate regression. The response of irrigation on production was well correlated with the climatological water balance variables (ratio between actual and potential evapotranspiration or between actual and maximum soil water storage). The models that performed best for estimating Guineagrass yield without irrigation were based on minimum temperature corrected by relative soil water storage, determined by the ratio between the actual soil water storage and the soil water holding capacity.irrigation in the same location, in 2000, 2010 and 2011. The results obtained show the satisfactory predictive capacity of the agrometeorological models under irrigated conditions based on univariate regression (mean temperature, potential evapotranspiration or degree-days) or multivariate regression. The response of irrigation on production was well correlated with the climatological water balance variables (ratio between actual and potential evapotranspiration or between actual and maximum soil water storage). The models that performed best for estimating Guineagrass yield without irrigation were based on degree-days corrected by the water deficit factor.

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

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

Simulation of Nonisothermal Consolidation of Saturated Soils Based on a Thermodynamic Model

PubMed Central

Cheng, Xiaohui

2013-01-01

Based on the nonequilibrium thermodynamics, a thermo-hydro-mechanical coupling model for saturated soils is established, including a constitutive model without such concepts as yield surface and flow rule. An elastic potential energy density function is defined to derive a hyperelastic relation among the effective stress, the elastic strain, and the dry density. The classical linear non-equilibrium thermodynamic theory is employed to quantitatively describe the unrecoverable energy processes like the nonelastic deformation development in materials by the concepts of dissipative force and dissipative flow. In particular the granular fluctuation, which represents the kinetic energy fluctuation and elastic potential energy fluctuation at particulate scale caused by the irregular mutual movement between particles, is introduced in the model and described by the concept of granular entropy. Using this model, the nonisothermal consolidation of saturated clays under cyclic thermal loadings is simulated in this paper to validate the model. The results show that the nonisothermal consolidation is heavily OCR dependent and unrecoverable. PMID:23983623

Minding the Cyber-Physical Gap: Model-Based Analysis and Mitigation of Systemic Perception-Induced Failure.

PubMed

Mordecai, Yaniv; Dori, Dov

2017-07-17

The cyber-physical gap (CPG) is the difference between the 'real' state of the world and the way the system perceives it. This discrepancy often stems from the limitations of sensing and data collection technologies and capabilities, and is inevitable at some degree in any cyber-physical system (CPS). Ignoring or misrepresenting such limitations during system modeling, specification, design, and analysis can potentially result in systemic misconceptions, disrupted functionality and performance, system failure, severe damage, and potential detrimental impacts on the system and its environment. We propose CPG-Aware Modeling & Engineering (CPGAME), a conceptual model-based approach to capturing, explaining, and mitigating the CPG. CPGAME enhances the systems engineer's ability to cope with CPGs, mitigate them by design, and prevent erroneous decisions and actions. We demonstrate CPGAME by applying it for modeling and analysis of the 1979 Three Miles Island 2 nuclear accident, and show how its meltdown could be mitigated. We use ISO-19450:2015-Object Process Methodology as our conceptual modeling framework.

Simulation of nonisothermal consolidation of saturated soils based on a thermodynamic model.

PubMed

Zhang, Zhichao; Cheng, Xiaohui

2013-01-01

Based on the nonequilibrium thermodynamics, a thermo-hydro-mechanical coupling model for saturated soils is established, including a constitutive model without such concepts as yield surface and flow rule. An elastic potential energy density function is defined to derive a hyperelastic relation among the effective stress, the elastic strain, and the dry density. The classical linear non-equilibrium thermodynamic theory is employed to quantitatively describe the unrecoverable energy processes like the nonelastic deformation development in materials by the concepts of dissipative force and dissipative flow. In particular the granular fluctuation, which represents the kinetic energy fluctuation and elastic potential energy fluctuation at particulate scale caused by the irregular mutual movement between particles, is introduced in the model and described by the concept of granular entropy. Using this model, the nonisothermal consolidation of saturated clays under cyclic thermal loadings is simulated in this paper to validate the model. The results show that the nonisothermal consolidation is heavily OCR dependent and unrecoverable.

Photovoltaic Grid-Connected Modeling and Characterization Based on Experimental Results.

PubMed

Humada, Ali M; Hojabri, Mojgan; Sulaiman, Mohd Herwan Bin; Hamada, Hussein M; Ahmed, Mushtaq N

2016-01-01

A grid-connected photovoltaic (PV) system operates under fluctuated weather condition has been modeled and characterized based on specific test bed. A mathematical model of a small-scale PV system has been developed mainly for residential usage, and the potential results have been simulated. The proposed PV model based on three PV parameters, which are the photocurrent, IL, the reverse diode saturation current, Io, the ideality factor of diode, n. Accuracy of the proposed model and its parameters evaluated based on different benchmarks. The results showed that the proposed model fitting the experimental results with high accuracy compare to the other models, as well as the I-V characteristic curve. The results of this study can be considered valuable in terms of the installation of a grid-connected PV system in fluctuated climatic conditions.

Photovoltaic Grid-Connected Modeling and Characterization Based on Experimental Results

PubMed Central

Humada, Ali M.; Hojabri, Mojgan; Sulaiman, Mohd Herwan Bin; Hamada, Hussein M.; Ahmed, Mushtaq N.

2016-01-01

A grid-connected photovoltaic (PV) system operates under fluctuated weather condition has been modeled and characterized based on specific test bed. A mathematical model of a small-scale PV system has been developed mainly for residential usage, and the potential results have been simulated. The proposed PV model based on three PV parameters, which are the photocurrent, IL, the reverse diode saturation current, Io, the ideality factor of diode, n. Accuracy of the proposed model and its parameters evaluated based on different benchmarks. The results showed that the proposed model fitting the experimental results with high accuracy compare to the other models, as well as the I-V characteristic curve. The results of this study can be considered valuable in terms of the installation of a grid-connected PV system in fluctuated climatic conditions. PMID:27035575

On the Hydrologic Adjustment of Climate-Model Projections: The Potential Pitfall of Potential Evapotranspiration

USGS Publications Warehouse

Milly, Paul C.D.; Dunne, Krista A.

2011-01-01

Hydrologic models often are applied to adjust projections of hydroclimatic change that come from climate models. Such adjustment includes climate-bias correction, spatial refinement ("downscaling"), and consideration of the roles of hydrologic processes that were neglected in the climate model. Described herein is a quantitative analysis of the effects of hydrologic adjustment on the projections of runoff change associated with projected twenty-first-century climate change. In a case study including three climate models and 10 river basins in the contiguous United States, the authors find that relative (i.e., fractional or percentage) runoff change computed with hydrologic adjustment more often than not was less positive (or, equivalently, more negative) than what was projected by the climate models. The dominant contributor to this decrease in runoff was a ubiquitous change in runoff (median -11%) caused by the hydrologic model’s apparent amplification of the climate-model-implied growth in potential evapotranspiration. Analysis suggests that the hydrologic model, on the basis of the empirical, temperature-based modified Jensen–Haise formula, calculates a change in potential evapotranspiration that is typically 3 times the change implied by the climate models, which explicitly track surface energy budgets. In comparison with the amplification of potential evapotranspiration, central tendencies of other contributions from hydrologic adjustment (spatial refinement, climate-bias adjustment, and process refinement) were relatively small. The authors’ findings highlight the need for caution when projecting changes in potential evapotranspiration for use in hydrologic models or drought indices to evaluate climate-change impacts on water.

Exploring a potential energy surface by machine learning for characterizing atomic transport

NASA Astrophysics Data System (ADS)

Kanamori, Kenta; Toyoura, Kazuaki; Honda, Junya; Hattori, Kazuki; Seko, Atsuto; Karasuyama, Masayuki; Shitara, Kazuki; Shiga, Motoki; Kuwabara, Akihide; Takeuchi, Ichiro

2018-03-01

We propose a machine-learning method for evaluating the potential barrier governing atomic transport based on the preferential selection of dominant points for atomic transport. The proposed method generates numerous random samples of the entire potential energy surface (PES) from a probabilistic Gaussian process model of the PES, which enables defining the likelihood of the dominant points. The robustness and efficiency of the method are demonstrated on a dozen model cases for proton diffusion in oxides, in comparison with a conventional nudge elastic band method.

Model-based hierarchical reinforcement learning and human action control

PubMed Central

Botvinick, Matthew; Weinstein, Ari

2014-01-01

Recent work has reawakened interest in goal-directed or ‘model-based’ choice, where decisions are based on prospective evaluation of potential action outcomes. Concurrently, there has been growing attention to the role of hierarchy in decision-making and action control. We focus here on the intersection between these two areas of interest, considering the topic of hierarchical model-based control. To characterize this form of action control, we draw on the computational framework of hierarchical reinforcement learning, using this to interpret recent empirical findings. The resulting picture reveals how hierarchical model-based mechanisms might play a special and pivotal role in human decision-making, dramatically extending the scope and complexity of human behaviour. PMID:25267822

The potential of coordinated reservoir operation for flood mitigation in large basins - A case study on the Bavarian Danube using coupled hydrological-hydrodynamic models

NASA Astrophysics Data System (ADS)

Seibert, S. P.; Skublics, D.; Ehret, U.

2014-09-01

The coordinated operation of reservoirs in large-scale river basins has great potential to improve flood mitigation. However, this requires large scale hydrological models to translate the effect of reservoir operation to downstream points of interest, in a quality sufficient for the iterative development of optimized operation strategies. And, of course, it requires reservoirs large enough to make a noticeable impact. In this paper, we present and discuss several methods dealing with these prerequisites for reservoir operation using the example of three major floods in the Bavarian Danube basin (45,000 km2) and nine reservoirs therein: We start by presenting an approach for multi-criteria evaluation of model performance during floods, including aspects of local sensitivity to simulation quality. Then we investigate the potential of joint hydrologic-2d-hydrodynamic modeling to improve model performance. Based on this, we evaluate upper limits of reservoir impact under idealized conditions (perfect knowledge of future rainfall) with two methods: Detailed simulations and statistical analysis of the reservoirs' specific retention volume. Finally, we investigate to what degree reservoir operation strategies optimized for local (downstream vicinity to the reservoir) and regional (at the Danube) points of interest are compatible. With respect to model evaluation, we found that the consideration of local sensitivities to simulation quality added valuable information not included in the other evaluation criteria (Nash-Sutcliffe efficiency and Peak timing). With respect to the second question, adding hydrodynamic models to the model chain did, contrary to our expectations, not improve simulations, despite the fact that under idealized conditions (using observed instead of simulated lateral inflow) the hydrodynamic models clearly outperformed the routing schemes of the hydrological models. Apparently, the advantages of hydrodynamic models could not be fully exploited when fed by output from hydrological models afflicted with systematic errors in volume and timing. This effect could potentially be reduced by joint calibration of the hydrological-hydrodynamic model chain. Finally, based on the combination of the simulation-based and statistical impact assessment, we identified one reservoir potentially useful for coordinated, regional flood mitigation for the Danube. While this finding is specific to our test basin, the more interesting and generally valid finding is that operation strategies optimized for local and regional flood mitigation are not necessarily mutually exclusive, sometimes they are identical, sometimes they can, due to temporal offsets, be pursued simultaneously.

A model-based reasoning approach to sensor placement for monitorability

NASA Technical Reports Server (NTRS)

Chien, Steve; Doyle, Richard; Homemdemello, Luiz

1992-01-01

An approach is presented to evaluating sensor placements to maximize monitorability of the target system while minimizing the number of sensors. The approach uses a model of the monitored system to score potential sensor placements on the basis of four monitorability criteria. The scores can then be analyzed to produce a recommended sensor set. An example from our NASA application domain is used to illustrate our model-based approach to sensor placement.

Modifying climate change habitat models using tree species-specific assessments of model uncertainty and life history-factors

Treesearch

Stephen N. Matthews; Louis R. Iverson; Anantha M. Prasad; Matthew P. Peters; Paul G. Rodewald

2011-01-01

Species distribution models (SDMs) to evaluate trees' potential responses to climate change are essential for developing appropriate forest management strategies. However, there is a great need to better understand these models' limitations and evaluate their uncertainties. We have previously developed statistical models of suitable habitat, based on both...

A new cellular automata model of traffic flow with negative exponential weighted look-ahead potential

NASA Astrophysics Data System (ADS)

Ma, Xiao; Zheng, Wei-Fan; Jiang, Bao-Shan; Zhang, Ji-Ye

2016-10-01

With the development of traffic systems, some issues such as traffic jams become more and more serious. Efficient traffic flow theory is needed to guide the overall controlling, organizing and management of traffic systems. On the basis of the cellular automata model and the traffic flow model with look-ahead potential, a new cellular automata traffic flow model with negative exponential weighted look-ahead potential is presented in this paper. By introducing the negative exponential weighting coefficient into the look-ahead potential and endowing the potential of vehicles closer to the driver with a greater coefficient, the modeling process is more suitable for the driver’s random decision-making process which is based on the traffic environment that the driver is facing. The fundamental diagrams for different weighting parameters are obtained by using numerical simulations which show that the negative exponential weighting coefficient has an obvious effect on high density traffic flux. The complex high density non-linear traffic behavior is also reproduced by numerical simulations. Project supported by the National Natural Science Foundation of China (Grant Nos. 11572264, 11172247, 11402214, and 61373009).

Diversity and Community: The Role of Agent-Based Modeling.

PubMed

Stivala, Alex

2017-06-01

Community psychology involves several dialectics between potentially opposing ideals, such as theory and practice, rights and needs, and respect for human diversity and sense of community. Some recent papers in the American Journal of Community Psychology have examined the diversity-community dialectic, some with the aid of agent-based modeling and concepts from network science. This paper further elucidates these concepts and suggests that research in community psychology can benefit from a useful dialectic between agent-based modeling and the real-world concerns of community psychology. © Society for Community Research and Action 2017.

Influence Diffusion Model in Text-Based Communication

NASA Astrophysics Data System (ADS)

Matsumura, Naohiro; Ohsawa, Yukio; Ishizuka, Mitsuru

Business people, especially marketing researchers, are keen to understand peoples' potential sense of value to create fascinating topics stimulating peoples' interest. In this paper, we aim at finding influential people, comments, and terms contributing the discovery of such topics. For this purpose, we propose an Influence Diffusion Model in text-based communication, where the influence of people, comments, and terms are defined as the degree of text-based relevance of messages. We apply this model to Bulletin Board Service(BBS) on the Internet, and present our discoveries on experimental evaluations.

Factorial Design Based Multivariate Modeling and Optimization of Tunable Bioresponsive Arginine Grafted Poly(cystaminebis(acrylamide)-diaminohexane) Polymeric Matrix Based Nanocarriers.

PubMed

Yang, Rongbing; Nam, Kihoon; Kim, Sung Wan; Turkson, James; Zou, Ye; Zuo, Yi Y; Haware, Rahul V; Chougule, Mahavir B

2017-01-03

Desired characteristics of nanocarriers are crucial to explore its therapeutic potential. This investigation aimed to develop tunable bioresponsive newly synthesized unique arginine grafted poly(cystaminebis(acrylamide)-diaminohexane) [ABP] polymeric matrix based nanocarriers by using L9 Taguchi factorial design, desirability function, and multivariate method. The selected formulation and process parameters were ABP concentration, acetone concentration, the volume ratio of acetone to ABP solution, and drug concentration. The measured nanocarrier characteristics were particle size, polydispersity index, zeta potential, and percentage drug loading. Experimental validation of nanocarrier characteristics computed from initially developed predictive model showed nonsignificant differences (p > 0.05). The multivariate modeling based optimized cationic nanocarrier formulation of <100 nm loaded with hydrophilic acetaminophen was readapted for a hydrophobic etoposide loading without significant changes (p > 0.05) except for improved loading percentage. This is the first study focusing on ABP polymeric matrix based nanocarrier development. Nanocarrier particle size was stable in PBS 7.4 for 48 h. The increase of zeta potential at lower pH 6.4, compared to the physiological pH, showed possible endosomal escape capability. The glutathione triggered release at the physiological conditions indicated the competence of cytosolic targeting delivery of the loaded drug from bioresponsive nanocarriers. In conclusion, this unique systematic approach provides rational evaluation and prediction of a tunable bioresponsive ABP based matrix nanocarrier, which was built on selected limited number of smart experimentation.

Agent-based Modeling with MATSim for Hazards Evacuation Planning

NASA Astrophysics Data System (ADS)

Jones, J. M.; Ng, P.; Henry, K.; Peters, J.; Wood, N. J.

2015-12-01

Hazard evacuation planning requires robust modeling tools and techniques, such as least cost distance or agent-based modeling, to gain an understanding of a community's potential to reach safety before event (e.g. tsunami) arrival. Least cost distance modeling provides a static view of the evacuation landscape with an estimate of travel times to safety from each location in the hazard space. With this information, practitioners can assess a community's overall ability for timely evacuation. More information may be needed if evacuee congestion creates bottlenecks in the flow patterns. Dynamic movement patterns are best explored with agent-based models that simulate movement of and interaction between individual agents as evacuees through the hazard space, reacting to potential congestion areas along the evacuation route. The multi-agent transport simulation model MATSim is an agent-based modeling framework that can be applied to hazard evacuation planning. Developed jointly by universities in Switzerland and Germany, MATSim is open-source software written in Java and freely available for modification or enhancement. We successfully used MATSim to illustrate tsunami evacuation challenges in two island communities in California, USA, that are impacted by limited escape routes. However, working with MATSim's data preparation, simulation, and visualization modules in an integrated development environment requires a significant investment of time to develop the software expertise to link the modules and run a simulation. To facilitate our evacuation research, we packaged the MATSim modules into a single application tailored to the needs of the hazards community. By exposing the modeling parameters of interest to researchers in an intuitive user interface and hiding the software complexities, we bring agent-based modeling closer to practitioners and provide access to the powerful visual and analytic information that this modeling can provide.

Gas Hydrate Petroleum System Modeling in western Nankai Trough Area

NASA Astrophysics Data System (ADS)

Tanaka, M.; Aung, T. T.; Fujii, T.; Wada, N.; Komatsu, Y.

2017-12-01

Since 2003, we have been conducting Gas Hydrate (GH) petroleum system models covering the eastern Nankai Trough, Japan, and results of resource potential from regional model shows good match with the value depicted from seismic and log data. In this year, we have applied this method to explore GH potential in study area. In our study area, GH prospects have been identified with aid of bottom simulating reflector (BSR) and presence of high velocity anomalies above the BSR interpreted based on 3D migration seismic and high density velocity cubes. In order to understand the pathway of biogenic methane from source to GH prospects 1D-2D-3D GH petroleum system models are built and investigated. This study comprises lower Miocene to Pleistocene, deep to shallow marine sedimentary successions of Pliocene and Pleistocene layers overlain the basement. The BSR were interpreted in Pliocene and Pleistocene layers. Based on 6 interpreted sequence boundaries from 3D migration seismic and velocity data, construction of a depth 3D framework model is made and distributed by a conceptual submarine fan depositional facies model derived from seismic facies analysis and referring existing geological report. 1D models are created to analyze lithology sensitivity to temperature and vitrinite data from an exploratory well drilled in the vicinity of study area. The PSM parameters are applied in 2D and 3D modeling and simulation. Existing report of the explanatory well reveals that thermogenic origin are considered to exist. For this reason, simulation scenarios including source formations for both biogenic and thermogenic reaction models are also investigated. Simulation results reveal lower boundary of GH saturation zone at pseudo wells has been simulated with sensitivity of a few tens of meters in comparing with interpreted BSR. From sensitivity analysis, simulated temperature was controlled by different peak generation temperature models and geochemical parameters. Progressive folding and updipping layers including paleostructure can effectively assist biogenic gas migration to upward. Biogenic and Thermogenic mixing model shows that kitchen center only has a potential for generating thermogenic hydrocarbon. Our Prospect based on seismic interpretation is consistent with high GH saturation area based on 3D modeling results.

Towards a 3d Spatial Urban Energy Modelling Approach

NASA Astrophysics Data System (ADS)

Bahu, J.-M.; Koch, A.; Kremers, E.; Murshed, S. M.

2013-09-01

Today's needs to reduce the environmental impact of energy use impose dramatic changes for energy infrastructure and existing demand patterns (e.g. buildings) corresponding to their specific context. In addition, future energy systems are expected to integrate a considerable share of fluctuating power sources and equally a high share of distributed generation of electricity. Energy system models capable of describing such future systems and allowing the simulation of the impact of these developments thus require a spatial representation in order to reflect the local context and the boundary conditions. This paper describes two recent research approaches developed at EIFER in the fields of (a) geo-localised simulation of heat energy demand in cities based on 3D morphological data and (b) spatially explicit Agent-Based Models (ABM) for the simulation of smart grids. 3D city models were used to assess solar potential and heat energy demand of residential buildings which enable cities to target the building refurbishment potentials. Distributed energy systems require innovative modelling techniques where individual components are represented and can interact. With this approach, several smart grid demonstrators were simulated, where heterogeneous models are spatially represented. Coupling 3D geodata with energy system ABMs holds different advantages for both approaches. On one hand, energy system models can be enhanced with high resolution data from 3D city models and their semantic relations. Furthermore, they allow for spatial analysis and visualisation of the results, with emphasis on spatially and structurally correlations among the different layers (e.g. infrastructure, buildings, administrative zones) to provide an integrated approach. On the other hand, 3D models can benefit from more detailed system description of energy infrastructure, representing dynamic phenomena and high resolution models for energy use at component level. The proposed modelling strategies conceptually and practically integrate urban spatial and energy planning approaches. The combined modelling approach that will be developed based on the described sectorial models holds the potential to represent hybrid energy systems coupling distributed generation of electricity with thermal conversion systems.

Spatial variability of climate change impacts on yield of rice and wheat in the Indian Ganga Basin.

PubMed

Mishra, Ashok; Singh, R; Raghuwanshi, N S; Chatterjee, C; Froebrich, Jochen

2013-12-01

Indian Ganga Basin (IGB), one of the most densely populated areas in the world, is facing a significant threat to food grain production, besides increased yield gap between actual and potential production, due to climate change. We have analyzed the spatial variability of climate change impacts on rice and wheat yields at three different locations representing the upper, middle and lower IGB. The DSSAT model is used to simulate the effects of climate variability and climate change on rice and wheat yields by analyzing: (i) spatial crop yield response to current climate, and (ii) impact of a changing climate as projected by two regional climate models, REMO and HadRM3, based on SRES A1B emission scenarios for the period 2011-2040. Results for current climate demonstrate a significant gap between actual and potential yield for upper, middle and lower IGB stations. The analysis based on RCM projections shows that during 2011-2040, the largest reduction in rice and wheat yields will occur in the upper IGB (reduction of potential rice and wheat yield respectively by 43.2% and 20.9% by REMO, and 24.8% and 17.2% by HadRM3). In the lower IGB, however, contrasting results are obtained, with HadRM3 based projections showing an increase in the potential rice and wheat yields, whereas, REMO based projections show decreased potential yields. We discuss the influence of agro-climatic factors; variation in temperature, length of maturity period and leaf area index which are responsible for modeled spatial variability in crop yield response within the IGB. Copyright © 2013 Elsevier B.V. All rights reserved.

Comparison of the effects of temperature and water potential on seed germination of Fabaceae species from desert and subalpine grassland.

PubMed

Hu, Xiao Wen; Fan, Yan; Baskin, Carol C; Baskin, Jerry M; Wang, Yan Rong

2015-05-01

Temperature and water potential for germination based on the thermal and hydrotime models have been successfully applied in predicting germination requirements of physiologically dormant seeds as well as nondormant seeds. However, comparative studies of the germination requirements of physically dormant seeds from different ecosystems have not been done. Germination of scarified seeds of four legume species collected from the Qing-Tibetan Plateau and of four collected in the Alax Desert in China was compared over a range of temperatures and water potentials based on thermal time and hydrotime models. Seeds of species from the Qing-Tibetan Plateau had a lower base temperature (T b) and optimal temperature (T o) for germination than those from the Alax Desert. Seeds of the four species from the Qing-Tibetan Plateau germinated to high percentages at 5°C, whereas none of the four desert species did so. Seeds of species from the Alax Desert germinated to a high percentage at 35°C or 40°C, while no seeds of species from the Qing-Tibetan Plateau germinated at 35°C or 40°C. The base median water potential [Ψ b(50)] differed among species but not between the two habitats. The thermal time and hydrotime models accurately predicted the germination time course of scarified seeds of most of the eight species in response to temperature and water potential; thus, they can be useful tools in comparative studies on germination of seeds with physical dormancy. Habitat temperatures but not rainfall is closely related to germination requirements of these species. © 2015 Botanical Society of America, Inc.

Use of the ventricular propagated excitation model in the magnetocardiographic inverse problem for reconstruction of electrophysiological properties.

PubMed

Ohyu, Shigeharu; Okamoto, Yoshiwo; Kuriki, Shinya

2002-06-01

A novel magnetocardiographic inverse method for reconstructing the action potential amplitude (APA) and the activation time (AT) on the ventricular myocardium is proposed. This method is based on the propagated excitation model, in which the excitation is propagated through the ventricle with nonuniform height of action potential. Assumption of stepwise waveform on the transmembrane potential was introduced in the model. Spatial gradient of transmembrane potential, which is defined by APA and AT distributed in the ventricular wall, is used for the computation of a current source distribution. Based on this source model, the distributions of APA and AT are inversely reconstructed from the QRS interval of magnetocardiogram (MCG) utilizing a maximum a posteriori approach. The proposed reconstruction method was tested through computer simulations. Stability of the methods with respect to measurement noise was demonstrated. When reference APA was provided as a uniform distribution, root-mean-square errors of estimated APA were below 10 mV for MCG signal-to-noise ratios greater than, or equal to, 20 dB. Low-amplitude regions located at several sites in reference APA distributions were correctly reproduced in reconstructed APA distributions. The goal of our study is to develop a method for detecting myocardial ischemia through the depression of reconstructed APA distributions.

Radon potential mapping of the Tralee-Castleisland and Cavan areas (Ireland) based on airborne gamma-ray spectrometry and geology.

PubMed

Appleton, J D; Doyle, E; Fenton, D; Organo, C

2011-06-01

The probability of homes in Ireland having high indoor radon concentrations is estimated on the basis of known in-house radon measurements averaged over 10 km × 10 km grid squares. The scope for using airborne gamma-ray spectrometer data for the Tralee-Castleisland area of county Kerry and county Cavan to predict the radon potential (RP) in two distinct areas of Ireland is evaluated in this study. Airborne data are compared statistically with in-house radon measurements in conjunction with geological and ground permeability data to establish linear regression models and produce radon potential maps. The best agreement between the percentage of dwellings exceeding the reference level (RL) for radon concentrations in Ireland (% > RL), estimated from indoor radon data, and modelled RP in the Tralee-Castleisland area is produced using models based on airborne gamma-ray spectrometry equivalent uranium (eU) and ground permeability data. Good agreement was obtained between the % > RL from indoor radon data and RP estimated from eU data in the Cavan area using terrain specific models. In both areas, RP maps derived from eU data are spatially more detailed than the published 10 km grid map. The results show the potential for using airborne radiometric data for producing RP maps.

The growth of finfish in global open-ocean aquaculture under climate change.

PubMed

Klinger, Dane H; Levin, Simon A; Watson, James R

2017-10-11

Aquaculture production is projected to expand from land-based operations to the open ocean as demand for seafood grows and competition increases for inputs to land-based aquaculture, such as freshwater and suitable land. In contrast to land-based production, open-ocean aquaculture is constrained by oceanographic factors, such as current speeds and seawater temperature, which are dynamic in time and space, and cannot easily be controlled. As such, the potential for offshore aquaculture to increase seafood production is tied to the physical state of the oceans. We employ a novel spatial model to estimate the potential of open-ocean finfish aquaculture globally, given physical, biological and technological constraints. Finfish growth potential for three common aquaculture species representing different thermal guilds-Atlantic salmon ( Salmo salar ), gilthead seabream ( Sparus aurata ) and cobia ( Rachycentron canadum )-is compared across species and regions and with climate change, based on outputs of a high-resolution global climate model. Globally, there are ample areas that are physically suitable for fish growth and potential expansion of the nascent aquaculture industry. The effects of climate change are heterogeneous across species and regions, but areas with existing aquaculture industries are likely to see increases in growth rates. In areas where climate change results in reduced growth rates, adaptation measures, such as selective breeding, can probably offset potential production losses. © 2017 The Author(s).

Validation of Fatigue Modeling Predictions in Aviation Operations

NASA Technical Reports Server (NTRS)

Gregory, Kevin; Martinez, Siera; Flynn-Evans, Erin

2017-01-01

Bio-mathematical fatigue models that predict levels of alertness and performance are one potential tool for use within integrated fatigue risk management approaches. A number of models have been developed that provide predictions based on acute and chronic sleep loss, circadian desynchronization, and sleep inertia. Some are publicly available and gaining traction in settings such as commercial aviation as a means of evaluating flight crew schedules for potential fatigue-related risks. Yet, most models have not been rigorously evaluated and independently validated for the operations to which they are being applied and many users are not fully aware of the limitations in which model results should be interpreted and applied.

Modeling, Uncertainty Quantification and Sensitivity Analysis of Subsurface Fluid Migration in the Above Zone Monitoring Interval of a Geologic Carbon Storage

NASA Astrophysics Data System (ADS)

Namhata, A.; Dilmore, R. M.; Oladyshkin, S.; Zhang, L.; Nakles, D. V.

2015-12-01

Carbon dioxide (CO2) storage into geological formations has significant potential for mitigating anthropogenic CO2 emissions. An increasing emphasis on the commercialization and implementation of this approach to store CO2 has led to the investigation of the physical processes involved and to the development of system-wide mathematical models for the evaluation of potential geologic storage sites and the risk associated with them. The sub-system components under investigation include the storage reservoir, caprock seals, and the above zone monitoring interval, or AZMI, to name a few. Diffusive leakage of CO2 through the caprock seal to overlying formations may occur due to its intrinsic permeability and/or the presence of natural/induced fractures. This results in a potential risk to environmental receptors such as underground sources of drinking water. In some instances, leaking CO2 also has the potential to reach the ground surface and result in atmospheric impacts. In this work, fluid (i.e., CO2 and brine) flow above the caprock, in the region designated as the AZMI, is modeled for a leakage event of a typical geologic storage system with different possible boundary scenarios. An analytical and approximate solution for radial migration of fluids in the AZMI with continuous inflow of fluids from the reservoir through the caprock has been developed. In its present form, the AZMI model predicts the spatial changes in pressure - gas saturations over time in a layer immediately above the caprock. The modeling is performed for a benchmark case and the data-driven approach of arbitrary Polynomial Chaos (aPC) Expansion is used to quantify the uncertainty of the model outputs based on the uncertainty of model input parameters such as porosity, permeability, formation thickness, and residual brine saturation. The recently developed aPC approach performs stochastic model reduction and approximates the models by a polynomial-based response surface. Finally, a global sensitivity analysis was performed with Sobol indices based on the aPC technique to determine the relative importance of these input parameters on the model output space.

IRT Model Selection Methods for Dichotomous Items

ERIC Educational Resources Information Center

Kang, Taehoon; Cohen, Allan S.

2007-01-01

Fit of the model to the data is important if the benefits of item response theory (IRT) are to be obtained. In this study, the authors compared model selection results using the likelihood ratio test, two information-based criteria, and two Bayesian methods. An example illustrated the potential for inconsistency in model selection depending on…

CHALLENGES IN CONSTRUCTING STATISTICALLY-BASED SAR MODELS FOR DEVELOPMENTAL TOXICITY

EPA Science Inventory

Regulatory agencies are increasingly called upon to review large numbers of environmental contaminants that have not been characterized for their potential to pose a health risk. Additionally, there is special interest in protecting potentially sensitive subpopulations and identi...

From Creatures of Habit to Goal-Directed Learners: Tracking the Developmental Emergence of Model-Based Reinforcement Learning.

PubMed

Decker, Johannes H; Otto, A Ross; Daw, Nathaniel D; Hartley, Catherine A

2016-06-01

Theoretical models distinguish two decision-making strategies that have been formalized in reinforcement-learning theory. A model-based strategy leverages a cognitive model of potential actions and their consequences to make goal-directed choices, whereas a model-free strategy evaluates actions based solely on their reward history. Research in adults has begun to elucidate the psychological mechanisms and neural substrates underlying these learning processes and factors that influence their relative recruitment. However, the developmental trajectory of these evaluative strategies has not been well characterized. In this study, children, adolescents, and adults performed a sequential reinforcement-learning task that enabled estimation of model-based and model-free contributions to choice. Whereas a model-free strategy was apparent in choice behavior across all age groups, a model-based strategy was absent in children, became evident in adolescents, and strengthened in adults. These results suggest that recruitment of model-based valuation systems represents a critical cognitive component underlying the gradual maturation of goal-directed behavior. © The Author(s) 2016.

Deriving dynamical models from paleoclimatic records: application to glacial millennial-scale climate variability.

PubMed

Kwasniok, Frank; Lohmann, Gerrit

2009-12-01

A method for systematically deriving simple nonlinear dynamical models from ice-core data is proposed. It offers a tool to integrate models and theories with paleoclimatic data. The method is based on the unscented Kalman filter, a nonlinear extension of the conventional Kalman filter. Here, we adopt the abstract conceptual model of stochastically driven motion in a potential that allows for two distinctly different states. The parameters of the model-the shape of the potential and the noise level-are estimated from a North Greenland ice-core record. For the glacial period from 70 to 20 ky before present, a potential is derived that is asymmetric and almost degenerate. There is a deep well corresponding to a cold stadial state and a very shallow well corresponding to a warm interstadial state.

Inter-layer potential for hexagonal boron nitride

NASA Astrophysics Data System (ADS)

Leven, Itai; Azuri, Ido; Kronik, Leeor; Hod, Oded

2014-03-01

A new interlayer force-field for layered hexagonal boron nitride (h-BN) based structures is presented. The force-field contains three terms representing the interlayer attraction due to dispersive interactions, repulsion due to anisotropic overlaps of electron clouds, and monopolar electrostatic interactions. With appropriate parameterization, the potential is able to simultaneously capture well the binding and lateral sliding energies of planar h-BN based dimer systems as well as the interlayer telescoping and rotation of double walled boron-nitride nanotubes of different crystallographic orientations. The new potential thus allows for the accurate and efficient modeling and simulation of large-scale h-BN based layered structures.

Exploration of Novel Materials for Development of Next Generation OPV Devices: Cooperative Research and Development Final Report, CRADA Number CRD-10-398

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

Olson, D.

2012-09-01

Organic-based solar cells offer the potential for low cost, scalable conversion of solar energy. This project will try to utilize the extensive organic synthetic capabilities of ConocoPhillips to produce novel acceptor and donor materials as well potentially as interface modifiers to produce improved OPV devices with greater efficiency and stability. The synthetic effort will be based on the knowledge base and modeling being done at NREL to identify new candidate materials.

Complex absorbing potential based Lorentzian fitting scheme and time dependent quantum transport.

PubMed

Xie, Hang; Kwok, Yanho; Jiang, Feng; Zheng, Xiao; Chen, GuanHua

2014-10-28

Based on the complex absorbing potential (CAP) method, a Lorentzian expansion scheme is developed to express the self-energy. The CAP-based Lorentzian expansion of self-energy is employed to solve efficiently the Liouville-von Neumann equation of one-electron density matrix. The resulting method is applicable for both tight-binding and first-principles models and is used to simulate the transient currents through graphene nanoribbons and a benzene molecule sandwiched between two carbon-atom chains.

Current use of impact models for agri-environment schemes and potential for improvements of policy design and assessment.

PubMed

Primdahl, Jørgen; Vesterager, Jens Peter; Finn, John A; Vlahos, George; Kristensen, Lone; Vejre, Henrik

2010-06-01

Agri-Environment Schemes (AES) to maintain or promote environmentally-friendly farming practices were implemented on about 25% of all agricultural land in the EU by 2002. This article analyses and discusses the actual and potential use of impact models in supporting the design, implementation and evaluation of AES. Impact models identify and establish the causal relationships between policy objectives and policy outcomes. We review and discuss the role of impact models at different stages in the AES policy process, and present results from a survey of impact models underlying 60 agri-environmental schemes in seven EU member states. We distinguished among three categories of impact models (quantitative, qualitative or common sense), depending on the degree of evidence in the formal scheme description, additional documents, or key person interviews. The categories of impact models used mainly depended on whether scheme objectives were related to natural resources, biodiversity or landscape. A higher proportion of schemes dealing with natural resources (primarily water) were based on quantitative impact models, compared to those concerned with biodiversity or landscape. Schemes explicitly targeted either on particular parts of individual farms or specific areas tended to be based more on quantitative impact models compared to whole-farm schemes and broad, horizontal schemes. We conclude that increased and better use of impact models has significant potential to improve efficiency and effectiveness of AES. (c) 2009 Elsevier Ltd. All rights reserved.

Climate and dengue transmission: evidence and implications.

PubMed

Morin, Cory W; Comrie, Andrew C; Ernst, Kacey

2013-01-01

Climate influences dengue ecology by affecting vector dynamics, agent development, and mosquito/human interactions. Although these relationships are known, the impact climate change will have on transmission is unclear. Climate-driven statistical and process-based models are being used to refine our knowledge of these relationships and predict the effects of projected climate change on dengue fever occurrence, but results have been inconsistent. We sought to identify major climatic influences on dengue virus ecology and to evaluate the ability of climate-based dengue models to describe associations between climate and dengue, simulate outbreaks, and project the impacts of climate change. We reviewed the evidence for direct and indirect relationships between climate and dengue generated from laboratory studies, field studies, and statistical analyses of associations between vectors, dengue fever incidence, and climate conditions. We assessed the potential contribution of climate-driven, process-based dengue models and provide suggestions to improve their performance. Relationships between climate variables and factors that influence dengue transmission are complex. A climate variable may increase dengue transmission potential through one aspect of the system while simultaneously decreasing transmission potential through another. This complexity may at least partly explain inconsistencies in statistical associations between dengue and climate. Process-based models can account for the complex dynamics but often omit important aspects of dengue ecology, notably virus development and host-species interactions. Synthesizing and applying current knowledge of climatic effects on all aspects of dengue virus ecology will help direct future research and enable better projections of climate change effects on dengue incidence.

A machine learning approach to the potential-field method for implicit modeling of geological structures

NASA Astrophysics Data System (ADS)

Gonçalves, Ítalo Gomes; Kumaira, Sissa; Guadagnin, Felipe

2017-06-01

Implicit modeling has experienced a rise in popularity over the last decade due to its advantages in terms of speed and reproducibility in comparison with manual digitization of geological structures. The potential-field method consists in interpolating a scalar function that indicates to which side of a geological boundary a given point belongs to, based on cokriging of point data and structural orientations. This work proposes a vector potential-field solution from a machine learning perspective, recasting the problem as multi-class classification, which alleviates some of the original method's assumptions. The potentials related to each geological class are interpreted in a compositional data framework. Variogram modeling is avoided through the use of maximum likelihood to train the model, and an uncertainty measure is introduced. The methodology was applied to the modeling of a sample dataset provided with the software Move™. The calculations were implemented in the R language and 3D visualizations were prepared with the rgl package.

Modeling marine oily wastewater treatment by a probabilistic agent-based approach.

PubMed

Jing, Liang; Chen, Bing; Zhang, Baiyu; Ye, Xudong

2018-02-01

This study developed a novel probabilistic agent-based approach for modeling of marine oily wastewater treatment processes. It begins first by constructing a probability-based agent simulation model, followed by a global sensitivity analysis and a genetic algorithm-based calibration. The proposed modeling approach was tested through a case study of the removal of naphthalene from marine oily wastewater using UV irradiation. The removal of naphthalene was described by an agent-based simulation model using 8 types of agents and 11 reactions. Each reaction was governed by a probability parameter to determine its occurrence. The modeling results showed that the root mean square errors between modeled and observed removal rates were 8.73 and 11.03% for calibration and validation runs, respectively. Reaction competition was analyzed by comparing agent-based reaction probabilities, while agents' heterogeneity was visualized by plotting their real-time spatial distribution, showing a strong potential for reactor design and process optimization. Copyright © 2017 Elsevier Ltd. All rights reserved.

3D Finite Element Electrical Model of Larval Zebrafish ECG Signals

PubMed Central

Crowcombe, James; Dhillon, Sundeep Singh; Hurst, Rhiannon Mary; Egginton, Stuart; Müller, Ferenc; Sík, Attila; Tarte, Edward

2016-01-01

Assessment of heart function in zebrafish larvae using electrocardiography (ECG) is a potentially useful tool in developing cardiac treatments and the assessment of drug therapies. In order to better understand how a measured ECG waveform is related to the structure of the heart, its position within the larva and the position of the electrodes, a 3D model of a 3 days post fertilisation (dpf) larval zebrafish was developed to simulate cardiac electrical activity and investigate the voltage distribution throughout the body. The geometry consisted of two main components; the zebrafish body was modelled as a homogeneous volume, while the heart was split into five distinct regions (sinoatrial region, atrial wall, atrioventricular band, ventricular wall and heart chambers). Similarly, the electrical model consisted of two parts with the body described by Laplace’s equation and the heart using a bidomain ionic model based upon the Fitzhugh-Nagumo equations. Each region of the heart was differentiated by action potential (AP) parameters and activation wave conduction velocities, which were fitted and scaled based on previously published experimental results. ECG measurements in vivo at different electrode recording positions were then compared to the model results. The model was able to simulate action potentials, wave propagation and all the major features (P wave, R wave, T wave) of the ECG, as well as polarity of the peaks observed at each position. This model was based upon our current understanding of the structure of the normal zebrafish larval heart. Further development would enable us to incorporate features associated with the diseased heart and hence assist in the interpretation of larval zebrafish ECGs in these conditions. PMID:27824910

Estimation of the potential leakage of the chemical munitions based on two hydrodynamical models implemented for the Baltic Sea

NASA Astrophysics Data System (ADS)

Jakacki, Jaromir; Golenko, Mariya

2014-05-01

Two hydrodynamical models (Princeton Ocean Model (POM) and Parallel Ocean Program (POP)) have been implemented for the Baltic Sea area that consists of locations of the dumped chemical munitions during II War World. The models have been configured based on similar data source - bathymetry, initial conditions and external forces were implemented based on identical data. The horizontal resolutions of the models are also very similar. Several simulations with different initial conditions have been done. Comparison and analysis of the bottom currents from both models have been performed. Based on it estimating of the dangerous area and critical time have been done. Also lagrangian particle tracking and passive tracer were implemented and based on these results probability of the appearing dangerous doses and its time evolution have been presented. This work has been performed in the frame of the MODUM project financially supported by NATO.

Photodissociation of phenol via nonadiabatic tunneling: Comparison of two ab initio based potential energy surfaces

NASA Astrophysics Data System (ADS)

Xie, Changjian; Guo, Hua

2017-09-01

The nonadiabatic tunneling-facilitated photodissociation of phenol is investigated using a reduced-dimensional quantum model on two ab initio-based coupled potential energy surfaces (PESs). Although dynamics occurs largely on the lower adiabat, the proximity to a conical intersection between the S1 and S2 states requires the inclusion of both the geometric phase (GP) and diagonal Born-Oppenheimer correction (DBOC). The lifetime of the lowest-lying vibronic state is computed using the diabatic and various adiabatic models. The GP and DBOC terms are found to be essential on one set of PESs, but have a small impact on the other.

On the topology of the inflaton field in minimal supergravity models

NASA Astrophysics Data System (ADS)

Ferrara, Sergio; Fré, Pietro; Sorin, Alexander S.

2014-04-01

We consider global issues in minimal supergravity models where a single field inflaton potential emerges. In a particular case we reproduce the Starobinsky model and its description dual to a certain formulation of R + R 2 supergravity. For definiteness we confine our analysis to spaces at constant curvature, either vanishing or negative. Five distinct models arise, two flat models with respectively a quadratic and a quartic potential and three based on the space where its distinct isometries, elliptic, hyperbolic and parabolic are gauged. Fayet-Iliopoulos terms are introduced in a geometric way and they turn out to be a crucial ingredient in order to describe the de Sitter inflationary phase of the Starobinsky model.

Wet deposition of mercury at a New York state rural site: Concentrations, fluxes, and source areas

NASA Astrophysics Data System (ADS)

Lai, Soon-onn; Holsen, Thomas M.; Hopke, Philip K.; Liu, Peng

Event-based mercury (Hg) precipitation samples were collected with a modified MIC-B sampler between September 2003 and April 2005 at Potsdam, NY to investigate Hg in wet deposition and identify potential source areas using the potential source contribution function (PCSF) and residence time weighted concentration (RTWC) models. The volume-weighted mean (VWM) concentration and wet deposition flux were 5.5ngL-1 and 7.6μgm-2 during the study period, and 5.5ngL-1 and 5.9μgm-2 in 2004, respectively, and show seasonal trends with larger values in the spring and summer. The PSCF model results matched known source areas based on an emission inventory better than did the RTWC results based on the spatial correlation index. Both modeling results identified large Hg source areas that contain a number of coal-fired power plants located in the Upper Ohio River Valley and in southeastern Michigan, as well as in Quebec and Ontario where there are metal production facilities, waste incinerators and paper mills. Emissions from the Atlantic Ocean were also determined to be a potential source.

Use of Network Inference to Elucidate Common and Chemical-specific Effects on Steoidogenesis

EPA Science Inventory

Microarray data is a key source for modeling gene regulatory interactions. Regulatory network models based on multiple datasets are potentially more robust and can provide greater confidence. In this study, we used network modeling on microarray data generated by exposing the fat...

PROJECT SUMMARY: DEVELOPMENT OF THE VIRTUAL BEACH MODEL, PHASE I: AN EMPIRICAL MODEL

EPA Science Inventory

Mathematical models based on water-quality and other environmental surrogates may help to provide water quality assessment within a few hours and potentially provide one to three day forecasts, providing beach managers and public-health officials a tool for developing beach-speci...

Multiple model analysis with discriminatory data collection (MMA-DDC): A new method for improving measurement selection

NASA Astrophysics Data System (ADS)

Kikuchi, C.; Ferre, P. A.; Vrugt, J. A.

2011-12-01

Hydrologic models are developed, tested, and refined based on the ability of those models to explain available hydrologic data. The optimization of model performance based upon mismatch between model outputs and real world observations has been extensively studied. However, identification of plausible models is sensitive not only to the models themselves - including model structure and model parameters - but also to the location, timing, type, and number of observations used in model calibration. Therefore, careful selection of hydrologic observations has the potential to significantly improve the performance of hydrologic models. In this research, we seek to reduce prediction uncertainty through optimization of the data collection process. A new tool - multiple model analysis with discriminatory data collection (MMA-DDC) - was developed to address this challenge. In this approach, multiple hydrologic models are developed and treated as competing hypotheses. Potential new data are then evaluated on their ability to discriminate between competing hypotheses. MMA-DDC is well-suited for use in recursive mode, in which new observations are continuously used in the optimization of subsequent observations. This new approach was applied to a synthetic solute transport experiment, in which ranges of parameter values constitute the multiple hydrologic models, and model predictions are calculated using likelihood-weighted model averaging. MMA-DDC was used to determine the optimal location, timing, number, and type of new observations. From comparison with an exhaustive search of all possible observation sequences, we find that MMA-DDC consistently selects observations which lead to the highest reduction in model prediction uncertainty. We conclude that using MMA-DDC to evaluate potential observations may significantly improve the performance of hydrologic models while reducing the cost associated with collecting new data.

Permutation on hybrid natural inflation

NASA Astrophysics Data System (ADS)

Carone, Christopher D.; Erlich, Joshua; Ramos, Raymundo; Sher, Marc

2014-09-01

We analyze a model of hybrid natural inflation based on the smallest non-Abelian discrete group S3. Leading invariant terms in the scalar potential have an accidental global symmetry that is spontaneously broken, providing a pseudo-Goldstone boson that is identified as the inflaton. The S3 symmetry restricts both the form of the inflaton potential and the couplings of the inflaton field to the waterfall fields responsible for the end of inflation. We identify viable points in the model parameter space. Although the power in tensor modes is small in most of the parameter space of the model, we identify parameter choices that yield potentially observable values of r without super-Planckian initial values of the inflaton field.

Land-use and land-cover scenarios and spatial modeling at the regional scale

USGS Publications Warehouse

Sohl, Terry L.; Sleeter, Benjamin M.

2012-01-01

Land-use and land-cover (LULC) change has altered a large part of the earth's surface. Scenarios of potential future LULC change are required in order to better manage potential impacts on biodiversity, carbon fluxes, climate change, hydrology, and many other ecological processes. The U.S. Geological Survey is analyzing potential future LULC change in the United States, using an approach based on scenario construction and spatially explicit modeling. Similar modeling techniques are being used to produce historical LULC maps from 1940 to present. With the combination of backcast and forecast LULC data, the USGS is providing consistent LULC data for historical, current, and future time frames to support a variety of research applications.

Suitability of temperature sum models to simulate the flowering period of birches on regional scale as basis for realistic predictions of the allergenic potential of atmospheric pollen loads

NASA Astrophysics Data System (ADS)

Biernath, Christian; Hauck, Julia; Klein, Christian; Thieme, Christoph; Heinlein, Florian; Priesack, Eckart

2014-05-01

Persons susceptible to allergenic pollen grains need to apply suppressive pharmacy before the occurrence of the first allergy symptoms. Patient targeted medication could be improved if forecasts of the allergenic potential of pollen (biochemical composition of the pollen grain) and the onset, duration, and end of the pollen season are precise on regional scale. In plant tissue the biochemical composition may change within hours due to the resource availability for plant growth and plant internal nutrient re-mobilization. As these processes highly depend on both, the environmental conditions and the development stage of a plant, precise simulations of the onset and duration of the flowering period are crucial to determine the allergenic potential of tissues and pollen. Here, dynamic plant models that consider the dependence of the chemical composition of tissue on the development stage of the plant embedded in process-based ecosystem models seem promising tools; however, today dynamic plant growth is widely ignored in simulations of atmospheric pollen loads. In this study we raise the question whether frequently applied temperature sum models (TSM) could precisely simulate the plant development stages in case of birches on regional scale. These TSM integrate average temperatures above a base temperature below which no further plant development is assumed. In this study, we therefore tested the ability of TSM to simulate the flowering period of birches on more than 100 sites in Bavaria, Germany over a period of three years (2010-2012). Our simulations indicate that the often applied base temperatures between 2.3°C and 3.5°C for the integration of daily or hourly average temperatures, respectively, in Europe are too high to adequately simulate the onset of birch flowering in Bavaria where a base temperature of 1°C seems more convenient. A more regional calibration of the models to sub-regions in Bavaria with comparable climatic conditions could further improve the simulation results if compared to simulations using a model that was adjusted to only one representative location in Bavaria. Our simulation results suggest that birch phenology needs to be modelled on a more regional scale to derive precise predictions of the flowering period. Some weak simulation results are suspected to be due to the high genetic diversity of birches and their high adaptive potential to a wide range of environmental conditions which indeed is a characteristic for many pioneer species. The high adaptive potential could be an explanation why authors who calibrate their models to other climatic regions observe better simulation results using higher base temperatures. However, our simulations indicate that the simulation results may be biased if the base temperatures are assumed constant for one species and transferred to larger or smaller scales, to other regions with different climatic conditions, or when applied to extrapolate birch pollen seasons to future climate conditions.

Patch-based models and algorithms for image processing: a review of the basic principles and methods, and their application in computed tomography.

PubMed

Karimi, Davood; Ward, Rabab K

2016-10-01

Image models are central to all image processing tasks. The great advancements in digital image processing would not have been made possible without powerful models which, themselves, have evolved over time. In the past decade, "patch-based" models have emerged as one of the most effective models for natural images. Patch-based methods have outperformed other competing methods in many image processing tasks. These developments have come at a time when greater availability of powerful computational resources and growing concerns over the health risks of the ionizing radiation encourage research on image processing algorithms for computed tomography (CT). The goal of this paper is to explain the principles of patch-based methods and to review some of their recent applications in CT. We first review the central concepts in patch-based image processing and explain some of the state-of-the-art algorithms, with a focus on aspects that are more relevant to CT. Then, we review some of the recent application of patch-based methods in CT. Patch-based methods have already transformed the field of image processing, leading to state-of-the-art results in many applications. More recently, several studies have proposed patch-based algorithms for various image processing tasks in CT, from denoising and restoration to iterative reconstruction. Although these studies have reported good results, the true potential of patch-based methods for CT has not been yet appreciated. Patch-based methods can play a central role in image reconstruction and processing for CT. They have the potential to lead to substantial improvements in the current state of the art.

Model-based estimation for dynamic cardiac studies using ECT.

PubMed

Chiao, P C; Rogers, W L; Clinthorne, N H; Fessler, J A; Hero, A O

1994-01-01

The authors develop a strategy for joint estimation of physiological parameters and myocardial boundaries using ECT (emission computed tomography). They construct an observation model to relate parameters of interest to the projection data and to account for limited ECT system resolution and measurement noise. The authors then use a maximum likelihood (ML) estimator to jointly estimate all the parameters directly from the projection data without reconstruction of intermediate images. They also simulate myocardial perfusion studies based on a simplified heart model to evaluate the performance of the model-based joint ML estimator and compare this performance to the Cramer-Rao lower bound. Finally, the authors discuss model assumptions and potential uses of the joint estimation strategy.

[Modeling in value-based medicine].

PubMed

Neubauer, A S; Hirneiss, C; Kampik, A

2010-03-01

Modeling plays an important role in value-based medicine (VBM). It allows decision support by predicting potential clinical and economic consequences, frequently combining different sources of evidence. Based on relevant publications and examples focusing on ophthalmology the key economic modeling methods are explained and definitions are given. The most frequently applied model types are decision trees, Markov models, and discrete event simulation (DES) models. Model validation includes besides verifying internal validity comparison with other models (external validity) and ideally validation of its predictive properties. The existing uncertainty with any modeling should be clearly stated. This is true for economic modeling in VBM as well as when using disease risk models to support clinical decisions. In economic modeling uni- and multivariate sensitivity analyses are usually applied; the key concepts here are tornado plots and cost-effectiveness acceptability curves. Given the existing uncertainty, modeling helps to make better informed decisions than without this additional information.

Land-use and carbon cycle responses to moderate climate change: implications for land-based mitigation?

PubMed

Humpenöder, Florian; Popp, Alexander; Stevanovic, Miodrag; Müller, Christoph; Bodirsky, Benjamin Leon; Bonsch, Markus; Dietrich, Jan Philipp; Lotze-Campen, Hermann; Weindl, Isabelle; Biewald, Anne; Rolinski, Susanne

2015-06-02

Climate change has impacts on agricultural yields, which could alter cropland requirements and hence deforestation rates. Thus, land-use responses to climate change might influence terrestrial carbon stocks. Moreover, climate change could alter the carbon storage capacity of the terrestrial biosphere and hence the land-based mitigation potential. We use a global spatially explicit economic land-use optimization model to (a) estimate the mitigation potential of a climate policy that provides economic incentives for carbon stock conservation and enhancement, (b) simulate land-use and carbon cycle responses to moderate climate change (RCP2.6), and (c) investigate the combined effects throughout the 21st century. The climate policy immediately stops deforestation and strongly increases afforestation, resulting in a global mitigation potential of 191 GtC in 2100. Climate change increases terrestrial carbon stocks not only directly through enhanced carbon sequestration (62 GtC by 2100) but also indirectly through less deforestation due to higher crop yields (16 GtC by 2100). However, such beneficial climate impacts increase the potential of the climate policy only marginally, as the potential is already large under static climatic conditions. In the broader picture, this study highlights the importance of land-use dynamics for modeling carbon cycle responses to climate change in integrated assessment modeling.

Technology based transportation solutions : model deployment initiative

DOT National Transportation Integrated Search

1997-08-01

The Model Deployment Initiative provides real-life examples of technologys potential in metropolitan areas across the country. Investments from public and private sector partners will integrate existing ITS elements in the four sites as part of a ...

QUANTITATIVE PROCEDURES FOR NEUROTOXICOLOGY RISK ASSESSMENT

EPA Science Inventory

In this project, previously published information on biologically based dose-response model for brain development was used to quantitatively evaluate critical neurodevelopmental processes, and to assess potential chemical impacts on early brain development. This model has been ex...

A water market simulator considering pair-wise trades between agents

NASA Astrophysics Data System (ADS)

Huskova, I.; Erfani, T.; Harou, J. J.

2012-04-01

In many basins in England no further water abstraction licences are available. Trading water between water rights holders has been recognized as a potentially effective and economically efficient strategy to mitigate increasing scarcity. A screening tool that could assess the potential for trade through realistic simulation of individual water rights holders would help assess the solution's potential contribution to local water management. We propose an optimisation-driven water market simulator that predicts pair-wise trade in a catchment and represents its interaction with natural hydrology and engineered infrastructure. A model is used to emulate licence-holders' willingness to engage in short-term trade transactions. In their simplest form agents are represented using an economic benefit function. The working hypothesis is that trading behaviour can be partially predicted based on differences in marginal values of water over space and time and estimates of transaction costs on pair-wise trades. We discuss the further possibility of embedding rules, norms and preferences of the different water user sectors to more realistically represent the behaviours, motives and constraints of individual licence holders. The potential benefits and limitations of such a social simulation (agent-based) approach is contrasted with our simulator where agents are driven by economic optimization. A case study based on the Dove River Basin (UK) demonstrates model inputs and outputs. The ability of the model to suggest impacts of water rights policy reforms on trading is discussed.

Modeling and Data Analysis at the CCMC to Determine Threat of Spacecraft Surface Charging in Low Earth Orbit

NASA Astrophysics Data System (ADS)

Rastaetter, L.; Kuznetsova, M. M.; Zheng, Y.; Jordanova, V.; Yu, Y.; Minow, J. I.

2016-12-01

Spacecraft surface charging in Low-Earth Orbit occurs primarily in regions of low plasma density when precipitating electrons drive the spacecraft potential. Sudden changes in electric potentials occur when a spacecraft enters and leaves the sunlit region.At the Community Coordinated Modeling Center, we can employ a multitude of models of the ionosphere-thermosphere and inner magnetosphere to identify regions where spacecraft charging can occur based on thresholds of electron precipitation flux and energy and track the proximity of those areas to positions of satellites of interest. The identified regions will be validated and refined based on satellite observations. This work is in conjunction with the Spacecraft Charging Challenge organized by the GEM Workshop in collaboration with CCMC and the SHIELDS project at LANL.

Statistical Methods for Assessments in Simulations and Serious Games. Research Report. ETS RR-14-12

ERIC Educational Resources Information Center

Fu, Jianbin; Zapata, Diego; Mavronikolas, Elia

2014-01-01

Simulation or game-based assessments produce outcome data and process data. In this article, some statistical models that can potentially be used to analyze data from simulation or game-based assessments are introduced. Specifically, cognitive diagnostic models that can be used to estimate latent skills from outcome data so as to scale these…

A System to Derive Optimal Tree Diameter Increment Models from the Eastwide Forest Inventory Data Base (EFIDB)

Treesearch

Don C. Bragg

2002-01-01

This article is an introduction to the computer software used by the Potential Relative Increment (PRI) approach to optimal tree diameter growth modeling. These DOS programs extract qualified tree and plot data from the Eastwide Forest Inventory Data Base (EFIDB), calculate relative tree increment, sort for the highest relative increments by diameter class, and...

Addressing Early Life Sensitivity Using Physiologically Based Pharmacokinetic Modeling and In Vitro to In Vivo Extrapolation

PubMed Central

Yoon, Miyoung; Clewell, Harvey J.

2016-01-01

Physiologically based pharmacokinetic (PBPK) modeling can provide an effective way to utilize in vitro and in silico based information in modern risk assessment for children and other potentially sensitive populations. In this review, we describe the process of in vitro to in vivo extrapolation (IVIVE) to develop PBPK models for a chemical in different ages in order to predict the target tissue exposure at the age of concern in humans. We present our on-going studies on pyrethroids as a proof of concept to guide the readers through the IVIVE steps using the metabolism data collected either from age-specific liver donors or expressed enzymes in conjunction with enzyme ontogeny information to provide age-appropriate metabolism parameters in the PBPK model in the rat and human, respectively. The approach we present here is readily applicable to not just to other pyrethroids, but also to other environmental chemicals and drugs. Establishment of an in vitro and in silico-based evaluation strategy in conjunction with relevant exposure information in humans is of great importance in risk assessment for potentially vulnerable populations like early ages where the necessary information for decision making is limited. PMID:26977255

Addressing Early Life Sensitivity Using Physiologically Based Pharmacokinetic Modeling and In Vitro to In Vivo Extrapolation.

PubMed

Yoon, Miyoung; Clewell, Harvey J

2016-01-01

Physiologically based pharmacokinetic (PBPK) modeling can provide an effective way to utilize in vitro and in silico based information in modern risk assessment for children and other potentially sensitive populations. In this review, we describe the process of in vitro to in vivo extrapolation (IVIVE) to develop PBPK models for a chemical in different ages in order to predict the target tissue exposure at the age of concern in humans. We present our on-going studies on pyrethroids as a proof of concept to guide the readers through the IVIVE steps using the metabolism data collected either from age-specific liver donors or expressed enzymes in conjunction with enzyme ontogeny information to provide age-appropriate metabolism parameters in the PBPK model in the rat and human, respectively. The approach we present here is readily applicable to not just to other pyrethroids, but also to other environmental chemicals and drugs. Establishment of an in vitro and in silico-based evaluation strategy in conjunction with relevant exposure information in humans is of great importance in risk assessment for potentially vulnerable populations like early ages where the necessary information for decision making is limited.

Providers’ Perspectives Regarding the Development of a Web-Based Depression Intervention for Latina/o Youth

PubMed Central

Davidson, Tatiana M.; Soltis, Kathryn; Albia, Christina MinHee; de Arellano, Michael; Ruggiero, Kenneth J.

2014-01-01

Latina/o youth appear to be at significant risk for depression and, of concern, is high underutilization of mental health services observed in this population. There is a tremendous need for novel intervention methods to better serve the unique needs of this population. This paper describes the development of Rise Above (Siempre Sale el Sol), a Web-based, self-help, depression intervention for Latina/o adolescents funded by the National Institute of Mental Health. We applied a cultural adaptation model to an evidence-based depression treatment to reduce potential service barriers and increase the relevance and potential efficacy of the intervention for Latina/o youth. We conducted thematic interviews with 32 national experts to obtain feedback that would inform our application of the cultural adaptation model, the potential efficacy of the intervention, and the feasibility of implementation. Future directions for the evaluation of Rise Above (Siempre Sale el Sol) are described. PMID:25133417

A regressive storm model for extreme space weather

NASA Astrophysics Data System (ADS)

Terkildsen, Michael; Steward, Graham; Neudegg, Dave; Marshall, Richard

2012-07-01

Extreme space weather events, while rare, pose significant risk to society in the form of impacts on critical infrastructure such as power grids, and the disruption of high end technological systems such as satellites and precision navigation and timing systems. There has been an increased focus on modelling the effects of extreme space weather, as well as improving the ability of space weather forecast centres to identify, with sufficient lead time, solar activity with the potential to produce extreme events. This paper describes the development of a data-based model for predicting the occurrence of extreme space weather events from solar observation. The motivation for this work was to develop a tool to assist space weather forecasters in early identification of solar activity conditions with the potential to produce extreme space weather, and with sufficient lead time to notify relevant customer groups. Data-based modelling techniques were used to construct the model, and an extensive archive of solar observation data used to train, optimise and test the model. The optimisation of the base model aimed to eliminate false negatives (missed events) at the expense of a tolerable increase in false positives, under the assumption of an iterative improvement in forecast accuracy during progression of the solar disturbance, as subsequent data becomes available.

Decreasing redox voltage of terephthalate-based electrode material for Li-ion battery using substituent effect

NASA Astrophysics Data System (ADS)

Lakraychi, A. E.; Dolhem, F.; Djedaïni-Pilard, F.; Thiam, A.; Frayret, C.; Becuwe, M.

2017-08-01

The preparation and assessment versus lithium of a functionalized terephthalate-based as a potential new negative electrode material for Li-ion battery is presented. Inspired from molecular modelling, a decrease in redox potential is achieved through the symmetrical adjunction of electron-donating fragments (-CH3) on the aromatic ring. While the electrochemical activity of this organic material was maximized when used as nanocomposite and without any binder, the potential is furthermore lowered by 110 mV upon functionalization, consistently with predicted value gained from DFT calculations.

Value-based Proposition for a Dedicated Interventional Pulmonology Suite: an Adaptable Business Model.

PubMed

Desai, Neeraj R; French, Kim D; Diamond, Edward; Kovitz, Kevin L

2018-05-31

Value-based care is evolving with a focus on improving efficiency, reducing cost, and enhancing the patient experience. Interventional pulmonology has the opportunity to lead an effective value-based care model. This model is supported by the relatively low cost of pulmonary procedures and has the potential to improve efficiencies in thoracic care. We discuss key strategies to evaluate and improve efficiency in Interventional Pulmonology practice and describe our experience in developing an interventional pulmonology suite. Such a model can be adapted to other specialty areas and may encourage a more coordinated approach to specialty care. Copyright © 2018. Published by Elsevier Inc.

Whole plant based treatment of hypercholesterolemia with Crataegus laevigata in a zebrafish model.

PubMed

Littleton, Robert M; Miller, Matthew; Hove, Jay R

2012-07-23

Consumers are increasingly turning to plant-based complementary and alternative medicines to treat hypercholesterolemia. Many of these treatments are untested and their efficacy is unknown. This multitude of potential remedies necessitates a model system amenable to testing large numbers of organisms that maintains similarity to humans in both mode of drug administration and overall physiology. Here we develop the larval zebrafish (4-30 days post fertilization) as a vertebrate model of dietary plant-based treatment of hypercholesterolemia and test the effects of Crataegus laevigata in this model. Larval zebrafish were fed high cholesterol diets infused with fluorescent sterols and phytomedicines. Plants were ground with mortar and pestle into a fine powder before addition to food. Fluorescent sterols were utilized to optically quantify relative difference in intravascular cholesterol levels between groups of fish. We utilized the Zeiss 7-Live Duo high-speed confocal platform in order to both quantify intravascular sterol fluorescence and to capture video of the heart beat for determination of cardiac output. In this investigation we developed and utilized a larval zebrafish model to investigate dietary plant-based intervention of the pathophysiology of hypercholesterolemia. We found BODIPY-cholesterol effectively labels diet-introduced intravascular cholesterol levels (P < 0.05, Student's t-test). We also established that zebrafish cardiac output declines as cholesterol dose increases (difference between 0.1% and 8% (w/w) high cholesterol diet-treated cardiac output significant at P < 0.05, 1-way ANOVA). Using this model, we found hawthorn leaves and flowers significantly reduce intravascular cholesterol levels (P < 0.05, 1-way ANOVA) and interact with cholesterol to impact cardiac output in hypercholesterolemic fish (2-way ANOVA, P < 0.05 for interaction effect). The results of this study demonstrate that the larval zebrafish has the potential to become a powerful model to test plant based dietary intervention of hypercholesterolemia. Using this model we have shown that hawthorn leaves and flowers have the potential to affect cardiac output as well as intravascular cholesterol levels. Further, our observation that hawthorn leaves and flowers interact with cholesterol to impact cardiac output indicates that the physiological effects of hawthorn may depend on diet.

On the hydrologic adjustment of climate-model projections: The potential pitfall of potential evapotranspiration

USGS Publications Warehouse

Milly, P.C.D.; Dunne, K.A.

2011-01-01

Hydrologic models often are applied to adjust projections of hydroclimatic change that come from climate models. Such adjustment includes climate-bias correction, spatial refinement ("downscaling"), and consideration of the roles of hydrologic processes that were neglected in the climate model. Described herein is a quantitative analysis of the effects of hydrologic adjustment on the projections of runoff change associated with projected twenty-first-century climate change. In a case study including three climate models and 10 river basins in the contiguous United States, the authors find that relative (i.e., fractional or percentage) runoff change computed with hydrologic adjustment more often than not was less positive (or, equivalently, more negative) than what was projected by the climate models. The dominant contributor to this decrease in runoff was a ubiquitous change in runoff (median 211%) caused by the hydrologic model's apparent amplification of the climate-model-implied growth in potential evapotranspiration. Analysis suggests that the hydrologic model, on the basis of the empirical, temperature-based modified Jensen-Haise formula, calculates a change in potential evapotranspiration that is typically 3 times the change implied by the climate models, which explicitly track surface energy budgets. In comparison with the amplification of potential evapotranspiration, central tendencies of other contributions from hydrologic adjustment (spatial refinement, climate-bias adjustment, and process refinement) were relatively small. The authors' findings highlight the need for caution when projecting changes in potential evapotranspiration for use in hydrologic models or drought indices to evaluate climatechange impacts on water. Copyright ?? 2011, Paper 15-001; 35,952 words, 3 Figures, 0 Animations, 1 Tables.

State-and-transition models for heterogeneous landscapes: A strategy for development and application

USDA-ARS?s Scientific Manuscript database

Interpretation of assessment and monitoring data requires information about reference conditions and ecological resilience. Reference conditions used as benchmarks can be specified via potential-based land classifications (e.g., ecological sites) that describe the plant communities potentially obser...

Polyhydroxyalkanoates in waste activated sludge enhances anaerobic methane production through improving biochemical methane potential instead of hydrolysis rate.

PubMed

Wang, Qilin; Sun, Jing; Zhang, Chang; Xie, Guo-Jun; Zhou, Xu; Qian, Jin; Yang, Guojing; Zeng, Guangming; Liu, Yiqi; Wang, Dongbo

2016-01-21

Anaerobic sludge digestion is the main technology for sludge reduction and stabilization prior to sludge disposal. Nevertheless, methane production from anaerobic digestion of waste activated sludge (WAS) is often restricted by the poor biochemical methane potential and slow hydrolysis rate of WAS. This work systematically investigated the effect of PHA levels of WAS on anaerobic methane production, using both experimental and mathematical modeling approaches. Biochemical methane potential tests showed that methane production increased with increased PHA levels in WAS. Model-based analysis suggested that the PHA-based method enhanced methane production by improving biochemical methane potential of WAS, with the highest enhancement being around 40% (from 192 to 274 L CH4/kg VS added; VS: volatile solid) when the PHA levels increased from 21 to 143 mg/g VS. In contrast, the hydrolysis rate (approximately 0.10 d(-1)) was not significantly affected by the PHA levels. Economic analysis suggested that the PHA-based method could save $1.2/PE/y (PE: population equivalent) in a typical wastewater treatment plant (WWTP). The PHA-based method can be easily integrated into the current WWTP to enhance methane production, thereby providing a strong support to the on-going paradigm shift in wastewater management from pollutant removal to resource recovery.

Polyhydroxyalkanoates in waste activated sludge enhances anaerobic methane production through improving biochemical methane potential instead of hydrolysis rate

PubMed Central

Wang, Qilin; Sun, Jing; Zhang, Chang; Xie, Guo-Jun; Zhou, Xu; Qian, Jin; Yang, Guojing; Zeng, Guangming; Liu, Yiqi; Wang, Dongbo

2016-01-01

Anaerobic sludge digestion is the main technology for sludge reduction and stabilization prior to sludge disposal. Nevertheless, methane production from anaerobic digestion of waste activated sludge (WAS) is often restricted by the poor biochemical methane potential and slow hydrolysis rate of WAS. This work systematically investigated the effect of PHA levels of WAS on anaerobic methane production, using both experimental and mathematical modeling approaches. Biochemical methane potential tests showed that methane production increased with increased PHA levels in WAS. Model-based analysis suggested that the PHA-based method enhanced methane production by improving biochemical methane potential of WAS, with the highest enhancement being around 40% (from 192 to 274 L CH4/kg VS added; VS: volatile solid) when the PHA levels increased from 21 to 143 mg/g VS. In contrast, the hydrolysis rate (approximately 0.10 d−1) was not significantly affected by the PHA levels. Economic analysis suggested that the PHA-based method could save $1.2/PE/y (PE: population equivalent) in a typical wastewater treatment plant (WWTP). The PHA-based method can be easily integrated into the current WWTP to enhance methane production, thereby providing a strong support to the on-going paradigm shift in wastewater management from pollutant removal to resource recovery. PMID:26791952

Polyhydroxyalkanoates in waste activated sludge enhances anaerobic methane production through improving biochemical methane potential instead of hydrolysis rate

NASA Astrophysics Data System (ADS)

Wang, Qilin; Sun, Jing; Zhang, Chang; Xie, Guo-Jun; Zhou, Xu; Qian, Jin; Yang, Guojing; Zeng, Guangming; Liu, Yiqi; Wang, Dongbo

2016-01-01

Anaerobic sludge digestion is the main technology for sludge reduction and stabilization prior to sludge disposal. Nevertheless, methane production from anaerobic digestion of waste activated sludge (WAS) is often restricted by the poor biochemical methane potential and slow hydrolysis rate of WAS. This work systematically investigated the effect of PHA levels of WAS on anaerobic methane production, using both experimental and mathematical modeling approaches. Biochemical methane potential tests showed that methane production increased with increased PHA levels in WAS. Model-based analysis suggested that the PHA-based method enhanced methane production by improving biochemical methane potential of WAS, with the highest enhancement being around 40% (from 192 to 274 L CH4/kg VS added; VS: volatile solid) when the PHA levels increased from 21 to 143 mg/g VS. In contrast, the hydrolysis rate (approximately 0.10 d-1) was not significantly affected by the PHA levels. Economic analysis suggested that the PHA-based method could save $1.2/PE/y (PE: population equivalent) in a typical wastewater treatment plant (WWTP). The PHA-based method can be easily integrated into the current WWTP to enhance methane production, thereby providing a strong support to the on-going paradigm shift in wastewater management from pollutant removal to resource recovery.

Potential influences of neglecting aerosol effects on the NCEP GFS precipitation forecast

NASA Astrophysics Data System (ADS)

Jiang, Mengjiao; Feng, Jinqin; Li, Zhanqing; Sun, Ruiyu; Hou, Yu-Tai; Zhu, Yuejian; Wan, Bingcheng; Guo, Jianping; Cribb, Maureen

2017-11-01

Aerosol-cloud interactions (ACIs) have been widely recognized as a factor affecting precipitation. However, they have not been considered in the operational National Centers for Environmental Predictions Global Forecast System model. We evaluated the potential impact of neglecting ACI on the operational rainfall forecast using ground-based and satellite observations and model reanalysis. The Climate Prediction Center unified gauge-based precipitation analysis and the Modern-Era Retrospective analysis for Research and Applications Version 2 aerosol reanalysis were used to evaluate the forecast in three countries for the year 2015. The overestimation of light rain (47.84 %) and underestimation of heavier rain (31.83, 52.94, and 65.74 % for moderate rain, heavy rain, and very heavy rain, respectively) from the model are qualitatively consistent with the potential errors arising from not accounting for ACI, although other factors cannot be totally ruled out. The standard deviation of the forecast bias was significantly correlated with aerosol optical depth in Australia, the US, and China. To gain further insight, we chose the province of Fujian in China to pursue a more insightful investigation using a suite of variables from gauge-based observations of precipitation, visibility, water vapor, convective available potential energy (CAPE), and satellite datasets. Similar forecast biases were found: over-forecasted light rain and under-forecasted heavy rain. Long-term analyses revealed an increasing trend in heavy rain in summer and a decreasing trend in light rain in other seasons, accompanied by a decreasing trend in visibility, no trend in water vapor, and a slight increasing trend in summertime CAPE. More aerosols decreased cloud effective radii for cases where the liquid water path was greater than 100 g m-2. All findings are consistent with the effects of ACI, i.e., where aerosols inhibit the development of shallow liquid clouds and invigorate warm-base mixed-phase clouds (especially in summertime), which in turn affects precipitation. While we cannot establish rigorous causal relations based on the analyses presented in this study, the significant rainfall forecast bias seen in operational weather forecast model simulations warrants consideration in future model improvements.

Adapting APSIM to model the physiology and genetics of complex adaptive traits in field crops.

PubMed

Hammer, Graeme L; van Oosterom, Erik; McLean, Greg; Chapman, Scott C; Broad, Ian; Harland, Peter; Muchow, Russell C

2010-05-01

Progress in molecular plant breeding is limited by the ability to predict plant phenotype based on its genotype, especially for complex adaptive traits. Suitably constructed crop growth and development models have the potential to bridge this predictability gap. A generic cereal crop growth and development model is outlined here. It is designed to exhibit reliable predictive skill at the crop level while also introducing sufficient physiological rigour for complex phenotypic responses to become emergent properties of the model dynamics. The approach quantifies capture and use of radiation, water, and nitrogen within a framework that predicts the realized growth of major organs based on their potential and whether the supply of carbohydrate and nitrogen can satisfy that potential. The model builds on existing approaches within the APSIM software platform. Experiments on diverse genotypes of sorghum that underpin the development and testing of the adapted crop model are detailed. Genotypes differing in height were found to differ in biomass partitioning among organs and a tall hybrid had significantly increased radiation use efficiency: a novel finding in sorghum. Introducing these genetic effects associated with plant height into the model generated emergent simulated phenotypic differences in green leaf area retention during grain filling via effects associated with nitrogen dynamics. The relevance to plant breeding of this capability in complex trait dissection and simulation is discussed.

Argumentation in Science Education: A Model-based Framework

NASA Astrophysics Data System (ADS)

Böttcher, Florian; Meisert, Anke

2011-02-01

The goal of this article is threefold: First, the theoretical background for a model-based framework of argumentation to describe and evaluate argumentative processes in science education is presented. Based on the general model-based perspective in cognitive science and the philosophy of science, it is proposed to understand arguments as reasons for the appropriateness of a theoretical model which explains a certain phenomenon. Argumentation is considered to be the process of the critical evaluation of such a model if necessary in relation to alternative models. Secondly, some methodological details are exemplified for the use of a model-based analysis in the concrete classroom context. Third, the application of the approach in comparison with other analytical models will be presented to demonstrate the explicatory power and depth of the model-based perspective. Primarily, the framework of Toulmin to structurally analyse arguments is contrasted with the approach presented here. It will be demonstrated how common methodological and theoretical problems in the context of Toulmin's framework can be overcome through a model-based perspective. Additionally, a second more complex argumentative sequence will also be analysed according to the invented analytical scheme to give a broader impression of its potential in practical use.

Assessing skill of a global bimonthly streamflow ensemble prediction system

NASA Astrophysics Data System (ADS)

van Dijk, A. I.; Peña-Arancibia, J.; Sheffield, J.; Wood, E. F.

2011-12-01

Ideally, a seasonal streamflow forecasting system might be conceived of as a system that ingests skillful climate forecasts from general circulation models and propagates these through thoroughly calibrated hydrological models that are initialised using hydrometric observations. In practice, there are practical problems with each of these aspects. Instead, we analysed whether a comparatively simple hydrological model-based Ensemble Prediction System (EPS) can provide global bimonthly streamflow forecasts with some skill and if so, under what circumstances the greatest skill may be expected. The system tested produces ensemble forecasts for each of six annual bimonthly periods based on the previous 30 years of global daily gridded 1° resolution climate variables and an initialised global hydrological model. To incorporate some of the skill derived from ocean conditions, a post-EPS analog method was used to sample from the ensemble based on El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), North Atlantic Oscillation (NAO) and Pacific Decadal Oscillation (PDO) index values observed prior to the forecast. Forecasts skill was assessed through a hind-casting experiment for the period 1979-2008. Potential skill was calculated with reference to a model run with the actual forcing for the forecast period (the 'perfect' model) and was compared to actual forecast skill calculated for each of the six forecast times for an average 411 Australian and 51 pan-tropical catchments. Significant potential skill in bimonthly forecasts was largely limited to northern regions during the snow melt period, seasonally wet tropical regions at the transition of wet to dry season, and the Indonesian region where rainfall is well correlated to ENSO. The actual skill was approximately 34-50% of the potential skill. We attribute this primarily to limitations in the model structure, parameterisation and global forcing data. Use of better climate forecasts and remote sensing observations of initial catchment conditions should help to increase actual skill in future. Future work also could address the potential skill gain from using weather and climate forecasts and from a calibrated and/or alternative hydrological model or model ensemble. The approach and data might be useful as a benchmark for joint seasonal forecasting experiments planned under GEWEX.

Subgrid-scale Condensation Modeling for Entropy-based Large Eddy Simulations of Clouds

NASA Astrophysics Data System (ADS)

Kaul, C. M.; Schneider, T.; Pressel, K. G.; Tan, Z.

2015-12-01

An entropy- and total water-based formulation of LES thermodynamics, such as that used by the recently developed code PyCLES, is advantageous from physical and numerical perspectives. However, existing closures for subgrid-scale thermodynamic fluctuations assume more traditional choices for prognostic thermodynamic variables, such as liquid potential temperature, and are not directly applicable to entropy-based modeling. Since entropy and total water are generally nonlinearly related to diagnosed quantities like temperature and condensate amounts, neglecting their small-scale variability can lead to bias in simulation results. Here we present the development of a subgrid-scale condensation model suitable for use with entropy-based thermodynamic formulations.

Frequency-Dependent Selection: The High Potential for Permanent Genetic Variation in the Diallelic, Pairwise Interaction Model

PubMed Central

Asmussen, M. A.; Basnayake, E.

1990-01-01

A detailed analytic and numerical study is made of the potential for permanent genetic variation in frequency-dependent models based on pairwise interactions among genotypes at a single diallelic locus. The full equilibrium structure and qualitative gene-frequency dynamics are derived analytically for a symmetric model, in which pairwise fitnesses are chiefly determined by the genetic similarity of the individuals involved. This is supplemented by an extensive numerical investigation of the general model, the symmetric model, and nine other special cases. Together the results show that there is a high potential for permanent genetic diversity in the pairwise interaction model, and provide insight into the extent to which various forms of genotypic interactions enhance or reduce this potential. Technically, although two stable polymorphic equilibria are possible, the increased likelihood of maintaining both alleles, and the poor performance of protected polymorphism conditions as a measure of this likelihood, are primarily due to a greater variety and frequency of equilibrium patterns with one stable polymorphic equilibrium, in conjunction with a disproportionately large domain of attraction for stable internal equilibria. PMID:2341034

Modeling and MBL: Software Tools for Science.

ERIC Educational Resources Information Center

Tinker, Robert F.

Recent technological advances and new software packages put unprecedented power for experimenting and theory-building in the hands of students at all levels. Microcomputer-based laboratory (MBL) and model-solving tools illustrate the educational potential of the technology. These tools include modeling software and three MBL packages (which are…

PREDICTING ER BINDING AFFINITY FOR EDC RANKING AND PRIORITIZATION: A COMPARISON OF THREE MODELS

EPA Science Inventory

A comparative analysis of how three COREPA models for ER binding affinity performed when used to predict potential estrogen receptor (ER) ligands is presented. Models I and II were developed based on training sets of 232 and 279 rat ER binding affinity measurements, respectively....

A Systems Approach to the Estimation of Ecosystem and Human Health Stressors in Air, Land and Water

EPA Science Inventory

A model linkage paradigm, based on the nitrogen cascade, is introduced. This general paradigm is then adapted to specific multi-media nitrogen issues and specific models to be linked. An example linked modeling system addressing potential nitrogen responses to biofuel-driven co...

Atomistic modeling for interfacial properties of Ni-Al-V ternary system

NASA Astrophysics Data System (ADS)

Dong, Wei-ping; Lee, Byeong-Joo; Chen, Zheng

2014-05-01

Interatomic potentials for Ni-Al-V ternary systems have been developed based on the second-nearest-neighbor modified embedded-atom method potential formalism. The potentials can describe various fundamental physical properties of the relevant materials in good agreement with experimental information. The potential is utilized for an atomistic computation of interfacial properties of Ni-Al-V alloys. It is found that vanadium atoms segregate on the γ-fcc/L12 interface and this segregation affects the interfacial properties. The applicability of the atomistic approach to an elaborate alloy design of advanced Ni-based superalloys through the investigation of the effect of alloying elements on interfacial properties is discussed.

The potential energy landscape contribution to the dynamic heat capacity

NASA Astrophysics Data System (ADS)

Brown, Jonathan R.; McCoy, John D.

2011-05-01

The dynamic heat capacity of a simple polymeric, model glassformer was computed using molecular dynamics simulations by sinusoidally driving the temperature and recording the resultant energy. The underlying potential energy landscape of the system was probed by taking a time series of particle positions and quenching them. The resulting dynamic heat capacity demonstrates that the long time relaxation is the direct result of dynamics resulting from the potential energy landscape. Moreover, the equilibrium (low frequency) portion of the potential energy landscape contribution to the heat capacity is found to increase rapidly at low temperatures and at high packing fractions. This increase in the heat capacity is explained by a statistical mechanical model based on the distribution of minima in the potential energy landscape.

Design of a global soil moisture initialization procedure for the simple biosphere model

NASA Technical Reports Server (NTRS)

Liston, G. E.; Sud, Y. C.; Walker, G. K.

1993-01-01

Global soil moisture and land-surface evapotranspiration fields are computed using an analysis scheme based on the Simple Biosphere (SiB) soil-vegetation-atmosphere interaction model. The scheme is driven with observed precipitation, and potential evapotranspiration, where the potential evapotranspiration is computed following the surface air temperature-potential evapotranspiration regression of Thomthwaite (1948). The observed surface air temperature is corrected to reflect potential (zero soil moisture stress) conditions by letting the ratio of actual transpiration to potential transpiration be a function of normalized difference vegetation index (NDVI). Soil moisture, evapotranspiration, and runoff data are generated on a daily basis for a 10-year period, January 1979 through December 1988, using observed precipitation gridded at a 4 deg by 5 deg resolution.

Entropic elasticity based coarse-grained model of lipid membranes

NASA Astrophysics Data System (ADS)

Feng, Shuo; Hu, Yucai; Liang, Haiyi

2018-04-01

Various models for lipid bilayer membranes have been presented to investigate their morphologies. Among them, the aggressive coarse-grained models, where the membrane is represented by a single layer of particles, are computationally efficient and of practical importance for simulating membrane dynamics at the microscopic scale. In these models, soft potentials between particle pairs are used to maintain the fluidity of membranes, but the underlying mechanism of the softening requires further clarification. We have analyzed the membrane area decrease due to thermal fluctuations, and the results demonstrate that the intraparticle part of entropic elasticity is responsible for the softening of the potential. Based on the stretching response of the membrane, a bottom-up model is developed with an entropic effect explicitly involved. The model reproduces several essential properties of the lipid membrane, including the fluid state and a plateau in the stretching curve. In addition, the area compressibility modulus, bending rigidity, and spontaneous curvature display linear dependence on model parameters. As a demonstration, we have investigated the closure and morphology evolution of membrane systems driven by spontaneous curvature, and vesicle shapes observed experimentally are faithfully reproduced.

Collision Models for Particle Orbit Code on SSX

NASA Astrophysics Data System (ADS)

Fisher, M. W.; Dandurand, D.; Gray, T.; Brown, M. R.; Lukin, V. S.

2011-10-01

Coulomb collision models are being developed and incorporated into the Hamiltonian particle pushing code (PPC) for applications to the Swarthmore Spheromak eXperiment (SSX). A Monte Carlo model based on that of Takizuka and Abe [JCP 25, 205 (1977)] performs binary collisions between test particles and thermal plasma field particles randomly drawn from a stationary Maxwellian distribution. A field-based electrostatic fluctuation model scatters particles from a spatially uniform random distribution of positive and negative spherical potentials generated throughout the plasma volume. The number, radii, and amplitude of these potentials are chosen to mimic the correct particle diffusion statistics without the use of random particle draws or collision frequencies. An electromagnetic fluctuating field model will be presented, if available. These numerical collision models will be benchmarked against known analytical solutions, including beam diffusion rates and Spitzer resistivity, as well as each other. The resulting collisional particle orbit models will be used to simulate particle collection with electrostatic probes in the SSX wind tunnel, as well as particle confinement in typical SSX fields. This work has been supported by US DOE, NSF and ONR.

Applying quantitative adiposity feature analysis models to predict benefit of bevacizumab-based chemotherapy in ovarian cancer patients

NASA Astrophysics Data System (ADS)

Wang, Yunzhi; Qiu, Yuchen; Thai, Theresa; More, Kathleen; Ding, Kai; Liu, Hong; Zheng, Bin

2016-03-01

How to rationally identify epithelial ovarian cancer (EOC) patients who will benefit from bevacizumab or other antiangiogenic therapies is a critical issue in EOC treatments. The motivation of this study is to quantitatively measure adiposity features from CT images and investigate the feasibility of predicting potential benefit of EOC patients with or without receiving bevacizumab-based chemotherapy treatment using multivariate statistical models built based on quantitative adiposity image features. A dataset involving CT images from 59 advanced EOC patients were included. Among them, 32 patients received maintenance bevacizumab after primary chemotherapy and the remaining 27 patients did not. We developed a computer-aided detection (CAD) scheme to automatically segment subcutaneous fat areas (VFA) and visceral fat areas (SFA) and then extracted 7 adiposity-related quantitative features. Three multivariate data analysis models (linear regression, logistic regression and Cox proportional hazards regression) were performed respectively to investigate the potential association between the model-generated prediction results and the patients' progression-free survival (PFS) and overall survival (OS). The results show that using all 3 statistical models, a statistically significant association was detected between the model-generated results and both of the two clinical outcomes in the group of patients receiving maintenance bevacizumab (p<0.01), while there were no significant association for both PFS and OS in the group of patients without receiving maintenance bevacizumab. Therefore, this study demonstrated the feasibility of using quantitative adiposity-related CT image features based statistical prediction models to generate a new clinical marker and predict the clinical outcome of EOC patients receiving maintenance bevacizumab-based chemotherapy.

Reconstruction of the action potential of ventricular myocardial fibres

PubMed Central

Beeler, G. W.; Reuter, H.

1977-01-01

1. A mathematical model of membrane action potentials of mammalian ventricular myocardial fibres is described. The reconstruction model is based as closely as possible on ionic currents which have been measured by the voltage-clamp method. 2. Four individual components of ionic current were formulated mathematically in terms of Hodgkin—Huxley type equations. The model incorporates two voltage- and time-dependent inward currents, the excitatory inward sodium current, iNa, and a secondary or slow inward current, is, primarily carried by calcium ions. A time-independent outward potassium current, iK1, exhibiting inward-going rectification, and a voltage- and time-dependent outward current, ix1, primarily carried by potassium ions, are further elements of the model. 3. The iNa is primarily responsible for the rapid upstroke of the action potential, while the other current components determine the configuration of the plateau of the action potential and the re-polarization phase. The relative importance of inactivation of is and of activation of ix1 for termination of the plateau is evaluated by the model. 4. Experimental phenomena like slow recovery of the sodium system from inactivation, frequency dependence of the action potential duration, all-or-nothing re-polarization, membrane oscillations are adequately described by the model. 5. Possible inadequacies and shortcomings of the model are discussed. PMID:874889

How Many Wolves (Canis lupus) Fit into Germany? The Role of Assumptions in Predictive Rule-Based Habitat Models for Habitat Generalists

PubMed Central

Fechter, Dominik; Storch, Ilse

2014-01-01

Due to legislative protection, many species, including large carnivores, are currently recolonizing Europe. To address the impending human-wildlife conflicts in advance, predictive habitat models can be used to determine potentially suitable habitat and areas likely to be recolonized. As field data are often limited, quantitative rule based models or the extrapolation of results from other studies are often the techniques of choice. Using the wolf (Canis lupus) in Germany as a model for habitat generalists, we developed a habitat model based on the location and extent of twelve existing wolf home ranges in Eastern Germany, current knowledge on wolf biology, different habitat modeling techniques and various input data to analyze ten different input parameter sets and address the following questions: (1) How do a priori assumptions and different input data or habitat modeling techniques affect the abundance and distribution of potentially suitable wolf habitat and the number of wolf packs in Germany? (2) In a synthesis across input parameter sets, what areas are predicted to be most suitable? (3) Are existing wolf pack home ranges in Eastern Germany consistent with current knowledge on wolf biology and habitat relationships? Our results indicate that depending on which assumptions on habitat relationships are applied in the model and which modeling techniques are chosen, the amount of potentially suitable habitat estimated varies greatly. Depending on a priori assumptions, Germany could accommodate between 154 and 1769 wolf packs. The locations of the existing wolf pack home ranges in Eastern Germany indicate that wolves are able to adapt to areas densely populated by humans, but are limited to areas with low road densities. Our analysis suggests that predictive habitat maps in general, should be interpreted with caution and illustrates the risk for habitat modelers to concentrate on only one selection of habitat factors or modeling technique. PMID:25029506

Predicting the potential distribution of the amphibian pathogen Batrachochytrium dendrobatidis in East and Southeast Asia.

PubMed

Moriguchi, Sachiko; Tominaga, Atsushi; Irwin, Kelly J; Freake, Michael J; Suzuki, Kazutaka; Goka, Koichi

2015-04-08

Batrachochytrium dendrobatidis (Bd) is the pathogen responsible for chytridiomycosis, a disease that is associated with a worldwide amphibian population decline. In this study, we predicted the potential distribution of Bd in East and Southeast Asia based on limited occurrence data. Our goal was to design an effective survey area where efforts to detect the pathogen can be focused. We generated ecological niche models using the maximum-entropy approach, with alleviation of multicollinearity and spatial autocorrelation. We applied eigenvector-based spatial filters as independent variables, in addition to environmental variables, to resolve spatial autocorrelation, and compared the model's accuracy and the degree of spatial autocorrelation with those of a model estimated using only environmental variables. We were able to identify areas of high suitability for Bd with accuracy. Among the environmental variables, factors related to temperature and precipitation were more effective in predicting the potential distribution of Bd than factors related to land use and cover type. Our study successfully predicted the potential distribution of Bd in East and Southeast Asia. This information should now be used to prioritize survey areas and generate a surveillance program to detect the pathogen.

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

Migunov, V., E-mail: v.migunov@fz-juelich.de; Dunin-Borkowski, R. E.; London, A.

The one-dimensional charge density distribution along an electrically biased Fe atom probe needle is measured using a model-independent approach based on off-axis electron holography in the transmission electron microscope. Both the mean inner potential and the magnetic contribution to the phase shift are subtracted by taking differences between electron-optical phase images recorded with different voltages applied to the needle. The measured one-dimensional charge density distribution along the needle is compared with a similar result obtained using model-based fitting of the phase shift surrounding the needle. On the assumption of cylindrical symmetry, it is then used to infer the three-dimensional electricmore » field and electrostatic potential around the needle with ∼10 nm spatial resolution, without needing to consider either the influence of the perturbed reference wave or the extension of the projected potential outside the field of view of the electron hologram. The present study illustrates how a model-independent approach can be used to measure local variations in charge density in a material using electron holography in the presence of additional contributions to the phase, such as those arising from changes in mean inner potential and specimen thickness.« less

Analysis of the physical atomic forces between noble gas atoms, alkali ions and halogen ions

NASA Technical Reports Server (NTRS)

Wilson, J. W.; Heinbockel, J. H.; Outlaw, R. A.

1986-01-01

The physical forces between atoms and molecules are important in a number of processes of practical importance, including line broadening in radiative processes, gas and crystal properties, adhesion, and thin films. The components of the physical forces between noble gas atoms, alkali ions, and halogen ions are analyzed and a data base for the dispersion forces is developed from the literature based on evaluations with the harmonic oscillator dispersion model for higher order coefficients. The Zener model of the repulsive core is used in the context of the recent asymptotic wave functions of Handler and Smith; and an effective ionization potential within the Handler and Smith wave functions is defined to analyze the two body potential data of Waldman and Gordon, the alkali-halide molecular data, and the noble gas crystal and salt crystal data. A satisfactory global fit to this molecular and crystal data is then reproduced by the model to within several percent. Surface potentials are evaluated for noble gas atoms on noble gas and salt crystal surfaces with surface tension neglected. Within this context, the noble gas surface potentials on noble gas and salt crystals are considered to be accurate to within several percent.

New interatomic potential for Mg–Al–Zn alloys with specific application to dilute Mg-based alloys

NASA Astrophysics Data System (ADS)

Dickel, Doyl E.; Baskes, Michael I.; Aslam, Imran; Barrett, Christopher D.

2018-06-01

Because of its very large c/a ratio, zinc has proven to be a difficult element to model using semi-empirical classical potentials. It has been shown, in particular, that for the modified embedded atom method (MEAM), a potential cannot simultaneously have an hcp ground state and c/a ratio greater than ideal. As an alloying element, however, useful zinc potentials can be generated by relaxing the condition that hcp be the lowest energy structure. In this paper, we present a MEAM zinc potential, which gives accurate material properties for the pure state, as well as a MEAM ternary potential for the Mg–Al–Zn system which will allow the atomistic modeling of a wide class of alloys containing zinc. The effects of zinc in simple Mg–Zn for this potential is demonstrated and these results verify the accuracy for the new potential in these systems.

Potentiality Prediction of Electric Power Replacement Based on Power Market Development Strategy

NASA Astrophysics Data System (ADS)

Miao, Bo; Yang, Shuo; Liu, Qiang; Lin, Jingyi; Zhao, Le; Liu, Chang; Li, Bin

2017-05-01

The application of electric power replacement plays an important role in promoting the development of energy conservation and emission reduction in our country. To exploit the potentiality of regional electric power replacement, the regional GDP (gross domestic product) and energy consumption are taken as potentiality evaluation indicators. The principal component factors are extracted with PCA (principal component analysis), and the integral potentiality analysis is made to the potentiality of electric power replacement in the national various regions; a region is taken as a research object, and the potentiality of electric power replacement is defined and quantified. The analytical model for the potentiality of multi-scenario electric power replacement is developed, and prediction is made to the energy consumption with the grey prediction model. The relevant theoretical research is utilized to realize prediction analysis on the potentiality amount of multi-scenario electric power replacement.

A comparative assessment of GIS-based data mining models and a novel ensemble model in groundwater well potential mapping

NASA Astrophysics Data System (ADS)

Naghibi, Seyed Amir; Moghaddam, Davood Davoodi; Kalantar, Bahareh; Pradhan, Biswajeet; Kisi, Ozgur

2017-05-01

In recent years, application of ensemble models has been increased tremendously in various types of natural hazard assessment such as landslides and floods. However, application of this kind of robust models in groundwater potential mapping is relatively new. This study applied four data mining algorithms including AdaBoost, Bagging, generalized additive model (GAM), and Naive Bayes (NB) models to map groundwater potential. Then, a novel frequency ratio data mining ensemble model (FREM) was introduced and evaluated. For this purpose, eleven groundwater conditioning factors (GCFs), including altitude, slope aspect, slope angle, plan curvature, stream power index (SPI), river density, distance from rivers, topographic wetness index (TWI), land use, normalized difference vegetation index (NDVI), and lithology were mapped. About 281 well locations with high potential were selected. Wells were randomly partitioned into two classes for training the models (70% or 197) and validating them (30% or 84). AdaBoost, Bagging, GAM, and NB algorithms were employed to get groundwater potential maps (GPMs). The GPMs were categorized into potential classes using natural break method of classification scheme. In the next stage, frequency ratio (FR) value was calculated for the output of the four aforementioned models and were summed, and finally a GPM was produced using FREM. For validating the models, area under receiver operating characteristics (ROC) curve was calculated. The ROC curve for prediction dataset was 94.8, 93.5, 92.6, 92.0, and 84.4% for FREM, Bagging, AdaBoost, GAM, and NB models, respectively. The results indicated that FREM had the best performance among all the models. The better performance of the FREM model could be related to reduction of over fitting and possible errors. Other models such as AdaBoost, Bagging, GAM, and NB also produced acceptable performance in groundwater modelling. The GPMs produced in the current study may facilitate groundwater exploitation by determining high and very high groundwater potential zones.

Calculation of single chain cellulose elasticity using fully atomistic modeling

Treesearch

Xiawa Wu; Robert J. Moon; Ashlie Martini

2011-01-01

Cellulose nanocrystals, a potential base material for green nanocomposites, are ordered bundles of cellulose chains. The properties of these chains have been studied for many years using atomic-scale modeling. However, model predictions are difficult to interpret because of the significant dependence of predicted properties on model details. The goal of this study is...

Effects of large vessel on temperature distribution based on photothermal coupling interaction model

NASA Astrophysics Data System (ADS)

Li, Zhifang; Zhang, Xiyang; Li, Zuoran; Li, Hui

2016-10-01

This paper is based on the finite element analysis method for studying effects of large blood vessel on temperature based on photothermal coupling interaction model, and it couples the physical field of optical transmission with the physical field of heat transfer in biological tissue by using COMSOL Multiphysics 4.4 software. The results demonstrate the cooling effect of large blood vessel, which can be potential application for the treatment of liver tumors.

MODELING DYNAMIC VEGETATION RESPONSE TO RAPID CLIMATE CHANGE USING BIOCLIMATIC CLASSIFICATION

EPA Science Inventory

Modeling potential global redistribution of terrestrial vegetation frequently is based on bioclimatic classifications which relate static regional vegetation zones (biomes) to a set of static climate parameters. The equilibrium character of the relationships limits our confidence...

Differential geometry based solvation model. III. Quantum formulation

PubMed Central

Chen, Zhan; Wei, Guo-Wei

2011-01-01

Solvation is of fundamental importance to biomolecular systems. Implicit solvent models, particularly those based on the Poisson-Boltzmann equation for electrostatic analysis, are established approaches for solvation analysis. However, ad hoc solvent-solute interfaces are commonly used in the implicit solvent theory. Recently, we have introduced differential geometry based solvation models which allow the solvent-solute interface to be determined by the variation of a total free energy functional. Atomic fixed partial charges (point charges) are used in our earlier models, which depends on existing molecular mechanical force field software packages for partial charge assignments. As most force field models are parameterized for a certain class of molecules or materials, the use of partial charges limits the accuracy and applicability of our earlier models. Moreover, fixed partial charges do not account for the charge rearrangement during the solvation process. The present work proposes a differential geometry based multiscale solvation model which makes use of the electron density computed directly from the quantum mechanical principle. To this end, we construct a new multiscale total energy functional which consists of not only polar and nonpolar solvation contributions, but also the electronic kinetic and potential energies. By using the Euler-Lagrange variation, we derive a system of three coupled governing equations, i.e., the generalized Poisson-Boltzmann equation for the electrostatic potential, the generalized Laplace-Beltrami equation for the solvent-solute boundary, and the Kohn-Sham equations for the electronic structure. We develop an iterative procedure to solve three coupled equations and to minimize the solvation free energy. The present multiscale model is numerically validated for its stability, consistency and accuracy, and is applied to a few sets of molecules, including a case which is difficult for existing solvation models. Comparison is made to many other classic and quantum models. By using experimental data, we show that the present quantum formulation of our differential geometry based multiscale solvation model improves the prediction of our earlier models, and outperforms some explicit solvation model. PMID:22112067

Evaluation of in silico tools to predict the skin sensitization potential of chemicals.

PubMed

Verheyen, G R; Braeken, E; Van Deun, K; Van Miert, S

2017-01-01

Public domain and commercial in silico tools were compared for their performance in predicting the skin sensitization potential of chemicals. The packages were either statistical based (Vega, CASE Ultra) or rule based (OECD Toolbox, Toxtree, Derek Nexus). In practice, several of these in silico tools are used in gap filling and read-across, but here their use was limited to make predictions based on presence/absence of structural features associated to sensitization. The top 400 ranking substances of the ATSDR 2011 Priority List of Hazardous Substances were selected as a starting point. Experimental information was identified for 160 chemically diverse substances (82 positive and 78 negative). The prediction for skin sensitization potential was compared with the experimental data. Rule-based tools perform slightly better, with accuracies ranging from 0.6 (OECD Toolbox) to 0.78 (Derek Nexus), compared with statistical tools that had accuracies ranging from 0.48 (Vega) to 0.73 (CASE Ultra - LLNA weak model). Combining models increased the performance, with positive and negative predictive values up to 80% and 84%, respectively. However, the number of substances that were predicted positive or negative for skin sensitization in both models was low. Adding more substances to the dataset will increase the confidence in the conclusions reached. The insights obtained in this evaluation are incorporated in a web database www.asopus.weebly.com that provides a potential end user context for the scope and performance of different in silico tools with respect to a common dataset of curated skin sensitization data.

A semi-analytical bearing model considering outer race flexibility for model based bearing load monitoring

NASA Astrophysics Data System (ADS)

Kerst, Stijn; Shyrokau, Barys; Holweg, Edward

2018-05-01

This paper proposes a novel semi-analytical bearing model addressing flexibility of the bearing outer race structure. It furthermore presents the application of this model in a bearing load condition monitoring approach. The bearing model is developed as current computational low cost bearing models fail to provide an accurate description of the more and more common flexible size and weight optimized bearing designs due to their assumptions of rigidity. In the proposed bearing model raceway flexibility is described by the use of static deformation shapes. The excitation of the deformation shapes is calculated based on the modelled rolling element loads and a Fourier series based compliance approximation. The resulting model is computational low cost and provides an accurate description of the rolling element loads for flexible outer raceway structures. The latter is validated by a simulation-based comparison study with a well-established bearing simulation software tool. An experimental study finally shows the potential of the proposed model in a bearing load monitoring approach.

Illustrative visualization of 3D city models

NASA Astrophysics Data System (ADS)

Doellner, Juergen; Buchholz, Henrik; Nienhaus, Marc; Kirsch, Florian

2005-03-01

This paper presents an illustrative visualization technique that provides expressive representations of large-scale 3D city models, inspired by the tradition of artistic and cartographic visualizations typically found in bird"s-eye view and panoramic maps. We define a collection of city model components and a real-time multi-pass rendering algorithm that achieves comprehensible, abstract 3D city model depictions based on edge enhancement, color-based and shadow-based depth cues, and procedural facade texturing. Illustrative visualization provides an effective visual interface to urban spatial information and associated thematic information complementing visual interfaces based on the Virtual Reality paradigm, offering a huge potential for graphics design. Primary application areas include city and landscape planning, cartoon worlds in computer games, and tourist information systems.

Parcels versus pixels: modeling agricultural land use across broad geographic regions using parcel-based field boundaries

USGS Publications Warehouse

Sohl, Terry L.; Dornbierer, Jordan; Wika, Steve; Sayler, Kristi L.; Quenzer, Robert

2017-01-01

Land use and land cover (LULC) change occurs at a local level within contiguous ownership and management units (parcels), yet LULC models primarily use pixel-based spatial frameworks. The few parcel-based models being used overwhelmingly focus on small geographic areas, limiting the ability to assess LULC change impacts at regional to national scales. We developed a modified version of the Forecasting Scenarios of land use change model to project parcel-based agricultural change across a large region in the United States Great Plains. A scenario representing an agricultural biofuel scenario was modeled from 2012 to 2030, using real parcel boundaries based on contiguous ownership and land management units. The resulting LULC projection provides a vastly improved representation of landscape pattern over existing pixel-based models, while simultaneously providing an unprecedented combination of thematic detail and broad geographic extent. The conceptual approach is practical and scalable, with potential use for national-scale projections.

A relational data-knowledge base system and its potential in developing a distributed data-knowledge system

NASA Technical Reports Server (NTRS)

Rahimian, Eric N.; Graves, Sara J.

1988-01-01

A new approach used in constructing a rational data knowledge base system is described. The relational database is well suited for distribution due to its property of allowing data fragmentation and fragmentation transparency. An example is formulated of a simple relational data knowledge base which may be generalized for use in developing a relational distributed data knowledge base system. The efficiency and ease of application of such a data knowledge base management system is briefly discussed. Also discussed are the potentials of the developed model for sharing the data knowledge base as well as the possible areas of difficulty in implementing the relational data knowledge base management system.

Density-Dependent Formulation of Dispersion-Repulsion Interactions in Hybrid Multiscale Quantum/Molecular Mechanics (QM/MM) Models.

PubMed

Curutchet, Carles; Cupellini, Lorenzo; Kongsted, Jacob; Corni, Stefano; Frediani, Luca; Steindal, Arnfinn Hykkerud; Guido, Ciro A; Scalmani, Giovanni; Mennucci, Benedetta

2018-03-13

Mixed multiscale quantum/molecular mechanics (QM/MM) models are widely used to explore the structure, reactivity, and electronic properties of complex chemical systems. Whereas such models typically include electrostatics and potentially polarization in so-called electrostatic and polarizable embedding approaches, respectively, nonelectrostatic dispersion and repulsion interactions are instead commonly described through classical potentials despite their quantum mechanical origin. Here we present an extension of the Tkatchenko-Scheffler semiempirical van der Waals (vdW TS ) scheme aimed at describing dispersion and repulsion interactions between quantum and classical regions within a QM/MM polarizable embedding framework. Starting from the vdW TS expression, we define a dispersion and a repulsion term, both of them density-dependent and consistently based on a Lennard-Jones-like potential. We explore transferable atom type-based parametrization strategies for the MM parameters, based on either vdW TS calculations performed on isolated fragments or on a direct estimation of the parameters from atomic polarizabilities taken from a polarizable force field. We investigate the performance of the implementation by computing self-consistent interaction energies for the S22 benchmark set, designed to represent typical noncovalent interactions in biological systems, in both equilibrium and out-of-equilibrium geometries. Overall, our results suggest that the present implementation is a promising strategy to include dispersion and repulsion in multiscale QM/MM models incorporating their explicit dependence on the electronic density.

Integration of Dynamic Models in Range Operations

NASA Technical Reports Server (NTRS)

Bardina, Jorge; Thirumalainambi, Rajkumar

2004-01-01

This work addresses the various model interactions in real-time to make an efficient internet based decision making tool for Shuttle launch. The decision making tool depends on the launch commit criteria coupled with physical models. Dynamic interaction between a wide variety of simulation applications and techniques, embedded algorithms, and data visualizations are needed to exploit the full potential of modeling and simulation. This paper also discusses in depth details of web based 3-D graphics and applications to range safety. The advantages of this dynamic model integration are secure accessibility and distribution of real time information to other NASA centers.

An in silico algal toxicity model with a wide applicability potential for industrial chemicals and pharmaceuticals.

PubMed

Önlü, Serli; Saçan, Melek Türker

2017-04-01

The authors modeled the 72-h algal toxicity data of hundreds of chemicals with different modes of action as a function of chemical structures. They developed mode of action-based local quantitative structure-toxicity relationship (QSTR) models for nonpolar and polar narcotics as well as a global QSTR model with a wide applicability potential for industrial chemicals and pharmaceuticals. The present study rigorously evaluated the generated models, meeting the Organisation for Economic Co-operation and Development principles of robustness, validity, and transparency. The proposed global model had a broad structural coverage for the toxicity prediction of diverse chemicals (some of which are high-production volume chemicals) with no experimental toxicity data. The global model is potentially useful for endpoint predictions, the evaluation of algal toxicity screening, and the prioritization of chemicals, as well as for the decision of further testing and the development of risk-management measures in a scientific and regulatory frame. Environ Toxicol Chem 2017;36:1012-1019. © 2016 SETAC. © 2016 SETAC.

Projected Changes in Evapotranspiration Rates over Northeast Brazil

NASA Astrophysics Data System (ADS)

Costa, Alexandre; Guimarães, Sullyandro; Vasconcelos, Francisco, Jr.; Sales, Domingo; da Silva, Emerson

2015-04-01

Climate simulations were performed using a regional model (Regional Atmospheric Modeling System, RAMS 6.0) driven by data from one of the CMIP5 models (Hadley Centre Global Environmental Model, version 2 - Earth System, HadGEM2-ES) over two CORDEX domains (South America and Central America) for the heavy-emission scenario (RCP8.5). Potential evapotranspiraion data from the RCM and from the CMIP5 global models were analyzed over Northeast Brazil, a semiarid region with a short rainy season (usually February to May in its northern portion due to the seasonal shift of the Intertropical Convergence Zone) and over which droughts are frequent. Significant changes in the potential evapotranspiration were found, with most models showing a increasing trend along the 21st century, which are expected to alter the surface water budget, increasing the current water deficit (precipitation is currently much smaller than potential evapotranspiration). Based on the projections from the majority of the models, we expect important impacts over local agriculture and water resources over Northeast Brazil.

Spatially explicit land-use and land-cover scenarios for the Great Plains of the United States

USGS Publications Warehouse

Sohl, Terry L.; Sleeter, Benjamin M.; Sayler, Kristi L.; Bouchard, Michelle A.; Reker, Ryan R.; Bennett, Stacie L.; Sleeter, Rachel R.; Kanengieter, Ronald L.; Zhu, Zhi-Liang

2012-01-01

The Great Plains of the United States has undergone extensive land-use and land-cover change in the past 150 years, with much of the once vast native grasslands and wetlands converted to agricultural crops, and much of the unbroken prairie now heavily grazed. Future land-use change in the region could have dramatic impacts on ecological resources and processes. A scenario-based modeling framework is needed to support the analysis of potential land-use change in an uncertain future, and to mitigate potentially negative future impacts on ecosystem processes. We developed a scenario-based modeling framework to analyze potential future land-use change in the Great Plains. A unique scenario construction process, using an integrated modeling framework, historical data, workshops, and expert knowledge, was used to develop quantitative demand for future land-use change for four IPCC scenarios at the ecoregion level. The FORE-SCE model ingested the scenario information and produced spatially explicit land-use maps for the region at relatively fine spatial and thematic resolutions. Spatial modeling of the four scenarios provided spatial patterns of land-use change consistent with underlying assumptions and processes associated with each scenario. Economically oriented scenarios were characterized by significant loss of natural land covers and expansion of agricultural and urban land uses. Environmentally oriented scenarios experienced modest declines in natural land covers to slight increases. Model results were assessed for quantity and allocation disagreement between each scenario pair. In conjunction with the U.S. Geological Survey's Biological Carbon Sequestration project, the scenario-based modeling framework used for the Great Plains is now being applied to the entire United States.

Potential for Woody Bioenergy Crops Grown on Marginal Lands in the US Midwest to Reduce Carbon Emissions

NASA Astrophysics Data System (ADS)

Sahajpal, R.; Hurtt, G. C.; Fisk, J. P.; Izaurralde, R. C.; Zhang, X.

2012-12-01

While cellulosic biofuels are widely considered to be a low carbon energy source for the future, a comprehensive assessment of the environmental sustainability of existing and future biofuel systems is needed to assess their utility in meeting US energy and food needs without exacerbating environmental harm. To assess the carbon emission reduction potential of cellulosic biofuels, we need to identify lands that are initially not storing large quantities of carbon in soil and vegetation but are capable of producing abundant biomass with limited management inputs, and accurately model forest production rates and associated input requirements. Here we present modeled results for carbon emission reduction potential and cellulosic ethanol production of woody bioenergy crops replacing existing native prairie vegetation grown on marginal lands in the US Midwest. Marginal lands are selected based on soil properties describing use limitation, and are extracted from the SSURGO (Soil Survey Geographic) database. Yield estimates for existing native prairie vegetation on marginal lands modeled using the process-based field-scale model EPIC (Environmental Policy Integrated Climate) amount to ~ 6.7±2.0 Mg ha-1. To model woody bioenergy crops, the individual-based terrestrial ecosystem model ED (Ecosystem Demography) is initialized with the soil organic carbon stocks estimated at the end of the EPIC simulation. Four woody bioenergy crops: willow, southern pine, eucalyptus and poplar are parameterized in ED. Sensitivity analysis of model parameters and drivers is conducted to explore the range of carbon emission reduction possible with variation in woody bioenergy crop types, spatial and temporal resolution. We hypothesize that growing cellulosic crops on these marginal lands can provide significant water quality, biodiversity and GHG emissions mitigation benefits, without accruing additional carbon costs from the displacement of food and feed production.

RAPID POST-FIRE HYDROLOGIC WATERSHED ASSESSMENT USING THE AGWA GIS-BASED HYDROLOGIC MODELING TOOL

EPA Science Inventory

Rapid post-fire watershed assessment to identify potential trouble spots for erosion and flooding can potentially aid land managers and Burned Area Emergency Rehabilitation (BAER) teams in deploying mitigation and rehabilitation resources.

These decisions are inherently co...

Simple prescription for computing the interparticle potential energy for D-dimensional gravity systems

NASA Astrophysics Data System (ADS)

Accioly, Antonio; Helayël-Neto, José; Barone, F. E.; Herdy, Wallace

2015-02-01

A straightforward prescription for computing the D-dimensional potential energy of gravitational models, which is strongly based on the Feynman path integral, is built up. Using this method, the static potential energy for the interaction of two masses is found in the context of D-dimensional higher-derivative gravity models, and its behavior is analyzed afterwards in both ultraviolet and infrared regimes. As a consequence, two new gravity systems in which the potential energy is finite at the origin, respectively, in D = 5 and D = 6, are found. Since the aforementioned prescription is equivalent to that based on the marriage between quantum mechanics (to leading order, i.e., in the first Born approximation) and the nonrelativistic limit of quantum field theory, and bearing in mind that the latter relies basically on the calculation of the nonrelativistic Feynman amplitude ({{M}NR}), a trivial expression for computing {{M}NR} is obtained from our prescription as an added bonus.

Hospital-Based Comparative Effectiveness Centers: Translating Research into Practice to Improve the Quality, Safety and Value of Patient Care

PubMed Central

Williams, Kendal; Brennan, Patrick J.

2010-01-01

Hospital-based comparative effectiveness (CE) centers provide a model that clinical leaders can use to improve evidence-based practice locally. The model is used by integrated health systems outside the US, but is less recognized in the US. Such centers can identify and adapt national evidence-based policies for the local setting, create local evidence-based policies in the absence of national policies, and implement evidence into practice through health information technology (HIT) and quality initiatives. Given the increasing availability of CE evidence and incentives to meaningfully use HIT, the relevance of this model to US practitioners is increasing. This is especially true in the context of healthcare reform, which will likely reduce reimbursements for care deemed unnecessary by published evidence or guidelines. There are challenges to operating hospital-based CE centers, but many of these challenges can be overcome using solutions developed by those currently leading such centers. In conclusion, these centers have the potential to improve the quality, safety and value of care locally, ultimately translating into higher quality and more cost-effective care nationally. To better understand this potential, the current activity and impact of hospital-based CE centers in the US should be rigorously examined. PMID:20697961

Identifying potential misfit items in cognitive process of learning engineering mathematics based on Rasch model

NASA Astrophysics Data System (ADS)

Ataei, Sh; Mahmud, Z.; Khalid, M. N.

2014-04-01

The students learning outcomes clarify what students should know and be able to demonstrate after completing their course. So, one of the issues on the process of teaching and learning is how to assess students' learning. This paper describes an application of the dichotomous Rasch measurement model in measuring the cognitive process of engineering students' learning of mathematics. This study provides insights into the perspective of 54 engineering students' cognitive ability in learning Calculus III based on Bloom's Taxonomy on 31 items. The results denote that some of the examination questions are either too difficult or too easy for the majority of the students. This analysis yields FIT statistics which are able to identify if there is data departure from the Rasch theoretical model. The study has identified some potential misfit items based on the measurement of ZSTD where the removal misfit item was accomplished based on the MNSQ outfit of above 1.3 or less than 0.7 logit. Therefore, it is recommended that these items be reviewed or revised to better match the range of students' ability in the respective course.

Potential impact of climate change to the future streamflow of Yellow River Basin based on CMIP5 data

NASA Astrophysics Data System (ADS)

Yang, Xiaoli; Zheng, Weifei; Ren, Liliang; Zhang, Mengru; Wang, Yuqian; Liu, Yi; Yuan, Fei; Jiang, Shanhu

2018-02-01

The Yellow River Basin (YRB) is the largest river basin in northern China, which has suffering water scarcity and drought hazard for many years. Therefore, assessments the potential impacts of climate change on the future streamflow in this basin is very important for local policy and planning on food security. In this study, based on the observations of 101 meteorological stations in YRB, equidistant CDF matching (EDCDFm) statistical downscaling approach was applied to eight climate models under two emissions scenarios (RCP4.5 and RCP8.5) from phase five of the Coupled Model Intercomparison Project (CMIP5). Variable infiltration capacity (VIC) model with 0.25° × 0.25° spatial resolution was developed based on downscaled fields for simulating streamflow in the future period over YRB. The results show that with the global warming trend, the annual streamflow will reduced about 10 % during the period of 2021-2050, compared to the base period of 1961-1990 in YRB. There should be suitable water resources planning to meet the demands of growing populations and future climate changing in this region.

3D Pharmacophore-Based Virtual Screening and Docking Approaches toward the Discovery of Novel HPPD Inhibitors.

PubMed

Fu, Ying; Sun, Yi-Na; Yi, Ke-Han; Li, Ming-Qiang; Cao, Hai-Feng; Li, Jia-Zhong; Ye, Fei

2017-06-09

p -Hydroxyphenylpyruvate dioxygenase (HPPD) is not only the useful molecular target in treating life-threatening tyrosinemia type I, but also an important target for chemical herbicides. A combined in silico structure-based pharmacophore and molecular docking-based virtual screening were performed to identify novel potential HPPD inhibitors. The complex-based pharmacophore model (CBP) with 0.721 of ROC used for screening compounds showed remarkable ability to retrieve known active ligands from among decoy molecules. The ChemDiv database was screened using CBP-Hypo2 as a 3D query, and the best-fit hits subjected to molecular docking with two methods of LibDock and CDOCKER in Accelrys Discovery Studio 2.5 (DS 2.5) to discern interactions with key residues at the active site of HPPD. Four compounds with top rankings in the HipHop model and well-known binding model were finally chosen as lead compounds with potential inhibitory effects on the active site of target. The results provided powerful insight into the development of novel HPPD inhibitors herbicides using computational techniques.

A Comparative Study of High and Low Fidelity Fan Models for Turbofan Engine System Simulation

NASA Technical Reports Server (NTRS)

Reed, John A.; Afjeh, Abdollah A.

1991-01-01

In this paper, a heterogeneous propulsion system simulation method is presented. The method is based on the formulation of a cycle model of a gas turbine engine. The model includes the nonlinear characteristics of the engine components via use of empirical data. The potential to simulate the entire engine operation on a computer without the aid of data is demonstrated by numerically generating "performance maps" for a fan component using two flow models of varying fidelity. The suitability of the fan models were evaluated by comparing the computed performance with experimental data. A discussion of the potential benefits and/or difficulties in connecting simulations solutions of differing fidelity is given.

Identifying traits for genotypic adaptation using crop models.

PubMed

Ramirez-Villegas, Julian; Watson, James; Challinor, Andrew J

2015-06-01

Genotypic adaptation involves the incorporation of novel traits in crop varieties so as to enhance food productivity and stability and is expected to be one of the most important adaptation strategies to future climate change. Simulation modelling can provide the basis for evaluating the biophysical potential of crop traits for genotypic adaptation. This review focuses on the use of models for assessing the potential benefits of genotypic adaptation as a response strategy to projected climate change impacts. Some key crop responses to the environment, as well as the role of models and model ensembles for assessing impacts and adaptation, are first reviewed. Next, the review describes crop-climate models can help focus the development of future-adapted crop germplasm in breeding programmes. While recently published modelling studies have demonstrated the potential of genotypic adaptation strategies and ideotype design, it is argued that, for model-based studies of genotypic adaptation to be used in crop breeding, it is critical that modelled traits are better grounded in genetic and physiological knowledge. To this aim, two main goals need to be pursued in future studies: (i) a better understanding of plant processes that limit productivity under future climate change; and (ii) a coupling between genetic and crop growth models-perhaps at the expense of the number of traits analysed. Importantly, the latter may imply additional complexity (and likely uncertainty) in crop modelling studies. Hence, appropriately constraining processes and parameters in models and a shift from simply quantifying uncertainty to actually quantifying robustness towards modelling choices are two key aspects that need to be included into future crop model-based analyses of genotypic adaptation. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Model methodology for estimating pesticide concentration extremes based on sparse monitoring data

USGS Publications Warehouse

Vecchia, Aldo V.

2018-03-22

This report describes a new methodology for using sparse (weekly or less frequent observations) and potentially highly censored pesticide monitoring data to simulate daily pesticide concentrations and associated quantities used for acute and chronic exposure assessments, such as the annual maximum daily concentration. The new methodology is based on a statistical model that expresses log-transformed daily pesticide concentration in terms of a seasonal wave, flow-related variability, long-term trend, and serially correlated errors. Methods are described for estimating the model parameters, generating conditional simulations of daily pesticide concentration given sparse (weekly or less frequent) and potentially highly censored observations, and estimating concentration extremes based on the conditional simulations. The model can be applied to datasets with as few as 3 years of record, as few as 30 total observations, and as few as 10 uncensored observations. The model was applied to atrazine, carbaryl, chlorpyrifos, and fipronil data for U.S. Geological Survey pesticide sampling sites with sufficient data for applying the model. A total of 112 sites were analyzed for atrazine, 38 for carbaryl, 34 for chlorpyrifos, and 33 for fipronil. The results are summarized in this report; and, R functions, described in this report and provided in an accompanying model archive, can be used to fit the model parameters and generate conditional simulations of daily concentrations for use in investigations involving pesticide exposure risk and uncertainty.

Measurement of cytotoxicity and irritancy potential of sugar-based surfactants on skin-related 3D models.

PubMed

Lu, Biao; Miao, Yong; Vigneron, Pascale; Chagnault, Vincent; Grand, Eric; Wadouachi, Anne; Postel, Denis; Pezron, Isabelle; Egles, Christophe; Vayssade, Muriel

2017-04-01

Sugar-based surfactants present surface-active properties and relatively low cytotoxicity. They are often considered as safe alternatives to currently used surfactants in cosmetic industries. In this study, four sugar-based surfactants, each with an eight carbon alkyl chain bound to a glucose or a maltose headgroup through an amide linkage, were synthesized and compared to two standard surfactants. The cytotoxic and irritant effects of surfactants were evaluated using two biologically relevant models: 3D dermal model (mouse fibroblasts embedded in collagen gel) and reconstituted human epidermis (RHE, multi-layered human keratinocytes). Results show that three synthesized surfactants possess lower cytotoxicity compared to standard surfactants as demonstrated in the 3D dermal model. Moreover, the IC50s of surfactants against the 3D dermal model are higher than IC50s obtained with the 2D dermal model (monolayer mouse fibroblasts). Both synthesized and standard surfactants show no irritant effects after 48h of topical application on RHE. Throughout the study, we demonstrate the difficulty to link the physico-chemical properties of surfactants and their cytotoxicity in complex models. More importantly, our data suggest that, prior to in vivo tests, a complete understanding of surfactant cytotoxicity or irritancy potential requires a combination of cellular and tissue models. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estimating spatial accessibility to facilities on the regional scale: an extended commuting-based interaction potential model

PubMed Central

2011-01-01

Background There is growing interest in the study of the relationships between individual health-related behaviours (e.g. food intake and physical activity) and measurements of spatial accessibility to the associated facilities (e.g. food outlets and sport facilities). The aim of this study is to propose measurements of spatial accessibility to facilities on the regional scale, using aggregated data. We first used a potential accessibility model that partly makes it possible to overcome the limitations of the most frequently used indices such as the count of opportunities within a given neighbourhood. We then propose an extended model in order to take into account both home and work-based accessibility for a commuting population. Results Potential accessibility estimation provides a very different picture of the accessibility levels experienced by the population than the more classical "number of opportunities per census tract" index. The extended model for commuters increases the overall accessibility levels but this increase differs according to the urbanisation level. Strongest increases are observed in some rural municipalities with initial low accessibility levels. Distance to major urban poles seems to play an essential role. Conclusions Accessibility is a multi-dimensional concept that should integrate some aspects of travel behaviour. Our work supports the evidence that the choice of appropriate accessibility indices including both residential and non-residential environmental features is necessary. Such models have potential implications for providing relevant information to policy-makers in the field of public health. PMID:21219597

Optimized Free Energies from Bidirectional Single-Molecule Force Spectroscopy

NASA Astrophysics Data System (ADS)

Minh, David D. L.; Adib, Artur B.

2008-05-01

An optimized method for estimating path-ensemble averages using data from processes driven in opposite directions is presented. Based on this estimator, bidirectional expressions for reconstructing free energies and potentials of mean force from single-molecule force spectroscopy—valid for biasing potentials of arbitrary stiffness—are developed. Numerical simulations on a model potential indicate that these methods perform better than unidirectional strategies.

Molecular ion battery: a rechargeable system without using any elemental ions as a charge carrier

PubMed Central

Yao, Masaru; Sano, Hikaru; Ando, Hisanori; Kiyobayashi, Tetsu

2015-01-01

Is it possible to exceed the lithium redox potential in electrochemical systems? It seems impossible to exceed the lithium potential because the redox potential of the elemental lithium is the lowest among all the elements, which contributes to the high voltage characteristics of the widely used lithium ion battery. However, it should be possible when we use a molecule-based ion which is not reduced even at the lithium potential in principle. Here we propose a new model system using a molecular electrolyte salt with polymer-based active materials in order to verify whether a molecular ion species serves as a charge carrier. Although the potential of the negative-electrode is not yet lower than that of lithium at present, this study reveals that a molecular ion can work as a charge carrier in a battery and the system is certainly a molecular ion-based “rocking chair” type battery. PMID:26043147

A hydrothermal after-ripening time model for seed dormancy loss in Bromus tectorum L.

Treesearch

Necia B. Bair; Susan E. Meyer; Phil S. Allen

2006-01-01

After-ripening, the loss of dormancy under dry conditions, is associated with a decrease in mean base water potential for germination of Bromus tectorum L. seeds. After-ripening rate is a linear function of temperature above a base temperature, so that dormancy loss can be quantified using a thermal after-ripening time (TAR) model. To incorporate storage water...

Can Socioeconomic Status Substitute for Race in Affirmative Action College Admissions Policies? Evidence from a Simulation Model. CEPA Working Paper No. 15-04

ERIC Educational Resources Information Center

Reardon, Sean F.; Baker, Rachel; Kasman, Matt; Klasik, Daniel; Townsend, Joseph

2017-01-01

This paper simulates a system of socioeconomic status (SES)-based affirmative action in college admissions and examines the extent to which it can produce racial diversity in selective colleges. Using simulation models, we investigate the potential relative effects of race- and/or SES-based affirmative action policies, alongside targeted,…

Possible Experiment for the Demonstration of Neutron Waves Interaction with Spatially Oscillating Potential

NASA Astrophysics Data System (ADS)

Miloi, Mădălina Mihaela; Goryunov, Semyon; Kulin, German

2018-04-01

A wide range of problems in neutron optics is well described by a theory based on application of the effective potential model. It was assumed that the concept of the effective potential in neutron optics have a limited region of validity and ceases to be correct in the case of the giant acceleration of a matter. To test this hypothesis a new Ultra Cold neutron experiment for the observation neutron interaction with potential structure oscillating in space was proposed. The report is focused on the model calculations of the topography of sample surface that oscillate in space. These calculations are necessary to find an optimal parameters and geometry of the planned experiment.

Differential geometry based solvation model II: Lagrangian formulation.

PubMed

Chen, Zhan; Baker, Nathan A; Wei, G W

2011-12-01

Solvation is an elementary process in nature and is of paramount importance to more sophisticated chemical, biological and biomolecular processes. The understanding of solvation is an essential prerequisite for the quantitative description and analysis of biomolecular systems. This work presents a Lagrangian formulation of our differential geometry based solvation models. The Lagrangian representation of biomolecular surfaces has a few utilities/advantages. First, it provides an essential basis for biomolecular visualization, surface electrostatic potential map and visual perception of biomolecules. Additionally, it is consistent with the conventional setting of implicit solvent theories and thus, many existing theoretical algorithms and computational software packages can be directly employed. Finally, the Lagrangian representation does not need to resort to artificially enlarged van der Waals radii as often required by the Eulerian representation in solvation analysis. The main goal of the present work is to analyze the connection, similarity and difference between the Eulerian and Lagrangian formalisms of the solvation model. Such analysis is important to the understanding of the differential geometry based solvation model. The present model extends the scaled particle theory of nonpolar solvation model with a solvent-solute interaction potential. The nonpolar solvation model is completed with a Poisson-Boltzmann (PB) theory based polar solvation model. The differential geometry theory of surfaces is employed to provide a natural description of solvent-solute interfaces. The optimization of the total free energy functional, which encompasses the polar and nonpolar contributions, leads to coupled potential driven geometric flow and PB equations. Due to the development of singularities and nonsmooth manifolds in the Lagrangian representation, the resulting potential-driven geometric flow equation is embedded into the Eulerian representation for the purpose of computation, thanks to the equivalence of the Laplace-Beltrami operator in the two representations. The coupled partial differential equations (PDEs) are solved with an iterative procedure to reach a steady state, which delivers desired solvent-solute interface and electrostatic potential for problems of interest. These quantities are utilized to evaluate the solvation free energies and protein-protein binding affinities. A number of computational methods and algorithms are described for the interconversion of Lagrangian and Eulerian representations, and for the solution of the coupled PDE system. The proposed approaches have been extensively validated. We also verify that the mean curvature flow indeed gives rise to the minimal molecular surface and the proposed variational procedure indeed offers minimal total free energy. Solvation analysis and applications are considered for a set of 17 small compounds and a set of 23 proteins. The salt effect on protein-protein binding affinity is investigated with two protein complexes by using the present model. Numerical results are compared to the experimental measurements and to those obtained by using other theoretical methods in the literature. © Springer-Verlag 2011

Differential geometry based solvation model II: Lagrangian formulation

PubMed Central

Chen, Zhan; Baker, Nathan A.; Wei, G. W.

2010-01-01

Solvation is an elementary process in nature and is of paramount importance to more sophisticated chemical, biological and biomolecular processes. The understanding of solvation is an essential prerequisite for the quantitative description and analysis of biomolecular systems. This work presents a Lagrangian formulation of our differential geometry based solvation model. The Lagrangian representation of biomolecular surfaces has a few utilities/advantages. First, it provides an essential basis for biomolecular visualization, surface electrostatic potential map and visual perception of biomolecules. Additionally, it is consistent with the conventional setting of implicit solvent theories and thus, many existing theoretical algorithms and computational software packages can be directly employed. Finally, the Lagrangian representation does not need to resort to artificially enlarged van der Waals radii as often required by the Eulerian representation in solvation analysis. The main goal of the present work is to analyze the connection, similarity and difference between the Eulerian and Lagrangian formalisms of the solvation model. Such analysis is important to the understanding of the differential geometry based solvation model. The present model extends the scaled particle theory (SPT) of nonpolar solvation model with a solvent-solute interaction potential. The nonpolar solvation model is completed with a Poisson-Boltzmann (PB) theory based polar solvation model. The differential geometry theory of surfaces is employed to provide a natural description of solvent-solute interfaces. The minimization of the total free energy functional, which encompasses the polar and nonpolar contributions, leads to coupled potential driven geometric flow and Poisson-Boltzmann equations. Due to the development of singularities and nonsmooth manifolds in the Lagrangian representation, the resulting potential-driven geometric flow equation is embedded into the Eulerian representation for the purpose of computation, thanks to the equivalence of the Laplace-Beltrami operator in the two representations. The coupled partial differential equations (PDEs) are solved with an iterative procedure to reach a steady state, which delivers desired solvent-solute interface and electrostatic potential for problems of interest. These quantities are utilized to evaluate the solvation free energies and protein-protein binding affinities. A number of computational methods and algorithms are described for the interconversion of Lagrangian and Eulerian representations, and for the solution of the coupled PDE system. The proposed approaches have been extensively validated. We also verify that the mean curvature flow indeed gives rise to the minimal molecular surface (MMS) and the proposed variational procedure indeed offers minimal total free energy. Solvation analysis and applications are considered for a set of 17 small compounds and a set of 23 proteins. The salt effect on protein-protein binding affinity is investigated with two protein complexes by using the present model. Numerical results are compared to the experimental measurements and to those obtained by using other theoretical methods in the literature. PMID:21279359

Assessment of the dose reduction potential of a model-based iterative reconstruction algorithm using a task-based performance metrology

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

Samei, Ehsan, E-mail: samei@duke.edu; Richard, Samuel

2015-01-15

Purpose: Different computed tomography (CT) reconstruction techniques offer different image quality attributes of resolution and noise, challenging the ability to compare their dose reduction potential against each other. The purpose of this study was to evaluate and compare the task-based imaging performance of CT systems to enable the assessment of the dose performance of a model-based iterative reconstruction (MBIR) to that of an adaptive statistical iterative reconstruction (ASIR) and a filtered back projection (FBP) technique. Methods: The ACR CT phantom (model 464) was imaged across a wide range of mA setting on a 64-slice CT scanner (GE Discovery CT750 HD,more » Waukesha, WI). Based on previous work, the resolution was evaluated in terms of a task-based modulation transfer function (MTF) using a circular-edge technique and images from the contrast inserts located in the ACR phantom. Noise performance was assessed in terms of the noise-power spectrum (NPS) measured from the uniform section of the phantom. The task-based MTF and NPS were combined with a task function to yield a task-based estimate of imaging performance, the detectability index (d′). The detectability index was computed as a function of dose for two imaging tasks corresponding to the detection of a relatively small and a relatively large feature (1.5 and 25 mm, respectively). The performance of MBIR in terms of the d′ was compared with that of ASIR and FBP to assess its dose reduction potential. Results: Results indicated that MBIR exhibits a variability spatial resolution with respect to object contrast and noise while significantly reducing image noise. The NPS measurements for MBIR indicated a noise texture with a low-pass quality compared to the typical midpass noise found in FBP-based CT images. At comparable dose, the d′ for MBIR was higher than those of FBP and ASIR by at least 61% and 19% for the small feature and the large feature tasks, respectively. Compared to FBP and ASIR, MBIR indicated a 46%–84% dose reduction potential, depending on task, without compromising the modeled detection performance. Conclusions: The presented methodology based on ACR phantom measurements extends current possibilities for the assessment of CT image quality under the complex resolution and noise characteristics exhibited with statistical and iterative reconstruction algorithms. The findings further suggest that MBIR can potentially make better use of the projections data to reduce CT dose by approximately a factor of 2. Alternatively, if the dose held unchanged, it can improve image quality by different levels for different tasks.« less

SECURITY MODELING FOR MARITIME PORT DEFENSE RESOURCE ALLOCATION

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

Harris, S.; Dunn, D.

2010-09-07

Redeployment of existing law enforcement resources and optimal use of geographic terrain are examined for countering the threat of a maritime based small-vessel radiological or nuclear attack. The evaluation was based on modeling conducted by the Savannah River National Laboratory that involved the development of options for defensive resource allocation that can reduce the risk of a maritime based radiological or nuclear threat. A diverse range of potential attack scenarios has been assessed. As a result of identifying vulnerable pathways, effective countermeasures can be deployed using current resources. The modeling involved the use of the Automated Vulnerability Evaluation for Risksmore » of Terrorism (AVERT{reg_sign}) software to conduct computer based simulation modeling. The models provided estimates for the probability of encountering an adversary based on allocated resources including response boats, patrol boats and helicopters over various environmental conditions including day, night, rough seas and various traffic flow rates.« less

Statistical properties of nonlinear one-dimensional wave fields

NASA Astrophysics Data System (ADS)

Chalikov, D.

2005-06-01

A numerical model for long-term simulation of gravity surface waves is described. The model is designed as a component of a coupled Wave Boundary Layer/Sea Waves model, for investigation of small-scale dynamic and thermodynamic interactions between the ocean and atmosphere. Statistical properties of nonlinear wave fields are investigated on a basis of direct hydrodynamical modeling of 1-D potential periodic surface waves. The method is based on a nonstationary conformal surface-following coordinate transformation; this approach reduces the principal equations of potential waves to two simple evolutionary equations for the elevation and the velocity potential on the surface. The numerical scheme is based on a Fourier transform method. High accuracy was confirmed by validation of the nonstationary model against known solutions, and by comparison between the results obtained with different resolutions in the horizontal. The scheme allows reproduction of the propagation of steep Stokes waves for thousands of periods with very high accuracy. The method here developed is applied to simulation of the evolution of wave fields with large number of modes for many periods of dominant waves. The statistical characteristics of nonlinear wave fields for waves of different steepness were investigated: spectra, curtosis and skewness, dispersion relation, life time. The prime result is that wave field may be presented as a superposition of linear waves is valid only for small amplitudes. It is shown as well, that nonlinear wave fields are rather a superposition of Stokes waves not linear waves. Potential flow, free surface, conformal mapping, numerical modeling of waves, gravity waves, Stokes waves, breaking waves, freak waves, wind-wave interaction.

The alarming problems of confounding equivalence using logistic regression models in the perspective of causal diagrams.

PubMed

Yu, Yuanyuan; Li, Hongkai; Sun, Xiaoru; Su, Ping; Wang, Tingting; Liu, Yi; Yuan, Zhongshang; Liu, Yanxun; Xue, Fuzhong

2017-12-28

Confounders can produce spurious associations between exposure and outcome in observational studies. For majority of epidemiologists, adjusting for confounders using logistic regression model is their habitual method, though it has some problems in accuracy and precision. It is, therefore, important to highlight the problems of logistic regression and search the alternative method. Four causal diagram models were defined to summarize confounding equivalence. Both theoretical proofs and simulation studies were performed to verify whether conditioning on different confounding equivalence sets had the same bias-reducing potential and then to select the optimum adjusting strategy, in which logistic regression model and inverse probability weighting based marginal structural model (IPW-based-MSM) were compared. The "do-calculus" was used to calculate the true causal effect of exposure on outcome, then the bias and standard error were used to evaluate the performances of different strategies. Adjusting for different sets of confounding equivalence, as judged by identical Markov boundaries, produced different bias-reducing potential in the logistic regression model. For the sets satisfied G-admissibility, adjusting for the set including all the confounders reduced the equivalent bias to the one containing the parent nodes of the outcome, while the bias after adjusting for the parent nodes of exposure was not equivalent to them. In addition, all causal effect estimations through logistic regression were biased, although the estimation after adjusting for the parent nodes of exposure was nearest to the true causal effect. However, conditioning on different confounding equivalence sets had the same bias-reducing potential under IPW-based-MSM. Compared with logistic regression, the IPW-based-MSM could obtain unbiased causal effect estimation when the adjusted confounders satisfied G-admissibility and the optimal strategy was to adjust for the parent nodes of outcome, which obtained the highest precision. All adjustment strategies through logistic regression were biased for causal effect estimation, while IPW-based-MSM could always obtain unbiased estimation when the adjusted set satisfied G-admissibility. Thus, IPW-based-MSM was recommended to adjust for confounders set.

Community Health Workers-Promotores de Salud in Mexico: History and Potential for Building Effective Community Actions.

PubMed

Balcazar, Hector; Perez-Lizaur, Ana Bertha; Izeta, Ericka Escalante; Villanueva, Maria Angeles

2016-01-01

This article takes a historical perspective combining 3 illustrative examples of the origins of the community health worker (CHW) model in Mexico, as a community-based participatory strategy. Three examples were identified from the sparse literature about CHWs in Mexico emphasizing their key roles and functions in various community settings. The CHW models illustrate what is known of training-development and planning, implementation, and evaluation of the CHWs model in different settings addressing cardiovascular disease and risk factors. The potential exists for integrating CHW projects to expand the health promotion model with new emphasis on municipality and regional participation.

Mixed quantum-classical simulation of the hydride transfer reaction catalyzed by dihydrofolate reductase based on a mapped system-harmonic bath model

NASA Astrophysics Data System (ADS)

Xu, Yang; Song, Kai; Shi, Qiang

2018-03-01

The hydride transfer reaction catalyzed by dihydrofolate reductase is studied using a recently developed mixed quantum-classical method to investigate the nuclear quantum effects on the reaction. Molecular dynamics simulation is first performed based on a two-state empirical valence bond potential to map the atomistic model to an effective double-well potential coupled to a harmonic bath. In the mixed quantum-classical simulation, the hydride degree of freedom is quantized, and the effective harmonic oscillator modes are treated classically. It is shown that the hydride transfer reaction rate using the mapped effective double-well/harmonic-bath model is dominated by the contribution from the ground vibrational state. Further comparison with the adiabatic reaction rate constant based on the Kramers theory confirms that the reaction is primarily vibrationally adiabatic, which agrees well with the high transmission coefficients found in previous theoretical studies. The calculated kinetic isotope effect is also consistent with the experimental and recent theoretical results.

Dual metal gate tunneling field effect transistors based on MOSFETs: A 2-D analytical approach

NASA Astrophysics Data System (ADS)

Ramezani, Zeinab; Orouji, Ali A.

2018-01-01

A novel 2-D analytical drain current model of novel Dual Metal Gate Tunnel Field Effect Transistors Based on MOSFETs (DMG-TFET) is presented in this paper. The proposed Tunneling FET is extracted from a MOSFET structure by employing an additional electrode in the source region with an appropriate work function to induce holes in the N+ source region and hence makes it as a P+ source region. The electric field is derived which is utilized to extract the expression of the drain current by analytically integrating the band to band tunneling generation rate in the tunneling region based on the potential profile by solving the Poisson's equation. Through this model, the effects of the thin film thickness and gate voltage on the potential, the electric field, and the effects of the thin film thickness on the tunneling current can be studied. To validate our present model we use SILVACO ATLAS device simulator and the analytical results have been compared with it and found a good agreement.

Hyperspectral-based predictive modelling of grapevine water status in the Portuguese Douro wine region

NASA Astrophysics Data System (ADS)

Pôças, Isabel; Gonçalves, João; Costa, Patrícia Malva; Gonçalves, Igor; Pereira, Luís S.; Cunha, Mario

2017-06-01

In this study, hyperspectral reflectance (HySR) data derived from a handheld spectroradiometer were used to assess the water status of three grapevine cultivars in two sub-regions of Douro wine region during two consecutive years. A large set of potential predictors derived from the HySR data were considered for modelling/predicting the predawn leaf water potential (Ψpd) through different statistical and machine learning techniques. Three HySR vegetation indices were selected as final predictors for the computation of the models and the in-season time trend was removed from data by using a time predictor. The vegetation indices selected were the Normalized Reflectance Index for the wavelengths 554 nm and 561 nm (NRI554;561), the water index (WI) for the wavelengths 900 nm and 970 nm, and the D1 index which is associated with the rate of reflectance increase in the wavelengths of 706 nm and 730 nm. These vegetation indices covered the green, red edge and the near infrared domains of the electromagnetic spectrum. A large set of state-of-the-art analysis and statistical and machine-learning modelling techniques were tested. Predictive modelling techniques based on generalized boosted model (GBM), bagged multivariate adaptive regression splines (B-MARS), generalized additive model (GAM), and Bayesian regularized neural networks (BRNN) showed the best performance for predicting Ψpd, with an average determination coefficient (R2) ranging between 0.78 and 0.80 and RMSE varying between 0.11 and 0.12 MPa. When cultivar Touriga Nacional was used for training the models and the cultivars Touriga Franca and Tinta Barroca for testing (independent validation), the models performance was good, particularly for GBM (R2 = 0.85; RMSE = 0.09 MPa). Additionally, the comparison of Ψpd observed and predicted showed an equitable dispersion of data from the various cultivars. The results achieved show a good potential of these predictive models based on vegetation indices to support irrigation scheduling in vineyard.

Geothermal studies at Kirtland Air Force Base, Albuquerque, New Mexico

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

Riddle, L.; Grant, B.

Due to an effort by government installations to discontinue use of natural gas, alternative energy sources are being investigated at Kirtland Air Force Base, Albuquerque, New Mexico. New Mexico has geologic characteristics favorable for geothermal energy utilization. Local heat flow and geochemical studies indicate a normal subsurface temperature regime. The alluvial deposits, however, extend to great depths where hot fluids, heated by the normal geothermal gradient, could be encountered. Two potential models for tapping geothermal energy are presented: the basin model and the fault model.

Electronic Cigarettes and Indoor Air Quality: A Simple Approach to Modeling Potential Bystander Exposures to Nicotine

PubMed Central

Colard, Stéphane; O’Connell, Grant; Verron, Thomas; Cahours, Xavier; Pritchard, John D.

2014-01-01

There has been rapid growth in the use of electronic cigarettes (“vaping”) in Europe, North America and elsewhere. With such increased prevalence, there is currently a debate on whether the aerosol exhaled following the use of e-cigarettes has implications for the quality of air breathed by bystanders. Conducting chemical analysis of the indoor environment can be costly and resource intensive, limiting the number of studies which can be conducted. However, this can be modelled reasonably accurately based on empirical emissions data and using some basic assumptions. Here, we present a simplified model, based on physical principles, which considers aerosol propagation, dilution and extraction to determine the potential contribution of a single puff from an e-cigarette to indoor air. From this, it was then possible to simulate the cumulative effect of vaping over time. The model was applied to a virtual, but plausible, scenario considering an e-cigarette user and a non-user working in the same office space. The model was also used to reproduce published experimental studies and showed good agreement with the published values of indoor air nicotine concentration. With some additional refinements, such an approach may be a cost-effective and rapid way of assessing the potential exposure of bystanders to exhaled e-cigarette aerosol constituents. PMID:25547398

A patient-specific EMG-driven neuromuscular model for the potential use of human-inspired gait rehabilitation robots.

PubMed

Ma, Ye; Xie, Shengquan; Zhang, Yanxin

2016-03-01

A patient-specific electromyography (EMG)-driven neuromuscular model (PENm) is developed for the potential use of human-inspired gait rehabilitation robots. The PENm is modified based on the current EMG-driven models by decreasing the calculation time and ensuring good prediction accuracy. To ensure the calculation efficiency, the PENm is simplified into two EMG channels around one joint with minimal physiological parameters. In addition, a dynamic computation model is developed to achieve real-time calculation. To ensure the calculation accuracy, patient-specific muscle kinematics information, such as the musculotendon lengths and the muscle moment arms during the entire gait cycle, are employed based on the patient-specific musculoskeletal model. Moreover, an improved force-length-velocity relationship is implemented to generate accurate muscle forces. Gait analysis data including kinematics, ground reaction forces, and raw EMG signals from six adolescents at three different speeds were used to evaluate the PENm. The simulation results show that the PENm has the potential to predict accurate joint moment in real-time. The design of advanced human-robot interaction control strategies and human-inspired gait rehabilitation robots can benefit from the application of the human internal state provided by the PENm. Copyright © 2016 Elsevier Ltd. All rights reserved.

Gay-Berne and electrostatic multipole based coarse-grain potential in implicit solvent

PubMed Central

Wu, Johnny; Zhen, Xia; Shen, Hujun; Li, Guohui; Ren, Pengyu

2011-01-01

A general, transferable coarse-grain (CG) framework based on the Gay-Berne potential and electrostatic point multipole expansion is presented for polypeptide simulations. The solvent effect is described by the Generalized Kirkwood theory. The CG model is calibrated using the results of all-atom simulations of model compounds in solution. Instead of matching the overall effective forces produced by atomic models, the fundamental intermolecular forces such as electrostatic, repulsion-dispersion, and solvation are represented explicitly at a CG level. We demonstrate that the CG alanine dipeptide model is able to reproduce quantitatively the conformational energy of all-atom force fields in both gas and solution phases, including the electrostatic and solvation components. Replica exchange molecular dynamics and microsecond dynamic simulations of polyalanine of 5 and 12 residues reveal that the CG polyalanines fold into “alpha helix” and “beta sheet” structures. The 5-residue polyalanine displays a substantial increase in the “beta strand” fraction relative to the 12-residue polyalanine. The detailed conformational distribution is compared with those reported from recent all-atom simulations and experiments. The results suggest that the new coarse-graining approach presented in this study has the potential to offer both accuracy and efficiency for biomolecular modeling. PMID:22029338

Plant water potential improves prediction of empirical stomatal models.

PubMed

Anderegg, William R L; Wolf, Adam; Arango-Velez, Adriana; Choat, Brendan; Chmura, Daniel J; Jansen, Steven; Kolb, Thomas; Li, Shan; Meinzer, Frederick; Pita, Pilar; Resco de Dios, Víctor; Sperry, John S; Wolfe, Brett T; Pacala, Stephen

2017-01-01

Climate change is expected to lead to increases in drought frequency and severity, with deleterious effects on many ecosystems. Stomatal responses to changing environmental conditions form the backbone of all ecosystem models, but are based on empirical relationships and are not well-tested during drought conditions. Here, we use a dataset of 34 woody plant species spanning global forest biomes to examine the effect of leaf water potential on stomatal conductance and test the predictive accuracy of three major stomatal models and a recently proposed model. We find that current leaf-level empirical models have consistent biases of over-prediction of stomatal conductance during dry conditions, particularly at low soil water potentials. Furthermore, the recently proposed stomatal conductance model yields increases in predictive capability compared to current models, and with particular improvement during drought conditions. Our results reveal that including stomatal sensitivity to declining water potential and consequent impairment of plant water transport will improve predictions during drought conditions and show that many biomes contain a diversity of plant stomatal strategies that range from risky to conservative stomatal regulation during water stress. Such improvements in stomatal simulation are greatly needed to help unravel and predict the response of ecosystems to future climate extremes.

Population of computational rabbit-specific ventricular action potential models for investigating sources of variability in cellular repolarisation.

PubMed

Gemmell, Philip; Burrage, Kevin; Rodriguez, Blanca; Quinn, T Alexander

2014-01-01

Variability is observed at all levels of cardiac electrophysiology. Yet, the underlying causes and importance of this variability are generally unknown, and difficult to investigate with current experimental techniques. The aim of the present study was to generate populations of computational ventricular action potential models that reproduce experimentally observed intercellular variability of repolarisation (represented by action potential duration) and to identify its potential causes. A systematic exploration of the effects of simultaneously varying the magnitude of six transmembrane current conductances (transient outward, rapid and slow delayed rectifier K(+), inward rectifying K(+), L-type Ca(2+), and Na(+)/K(+) pump currents) in two rabbit-specific ventricular action potential models (Shannon et al. and Mahajan et al.) at multiple cycle lengths (400, 600, 1,000 ms) was performed. This was accomplished with distributed computing software specialised for multi-dimensional parameter sweeps and grid execution. An initial population of 15,625 parameter sets was generated for both models at each cycle length. Action potential durations of these populations were compared to experimentally derived ranges for rabbit ventricular myocytes. 1,352 parameter sets for the Shannon model and 779 parameter sets for the Mahajan model yielded action potential duration within the experimental range, demonstrating that a wide array of ionic conductance values can be used to simulate a physiological rabbit ventricular action potential. Furthermore, by using clutter-based dimension reordering, a technique that allows visualisation of multi-dimensional spaces in two dimensions, the interaction of current conductances and their relative importance to the ventricular action potential at different cycle lengths were revealed. Overall, this work represents an important step towards a better understanding of the role that variability in current conductances may play in experimentally observed intercellular variability of rabbit ventricular action potential repolarisation.

Population of Computational Rabbit-Specific Ventricular Action Potential Models for Investigating Sources of Variability in Cellular Repolarisation

PubMed Central

Gemmell, Philip; Burrage, Kevin; Rodriguez, Blanca; Quinn, T. Alexander

2014-01-01

Variability is observed at all levels of cardiac electrophysiology. Yet, the underlying causes and importance of this variability are generally unknown, and difficult to investigate with current experimental techniques. The aim of the present study was to generate populations of computational ventricular action potential models that reproduce experimentally observed intercellular variability of repolarisation (represented by action potential duration) and to identify its potential causes. A systematic exploration of the effects of simultaneously varying the magnitude of six transmembrane current conductances (transient outward, rapid and slow delayed rectifier K+, inward rectifying K+, L-type Ca2+, and Na+/K+ pump currents) in two rabbit-specific ventricular action potential models (Shannon et al. and Mahajan et al.) at multiple cycle lengths (400, 600, 1,000 ms) was performed. This was accomplished with distributed computing software specialised for multi-dimensional parameter sweeps and grid execution. An initial population of 15,625 parameter sets was generated for both models at each cycle length. Action potential durations of these populations were compared to experimentally derived ranges for rabbit ventricular myocytes. 1,352 parameter sets for the Shannon model and 779 parameter sets for the Mahajan model yielded action potential duration within the experimental range, demonstrating that a wide array of ionic conductance values can be used to simulate a physiological rabbit ventricular action potential. Furthermore, by using clutter-based dimension reordering, a technique that allows visualisation of multi-dimensional spaces in two dimensions, the interaction of current conductances and their relative importance to the ventricular action potential at different cycle lengths were revealed. Overall, this work represents an important step towards a better understanding of the role that variability in current conductances may play in experimentally observed intercellular variability of rabbit ventricular action potential repolarisation. PMID:24587229

PHOTOTOXIC POLYCYCLIC AROMATIC HYDROCARBONS IN SEDIMENTS: A MODEL-BASED APPROACH FOR ASSESSING RISK

EPA Science Inventory

Over the past five years we have developed a number of models which will be combined in an integrated framework with chemical-monitoring information to assess the potential for widespread risk of phototoxic PAHs in sediments.

Electrodiffusion Models of Neurons and Extracellular Space Using the Poisson-Nernst-Planck Equations—Numerical Simulation of the Intra- and Extracellular Potential for an Axon Model

PubMed Central

Pods, Jurgis; Schönke, Johannes; Bastian, Peter

2013-01-01

In neurophysiology, extracellular signals—as measured by local field potentials (LFP) or electroencephalography—are of great significance. Their exact biophysical basis is, however, still not fully understood. We present a three-dimensional model exploiting the cylinder symmetry of a single axon in extracellular fluid based on the Poisson-Nernst-Planck equations of electrodiffusion. The propagation of an action potential along the axonal membrane is investigated by means of numerical simulations. Special attention is paid to the Debye layer, the region with strong concentration gradients close to the membrane, which is explicitly resolved by the computational mesh. We focus on the evolution of the extracellular electric potential. A characteristic up-down-up LFP waveform in the far-field is found. Close to the membrane, the potential shows a more intricate shape. A comparison with the widely used line source approximation reveals similarities and demonstrates the strong influence of membrane currents. However, the electrodiffusion model shows another signal component stemming directly from the intracellular electric field, called the action potential echo. Depending on the neuronal configuration, this might have a significant effect on the LFP. In these situations, electrodiffusion models should be used for quantitative comparisons with experimental data. PMID:23823244

Spline Laplacian estimate of EEG potentials over a realistic magnetic resonance-constructed scalp surface model.

PubMed

Babiloni, F; Babiloni, C; Carducci, F; Fattorini, L; Onorati, P; Urbano, A

1996-04-01

This paper presents a realistic Laplacian (RL) estimator based on a tensorial formulation of the surface Laplacian (SL) that uses the 2-D thin plate spline function to obtain a mathematical description of a realistic scalp surface. Because of this tensorial formulation, the RL does not need an orthogonal reference frame placed on the realistic scalp surface. In simulation experiments the RL was estimated with an increasing number of "electrodes" (up to 256) on a mathematical scalp model, the analytic Laplacian being used as a reference. Second and third order spherical spline Laplacian estimates were examined for comparison. Noise of increasing magnitude and spatial frequency was added to the simulated potential distributions. Movement-related potentials and somatosensory evoked potentials sampled with 128 electrodes were used to estimate the RL on a realistically shaped, MR-constructed model of the subject's scalp surface. The RL was also estimated on a mathematical spherical scalp model computed from the real scalp surface. Simulation experiments showed that the performances of the RL estimator were similar to those of the second and third order spherical spline Laplacians. Furthermore, the information content of scalp-recorded potentials was clearly better when the RL estimator computed the SL of the potential on an MR-constructed scalp surface model.

Modelling the impact of the light regime on single tree transpiration based on 3D representations of plant architecture

NASA Astrophysics Data System (ADS)

Bittner, S.; Priesack, E.

2012-04-01

We apply a functional-structural model of tree water flow to single old-growth trees in a temperate broad-leaved forest stand. Roots, stems and branches are represented by connected porous cylinder elements further divided into the inner heartwood cylinders surrounded by xylem and phloem. Xylem water flow is simulated by applying a non-linear Darcy flow in porous media driven by the water potential gradient according to the cohesion-tension theory. The flow model is based on physiological input parameters such as the hydraulic conductivity, stomatal response to leaf water potential and root water uptake capability and, thus, can reflect the different properties of tree species. The actual root water uptake is calculated using also a non-linear Darcy law based on the gradient between root xylem water potential and rhizosphere soil water potential and by the simulation of soil water flow applying Richards equation. A leaf stomatal conductance model is combined with the hydrological tree and soil water flow model and a spatially explicit three-dimensional canopy light model. The structure of the canopy and the tree architectures are derived by applying an automatic tree skeleton extraction algorithm from point clouds obtained by use of a terrestrial laser scanner allowing an explicit representation of the water flow path in the stem and branches. The high spatial resolution of the root and branch geometry and their connectivity makes the detailed modelling of the water use of single trees possible and allows for the analysis of the interaction between single trees and the influence of the canopy light regime (including different fractions of direct sunlight and diffuse skylight) on the simulated sap flow and transpiration. The model can be applied at various sites and to different tree species, enabling the up-scaling of the water usage of single trees to the total transpiration of mixed stands. Examples are given to reveal differences between diffuse- and ring-porous tree species and to simulate the diurnal dynamics of transpiration, stem sap flux, and root water uptake observed during the vegetation period in the year 2009.

Model-based estimation for dynamic cardiac studies using ECT

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

Chiao, P.C.; Rogers, W.L.; Clinthorne, N.H.

1994-06-01

In this paper, the authors develop a strategy for joint estimation of physiological parameters and myocardial boundaries using ECT (Emission Computed Tomography). The authors construct an observation model to relate parameters of interest to the projection data and to account for limited ECT system resolution and measurement noise. The authors then use a maximum likelihood (ML) estimator to jointly estimate all the parameters directly from the projection data without reconstruction of intermediate images. The authors also simulate myocardial perfusion studies based on a simplified heart model to evaluate the performance of the model-based joint ML estimator and compare this performancemore » to the Cramer-Rao lower bound. Finally, model assumptions and potential uses of the joint estimation strategy are discussed.« less

Stochastic, compartmental, and dynamic modeling of cross-contamination during mechanical smearing of cheeses.

PubMed

Aziza, Fanny; Mettler, Eric; Daudin, Jean-Jacques; Sanaa, Moez

2006-06-01

Cheese smearing is a complex process and the potential for cross-contamination with pathogenic or undesirable microorganisms is critical. During ripening, cheeses are salted and washed with brine to develop flavor and remove molds that could develop on the surfaces. Considering the potential for cross-contamination of this process in quantitative risk assessments could contribute to a better understanding of this phenomenon and, eventually, improve its control. The purpose of this article is to model the cross-contamination of smear-ripened cheeses due to the smearing operation under industrial conditions. A compartmental, dynamic, and stochastic model is proposed for mechanical brush smearing. This model has been developed to describe the exchange of microorganisms between compartments. Based on the analytical solution of the model equations and on experimental data collected with an industrial smearing machine, we assessed the values of the transfer parameters of the model. Monte Carlo simulations, using the distributions of transfer parameters, provide the final number of contaminated products in a batch and their final level of contamination for a given scenario taking into account the initial number of contaminated cheeses of the batch and their contaminant load. Based on analytical results, the model provides indicators for smearing efficiency and propensity of the process for cross-contamination. Unlike traditional approaches in mechanistic models, our approach captures the variability and uncertainty inherent in the process and the experimental data. More generally, this model could represent a generic base to use in modeling similar processes prone to cross-contamination.

Pharmacophore modeling and virtual screening to identify potential RET kinase inhibitors.

PubMed

Shih, Kuei-Chung; Shiau, Chung-Wai; Chen, Ting-Shou; Ko, Ching-Huai; Lin, Chih-Lung; Lin, Chun-Yuan; Hwang, Chrong-Shiong; Tang, Chuan-Yi; Chen, Wan-Ru; Huang, Jui-Wen

2011-08-01

Chemical features based 3D pharmacophore model for REarranged during Transfection (RET) tyrosine kinase were developed by using a training set of 26 structurally diverse known RET inhibitors. The best pharmacophore hypothesis, which identified inhibitors with an associated correlation coefficient of 0.90 between their experimental and estimated anti-RET values, contained one hydrogen-bond acceptor, one hydrogen-bond donor, one hydrophobic, and one ring aromatic features. The model was further validated by a testing set, Fischer's randomization test, and goodness of hit (GH) test. We applied this pharmacophore model to screen NCI database for potential RET inhibitors. The hits were docked to RET with GOLD and CDOCKER after filtering by Lipinski's rules. Ultimately, 24 molecules were selected as potential RET inhibitors for further investigation. Copyright © 2011 Elsevier Ltd. All rights reserved.

Investigating the potential of e-Learning in healthcare postgraduate curricula: a structural equation model.

PubMed

Katharaki, Maria; Daskalakis, Stelios; Mantas, John

2010-01-01

The objective of this paper is to assess the future adaptability of e-Learning platforms within postgraduate modules. An ongoing empirical assessment was conducted amongst postgraduate students, based on the Technology Acceptance Model (TAM). The current paper presents the outcomes from the second phase of a survey, involving fifty six participants. Data analysis was performed using a structural equation model, based on partial least squares. Results highlighted the very strong effect of perceived usefulness and perceived ease of use to attitude towards using e-Learning platforms. Consequently, attitude towards use proved to be a very strong predictor of behavioral intention. Perceived usefulness, on the contrary, did not prove to have an effect to behavioral intention. Implications on the potential of using e-Learning platforms are discussed along with limitations and future directions of the study.

From nuclear submarines to graduate medical education: applying David Marquet's intent-based leadership model.

PubMed

Fernandez-Salvador, Camilo; Oney, Rebecca; Song, Sungjin A; Camacho, Macario

2017-10-11

L. David Marquet, a decorated Navy Captain, transformed an underperforming submarine crew by empowering his subordinates to be leaders and reach their full potential. He called this intent-based leadership (IBL). What would happen if Marquet's model were implemented in Graduate Medical Education (GME)?In this letter to the editor, we summarize the potential of the IBL model in graduate medical education as opposed to the traditional leader-follower method. IBL harnesses human productivity toward the shared goals of GME, which are patient care and trainee learning. This shift in mindset could lead both teachers and trainees to focus more on the real reason that we undertake GME and change behaviors for the better. We suggest that IBL can and should be adopted in GME and propose that both patients and providers will benefit from this action.

Transfer function of multimode fiber links using an electric field propagation model: Application to Radio over Fibre Systems.

PubMed

Gasulla, I; Capmany, J

2006-10-02

We present a closed-form expression for the evaluation of the transfer function of a multimode fiber (MMF) link based on the electric field propagation model. After validating the result we investigate the potential for broadband transmission in regions far from baseband. We find that MMFs offer the potential for broadband ROF transmission in the microwave and millimetre wave regions in short and middle reach distances.

Improving Recovery from Catastrophic Bone Injuries: An Animal Model for Assessing the Bone Reparative Potential of Progenitor Cell Therapy

DTIC Science & Technology

2009-08-01

make structurally different bone in vivo – Although calvarial and BMSC have osteogenic potential, they make a very different type of bone. The two...calvarial defect model. Extracel™ hydrogel is based on thiolated hyaluronate (Glycosil) and thiolated gelatin (Gelin- S) which are crosslinked by...for encapsulation of cells for 3D cultures and in vivo study. Each component of Extracel™ is chemically defined. Variation of the hydrogel

Using Necessary Information to Identify Item Dependence in Passage-Based Reading Comprehension Tests

ERIC Educational Resources Information Center

Baldonado, Angela Argo; Svetina, Dubravka; Gorin, Joanna

2015-01-01

Applications of traditional unidimensional item response theory models to passage-based reading comprehension assessment data have been criticized based on potential violations of local independence. However, simple rules for determining dependency, such as including all items associated with a particular passage, may overestimate the dependency…

Ligand- and structure-based in silico studies to identify kinesin spindle protein (KSP) inhibitors as potential anticancer agents.

PubMed

Balakumar, Chandrasekaran; Ramesh, Muthusamy; Tham, Chuin Lean; Khathi, Samukelisiwe Pretty; Kozielski, Frank; Srinivasulu, Cherukupalli; Hampannavar, Girish A; Sayyad, Nisar; Soliman, Mahmoud E; Karpoormath, Rajshekhar

2017-11-29

Kinesin spindle protein (KSP) belongs to the kinesin superfamily of microtubule-based motor proteins. KSP is responsible for the establishment of the bipolar mitotic spindle which mediates cell division. Inhibition of KSP expedites the blockade of the normal cell cycle during mitosis through the generation of monoastral MT arrays that finally cause apoptotic cell death. As KSP is highly expressed in proliferating/cancer cells, it has gained considerable attention as a potential drug target for cancer chemotherapy. Therefore, this study envisaged to design novel KSP inhibitors by employing computational techniques/tools such as pharmacophore modelling, virtual database screening, molecular docking and molecular dynamics. Initially, the pharmacophore models were generated from the data-set of highly potent KSP inhibitors and the pharmacophore models were validated against in house test set ligands. The validated pharmacophore model was then taken for database screening (Maybridge and ChemBridge) to yield hits, which were further filtered for their drug-likeliness. The potential hits retrieved from virtual database screening were docked using CDOCKER to identify the ligand binding landscape. The top-ranked hits obtained from molecular docking were progressed to molecular dynamics (AMBER) simulations to deduce the ligand binding affinity. This study identified MB-41570 and CB-10358 as potential hits and evaluated these experimentally using in vitro KSP ATPase inhibition assays.

Modelling potential/current distribution in microbial electrochemical systems shows how the optimal bioanode architecture depends on electrolyte conductivity.

PubMed

Lacroix, Rémy; Da Silva, Serge; Gaig, Monica Viaplana; Rousseau, Raphael; Délia, Marie-Line; Bergel, Alain

2014-11-07

The theoretical bases for modelling the distribution of the electrostatic potential in microbial electrochemical systems are described. The secondary potential distribution (i.e. without mass transport limitation of the substrate) is shown to be sufficient to validly address microbial electrolysis cells (MECs). MECs are modelled with two different ionic conductivities of the solution (1 and 5.3 S m(-1)) and two bioanode kinetics (jmax = 5.8 or 34 A m(-2)). A conventional reactor configuration, with the anode and the cathode face to face, is compared with a configuration where the bioanode perpendicular to the cathode implements the electrochemical reaction on its two sides. The low solution conductivity is shown to have a crucial impact, which cancels out the advantages obtained by setting the bioanode perpendicular to the cathode. For the same reason, when the surface area of the anode is increased by multiplying the number of plates, care must be taken not to create too dense anode architecture. Actually, the advantages of increasing the surface area by multiplying the number of plates can be lost through worsening of the electrochemical conditions in the multi-layered anode, because of the increase of the electrostatic potential of the solution inside the anode structure. The model gives the first theoretical bases for scaling up MECs in a rather simple but rigorous way.

Evaluating simplified methods for liquefaction assessment for loss estimation

NASA Astrophysics Data System (ADS)

Kongar, Indranil; Rossetto, Tiziana; Giovinazzi, Sonia

2017-06-01

Currently, some catastrophe models used by the insurance industry account for liquefaction by applying a simple factor to shaking-induced losses. The factor is based only on local liquefaction susceptibility and this highlights the need for a more sophisticated approach to incorporating the effects of liquefaction in loss models. This study compares 11 unique models, each based on one of three principal simplified liquefaction assessment methods: liquefaction potential index (LPI) calculated from shear-wave velocity, the HAZUS software method and a method created specifically to make use of USGS remote sensing data. Data from the September 2010 Darfield and February 2011 Christchurch earthquakes in New Zealand are used to compare observed liquefaction occurrences to forecasts from these models using binary classification performance measures. The analysis shows that the best-performing model is the LPI calculated using known shear-wave velocity profiles, which correctly forecasts 78 % of sites where liquefaction occurred and 80 % of sites where liquefaction did not occur, when the threshold is set at 7. However, these data may not always be available to insurers. The next best model is also based on LPI but uses shear-wave velocity profiles simulated from the combination of USGS VS30 data and empirical functions that relate VS30 to average shear-wave velocities at shallower depths. This model correctly forecasts 58 % of sites where liquefaction occurred and 84 % of sites where liquefaction did not occur, when the threshold is set at 4. These scores increase to 78 and 86 %, respectively, when forecasts are based on liquefaction probabilities that are empirically related to the same values of LPI. This model is potentially more useful for insurance since the input data are publicly available. HAZUS models, which are commonly used in studies where no local model is available, perform poorly and incorrectly forecast 87 % of sites where liquefaction occurred, even at optimal thresholds. This paper also considers two models (HAZUS and EPOLLS) for estimation of the scale of liquefaction in terms of permanent ground deformation but finds that both models perform poorly, with correlations between observations and forecasts lower than 0.4 in all cases. Therefore these models potentially provide negligible additional value to loss estimation analysis outside of the regions for which they have been developed.

A gauged finite-element potential formulation for accurate inductive and galvanic modelling of 3-D electromagnetic problems

NASA Astrophysics Data System (ADS)

Ansari, S. M.; Farquharson, C. G.; MacLachlan, S. P.

2017-07-01

In this paper, a new finite-element solution to the potential formulation of the geophysical electromagnetic (EM) problem that explicitly implements the Coulomb gauge, and that accurately computes the potentials and hence inductive and galvanic components, is proposed. The modelling scheme is based on using unstructured tetrahedral meshes for domain subdivision, which enables both realistic Earth models of complex geometries to be considered and efficient spatially variable refinement of the mesh to be done. For the finite-element discretization edge and nodal elements are used for approximating the vector and scalar potentials respectively. The issue of non-unique, incorrect potentials from the numerical solution of the usual incomplete-gauged potential system is demonstrated for a benchmark model from the literature that uses an electric-type EM source, through investigating the interface continuity conditions for both the normal and tangential components of the potential vectors, and by showing inconsistent results obtained from iterative and direct linear equation solvers. By explicitly introducing the Coulomb gauge condition as an extra equation, and by augmenting the Helmholtz equation with the gradient of a Lagrange multiplier, an explicitly gauged system for the potential formulation is formed. The solution to the discretized form of this system is validated for the above-mentioned example and for another classic example that uses a magnetic EM source. In order to stabilize the iterative solution of the gauged system, a block diagonal pre-conditioning scheme that is based upon the Schur complement of the potential system is used. For all examples, both the iterative and direct solvers produce the same responses for the potentials, demonstrating the uniqueness of the numerical solution for the potentials and fixing the problems with the interface conditions between cells observed for the incomplete-gauged system. These solutions of the gauged system also produce the physically anticipated behaviours for the inductive and galvanic components of the electric field. For a realistic geophysical scenario, the gauged scheme is also used to synthesize the magnetic field response of a model of the Ovoid ore deposit at Voisey's Bay, Labrador, Canada. The results are in good agreement with the helicopter-borne EM data from the real survey, and the inductive and galvanic parts of the current density show expected behaviours.

Surrogate Based Uni/Multi-Objective Optimization and Distribution Estimation Methods

NASA Astrophysics Data System (ADS)

Gong, W.; Duan, Q.; Huo, X.

2017-12-01

Parameter calibration has been demonstrated as an effective way to improve the performance of dynamic models, such as hydrological models, land surface models, weather and climate models etc. Traditional optimization algorithms usually cost a huge number of model evaluations, making dynamic model calibration very difficult, or even computationally prohibitive. With the help of a serious of recently developed adaptive surrogate-modelling based optimization methods: uni-objective optimization method ASMO, multi-objective optimization method MO-ASMO, and probability distribution estimation method ASMO-PODE, the number of model evaluations can be significantly reduced to several hundreds, making it possible to calibrate very expensive dynamic models, such as regional high resolution land surface models, weather forecast models such as WRF, and intermediate complexity earth system models such as LOVECLIM. This presentation provides a brief introduction to the common framework of adaptive surrogate-based optimization algorithms of ASMO, MO-ASMO and ASMO-PODE, a case study of Common Land Model (CoLM) calibration in Heihe river basin in Northwest China, and an outlook of the potential applications of the surrogate-based optimization methods.

Integrating species distributional, conservation planning, and individual based population models: A case study in critical habitat evaluation for the Northern Spotted Owl

EPA Science Inventory

Background / Question / Methods As part of the ongoing northern spotted owl recovery planning effort, we evaluated a series of alternative potential critical habitat scenarios using a species-distribution model (MaxEnt), a conservation-planning model (Zonation), and an individua...

DYNAMIC EVALUATION OF REGIONAL AIR QUALITY MODELS: ASSESSING CHANGES TO O 3 STEMMING FROM CHANGES IN EMISSIONS AND METEOROLOGY

EPA Science Inventory

Regional-scale air quality models are used to estimate the response of air pollutants to potential emission control strategies as part of the decision-making process. Traditionally, the model predicted pollutant concentrations are evaluated for the “base case” to assess a model’s...

Applying Silvia's Model of Interest to Academic Text: Is There a Third Appraisal?

ERIC Educational Resources Information Center

Connelly, Daniel A.

2011-01-01

Recent research, treating interest as an emotion, indicates the cognitive appraisals of novelty-complexity and coping potential predict interest. This appraisal-based model of interest has not yet been applied to educational research. The present study evaluated the significance of the model regarding the activity of reading expository,…

A brain-region-based meta-analysis method utilizing the Apriori algorithm.

PubMed

Niu, Zhendong; Nie, Yaoxin; Zhou, Qian; Zhu, Linlin; Wei, Jieyao

2016-05-18

Brain network connectivity modeling is a crucial method for studying the brain's cognitive functions. Meta-analyses can unearth reliable results from individual studies. Meta-analytic connectivity modeling is a connectivity analysis method based on regions of interest (ROIs) which showed that meta-analyses could be used to discover brain network connectivity. In this paper, we propose a new meta-analysis method that can be used to find network connectivity models based on the Apriori algorithm, which has the potential to derive brain network connectivity models from activation information in the literature, without requiring ROIs. This method first extracts activation information from experimental studies that use cognitive tasks of the same category, and then maps the activation information to corresponding brain areas by using the automatic anatomical label atlas, after which the activation rate of these brain areas is calculated. Finally, using these brain areas, a potential brain network connectivity model is calculated based on the Apriori algorithm. The present study used this method to conduct a mining analysis on the citations in a language review article by Price (Neuroimage 62(2):816-847, 2012). The results showed that the obtained network connectivity model was consistent with that reported by Price. The proposed method is helpful to find brain network connectivity by mining the co-activation relationships among brain regions. Furthermore, results of the co-activation relationship analysis can be used as a priori knowledge for the corresponding dynamic causal modeling analysis, possibly achieving a significant dimension-reducing effect, thus increasing the efficiency of the dynamic causal modeling analysis.

A Critical Assessment of Combined Ligand-based and Structure-based Approaches to hERG Channel Blocker Modeling

PubMed Central

Du-Cuny, Lei; Chen, Lu; Zhang, Shuxing

2014-01-01

Blockade of hERG channel prolongs the duration of the cardiac action potential and is a common reason for drug failure in preclinical safety trials. Therefore, it is of great importance to develop robust in silico tools to predict potential hERG blockers in the early stages of drug discovery and development. Herein we described comprehensive approaches to assess the discrimination of hERG-active and -inactive compounds by combining QSAR modeling, pharmacophore analysis, and molecular docking. Our consensus models demonstrated high predictive capacity and improved enrichment, and they could correctly classify 91.8% of 147 hERG blockers from 351 inactives. To further enhance our modeling effort, hERG homology models were constructed and molecular docking studies were conducted, resulting in high correlations (R2=0.81) between predicted and experimental binding affinities. We expect our unique models can be applied to efficient screening for hERG blockades, and our extensive understanding of the hERG-inhibitor interactions will facilitate the rational design of drugs devoid of hERG channel activity and hence with reduced cardiac toxicities. PMID:21902220

Monthly hydroclimatology of the continental United States

NASA Astrophysics Data System (ADS)

Petersen, Thomas; Devineni, Naresh; Sankarasubramanian, A.

2018-04-01

Physical/semi-empirical models that do not require any calibration are of paramount need for estimating hydrological fluxes for ungauged sites. We develop semi-empirical models for estimating the mean and variance of the monthly streamflow based on Taylor Series approximation of a lumped physically based water balance model. The proposed models require mean and variance of monthly precipitation and potential evapotranspiration, co-variability of precipitation and potential evapotranspiration and regionally calibrated catchment retention sensitivity, atmospheric moisture uptake sensitivity, groundwater-partitioning factor, and the maximum soil moisture holding capacity parameters. Estimates of mean and variance of monthly streamflow using the semi-empirical equations are compared with the observed estimates for 1373 catchments in the continental United States. Analyses show that the proposed models explain the spatial variability in monthly moments for basins in lower elevations. A regionalization of parameters for each water resources region show good agreement between observed moments and model estimated moments during January, February, March and April for mean and all months except May and June for variance. Thus, the proposed relationships could be employed for understanding and estimating the monthly hydroclimatology of ungauged basins using regional parameters.

Minding the Cyber-Physical Gap: Model-Based Analysis and Mitigation of Systemic Perception-Induced Failure

PubMed Central

2017-01-01

The cyber-physical gap (CPG) is the difference between the ‘real’ state of the world and the way the system perceives it. This discrepancy often stems from the limitations of sensing and data collection technologies and capabilities, and is inevitable at some degree in any cyber-physical system (CPS). Ignoring or misrepresenting such limitations during system modeling, specification, design, and analysis can potentially result in systemic misconceptions, disrupted functionality and performance, system failure, severe damage, and potential detrimental impacts on the system and its environment. We propose CPG-Aware Modeling & Engineering (CPGAME), a conceptual model-based approach to capturing, explaining, and mitigating the CPG. CPGAME enhances the systems engineer’s ability to cope with CPGs, mitigate them by design, and prevent erroneous decisions and actions. We demonstrate CPGAME by applying it for modeling and analysis of the 1979 Three Miles Island 2 nuclear accident, and show how its meltdown could be mitigated. We use ISO-19450:2015—Object Process Methodology as our conceptual modeling framework. PMID:28714910

A full potential inverse method based on a density linearization scheme for wing design

NASA Technical Reports Server (NTRS)

Shankar, V.

1982-01-01

A mixed analysis inverse procedure based on the full potential equation in conservation form was developed to recontour a given base wing to produce density linearization scheme in applying the pressure boundary condition in terms of the velocity potential. The FL030 finite volume analysis code was modified to include the inverse option. The new surface shape information, associated with the modified pressure boundary condition, is calculated at a constant span station based on a mass flux integration. The inverse method is shown to recover the original shape when the analysis pressure is not altered. Inverse calculations for weakening of a strong shock system and for a laminar flow control (LFC) pressure distribution are presented. Two methods for a trailing edge closure model are proposed for further study.

The interaction model of client health behavior: application to the study of community-based elders.

PubMed

Cox, C L

1986-10-01

The Interaction Model of Client Health Behavior (IMCHB) was used to direct a systematic and comprehensive description of community-based elders. The abstract concepts, constructs, factors, and variables described by one element of the model were able to account for 54% of the variance in elders' health status and 47% of the variance in their well-being. The model, as operationalized in this study, pointed to clear demographic, social, and health profiles that identified the elder at risk for decreased health, well-being, and self-care potential. The IMCHB would appear to be a useful framework with which to establish an empirical base on which nursing interventions could be developed.

Characterizing attention with predictive network models

PubMed Central

Rosenberg, M. D.; Finn, E. S.; Scheinost, D.; Constable, R. T.; Chun, M. M.

2017-01-01

Recent work shows that models based on functional connectivity in large-scale brain networks can predict individuals’ attentional abilities. Some of the first generalizable neuromarkers of cognitive function, these models also inform our basic understanding of attention, providing empirical evidence that (1) attention is a network property of brain computation, (2) the functional architecture that underlies attention can be measured while people are not engaged in any explicit task, and (3) this architecture supports a general attentional ability common to several lab-based tasks and impaired in attention deficit hyperactivity disorder. Looking ahead, connectivity-based predictive models of attention and other cognitive abilities and behaviors may potentially improve the assessment, diagnosis, and treatment of clinical dysfunction. PMID:28238605

3-D model-based tracking for UAV indoor localization.

PubMed

Teulière, Céline; Marchand, Eric; Eck, Laurent

2015-05-01

This paper proposes a novel model-based tracking approach for 3-D localization. One main difficulty of standard model-based approach lies in the presence of low-level ambiguities between different edges. In this paper, given a 3-D model of the edges of the environment, we derive a multiple hypotheses tracker which retrieves the potential poses of the camera from the observations in the image. We also show how these candidate poses can be integrated into a particle filtering framework to guide the particle set toward the peaks of the distribution. Motivated by the UAV indoor localization problem where GPS signal is not available, we validate the algorithm on real image sequences from UAV flights.

An assessment of the carbon balance of arctic tundra: comparisons among observations, process models, and atmospheric inversions

USGS Publications Warehouse

McGuire, A.D.; Christensen, T.R.; Hayes, D.; Heroult, A.; Euskirchen, E.; Yi, Y.; Kimball, J.S.; Koven, C.; Lafleur, P.; Miller, P.A.; Oechel, W.; Peylin, P.; Williams, M.

2012-01-01

Although arctic tundra has been estimated to cover only 8% of the global land surface, the large and potentially labile carbon pools currently stored in tundra soils have the potential for large emissions of carbon (C) under a warming climate. These emissions as radiatively active greenhouse gases in the form of both CO2 and CH4 could amplify global warming. Given the potential sensitivity of these ecosystems to climate change and the expectation that the Arctic will experience appreciable warming over the next century, it is important to assess whether responses of C exchange in tundra regions are likely to enhance or mitigate warming. In this study we compared analyses of C exchange of Arctic tundra between 1990–1999 and 2000–2006 among observations, regional and global applications of process-based terrestrial biosphere models, and atmospheric inversion models. Syntheses of the compilation of flux observations and of inversion model results indicate that the annual exchange of CO2 between arctic tundra and the atmosphere has large uncertainties that cannot be distinguished from neutral balance. The mean estimate from an ensemble of process-based model simulations suggests that arctic tundra acted as a sink for atmospheric CO2 in recent decades, but based on the uncertainty estimates it cannot be determined with confidence whether these ecosystems represent a weak or a strong sink. Tundra was 0.6 °C warmer in the 2000s compared to the 1990s. The central estimates of the observations, process-based models, and inversion models each identify stronger sinks in the 2000s compared with the 1990s. Similarly, the observations and the applications of regional process-based models suggest that CH4 emissions from arctic tundra have increased from the 1990s to 2000s. Based on our analyses of the estimates from observations, process-based models, and inversion models, we estimate that arctic tundra was a sink for atmospheric CO2 of 110 Tg C yr-1 (uncertainty between a sink of 291 Tg C yr-1 and a source of 80 Tg C yr-1) and a source of CH4 to the atmosphere of 19 Tg C yr-1 (uncertainty between sources of 8 and 29 Tg C yr-1). The suite of analyses conducted in this study indicate that it is clearly important to reduce uncertainties in the observations, process-based models, and inversions in order to better understand the degree to which Arctic tundra is influencing atmospheric CO2 and CH4 concentrations. The reduction of uncertainties can be accomplished through (1) the strategic placement of more CO2 and CH4 monitoring stations to reduce uncertainties in inversions, (2) improved observation networks of ground-based measurements of CO2 and CH4 exchange to understand exchange in response to disturbance and across gradients of hydrological variability, and (3) the effective transfer of information from enhanced observation networks into process-based models to improve the simulation of CO2 and CH4 exchange from arctic tundra to the atmosphere.

Nonassociative plasticity model for cohesionless materials and its implementation in soil-structure interaction

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

Hashmi, Q.S.E.

A constitutive model based on rate-independent elastoplasticity concepts is developed and used to simulate the behavior of geologic materials under arbitrary three-dimensional stress paths. The model accounts for various factors such as friction, stress path, and stress history that influence the behavior of geologic materials. A hierarchical approach is adopted whereby models of progressively increasing sophistication are developed from a basic isotropic-hardening associate model. Nonassociativeness is introduced as correction or perturbation to the basic model. Deviation of normality of the plastic-strain increments to the yield surface F is captured through nonassociativeness. The plastic potential Q is obtained by applying amore » correction to F. This simplified approach restricts the number of extra parameters required to define the plastic potential Q. The material constants associated with the model are identified, and they are evaluated for three different sands (Leighton Buzzard, Munich and McCormick Ranch). The model is then verified by comparing predictions with laboratory tests from which the constants were found, and typical tests not used for finding the constants. Based on the above findings, a soil-footing system is analyzed using finite-element techniques.« less

The Danger Model Approach to the Pathogenesis of the Rheumatic Diseases

PubMed Central

Pacheco-Tena, César; González-Chávez, Susana Aideé

2015-01-01

The danger model was proposed by Polly Matzinger as complement to the traditional self-non-self- (SNS-) model to explain the immunoreactivity. The danger model proposes a central role of the tissular cells' discomfort as an element to prime the immune response processes in opposition to the traditional SNS-model where foreignness is a prerequisite. However recent insights in the proteomics of diverse tissular cells have revealed that under stressful conditions they have a significant potential to initiate, coordinate, and perpetuate autoimmune processes, in many cases, ruling over the adaptive immune response cells; this ruling potential can also be confirmed by observations in several genetically manipulated animal models. Here, we review the pathogenesis of rheumatic diseases such as systemic lupus erythematous, rheumatoid arthritis, spondyloarthritis including ankylosing spondylitis, psoriasis, and Crohn's disease and provide realistic approaches based on the logic of the danger model. We assume that tissular dysfunction is a prerequisite for chronic autoimmunity and propose two genetically conferred hypothetical roles for the tissular cells causing the disease: (A) the Impaired cell and (B) the paranoid cell. Both roles are not mutually exclusive. Some examples in human disease and in animal models are provided based on current evidence. PMID:25973436

Analysis of Solar Potential of Roofs Based on Digital Terrain Model

NASA Astrophysics Data System (ADS)

Gorički, M.; Poslončec-Petrić, V.; Frangeš, S.; Bačić, Ž.

2017-09-01

One of the basic goals of the smart city concept is to create a high-quality environment that is long sustainable and economically justifiable. The priority and concrete goal today is to promote and provide sustainable sources of energy (SSE). Croatia is rich with sun energy and as one of the sunniest European countries, it has a huge insufficiently used solar potential at its disposal. The paper describes the procedure of analysing the solar potential of a pilot area Sveti Križ Začretje by means of digital surface model (DSM) and based on the data available in the Meteorological and Hydrological Service of the Republic of Croatia. Although a more detailed analysis would require some additional factors, it is clear that the installation of 19,6m2 of solar panels in each household could cover annual requirements of the household in the analysed area, the locality Sveti Križ Začretje.

Global structure–activity relationship model for nonmutagenic carcinogens using virtual ligand-protein interactions as model descriptors

PubMed Central

Cunningham, Albert R.; Trent, John O.

2012-01-01

Structure–activity relationship (SAR) models are powerful tools to investigate the mechanisms of action of chemical carcinogens and to predict the potential carcinogenicity of untested compounds. We describe the use of a traditional fragment-based SAR approach along with a new virtual ligand-protein interaction-based approach for modeling of nonmutagenic carcinogens. The ligand-based SAR models used descriptors derived from computationally calculated ligand-binding affinities for learning set agents to 5495 proteins. Two learning sets were developed. One set was from the Carcinogenic Potency Database, where chemicals tested for rat carcinogenesis along with Salmonella mutagenicity data were provided. The second was from Malacarne et al. who developed a learning set of nonalerting compounds based on rodent cancer bioassay data and Ashby’s structural alerts. When the rat cancer models were categorized based on mutagenicity, the traditional fragment model outperformed the ligand-based model. However, when the learning sets were composed solely of nonmutagenic or nonalerting carcinogens and noncarcinogens, the fragment model demonstrated a concordance of near 50%, whereas the ligand-based models demonstrated a concordance of 71% for nonmutagenic carcinogens and 74% for nonalerting carcinogens. Overall, these findings suggest that expert system analysis of virtual chemical protein interactions may be useful for developing predictive SAR models for nonmutagenic carcinogens. Moreover, a more practical approach for developing SAR models for carcinogenesis may include fragment-based models for chemicals testing positive for mutagenicity and ligand-based models for chemicals devoid of DNA reactivity. PMID:22678118

Global structure-activity relationship model for nonmutagenic carcinogens using virtual ligand-protein interactions as model descriptors.

PubMed

Cunningham, Albert R; Carrasquer, C Alex; Qamar, Shahid; Maguire, Jon M; Cunningham, Suzanne L; Trent, John O

2012-10-01

Structure-activity relationship (SAR) models are powerful tools to investigate the mechanisms of action of chemical carcinogens and to predict the potential carcinogenicity of untested compounds. We describe the use of a traditional fragment-based SAR approach along with a new virtual ligand-protein interaction-based approach for modeling of nonmutagenic carcinogens. The ligand-based SAR models used descriptors derived from computationally calculated ligand-binding affinities for learning set agents to 5495 proteins. Two learning sets were developed. One set was from the Carcinogenic Potency Database, where chemicals tested for rat carcinogenesis along with Salmonella mutagenicity data were provided. The second was from Malacarne et al. who developed a learning set of nonalerting compounds based on rodent cancer bioassay data and Ashby's structural alerts. When the rat cancer models were categorized based on mutagenicity, the traditional fragment model outperformed the ligand-based model. However, when the learning sets were composed solely of nonmutagenic or nonalerting carcinogens and noncarcinogens, the fragment model demonstrated a concordance of near 50%, whereas the ligand-based models demonstrated a concordance of 71% for nonmutagenic carcinogens and 74% for nonalerting carcinogens. Overall, these findings suggest that expert system analysis of virtual chemical protein interactions may be useful for developing predictive SAR models for nonmutagenic carcinogens. Moreover, a more practical approach for developing SAR models for carcinogenesis may include fragment-based models for chemicals testing positive for mutagenicity and ligand-based models for chemicals devoid of DNA reactivity.

An advanced process-based distributed model for the investigation of rainfall-induced landslides: The effect of process representation and boundary conditions

NASA Astrophysics Data System (ADS)

Anagnostopoulos, Grigorios G.; Fatichi, Simone; Burlando, Paolo

2015-09-01

Extreme rainfall events are the major driver of shallow landslide occurrences in mountainous and steep terrain regions around the world. Subsurface hydrology has a dominant role on the initiation of rainfall-induced shallow landslides, since changes in the soil water content affect significantly the soil shear strength. Rainfall infiltration produces an increase of soil water potential, which is followed by a rapid drop in apparent cohesion. Especially on steep slopes of shallow soils, this loss of shear strength can lead to failure even in unsaturated conditions before positive water pressures are developed. We present HYDROlisthisis, a process-based model, fully distributed in space with fine time resolution, in order to investigate the interactions between surface and subsurface hydrology and shallow landslides initiation. Fundamental elements of the approach are the dependence of shear strength on the three-dimensional (3-D) field of soil water potential, as well as the temporal evolution of soil water potential during the wetting and drying phases. Specifically, 3-D variably saturated flow conditions, including soil hydraulic hysteresis and preferential flow phenomena, are simulated for the subsurface flow, coupled with a surface runoff routine based on the kinematic wave approximation. The geotechnical component of the model is based on a multidimensional limit equilibrium analysis, which takes into account the basic principles of unsaturated soil mechanics. A series of numerical simulations were carried out with various boundary conditions and using different hydrological and geotechnical components. Boundary conditions in terms of distributed soil depth were generated using both empirical and process-based models. The effect of including preferential flow and soil hydraulic hysteresis was tested together with the replacement of the infinite slope assumption with the multidimensional limit equilibrium analysis. The results show that boundary conditions play a crucial role in the model performance and that the introduced hydrological (preferential flow and soil hydraulic hysteresis) and geotechnical components (multidimensional limit equilibrium analysis) significantly improve predictive capabilities in the presented case study.

Comparison of structural, thermodynamic, kinetic and mass transport properties of Mg(2+) ion models commonly used in biomolecular simulations.

PubMed

Panteva, Maria T; Giambaşu, George M; York, Darrin M

2015-05-15

The prevalence of Mg(2+) ions in biology and their essential role in nucleic acid structure and function has motivated the development of various Mg(2+) ion models for use in molecular simulations. Currently, the most widely used models in biomolecular simulations represent a nonbonded metal ion as an ion-centered point charge surrounded by a nonelectrostatic pairwise potential that takes into account dispersion interactions and exchange effects that give rise to the ion's excluded volume. One strategy toward developing improved models for biomolecular simulations is to first identify a Mg(2+) model that is consistent with the simulation force fields that closely reproduces a range of properties in aqueous solution, and then, in a second step, balance the ion-water and ion-solute interactions by tuning parameters in a pairwise fashion where necessary. The present work addresses the first step in which we compare 17 different nonbonded single-site Mg(2+) ion models with respect to their ability to simultaneously reproduce structural, thermodynamic, kinetic and mass transport properties in aqueous solution. None of the models based on a 12-6 nonelectrostatic nonbonded potential was able to reproduce the experimental radial distribution function, solvation free energy, exchange barrier and diffusion constant. The models based on a 12-6-4 potential offered improvement, and one model in particular, in conjunction with the SPC/E water model, performed exceptionally well for all properties. The results reported here establish useful benchmark calculations for Mg(2+) ion models that provide insight into the origin of the behavior in aqueous solution, and may aid in the development of next-generation models that target specific binding sites in biomolecules. © 2015 Wiley Periodicals, Inc.

Review and analysis of the DNW/Model 360 rotor acoustic data base

NASA Technical Reports Server (NTRS)

Zinner, R. A.; Boxwell, D. A.; Spencer, R. H.

1989-01-01

A comprehensive model rotor aeroacoustic data base was collected in a large anechoic wind tunnel in 1986. Twenty-six microphones were positioned around the azimuth to collect acoustic data for approximately 150 different test conditions. A dynamically scaled, blade-pressure-instrumented model of the forward rotor of the BH360 helicopter simultaneously provided blade pressures for correlation with the acoustic data. High-speed impulsive noise, blade-vortex interaction noise, low-frequency noise, and broadband noise were all captured in this extensive data base. Trends are presentes for each noise source, with important parametric variations. The purpose of this paper is to introduce this data base and illustrate its potential for predictive code validation.

Updating the Duplex Design for Test-Based Accountability in the Twenty-First Century

ERIC Educational Resources Information Center

Bejar, Isaac I.; Graf, E. Aurora

2010-01-01

The duplex design by Bock and Mislevy for school-based testing is revisited and evaluated as a potential platform in test-based accountability assessments today. We conclude that the model could be useful in meeting the many competing demands of today's test-based accountability assessments, although many research questions will need to be…

Computational identification of structural factors affecting the mutagenic potential of aromatic amines: study design and experimental validation.

PubMed

Slavov, Svetoslav H; Stoyanova-Slavova, Iva; Mattes, William; Beger, Richard D; Brüschweiler, Beat J

2018-07-01

A grid-based, alignment-independent 3D-SDAR (three-dimensional spectral data-activity relationship) approach based on simulated 13 C and 15 N NMR chemical shifts augmented with through-space interatomic distances was used to model the mutagenicity of 554 primary and 419 secondary aromatic amines. A robust modeling strategy supported by extensive validation including randomized training/hold-out test set pairs, validation sets, "blind" external test sets as well as experimental validation was applied to avoid over-parameterization and build Organization for Economic Cooperation and Development (OECD 2004) compliant models. Based on an experimental validation set of 23 chemicals tested in a two-strain Salmonella typhimurium Ames assay, 3D-SDAR was able to achieve performance comparable to 5-strain (Ames) predictions by Lhasa Limited's Derek and Sarah Nexus for the same set. Furthermore, mapping of the most frequently occurring bins on the primary and secondary aromatic amine structures allowed the identification of molecular features that were associated either positively or negatively with mutagenicity. Prominent structural features found to enhance the mutagenic potential included: nitrobenzene moieties, conjugated π-systems, nitrothiophene groups, and aromatic hydroxylamine moieties. 3D-SDAR was also able to capture "true" negative contributions that are particularly difficult to detect through alternative methods. These include sulphonamide, acetamide, and other functional groups, which not only lack contributions to the overall mutagenic potential, but are known to actively lower it, if present in the chemical structures of what otherwise would be potential mutagens.

Testing the robustness of management decisions to uncertainty: Everglades restoration scenarios.

PubMed

Fuller, Michael M; Gross, Louis J; Duke-Sylvester, Scott M; Palmer, Mark

2008-04-01

To effectively manage large natural reserves, resource managers must prepare for future contingencies while balancing the often conflicting priorities of different stakeholders. To deal with these issues, managers routinely employ models to project the response of ecosystems to different scenarios that represent alternative management plans or environmental forecasts. Scenario analysis is often used to rank such alternatives to aid the decision making process. However, model projections are subject to uncertainty in assumptions about model structure, parameter values, environmental inputs, and subcomponent interactions. We introduce an approach for testing the robustness of model-based management decisions to the uncertainty inherent in complex ecological models and their inputs. We use relative assessment to quantify the relative impacts of uncertainty on scenario ranking. To illustrate our approach we consider uncertainty in parameter values and uncertainty in input data, with specific examples drawn from the Florida Everglades restoration project. Our examples focus on two alternative 30-year hydrologic management plans that were ranked according to their overall impacts on wildlife habitat potential. We tested the assumption that varying the parameter settings and inputs of habitat index models does not change the rank order of the hydrologic plans. We compared the average projected index of habitat potential for four endemic species and two wading-bird guilds to rank the plans, accounting for variations in parameter settings and water level inputs associated with hypothetical future climates. Indices of habitat potential were based on projections from spatially explicit models that are closely tied to hydrology. For the American alligator, the rank order of the hydrologic plans was unaffected by substantial variation in model parameters. By contrast, simulated major shifts in water levels led to reversals in the ranks of the hydrologic plans in 24.1-30.6% of the projections for the wading bird guilds and several individual species. By exposing the differential effects of uncertainty, relative assessment can help resource managers assess the robustness of scenario choice in model-based policy decisions.

Virtual Universities: Current Models and Future Trends.

ERIC Educational Resources Information Center

Guri-Rosenblit, Sarah

2001-01-01

Describes current models of distance education (single-mode distance teaching universities, dual- and mixed-mode universities, extension services, consortia-type ventures, and new technology-based universities), including their merits and problems. Discusses future trends in potential student constituencies, faculty roles, forms of knowledge…

Computer-Based Resource Accounting Model for Generating Aggregate Resource Impacts of Alternative Automobile Technologies : Volume 1. Fleet Attributes Model

DOT National Transportation Integrated Search

1977-01-01

Auto production and operation consume energy, material, capital and labor resources. Numerous substitution possibilities exist within and between resource sectors, corresponding to the broad spectrum of potential design technologies. Alternative auto...

Modelling the Interior Structure of Enceladus Based on the 2014's Cassini Gravity Data.

PubMed

Taubner, R-S; Leitner, J J; Firneis, M G; Hitzenberger, R

2016-06-01

We present a model for the internal structure of Saturn's moon Enceladus. This model allows us to estimate the physical conditions at the bottom of the satellite's potential subsurface water reservoir and to determine the radial distribution of pressure and gravity. This leads to a better understanding of the physical and chemical conditions at the water/rock boundary. This boundary is the most promising area on icy moons for astrobiological studies as it could serve as a potential habitat for extraterrestrial life similar to terrestrial microbes that inhabit rocky mounds on Earth's sea floors.

[Discovery of potential LXRβ agonists from Chinese herbs using molecular simulation methods].

PubMed

Luo, Gang-Gang; Lu, Fang; Qiao, Lian-Sheng; Li, Yong; Zhang, Yan-Ling

2016-08-01

Liver X receptor β (LXRβ) has been a new target in the treatment of hyperlipemia, which was related to the cholesterol homeostasis. In this study, the quantitative pharmacophores were constructed by 3D-QSAR pharmacophore (Hypogen) method based on the LXRβ agonists. The optimal pharmacophore model containing one hydrogen bond acceptor, two hydrophobics and one ring aromatic was obtained based on five assessment indictors, including the correlation between predicted value and experimental value of the compounds in training set (correlation), Δcost of the models (Δcost), hit rate of active compounds (HRA), identification of effectiveness index (IEI) and comprehensive evaluation index (CAI). And the values of the five assessment indicators were 0.95, 128.65, 84.44%, 2.58 and 2.18 respectively. The best model as a query to screen the traditional Chinese medicine database (TCMD), a list of 309 compounds was obtained andwere then refined using Libdock program. Finally, based on the screening rules of the Libdock score of initial compound and the key interactions between initial compound and receptor, four compounds, demethoxycurcumin, isolicoflavonol, licochalcone E and silydianin, were selected as potential LXRβ agonists. The molecular simulation methods were high-efficiency and time-saving to obtainthe potential LXRβ agonists, which could provide assistance for further researchingnovel anti-hyperlipidemia drugs. Copyright© by the Chinese Pharmaceutical Association.

Improved Ionospheric Electrodynamic Models and Application to Calculating Joule Heating Rates

NASA Technical Reports Server (NTRS)

Weimer, D. R.

2004-01-01

Improved techniques have been developed for empirical modeling of the high-latitude electric potentials and magnetic field aligned currents (FAC) as a function of the solar wind parameters. The FAC model is constructed using scalar magnetic Euler potentials, and functions as a twin to the electric potential model. The improved models have more accurate field values as well as more accurate boundary locations. Non-linear saturation effects in the solar wind-magnetosphere coupling are also better reproduced. The models are constructed using a hybrid technique, which has spherical harmonic functions only within a small area at the pole. At lower latitudes the potentials are constructed from multiple Fourier series functions of longitude, at discrete latitudinal steps. It is shown that the two models can be used together in order to calculate the total Poynting flux and Joule heating in the ionosphere. An additional model of the ionospheric conductivity is not required in order to obtain the ionospheric currents and Joule heating, as the conductivity variations as a function of the solar inclination are implicitly contained within the FAC model's data. The models outputs are shown for various input conditions, as well as compared with satellite measurements. The calculations of the total Joule heating are compared with results obtained by the inversion of ground-based magnetometer measurements. Like their predecessors, these empirical models should continue to be a useful research and forecast tools.

Applying the cell-based coagulation model in the management of critical bleeding.

PubMed

Ho, K M; Pavey, W

2017-03-01

The cell-based coagulation model was proposed 15 years ago, yet has not been applied commonly in the management of critical bleeding. Nevertheless, this alternative model may better explain the physiological basis of current coagulation management during critical bleeding. In this article we describe the limitations of the traditional coagulation protein cascade and standard coagulation tests, and explain the potential advantages of applying the cell-based model in current coagulation management strategies. The cell-based coagulation model builds on the traditional coagulation model and explains many recent clinical observations and research findings related to critical bleeding unexplained by the traditional model, including the encouraging results of using empirical 1:1:1 fresh frozen plasma:platelets:red blood cells transfusion strategy, and the use of viscoelastic and platelet function tests in patients with critical bleeding. From a practical perspective, applying the cell-based coagulation model also explains why new direct oral anticoagulants are effective systemic anticoagulants even without affecting activated partial thromboplastin time or the International Normalized Ratio in a dose-related fashion. The cell-based coagulation model represents the most cohesive scientific framework on which we can understand and manage coagulation during critical bleeding.

A technology path to tactical agent-based modeling

NASA Astrophysics Data System (ADS)

James, Alex; Hanratty, Timothy P.

2017-05-01

Wargaming is a process of thinking through and visualizing events that could occur during a possible course of action. Over the past 200 years, wargaming has matured into a set of formalized processes. One area of growing interest is the application of agent-based modeling. Agent-based modeling and its additional supporting technologies has potential to introduce a third-generation wargaming capability to the Army, creating a positive overmatch decision-making capability. In its simplest form, agent-based modeling is a computational technique that helps the modeler understand and simulate how the "whole of a system" responds to change over time. It provides a decentralized method of looking at situations where individual agents are instantiated within an environment, interact with each other, and empowered to make their own decisions. However, this technology is not without its own risks and limitations. This paper explores a technology roadmap, identifying research topics that could realize agent-based modeling within a tactical wargaming context.

Modeling Hemispheric Detonation Experiments in 2-Dimensions

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

Howard, W M; Fried, L E; Vitello, P A

2006-06-22

Experiments have been performed with LX-17 (92.5% TATB and 7.5% Kel-F 800 binder) to study scaling of detonation waves using a dimensional scaling in a hemispherical divergent geometry. We model these experiments using an arbitrary Lagrange-Eulerian (ALE3D) hydrodynamics code, with reactive flow models based on the thermo-chemical code, Cheetah. The thermo-chemical code Cheetah provides a pressure-dependent kinetic rate law, along with an equation of state based on exponential-6 fluid potentials for individual detonation product species, calibrated to high pressures ({approx} few Mbars) and high temperatures (20000K). The parameters for these potentials are fit to a wide variety of experimental data,more » including shock, compression and sound speed data. For the un-reacted high explosive equation of state we use a modified Murnaghan form. We model the detonator (including the flyer plate) and initiation system in detail. The detonator is composed of LX-16, for which we use a program burn model. Steinberg-Guinan models5 are used for the metal components of the detonator. The booster and high explosive are LX-10 and LX-17, respectively. For both the LX-10 and LX-17, we use a pressure dependent rate law, coupled with a chemical equilibrium equation of state based on Cheetah. For LX-17, the kinetic model includes carbon clustering on the nanometer size scale.« less

DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics

NASA Astrophysics Data System (ADS)

Wang, Han; Zhang, Linfeng; Han, Jiequn; E, Weinan

2018-07-01

Recent developments in many-body potential energy representation via deep learning have brought new hopes to addressing the accuracy-versus-efficiency dilemma in molecular simulations. Here we describe DeePMD-kit, a package written in Python/C++ that has been designed to minimize the effort required to build deep learning based representation of potential energy and force field and to perform molecular dynamics. Potential applications of DeePMD-kit span from finite molecules to extended systems and from metallic systems to chemically bonded systems. DeePMD-kit is interfaced with TensorFlow, one of the most popular deep learning frameworks, making the training process highly automatic and efficient. On the other end, DeePMD-kit is interfaced with high-performance classical molecular dynamics and quantum (path-integral) molecular dynamics packages, i.e., LAMMPS and the i-PI, respectively. Thus, upon training, the potential energy and force field models can be used to perform efficient molecular simulations for different purposes. As an example of the many potential applications of the package, we use DeePMD-kit to learn the interatomic potential energy and forces of a water model using data obtained from density functional theory. We demonstrate that the resulted molecular dynamics model reproduces accurately the structural information contained in the original model.

Investigations of potential bias in the estimation of lambda using Pradel's (1996) model for capture-recapture data

USGS Publications Warehouse

Hines, James E.; Nichols, James D.

2002-01-01

Pradel's (1996) temporal symmetry model permitting direct estimation and modelling of population growth rate, u i , provides a potentially useful tool for the study of population dynamics using marked animals. Because of its recent publication date, the approach has not seen much use, and there have been virtually no investigations directed at robustness of the resulting estimators. Here we consider several potential sources of bias, all motivated by specific uses of this estimation approach. We consider sampling situations in which the study area expands with time and present an analytic expression for the bias in u i We next consider trap response in capture probabilities and heterogeneous capture probabilities and compute large-sample and simulation-based approximations of resulting bias in u i . These approximations indicate that trap response is an especially important assumption violation that can produce substantial bias. Finally, we consider losses on capture and emphasize the importance of selecting the estimator for u i that is appropriate to the question being addressed. For studies based on only sighting and resighting data, Pradel's (1996) u i ' is the appropriate estimator.

Characterization of dipeptidylcarboxypeptidase of Leishmania donovani: a molecular model for structure based design of antileishmanials

NASA Astrophysics Data System (ADS)

Baig, Mirza Saqib; Kumar, Ashutosh; Siddiqi, Mohammad Imran; Goyal, Neena

2010-01-01

Leishmania donovani dipeptidylcarboxypeptidsae (LdDCP), an angiotensin converting enzyme (ACE) related metallopeptidase has been identified and characterized as a putative drug target for antileishmanial chemotherapy. The kinetic parameters for LdDCP with substrate, Hip-His-Leu were determined as, Km, 4 mM and Vmax, 1.173 μmole/ml/min. Inhibition studies revealed that known ACE inhibitors (captopril and bradykinin potentiating peptide; BPP1) were weak inhibitors for LdDCP as compared to human testicular ACE (htACE) with Ki values of 35.8 nM and 3.9 μM, respectively. Three dimensional model of LdDCP was generated based on crystal structure of Escherichia coli DCP (EcDCP) by means of comparative modeling and assessed using PROSAII, PROCHECK and WHATIF. Captopril docking with htACE, LdDCP and EcDCP and analysis of molecular electrostatic potentials (MEP) suggested that the active site domain of three enzymes has several minor but potentially important structural differences. These differences could be exploited for designing selective inhibitor of LdDCP thereby antileishmanial compounds either by denovo drug design or virtual screening of small molecule databases.

Upcrowding energy co-operatives - Evaluating the potential of crowdfunding for business model innovation of energy co-operatives.

PubMed

Dilger, Mathias Georg; Jovanović, Tanja; Voigt, Kai-Ingo

2017-08-01

Practice and theory have proven the relevance of energy co-operatives for civic participation in the energy turnaround. However, due to a still low awareness and changing regulation, there seems an unexploited potential of utilizing the legal form 'co-operative' in this context. The aim of this study is therefore to investigate the crowdfunding implementation in the business model of energy co-operatives in order to cope with the mentioned challenges. Based on a theoretical framework, we derive a Business Model Innovation (BMI) through crowdfunding including synergies and differences. A qualitative study design, particularly a multiple-case study of energy co-operatives, was chosen to prove the BMI and to reveal barriers. The results show that although most co-operatives are not familiar with crowdfunding, there is strong potential in opening up predominantly local structures to a broader group of members. Building on this, equity-based crowdfunding is revealed to be suitable for energy co-operatives as BMI and to accompany other challenges in the same way. Copyright © 2017 Elsevier Ltd. All rights reserved.

Gurtin-Murdoch surface elasticity theory revisit: An orbital-free density functional theory perspective

NASA Astrophysics Data System (ADS)

Zhu, Yichao; Wei, Yihai; Guo, Xu

2017-12-01

In the present paper, the well-established Gurtin-Murdoch theory of surface elasticity (Gurtin and Murdoch, 1975, 1978) is revisited from an orbital-free density functional theory (OFDFT) perspective by taking the boundary layer into consideration. Our analysis indicates that firstly, the quantities introduced in the Gurtin-Murdoch theory of surface elasticity can all find their explicit expressions in the derived OFDFT-based theoretical model. Secondly, the derived expression for surface energy density captures a competition between the surface normal derivatives of the electron density and the electrostatic potential, which well rationalises the onset of signed elastic constants that are observed both experimentally and computationally. Thirdly, the established model naturally yields an inversely linear relationship between the materials surface stiffness and its size, which conforms to relevant findings in literature. Since the proposed OFDFT-based model is established under arbitrarily imposed boundary condition of electron density, electrostatic potential and external load, it also has the potential of being used to investigate the electro-mechanical behaviour of nanoscale materials manifesting surface effect.

A spatial model for a stream networks of Citarik River with the environmental variables: potential of hydrogen (PH) and temperature

NASA Astrophysics Data System (ADS)

Bachrudin, A.; Mohamed, N. B.; Supian, S.; Sukono; Hidayat, Y.

2018-03-01

Application of existing geostatistical theory of stream networks provides a number of interesting and challenging problems. Most of statistical tools in the traditional geostatistics have been based on a Euclidean distance such as autocovariance functions, but for stream data is not permissible since it deals with a stream distance. To overcome this autocovariance developed a model based on the distance the flow with using convolution kernel approach (moving average construction). Spatial model for a stream networks is widely used to monitor environmental on a river networks. In a case study of a river in province of West Java, the objective of this paper is to analyze a capability of a predictive on two environmental variables, potential of hydrogen (PH) and temperature using ordinary kriging. Several the empirical results show: (1) The best fit of autocovariance functions for temperature and potential hydrogen (ph) of Citarik River is linear which also yields the smallest root mean squared prediction error (RMSPE), (2) the spatial correlation values between the locations on upstream and on downstream of Citarik river exhibit decreasingly

Potential for Metabolomics-Based Markers of Exposure:Encouraging Evidence from Studies using Model Organisms

EPA Science Inventory

Genomic techniques (transcriptomics, proteomics, and metabolomics) have the potential to significantly improve the way chemical risk is managed in the 21st century. Indeed, a significant amount of research has been devoted to the use of these techniques to screen chemicals for h...

Marine and Hydrokinetic Research | Water Power | NREL

Science.gov Websites

. Resource Characterization and Maps NREL develops measurement systems, simulation tools, and web-based models and tools to evaluate the economic potential of power-generating devices for all technology Acceleration NREL analysts study the potential impacts that developing a robust MHK market could have on

20170921 - An evaluation of selected (Q)SARs/expert systems for the Prediction of Skin Sensitization Potential (ASCCT)

EPA Science Inventory

Predictive testing to characterize substances for their skin sensitization potential has historically been based on animal models such as the Local Lymph Node Assay (LLNA) and the Guinea Pig Maximization Test (GPMT). In recent years, EU regulations have provided a strong incentiv...

The potential of 2D Kalman filtering for soil moisture data assimilation

USDA-ARS?s Scientific Manuscript database

We examine the potential for parameterizing a two-dimensional (2D) land data assimilation system using spatial error auto-correlation statistics gleaned from a triple collocation analysis and the triplet of: (1) active microwave-, (2) passive microwave- and (3) land surface model-based surface soil ...

Use of High-Throughput Cell-Based and Model Organism Assays for Understanding the Potential Toxicity of Engineered Nanomaterials

EPA Science Inventory

The rapidly expanding field of nanotechnology is introducing a large number and diversity of engineered nanomaterials into research and commerce with concordant uncertainty regarding the potential adverse health and ecological effects. With costs and time of traditional animal to...

[Model-based biofuels system analysis: a review].

PubMed

Chang, Shiyan; Zhang, Xiliang; Zhao, Lili; Ou, Xunmin

2011-03-01

Model-based system analysis is an important tool for evaluating the potential and impacts of biofuels, and for drafting biofuels technology roadmaps and targets. The broad reach of the biofuels supply chain requires that biofuels system analyses span a range of disciplines, including agriculture/forestry, energy, economics, and the environment. Here we reviewed various models developed for or applied to modeling biofuels, and presented a critical analysis of Agriculture/Forestry System Models, Energy System Models, Integrated Assessment Models, Micro-level Cost, Energy and Emission Calculation Models, and Specific Macro-level Biofuel Models. We focused on the models' strengths, weaknesses, and applicability, facilitating the selection of a suitable type of model for specific issues. Such an analysis was a prerequisite for future biofuels system modeling, and represented a valuable resource for researchers and policy makers.