WorldWideScience

Sample records for mechanistic model incorporating

  1. INCORPORATION OF MECHANISTIC INFORMATION IN THE ARSENIC PBPK MODEL DEVELOPMENT PROCESS

    Science.gov (United States)

    INCORPORATING MECHANISTIC INSIGHTS IN A PBPK MODEL FOR ARSENICElaina M. Kenyon, Michael F. Hughes, Marina V. Evans, David J. Thomas, U.S. EPA; Miroslav Styblo, University of North Carolina; Michael Easterling, Analytical Sciences, Inc.A physiologically based phar...

  2. Mechanistic species distribution modelling as a link between physiology and conservation.

    Science.gov (United States)

    Evans, Tyler G; Diamond, Sarah E; Kelly, Morgan W

    2015-01-01

    Climate change conservation planning relies heavily on correlative species distribution models that estimate future areas of occupancy based on environmental conditions encountered in present-day ranges. The approach benefits from rapid assessment of vulnerability over a large number of organisms, but can have poor predictive power when transposed to novel environments and reveals little in the way of causal mechanisms that define changes in species distribution or abundance. Having conservation planning rely largely on this single approach also increases the risk of policy failure. Mechanistic models that are parameterized with physiological information are expected to be more robust when extrapolating distributions to future environmental conditions and can identify physiological processes that set range boundaries. Implementation of mechanistic species distribution models requires knowledge of how environmental change influences physiological performance, and because this information is currently restricted to a comparatively small number of well-studied organisms, use of mechanistic modelling in the context of climate change conservation is limited. In this review, we propose that the need to develop mechanistic models that incorporate physiological data presents an opportunity for physiologists to contribute more directly to climate change conservation and advance the field of conservation physiology. We begin by describing the prevalence of species distribution modelling in climate change conservation, highlighting the benefits and drawbacks of both mechanistic and correlative approaches. Next, we emphasize the need to expand mechanistic models and discuss potential metrics of physiological performance suitable for integration into mechanistic models. We conclude by summarizing other factors, such as the need to consider demography, limiting broader application of mechanistic models in climate change conservation. Ideally, modellers, physiologists and

  3. Incorporation of lysosomal sequestration in the mechanistic model for prediction of tissue distribution of basic drugs.

    Science.gov (United States)

    Assmus, Frauke; Houston, J Brian; Galetin, Aleksandra

    2017-11-15

    The prediction of tissue-to-plasma water partition coefficients (Kpu) from in vitro and in silico data using the tissue-composition based model (Rodgers & Rowland, J Pharm Sci. 2005, 94(6):1237-48.) is well established. However, distribution of basic drugs, in particular into lysosome-rich lung tissue, tends to be under-predicted by this approach. The aim of this study was to develop an extended mechanistic model for the prediction of Kpu which accounts for lysosomal sequestration and the contribution of different cell types in the tissue of interest. The extended model is based on compound-specific physicochemical properties and tissue composition data to describe drug ionization, distribution into tissue water and drug binding to neutral lipids, neutral phospholipids and acidic phospholipids in tissues, including lysosomes. Physiological data on the types of cells contributing to lung, kidney and liver, their lysosomal content and lysosomal pH were collated from the literature. The predictive power of the extended mechanistic model was evaluated using a dataset of 28 basic drugs (pK a ≥7.8, 17 β-blockers, 11 structurally diverse drugs) for which experimentally determined Kpu data in rat tissue have been reported. Accounting for the lysosomal sequestration in the extended mechanistic model improved the accuracy of Kpu predictions in lung compared to the original Rodgers model (56% drugs within 2-fold or 88% within 3-fold of observed values). Reduction in the extent of Kpu under-prediction was also evident in liver and kidney. However, consideration of lysosomal sequestration increased the occurrence of over-predictions, yielding overall comparable model performances for kidney and liver, with 68% and 54% of Kpu values within 2-fold error, respectively. High lysosomal concentration ratios relative to cytosol (>1000-fold) were predicted for the drugs investigated; the extent differed depending on the lysosomal pH and concentration of acidic phospholipids among

  4. Assessing uncertainty in mechanistic models

    Science.gov (United States)

    Edwin J. Green; David W. MacFarlane; Harry T. Valentine

    2000-01-01

    Concern over potential global change has led to increased interest in the use of mechanistic models for predicting forest growth. The rationale for this interest is that empirical models may be of limited usefulness if environmental conditions change. Intuitively, we expect that mechanistic models, grounded as far as possible in an understanding of the biology of tree...

  5. An Emphasis on Perception: Teaching Image Formation Using a Mechanistic Model of Vision.

    Science.gov (United States)

    Allen, Sue; And Others

    An effective way to teach the concept of image is to give students a model of human vision which incorporates a simple mechanism of depth perception. In this study two almost identical versions of a curriculum in geometrical optics were created. One used a mechanistic, interpretive eye model, and in the other the eye was modeled as a passive,…

  6. Mechanistic variables can enhance predictive models of endotherm distributions: The American pika under current, past, and future climates

    Science.gov (United States)

    Mathewson, Paul; Moyer-Horner, Lucas; Beever, Erik; Briscoe, Natalie; Kearney, Michael T.; Yahn, Jeremiah; Porter, Warren P.

    2017-01-01

    How climate constrains species’ distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat-balance model, to convert macroclimate data to pika-specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8–19% less habitat loss in response to annual temperature increases of ~3–5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect

  7. Mechanistic variables can enhance predictive models of endotherm distributions: the American pika under current, past, and future climates.

    Science.gov (United States)

    Mathewson, Paul D; Moyer-Horner, Lucas; Beever, Erik A; Briscoe, Natalie J; Kearney, Michael; Yahn, Jeremiah M; Porter, Warren P

    2017-03-01

    How climate constrains species' distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat-balance model, to convert macroclimate data to pika-specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8-19% less habitat loss in response to annual temperature increases of ~3-5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect

  8. Mechanistic Oral Absorption Modeling and Simulation for Formulation Development and Bioequivalence Evaluation: Report of an FDA Public Workshop.

    Science.gov (United States)

    Zhang, X; Duan, J; Kesisoglou, F; Novakovic, J; Amidon, G L; Jamei, M; Lukacova, V; Eissing, T; Tsakalozou, E; Zhao, L; Lionberger, R

    2017-08-01

    On May 19, 2016, the US Food and Drug Administration (FDA) hosted a public workshop, entitled "Mechanistic Oral Absorption Modeling and Simulation for Formulation Development and Bioequivalence Evaluation." The topic of mechanistic oral absorption modeling, which is one of the major applications of physiologically based pharmacokinetic (PBPK) modeling and simulation, focuses on predicting oral absorption by mechanistically integrating gastrointestinal transit, dissolution, and permeation processes, incorporating systems, active pharmaceutical ingredient (API), and the drug product information, into a systemic mathematical whole-body framework. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

  9. Testing mechanistic models of growth in insects.

    Science.gov (United States)

    Maino, James L; Kearney, Michael R

    2015-11-22

    Insects are typified by their small size, large numbers, impressive reproductive output and rapid growth. However, insect growth is not simply rapid; rather, insects follow a qualitatively distinct trajectory to many other animals. Here we present a mechanistic growth model for insects and show that increasing specific assimilation during the growth phase can explain the near-exponential growth trajectory of insects. The presented model is tested against growth data on 50 insects, and compared against other mechanistic growth models. Unlike the other mechanistic models, our growth model predicts energy reserves per biomass to increase with age, which implies a higher production efficiency and energy density of biomass in later instars. These predictions are tested against data compiled from the literature whereby it is confirmed that insects increase their production efficiency (by 24 percentage points) and energy density (by 4 J mg(-1)) between hatching and the attainment of full size. The model suggests that insects achieve greater production efficiencies and enhanced growth rates by increasing specific assimilation and increasing energy reserves per biomass, which are less costly to maintain than structural biomass. Our findings illustrate how the explanatory and predictive power of mechanistic growth models comes from their grounding in underlying biological processes. © 2015 The Author(s).

  10. Improving Predictive Modeling in Pediatric Drug Development: Pharmacokinetics, Pharmacodynamics, and Mechanistic Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Slikker, William; Young, John F.; Corley, Rick A.; Dorman, David C.; Conolly, Rory B.; Knudsen, Thomas; Erstad, Brian L.; Luecke, Richard H.; Faustman, Elaine M.; Timchalk, Chuck; Mattison, Donald R.

    2005-07-26

    A workshop was conducted on November 18?19, 2004, to address the issue of improving predictive models for drug delivery to developing humans. Although considerable progress has been made for adult humans, large gaps remain for predicting pharmacokinetic/pharmacodynamic (PK/PD) outcome in children because most adult models have not been tested during development. The goals of the meeting included a description of when, during development, infants/children become adultlike in handling drugs. The issue of incorporating the most recent advances into the predictive models was also addressed: both the use of imaging approaches and genomic information were considered. Disease state, as exemplified by obesity, was addressed as a modifier of drug pharmacokinetics and pharmacodynamics during development. Issues addressed in this workshop should be considered in the development of new predictive and mechanistic models of drug kinetics and dynamics in the developing human.

  11. Behavioural Procedural Models – a multipurpose mechanistic account

    Directory of Open Access Journals (Sweden)

    Leonardo Ivarola

    2012-05-01

    Full Text Available In this paper we outline an epistemological defence of what wecall Behavioural Procedural Models (BPMs, which represent the processes of individual decisions that lead to relevant economic patterns as psychologically (rather than rationally driven. Their general structure, and the way in which they may be incorporated to a multipurpose view of models, where the representational and interventionist goals are combined, is shown. It is argued that BPMs may provide “mechanistic-based explanations” in the sense defended by Hedström and Ylikoski (2010, which involve invariant regularities in Woodward’s sense. Such mechanisms provide a causal sort of explanation of anomalous economic patterns, which allow for extra marketintervention and manipulability in order to correct and improve some key individual decisions. This capability sets the basis for the so called libertarian paternalism (Sunstein and Thaler 2003.

  12. Modeling Bird Migration under Climate Change: A Mechanistic Approach

    Science.gov (United States)

    Smith, James A.

    2009-01-01

    How will migrating birds respond to changes in the environment under climate change? What are the implications for migratory success under the various accelerated climate change scenarios as forecast by the Intergovernmental Panel on Climate Change? How will reductions or increased variability in the number or quality of wetland stop-over sites affect migratory bird species? The answers to these questions have important ramifications for conservation biology and wildlife management. Here, we describe the use of continental scale simulation modeling to explore how spatio-temporal changes along migratory flyways affect en-route migration success. We use an individually based, biophysical, mechanistic, bird migration model to simulate the movement of shorebirds in North America as a tool to study how such factors as drought and wetland loss may impact migratory success and modify migration patterns. Our model is driven by remote sensing and climate data and incorporates important landscape variables. The energy budget components of the model include resting, foraging, and flight, but presently predation is ignored. Results/Conclusions We illustrate our model by studying the spring migration of sandpipers through the Great Plains to their Arctic breeding grounds. Why many species of shorebirds have shown significant declines remains a puzzle. Shorebirds are sensitive to stop-over quality and spacing because of their need for frequent refueling stops and their opportunistic feeding patterns. We predict bird "hydrographs that is, stop-over frequency with latitude, that are in agreement with the literature. Mean stop-over durations predicted from our model for nominal cases also are consistent with the limited, but available data. For the shorebird species simulated, our model predicts that shorebirds exhibit significant plasticity and are able to shift their migration patterns in response to changing drought conditions. However, the question remains as to whether this

  13. Mechanistic modeling of reactive soil nitrogen emissions across agricultural management practices

    Science.gov (United States)

    Rasool, Q. Z.; Miller, D. J.; Bash, J. O.; Venterea, R. T.; Cooter, E. J.; Hastings, M. G.; Cohan, D. S.

    2017-12-01

    The global reactive nitrogen (N) budget has increased by a factor of 2-3 from pre-industrial levels. This increase is especially pronounced in highly N fertilized agricultural regions in summer. The reactive N emissions from soil to atmosphere can be in reduced (NH3) or oxidized (NO, HONO, N2O) forms, depending on complex biogeochemical transformations of soil N reservoirs. Air quality models like CMAQ typically neglect soil emissions of HONO and N2O. Previously, soil NO emissions estimated by models like CMAQ remained parametric and inconsistent with soil NH3 emissions. Thus, there is a need to more mechanistically and consistently represent the soil N processes that lead to reactive N emissions to the atmosphere. Our updated approach estimates soil NO, HONO and N2O emissions by incorporating detailed agricultural fertilizer inputs from EPIC, and CMAQ-modeled N deposition, into the soil N pool. EPIC addresses the nitrification, denitrification and volatilization rates along with soil N pools for agricultural soils. Suitable updates to account for factors like nitrite (NO2-) accumulation not addressed in EPIC, will also be made. The NO and N2O emissions from nitrification and denitrification are computed mechanistically using the N sub-model of DAYCENT. These mechanistic definitions use soil water content, temperature, NH4+ and NO3- concentrations, gas diffusivity and labile C availability as dependent parameters at various soil layers. Soil HONO emissions found to be most probable under high NO2- availability will be based on observed ratios of HONO to NO emissions under different soil moistures, pH and soil types. The updated scheme will utilize field-specific soil properties and N inputs across differing manure management practices such as tillage. Comparison of the modeled soil NO emission rates from the new mechanistic and existing schemes against field measurements will be discussed. Our updated framework will help to predict the diurnal and daily variability

  14. Mechanistic modelling of genetic and epigenetic events in radiation carcinogenesis

    International Nuclear Information System (INIS)

    Andreev, S. G.; Eidelman, Y. A.; Salnikov, I. V.; Khvostunov, I. K.

    2006-01-01

    Methodological problems arise on the way of radiation carcinogenesis modelling with the incorporation of radiobiological and cancer biology mechanistic data. The results of biophysical modelling of different endpoints [DNA DSB induction, repair, chromosome aberrations (CA) and cell proliferation] are presented and applied to the analysis of RBE-LET relationships for radiation-induced neoplastic transformation (RINT) of C3H/10T1/2 cells in culture. Predicted values for some endpoints correlate well with the data. It is concluded that slowly repaired DSB clusters, as well as some kind of CA, may be initiating events for RINT. As an alternative interpretation, it is possible that DNA damage can induce RINT indirectly via epigenetic process. A hypothetical epigenetic pathway for RINT is discussed. (authors)

  15. Calibrating mechanistic-empirical pavement performance models with an expert matrix

    Energy Technology Data Exchange (ETDEWEB)

    Tighe, S.; AlAssar, R.; Haas, R. [Waterloo Univ., ON (Canada). Dept. of Civil Engineering; Zhiwei, H. [Stantec Consulting Ltd., Cambridge, ON (Canada)

    2001-07-01

    Proper management of pavement infrastructure requires pavement performance modelling. For the past 20 years, the Ontario Ministry of Transportation has used the Ontario Pavement Analysis of Costs (OPAC) system for pavement design. Pavement needs, however, have changed substantially during that time. To address this need, a new research contract is underway to enhance the model and verify the predictions, particularly at extreme points such as low and high traffic volume pavement design. This initiative included a complete evaluation of the existing OPAC pavement design method, the construction of a new set of pavement performance prediction models, and the development of the flexible pavement design procedure that incorporates reliability analysis. The design was also expanded to include rigid pavement designs and modification of the existing life cycle cost analysis procedure which includes both the agency cost and road user cost. Performance prediction and life-cycle costs were developed based on several factors, including material properties, traffic loads and climate. Construction and maintenance schedules were also considered. The methodology for the calibration and validation of a mechanistic-empirical flexible pavement performance model was described. Mechanistic-empirical design methods combine theory based design such as calculated stresses, strains or deflections with empirical methods, where a measured response is associated with thickness and pavement performance. Elastic layer analysis was used to determine pavement response to determine the most effective design using cumulative Equivalent Single Axle Loads (ESALs), below grade type and layer thickness.The new mechanistic-empirical model separates the environment and traffic effects on performance. This makes it possible to quantify regional differences between Southern and Northern Ontario. In addition, roughness can be calculated in terms of the International Roughness Index or Riding comfort Index

  16. Appropriateness of mechanistic and non-mechanistic models for the application of ultrafiltration to mixed waste

    International Nuclear Information System (INIS)

    Foust, Henry; Ghosehajra, Malay

    2007-01-01

    This study asks two questions: (1) How appropriate is the use of a basic filtration equation to the application of ultrafiltration of mixed waste, and (2) How appropriate are non-parametric models for permeate rates (volumes)? To answer these questions, mechanistic and non-mechanistic approaches are developed for permeate rates and volumes associated with an ultrafiltration/mixed waste system in dia-filtration mode. The mechanistic approach is based on a filtration equation which states that t/V vs. V is a linear relationship. The coefficients associated with this linear regression are composed of physical/chemical parameters of the system and based the mass balance equation associated with the membrane and associated developing cake layer. For several sets of data, a high correlation is shown that supports the assertion that t/V vs. V is a linear relationship. It is also shown that non-mechanistic approaches, i.e., the use of regression models to are not appropriate. One models considered is Q(p) = a*ln(Cb)+b. Regression models are inappropriate because the scale-up from a bench scale (pilot scale) study to full-scale for permeate rates (volumes) is not simply the ratio of the two membrane surface areas. (authors)

  17. Mechanistic modelling of a cathode-supported tubular solid oxide fuel cell

    Science.gov (United States)

    Suwanwarangkul, R.; Croiset, E.; Pritzker, M. D.; Fowler, M. W.; Douglas, P. L.; Entchev, E.

    A two-dimensional mechanistic model of a tubular solid oxide fuel cell (SOFC) considering momentum, energy, mass and charge transport is developed. The model geometry of a single cell comprises an air-preheating tube, air channel, fuel channel, anode, cathode and electrolyte layers. The heat radiation between cell and air-preheating tube is also incorporated into the model. This allows the model to predict heat transfer between the cell and air-preheating tube accurately. The model is validated and shows good agreement with literature data. It is anticipated that this model can be used to help develop efficient fuel cell designs and set operating variables under practical conditions. The transport phenomena inside the cell, including gas flow behaviour, temperature, overpotential, current density and species concentration, are analysed and discussed in detail. Fuel and air velocities are found to vary along flow passages depending on the local temperature and species concentrations. This model demonstrates the importance of incorporating heat radiation into a tubular SOFC model. Furthermore, the model shows that the overall cell performance is limited by O 2 diffusion through the thick porous cathode and points to the development of new cathode materials and designs being important avenues to enhance cell performance.

  18. Application of mechanistic models to fermentation and biocatalysis for next-generation processes

    DEFF Research Database (Denmark)

    Gernaey, Krist; Eliasson Lantz, Anna; Tufvesson, Pär

    2010-01-01

    of variables required for measurement, control and process design. In the near future, mechanistic models with a higher degree of detail will play key roles in the development of efficient next-generation fermentation and biocatalytic processes. Moreover, mechanistic models will be used increasingly......Mechanistic models are based on deterministic principles, and recently, interest in them has grown substantially. Herein we present an overview of mechanistic models and their applications in biotechnology, including future perspectives. Model utility is highlighted with respect to selection...

  19. Bridging Mechanistic and Phenomenological Models of Complex Biological Systems.

    Science.gov (United States)

    Transtrum, Mark K; Qiu, Peng

    2016-05-01

    The inherent complexity of biological systems gives rise to complicated mechanistic models with a large number of parameters. On the other hand, the collective behavior of these systems can often be characterized by a relatively small number of phenomenological parameters. We use the Manifold Boundary Approximation Method (MBAM) as a tool for deriving simple phenomenological models from complicated mechanistic models. The resulting models are not black boxes, but remain expressed in terms of the microscopic parameters. In this way, we explicitly connect the macroscopic and microscopic descriptions, characterize the equivalence class of distinct systems exhibiting the same range of collective behavior, and identify the combinations of components that function as tunable control knobs for the behavior. We demonstrate the procedure for adaptation behavior exhibited by the EGFR pathway. From a 48 parameter mechanistic model, the system can be effectively described by a single adaptation parameter τ characterizing the ratio of time scales for the initial response and recovery time of the system which can in turn be expressed as a combination of microscopic reaction rates, Michaelis-Menten constants, and biochemical concentrations. The situation is not unlike modeling in physics in which microscopically complex processes can often be renormalized into simple phenomenological models with only a few effective parameters. The proposed method additionally provides a mechanistic explanation for non-universal features of the behavior.

  20. Evaluation of mechanistic DNB models using HCLWR CHF data

    International Nuclear Information System (INIS)

    Iwamura, Takamichi; Watanabe, Hironori; Okubo, Tsutomu; Araya, Fumimasa; Murao, Yoshio.

    1992-03-01

    An onset of departure from nucleate boiling (DNB) in light water reactor (LWR) has been generally predicted with empirical correlations. Since these correlations have less physical bases and contain adjustable empirical constants determined by best fitting of test data, applicable geometries and flow conditions are limited within the original experiment ranges. In order to obtain more universal prediction method, several mechanistic DNB models based on physical approaches have been proposed in recent years. However, the predictive capabilities of mechanistic DNB models have not been verified successfully especially for advanced LWR design purposes. In this report, typical DNB mechanistic models are reviewed and compared with critical heat flux (CHF) data for high conversion light water reactor (HCLWR). The experiments were performed using triangular 7-rods array with non-uniform axial heat flux distribution. Test pressure was 16 MPa, mass velocities ranged from 800 t0 3100 kg/s·m 2 and exit qualities from -0.07 to 0.19. The evaluated models are: 1) Wisman-Pei, 2) Chang-Lee, 3) Lee-Mudawwar, 4) Lin-Lee-Pei, and 5) Katto. The first two models are based on near-wall bubble crowding model and the other three models on sublayer dryout model. The comparison with experimental data indicated that the Weisman-Pei model agreed relatively well with the CHF data. Effects of empirical constants in each model on CHF calculation were clarified by sensitivity studies. It was also found that the magnitudes of physical quantities obtained in the course of calculation were significantly different for each model. Therefore, microscopic observation of the onset of DNB on heated surface is essential to clarify the DNB mechanism and establish a general DNB mechanistic model based on physical phenomenon. (author)

  1. Specialists without spirit: limitations of the mechanistic biomedical model.

    Science.gov (United States)

    Hewa, S; Hetherington, R W

    1995-06-01

    This paper examines the origin and the development of the mechanistic model of the human body and health in terms of Max Weber's theory of rationalization. It is argued that the development of Western scientific medicine is a part of the broad process of rationalization that began in sixteenth century Europe as a result of the Reformation. The development of the mechanistic view of the human body in Western medicine is consistent with the ideas of calculability, predictability, and control-the major tenets of the process of rationalization as described by Weber. In recent years, however, the limitations of the mechanistic model have been the topic of many discussions. George Engel, a leading advocate of general systems theory, is one of the leading proponents of a new medical model which includes the general quality of life, clean environment, and psychological, or spiritual stability of life. The paper concludes with consideration of the potential of Engel's proposed new model in the context of the current state of rationalization in modern industrialized society.

  2. Mechanistic Fermentation Models for Process Design, Monitoring, and Control

    DEFF Research Database (Denmark)

    Mears, Lisa; Stocks, Stuart M.; Albæk, Mads Orla

    2017-01-01

    Mechanistic models require a significant investment of time and resources, but their application to multiple stages of fermentation process development and operation can make this investment highly valuable. This Opinion article discusses how an established fermentation model may be adapted...... for application to different stages of fermentation process development: planning, process design, monitoring, and control. Although a longer development time is required for such modeling methods in comparison to purely data-based model techniques, the wide range of applications makes them a highly valuable tool...... for fermentation research and development. In addition, in a research environment, where collaboration is important, developing mechanistic models provides a platform for knowledge sharing and consolidation of existing process understanding....

  3. Mechanistic model for microbial growth on hydrocarbons

    Energy Technology Data Exchange (ETDEWEB)

    Mallee, F M; Blanch, H W

    1977-12-01

    Based on available information describing the transport and consumption of insoluble alkanes, a mechanistic model is proposed for microbial growth on hydrocarbons. The model describes the atypical growth kinetics observed, and has implications in the design of large scale equipment for single cell protein (SCP) manufacture from hydrocarbons. The model presents a framework for comparison of the previously published experimental kinetic data.

  4. Description and evaluation of a mechanistically based conceptual model for spall

    Energy Technology Data Exchange (ETDEWEB)

    Hansen, F.D.; Knowles, M.K.; Thompson, T.W. [and others

    1997-08-01

    A mechanistically based model for a possible spall event at the WIPP site is developed and evaluated in this report. Release of waste material to the surface during an inadvertent borehole intrusion is possible if future states of the repository include high gas pressure and waste material consisting of fine particulates having low mechanical strength. The conceptual model incorporates the physics of wellbore hydraulics coupled to transient gas flow to the intrusion borehole, and mechanical response of the waste. Degraded waste properties using of the model. The evaluations include both numerical and analytical implementations of the conceptual model. A tensile failure criterion is assumed appropriate for calculation of volumes of waste experiencing fragmentation. Calculations show that for repository gas pressures less than 12 MPa, no tensile failure occurs. Minimal volumes of material experience failure below gas pressure of 14 MPa. Repository conditions dictate that the probability of gas pressures exceeding 14 MPa is approximately 1%. For these conditions, a maximum failed volume of 0.25 m{sup 3} is calculated.

  5. Description and evaluation of a mechanistically based conceptual model for spall

    International Nuclear Information System (INIS)

    Hansen, F.D.; Knowles, M.K.; Thompson, T.W.

    1997-08-01

    A mechanistically based model for a possible spall event at the WIPP site is developed and evaluated in this report. Release of waste material to the surface during an inadvertent borehole intrusion is possible if future states of the repository include high gas pressure and waste material consisting of fine particulates having low mechanical strength. The conceptual model incorporates the physics of wellbore hydraulics coupled to transient gas flow to the intrusion borehole, and mechanical response of the waste. Degraded waste properties using of the model. The evaluations include both numerical and analytical implementations of the conceptual model. A tensile failure criterion is assumed appropriate for calculation of volumes of waste experiencing fragmentation. Calculations show that for repository gas pressures less than 12 MPa, no tensile failure occurs. Minimal volumes of material experience failure below gas pressure of 14 MPa. Repository conditions dictate that the probability of gas pressures exceeding 14 MPa is approximately 1%. For these conditions, a maximum failed volume of 0.25 m 3 is calculated

  6. Conceptual models for waste tank mechanistic analysis

    International Nuclear Information System (INIS)

    Allemann, R.T.; Antoniak, Z.I.; Eyler, L.L.; Liljegren, L.M.; Roberts, J.S.

    1992-02-01

    Pacific Northwest Laboratory (PNL) is conducting a study for Westinghouse Hanford Company (Westinghouse Hanford), a contractor for the US Department of Energy (DOE). The purpose of the work is to study possible mechanisms and fluid dynamics contributing to the periodic release of gases from double-shell waste storage tanks at the Hanford Site in Richland, Washington. This interim report emphasizing the modeling work follows two other interim reports, Mechanistic Analysis of Double-Shell Tank Gas Release Progress Report -- November 1990 and Collection and Analysis of Existing Data for Waste Tank Mechanistic Analysis Progress Report -- December 1990, that emphasized data correlation and mechanisms. The approach in this study has been to assemble and compile data that are pertinent to the mechanisms, analyze the data, evaluate physical properties and parameters, evaluate hypothetical mechanisms, and develop mathematical models of mechanisms

  7. Advanced reach tool (ART) : Development of the mechanistic model

    NARCIS (Netherlands)

    Fransman, W.; Tongeren, M. van; Cherrie, J.W.; Tischer, M.; Schneider, T.; Schinkel, J.; Kromhout, H.; Warren, N.; Goede, H.; Tielemans, E.

    2011-01-01

    This paper describes the development of the mechanistic model within a collaborative project, referred to as the Advanced REACH Tool (ART) project, to develop a tool to model inhalation exposure for workers sharing similar operational conditions across different industries and locations in Europe.

  8. Descriptive and mechanistic models of crop–weed competition

    NARCIS (Netherlands)

    Bastiaans, L.; Storkey, J.

    2017-01-01

    Crop-weed competitive relations are an important element of agroecosystems. Quantifying and understanding them helps to design appropriate weed management at operational, tactical and strategic level. This chapter presents and discusses simple descriptive and more mechanistic models for crop-weed

  9. Requirements on mechanistic NPP models used in CSS for diagnostics and predictions

    International Nuclear Information System (INIS)

    Juslin, K.

    1996-01-01

    Mechanistic models have for several years with good experience been used for operators' support in electric power dispatching centres. Some models of limited scope have already been in use at nuclear power plants. It is considered that also advanced mechanistic models in combination with present computer technology with preference could be used in Computerized Support Systems (CSS) for the assistance of Nuclear Power Plant (NPP) operators. Requirements with respect to accuracy, validity range, speed flexibility and level of detail on the models used for such purposes are discussed. Quality Assurance, Verification and Validation efforts are considered. A long term commitment in the field of mechanistic modelling and real time simulation is considered as the key to successful implementations. The Advanced PROcess Simulation (APROS) code system and simulation environment developed at the Technical Research Centre of Finland (VTT) is intended also for CSS applications in NPP control rooms. (author). 4 refs

  10. Mechanistic Models for Process Development and Optimization of Fed-batch Fermentation Systems

    DEFF Research Database (Denmark)

    Mears, Lisa; Stocks, Stuart M.; Albæk, Mads O.

    2016-01-01

    This work discusses the application of mechanistic models to pilot scale filamentous fungal fermentation systems operated at Novozymes A/S. For on-line applications, a state estimator model is developed based on a stoichiometric balance in order to predict the biomass and product concentration....... This is based on on-line gas measurements and ammonia addition flow rate measurements. Additionally, a mechanistic model is applied offline as a tool for batch planning, based on definition of the process back pressure, aeration rate and stirrer speed. This allows the batch starting fill to be planned, taking...... into account the oxygen transfer conditions, as well as the evaporation rates of the system. Mechanistic models are valuable tools which are applicable for both process development and optimization. The state estimator described will be a valuable tool for future work as part of control strategy development...

  11. Numerical simulation in steam injection process by a mechanistic approach

    Energy Technology Data Exchange (ETDEWEB)

    De Souza, J.C.Jr.; Campos, W.; Lopes, D.; Moura, L.S.S. [Petrobras, Rio de Janeiro (Brazil)

    2008-10-15

    Steam injection is a common thermal recovery method used in very viscous oil reservoirs. The method involves the injection of heat to reduce viscosity and mobilize oil. A steam generation and injection system consists primarily of a steam source, distribution lines, injection wells and a discarding tank. In order to optimize injection and improve the oil recovery factor, one must determine the parameters of steam flow such as pressure, temperature and steam quality. This study focused on developing a unified mathematical model by means of a mechanistic approach for two-phase steam flow in pipelines and wells. The hydrodynamic and heat transfer mechanistic model was implemented in a computer simulator to model the parameters of steam injection while trying to avoid the use of empirical correlations. A marching algorithm was used to determine the distribution of pressure and temperature along the pipelines and wellbores. The mathematical model for steam flow in injection systems, developed by a mechanistic approach (VapMec) performed well when the simulated values of pressures and temperatures were compared with the values measured during field tests. The newly developed VapMec model was incorporated in the LinVap-3 simulator that constitutes an engineering supporting tool for steam injection wells operated by Petrobras. 23 refs., 7 tabs., 6 figs.

  12. A mechanistic modeling and data assimilation framework for Mojave Desert ecohydrology

    Science.gov (United States)

    Ng, Gene-Hua Crystal; Bedford, David R.; Miller, David M.

    2014-06-01

    This study demonstrates and addresses challenges in coupled ecohydrological modeling in deserts, which arise due to unique plant adaptations, marginal growing conditions, slow net primary production rates, and highly variable rainfall. We consider model uncertainty from both structural and parameter errors and present a mechanistic model for the shrub Larrea tridentata (creosote bush) under conditions found in the Mojave National Preserve in southeastern California (USA). Desert-specific plant and soil features are incorporated into the CLM-CN model by Oleson et al. (2010). We then develop a data assimilation framework using the ensemble Kalman filter (EnKF) to estimate model parameters based on soil moisture and leaf-area index observations. A new implementation procedure, the "multisite loop EnKF," tackles parameter estimation difficulties found to affect desert ecohydrological applications. Specifically, the procedure iterates through data from various observation sites to alleviate adverse filter impacts from non-Gaussianity in small desert vegetation state values. It also readjusts inconsistent parameters and states through a model spin-up step that accounts for longer dynamical time scales due to infrequent rainfall in deserts. Observation error variance inflation may also be needed to help prevent divergence of estimates from true values. Synthetic test results highlight the importance of adequate observations for reducing model uncertainty, which can be achieved through data quality or quantity.

  13. A mechanistic modeling and data assimilation framework for Mojave Desert ecohydrology

    Science.gov (United States)

    Ng, Gene-Hua Crystal.; Bedford, David; Miller, David

    2014-01-01

    This study demonstrates and addresses challenges in coupled ecohydrological modeling in deserts, which arise due to unique plant adaptations, marginal growing conditions, slow net primary production rates, and highly variable rainfall. We consider model uncertainty from both structural and parameter errors and present a mechanistic model for the shrub Larrea tridentata (creosote bush) under conditions found in the Mojave National Preserve in southeastern California (USA). Desert-specific plant and soil features are incorporated into the CLM-CN model by Oleson et al. (2010). We then develop a data assimilation framework using the ensemble Kalman filter (EnKF) to estimate model parameters based on soil moisture and leaf-area index observations. A new implementation procedure, the “multisite loop EnKF,” tackles parameter estimation difficulties found to affect desert ecohydrological applications. Specifically, the procedure iterates through data from various observation sites to alleviate adverse filter impacts from non-Gaussianity in small desert vegetation state values. It also readjusts inconsistent parameters and states through a model spin-up step that accounts for longer dynamical time scales due to infrequent rainfall in deserts. Observation error variance inflation may also be needed to help prevent divergence of estimates from true values. Synthetic test results highlight the importance of adequate observations for reducing model uncertainty, which can be achieved through data quality or quantity.

  14. Mechanistic model for Sr and Ba release from severely damaged fuel

    International Nuclear Information System (INIS)

    Rest, J.; Cronenberg, A.W.

    1985-11-01

    Among radionuclides associated with fission product release during severe accidents, the primary ones with health consequences are the volatile species of I, Te, and Cs, and the next most important are Sr, Ba, and Ru. Considerable progress has been made in the mechanistic understanding of I, Cs, Te, and noble gas release; however, no capability presently exists for estimating the release of Sr, Ba, and Ru. This paper presents a description of the primary physical/chemical models recently incorporated into the FASTGRASS-VFP (volatile fission product) code for the estimation of Sr and Ba release. FASTGRASS-VFP release predictions are compared with two data sets: (1) data from out-of-reactor induction-heating experiments on declad low-burnup (1000 and 4000 MWd/t) pellets, and (2) data from the more recent in-reactor PBF Severe Fuel Damage Tests, in which one-meter-long, trace-irradiated (89 MWd/t) and normally irradiated (approx.35,000 MWd/t) fuel rods were tested under accident conditions. 10 refs

  15. A Physics-Inspired Mechanistic Model of Migratory Movement Patterns in Birds.

    Science.gov (United States)

    Revell, Christopher; Somveille, Marius

    2017-08-29

    In this paper, we introduce a mechanistic model of migratory movement patterns in birds, inspired by ideas and methods from physics. Previous studies have shed light on the factors influencing bird migration but have mainly relied on statistical correlative analysis of tracking data. Our novel method offers a bottom up explanation of population-level migratory movement patterns. It differs from previous mechanistic models of animal migration and enables predictions of pathways and destinations from a given starting location. We define an environmental potential landscape from environmental data and simulate bird movement within this landscape based on simple decision rules drawn from statistical mechanics. We explore the capacity of the model by qualitatively comparing simulation results to the non-breeding migration patterns of a seabird species, the Black-browed Albatross (Thalassarche melanophris). This minimal, two-parameter model was able to capture remarkably well the previously documented migration patterns of the Black-browed Albatross, with the best combination of parameter values conserved across multiple geographically separate populations. Our physics-inspired mechanistic model could be applied to other bird and highly-mobile species, improving our understanding of the relative importance of various factors driving migration and making predictions that could be useful for conservation.

  16. Fuel swelling importance in PCI mechanistic modelling

    International Nuclear Information System (INIS)

    Arimescu, V.I.

    2005-01-01

    Under certain conditions, fuel pellet swelling is the most important factor in determining the intensity of the pellet-to-cladding mechanical interaction (PCMI). This is especially true during power ramps, which lead to a temperature increase to a higher terminal plateau that is maintained for hours. The time-dependent gaseous swelling is proportional to temperature and is also enhanced by the increased gas atom migration to the grain boundary during the power ramp. On the other hand, gaseous swelling is inhibited by a compressive hydrostatic stress in the pellet. Therefore, PCMI is the net result of combining gaseous swelling and pellet thermal expansion with the opposing feedback from the cladding mechanical reaction. The coupling of the thermal and mechanical processes, mentioned above, with various feedback loops is best simulated by a mechanistic fuel code. This paper discusses a mechanistic swelling model that is coupled with a fission gas release model as well as a mechanical model of the fuel pellet. The role of fuel swelling is demonstrated for typical power ramps at different burn-ups. Also, fuel swelling plays a significant role in avoiding the thermal instability for larger gap fuel rods, by limiting the potentially exponentially increasing gap due to the positive feedback loop effect of increasing fission gas release and the associated over-pressure inside the cladding. (author)

  17. Profiling the biological activity of oxide nanomaterials with mechanistic models

    NARCIS (Netherlands)

    Burello, E.

    2013-01-01

    In this study we present three mechanistic models for profiling the potential biological and toxicological effects of oxide nanomaterials. The models attempt to describe the reactivity, protein adsorption and membrane adhesion processes of a large range of oxide materials and are based on properties

  18. A mechanistic model on methane oxidation in the rice rhizosphere

    NARCIS (Netherlands)

    Bodegom, van P.M.; Leffelaar, P.A.; Goudriaan, J.

    2001-01-01

    A mechanistic model is presented on the processes leading to methane oxidation in rice rhizosphere. The model is driven by oxygen release from a rice root into anaerobic rice soil. Oxygen is consumed by heterotrophic and methanotrophic respiration, described by double Monod kinetics, and by iron

  19. An improved mechanistic critical heat flux model for subcooled flow boiling

    Energy Technology Data Exchange (ETDEWEB)

    Kwon, Young Min [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of); Chang, Soon Heung [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)

    1998-12-31

    Based on the bubble coalescence adjacent to the heated wall as a flow structure for CHF condition, Chang and Lee developed a mechanistic critical heat flux (CHF) model for subcooled flow boiling. In this paper, improvements of Chang-Lee model are implemented with more solid theoretical bases for subcooled and low-quality flow boiling in tubes. Nedderman-Shearer`s equations for the skin friction factor and universal velocity profile models are employed. Slip effect of movable bubbly layer is implemented to improve the predictability of low mass flow. Also, mechanistic subcooled flow boiling model is used to predict the flow quality and void fraction. The performance of the present model is verified using the KAIST CHF database of water in uniformly heated tubes. It is found that the present model can give a satisfactory agreement with experimental data within less than 9% RMS error. 9 refs., 5 figs. (Author)

  20. An improved mechanistic critical heat flux model for subcooled flow boiling

    Energy Technology Data Exchange (ETDEWEB)

    Kwon, Young Min [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of); Chang, Soon Heung [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)

    1997-12-31

    Based on the bubble coalescence adjacent to the heated wall as a flow structure for CHF condition, Chang and Lee developed a mechanistic critical heat flux (CHF) model for subcooled flow boiling. In this paper, improvements of Chang-Lee model are implemented with more solid theoretical bases for subcooled and low-quality flow boiling in tubes. Nedderman-Shearer`s equations for the skin friction factor and universal velocity profile models are employed. Slip effect of movable bubbly layer is implemented to improve the predictability of low mass flow. Also, mechanistic subcooled flow boiling model is used to predict the flow quality and void fraction. The performance of the present model is verified using the KAIST CHF database of water in uniformly heated tubes. It is found that the present model can give a satisfactory agreement with experimental data within less than 9% RMS error. 9 refs., 5 figs. (Author)

  1. Recent advances in mathematical modeling of developmental abnormalities using mechanistic information.

    Science.gov (United States)

    Kavlock, R J

    1997-01-01

    During the last several years, significant changes in the risk assessment process for developmental toxicity of environmental contaminants have begun to emerge. The first of these changes is the development and beginning use of statistically based dose-response models [the benchmark dose (BMD) approach] that better utilize data derived from existing testing approaches. Accompanying this change is the greater emphasis placed on understanding and using mechanistic information to yield more accurate, reliable, and less uncertain risk assessments. The next stage in the evolution of risk assessment will be the use of biologically based dose-response (BBDR) models that begin to build into the statistically based models factors related to the underlying kinetic, biochemical, and/or physiologic processes perturbed by a toxicant. Such models are now emerging from several research laboratories. The introduction of quantitative models and the incorporation of biologic information into them has pointed to the need for even more sophisticated modifications for which we offer the term embryologically based dose-response (EBDR) models. Because these models would be based upon the understanding of normal morphogenesis, they represent a quantum leap in our thinking, but their complexity presents daunting challenges both to the developmental biologist and the developmental toxicologist. Implementation of these models will require extensive communication between developmental toxicologists, molecular embryologists, and biomathematicians. The remarkable progress in the understanding of mammalian embryonic development at the molecular level that has occurred over the last decade combined with advances in computing power and computational models should eventually enable these as yet hypothetical models to be brought into use.

  2. A Mechanistically Informed User-Friendly Model to Predict Greenhouse Gas (GHG) Fluxes and Carbon Storage from Coastal Wetlands

    Science.gov (United States)

    Abdul-Aziz, O. I.; Ishtiaq, K. S.

    2015-12-01

    We present a user-friendly modeling tool on MS Excel to predict the greenhouse gas (GHG) fluxes and estimate potential carbon sequestration from the coastal wetlands. The dominant controls of wetland GHG fluxes and their relative mechanistic linkages with various hydro-climatic, sea level, biogeochemical and ecological drivers were first determined by employing a systematic data-analytics method, including Pearson correlation matrix, principal component and factor analyses, and exploratory partial least squares regressions. The mechanistic knowledge and understanding was then utilized to develop parsimonious non-linear (power-law) models to predict wetland carbon dioxide (CO2) and methane (CH4) fluxes based on a sub-set of climatic, hydrologic and environmental drivers such as the photosynthetically active radiation, soil temperature, water depth, and soil salinity. The models were tested with field data for multiple sites and seasons (2012-13) collected from the Waquoit Bay, MA. The model estimated the annual wetland carbon storage by up-scaling the instantaneous predicted fluxes to an extended growing season (e.g., May-October) and by accounting for the net annual lateral carbon fluxes between the wetlands and estuary. The Excel Spreadsheet model is a simple ecological engineering tool for coastal carbon management and their incorporation into a potential carbon market under a changing climate, sea level and environment. Specifically, the model can help to determine appropriate GHG offset protocols and monitoring plans for projects that focus on tidal wetland restoration and maintenance.

  3. Modeling systems-level dynamics: Understanding without mechanistic explanation in integrative systems biology.

    Science.gov (United States)

    MacLeod, Miles; Nersessian, Nancy J

    2015-02-01

    In this paper we draw upon rich ethnographic data of two systems biology labs to explore the roles of explanation and understanding in large-scale systems modeling. We illustrate practices that depart from the goal of dynamic mechanistic explanation for the sake of more limited modeling goals. These processes use abstract mathematical formulations of bio-molecular interactions and data fitting techniques which we call top-down abstraction to trade away accurate mechanistic accounts of large-scale systems for specific information about aspects of those systems. We characterize these practices as pragmatic responses to the constraints many modelers of large-scale systems face, which in turn generate more limited pragmatic non-mechanistic forms of understanding of systems. These forms aim at knowledge of how to predict system responses in order to manipulate and control some aspects of them. We propose that this analysis of understanding provides a way to interpret what many systems biologists are aiming for in practice when they talk about the objective of a "systems-level understanding." Copyright © 2014 Elsevier Ltd. All rights reserved.

  4. Mechanistic Indicators of Childhood Asthma (MICA) Study

    Science.gov (United States)

    The Mechanistic Indicators of Childhood Asthma (MICA) Study has been designed to incorporate state-of-the-art technologies to examine the physiological and environmental factors that interact to increase the risk of asthmatic responses. MICA is primarily a clinically-bases obser...

  5. Mechanistic effect modeling for ecological risk assessment: where to go from here?

    Science.gov (United States)

    Grimm, Volker; Martin, Benjamin T

    2013-07-01

    Mechanistic effect models (MEMs) consider the mechanisms of how chemicals affect individuals and ecological systems such as populations and communities. There is an increasing awareness that MEMs have high potential to make risk assessment of chemicals more ecologically relevant than current standard practice. Here we discuss what kinds of MEMs are needed to improve scientific and regulatory aspects of risk assessment. To make valid predictions for a wide range of environmental conditions, MEMs need to include a sufficient amount of emergence, for example, population dynamics emerging from what individual organisms do. We present 1 example where the life cycle of individuals is described using Dynamic Energy Budget theory. The resulting individual-based population model is thus parameterized at the individual level but correctly predicts multiple patterns at the population level. This is the case for both control and treated populations. We conclude that the state-of-the-art in mechanistic effect modeling has reached a level where MEMs are robust and predictive enough to be used in regulatory risk assessment. Mechanistic effect models will thus be used to advance the scientific basis of current standard practice and will, if their development follows Good Modeling Practice, be included in a standardized way in future regulatory risk assessments. Copyright © 2013 SETAC.

  6. Comparison of Two Mechanistic Microbial Growth Models to Estimate Shelf Life of Perishable Food Package under Dynamic Temperature Conditions

    Directory of Open Access Journals (Sweden)

    Dong Sun Lee

    2014-01-01

    Full Text Available Two mechanistic microbial growth models (Huang’s model and model of Baranyi and Roberts given in differential and integrated equation forms were compared in predicting the microbial growth and shelf life under dynamic temperature storage and distribution conditions. Literatures consistently reporting the microbial growth data under constant and changing temperature conditions were selected to obtain the primary model parameters, set up the secondary models, and apply them to predict the microbial growth and shelf life under fluctuating temperatures. When evaluated by general estimation behavior, bias factor, accuracy factor, and root-mean-square error, Huang’s model was comparable to Baranyi and Roberts’ model in the capability to estimate microbial growth under dynamic temperature conditions. Its simple form of single differential equation incorporating directly the growth rate and lag time may work as an advantage to be used in online shelf life estimation by using the electronic device.

  7. Mechanistic species distribution modeling reveals a niche shift during invasion.

    Science.gov (United States)

    Chapman, Daniel S; Scalone, Romain; Štefanić, Edita; Bullock, James M

    2017-06-01

    Niche shifts of nonnative plants can occur when they colonize novel climatic conditions. However, the mechanistic basis for niche shifts during invasion is poorly understood and has rarely been captured within species distribution models. We quantified the consequence of between-population variation in phenology for invasion of common ragweed (Ambrosia artemisiifolia L.) across Europe. Ragweed is of serious concern because of its harmful effects as a crop weed and because of its impact on public health as a major aeroallergen. We developed a forward mechanistic species distribution model based on responses of ragweed development rates to temperature and photoperiod. The model was parameterized and validated from the literature and by reanalyzing data from a reciprocal common garden experiment in which native and invasive populations were grown within and beyond the current invaded range. It could therefore accommodate between-population variation in the physiological requirements for flowering, and predict the potentially invaded ranges of individual populations. Northern-origin populations that were established outside the generally accepted climate envelope of the species had lower thermal requirements for bud development, suggesting local adaptation of phenology had occurred during the invasion. The model predicts that this will extend the potentially invaded range northward and increase the average suitability across Europe by 90% in the current climate and 20% in the future climate. Therefore, trait variation observed at the population scale can trigger a climatic niche shift at the biogeographic scale. For ragweed, earlier flowering phenology in established northern populations could allow the species to spread beyond its current invasive range, substantially increasing its risk to agriculture and public health. Mechanistic species distribution models offer the possibility to represent niche shifts by varying the traits and niche responses of individual

  8. The coefficient of restitution of pressurized balls: a mechanistic model

    Science.gov (United States)

    Georgallas, Alex; Landry, Gaëtan

    2016-01-01

    Pressurized, inflated balls used in professional sports are regulated so that their behaviour upon impact can be anticipated and allow the game to have its distinctive character. However, the dynamics governing the impacts of such balls, even on stationary hard surfaces, can be extremely complex. The energy transformations, which arise from the compression of the gas within the ball and from the shear forces associated with the deformation of the wall, are examined in this paper. We develop a simple mechanistic model of the dependence of the coefficient of restitution, e, upon both the gauge pressure, P_G, of the gas and the shear modulus, G, of the wall. The model is validated using the results from a simple series of experiments using three different sports balls. The fits to the data are extremely good for P_G > 25 kPa and consistent values are obtained for the value of G for the wall material. As far as the authors can tell, this simple, mechanistic model of the pressure dependence of the coefficient of restitution is the first in the literature. *%K Coefficient of Restitution, Dynamics, Inflated Balls, Pressure, Impact Model

  9. Global scale analysis and evaluation of an improved mechanistic representation of plant nitrogen and carbon dynamics in the Community Land Model (CLM)

    Science.gov (United States)

    Ghimire, B.; Riley, W. J.; Koven, C. D.; Randerson, J. T.; Mu, M.; Kattge, J.; Rogers, A.; Reich, P. B.

    2014-12-01

    In many ecosystems, nitrogen is the most limiting nutrient for plant growth and productivity. However mechanistic representation of nitrogen uptake linked to root traits, and functional nitrogen allocation among different leaf enzymes involved in respiration and photosynthesis is currently lacking in Earth System models. The linkage between nitrogen availability and plant productivity is simplistically represented by potential photosynthesis rates, and is subsequently downregulated depending on nitrogen supply and other nitrogen consumers in the model (e.g., nitrification). This type of potential photosynthesis rate calculation is problematic for several reasons. Firstly, plants do not photosynthesize at potential rates and then downregulate. Secondly, there is considerable subjectivity on the meaning of potential photosynthesis rates. Thirdly, there exists lack of understanding on modeling these potential photosynthesis rates in a changing climate. In addition to model structural issues in representing photosynthesis rates, the role of plant roots in nutrient acquisition have been largely ignored in Earth System models. For example, in CLM4.5, nitrogen uptake is linked to leaf level processes (e.g., primarily productivity) rather than root scale process involved in nitrogen uptake. We present a new plant model for CLM with an improved mechanistic presentation of plant nitrogen uptake based on root scale Michaelis Menten kinetics, and stronger linkages between leaf nitrogen and plant productivity by inferring relationships observed in global databases of plant traits (including the TRY database and several individual studies). We also incorporate improved representation of plant nitrogen leaf allocation, especially in tropical regions where significant over-prediction of plant growth and productivity in CLM4.5 simulations exist. We evaluate our improved global model simulations using the International Land Model Benchmarking (ILAMB) framework. We conclude that

  10. Mechanistic modeling of CHF in forced-convection subcooled boiling

    International Nuclear Information System (INIS)

    Podowski, M.Z.; Alajbegovic, A.; Kurul, N.; Drew, D.A.; Lahey, R.T. Jr.

    1997-05-01

    Because of the complexity of phenomena governing boiling heat transfer, the approach to solve practical problems has traditionally been based on experimental correlations rather than mechanistic models. The recent progress in computational fluid dynamics (CFD), combined with improved experimental techniques in two-phase flow and heat transfer, makes the use of rigorous physically-based models a realistic alternative to the current simplistic phenomenological approach. The objective of this paper is to present a new CFD model for critical heat flux (CHF) in low quality (in particular, in subcooled boiling) forced-convection flows in heated channels

  11. Development of Improved Mechanistic Deterioration Models for Flexible Pavements

    DEFF Research Database (Denmark)

    Ullidtz, Per; Ertman, Hans Larsen

    1998-01-01

    The paper describes a pilot study in Denmark with the main objective of developing improved mechanistic deterioration models for flexible pavements based on an accelerated full scale test on an instrumented pavement in the Danish Road Tessting Machine. The study was the first in "International...... Pavement Subgrade Performance Study" sponsored by the Federal Highway Administration (FHWA), USA. The paper describes in detail the data analysis and the resulting models for rutting, roughness, and a model for the plastic strain in the subgrade.The reader will get an understanding of the work needed...

  12. LASSIM-A network inference toolbox for genome-wide mechanistic modeling.

    Directory of Open Access Journals (Sweden)

    Rasmus Magnusson

    2017-06-01

    Full Text Available Recent technological advancements have made time-resolved, quantitative, multi-omics data available for many model systems, which could be integrated for systems pharmacokinetic use. Here, we present large-scale simulation modeling (LASSIM, which is a novel mathematical tool for performing large-scale inference using mechanistically defined ordinary differential equations (ODE for gene regulatory networks (GRNs. LASSIM integrates structural knowledge about regulatory interactions and non-linear equations with multiple steady state and dynamic response expression datasets. The rationale behind LASSIM is that biological GRNs can be simplified using a limited subset of core genes that are assumed to regulate all other gene transcription events in the network. The LASSIM method is implemented as a general-purpose toolbox using the PyGMO Python package to make the most of multicore computers and high performance clusters, and is available at https://gitlab.com/Gustafsson-lab/lassim. As a method, LASSIM works in two steps, where it first infers a non-linear ODE system of the pre-specified core gene expression. Second, LASSIM in parallel optimizes the parameters that model the regulation of peripheral genes by core system genes. We showed the usefulness of this method by applying LASSIM to infer a large-scale non-linear model of naïve Th2 cell differentiation, made possible by integrating Th2 specific bindings, time-series together with six public and six novel siRNA-mediated knock-down experiments. ChIP-seq showed significant overlap for all tested transcription factors. Next, we performed novel time-series measurements of total T-cells during differentiation towards Th2 and verified that our LASSIM model could monitor those data significantly better than comparable models that used the same Th2 bindings. In summary, the LASSIM toolbox opens the door to a new type of model-based data analysis that combines the strengths of reliable mechanistic models

  13. Conceptual models for waste tank mechanistic analysis. Status report, January 1991

    Energy Technology Data Exchange (ETDEWEB)

    Allemann, R. T.; Antoniak, Z. I.; Eyler, L. L.; Liljegren, L. M.; Roberts, J. S.

    1992-02-01

    Pacific Northwest Laboratory (PNL) is conducting a study for Westinghouse Hanford Company (Westinghouse Hanford), a contractor for the US Department of Energy (DOE). The purpose of the work is to study possible mechanisms and fluid dynamics contributing to the periodic release of gases from double-shell waste storage tanks at the Hanford Site in Richland, Washington. This interim report emphasizing the modeling work follows two other interim reports, Mechanistic Analysis of Double-Shell Tank Gas Release Progress Report -- November 1990 and Collection and Analysis of Existing Data for Waste Tank Mechanistic Analysis Progress Report -- December 1990, that emphasized data correlation and mechanisms. The approach in this study has been to assemble and compile data that are pertinent to the mechanisms, analyze the data, evaluate physical properties and parameters, evaluate hypothetical mechanisms, and develop mathematical models of mechanisms.

  14. Mechanistic models for the evaluation of biocatalytic reaction conditions and biosensor design optimization

    DEFF Research Database (Denmark)

    Semenova, Daria

    . In the first case study a mechanistic model was developed to describe the enzymatic reaction of glucose oxidase and glucose in the presence of catalase inside a commercial microfluidic platform with integrated oxygen sensor spots. The simplicity of the proposed model allowed an easy calibration of the reaction...... the microfluidic device. In the second case study the flexible microfluidic platform with integrated amperometric glucose biosensors was developed for continuous monitoring of glucose consumption rates. The integration of the mixing chamber inside the platform allowed performing sample dilutions which subsequently......BRs. In the third case study the mechanistic model of the cyclic voltammetry response of the first generation glucose biosensors was developed and applied for the biosensor design optimization. Furthermore the obtained qualitative and quantitative dependencies between the model output and experimental results were...

  15. The use of mechanistic descriptions of algal growth and zooplankton grazing in an estuarine eutrophication model

    Science.gov (United States)

    Baird, M. E.; Walker, S. J.; Wallace, B. B.; Webster, I. T.; Parslow, J. S.

    2003-03-01

    A simple model of estuarine eutrophication is built on biomechanical (or mechanistic) descriptions of a number of the key ecological processes in estuaries. Mechanistically described processes include the nutrient uptake and light capture of planktonic and benthic autotrophs, and the encounter rates of planktonic predators and prey. Other more complex processes, such as sediment biogeochemistry, detrital processes and phosphate dynamics, are modelled using empirical descriptions from the Port Phillip Bay Environmental Study (PPBES) ecological model. A comparison is made between the mechanistically determined rates of ecological processes and the analogous empirically determined rates in the PPBES ecological model. The rates generally agree, with a few significant exceptions. Model simulations were run at a range of estuarine depths and nutrient loads, with outputs presented as the annually averaged biomass of autotrophs. The simulations followed a simple conceptual model of eutrophication, suggesting a simple biomechanical understanding of estuarine processes can provide a predictive tool for ecological processes in a wide range of estuarine ecosystems.

  16. Biomeasures and mechanistic modeling highlight PK/PD risks for a monoclonal antibody targeting Fn14 in kidney disease.

    Science.gov (United States)

    Chen, Xiaoying; Farrokhi, Vahid; Singh, Pratap; Ocana, Mireia Fernandez; Patel, Jenil; Lin, Lih-Ling; Neubert, Hendrik; Brodfuehrer, Joanne

    2018-01-01

    Discovery of the upregulation of fibroblast growth factor-inducible-14 (Fn14) receptor following tissue injury has prompted investigation into biotherapeutic targeting of the Fn14 receptor for the treatment of conditions such as chronic kidney diseases. In the development of monoclonal antibody (mAb) therapeutics, there is an increasing trend to use biomeasures combined with mechanistic pharmacokinetic/pharmacodynamic (PK/PD) modeling to enable decision making in early discovery. With the aim of guiding preclinical efforts on designing an antibody with optimized properties, we developed a mechanistic site-of-action (SoA) PK/PD model for human application. This model incorporates experimental biomeasures, including concentration of soluble Fn14 (sFn14) in human plasma and membrane Fn14 (mFn14) in human kidney tissue, and turnover rate of human sFn14. Pulse-chase studies using stable isotope-labeled amino acids and mass spectrometry indicated the sFn14 half-life to be approximately 5 hours in healthy volunteers. The biomeasures (concentration, turnover) of sFn14 in plasma reveals a significant hurdle in designing an antibody against Fn14 with desired characteristics. The projected dose (>1 mg/kg/wk for 90% target coverage) derived from the human PK/PD model revealed potential high and frequent dosing requirements under certain conditions. The PK/PD model suggested a unique bell-shaped relationship between target coverage and antibody affinity for anti-Fn14 mAb, which could be applied to direct the antibody engineering towards an optimized affinity. This investigation highlighted potential applications, including assessment of PK/PD risks during early target validation, human dose prediction and drug candidate optimization.

  17. INTEGRATION OF QSAR AND SAR METHODS FOR THE MECHANISTIC INTERPRETATION OF PREDICTIVE MODELS FOR CARCINOGENICITY

    Directory of Open Access Journals (Sweden)

    Natalja Fjodorova

    2012-07-01

    Full Text Available The knowledge-based Toxtree expert system (SAR approach was integrated with the statistically based counter propagation artificial neural network (CP ANN model (QSAR approach to contribute to a better mechanistic understanding of a carcinogenicity model for non-congeneric chemicals using Dragon descriptors and carcinogenic potency for rats as a response. The transparency of the CP ANN algorithm was demonstrated using intrinsic mapping technique specifically Kohonen maps. Chemical structures were represented by Dragon descriptors that express the structural and electronic features of molecules such as their shape and electronic surrounding related to reactivity of molecules. It was illustrated how the descriptors are correlated with particular structural alerts (SAs for carcinogenicity with recognized mechanistic link to carcinogenic activity. Moreover, the Kohonen mapping technique enables one to examine the separation of carcinogens and non-carcinogens (for rats within a family of chemicals with a particular SA for carcinogenicity. The mechanistic interpretation of models is important for the evaluation of safety of chemicals.

  18. Toward a mechanistic modeling of nitrogen limitation for photosynthesis

    Science.gov (United States)

    Xu, C.; Fisher, R. A.; Travis, B. J.; Wilson, C. J.; McDowell, N. G.

    2011-12-01

    The nitrogen limitation is an important regulator for vegetation growth and global carbon cycle. Most current ecosystem process models simulate nitrogen effects on photosynthesis based on a prescribed relationship between leaf nitrogen and photosynthesis; however, there is a large amount of variability in this relationship with different light, temperature, nitrogen availability and CO2 conditions, which can affect the reliability of photosynthesis prediction under future climate conditions. To account for the variability in nitrogen-photosynthesis relationship under different environmental conditions, in this study, we developed a mechanistic model of nitrogen limitation for photosynthesis based on nitrogen trade-offs among light absorption, electron transport, carboxylization and carbon sink. Our model shows that strategies of nitrogen storage allocation as determined by tradeoff among growth and persistence is a key factor contributing to the variability in relationship between leaf nitrogen and photosynthesis. Nitrogen fertilization substantially increases the proportion of nitrogen in storage for coniferous trees but much less for deciduous trees, suggesting that coniferous trees allocate more nitrogen toward persistence compared to deciduous trees. The CO2 fertilization will cause lower nitrogen allocation for carboxylization but higher nitrogen allocation for storage, which leads to a weaker relationship between leaf nitrogen and maximum photosynthesis rate. Lower radiation will cause higher nitrogen allocation for light absorption and electron transport but less nitrogen allocation for carboxylyzation and storage, which also leads to weaker relationship between leaf nitrogen and maximum photosynthesis rate. At the same time, lower growing temperature will cause higher nitrogen allocation for carboxylyzation but lower allocation for light absorption, electron transport and storage, which leads to a stronger relationship between leaf nitrogen and maximum

  19. The Combined Use of Correlative and Mechanistic Species Distribution Models Benefits Low Conservation Status Species.

    Directory of Open Access Journals (Sweden)

    Thibaud Rougier

    Full Text Available Species can respond to climate change by tracking appropriate environmental conditions in space, resulting in a range shift. Species Distribution Models (SDMs can help forecast such range shift responses. For few species, both correlative and mechanistic SDMs were built, but allis shad (Alosa alosa, an endangered anadromous fish species, is one of them. The main purpose of this study was to provide a framework for joint analyses of correlative and mechanistic SDMs projections in order to strengthen conservation measures for species of conservation concern. Guidelines for joint representation and subsequent interpretation of models outputs were defined and applied. The present joint analysis was based on the novel mechanistic model GR3D (Global Repositioning Dynamics of Diadromous fish Distribution which was parameterized on allis shad and then used to predict its future distribution along the European Atlantic coast under different climate change scenarios (RCP 4.5 and RCP 8.5. We then used a correlative SDM for this species to forecast its distribution across the same geographic area and under the same climate change scenarios. First, projections from correlative and mechanistic models provided congruent trends in probability of habitat suitability and population dynamics. This agreement was preferentially interpreted as referring to the species vulnerability to climate change. Climate change could not be accordingly listed as a major threat for allis shad. The congruence in predicted range limits between SDMs projections was the next point of interest. The difference, when noticed, required to deepen our understanding of the niche modelled by each approach. In this respect, the relative position of the northern range limit between the two methods strongly suggested here that a key biological process related to intraspecific variability was potentially lacking in the mechanistic SDM. Based on our knowledge, we hypothesized that local

  20. Testing the molecular clock using mechanistic models of fossil preservation and molecular evolution.

    Science.gov (United States)

    Warnock, Rachel C M; Yang, Ziheng; Donoghue, Philip C J

    2017-06-28

    Molecular sequence data provide information about relative times only, and fossil-based age constraints are the ultimate source of information about absolute times in molecular clock dating analyses. Thus, fossil calibrations are critical to molecular clock dating, but competing methods are difficult to evaluate empirically because the true evolutionary time scale is never known. Here, we combine mechanistic models of fossil preservation and sequence evolution in simulations to evaluate different approaches to constructing fossil calibrations and their impact on Bayesian molecular clock dating, and the relative impact of fossil versus molecular sampling. We show that divergence time estimation is impacted by the model of fossil preservation, sampling intensity and tree shape. The addition of sequence data may improve molecular clock estimates, but accuracy and precision is dominated by the quality of the fossil calibrations. Posterior means and medians are poor representatives of true divergence times; posterior intervals provide a much more accurate estimate of divergence times, though they may be wide and often do not have high coverage probability. Our results highlight the importance of increased fossil sampling and improved statistical approaches to generating calibrations, which should incorporate the non-uniform nature of ecological and temporal fossil species distributions. © 2017 The Authors.

  1. Mechanistic model for void distribution in flashing flow

    International Nuclear Information System (INIS)

    Riznic, J.; Ishii, M.; Afgan, N.

    1987-01-01

    A problem of discharging of an initially subcooled liquid from a high pressure condition into a low pressure environment is quite important in several industrial systems such as nuclear reactors and chemical reactors. A new model for the flashing process is proposed here based on the wall nucleation theory, bubble growth model and drift-flux bubble transport model. In order to calculate the bubble number density, the bubble number transport equation with a distributed source from the wall nucleation sites is used. The model predictions in terms of the void fraction are compared to Moby Dick and BNL experimental data. It shows that satisfactory agreements could be obtained from the present model without any floating parameter to be adjusted with data. This result indicates that, at least for the experimental conditions considered here, the mechanistic prediction of the flashing phenomenon is possible based on the present wall nucleation based model. 43 refs., 4 figs

  2. Mechanistic modeling of heat transfer process governing pressure tube-to-calandria tube contact and fuel channel failure

    International Nuclear Information System (INIS)

    Luxat, J.C.

    2002-01-01

    Heat transfer behaviour and phenomena associated with ballooning deformation of a pressure tube into contact with a calandria tube have been analyzed and mechanistic models have been developed to describe the heat transfer and thermal-mechanical processes. These mechanistic models are applied to analyze experiments performed in various COG funded Contact Boiling Test series. Particular attention is given in the modeling to characterization of the conditions for which fuel channel failure may occur. Mechanistic models describing the governing heat transfer and thermal-mechanical processes are presented. The technical basis for characterizing parameters of the models from the general heat transfer literature is described. The validity of the models is demonstrated by comparison with experimental data. Fuel channel integrity criteria are proposed which are based upon three necessary and sequential mechanisms: Onset of CHF and local drypatch formation at contact; sustained film boiling in the post-contact period; and creep strain to failure of the calandria tube while in sustained film boiling. (author)

  3. A mechanistic model for electricity consumption on dairy farms: Definition, validation, and demonstration

    NARCIS (Netherlands)

    Upton, J.R.; Murphy, M.; Shallo, L.; Groot Koerkamp, P.W.G.; Boer, de I.J.M.

    2014-01-01

    Our objective was to define and demonstrate a mechanistic model that enables dairy farmers to explore the impact of a technical or managerial innovation on electricity consumption, associated CO2 emissions, and electricity costs. We, therefore, (1) defined a model for electricity consumption on

  4. Mechanistic modelling of cancer: some reflections from software engineering and philosophy of science.

    Science.gov (United States)

    Cañete-Valdeón, José M; Wieringa, Roel; Smallbone, Kieran

    2012-12-01

    There is a growing interest in mathematical mechanistic modelling as a promising strategy for understanding tumour progression. This approach is accompanied by a methodological change of making research, in which models help to actively generate hypotheses instead of waiting for general principles to become apparent once sufficient data are accumulated. This paper applies recent research from philosophy of science to uncover three important problems of mechanistic modelling which may compromise its mainstream application, namely: the dilemma of formal and informal descriptions, the need to express degrees of confidence and the need of an argumentation framework. We report experience and research on similar problems from software engineering and provide evidence that the solutions adopted there can be transferred to the biological domain. We hope this paper can provoke new opportunities for further and profitable interdisciplinary research in the field.

  5. Mechanistic model of mass-specific basal metabolic rate: evaluation in healthy young adults.

    Science.gov (United States)

    Wang, Z; Bosy-Westphal, A; Schautz, B; Müller, M

    2011-12-01

    Mass-specific basal metabolic rate (mass-specific BMR), defined as the resting energy expenditure per unit body mass per day, is an important parameter in energy metabolism research. However, a mechanistic explanation for magnitude of mass-specific BMR remains lacking. The objective of the present study was to validate the applicability of a proposed mass-specific BMR model in healthy adults. A mechanistic model was developed at the organ-tissue level, mass-specific BMR = Σ( K i × F i ), where Fi is the fraction of body mass as individual organs and tissues, and K i is the specific resting metabolic rate of major organs and tissues. The Fi values were measured by multiple MRI scans and the K i values were suggested by Elia in 1992. A database of healthy non-elderly non-obese adults (age 20 - 49 yrs, BMI BMR of all subjects was 21.6 ± 1.9 (mean ± SD) and 21.7 ± 1.6 kcal/kg per day, respectively. The measured mass-specific BMR was correlated with the predicted mass-specific BMR (r = 0.82, P BMR, versus the average of measured and predicted mass-specific BMR. In conclusion, the proposed mechanistic model was validated in non-elderly non-obese adults and can help to understand the inherent relationship between mass-specific BMR and body composition.

  6. Quantitative assessment of biological impact using transcriptomic data and mechanistic network models

    International Nuclear Information System (INIS)

    Thomson, Ty M.; Sewer, Alain; Martin, Florian; Belcastro, Vincenzo; Frushour, Brian P.; Gebel, Stephan; Park, Jennifer; Schlage, Walter K.; Talikka, Marja; Vasilyev, Dmitry M.; Westra, Jurjen W.; Hoeng, Julia; Peitsch, Manuel C.

    2013-01-01

    Exposure to biologically active substances such as therapeutic drugs or environmental toxicants can impact biological systems at various levels, affecting individual molecules, signaling pathways, and overall cellular processes. The ability to derive mechanistic insights from the resulting system responses requires the integration of experimental measures with a priori knowledge about the system and the interacting molecules therein. We developed a novel systems biology-based methodology that leverages mechanistic network models and transcriptomic data to quantitatively assess the biological impact of exposures to active substances. Hierarchically organized network models were first constructed to provide a coherent framework for investigating the impact of exposures at the molecular, pathway and process levels. We then validated our methodology using novel and previously published experiments. For both in vitro systems with simple exposure and in vivo systems with complex exposures, our methodology was able to recapitulate known biological responses matching expected or measured phenotypes. In addition, the quantitative results were in agreement with experimental endpoint data for many of the mechanistic effects that were assessed, providing further objective confirmation of the approach. We conclude that our methodology evaluates the biological impact of exposures in an objective, systematic, and quantifiable manner, enabling the computation of a systems-wide and pan-mechanistic biological impact measure for a given active substance or mixture. Our results suggest that various fields of human disease research, from drug development to consumer product testing and environmental impact analysis, could benefit from using this methodology. - Highlights: • The impact of biologically active substances is quantified at multiple levels. • The systems-level impact integrates the perturbations of individual networks. • The networks capture the relationships between

  7. Quantum Chemical Examination of the Sequential Halogen Incorporation Scheme for the Modeling of Speciation of I/Br/Cl-Containing Trihalomethanes.

    Science.gov (United States)

    Zhang, Chenyang; Li, Maodong; Han, Xuze; Yan, Mingquan

    2018-02-20

    The recently developed three-step ternary halogenation model interprets the incorporation of chlorine, bromine, and iodine ions into natural organic matter (NOM) and formation of iodine-, bromine-, and chlorine-containing trihalomethanes (THMs) based on the competition of iodine, bromine, and chlorine species at each node of the halogenation sequence. This competition is accounted for using the dimensionless ratios (denoted as γ) of kinetic rates of reactions of the initial attack sites or halogenated intermediates with chlorine, bromine, and iodine ions. However, correlations between the model predictions made and mechanistic aspects of the incorporation of halogen species need to be ascertained in more detail. In this study, quantum chemistry calculations were first used to probe the formation mechanism of 10 species of Cl-/Br-/I- THMs. The HOMO energy (E HOMO ) of each mono-, bi-, or trihalomethanes were calculated by B3LYP method in Gaussian 09 software. Linear correlations were found to exist between the logarithms of experimentally determined kinetic preference coefficients γ reported in prior research and, on the other hand, differences of E HOMO values between brominated/iodinated and chlorinated halomethanes. One notable exception from this trend was that observed for the incorporation of iodine into mono- and di-iodinated intermediates. These observations confirm the three-step halogen incorporation sequence and the factor γ in the statistical model. The combined use of quantum chemistry calculations and the ternary sequential halogenation model provides a new insight into the microscopic nature of NOM-halogen interactions and the trends seen in the behavior of γ factors incorporated in the THM speciation models.

  8. SITE-94. Adaptation of mechanistic sorption models for performance assessment calculations

    International Nuclear Information System (INIS)

    Arthur, R.C.

    1996-10-01

    Sorption is considered in most predictive models of radionuclide transport in geologic systems. Most models simulate the effects of sorption in terms of empirical parameters, which however can be criticized because the data are only strictly valid under the experimental conditions at which they were measured. An alternative is to adopt a more mechanistic modeling framework based on recent advances in understanding the electrical properties of oxide mineral-water interfaces. It has recently been proposed that these 'surface-complexation' models may be directly applicable to natural systems. A possible approach for adapting mechanistic sorption models for use in performance assessments, using this 'surface-film' concept, is described in this report. Surface-acidity parameters in the Generalized Two-Layer surface complexation model are combined with surface-complexation constants for Np(V) sorption ob hydrous ferric oxide to derive an analytical model enabling direct calculation of corresponding intrinsic distribution coefficients as a function of pH, and Ca 2+ , Cl - , and HCO 3 - concentrations. The surface film concept is then used to calculate whole-rock distribution coefficients for Np(V) sorption by altered granitic rocks coexisting with a hypothetical, oxidized Aespoe groundwater. The calculated results suggest that the distribution coefficients for Np adsorption on these rocks could range from 10 to 100 ml/g. Independent estimates of K d for Np sorption in similar systems, based on an extensive review of experimental data, are consistent, though slightly conservative, with respect to the calculated values. 31 refs

  9. Mechanistic CHF modeling for natural circulation applications in SMR

    Energy Technology Data Exchange (ETDEWEB)

    Luitjens, Jeffrey [Department of Nuclear Engineering and Radiation Health Physics, Oregon State University, 3451 SW Jefferson Way, Corvallis, OR 97331 (United States); Wu, Qiao, E-mail: qiao.wu@oregonstate.edu [Department of Nuclear Engineering and Radiation Health Physics, Oregon State University, 3451 SW Jefferson Way, Corvallis, OR 97331 (United States); Greenwood, Scott; Corradini, Michael [Department of Engineering Physics, University of Wisconsin, 1415 Engineering Drive, Madison, WI 53706 (United States)

    2016-12-15

    A mechanistic critical heat flux correlation has been developed for a wide range of operating conditions which include low mass fluxes of 540–890 kg/m{sup 2}-s, high pressures of 12–13 MPa, and critical heat fluxes of 835–1100 kW/m{sup 2}. Eleven experimental data points have been collected over these conditions to inform the development of the model using bundle geometry. Errors of within 15% have been obtained with the proposed model for predicting the critical heat flux value, location, and critical pin power for a non-uniform heat flux applied to a 2 × 2 bundle configuration.

  10. Mechanistic curiosity will not kill the Bayesian cat

    NARCIS (Netherlands)

    Borsboom, D.; Wagenmakers, E.-J.; Romeijn, J.-W.

    2011-01-01

    Jones & Love (J&L) suggest that Bayesian approaches to the explanation of human behavior should be constrained by mechanistic theories. We argue that their proposal misconstrues the relation between process models, such as the Bayesian model, and mechanisms. While mechanistic theories can answer

  11. Mechanistic curiosity will not kill the Bayesian cat

    NARCIS (Netherlands)

    Borsboom, Denny; Wagenmakers, Eric-Jan; Romeijn, Jan-Willem

    Jones & Love (J&L) suggest that Bayesian approaches to the explanation of human behavior should be constrained by mechanistic theories. We argue that their proposal misconstrues the relation between process models, such as the Bayesian model, and mechanisms. While mechanistic theories can answer

  12. Modeling of the pyruvate production with Escherichia coli: comparison of mechanistic and neural networks-based models.

    Science.gov (United States)

    Zelić, B; Bolf, N; Vasić-Racki, D

    2006-06-01

    Three different models: the unstructured mechanistic black-box model, the input-output neural network-based model and the externally recurrent neural network model were used to describe the pyruvate production process from glucose and acetate using the genetically modified Escherichia coli YYC202 ldhA::Kan strain. The experimental data were used from the recently described batch and fed-batch experiments [ Zelić B, Study of the process development for Escherichia coli-based pyruvate production. PhD Thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, Zagreb, Croatia, July 2003. (In English); Zelić et al. Bioproc Biosyst Eng 26:249-258 (2004); Zelić et al. Eng Life Sci 3:299-305 (2003); Zelić et al Biotechnol Bioeng 85:638-646 (2004)]. The neural networks were built out of the experimental data obtained in the fed-batch pyruvate production experiments with the constant glucose feed rate. The model validation was performed using the experimental results obtained from the batch and fed-batch pyruvate production experiments with the constant acetate feed rate. Dynamics of the substrate and product concentration changes was estimated using two neural network-based models for biomass and pyruvate. It was shown that neural networks could be used for the modeling of complex microbial fermentation processes, even in conditions in which mechanistic unstructured models cannot be applied.

  13. A mechanistic modelling and data assimilation approach to estimate the carbon/chlorophyll and carbon/nitrogen ratios in a coupled hydrodynamical-biological model

    Directory of Open Access Journals (Sweden)

    B. Faugeras

    2004-01-01

    Full Text Available The principal objective of hydrodynamical-biological models is to provide estimates of the main carbon fluxes such as total and export oceanic production. These models are nitrogen based, that is to say that the variables are expressed in terms of their nitrogen content. Moreover models are calibrated using chlorophyll data sets. Therefore carbon to chlorophyll (C:Chl and carbon to nitrogen (C:N ratios have to be assumed. This paper addresses the problem of the representation of these ratios. In a 1D framework at the DYFAMED station (NW Mediterranean Sea we propose a model which enables the estimation of the basic biogeochemical fluxes and in which the spatio-temporal variability of the C:Chl and C:N ratios is fully represented in a mechanical way. This is achieved through the introduction of new state variables coming from the embedding of a phytoplankton growth model in a more classical Redfieldian NNPZD-DOM model (in which the C:N ratio is assumed to be a constant. Following this modelling step, the parameters of the model are estimated using the adjoint data assimilation method which enables the assimilation of chlorophyll and nitrate data sets collected at DYFAMED in 1997.Comparing the predictions of the new Mechanistic model with those of the classical Redfieldian NNPZD-DOM model which was calibrated with the same data sets, we find that both models reproduce the reference data in a comparable manner. Both fluxes and stocks can be equally well predicted by either model. However if the models are coinciding on an average basis, they are diverging from a variability prediction point of view. In the Mechanistic model biology adapts much faster to its environment giving rise to higher short term variations. Moreover the seasonal variability in total production differs from the Redfieldian NNPZD-DOM model to the Mechanistic model. In summer the Mechanistic model predicts higher production values in carbon unit than the Redfieldian NNPZD

  14. A mechanistic Eulerian-Lagrangian model for dispersed flow film boiling

    International Nuclear Information System (INIS)

    Andreani, M.; Yadigaroglu, G.

    1991-01-01

    In this paper a new mechanistic model of heat transfer in the dispersed flow regime is presented. The usual assumptions that render most of the available models unsuitable for the analysis of the reflooding phase of the LOCA are discussed, and a two-dimensional time-independent numerical model is developed. The gas temperature field is solved in a fixed-grid (Eulerian) mesh, with the droplets behaving as mass and energy sources. The histories of a large number of computational droplets are followed in a Lagrangian frame, considering evaporation, break-up and interactions with the vapor and with the wall. comparisons of calculated wall and vapor temperatures with experimental data are shown for two reflooding tests

  15. Rational and Mechanistic Perspectives on Reinforcement Learning

    Science.gov (United States)

    Chater, Nick

    2009-01-01

    This special issue describes important recent developments in applying reinforcement learning models to capture neural and cognitive function. But reinforcement learning, as a theoretical framework, can apply at two very different levels of description: "mechanistic" and "rational." Reinforcement learning is often viewed in mechanistic terms--as…

  16. Mechanistic Systems Modeling to Improve Understanding and Prediction of Cardiotoxicity Caused by Targeted Cancer Therapeutics

    Directory of Open Access Journals (Sweden)

    Jaehee V. Shim

    2017-09-01

    Full Text Available Tyrosine kinase inhibitors (TKIs are highly potent cancer therapeutics that have been linked with serious cardiotoxicity, including left ventricular dysfunction, heart failure, and QT prolongation. TKI-induced cardiotoxicity is thought to result from interference with tyrosine kinase activity in cardiomyocytes, where these signaling pathways help to control critical processes such as survival signaling, energy homeostasis, and excitation–contraction coupling. However, mechanistic understanding is limited at present due to the complexities of tyrosine kinase signaling, and the wide range of targets inhibited by TKIs. Here, we review the use of TKIs in cancer and the cardiotoxicities that have been reported, discuss potential mechanisms underlying cardiotoxicity, and describe recent progress in achieving a more systematic understanding of cardiotoxicity via the use of mechanistic models. In particular, we argue that future advances are likely to be enabled by studies that combine large-scale experimental measurements with Quantitative Systems Pharmacology (QSP models describing biological mechanisms and dynamics. As such approaches have proven extremely valuable for understanding and predicting other drug toxicities, it is likely that QSP modeling can be successfully applied to cardiotoxicity induced by TKIs. We conclude by discussing a potential strategy for integrating genome-wide expression measurements with models, illustrate initial advances in applying this approach to cardiotoxicity, and describe challenges that must be overcome to truly develop a mechanistic and systematic understanding of cardiotoxicity caused by TKIs.

  17. Simulating the Risk of Liver Fluke Infection using a Mechanistic Hydro-epidemiological Model

    Science.gov (United States)

    Beltrame, Ludovica; Dunne, Toby; Rose, Hannah; Walker, Josephine; Morgan, Eric; Vickerman, Peter; Wagener, Thorsten

    2016-04-01

    Liver Fluke (Fasciola hepatica) is a common parasite found in livestock and responsible for considerable economic losses throughout the world. Risk of infection is strongly influenced by climatic and hydrological conditions, which characterise the host environment for parasite development and transmission. Despite on-going control efforts, increases in fluke outbreaks have been reported in recent years in the UK, and have been often attributed to climate change. Currently used fluke risk models are based on empirical relationships derived between historical climate and incidence data. However, hydro-climate conditions are becoming increasingly non-stationary due to climate change and direct anthropogenic impacts such as land use change, making empirical models unsuitable for simulating future risk. In this study we introduce a mechanistic hydro-epidemiological model for Liver Fluke, which explicitly simulates habitat suitability for disease development in space and time, representing the parasite life cycle in connection with key environmental conditions. The model is used to assess patterns of Liver Fluke risk for two catchments in the UK under current and potential future climate conditions. Comparisons are made with a widely used empirical model employing different datasets, including data from regional veterinary laboratories. Results suggest that mechanistic models can achieve adequate predictive ability and support adaptive fluke control strategies under climate change scenarios.

  18. A tissue-engineered gastric cancer model for mechanistic study of anti-tumor drugs

    International Nuclear Information System (INIS)

    Gao, Ming; Cai, Yiting; Wu, Wei; Shi, Yazhou; Fei, Zhewei

    2013-01-01

    The use of the traditional xenograft subcutaneous tumor model has been contested because of its limitations, such as a slow tumorigenesis, inconsistent chemotherapeutic results, etc. In light of these challenges, we aim to revamp the traditional model by employing an electrospun scaffold composed of polydioxanone, gelatin and elastin to boost the tumorigenesis. The scaffold featured a highly porous microstructure and successfully supported the growth of tumor cells in vitro without provoking apoptosis. In vivo studies showed that in the scaffold model the tumor volume increased by 43.27% and the weight by 75.58%, respectively, within a 12-week period. In addition, the scaffold model saw an increase of CD24 + and CD44 + cells in the tumor mass by 42% and 313%, respectively. The scaffolding materials did not lead to phenotypic changes during the tumorigenesis. Thereafter, in the scaffold model, we found that the chemotherapeutic regimen of docetaxel, cisplatin and fluorouracil unleashed a stronger capability than the regimen comprising cisplatin and fluorouracil to deplete the CD44 + subpopulation. This discovery sheds mechanistic lights on the role of docetaxel for its future chemotherapeutic applications. This revamped model affords cancer scientists a convenient and reliable platform to mechanistically investigate the chemotherapeutic drugs on gastric cancer stem cells. (paper)

  19. Comparison of Two-Phase Pipe Flow in OpenFOAM with a Mechanistic Model

    Science.gov (United States)

    Shuard, Adrian M.; Mahmud, Hisham B.; King, Andrew J.

    2016-03-01

    Two-phase pipe flow is a common occurrence in many industrial applications such as power generation and oil and gas transportation. Accurate prediction of liquid holdup and pressure drop is of vast importance to ensure effective design and operation of fluid transport systems. In this paper, a Computational Fluid Dynamics (CFD) study of a two-phase flow of air and water is performed using OpenFOAM. The two-phase solver, interFoam is used to identify flow patterns and generate values of liquid holdup and pressure drop, which are compared to results obtained from a two-phase mechanistic model developed by Petalas and Aziz (2002). A total of 60 simulations have been performed at three separate pipe inclinations of 0°, +10° and -10° respectively. A three dimensional, 0.052m diameter pipe of 4m length is used with the Shear Stress Transport (SST) k - ɷ turbulence model to solve the turbulent mixtures of air and water. Results show that the flow pattern behaviour and numerical values of liquid holdup and pressure drop compare reasonably well to the mechanistic model.

  20. Integrative modelling of animal movement: incorporating in situ habitat and behavioural information for a migratory marine predator.

    Science.gov (United States)

    Bestley, Sophie; Jonsen, Ian D; Hindell, Mark A; Guinet, Christophe; Charrassin, Jean-Benoît

    2013-01-07

    A fundamental goal in animal ecology is to quantify how environmental (and other) factors influence individual movement, as this is key to understanding responsiveness of populations to future change. However, quantitative interpretation of individual-based telemetry data is hampered by the complexity of, and error within, these multi-dimensional data. Here, we present an integrative hierarchical Bayesian state-space modelling approach where, for the first time, the mechanistic process model for the movement state of animals directly incorporates both environmental and other behavioural information, and observation and process model parameters are estimated within a single model. When applied to a migratory marine predator, the southern elephant seal (Mirounga leonina), we find the switch from directed to resident movement state was associated with colder water temperatures, relatively short dive bottom time and rapid descent rates. The approach presented here can have widespread utility for quantifying movement-behaviour (diving or other)-environment relationships across species and systems.

  1. A mechanistic model for the evolution of multicellularity

    Science.gov (United States)

    Amado, André; Batista, Carlos; Campos, Paulo R. A.

    2018-02-01

    Through a mechanistic approach we investigate the formation of aggregates of variable sizes, accounting mechanisms of aggregation, dissociation, death and reproduction. In our model, cells can produce two metabolites, but the simultaneous production of both metabolites is costly in terms of fitness. Thus, the formation of larger groups can favor the aggregates to evolve to a configuration where division of labor arises. It is assumed that the states of the cells in a group are those that maximize organismal fitness. In the model it is considered that the groups can grow linearly, forming a chain, or compactly keeping a roughly spherical shape. Starting from a population consisting of single-celled organisms, we observe the formation of groups with variable sizes and usually much larger than two-cell aggregates. Natural selection can favor the formation of large groups, which allows the system to achieve new and larger fitness maxima.

  2. A dynamic and mechanistic model of PCB bioaccumulation in the European hake ( Merluccius merluccius)

    Science.gov (United States)

    Bodiguel, Xavier; Maury, Olivier; Mellon-Duval, Capucine; Roupsard, François; Le Guellec, Anne-Marie; Loizeau, Véronique

    2009-08-01

    Bioaccumulation is difficult to document because responses differ among chemical compounds, with environmental conditions, and physiological processes characteristic of each species. We use a mechanistic model, based on the Dynamic Energy Budget (DEB) theory, to take into account this complexity and study factors impacting accumulation of organic pollutants in fish through ontogeny. The bioaccumulation model proposed is a comprehensive approach that relates evolution of hake PCB contamination to physiological information about the fish, such as diet, metabolism, reserve and reproduction status. The species studied is the European hake ( Merluccius merluccius, L. 1758). The model is applied to study the total concentration and the lipid normalised concentration of 4 PCB congeners in male and female hakes from the Gulf of Lions (NW Mediterranean sea) and the Bay of Biscay (NE Atlantic ocean). Outputs of the model compare consistently to measurements over the life span of fish. Simulation results clearly demonstrate the relative effects of food contamination, growth and reproduction on the PCB bioaccumulation in hake. The same species living in different habitats and exposed to different PCB prey concentrations exhibit marked difference in the body accumulation of PCBs. At the adult stage, female hakes have a lower PCB concentration compared to males for a given length. We successfully simulated these sex-specific PCB concentrations by considering two mechanisms: a higher energy allocation to growth for females and a transfer of PCBs from the female to its eggs when allocating lipids from reserve to eggs. Finally, by its mechanistic description of physiological processes, the model is relevant for other species and sets the stage for a mechanistic understanding of toxicity and ecological effects of organic contaminants in marine organisms.

  3. Assessing first-order emulator inference for physical parameters in nonlinear mechanistic models

    Science.gov (United States)

    Hooten, Mevin B.; Leeds, William B.; Fiechter, Jerome; Wikle, Christopher K.

    2011-01-01

    We present an approach for estimating physical parameters in nonlinear models that relies on an approximation to the mechanistic model itself for computational efficiency. The proposed methodology is validated and applied in two different modeling scenarios: (a) Simulation and (b) lower trophic level ocean ecosystem model. The approach we develop relies on the ability to predict right singular vectors (resulting from a decomposition of computer model experimental output) based on the computer model input and an experimental set of parameters. Critically, we model the right singular vectors in terms of the model parameters via a nonlinear statistical model. Specifically, we focus our attention on first-order models of these right singular vectors rather than the second-order (covariance) structure.

  4. Bird Migration Under Climate Change - A Mechanistic Approach Using Remote Sensing

    Science.gov (United States)

    Smith, James A.; Blattner, Tim; Messmer, Peter

    2010-01-01

    migratory shorebirds in the central fly ways of North America. We demonstrated the phenotypic plasticity of a migratory population of Pectoral sandpipers consisting of an ensemble of 10,000 individual birds in response to changes in stopover locations using an individual based migration model driven by remotely sensed land surface data, climate data and biological field data. With the advent of new computing capabilities enabled hy recent GPU-GP computing paradigms and commodity hardware, it now is possible to simulate both larger ensemble populations and to incorporate more realistic mechanistic factors into migration models. Here, we take our first steps use these tools to study the impact of long-term drought variability on shorebird survival.

  5. Prediction of warfarin maintenance dose in Han Chinese patients using a mechanistic model based on genetic and non-genetic factors.

    Science.gov (United States)

    Lu, Yuan; Yang, Jinbo; Zhang, Haiyan; Yang, Jin

    2013-07-01

    Many attempts have been made to predict the warfarin maintenance dose in patients beginning warfarin therapy using a descriptive model based on multiple linear regression. Here we report the first attempt to develop a comprehensive mechanistic model integrating in vitro-in vivo extrapolation (IVIVE) with a pharmacokinetic-pharmacodynamic model to predict the warfarin maintenance dose in Han Chinese patients. The model incorporates demographic factors [sex, age, body weight (BW)] and the genetic polymorphisms of cytochrome P450 (CYP) 2C9 (CYP2C9) and vitamin K epoxide reductase complex subunit 1 (VKORC1). Information on the various factors, mean warfarin daily dose and International Normalized Ratio (INR) was available for a cohort of 197 Han Chinese patients. Based on in vitro enzyme kinetic parameters for S-warfarin metabolism, demographic data for Han Chinese and some scaling factors, the S-warfarin clearance (CL) was predicted for patients in the cohort with different CYP2C9 genotypes using IVIVE. The plasma concentration of S-warfarin after a single oral dose was simulated using a one-compartment pharmacokinetic model with first-order absorption and a lag time and was combined with a mechanistic coagulation model to simulate the INR response. The warfarin maintenance dose was then predicted based on the demographic data and genotypes of CYP2C9 and VKORC1 for each patient and using the observed steady-state INR (INRss) as a target value. Finally, sensitivity analysis was carried out to determine which factor(s) affect the warfarin maintenance dose most strongly. The predictive performance of this mechanistic model is not inferior to that of our previous descriptive model. There were significant differences in the mean warfarin daily dose in patients with different CYP2C9 and VKORC1 genotypes. Using IVIVE, the predicted mean CL of S-warfarin for patients with CYP2C9*1/*3 (0.092 l/h, n = 11) was 57 % less than for those with wild-type *1/*1 (0.215 l/h, n

  6. Mechanistic modelling of the drying behaviour of single pharmaceutical granules

    DEFF Research Database (Denmark)

    Thérèse F.C. Mortier, Séverine; Beer, Thomas De; Gernaey, Krist

    2012-01-01

    The trend to move towards continuous production processes in pharmaceutical applications enhances the necessity to develop mechanistic models to understand and control these processes. This work focuses on the drying behaviour of a single wet granule before tabletting, using a six...... phase (submodel 2), the water inside the granule evaporates. The second submodel contains an empirical power coefficient, b. A sensitivity analysis was performed to study the influence of parameters on the moisture content of single pharmaceutical granules, which clearly points towards the importance...

  7. A Mechanistic Beta-Binomial Probability Model for mRNA Sequencing Data.

    Science.gov (United States)

    Smith, Gregory R; Birtwistle, Marc R

    2016-01-01

    A main application for mRNA sequencing (mRNAseq) is determining lists of differentially-expressed genes (DEGs) between two or more conditions. Several software packages exist to produce DEGs from mRNAseq data, but they typically yield different DEGs, sometimes markedly so. The underlying probability model used to describe mRNAseq data is central to deriving DEGs, and not surprisingly most softwares use different models and assumptions to analyze mRNAseq data. Here, we propose a mechanistic justification to model mRNAseq as a binomial process, with data from technical replicates given by a binomial distribution, and data from biological replicates well-described by a beta-binomial distribution. We demonstrate good agreement of this model with two large datasets. We show that an emergent feature of the beta-binomial distribution, given parameter regimes typical for mRNAseq experiments, is the well-known quadratic polynomial scaling of variance with the mean. The so-called dispersion parameter controls this scaling, and our analysis suggests that the dispersion parameter is a continually decreasing function of the mean, as opposed to current approaches that impose an asymptotic value to the dispersion parameter at moderate mean read counts. We show how this leads to current approaches overestimating variance for moderately to highly expressed genes, which inflates false negative rates. Describing mRNAseq data with a beta-binomial distribution thus may be preferred since its parameters are relatable to the mechanistic underpinnings of the technique and may improve the consistency of DEG analysis across softwares, particularly for moderately to highly expressed genes.

  8. Problems in mechanistic theoretical models for cell transformation by ionizing radiation

    International Nuclear Information System (INIS)

    Chatterjee, Aloke; Holley, W.R.

    1992-01-01

    A mechanistic model based on yields of double strand breaks has been developed to determine the dose response curves for cell transformation frequencies. At its present stage the model is applicable to immortal cell lines and to various qualities (X-rays, Neon and Iron) of ionizing radiation. Presently, we have considered four types of processes which can lead to activation phenomena: (i) point mutation events on a regulatory segment of selected oncogenes, (ii) inactivation of suppressor genes, through point mutation, (iii) deletion of a suppressor gene by a single track, and (iv) deletion of a suppressor gene by two tracks. (author)

  9. Mechanistic modeling for mammography screening risks

    International Nuclear Information System (INIS)

    Bijwaard, Harmen

    2008-01-01

    Full text: Western populations show a very high incidence of breast cancer and in many countries mammography screening programs have been set up for the early detection of these cancers. Through these programs large numbers of women (in the Netherlands, 700.000 per year) are exposed to low but not insignificant X-ray doses. ICRP based risk estimates indicate that the number of breast cancer casualties due to mammography screening can be as high as 50 in the Netherlands per year. The number of lives saved is estimated to be much higher, but for an accurate calculation of the benefits of screening a better estimate of these risks is indispensable. Here it is attempted to better quantify the radiological risks of mammography screening through the application of a biologically based model for breast tumor induction by X-rays. The model is applied to data obtained from the National Institutes of Health in the U.S. These concern epidemiological data of female TB patients who received high X-ray breast doses in the period 1930-1950 through frequent fluoroscopy of their lungs. The mechanistic model that is used to describe the increased breast cancer incidence is based on an earlier study by Moolgavkar et al. (1980), in which the natural background incidence of breast cancer was modeled. The model allows for a more sophisticated extrapolation of risks to the low dose X-ray exposures that are common in mammography screening and to the higher ages that are usually involved. Furthermore, it allows for risk transfer to other (non-western) populations. The results have implications for decisions on the frequency of screening, the number of mammograms taken at each screening, minimum and maximum ages for screening and the transfer to digital equipment. (author)

  10. Comparison of Two-Phase Pipe Flow in OpenFOAM with a Mechanistic Model

    International Nuclear Information System (INIS)

    Shuard, Adrian M; Mahmud, Hisham B; King, Andrew J

    2016-01-01

    Two-phase pipe flow is a common occurrence in many industrial applications such as power generation and oil and gas transportation. Accurate prediction of liquid holdup and pressure drop is of vast importance to ensure effective design and operation of fluid transport systems. In this paper, a Computational Fluid Dynamics (CFD) study of a two-phase flow of air and water is performed using OpenFOAM. The two-phase solver, interFoam is used to identify flow patterns and generate values of liquid holdup and pressure drop, which are compared to results obtained from a two-phase mechanistic model developed by Petalas and Aziz (2002). A total of 60 simulations have been performed at three separate pipe inclinations of 0°, +10° and -10° respectively. A three dimensional, 0.052m diameter pipe of 4m length is used with the Shear Stress Transport (SST) k - ω turbulence model to solve the turbulent mixtures of air and water. Results show that the flow pattern behaviour and numerical values of liquid holdup and pressure drop compare reasonably well to the mechanistic model. (paper)

  11. Malaria's missing number: calculating the human component of R0 by a within-host mechanistic model of Plasmodium falciparum infection and transmission.

    Directory of Open Access Journals (Sweden)

    Geoffrey L Johnston

    2013-04-01

    Full Text Available Human infection by malarial parasites of the genus Plasmodium begins with the bite of an infected Anopheles mosquito. Current estimates place malaria mortality at over 650,000 individuals each year, mostly in African children. Efforts to reduce disease burden can benefit from the development of mathematical models of disease transmission. To date, however, comprehensive modeling of the parameters defining human infectivity to mosquitoes has remained elusive. Here, we describe a mechanistic within-host model of Plasmodium falciparum infection in humans and pathogen transmission to the mosquito vector. Our model incorporates the entire parasite lifecycle, including the intra-erythrocytic asexual forms responsible for disease, the onset of symptoms, the development and maturation of intra-erythrocytic gametocytes that are transmissible to Anopheles mosquitoes, and human-to-mosquito infectivity. These model components were parameterized from malaria therapy data and other studies to simulate individual infections, and the ensemble of outputs was found to reproduce the full range of patient responses to infection. Using this model, we assessed human infectivity over the course of untreated infections and examined the effects in relation to transmission intensity, expressed by the basic reproduction number R0 (defined as the number of secondary cases produced by a single typical infection in a completely susceptible population. Our studies predict that net human-to-mosquito infectivity from a single non-immune individual is on average equal to 32 fully infectious days. This estimate of mean infectivity is equivalent to calculating the human component of malarial R0 . We also predict that mean daily infectivity exceeds five percent for approximately 138 days. The mechanistic framework described herein, made available as stand-alone software, will enable investigators to conduct detailed studies into theories of malaria control, including the effects of

  12. Monitoring the Orientational Changes of Alamethicin during Incorporation into Bilayer Lipid Membranes.

    Science.gov (United States)

    Forbrig, Enrico; Staffa, Jana K; Salewski, Johannes; Mroginski, Maria Andrea; Hildebrandt, Peter; Kozuch, Jacek

    2018-02-13

    Antimicrobial peptides (AMPs) are the first line of defense after contact of an infectious invader, for example, bacterium or virus, with a host and an integral part of the innate immune system of humans. Their broad spectrum of biological functions ranges from cell membrane disruption over facilitation of chemotaxis to interaction with membrane-bound or intracellular receptors, thus providing novel strategies to overcome bacterial resistances. Especially, the clarification of the mechanisms and dynamics of AMP incorporation into bacterial membranes is of high interest, and different mechanistic models are still under discussion. In this work, we studied the incorporation of the peptaibol alamethicin (ALM) into tethered bilayer lipid membranes on electrodes in combination with surface-enhanced infrared absorption (SEIRA) spectroscopy. This approach allows monitoring the spontaneous and potential-induced ion channel formation of ALM in situ. The complex incorporation kinetics revealed a multistep mechanism that points to peptide-peptide interactions prior to penetrating the membrane and adopting the transmembrane configuration. On the basis of the anisotropy of the backbone amide I and II infrared absorptions determined by density functional theory calculations, we employed a mathematical model to evaluate ALM reorientations monitored by SEIRA spectroscopy. Accordingly, ALM was found to adopt inclination angles of ca. 69°-78° and 21° in its interfacially adsorbed and transmembrane incorporated states, respectively. These orientations can be stabilized efficiently by the dipolar interaction with lipid head groups or by the application of a potential gradient. The presented potential-controlled mechanistic study suggests an N-terminal integration of ALM into membranes as monomers or parallel oligomers to form ion channels composed of parallel-oriented helices, whereas antiparallel oligomers are barred from intrusion.

  13. Mechanistic modeling of aberrant energy metabolism in human disease

    Directory of Open Access Journals (Sweden)

    Vineet eSangar

    2012-10-01

    Full Text Available Dysfunction in energy metabolism—including in pathways localized to the mitochondria—has been implicated in the pathogenesis of a wide array of disorders, ranging from cancer to neurodegenerative diseases to type II diabetes. The inherent complexities of energy and mitochondrial metabolism present a significant obstacle in the effort to understand the role that these molecular processes play in the development of disease. To help unravel these complexities, systems biology methods have been applied to develop an array of computational metabolic models, ranging from mitochondria-specific processes to genome-scale cellular networks. These constraint-based models can efficiently simulate aspects of normal and aberrant metabolism in various genetic and environmental conditions. Development of these models leverages—and also provides a powerful means to integrate and interpret—information from a wide range of sources including genomics, proteomics, metabolomics, and enzyme kinetics. Here, we review a variety of mechanistic modeling studies that explore metabolic functions, deficiency disorders, and aberrant biochemical pathways in mitochondria and related regions in the cell.

  14. Mechanistic movement models to understand epidemic spread.

    Science.gov (United States)

    Fofana, Abdou Moutalab; Hurford, Amy

    2017-05-05

    An overlooked aspect of disease ecology is considering how and why animals come into contact with one and other resulting in disease transmission. Mathematical models of disease spread frequently assume mass-action transmission, justified by stating that susceptible and infectious hosts mix readily, and foregoing any detailed description of host movement. Numerous recent studies have recorded, analysed and modelled animal movement. These movement models describe how animals move with respect to resources, conspecifics and previous movement directions and have been used to understand the conditions for the occurrence and the spread of infectious diseases when hosts perform a type of movement. Here, we summarize the effect of the different types of movement on the threshold conditions for disease spread. We identify gaps in the literature and suggest several promising directions for future research. The mechanistic inclusion of movement in epidemic models may be beneficial for the following two reasons. Firstly, the estimation of the transmission coefficient in an epidemic model is possible because animal movement data can be used to estimate the rate of contacts between conspecifics. Secondly, unsuccessful transmission events, where a susceptible host contacts an infectious host but does not become infected can be quantified. Following an outbreak, this enables disease ecologists to identify 'near misses' and to explore possible alternative epidemic outcomes given shifts in ecological or immunological parameters.This article is part of the themed issue 'Opening the black box: re-examining the ecology and evolution of parasite transmission'. © 2017 The Author(s).

  15. Prediction of net hepatic release of glucose using a “hybrid” mechanistic model in ruminants applied to positive energy balance

    OpenAIRE

    Bahloul, Lahlou; Ortigues, Isabelle; Vernet, Jean; Lapierre, Helène; Noziere, Pierre; Sauvant, Daniel

    2013-01-01

    Ruminants depend on hepatic gluconeogenesis to meet most of their metabolic demand for glucose which relies on availability of precursors from diet supply and animal requirements (Loncke et al., 2010). Several mechanistic models of the metabolic fate of nutrients across the liver exist that have been parameterized for dairy cows. They cannot be directly used to predict hepatic gluconeogenesis in all types of ruminants in different physiological status. A hybrid mechanistic model of nutrient f...

  16. A mechanistic model for electricity consumption on dairy farms: Definition, validation, and demonstration

    OpenAIRE

    Upton, J.R.; Murphy, M.; Shallo, L.; Groot Koerkamp, P.W.G.; Boer, de, I.J.M.

    2014-01-01

    Our objective was to define and demonstrate a mechanistic model that enables dairy farmers to explore the impact of a technical or managerial innovation on electricity consumption, associated CO2 emissions, and electricity costs. We, therefore, (1) defined a model for electricity consumption on dairy farms (MECD) capable of simulating total electricity consumption along with related CO2 emissions and electricity costs on dairy farms on a monthly basis; (2) validated the MECD using empirical d...

  17. Mechanistic systems modeling to guide drug discovery and development.

    Science.gov (United States)

    Schmidt, Brian J; Papin, Jason A; Musante, Cynthia J

    2013-02-01

    A crucial question that must be addressed in the drug development process is whether the proposed therapeutic target will yield the desired effect in the clinical population. Pharmaceutical and biotechnology companies place a large investment on research and development, long before confirmatory data are available from human trials. Basic science has greatly expanded the computable knowledge of disease processes, both through the generation of large omics data sets and a compendium of studies assessing cellular and systemic responses to physiologic and pathophysiologic stimuli. Given inherent uncertainties in drug development, mechanistic systems models can better inform target selection and the decision process for advancing compounds through preclinical and clinical research. Copyright © 2012 Elsevier Ltd. All rights reserved.

  18. Refined pipe theory for mechanistic modeling of wood development.

    Science.gov (United States)

    Deckmyn, Gaby; Evans, Sam P; Randle, Tim J

    2006-06-01

    We present a mechanistic model of wood tissue development in response to changes in competition, management and climate. The model is based on a refinement of the pipe theory, where the constant ratio between sapwood and leaf area (pipe theory) is replaced by a ratio between pipe conductivity and leaf area. Simulated pipe conductivity changes with age, stand density and climate in response to changes in allocation or pipe radius, or both. The central equation of the model, which calculates the ratio of carbon (C) allocated to leaves and pipes, can be parameterized to describe the contrasting stem conductivity behavior of different tree species: from constant stem conductivity (functional homeostasis hypothesis) to height-related reduction in stem conductivity with age (hydraulic limitation hypothesis). The model simulates the daily growth of pipes (vessels or tracheids), fibers and parenchyma as well as vessel size and simulates the wood density profile and the earlywood to latewood ratio from these data. Initial runs indicate the model yields realistic seasonal changes in pipe radius (decreasing pipe radius from spring to autumn) and wood density, as well as realistic differences associated with the competitive status of trees (denser wood in suppressed trees).

  19. Mechanistic modeling analysis of micro-evolutive responses from a Caenorhabditis elegans population exposed to a radioactive metallic stress

    International Nuclear Information System (INIS)

    Goussen, Benoit

    2013-01-01

    The evolution of toxic effects at a relevant scale is an important challenge for the ecosystem protection. Indeed, pollutants may impact populations over long-term and represent a new evolutionary force which can be adding itself to the natural selection forces. Thereby, it is necessary to acquire knowledge on the phenotypics and genetics changes that may appear in populations submitted to stress over several generations. Usually statistical analyses are performed to analyse such multi-generational studies. The use of a mechanistic mathematical model may provide a way to fully understand the impact of pollutants on the populations' dynamics. Such kind of model allows the integration of biological and toxic processes into the analysis of eco-toxicological data and the assessment of interactions between these processes. The aim of this Ph.D. project was to assess the contributions of the mechanistic modelling to the analysis of evolutionary experiment assessing long-term exposure. To do so, a three step strategy has been developed. Foremost, a multi-generational study was performed to assess the evolution of two populations of the ubiquitous nematode Caenorhabditis elegans in control conditions or exposed to 1.1 mM of uranium. Several generations were selected to assess growth, reproduction, and dose-responses relationships, through exposure to a range of concentrations (from 0 to 1.2 mM U) with all endpoints measured daily. A first statistical analysis was then performed. In a second step, a bio-energetic model adapted to the assessment of eco-toxicological data (DEBtox) was developed on C. elegans. Its numerical behaviour was analysed. Finally, this model was applied to all the selected generations in order to infer parameters values for the two populations and to assess their evolutions. Results highlighted an impact of the uranium starting from 0.4 mM U on both C. elegans' growth and reproduction. Results from the mechanistic analysis indicate this effect is due

  20. Multiscale mechanistic modeling in pharmaceutical research and development.

    Science.gov (United States)

    Kuepfer, Lars; Lippert, Jörg; Eissing, Thomas

    2012-01-01

    Discontinuation of drug development projects due to lack of efficacy or adverse events is one of the main cost drivers in pharmaceutical research and development (R&D). Investments have to be written-off and contribute to the total costs of a successful drug candidate receiving marketing authorization and allowing return on invest. A vital risk for pharmaceutical innovator companies is late stage clinical failure since costs for individual clinical trials may exceed the one billion Euro threshold. To guide investment decisions and to safeguard maximum medical benefit and safety for patients recruited in clinical trials, it is therefore essential to understand the clinical consequences of all information and data generated. The complexity of the physiological and pathophysiological processes and the sheer amount of information available overcharge the mental capacity of any human being and prevent a prediction of the success in clinical development. A rigorous integration of knowledge, assumption, and experimental data into computational models promises a significant improvement of the rationalization of decision making in pharmaceutical industry. We here give an overview of the current status of modeling and simulation in pharmaceutical R&D and outline the perspectives of more recent developments in mechanistic modeling. Specific modeling approaches for different biological scales ranging from intracellular processes to whole organism physiology are introduced and an example for integrative multiscale modeling of therapeutic efficiency in clinical oncology trials is showcased.

  1. Improving the International Agency for Research on Cancer's consideration of mechanistic evidence

    International Nuclear Information System (INIS)

    Goodman, Julie; Lynch, Heather

    2017-01-01

    Background: The International Agency for Research on Cancer (IARC) recently developed a framework for evaluating mechanistic evidence that includes a list of 10 key characteristics of carcinogens. This framework is useful for identifying and organizing large bodies of literature on carcinogenic mechanisms, but it lacks sufficient guidance for conducting evaluations that fully integrate mechanistic evidence into hazard assessments. Objectives: We summarize the framework, and suggest approaches to strengthen the evaluation of mechanistic evidence using this framework. Discussion: While the framework is useful for organizing mechanistic evidence, its lack of guidance for implementation limits its utility for understanding human carcinogenic potential. Specifically, it does not include explicit guidance for evaluating the biological significance of mechanistic endpoints, inter- and intra-individual variability, or study quality and relevance. It also does not explicitly address how mechanistic evidence should be integrated with other realms of evidence. Because mechanistic evidence is critical to understanding human cancer hazards, we recommend that IARC develop transparent and systematic guidelines for the use of this framework so that mechanistic evidence will be evaluated and integrated in a robust manner, and concurrently with other realms of evidence, to reach a final human cancer hazard conclusion. Conclusions: IARC does not currently provide a standardized approach to evaluating mechanistic evidence. Incorporating the recommendations discussed here will make IARC analyses of mechanistic evidence more transparent, and lead to assessments of cancer hazards that reflect the weight of the scientific evidence and allow for scientifically defensible decision-making. - Highlights: • IARC has a revised framework for evaluating literature on carcinogenic mechanisms. • The framework is based on 10 key characteristics of carcinogens. • IARC should develop transparent

  2. Improving the International Agency for Research on Cancer's consideration of mechanistic evidence

    Energy Technology Data Exchange (ETDEWEB)

    Goodman, Julie, E-mail: jgoodman@gradientcorp.com; Lynch, Heather

    2017-03-15

    Background: The International Agency for Research on Cancer (IARC) recently developed a framework for evaluating mechanistic evidence that includes a list of 10 key characteristics of carcinogens. This framework is useful for identifying and organizing large bodies of literature on carcinogenic mechanisms, but it lacks sufficient guidance for conducting evaluations that fully integrate mechanistic evidence into hazard assessments. Objectives: We summarize the framework, and suggest approaches to strengthen the evaluation of mechanistic evidence using this framework. Discussion: While the framework is useful for organizing mechanistic evidence, its lack of guidance for implementation limits its utility for understanding human carcinogenic potential. Specifically, it does not include explicit guidance for evaluating the biological significance of mechanistic endpoints, inter- and intra-individual variability, or study quality and relevance. It also does not explicitly address how mechanistic evidence should be integrated with other realms of evidence. Because mechanistic evidence is critical to understanding human cancer hazards, we recommend that IARC develop transparent and systematic guidelines for the use of this framework so that mechanistic evidence will be evaluated and integrated in a robust manner, and concurrently with other realms of evidence, to reach a final human cancer hazard conclusion. Conclusions: IARC does not currently provide a standardized approach to evaluating mechanistic evidence. Incorporating the recommendations discussed here will make IARC analyses of mechanistic evidence more transparent, and lead to assessments of cancer hazards that reflect the weight of the scientific evidence and allow for scientifically defensible decision-making. - Highlights: • IARC has a revised framework for evaluating literature on carcinogenic mechanisms. • The framework is based on 10 key characteristics of carcinogens. • IARC should develop transparent

  3. Development of a mechanistic model for release of radionuclides from spent fuel in brines: Salt Repository Project

    International Nuclear Information System (INIS)

    Reimus, P.W.; Windisch, C.F.

    1988-03-01

    At present there are no comprehensive mechanistic models describing the release of radionuclides from spent fuel in brine environments. This report provides a comprehensive review of the various factors that can affect radionuclide release from spent fuel, suggests a modeling approach, and discusses proposed experiments for obtaining a better mechanistic understanding of the radionuclide release processes. Factors affecting radionuclide release include the amount, location, and disposition of radionuclides in the fuel and environmental factors such as redox potential, pH, the presence of complexing anions, temperature, and radiolysis. It is concluded that a model describing the release of radionuclides from spent fuel should contain separate terms for release from the gap, grain boundaries, and grains of the fuel. Possible functional forms for these terms are discussed in the report. Experiments for assessing their validity and obtaining key model parameters are proposed. 71 refs., 4 figs., 6 tabs

  4. Mechanistic Modeling of Water Replenishment Rate of Zeer Refrigerator

    Directory of Open Access Journals (Sweden)

    B. N. Nwankwojike

    2017-06-01

    Full Text Available A model for predicting the water replenishment rate of zeer pot refrigerator was developed in this study using mechanistic modeling approach and evaluated at Obowo, Imo State, Nigeria using six fruits, tomatoes, guava, okra, banana, orange and avocado pear. The developed model confirmed zeer pot water replenishment rate as a function of ambient temperature, relative humidity, wind speed, thermal conductivity of the pot materials and sand, density of air and water vapor, permeability coefficient of clay and heat transfer coefficient of water into air, circumferential length, height of pot, geometrical profile of the pot, heat load of the food preserved, heat flow into the device and gradient at which the pot is placed above ground level. Compared to the conventional approach of water replenishment, performance analysis results revealed 44% to 58% water economy when the zeer pot’s water was replenished based on the model’s prediction; while there was no significant difference in the shelf-life of the fruits preserved with both replenishment methods. Application of the developed water replenishment model facilitates optimal water usage in this system, thereby reducing operational cost of zeer pot refrigerator.

  5. Growth and lipid production of Umbelopsis isabellina on a solid substrate - Mechanistic modeling and validation

    NARCIS (Netherlands)

    Meeuwse, P.; Klok, A.J.; Haemers, S.; Tramper, J.; Rinzema, A.

    2012-01-01

    Microbial lipids are an interesting feedstock for biodiesel. Their production from agricultural waste streams by fungi cultivated in solid-state fermentation may be attractive, but the yield of this process is still quite low. In this article, a mechanistic model is presented that describes growth,

  6. Phenomenological and mechanistic modeling of melt-structure-water interactions in a light water reactor severe accident

    International Nuclear Information System (INIS)

    Bui, V.A.

    1998-01-01

    The objective of this work is to address the modeling of the thermal hydrodynamic phenomena and interactions occurring during the progression of reactor severe accidents. Integrated phenomenological models are developed to describe the accident scenarios, which consist of many processes, while mechanistic modeling, including direct numerical simulation, is carried out to describe separate effects and selected physical phenomena of particular importance

  7. PROPOSED SUITE OF MODELS FOR ESTIMATING DOSE RESULTING FROM EXPOSURES BY THE DERMAL ROUTE

    Science.gov (United States)

    Recent risk assessment guidance emphasizes consideration of mechanistic factors for influencing disposition of a toxicant. To incorporate mechanistic information into risk assessment, a suite of models is proposed for use in characterizing and quantifying dosimetry of toxic age...

  8. Rapid Discrimination Among Putative Mechanistic Models of Biochemical Systems.

    Science.gov (United States)

    Lomnitz, Jason G; Savageau, Michael A

    2016-08-31

    An overarching goal in molecular biology is to gain an understanding of the mechanistic basis underlying biochemical systems. Success is critical if we are to predict effectively the outcome of drug treatments and the development of abnormal phenotypes. However, data from most experimental studies is typically noisy and sparse. This allows multiple potential mechanisms to account for experimental observations, and often devising experiments to test each is not feasible. Here, we introduce a novel strategy that discriminates among putative models based on their repertoire of qualitatively distinct phenotypes, without relying on knowledge of specific values for rate constants and binding constants. As an illustration, we apply this strategy to two synthetic gene circuits exhibiting anomalous behaviors. Our results show that the conventional models, based on their well-characterized components, cannot account for the experimental observations. We examine a total of 40 alternative hypotheses and show that only 5 have the potential to reproduce the experimental data, and one can do so with biologically relevant parameter values.

  9. BIOMAP A Daily Time Step, Mechanistic Model for the Study of Ecosystem Dynamics

    Science.gov (United States)

    Wells, J. R.; Neilson, R. P.; Drapek, R. J.; Pitts, B. S.

    2010-12-01

    BIOMAP simulates competition between two Plant Functional Types (PFT) at any given point in the conterminous U.S. using a time series of daily temperature (mean, minimum, maximum), precipitation, humidity, light and nutrients, with PFT-specific rooting within a multi-layer soil. The model employs a 2-layer canopy biophysics, Farquhar photosynthesis, the Beer-Lambert Law for light attenuation and a mechanistic soil hydrology. In essence, BIOMAP is a re-built version of the biogeochemistry model, BIOME-BGC, into the form of the MAPSS biogeography model. Specific enhancements are: 1) the 2-layer canopy biophysics of Dolman (1993); 2) the unique MAPSS-based hydrology, which incorporates canopy evaporation, snow dynamics, infiltration and saturated and unsaturated percolation with ‘fast’ flow and base flow and a ‘tunable aquifer’ capacity, a metaphor of D’Arcy’s Law; and, 3) a unique MAPSS-based stomatal conductance algorithm, which simultaneously incorporates vapor pressure and soil water potential constraints, based on physiological information and many other improvements. Over small domains the PFTs can be parameterized as individual species to investigate fundamental vs. potential niche theory; while, at more coarse scales the PFTs can be rendered as more general functional groups. Since all of the model processes are intrinsically leaf to plot scale (physiology to PFT competition), it essentially has no ‘intrinsic’ scale and can be implemented on a grid of any size, taking on the characteristics defined by the homogeneous climate of each grid cell. Currently, the model is implemented on the VEMAP 1/2 degree, daily grid over the conterminous U.S. Although both the thermal and water-limited ecotones are dynamic, following climate variability, the PFT distributions remain fixed. Thus, the model is currently being fitted with a ‘reproduction niche’ to allow full dynamic operation as a Dynamic General Vegetation Model (DGVM). While global simulations

  10. Mechanistic modelling of the corrosion behaviour of copper nuclear fuel waste containers

    Energy Technology Data Exchange (ETDEWEB)

    King, F; Kolar, M

    1996-10-01

    A mechanistic model has been developed to predict the long-term corrosion behaviour of copper nuclear fuel waste containers in a Canadian disposal vault. The model is based on a detailed description of the electrochemical, chemical, adsorption and mass-transport processes involved in the uniform corrosion of copper, developed from the results of an extensive experimental program. Predictions from the model are compared with the results of some of these experiments and with observations from a bronze cannon submerged in seawater saturated clay sediments. Quantitative comparisons are made between the observed and predicted corrosion potential, corrosion rate and copper concentration profiles adjacent to the corroding surface, as a way of validating the long-term model predictions. (author). 12 refs., 5 figs.

  11. Productivity of "collisions generate heat" for reconciling an energy model with mechanistic reasoning: A case study

    Science.gov (United States)

    Scherr, Rachel E.; Robertson, Amy D.

    2015-06-01

    We observe teachers in professional development courses about energy constructing mechanistic accounts of energy transformations. We analyze a case in which teachers investigating adiabatic compression develop a model of the transformation of kinetic energy to thermal energy. Among their ideas is the idea that thermal energy is generated as a byproduct of individual particle collisions, which is represented in science education research literature as an obstacle to learning. We demonstrate that in this instructional context, the idea that individual particle collisions generate thermal energy is not an obstacle to learning, but instead is productive: it initiates intellectual progress. Specifically, this idea initiates the reconciliation of the teachers' energy model with mechanistic reasoning about adiabatic compression, and leads to a canonically correct model of the transformation of kinetic energy into thermal energy. We claim that the idea's productivity is influenced by features of our particular instructional context, including the instructional goals of the course, the culture of collaborative sense making, and the use of certain representations of energy.

  12. Mechanistic modeling of insecticide risks to breeding birds in ...

    Science.gov (United States)

    Insecticide usage in the United States is ubiquitous in urban, suburban, and rural environments. In evaluating data for an insecticide registration application and for registration review, scientists at the United States Environmental Protection Agency (USEPA) assess the fate of the insecticide and the risk the insecticide poses to the environment and non-target wildlife. At the present time, current USEPA risk assessments do not include population-level endpoints. In this paper, we present a new mechanistic model, which allows risk assessors to estimate the effects of insecticide exposure on the survival and seasonal productivity of birds known to use agricultural fields during their breeding season. The new model was created from two existing USEPA avian risk assessment models, the Terrestrial Investigation Model (TIM v.3.0) and the Markov Chain Nest Productivity model (MCnest). The integrated TIM/MCnest model has been applied to assess the relative risk of 12 insecticides used to control corn pests on a suite of 31 avian species known to use cornfields in midwestern agroecosystems. The 12 insecticides that were assessed in this study are all used to treat major pests of corn (corn root worm borer, cutworm, and armyworm). After running the integrated TIM/MCnest model, we found extensive differences in risk to birds among insecticides, with chlorpyrifos and malathion (organophosphates) generally posing the greatest risk, and bifenthrin and ë-cyhalothrin (

  13. Mutual Dependence Between Sedimentary Organic Carbon and Infaunal Macrobenthos Resolved by Mechanistic Modeling

    Science.gov (United States)

    Zhang, Wenyan; Wirtz, Kai

    2017-10-01

    The mutual dependence between sedimentary total organic carbon (TOC) and infaunal macrobenthos is here quantified by a mechanistic model. The model describes (i) the vertical distribution of infaunal macrobenthic biomass resulting from a trade-off between nutritional benefit (quantity and quality of TOC) and the costs of burial (respiration) and mortality, and (ii) the variable vertical distribution of TOC being in turn shaped by bioturbation of local macrobenthos. In contrast to conventional approaches, our model emphasizes variations of bioturbation both spatially and temporally depending on local food resources and macrobenthic biomass. Our implementation of the dynamic interaction between TOC and infaunal macrobenthos is able to capture a temporal benthic response to both depositional and erosional environments and provides improved estimates of the material exchange flux at the sediment-water interface. Applications to literature data for the North Sea demonstrate the robustness and accuracy of the model and its potential as an analysis tool for the status of TOC and macrobenthos in marine sediments. Results indicate that the vertical distribution of infaunal biomass is shaped by both the quantity and the quality of OC, while the community structure is determined only by the quality of OC. Bioturbation intensity may differ by 1 order of magnitude over different seasons owing to variations in the OC input, resulting in a significant modulation on the distribution of OC. Our relatively simple implementation may further improve models of early diagenesis and marine food web dynamics by mechanistically connecting the vertical distribution of both TOC and macrobenthic biomass.

  14. Proceedings of the international workshop on mechanistic understanding of radionuclide migration in compacted/intact systems

    International Nuclear Information System (INIS)

    Tachi, Yukio; Yui, Mikazu

    2010-03-01

    The international workshop on mechanistic understanding of radionuclide migration in compacted / intact systems was held at ENTRY, JAEA, Tokai on 21st - 23rd January, 2009. This workshop was hosted by Japan Atomic Energy Agency (JAEA) as part of the project on the mechanistic model/database development for radionuclide sorption and diffusion behavior in compacted / intact systems. The overall goal of the project is to develop the mechanistic model / database for a consistent understanding and prediction of migration parameters and its uncertainties for performance assessment of geological disposal of radioactive waste. The objective of the workshop is to integrate the state-of-the-art of mechanistic sorption and diffusion model in compacted / intact systems, especially in bentonite / clay systems, and discuss the JAEA's mechanistic approaches and future challenges, especially the following discussions points; 1) What's the status and difficulties for mechanistic model/database development? 2) What's the status and difficulties for applicability of mechanistic model to the compacted/intact system? 3) What's the status and difficulties for obtaining evidences for mechanistic model? 4) What's the status and difficulties for standardization of experimental methodology for batch sorption and diffusion? 5) What's the uncertainties of transport parameters in radionuclides migration analysis due to a lack of understanding/experimental methodologies, and how do we derive them? This report includes workshop program, overview and materials of each presentation, summary of discussions. (author)

  15. Phenomenological and mechanistic modeling of melt-structure-water interactions in a light water reactor severe accident

    Energy Technology Data Exchange (ETDEWEB)

    Bui, V.A

    1998-10-01

    The objective of this work is to address the modeling of the thermal hydrodynamic phenomena and interactions occurring during the progression of reactor severe accidents. Integrated phenomenological models are developed to describe the accident scenarios, which consist of many processes, while mechanistic modeling, including direct numerical simulation, is carried out to describe separate effects and selected physical phenomena of particular importance 88 refs, 54 figs, 7 tabs

  16. Linking spring phenology with mechanistic models of host movement to predict disease transmission risk

    Science.gov (United States)

    Merkle, Jerod A.; Cross, Paul C.; Scurlock, Brandon M.; Cole, Eric K.; Courtemanch, Alyson B.; Dewey, Sarah R.; Kauffman, Matthew J.

    2018-01-01

    Disease models typically focus on temporal dynamics of infection, while often neglecting environmental processes that determine host movement. In many systems, however, temporal disease dynamics may be slow compared to the scale at which environmental conditions alter host space-use and accelerate disease transmission.Using a mechanistic movement modelling approach, we made space-use predictions of a mobile host (elk [Cervus Canadensis] carrying the bacterial disease brucellosis) under environmental conditions that change daily and annually (e.g., plant phenology, snow depth), and we used these predictions to infer how spring phenology influences the risk of brucellosis transmission from elk (through aborted foetuses) to livestock in the Greater Yellowstone Ecosystem.Using data from 288 female elk monitored with GPS collars, we fit step selection functions (SSFs) during the spring abortion season and then implemented a master equation approach to translate SSFs into predictions of daily elk distribution for five plausible winter weather scenarios (from a heavy snow, to an extreme winter drought year). We predicted abortion events by combining elk distributions with empirical estimates of daily abortion rates, spatially varying elk seroprevelance and elk population counts.Our results reveal strong spatial variation in disease transmission risk at daily and annual scales that is strongly governed by variation in host movement in response to spring phenology. For example, in comparison with an average snow year, years with early snowmelt are predicted to have 64% of the abortions occurring on feedgrounds shift to occurring on mainly public lands, and to a lesser extent on private lands.Synthesis and applications. Linking mechanistic models of host movement with disease dynamics leads to a novel bridge between movement and disease ecology. Our analysis framework offers new avenues for predicting disease spread, while providing managers tools to proactively mitigate

  17. Incorporating parametric uncertainty into population viability analysis models

    Science.gov (United States)

    McGowan, Conor P.; Runge, Michael C.; Larson, Michael A.

    2011-01-01

    Uncertainty in parameter estimates from sampling variation or expert judgment can introduce substantial uncertainty into ecological predictions based on those estimates. However, in standard population viability analyses, one of the most widely used tools for managing plant, fish and wildlife populations, parametric uncertainty is often ignored in or discarded from model projections. We present a method for explicitly incorporating this source of uncertainty into population models to fully account for risk in management and decision contexts. Our method involves a two-step simulation process where parametric uncertainty is incorporated into the replication loop of the model and temporal variance is incorporated into the loop for time steps in the model. Using the piping plover, a federally threatened shorebird in the USA and Canada, as an example, we compare abundance projections and extinction probabilities from simulations that exclude and include parametric uncertainty. Although final abundance was very low for all sets of simulations, estimated extinction risk was much greater for the simulation that incorporated parametric uncertainty in the replication loop. Decisions about species conservation (e.g., listing, delisting, and jeopardy) might differ greatly depending on the treatment of parametric uncertainty in population models.

  18. Unification and mechanistic detail as drivers of model construction: models of networks in economics and sociology.

    Science.gov (United States)

    Kuorikoski, Jaakko; Marchionni, Caterina

    2014-12-01

    We examine the diversity of strategies of modelling networks in (micro) economics and (analytical) sociology. Field-specific conceptions of what explaining (with) networks amounts to or systematic preference for certain kinds of explanatory factors are not sufficient to account for differences in modelling methodologies. We argue that network models in both sociology and economics are abstract models of network mechanisms and that differences in their modelling strategies derive to a large extent from field-specific conceptions of the way in which a good model should be a general one. Whereas the economics models aim at unification, the sociological models aim at a set of mechanism schemas that are extrapolatable to the extent that the underlying psychological mechanisms are general. These conceptions of generality induce specific biases in mechanistic explanation and are related to different views of when knowledge from different fields should be seen as relevant.

  19. WE-H-BRA-07: Mechanistic Modelling of the Relative Biological Effectiveness of Heavy Charged Particles

    Energy Technology Data Exchange (ETDEWEB)

    McMahon, S [Massachusetts General Hospital, Boston, MA (United States); Queen’s University, Belfast, Belfast (United Kingdom); McNamara, A; Schuemann, J; Paganetti, H [Massachusetts General Hospital, Boston, MA (United States); Prise, K [Queen’s University, Belfast, Belfast (United Kingdom)

    2016-06-15

    Purpose Uncertainty in the Relative Biological Effectiveness (RBE) of heavy charged particles compared to photons remains one of the major uncertainties in particle therapy. As RBEs depend strongly on clinical variables such as tissue type, dose, and radiation quality, more accurate individualised models are needed to fully optimise treatments. MethodsWe have developed a model of DNA damage and repair following X-ray irradiation in a number of settings, incorporating mechanistic descriptions of DNA repair pathways, geometric effects on DNA repair, cell cycle effects and cell death. Our model has previously been shown to accurately predict a range of biological endpoints including chromosome aberrations, mutations, and cell death. This model was combined with nanodosimetric models of individual ion tracks to calculate the additional probability of lethal damage forming within a single track. These lethal damage probabilities can be used to predict survival and RBE for cells irradiated with ions of different Linear Energy Transfer (LET). ResultsBy combining the X-ray response model with nanodosimetry information, predictions of RBE can be made without cell-line specific fitting. The model’s RBE predictions were found to agree well with empirical proton RBE models (Mean absolute difference between models of 1.9% and 1.8% for cells with α/β ratios of 9 and 1.4, respectively, for LETs between 0 and 15 keV/µm). The model also accurately recovers the impact of high-LET carbon ion exposures, showing both the reduced efficacy of ions at extremely high LET, as well as the impact of defects in non-homologous end joining on RBE values in Chinese Hamster Ovary cells.ConclusionOur model is predicts RBE without the inclusion of empirical LET fitting parameters for a range of experimental conditions. This approach has the potential to deliver improved personalisation of particle therapy, with future developments allowing for the calculation of individualised RBEs. SJM is

  20. Experimental investigation and mechanistic modelling of dilute bubbly bulk boiling

    International Nuclear Information System (INIS)

    Kutnjak, Josip

    2013-01-01

    During evaporation the geometric shape of the vapour is not described using thermodynamics. In bubbly flows the bubble shape is considered spheric with small diameters and changing into various shapes upon growth. The heat and mass transfer happens at the interfacial area. The forces acting on the bubbles depend on the bubble diameter and shape. In this work the prediction of the bubble diameter and/or bubble number density in bulk boiling was considered outside the vicinity of the heat input area. Thus the boiling effects that happened inside the nearly saturated bulk were under investigation. This situation is relevant for nuclear safety analysis concerning a stagnant coolant in the spent fuel pool. In this research project a new experimental set-up to investigate was built. The experimental set-up consists of an instrumented, partly transparent, high and slender boiling container for visual observation. The direct visual observation of the boiling phenomena is necessary for the identification of basic mechanisms, which should be incorporated in the simulation model. The boiling process has been recorded by means of video images and subsequently was evaluated by digital image processing methods, and by that data concerning the characteristics of the boiling process were generated for the model development and validation. Mechanistic modelling is based on the derivation of relevant mechanisms concluded from observation, which is in line with physical knowledge. In this context two mechanisms were identified; the growth/-shrink mechanism (GSM) of the vapour bubbles and sudden increases of the bubble number density. The GSM was implemented into the CFD-Code ANSYS-CFX using the CFX Expression Language (CEL) by calculation of the internal bubble pressure using the Young-Laplace-Equation. This way a hysteresis is realised as smaller bubbles have an increased internal pressure. The sudden increases of the bubble number density are explainable by liquid super

  1. Experimental investigation and mechanistic modelling of dilute bubbly bulk boiling

    Energy Technology Data Exchange (ETDEWEB)

    Kutnjak, Josip

    2013-06-27

    During evaporation the geometric shape of the vapour is not described using thermodynamics. In bubbly flows the bubble shape is considered spheric with small diameters and changing into various shapes upon growth. The heat and mass transfer happens at the interfacial area. The forces acting on the bubbles depend on the bubble diameter and shape. In this work the prediction of the bubble diameter and/or bubble number density in bulk boiling was considered outside the vicinity of the heat input area. Thus the boiling effects that happened inside the nearly saturated bulk were under investigation. This situation is relevant for nuclear safety analysis concerning a stagnant coolant in the spent fuel pool. In this research project a new experimental set-up to investigate was built. The experimental set-up consists of an instrumented, partly transparent, high and slender boiling container for visual observation. The direct visual observation of the boiling phenomena is necessary for the identification of basic mechanisms, which should be incorporated in the simulation model. The boiling process has been recorded by means of video images and subsequently was evaluated by digital image processing methods, and by that data concerning the characteristics of the boiling process were generated for the model development and validation. Mechanistic modelling is based on the derivation of relevant mechanisms concluded from observation, which is in line with physical knowledge. In this context two mechanisms were identified; the growth/-shrink mechanism (GSM) of the vapour bubbles and sudden increases of the bubble number density. The GSM was implemented into the CFD-Code ANSYS-CFX using the CFX Expression Language (CEL) by calculation of the internal bubble pressure using the Young-Laplace-Equation. This way a hysteresis is realised as smaller bubbles have an increased internal pressure. The sudden increases of the bubble number density are explainable by liquid super

  2. Higher plant modelling for life support applications: first results of a simple mechanistic model

    Science.gov (United States)

    Hezard, Pauline; Dussap, Claude-Gilles; Sasidharan L, Swathy

    2012-07-01

    In the case of closed ecological life support systems, the air and water regeneration and food production are performed using microorganisms and higher plants. Wheat, rice, soybean, lettuce, tomato or other types of eatable annual plants produce fresh food while recycling CO2 into breathable oxygen. Additionally, they evaporate a large quantity of water, which can be condensed and used as potable water. This shows that recycling functions of air revitalization and food production are completely linked. Consequently, the control of a growth chamber for higher plant production has to be performed with efficient mechanistic models, in order to ensure a realistic prediction of plant behaviour, water and gas recycling whatever the environmental conditions. Purely mechanistic models of plant production in controlled environments are not available yet. This is the reason why new models must be developed and validated. This work concerns the design and test of a simplified version of a mathematical model coupling plant architecture and mass balance purposes in order to compare its results with available data of lettuce grown in closed and controlled chambers. The carbon exchange rate, water absorption and evaporation rate, biomass fresh weight as well as leaf surface are modelled and compared with available data. The model consists of four modules. The first one evaluates plant architecture, like total leaf surface, leaf area index and stem length data. The second one calculates the rate of matter and energy exchange depending on architectural and environmental data: light absorption in the canopy, CO2 uptake or release, water uptake and evapotranspiration. The third module evaluates which of the previous rates is limiting overall biomass growth; and the last one calculates biomass growth rate depending on matter exchange rates, using a global stoichiometric equation. All these rates are a set of differential equations, which are integrated with time in order to provide

  3. A mechanistic nitrogen limitation model for CLM(ED)

    Science.gov (United States)

    Ali, A. A.; Xu, C.; McDowell, N. G.; Rogers, A.; Wullschleger, S. D.; Fisher, R.; Vrugt, J. A.

    2014-12-01

    Photosynthetic capacity is a key plant trait that determines the rate of photosynthesis; however, in Earth System Models it is either a fixed value or derived from a linear function of leaf nitrogen content. A mechanistic leaf nitrogen allocation model have been developed for a DOE-sponsored Community Land Model coupled to the Ecosystem Demography model (CLM-ED) to predict the photosynthetic capacity [Vc,max25 (μmol CO2 m-2 s-1)] under different environmental conditions at the global scale. We collected more than 800 data points of photosynthetic capacity (Vc,max25) for 124 species from 57 studies with the corresponding leaf nitrogen content and environmental conditions (temperature, radiation, humidity and day length) from literature and the NGEE arctic site (Barrow). Based on the data, we found that environmental control of Vc,max25 is about 4 times stronger than the leaf nitrogen content. Using the Markov-Chain Monte Carlo simulation approach, we fitted the collected data to our newly developed nitrogen allocation model, which predict the leaf nitrogen investment in different components including structure, storage, respiration, light capture, carboxylation and electron transport at different environmental conditions. Our results showed that our nitrogen allocation model explained 52% of variance in observed Vc,max25 and 65% variance in observed Jmax25 using a single set of fitted model parameters for all species. Across the growing season, we found that the modeled Vc,max25 explained 49% of the variability in measured Vc,max25. In the context of future global warming, our model predicts that a temperature increase by 5oC and the doubling of atmospheric carbon dioxide reduced the Vc,max25 by 5%, 11%, respectively.

  4. A dynamic, mechanistic model of metabolism in adipose tissue of lactating dairy cattle.

    Science.gov (United States)

    McNamara, J P; Huber, K; Kenéz, A

    2016-07-01

    Research in dairy cattle biology has resulted in a large body of knowledge on nutrition and metabolism in support of milk production and efficiency. This quantitative knowledge has been compiled in several model systems to balance and evaluate rations and predict requirements. There are also systems models for metabolism and reproduction in the cow that can be used to support research programs. Adipose tissue plays a significant role in the success and efficiency of lactation, and recent research has resulted in several data sets on genomic differences and changes in gene transcription of adipose tissue in dairy cattle. To fully use this knowledge, we need to build and expand mechanistic, dynamic models that integrate control of metabolism and production. Therefore, we constructed a second-generation dynamic, mechanistic model of adipose tissue metabolism of dairy cattle. The model describes the biochemical interconversions of glucose, acetate, β-hydroxybutyrate (BHB), glycerol, C16 fatty acids, and triacylglycerols. Data gathered from our own research and published references were used to set equation forms and parameter values. Acetate, glucose, BHB, and fatty acids are taken up from blood. The fatty acids are activated to the acyl coenzyme A moieties. Enzymatically catalyzed reactions are explicitly described with parameters including maximal velocity and substrate sensitivity. The control of enzyme activity is partially carried out by insulin and norepinephrine, portraying control in the cow. Model behavior was adequate, with sensitive responses to changing substrates and hormones. Increased nutrient uptake and increased insulin stimulate triacylglycerol synthesis, whereas a reduction in nutrient availability or increase in norepinephrine increases triacylglycerol hydrolysis and free fatty acid release to blood. This model can form a basis for more sophisticated integration of existing knowledge and future studies on metabolic efficiency of dairy cattle

  5. Incorporation of FcRn-mediated disposition model to describe the population pharmacokinetics of therapeutic monoclonal IgG antibody in clinical patients.

    Science.gov (United States)

    Ng, Chee M

    2016-03-01

    The two-compartment linear model used to describe the population pharmacokinetics (PK) of many therapeutic monoclonal antibodies (TMAbs) offered little biological insight to antibody disposition in humans. The purpose of this study is to develop a semi-mechanistic FcRn-mediated IgG disposition model to describe the population PK of TMAbs in clinical patients. A standard two-compartment linear PK model from a previously published population PK model of pertuzumab was used to simulate intensive PK data of 100 subjects for model development. Two different semi-mechanistic FcRn-mediated IgG disposition models were developed and First Order Conditional Estimation (FOCE) with the interaction method in NONMEM was used to obtain the final model estimates. The performances of these models were then compared with the two-compartment linear PK model used to simulate the data for model development. A semi-mechanistic FcRn-mediated IgG disposition model consisting of a peripheral tissue compartment and FcRn-containing endosomes in the central compartment best describes the simulated pertuzumab population PK data. This developed semi-mechanistic population PK model had the same number of model parameters, produced very similar concentration-time profiles but provided additional biological insight to the FcRn-mediated IgG disposition in human subjects compared with the standard linear two-compartment linear PK model. This first reported semi-mechanistic model may serve as an important model framework for developing future population PK models of TMAbs in clinical patients. Copyright © 2015 John Wiley & Sons, Ltd.

  6. Comparative ecophysiology of two sympatric lizards. Laying the groundwork for mechanistic distribution models

    Directory of Open Access Journals (Sweden)

    Enrique García-Muñoz

    2013-12-01

    Full Text Available Distribution modelling usually makes inferences correlating species presence and environmental variables but does not take biotic relations into account. Alternative approaches based on a mechanistic understanding of biological processes are now being applied. Regarding lacertid lizards, physiological traits such as preferred body temperature (Tp are well known to correlate with several physiological optima. Much less is known about their water ecology although body temperature and evaporative water loss (Wl may trade-off. Two saxicolous lacertids, Algyroides marchi and Podarcis hispanica ss are sympatric in the Subbetic Mountains (SE Spain were they can be found in syntopy. Previous distribution modelling indicates the first species is associated with mountains, low temperatures; high precipitation and forest cover whereas the second one is more generalistic. Here, we perform two ecophysiological tests with both species: a Tp experiment in thermal gradient and a Wl experiment in sealed chambers. Although both species attained similar body temperatures, A. marchi lost more water and more uniformly in time than P. hispanica ss that displayed an apparent response to dehydration. These results suggest that water loss rather temperature is crucial to explain the distribution patterns of A. marchi in relation to P. hispanica ss, the former risking dehydration in dry areas no matter what temperature is. Ecophysiological traits represent a promising tool to build future mechanistic models for (lacertid lizards. Additionally, the implications for their biogeography and conservation are discussed.

  7. Mechanistic kinetic models of enzymatic cellulose hydrolysis-A review.

    Science.gov (United States)

    Jeoh, Tina; Cardona, Maria J; Karuna, Nardrapee; Mudinoor, Akshata R; Nill, Jennifer

    2017-07-01

    Bioconversion of lignocellulose forms the basis for renewable, advanced biofuels, and bioproducts. Mechanisms of hydrolysis of cellulose by cellulases have been actively studied for nearly 70 years with significant gains in understanding of the cellulolytic enzymes. Yet, a full mechanistic understanding of the hydrolysis reaction has been elusive. We present a review to highlight new insights gained since the most recent comprehensive review of cellulose hydrolysis kinetic models by Bansal et al. (2009) Biotechnol Adv 27:833-848. Recent models have taken a two-pronged approach to tackle the challenge of modeling the complex heterogeneous reaction-an enzyme-centric modeling approach centered on the molecularity of the cellulase-cellulose interactions to examine rate limiting elementary steps and a substrate-centric modeling approach aimed at capturing the limiting property of the insoluble cellulose substrate. Collectively, modeling results suggest that at the molecular-scale, how rapidly cellulases can bind productively (complexation) and release from cellulose (decomplexation) is limiting, while the overall hydrolysis rate is largely insensitive to the catalytic rate constant. The surface area of the insoluble substrate and the degrees of polymerization of the cellulose molecules in the reaction both limit initial hydrolysis rates only. Neither enzyme-centric models nor substrate-centric models can consistently capture hydrolysis time course at extended reaction times. Thus, questions of the true reaction limiting factors at extended reaction times and the role of complexation and decomplexation in rate limitation remain unresolved. Biotechnol. Bioeng. 2017;114: 1369-1385. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  8. Incorporating groundwater flow into the WEPP model

    Science.gov (United States)

    William Elliot; Erin Brooks; Tim Link; Sue Miller

    2010-01-01

    The water erosion prediction project (WEPP) model is a physically-based hydrology and erosion model. In recent years, the hydrology prediction within the model has been improved for forest watershed modeling by incorporating shallow lateral flow into watershed runoff prediction. This has greatly improved WEPP's hydrologic performance on small watersheds with...

  9. Productivity of "Collisions Generate Heat" for Reconciling an Energy Model with Mechanistic Reasoning: A Case Study

    Science.gov (United States)

    Scherr, Rachel E.; Robertson, Amy D.

    2015-01-01

    We observe teachers in professional development courses about energy constructing mechanistic accounts of energy transformations. We analyze a case in which teachers investigating adiabatic compression develop a model of the transformation of kinetic energy to thermal energy. Among their ideas is the idea that thermal energy is generated as a…

  10. Fetal programming of CVD and renal disease: animal models and mechanistic considerations.

    Science.gov (United States)

    Langley-Evans, Simon C

    2013-08-01

    The developmental origins of health and disease hypothesis postulates that exposure to a less than optimal maternal environment during fetal development programmes physiological function, and determines risk of disease in adult life. Much evidence of such programming comes from retrospective epidemiological cohorts, which demonstrate associations between birth anthropometry and non-communicable diseases of adulthood. The assertion that variation in maternal nutrition drives these associations is supported by studies using animal models, which demonstrate that maternal under- or over-nutrition during pregnancy can programme offspring development. Typically, the offspring of animals that are undernourished in pregnancy exhibit a relatively narrow range of physiological phenotypes that includes higher blood pressure, glucose intolerance, renal insufficiency and increased adiposity. The observation that common phenotypes arise from very diverse maternal nutritional insults has led to the proposal that programming is driven by a small number of mechanistic processes. The remodelling of tissues during development as a consequence of maternal nutritional status being signalled by endocrine imbalance or key nutrients limiting processes in the fetus may lead to organs having irreversibly altered structures that may limit their function with ageing. It has been proposed that the maternal diet may impact upon epigenetic marks that determine gene expression in fetal tissues, and this may be an important mechanism connecting maternal nutrient intakes to long-term programming of offspring phenotype. The objective for this review is to provide an overview of the mechanistic basis of fetal programming, demonstrating the critical role of animal models as tools for the investigation of programming phenomena.

  11. Improving the prediction of methane production and representation of rumen fermentation for finishing beef cattle within a mechanistic model

    NARCIS (Netherlands)

    Ellis, J.L.; Dijkstra, J.; Bannink, A.; Kebreab, E.; Archibeque, S.; Benchaar, C.; Beauchemin, K.; Nkrumah, D.J.; France, J.

    2014-01-01

    The purpose of this study was to evaluate prediction of methane emissions from finishing beef cattle using an extant mechanistic model with pH-independent or pH-dependent VFA stoichiometries, a recent stoichiometry adjustment for the use of monensin, and adaptation of the underlying model structure,

  12. Development of a mechanistic model for prediction of CO2 capture from gas mixtures by amine solutions in porous membranes.

    Science.gov (United States)

    Ghadiri, Mehdi; Marjani, Azam; Shirazian, Saeed

    2017-06-01

    A mechanistic model was developed in order to predict capture and removal of CO 2 from air using membrane technology. The considered membrane was a hollow-fiber contactor module in which gas mixture containing CO 2 was assumed as feed while 2-amino-2-metyl-1-propanol (AMP) was used as an absorbent. The mechanistic model was developed according to transport phenomena taking into account mass transfer and chemical reaction between CO 2 and amine in the contactor module. The main aim of modeling was to track the composition and flux of CO 2 and AMP in the membrane module for process optimization. For modeling of the process, the governing equations were computed using finite element approach in which the whole model domain was discretized into small cells. To confirm the simulation findings, model outcomes were compared with experimental data and good consistency was revealed. The results showed that increasing temperature of AMP solution increases CO 2 removal in the hollow-fiber membrane contactor.

  13. Development of mechanistic sorption model and treatment of uncertainties for Ni sorption on montmorillonite/bentonite

    International Nuclear Information System (INIS)

    Ochs, Michael; Ganter, Charlotte; Tachi, Yukio; Suyama, Tadahiro; Yui, Mikazu

    2011-02-01

    Sorption and diffusion of radionuclides in buffer materials (bentonite) are the key processes in the safe geological disposal of radioactive waste, because migration of radionuclides in this barrier is expected to be diffusion-controlled and retarded by sorption processes. It is therefore necessary to understand the detailed/coupled processes of sorption and diffusion in compacted bentonite and develop mechanistic /predictive models, so that reliable parameters can be set under a variety of geochemical conditions relevant to performance assessment (PA). For this purpose, JAEA has developed the integrated sorption and diffusion (ISD) model/database in montmorillonite/bentonite systems. The main goal of the mechanistic model/database development is to provide a tool for a consistent explanation, prediction, and uncertainty assessment of K d as well as diffusion parameters needed for the quantification of radionuclide transport. The present report focuses on developing the thermodynamic sorption model (TSM) and on the quantification and handling of model uncertainties in applications, based on illustrating by example of Ni sorption on montmorillonite/bentonite. This includes 1) a summary of the present state of the art of thermodynamic sorption modeling, 2) a discussion of the selection of surface species and model design appropriate for the present purpose, 3) possible sources and representations of TSM uncertainties, and 4) details of modeling, testing and uncertainty evaluation for Ni sorption. Two fundamentally different approaches are presented and compared for representing TSM uncertainties: 1) TSM parameter uncertainties calculated by FITEQL optimization routines and some statistical procedure, 2) overall error estimated by direct comparison of modeled and experimental K d values. The overall error in K d is viewed as the best representation of model uncertainty in ISD model/database development. (author)

  14. Applicability of one-dimensional mechanistic post-dryout prediction model

    International Nuclear Information System (INIS)

    Jeong, Hae Yong; No Hee Cheon

    1996-01-01

    Through the analysis of many experimental post-dryout data, it is shown that the most probable flow regime near dryout or quench front is not annular flow but churn-turbulent flow when the mass flux is low. A correlation describing the initial droplet size just after the CHF position at low mass flux is low. A correlation describing the initial droplet size just after the CHF position at low mass flux is suggested through regression analysis. In the post-dryout region at low pressure and low flow, it is found that the suggested one-dimensional mechanistic model is not applicable when the vapor superficial velocity is very low, i. e., when the flow is bubbly or slug flow regime. This is explained by the change of main entrainment mechanism with the change of flow regime. Therefore, the suggested correlation is valid only in the churn-turbulent flow regime (j * g = 0.5 ∼ 4.5)

  15. Mechanistic characterization and molecular modeling of hepatitis B virus polymerase resistance to entecavir.

    Science.gov (United States)

    Walsh, Ann W; Langley, David R; Colonno, Richard J; Tenney, Daniel J

    2010-02-12

    Entecavir (ETV) is a deoxyguanosine analog competitive inhibitor of hepatitis B virus (HBV) polymerase that exhibits delayed chain termination of HBV DNA. A high barrier to entecavir-resistance (ETVr) is observed clinically, likely due to its potency and a requirement for multiple resistance changes to overcome suppression. Changes in the HBV polymerase reverse-transcriptase (RT) domain involve lamivudine-resistance (LVDr) substitutions in the conserved YMDD motif (M204V/I +/- L180M), plus an additional ETV-specific change at residues T184, S202 or M250. These substitutions surround the putative dNTP binding site or primer grip regions of the HBV RT. To determine the mechanistic basis for ETVr, wildtype, lamivudine-resistant (M204V, L180M) and ETVr HBVs were studied using in vitro RT enzyme and cell culture assays, as well as molecular modeling. Resistance substitutions significantly reduced ETV incorporation and chain termination in HBV DNA and increased the ETV-TP inhibition constant (K(i)) for HBV RT. Resistant HBVs exhibited impaired replication in culture and reduced enzyme activity (k(cat)) in vitro. Molecular modeling of the HBV RT suggested that ETVr residue T184 was adjacent to and stabilized S202 within the LVDr YMDD loop. ETVr arose through steric changes at T184 or S202 or by disruption of hydrogen-bonding between the two, both of which repositioned the loop and reduced the ETV-triphosphate (ETV-TP) binding pocket. In contrast to T184 and S202 changes, ETVr at primer grip residue M250 was observed during RNA-directed DNA synthesis only. Experimentally, M250 changes also impacted the dNTP-binding site. Modeling suggested a novel mechanism for M250 resistance, whereby repositioning of the primer-template component of the dNTP-binding site shifted the ETV-TP binding pocket. No structural data are available to confirm the HBV RT modeling, however, results were consistent with phenotypic analysis of comprehensive substitutions of each ETVr position

  16. Mechanistic characterization and molecular modeling of hepatitis B virus polymerase resistance to entecavir.

    Directory of Open Access Journals (Sweden)

    Ann W Walsh

    Full Text Available BACKGROUND: Entecavir (ETV is a deoxyguanosine analog competitive inhibitor of hepatitis B virus (HBV polymerase that exhibits delayed chain termination of HBV DNA. A high barrier to entecavir-resistance (ETVr is observed clinically, likely due to its potency and a requirement for multiple resistance changes to overcome suppression. Changes in the HBV polymerase reverse-transcriptase (RT domain involve lamivudine-resistance (LVDr substitutions in the conserved YMDD motif (M204V/I +/- L180M, plus an additional ETV-specific change at residues T184, S202 or M250. These substitutions surround the putative dNTP binding site or primer grip regions of the HBV RT. METHODS/PRINCIPAL FINDINGS: To determine the mechanistic basis for ETVr, wildtype, lamivudine-resistant (M204V, L180M and ETVr HBVs were studied using in vitro RT enzyme and cell culture assays, as well as molecular modeling. Resistance substitutions significantly reduced ETV incorporation and chain termination in HBV DNA and increased the ETV-TP inhibition constant (K(i for HBV RT. Resistant HBVs exhibited impaired replication in culture and reduced enzyme activity (k(cat in vitro. Molecular modeling of the HBV RT suggested that ETVr residue T184 was adjacent to and stabilized S202 within the LVDr YMDD loop. ETVr arose through steric changes at T184 or S202 or by disruption of hydrogen-bonding between the two, both of which repositioned the loop and reduced the ETV-triphosphate (ETV-TP binding pocket. In contrast to T184 and S202 changes, ETVr at primer grip residue M250 was observed during RNA-directed DNA synthesis only. Experimentally, M250 changes also impacted the dNTP-binding site. Modeling suggested a novel mechanism for M250 resistance, whereby repositioning of the primer-template component of the dNTP-binding site shifted the ETV-TP binding pocket. No structural data are available to confirm the HBV RT modeling, however, results were consistent with phenotypic analysis of

  17. A mechanistic model for electricity consumption on dairy farms: definition, validation, and demonstration.

    Science.gov (United States)

    Upton, J; Murphy, M; Shalloo, L; Groot Koerkamp, P W G; De Boer, I J M

    2014-01-01

    Our objective was to define and demonstrate a mechanistic model that enables dairy farmers to explore the impact of a technical or managerial innovation on electricity consumption, associated CO2 emissions, and electricity costs. We, therefore, (1) defined a model for electricity consumption on dairy farms (MECD) capable of simulating total electricity consumption along with related CO2 emissions and electricity costs on dairy farms on a monthly basis; (2) validated the MECD using empirical data of 1yr on commercial spring calving, grass-based dairy farms with 45, 88, and 195 milking cows; and (3) demonstrated the functionality of the model by applying 2 electricity tariffs to the electricity consumption data and examining the effect on total dairy farm electricity costs. The MECD was developed using a mechanistic modeling approach and required the key inputs of milk production, cow number, and details relating to the milk-cooling system, milking machine system, water-heating system, lighting systems, water pump systems, and the winter housing facilities as well as details relating to the management of the farm (e.g., season of calving). Model validation showed an overall relative prediction error (RPE) of less than 10% for total electricity consumption. More than 87% of the mean square prediction error of total electricity consumption was accounted for by random variation. The RPE values of the milk-cooling systems, water-heating systems, and milking machine systems were less than 20%. The RPE values for automatic scraper systems, lighting systems, and water pump systems varied from 18 to 113%, indicating a poor prediction for these metrics. However, automatic scrapers, lighting, and water pumps made up only 14% of total electricity consumption across all farms, reducing the overall impact of these poor predictions. Demonstration of the model showed that total farm electricity costs increased by between 29 and 38% by moving from a day and night tariff to a flat

  18. Mechanistic modelling of gaseous fission product behaviour in UO2 fuel by Rtop code

    International Nuclear Information System (INIS)

    Kanukova, V.D.; Khoruzhii, O.V.; Kourtchatov, S.Y.; Likhanskii, V.V.; Matveew, L.V.

    2002-01-01

    The current status of a mechanistic modelling by the RTOP code of the fission product behaviour in polycrystalline UO 2 fuel is described. An outline of the code and implemented physical models is presented. The general approach to code validation is discussed. It is exemplified by the results of validation of the models of fuel oxidation and grain growth. The different models of intragranular and intergranular gas bubble behaviour have been tested and the sensitivity of the code in the framework of these models has been analysed. An analysis of available models of the resolution of grain face bubbles is also presented. The possibilities of the RTOP code are presented through the example of modelling behaviour of WWER fuel over the course of a comparative WWER-PWR experiment performed at Halden and by comparison with Yanagisawa experiments. (author)

  19. Aspects of the incorporation of spatial data into radioecological and restoration analysis

    International Nuclear Information System (INIS)

    Beresford, N.A.; Wright, S.M.; Howard, B.J.; Crout, N.M.J.; Arkhipov, A.; Voigt, G.

    2002-01-01

    In the last decade geographical information systems have been increasingly used to incorporate spatial data into radioecological analysis. This has allowed the development of models with spatially variable outputs. Two main approaches have been adopted in the development of spatial models. Empirical Tag based models applied across a range of spatial scales utilize underlying soil type maps and readily available radioecological data. Soil processes can also be modelled to allow the dynamic prediction of radionuclide soil to plant transfer. We discuss a dynamic semi-mechanistic radiocaesium soil to plant-transfer model, which utilizes readily available spatially variable soil parameters. Both approaches allow the identification of areas that may be vulnerable to radionuclide deposition, therefore enabling the targeting of intervention measures. Improved estimates of radionuclide fluxes and ingestion doses can be achieved by incorporating spatially varying inputs such as agricultural production and dietary habits in to these models. In this paper, aspects of such models, including data requirements, implementation and outputs are discussed and critically evaluated. The relative merits and disadvantages of the two spatial model approaches adopted within radioecology are discussed. We consider the usefulness of such models to aid decision-makers and access the requirements and potential of further application within radiological protection. (author)

  20. Incorporating direct marketing activity into latent attrition models

    NARCIS (Netherlands)

    Schweidel, David A.; Knox, George

    2013-01-01

    When defection is unobserved, latent attrition models provide useful insights about customer behavior and accurate forecasts of customer value. Yet extant models ignore direct marketing efforts. Response models incorporate the effects of direct marketing, but because they ignore latent attrition,

  1. Model-based analysis of a twin-screw wet granulation system for continuous solid dosage manufacturing

    DEFF Research Database (Denmark)

    Kumar, Ashish; Vercruysse, Jurgen; Mortier, Severine T. F. C.

    2016-01-01

    Implementation of twin-screw granulation in a continuous from-powder-to-tablet manufacturing line requires process knowledge development. This is often pursued by application of mechanistic models incorporating the underlying mechanisms. In this study, granulation mechanisms considered to be domi......Implementation of twin-screw granulation in a continuous from-powder-to-tablet manufacturing line requires process knowledge development. This is often pursued by application of mechanistic models incorporating the underlying mechanisms. In this study, granulation mechanisms considered...... to be dominant in the kneading element regions of the granulator i.e., aggregation and breakage, were included in a one-dimensional population balance model. The model was calibrated using the experimentally determined inflow granule size distribution, and the mean residence time was used as additional input...

  2. Development of boiling transition analysis code TCAPE-INS/B based on mechanistic methods for BWR fuel bundles. Models and validations with boiling transition experimental data

    International Nuclear Information System (INIS)

    Ishida, Naoyuki; Utsuno, Hideaki; Kasahara, Fumio

    2003-01-01

    The Boiling Transition (BT) analysis code TCAPE-INS/B based on the mechanistic methods coupled with subchannel analysis has been developed for the evaluation of the integrity of Boiling Water Reactor (BWR) fuel rod bundles under abnormal operations. Objective of the development is the evaluation of the BT without using empirical BT and rewetting correlations needed for different bundle designs in the current analysis methods. TCAPE-INS/B consisted mainly of the drift-flux model, the film flow model, the cross-flow model, the thermal conductivity model and the heat transfer correlations. These models were validated systematically with the experimental data. The accuracy of the prediction for the steady-state Critical Heat Flux (CHF) and the transient temperature of the fuel rod surface after the occurrence of BT were evaluated on the validations. The calculations for the experiments with the single tube and bundles were carried out for the validations of the models incorporated in the code. The results showed that the steady-state CHF was predicted within about 6% average error. In the transient calculations, BT timing and temperature of the fuel rod surface gradient agreed well with experimental results, but rewetting was predicted lately. So, modeling of heat transfer phenomena during post-BT is under modification. (author)

  3. Soil pH controls the environmental availability of phosphorus: Experimental and mechanistic modelling approaches

    International Nuclear Information System (INIS)

    Devau, Nicolas; Cadre, Edith Le; Hinsinger, Philippe; Jaillard, Benoit; Gerard, Frederic

    2009-01-01

    Inorganic P is the least mobile major nutrient in most soils and is frequently the prime limiting factor for plant growth in terrestrial ecosystems. In this study, the extraction of soil inorganic P with CaCl 2 (P-CaCl 2 ) and geochemical modelling were combined in order to unravel the processes controlling the environmentally available P (EAP) of a soil over a range of pH values (pH ∼ 4-10). Mechanistic descriptions of the adsorption of cations and anions by the soil constituents were used (1-pK Triple Plane, ion-exchange and NICA-Donnan models). These models are implemented into the geochemical code Visual MINTEQ. An additive approach was used for their application to the surface horizon of a Cambisol. The geochemical code accurately reproduced the concentration of extracted P at the different soil pH values (R 2 = 0.9, RMSE = 0.03 mg kg -1 ). Model parameters were either directly found in the literature or estimated by fitting published experimental results in single mineral systems. The strong agreement between measurements and modelling results demonstrated that adsorption processes exerted a major control on the EAP of the soil over a large range of pH values. An influence of the precipitation of P-containing mineral is discounted based on thermodynamic calculations. Modelling results indicated that the variations in P-CaCl 2 with soil pH were controlled by the deprotonation/protonation of the surface hydroxyl groups, the distribution of P surface complexes, and the adsorption of Ca and Cl from the electrolyte background. Iron-oxides and gibbsite were found to be the major P-adsorbing soil constituents at acidic and alkaline pHs, whereas P was mainly adsorbed by clay minerals at intermediate pH values. This study demonstrates the efficacy of geochemical modelling to understand soil processes, and the applicability of mechanistic adsorption models to a 'real' soil, with its mineralogical complexity and the additional contribution of soil organic matter.

  4. Soil pH controls the environmental availability of phosphorus: Experimental and mechanistic modelling approaches

    Energy Technology Data Exchange (ETDEWEB)

    Devau, Nicolas [INRA, UMR 1222 Eco and Sols - Ecologie Fonctionnelle et Biogeochimie des Sols (INRA-IRD-SupAgro), Place Viala, F-34060 Montpellier (France); Cadre, Edith Le [Supagro, UMR 1222 Eco and Sols - Ecologie Fonctionnelle et Biogeochimie des Sols (INRA-IRD-SupAgro), Place Viala, F-34060 Montpellier (France); Hinsinger, Philippe; Jaillard, Benoit [INRA, UMR 1222 Eco and Sols - Ecologie Fonctionnelle et Biogeochimie des Sols (INRA-IRD-SupAgro), Place Viala, F-34060 Montpellier (France); Gerard, Frederic, E-mail: gerard@supagro.inra.fr [INRA, UMR 1222 Eco and Sols - Ecologie Fonctionnelle et Biogeochimie des Sols (INRA-IRD-SupAgro), Place Viala, F-34060 Montpellier (France)

    2009-11-15

    Inorganic P is the least mobile major nutrient in most soils and is frequently the prime limiting factor for plant growth in terrestrial ecosystems. In this study, the extraction of soil inorganic P with CaCl{sub 2} (P-CaCl{sub 2}) and geochemical modelling were combined in order to unravel the processes controlling the environmentally available P (EAP) of a soil over a range of pH values (pH {approx} 4-10). Mechanistic descriptions of the adsorption of cations and anions by the soil constituents were used (1-pK Triple Plane, ion-exchange and NICA-Donnan models). These models are implemented into the geochemical code Visual MINTEQ. An additive approach was used for their application to the surface horizon of a Cambisol. The geochemical code accurately reproduced the concentration of extracted P at the different soil pH values (R{sup 2} = 0.9, RMSE = 0.03 mg kg{sup -1}). Model parameters were either directly found in the literature or estimated by fitting published experimental results in single mineral systems. The strong agreement between measurements and modelling results demonstrated that adsorption processes exerted a major control on the EAP of the soil over a large range of pH values. An influence of the precipitation of P-containing mineral is discounted based on thermodynamic calculations. Modelling results indicated that the variations in P-CaCl{sub 2} with soil pH were controlled by the deprotonation/protonation of the surface hydroxyl groups, the distribution of P surface complexes, and the adsorption of Ca and Cl from the electrolyte background. Iron-oxides and gibbsite were found to be the major P-adsorbing soil constituents at acidic and alkaline pHs, whereas P was mainly adsorbed by clay minerals at intermediate pH values. This study demonstrates the efficacy of geochemical modelling to understand soil processes, and the applicability of mechanistic adsorption models to a 'real' soil, with its mineralogical complexity and the additional

  5. Mechanistic Links Between PARP, NAD, and Brain Inflammation After TBI

    Science.gov (United States)

    2015-10-01

    1 AWARD NUMBER: W81XWH-13-2-0091 TITLE: Mechanistic Links Between PARP, NAD , and Brain Inflammation After TBI PRINCIPAL INVESTIGATOR...COVERED 25 Sep 2014 - 24 Sep 2015 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Mechanistic Links Between PARP, NAD , and Brain Inflammation After TBI 5b. GRANT...efficacy of veliparib and NAD as agents for suppressing inflammation and improving outcomes after traumatic brain injury. The animal models include

  6. A rigorous mechanistic model for predicting gas hydrate formation kinetics: The case of CO2 recovery and sequestration

    International Nuclear Information System (INIS)

    ZareNezhad, Bahman; Mottahedin, Mona

    2012-01-01

    Highlights: ► A mechanistic model for predicting gas hydrate formation kinetics is presented. ► A secondary nucleation rate model is proposed for the first time. ► Crystal–crystal collisions and crystal–impeller collisions are distinguished. ► Simultaneous determination of nucleation and growth kinetics are established. ► Important for design of gas hydrate based energy storage and CO 2 recovery systems. - Abstract: A rigorous mechanistic model for predicting gas hydrate formation crystallization kinetics is presented and the special case of CO 2 gas hydrate formation regarding CO 2 recovery and sequestration processes has been investigated by using the proposed model. A physical model for prediction of secondary nucleation rate is proposed for the first time and the formation rates of secondary nuclei by crystal–crystal collisions and crystal–impeller collisions are formulated. The objective functions for simultaneous determination of nucleation and growth kinetics are presented and a theoretical framework for predicting the dynamic behavior of gas hydrate formation is presented. Predicted time variations of CO 2 content, total number and surface area of produced hydrate crystals are in good agreement with the available experimental data. The proposed approach can have considerable application for design of gas hydrate converters regarding energy storage and CO 2 recovery processes.

  7. A mechanistic compartmental model for total antibody uptake in tumors.

    Science.gov (United States)

    Thurber, Greg M; Dane Wittrup, K

    2012-12-07

    Antibodies are under development to treat a variety of cancers, such as lymphomas, colon, and breast cancer. A major limitation to greater efficacy for this class of drugs is poor distribution in vivo. Localization of antibodies occurs slowly, often in insufficient therapeutic amounts, and distributes heterogeneously throughout the tumor. While the microdistribution around individual vessels is important for many therapies, the total amount of antibody localized in the tumor is paramount for many applications such as imaging, determining the therapeutic index with antibody drug conjugates, and dosing in radioimmunotherapy. With imaging and pretargeted therapeutic strategies, the time course of uptake is critical in determining when to take an image or deliver a secondary reagent. We present here a simple mechanistic model of antibody uptake and retention that captures the major rates that determine the time course of antibody concentration within a tumor including dose, affinity, plasma clearance, target expression, internalization, permeability, and vascularization. Since many of the parameters are known or can be estimated in vitro, this model can approximate the time course of antibody concentration in tumors to aid in experimental design, data interpretation, and strategies to improve localization. Copyright © 2012 Elsevier Ltd. All rights reserved.

  8. Coupling machine learning with mechanistic models to study runoff production and river flow at the hillslope scale

    Science.gov (United States)

    Marçais, J.; Gupta, H. V.; De Dreuzy, J. R.; Troch, P. A. A.

    2016-12-01

    Geomorphological structure and geological heterogeneity of hillslopes are major controls on runoff responses. The diversity of hillslopes (morphological shapes and geological structures) on one hand, and the highly non linear runoff mechanism response on the other hand, make it difficult to transpose what has been learnt at one specific hillslope to another. Therefore, making reliable predictions on runoff appearance or river flow for a given hillslope is a challenge. Applying a classic model calibration (based on inverse problems technique) requires doing it for each specific hillslope and having some data available for calibration. When applied to thousands of cases it cannot always be promoted. Here we propose a novel modeling framework based on coupling process based models with data based approach. First we develop a mechanistic model, based on hillslope storage Boussinesq equations (Troch et al. 2003), able to model non linear runoff responses to rainfall at the hillslope scale. Second we set up a model database, representing thousands of non calibrated simulations. These simulations investigate different hillslope shapes (real ones obtained by analyzing 5m digital elevation model of Brittany and synthetic ones), different hillslope geological structures (i.e. different parametrizations) and different hydrologic forcing terms (i.e. different infiltration chronicles). Then, we use this model library to train a machine learning model on this physically based database. Machine learning model performance is then assessed by a classic validating phase (testing it on new hillslopes and comparing machine learning with mechanistic outputs). Finally we use this machine learning model to learn what are the hillslope properties controlling runoffs. This methodology will be further tested combining synthetic datasets with real ones.

  9. Four Mechanistic Models of Peer Influence on Adolescent Cannabis Use.

    Science.gov (United States)

    Caouette, Justin D; Feldstein Ewing, Sarah W

    2017-06-01

    Most adolescents begin exploring cannabis in peer contexts, but the neural mechanisms that underlie peer influence on adolescent cannabis use are still unknown. This theoretical overview elucidates the intersecting roles of neural function and peer factors in cannabis use in adolescents. Novel paradigms using functional magnetic resonance imaging (fMRI) in adolescents have identified distinct neural mechanisms of risk decision-making and incentive processing in peer contexts, centered on reward-motivation and affect regulatory neural networks; these findings inform a theoretical model of peer-driven cannabis use decisions in adolescents. We propose four "mechanistic profiles" of social facilitation of cannabis use in adolescents: (1) peer influence as the primary driver of use; (2) cannabis exploration as the primary driver, which may be enhanced in peer contexts; (3) social anxiety; and (4) negative peer experiences. Identification of "neural targets" involved in motivating cannabis use may inform clinicians about which treatment strategies work best in adolescents with cannabis use problems, and via which social and neurocognitive processes.

  10. Uncertainty, sensitivity analysis and the role of data based mechanistic modeling in hydrology

    Science.gov (United States)

    Ratto, M.; Young, P. C.; Romanowicz, R.; Pappenberger, F.; Saltelli, A.; Pagano, A.

    2007-05-01

    In this paper, we discuss a joint approach to calibration and uncertainty estimation for hydrologic systems that combines a top-down, data-based mechanistic (DBM) modelling methodology; and a bottom-up, reductionist modelling methodology. The combined approach is applied to the modelling of the River Hodder catchment in North-West England. The top-down DBM model provides a well identified, statistically sound yet physically meaningful description of the rainfall-flow data, revealing important characteristics of the catchment-scale response, such as the nature of the effective rainfall nonlinearity and the partitioning of the effective rainfall into different flow pathways. These characteristics are defined inductively from the data without prior assumptions about the model structure, other than it is within the generic class of nonlinear differential-delay equations. The bottom-up modelling is developed using the TOPMODEL, whose structure is assumed a priori and is evaluated by global sensitivity analysis (GSA) in order to specify the most sensitive and important parameters. The subsequent exercises in calibration and validation, performed with Generalized Likelihood Uncertainty Estimation (GLUE), are carried out in the light of the GSA and DBM analyses. This allows for the pre-calibration of the the priors used for GLUE, in order to eliminate dynamical features of the TOPMODEL that have little effect on the model output and would be rejected at the structure identification phase of the DBM modelling analysis. In this way, the elements of meaningful subjectivity in the GLUE approach, which allow the modeler to interact in the modelling process by constraining the model to have a specific form prior to calibration, are combined with other more objective, data-based benchmarks for the final uncertainty estimation. GSA plays a major role in building a bridge between the hypothetico-deductive (bottom-up) and inductive (top-down) approaches and helps to improve the

  11. True dose from incorporated activities. Models for internal dosimetry

    International Nuclear Information System (INIS)

    Breustedt, B.; Eschner, W.; Nosske, D.

    2012-01-01

    The assessment of doses after incorporation of radionuclides cannot use direct measurements of the doses, as for example dosimetry in external radiation fields. The only observables are activities in the body or in excretions. Models are used to calculate the doses based on the measured activities. The incorporated activities and the resulting doses can vary by more than seven orders of magnitude between occupational and medical exposures. Nevertheless the models and calculations applied in both cases are similar. Since the models for the different applications have been developed independently by ICRP and MIRD different terminologies have been used. A unified terminology is being developed. (orig.)

  12. Rotary ultrasonic machining of CFRP: a mechanistic predictive model for cutting force.

    Science.gov (United States)

    Cong, W L; Pei, Z J; Sun, X; Zhang, C L

    2014-02-01

    Cutting force is one of the most important output variables in rotary ultrasonic machining (RUM) of carbon fiber reinforced plastic (CFRP) composites. Many experimental investigations on cutting force in RUM of CFRP have been reported. However, in the literature, there are no cutting force models for RUM of CFRP. This paper develops a mechanistic predictive model for cutting force in RUM of CFRP. The material removal mechanism of CFRP in RUM has been analyzed first. The model is based on the assumption that brittle fracture is the dominant mode of material removal. CFRP micromechanical analysis has been conducted to represent CFRP as an equivalent homogeneous material to obtain the mechanical properties of CFRP from its components. Based on this model, relationships between input variables (including ultrasonic vibration amplitude, tool rotation speed, feedrate, abrasive size, and abrasive concentration) and cutting force can be predicted. The relationships between input variables and important intermediate variables (indentation depth, effective contact time, and maximum impact force of single abrasive grain) have been investigated to explain predicted trends of cutting force. Experiments are conducted to verify the model, and experimental results agree well with predicted trends from this model. Copyright © 2013 Elsevier B.V. All rights reserved.

  13. Supporting Mechanistic Reasoning in Domain-Specific Contexts

    Science.gov (United States)

    Weinberg, Paul J.

    2017-01-01

    Mechanistic reasoning is an epistemic practice central within science, technology, engineering, and mathematics disciplines. Although there has been some work on mechanistic reasoning in the research literature and standards documents, much of this work targets domain-general characterizations of mechanistic reasoning; this study provides…

  14. Using a Mechanistic Reactive Transport Model to Represent Soil Organic Matter Dynamics and Climate Sensitivity

    Science.gov (United States)

    Guerry, N.; Riley, W. J.; Maggi, F.; Torn, M. S.; Kleber, M.

    2011-12-01

    The nature of long term Soil Organic Matter (SOM) dynamics is uncertain and the mechanisms involved are crudely represented in site, regional, and global models. Recent work challenging the paradigm that SOM is stabilized because of its sequential transformations to more intrinsically recalcitrant compounds motivated us to develop a mechanistic modeling framework that can be used to test hypotheses of SOM dynamics. We developed our C cycling model in TOUGHREACT, an established 3-dimensional reactive transport solver that accounts for multiple phases (aqueous, gaseous, sorbed), multiple species, advection and diffusion, and multiple microbial populations. Energy and mass exchange through the soil boundaries are accounted for via ground heat flux, rainfall, C sources (e.g., exudation, woody, leaf, root litter) and C losses (e.g., CO2 emissions and DOC deep percolation). SOM is categorized according to the various types of compounds commonly found in the above mentioned C sources and microbial byproducts, including poly- and monosaccharides, lignin, amino compounds, organic acids, nucleic acids, lipids, and phenols. Each of these compounds is accounted for by one or more representative species in the model. A reaction network was developed to describe the microbially-mediated processes and chemical interactions of these species, including depolymerization, microbial assimilation, respiration and deposition of byproducts, and incorporation of dead biomass into SOM stocks. Enzymatic reactions are characterized by Michaelis-Menten kinetics, with maximum reaction rates determined by the species' O/C ratio. Microbial activity is further regulated by soil moisture content, O2 availability, pH, and temperature. For the initial set of simulations, literature values were used to constrain microbial Monod parameters, Michaelis-Menten parameters, sorption parameters, physical protection, partitioning of microbial byproducts, and partitioning of litter inputs, although there is

  15. Incorporating interfacial phenomena in solidification models

    Science.gov (United States)

    Beckermann, Christoph; Wang, Chao Yang

    1994-01-01

    A general methodology is available for the incorporation of microscopic interfacial phenomena in macroscopic solidification models that include diffusion and convection. The method is derived from a formal averaging procedure and a multiphase approach, and relies on the presence of interfacial integrals in the macroscopic transport equations. In a wider engineering context, these techniques are not new, but their application in the analysis and modeling of solidification processes has largely been overlooked. This article describes the techniques and demonstrates their utility in two examples in which microscopic interfacial phenomena are of great importance.

  16. High-Strain Rate Failure Modeling Incorporating Shear Banding and Fracture

    Science.gov (United States)

    2017-11-22

    High Strain Rate Failure Modeling Incorporating Shear Banding and Fracture The views, opinions and/or findings contained in this report are those of...SECURITY CLASSIFICATION OF: 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 13. SUPPLEMENTARY NOTES 12. DISTRIBUTION AVAILIBILITY STATEMENT 6. AUTHORS...Report as of 05-Dec-2017 Agreement Number: W911NF-13-1-0238 Organization: Columbia University Title: High Strain Rate Failure Modeling Incorporating

  17. Precision and accuracy of mechanistic-empirical pavement design

    CSIR Research Space (South Africa)

    Theyse, HL

    2006-09-01

    Full Text Available are discussed in general. The effects of variability and error on the design accuracy and design risk are lastly illustrated at the hand of a simple mechanistic-empirical design problem, showing that the engineering models alone determine the accuracy...

  18. Toward a mechanistic modeling of nitrogen limitation on vegetation dynamics.

    Science.gov (United States)

    Xu, Chonggang; Fisher, Rosie; Wullschleger, Stan D; Wilson, Cathy J; Cai, Michael; McDowell, Nate G

    2012-01-01

    Nitrogen is a dominant regulator of vegetation dynamics, net primary production, and terrestrial carbon cycles; however, most ecosystem models use a rather simplistic relationship between leaf nitrogen content and photosynthetic capacity. Such an approach does not consider how patterns of nitrogen allocation may change with differences in light intensity, growing-season temperature and CO(2) concentration. To account for this known variability in nitrogen-photosynthesis relationships, we develop a mechanistic nitrogen allocation model based on a trade-off of nitrogen allocated between growth and storage, and an optimization of nitrogen allocated among light capture, electron transport, carboxylation, and respiration. The developed model is able to predict the acclimation of photosynthetic capacity to changes in CO(2) concentration, temperature, and radiation when evaluated against published data of V(c,max) (maximum carboxylation rate) and J(max) (maximum electron transport rate). A sensitivity analysis of the model for herbaceous plants, deciduous and evergreen trees implies that elevated CO(2) concentrations lead to lower allocation of nitrogen to carboxylation but higher allocation to storage. Higher growing-season temperatures cause lower allocation of nitrogen to carboxylation, due to higher nitrogen requirements for light capture pigments and for storage. Lower levels of radiation have a much stronger effect on allocation of nitrogen to carboxylation for herbaceous plants than for trees, resulting from higher nitrogen requirements for light capture for herbaceous plants. As far as we know, this is the first model of complete nitrogen allocation that simultaneously considers nitrogen allocation to light capture, electron transport, carboxylation, respiration and storage, and the responses of each to altered environmental conditions. We expect this model could potentially improve our confidence in simulations of carbon-nitrogen interactions and the vegetation

  19. Toward a Mechanistic Modeling of Nitrogen Limitation on Vegetation Dynamics

    Science.gov (United States)

    Xu, Chonggang; Fisher, Rosie; Wullschleger, Stan D.; Wilson, Cathy J.; Cai, Michael; McDowell, Nate G.

    2012-01-01

    Nitrogen is a dominant regulator of vegetation dynamics, net primary production, and terrestrial carbon cycles; however, most ecosystem models use a rather simplistic relationship between leaf nitrogen content and photosynthetic capacity. Such an approach does not consider how patterns of nitrogen allocation may change with differences in light intensity, growing-season temperature and CO2 concentration. To account for this known variability in nitrogen-photosynthesis relationships, we develop a mechanistic nitrogen allocation model based on a trade-off of nitrogen allocated between growth and storage, and an optimization of nitrogen allocated among light capture, electron transport, carboxylation, and respiration. The developed model is able to predict the acclimation of photosynthetic capacity to changes in CO2 concentration, temperature, and radiation when evaluated against published data of Vc,max (maximum carboxylation rate) and Jmax (maximum electron transport rate). A sensitivity analysis of the model for herbaceous plants, deciduous and evergreen trees implies that elevated CO2 concentrations lead to lower allocation of nitrogen to carboxylation but higher allocation to storage. Higher growing-season temperatures cause lower allocation of nitrogen to carboxylation, due to higher nitrogen requirements for light capture pigments and for storage. Lower levels of radiation have a much stronger effect on allocation of nitrogen to carboxylation for herbaceous plants than for trees, resulting from higher nitrogen requirements for light capture for herbaceous plants. As far as we know, this is the first model of complete nitrogen allocation that simultaneously considers nitrogen allocation to light capture, electron transport, carboxylation, respiration and storage, and the responses of each to altered environmental conditions. We expect this model could potentially improve our confidence in simulations of carbon-nitrogen interactions and the vegetation feedbacks

  20. Toward a mechanistic modeling of nitrogen limitation on vegetation dynamics.

    Directory of Open Access Journals (Sweden)

    Chonggang Xu

    Full Text Available Nitrogen is a dominant regulator of vegetation dynamics, net primary production, and terrestrial carbon cycles; however, most ecosystem models use a rather simplistic relationship between leaf nitrogen content and photosynthetic capacity. Such an approach does not consider how patterns of nitrogen allocation may change with differences in light intensity, growing-season temperature and CO(2 concentration. To account for this known variability in nitrogen-photosynthesis relationships, we develop a mechanistic nitrogen allocation model based on a trade-off of nitrogen allocated between growth and storage, and an optimization of nitrogen allocated among light capture, electron transport, carboxylation, and respiration. The developed model is able to predict the acclimation of photosynthetic capacity to changes in CO(2 concentration, temperature, and radiation when evaluated against published data of V(c,max (maximum carboxylation rate and J(max (maximum electron transport rate. A sensitivity analysis of the model for herbaceous plants, deciduous and evergreen trees implies that elevated CO(2 concentrations lead to lower allocation of nitrogen to carboxylation but higher allocation to storage. Higher growing-season temperatures cause lower allocation of nitrogen to carboxylation, due to higher nitrogen requirements for light capture pigments and for storage. Lower levels of radiation have a much stronger effect on allocation of nitrogen to carboxylation for herbaceous plants than for trees, resulting from higher nitrogen requirements for light capture for herbaceous plants. As far as we know, this is the first model of complete nitrogen allocation that simultaneously considers nitrogen allocation to light capture, electron transport, carboxylation, respiration and storage, and the responses of each to altered environmental conditions. We expect this model could potentially improve our confidence in simulations of carbon-nitrogen interactions and the

  1. Semi-Mechanistic Population Pharmacokinetic Modeling of L-Histidine Disposition and Brain Uptake in Wildtype and Pht1 Null Mice.

    Science.gov (United States)

    Wang, Xiao-Xing; Li, Yang-Bing; Feng, Meihua R; Smith, David E

    2018-01-05

    To develop a semi-mechanistic population pharmacokinetic (PK) model to quantitate the disposition kinetics of L-histidine, a peptide-histidine transporter 1 (PHT1) substrate, in the plasma, cerebrospinal fluid and brain parenchyma of wildtype (WT) and Pht1 knockout (KO) mice. L-[ 14 C]Hisidine (L-His) was administrated to WT and KO mice via tail vein injection, after which plasma, cerebrospinal fluid (CSF) and brain parenchyma samples were collected. A PK model was developed using non-linear mixed effects modeling (NONMEM). The disposition of L-His between the plasma, brain, and CSF was described by a combination of PHT1-mediated uptake, CSF bulk flow and first-order micro-rate constants. The PK profile of L-His was best described by a four-compartment model. A more rapid uptake of L-His in brain parenchyma was observed in WT mice due to PHT1-mediated uptake, a process characterized by a Michaelis-Menten component (V max  = 0.051 nmoL/min and K m  = 34.94 μM). A semi-mechanistic population PK model was successfully developed, for the first time, to quantitatively characterize the disposition kinetics of L-His in brain under in vivo conditions. This model may prove a useful tool in predicting the uptake of L-His, and possibly other PHT1 peptide/mimetic substrates, for drug delivery to the brain.

  2. A new mechanistic and engineering fission gas release model for a uranium dioxide fuel

    International Nuclear Information System (INIS)

    Lee, Chan Bock; Yang, Yong Sik; Kim, Dae Ho; Kim, Sun Ki; Bang, Je Geun

    2008-01-01

    A mechanistic and engineering fission gas release model (MEGA) for uranium dioxide (UO 2 ) fuel was developed. It was based upon the diffusional release of fission gases from inside the grain to the grain boundary and the release of fission gases from the grain boundary to the external surface by the interconnection of the fission gas bubbles in the grain boundary. The capability of the MEGA model was validated by a comparison with the fission gas release data base and the sensitivity analyses of the parameters. It was found that the MEGA model correctly predicts the fission gas release in the broad range of fuel burnups up to 98 MWd/kgU. Especially, the enhancement of fission gas release in a high-burnup fuel, and the reduction of fission gas release at a high burnup by increasing the UO 2 grain size were found to be correctly predicted by the MEGA model without using any artificial factor. (author)

  3. Integrity: A semi-mechanistic model for stress corrosion cracking of fuel

    Energy Technology Data Exchange (ETDEWEB)

    Tayal, M; Hallgrimson, K; Macquarrie, J; Alavi, P [Atomic Energy of Canada Ltd., Mississauga, ON (Canada); Sato, S; Kinoshita, Y; Nishimura, T [Electric Power Development Co. Ltd., Tokyo (Japan)

    1997-08-01

    In this paper we describe the features, validation, and illustrative applications of a semi-mechanistic model, INTEGRITY, which calculates the probability of fuel defects due to stress corrosion cracking. The model expresses the defect probability in terms of fundamental parameters such as local stresses, local strains, and fission product concentration. The assessments of defect probability continue to reflect the influence of conventional parameters like ramped power, power-ramp, burnup and Canlub coating. In addition, the INTEGRITY model provides a mechanism to account for the impacts of additional factors involving detailed fuel design and reactor operation. Some examples of the latter include pellet density, pellet shape and size, sheath diameter and thickness, pellet/sheath clearance, coolant temperature and pressure, etc. The model has been fitted to a database of 554 power-ramp irradiations of CANDU fuel with and without Canlub. For this database the INTEGRITY model calculates 75 defects vs 75 actual defects. Similarly good agreements were noted in the different sub-groups of the data involving non-Canlub, thin-Canlub, and thick-Canlub fuel. Moreover, the shapes and the locations of the defect thresholds were consistent with all the above defects as well as with additional 14 ripple defects that were not in the above database. Two illustrative examples demonstrate how the defect thresholds are influenced by changes in the internal design of the fuel element and by extended burnup. (author). 19 refs, 7 figs.

  4. Integrity: A semi-mechanistic model for stress corrosion cracking of fuel

    International Nuclear Information System (INIS)

    Tayal, M.; Hallgrimson, K.; Macquarrie, J.; Alavi, P.; Sato, S.; Kinoshita, Y.; Nishimura, T.

    1997-01-01

    In this paper we describe the features, validation, and illustrative applications of a semi-mechanistic model, INTEGRITY, which calculates the probability of fuel defects due to stress corrosion cracking. The model expresses the defect probability in terms of fundamental parameters such as local stresses, local strains, and fission product concentration. The assessments of defect probability continue to reflect the influence of conventional parameters like ramped power, power-ramp, burnup and Canlub coating. In addition, the INTEGRITY model provides a mechanism to account for the impacts of additional factors involving detailed fuel design and reactor operation. Some examples of the latter include pellet density, pellet shape and size, sheath diameter and thickness, pellet/sheath clearance, coolant temperature and pressure, etc. The model has been fitted to a database of 554 power-ramp irradiations of CANDU fuel with and without Canlub. For this database the INTEGRITY model calculates 75 defects vs 75 actual defects. Similarly good agreements were noted in the different sub-groups of the data involving non-Canlub, thin-Canlub, and thick-Canlub fuel. Moreover, the shapes and the locations of the defect thresholds were consistent with all the above defects as well as with additional 14 ripple defects that were not in the above database. Two illustrative examples demonstrate how the defect thresholds are influenced by changes in the internal design of the fuel element and by extended burnup. (author). 19 refs, 7 figs

  5. Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

    Science.gov (United States)

    He, Yujie; Yang, Jinyan; Zhuang, Qianlai; Harden, Jennifer W.; McGuire, A. David; Liu, Yaling; Wang, Gangsheng; Gu, Lianhong

    2015-01-01

    Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4–0.6) in the simulated spatial pattern of soil RHwith both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = −0.43 to −0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

  6. Application of a Mechanistic Model as a Tool for On-line Monitoring of Pilot Scale Filamentous Fungal Fermentation Processes - The Importance of Evaporation Effects

    DEFF Research Database (Denmark)

    Mears, Lisa; Stocks, Stuart M.; Albæk, Mads Orla

    2017-01-01

    A mechanistic model-based soft sensor is developed and validated for 550L filamentous fungus fermentations operated at Novozymes A/S. The soft sensor is comprised of a parameter estimation block based on a stoichiometric balance, coupled to a dynamic process model. The on-line parameter estimation...... a historical dataset of eleven batches from the fermentation pilot plant (550L) at Novozymes A/S. The model is then implemented on-line in 550L fermentation processes operated at Novozymes A/S in order to validate the state estimator model on fourteen new batches utilizing a new strain. The product...... block models the changing rates of formation of product, biomass, and water, and the rate of consumption of feed using standard, available on-line measurements. This parameter estimation block, is coupled to a mechanistic process model, which solves the current states of biomass, product, substrate...

  7. Detailed Mechanistic Studies on Palladium-Catalyzed Selective C-H Olefination with Aliphatic Alkenes: A Significant Influence of Proton Shuttling.

    Science.gov (United States)

    Deb, Arghya; Hazra, Avijit; Peng, Qian; Paton, Robert S; Maiti, Debabrata

    2017-01-18

    Directing group-assisted regioselective C-H olefination with electronically biased olefins is well studied. However, the incorporation of unactivated olefins has remained largely unsuccessful. A proper mechanistic understanding of olefination involving unactivated alkenes is therefore essential for enhancing their usage in future. In this Article, detailed experimental and computational mechanistic studies on palladium catalyzed C-H olefination with unactivated, aliphatic alkenes are described. The isolation of Pd(II) intermediates is shown to be effective for elucidating the elementary steps involved in catalytic olefination. Reaction rate and order determination, control experiments, isotopic labeling studies, and Hammett analysis have been used to understand the reaction mechanism. The results from these experimental studies implicate β-hydride elimination as the rate-determining step and that a mechanistic switch occurs between cationic and neutral pathway. Computational studies support this interpretation of the experimental evidence and are used to uncover the origins of selectivity.

  8. Incorporating the life course model into MCH nutrition leadership education and training programs.

    Science.gov (United States)

    Haughton, Betsy; Eppig, Kristen; Looney, Shannon M; Cunningham-Sabo, Leslie; Spear, Bonnie A; Spence, Marsha; Stang, Jamie S

    2013-01-01

    Life course perspective, social determinants of health, and health equity have been combined into one comprehensive model, the life course model (LCM), for strategic planning by US Health Resources and Services Administration's Maternal and Child Health Bureau. The purpose of this project was to describe a faculty development process; identify strategies for incorporation of the LCM into nutrition leadership education and training at the graduate and professional levels; and suggest broader implications for training, research, and practice. Nineteen representatives from 6 MCHB-funded nutrition leadership education and training programs and 10 federal partners participated in a one-day session that began with an overview of the models and concluded with guided small group discussions on how to incorporate them into maternal and child health (MCH) leadership training using obesity as an example. Written notes from group discussions were compiled and coded emergently. Content analysis determined the most salient themes about incorporating the models into training. Four major LCM-related themes emerged, three of which were about training: (1) incorporation by training grants through LCM-framed coursework and experiences for trainees, and similarly framed continuing education and skills development for professionals; (2) incorporation through collaboration with other training programs and state and community partners, and through advocacy; and (3) incorporation by others at the federal and local levels through policy, political, and prevention efforts. The fourth theme focused on anticipated challenges of incorporating the model in training. Multiple methods for incorporating the LCM into MCH training and practice are warranted. Challenges to incorporating include the need for research and related policy development.

  9. Process model for ammonia volatilization from anaerobic swine lagoons incorporating varying wind speeds and biogas bubbling

    Science.gov (United States)

    Ammonia volatilization from treatment lagoons varies widely with the total ammonia concentration, pH, temperature, suspended solids, atmospheric ammonia concentration above the water surface, and wind speed. Ammonia emissions were estimated with a process-based mechanistic model integrating ammonia ...

  10. Fidelity in Animal Modeling: Prerequisite for a Mechanistic Research Front Relevant to the Inflammatory Incompetence of Acute Pediatric Malnutrition

    Science.gov (United States)

    Woodward, Bill

    2016-01-01

    Inflammatory incompetence is characteristic of acute pediatric protein-energy malnutrition, but its underlying mechanisms remain obscure. Perhaps substantially because the research front lacks the driving force of a scholarly unifying hypothesis, it is adrift and research activity is declining. A body of animal-based research points to a unifying paradigm, the Tolerance Model, with some potential to offer coherence and a mechanistic impetus to the field. However, reasonable skepticism prevails regarding the relevance of animal models of acute pediatric malnutrition; consequently, the fundamental contributions of the animal-based component of this research front are largely overlooked. Design-related modifications to improve the relevance of animal modeling in this research front include, most notably, prioritizing essential features of pediatric malnutrition pathology rather than dietary minutiae specific to infants and children, selecting windows of experimental animal development that correspond to targeted stages of pediatric immunological ontogeny, and controlling for ontogeny-related confounders. In addition, important opportunities are presented by newer tools including the immunologically humanized mouse and outbred stocks exhibiting a magnitude of genetic heterogeneity comparable to that of human populations. Sound animal modeling is within our grasp to stimulate and support a mechanistic research front relevant to the immunological problems that accompany acute pediatric malnutrition. PMID:27077845

  11. Fidelity in Animal Modeling: Prerequisite for a Mechanistic Research Front Relevant to the Inflammatory Incompetence of Acute Pediatric Malnutrition.

    Science.gov (United States)

    Woodward, Bill

    2016-04-11

    Inflammatory incompetence is characteristic of acute pediatric protein-energy malnutrition, but its underlying mechanisms remain obscure. Perhaps substantially because the research front lacks the driving force of a scholarly unifying hypothesis, it is adrift and research activity is declining. A body of animal-based research points to a unifying paradigm, the Tolerance Model, with some potential to offer coherence and a mechanistic impetus to the field. However, reasonable skepticism prevails regarding the relevance of animal models of acute pediatric malnutrition; consequently, the fundamental contributions of the animal-based component of this research front are largely overlooked. Design-related modifications to improve the relevance of animal modeling in this research front include, most notably, prioritizing essential features of pediatric malnutrition pathology rather than dietary minutiae specific to infants and children, selecting windows of experimental animal development that correspond to targeted stages of pediatric immunological ontogeny, and controlling for ontogeny-related confounders. In addition, important opportunities are presented by newer tools including the immunologically humanized mouse and outbred stocks exhibiting a magnitude of genetic heterogeneity comparable to that of human populations. Sound animal modeling is within our grasp to stimulate and support a mechanistic research front relevant to the immunological problems that accompany acute pediatric malnutrition.

  12. 75 FR 20265 - Airworthiness Directives; Liberty Aerospace Incorporated Model XL-2 Airplanes

    Science.gov (United States)

    2010-04-19

    ... Office, 1701 Columbia Avenue, College Park, Georgia 30337; telephone: (404) 474-5524; facsimile: (404... Airworthiness Directives; Liberty Aerospace Incorporated Model XL-2 Airplanes AGENCY: Federal Aviation...-08- 05, which applies to certain Liberty Aerospace Incorporated Model XL-2 airplanes. AD 2009-08-05...

  13. Simulating soil C stability with mechanistic systems models: a multisite comparison of measured fractions and modelled pools

    Science.gov (United States)

    Robertson, Andy; Schipanski, Meagan; Sherrod, Lucretia; Ma, Liwang; Ahuja, Lajpat; McNamara, Niall; Smith, Pete; Davies, Christian

    2016-04-01

    Agriculture, covering more than 30% of global land area, has an exciting opportunity to help combat climate change by effectively managing its soil to promote increased C sequestration. Further, newly sequestered soil carbon (C) through agriculture needs to be stored in more stable forms in order to have a lasting impact on reducing atmospheric CO2 concentrations. While land uses in different climates and soils require different management strategies, the fundamental mechanisms that regulate C sequestration and stabilisation remain the same. These mechanisms are used by a number of different systems models to simulate C dynamics, and thus assess the impacts of change in management or climate. To evaluate the accuracy of these model simulations, our research uses a multidirectional approach to compare C stocks of physicochemical soil fractions collected at two long-term agricultural sites. Carbon stocks for a number of soil fractions were measured at two sites (Lincoln, UK; Colorado, USA) over 8 and 12 years, respectively. Both sites represent managed agricultural land but have notably different climates and levels of disturbance. The measured soil fractions act as proxies for varying degrees of stability, with C contained within these fractions relatable to the C simulated within the soil pools of mechanistic systems models1. Using stable isotope techniques at the UK site, specific turnover times of C within the different fractions were determined and compared with those simulated in the pools of 3 different models of varying complexity (RothC, DayCent and RZWQM2). Further, C dynamics and N-mineralisation rates of the measured fractions at the US site were assessed and compared to results of the same three models. The UK site saw a significant increase in C stocks within the most stable fractions, with topsoil (0-30cm) sequestration rates of just over 0.3 tC ha-1 yr-1 after only 8 years. Further, the sum of all fractions reported C sequestration rates of nearly 1

  14. Incorporation of Uranium into Hematite during Crystallization from Ferrihydrite

    Science.gov (United States)

    2014-01-01

    Ferrihydrite was exposed to U(VI)-containing cement leachate (pH 10.5) and aged to induce crystallization of hematite. A combination of chemical extractions, TEM, and XAS techniques provided the first evidence that adsorbed U(VI) (≈3000 ppm) was incorporated into hematite during ferrihydrite aggregation and the early stages of crystallization, with continued uptake occurring during hematite ripening. Analysis of EXAFS and XANES data indicated that the U(VI) was incorporated into a distorted, octahedrally coordinated site replacing Fe(III). Fitting of the EXAFS showed the uranyl bonds lengthened from 1.81 to 1.87 Å, in contrast to previous studies that have suggested that the uranyl bond is lost altogether upon incorporation into hematite. The results of this study both provide a new mechanistic understanding of uranium incorporation into hematite and define the nature of the bonding environment of uranium within the mineral structure. Immobilization of U(VI) by incorporation into hematite has clear and important implications for limiting uranium migration in natural and engineered environments. PMID:24580024

  15. Predicting the impact of long-term temperature changes on the epidemiology and control of schistosomiasis: a mechanistic model.

    Directory of Open Access Journals (Sweden)

    Tara D Mangal

    2008-01-01

    Full Text Available Many parasites of medical and veterinary importance are transmitted by cold-blooded intermediate hosts or vectors, the abundance of which will vary with ambient temperatures, potentially altering disease prevalence. In particular, if global climate change will increase mean ambient temperature in a region endemic with a human pathogen then it is possible that the incidence of disease will similarly increase. Here we examine this possibility by using a mathematical model to explore the effects of increasing long-term mean ambient temperature on the prevalence and abundance of the parasite Schistosoma mansoni, the causative agent of schistosomiasis in humans.The model showed that the impact of temperature on disease prevalence and abundance is not straightforward; the mean infection burden in humans increases up to 30 degrees C, but then crashes at 35 degrees C, primarily due to increased mortalities of the snail intermediate host. In addition, increased temperatures changed the dynamics of disease from stable, endemic infection to unstable, epidemic cycles at 35 degrees C. However, the prevalence of infection was largely unchanged by increasing temperatures. Temperature increases also affected the response of the model to changes in each parameter, indicating certain control strategies may become less effective with local temperature changes. At lower temperatures, the most effective single control strategy is to target the adult parasites through chemotherapy. However, as temperatures increase, targeting the snail intermediate hosts, for example through molluscicide use, becomes more effective.These results show that S. mansoni will not respond to increased temperatures in a linear fashion, and the optimal control strategy is likely to change as temperatures change. It is only through a mechanistic approach, incorporating the combined effects of temperature on all stages of the life-cycle, that we can begin to predict the consequences of climate

  16. Mechanistic-empirical subgrade design model based on heavy vehicle simulator test results

    CSIR Research Space (South Africa)

    Theyse, HL

    2006-06-01

    Full Text Available Although Accelerated Pavement Testing (APT) is often done with specific objectives, valuable pavement performance data is generated over the long-term that may be used to investigate pavement behaviour in general and calibrate mechanistic...

  17. Evaluation of five dry particle deposition parameterizations for incorporation into atmospheric transport models

    Science.gov (United States)

    Khan, Tanvir R.; Perlinger, Judith A.

    2017-10-01

    Despite considerable effort to develop mechanistic dry particle deposition parameterizations for atmospheric transport models, current knowledge has been inadequate to propose quantitative measures of the relative performance of available parameterizations. In this study, we evaluated the performance of five dry particle deposition parameterizations developed by Zhang et al. (2001) (Z01), Petroff and Zhang (2010) (PZ10), Kouznetsov and Sofiev (2012) (KS12), Zhang and He (2014) (ZH14), and Zhang and Shao (2014) (ZS14), respectively. The evaluation was performed in three dimensions: model ability to reproduce observed deposition velocities, Vd (accuracy); the influence of imprecision in input parameter values on the modeled Vd (uncertainty); and identification of the most influential parameter(s) (sensitivity). The accuracy of the modeled Vd was evaluated using observations obtained from five land use categories (LUCs): grass, coniferous and deciduous forests, natural water, and ice/snow. To ascertain the uncertainty in modeled Vd, and quantify the influence of imprecision in key model input parameters, a Monte Carlo uncertainty analysis was performed. The Sobol' sensitivity analysis was conducted with the objective to determine the parameter ranking from the most to the least influential. Comparing the normalized mean bias factors (indicators of accuracy), we find that the ZH14 parameterization is the most accurate for all LUCs except for coniferous forest, for which it is second most accurate. From Monte Carlo simulations, the estimated mean normalized uncertainties in the modeled Vd obtained for seven particle sizes (ranging from 0.005 to 2.5 µm) for the five LUCs are 17, 12, 13, 16, and 27 % for the Z01, PZ10, KS12, ZH14, and ZS14 parameterizations, respectively. From the Sobol' sensitivity results, we suggest that the parameter rankings vary by particle size and LUC for a given parameterization. Overall, for dp = 0.001 to 1.0 µm, friction velocity was one of

  18. Regulatory Technology Development Plan - Sodium Fast Reactor: Mechanistic Source Term - Trial Calculation

    International Nuclear Information System (INIS)

    Grabaskas, David

    2016-01-01

    The potential release of radioactive material during a plant incident, referred to as the source term, is a vital design metric and will be a major focus of advanced reactor licensing. The U.S. Nuclear Regulatory Commission has stated an expectation for advanced reactor vendors to present a mechanistic assessment of the potential source term in their license applications. The mechanistic source term presents an opportunity for vendors to realistically assess the radiological consequences of an incident, and may allow reduced emergency planning zones and smaller plant sites. However, the development of a mechanistic source term for advanced reactors is not without challenges, as there are often numerous phenomena impacting the transportation and retention of radionuclides. This project sought to evaluate U.S. capabilities regarding the mechanistic assessment of radionuclide release from core damage incidents at metal fueled, pool-type sodium fast reactors (SFRs). The purpose of the analysis was to identify, and prioritize, any gaps regarding computational tools or data necessary for the modeling of radionuclide transport and retention phenomena. To accomplish this task, a parallel-path analysis approach was utilized. One path, led by Argonne and Sandia National Laboratories, sought to perform a mechanistic source term assessment using available codes, data, and models, with the goal to identify gaps in the current knowledge base. The second path, performed by an independent contractor, performed sensitivity analyses to determine the importance of particular radionuclides and transport phenomena in regards to offsite consequences. The results of the two pathways were combined to prioritize gaps in current capabilities.

  19. Study of n-Butyl Acrylate Self-Initiation Reaction Experimentally and via Macroscopic Mechanistic Modeling

    Directory of Open Access Journals (Sweden)

    Ahmad Arabi Shamsabadi

    2016-04-01

    Full Text Available This paper presents an experimental study of the self-initiation reaction of n-butyl acrylate (n-BA in free-radical polymerization. For the first time, the frequency factor and activation energy of the monomer self-initiation reaction are estimated from measurements of n-BA conversion in free-radical homo-polymerization initiated only by the monomer. The estimation was carried out using a macroscopic mechanistic mathematical model of the reactor. In addition to already-known reactions that contribute to the polymerization, the model considers a n-BA self-initiation reaction mechanism that is based on our previous electronic-level first-principles theoretical study of the self-initiation reaction. Reaction rate equations are derived using the method of moments. The reaction-rate parameter estimates obtained from conversion measurements agree well with estimates obtained via our purely-theoretical quantum chemical calculations.

  20. In silico, experimental, mechanistic model for extended-release felodipine disposition exhibiting complex absorption and a highly variable food interaction.

    Directory of Open Access Journals (Sweden)

    Sean H J Kim

    Full Text Available The objective of this study was to develop and explore new, in silico experimental methods for deciphering complex, highly variable absorption and food interaction pharmacokinetics observed for a modified-release drug product. Toward that aim, we constructed an executable software analog of study participants to whom product was administered orally. The analog is an object- and agent-oriented, discrete event system, which consists of grid spaces and event mechanisms that map abstractly to different physiological features and processes. Analog mechanisms were made sufficiently complicated to achieve prespecified similarity criteria. An equation-based gastrointestinal transit model with nonlinear mixed effects analysis provided a standard for comparison. Subject-specific parameterizations enabled each executed analog's plasma profile to mimic features of the corresponding six individual pairs of subject plasma profiles. All achieved prespecified, quantitative similarity criteria, and outperformed the gastrointestinal transit model estimations. We observed important subject-specific interactions within the simulation and mechanistic differences between the two models. We hypothesize that mechanisms, events, and their causes occurring during simulations had counterparts within the food interaction study: they are working, evolvable, concrete theories of dynamic interactions occurring within individual subjects. The approach presented provides new, experimental strategies for unraveling the mechanistic basis of complex pharmacological interactions and observed variability.

  1. Modelling pesticide volatilization after soil application using the mechanistic model Volt'Air

    Science.gov (United States)

    Bedos, Carole; Génermont, Sophie; Le Cadre, Edith; Garcia, Lucas; Barriuso, Enrique; Cellier, Pierre

    Volatilization of pesticides participates in atmospheric contamination and affects environmental ecosystems including human welfare. Modelling at relevant time and spatial scales is needed to better understand the complex processes involved in pesticide volatilization. Volt'Air-Pesticides has been developed following a two-step procedure to study pesticide volatilization at the field scale and at a quarter time step. Firstly, Volt'Air-NH 3 was adapted by extending the initial transfer of solutes to pesticides and by adding specific calculations for physico-chemical equilibriums as well as for the degradation of pesticides in soil. Secondly, the model was evaluated in terms of 3 pesticides applied on bare soil (atrazine, alachlor, and trifluralin) which display a wide range of volatilization rates. A sensitivity analysis confirmed the relevance of tuning to K h. Then, using Volt'Air-Pesticides, environmental conditions and emission fluxes of the pesticides were compared to fluxes measured under 2 environmental conditions. The model fairly well described water temporal dynamics, soil surface temperature, and energy budget. Overall, Volt'Air-Pesticides estimates of the order of magnitude of the volatilization flux of all three compounds were in good agreement with the field measurements. The model also satisfactorily simulated the decrease in the volatilization rate of the three pesticides during night-time as well as the decrease in the soil surface residue of trifluralin before and after incorporation. However, the timing of the maximum flux rate during the day was not correctly described, thought to be linked to an increased adsorption under dry soil conditions. Thanks to Volt'Air's capacity to deal with pedo-climatic conditions, several existing parameterizations describing adsorption as a function of soil water content could be tested. However, this point requires further investigation. Practically speaking, Volt'Air-Pesticides can be a useful tool to make

  2. Exploring BSEP Inhibition-Mediated Toxicity with a Mechanistic Model of Drug-Induced Liver Injury

    Directory of Open Access Journals (Sweden)

    Jeffrey L Woodhead

    2014-11-01

    Full Text Available Inhibition of the bile salt export pump (BSEP has been linked to incidence of drug-induced liver injury (DILI, presumably by the accumulation of toxic bile acids in the liver. We have previously constructed and validated a model of bile acid disposition within DILIsym®, a mechanistic model of DILI. In this paper, we use DILIsym® to simulate the DILI response of the hepatotoxic BSEP inhibitors bosentan and CP-724,714 and the non-hepatotoxic BSEP inhibitor telmisartan in humans in order to explore whether we can predict that hepatotoxic BSEP inhibitors can cause bile acid accumulation to reach toxic levels. We also simulate bosentan in rats in order to illuminate potential reasons behind the lack of toxicity in rats compared to the toxicity observed in humans. DILIsym® predicts that bosentan, but not telmisartan, will cause mild hepatocellular ATP decline and serum ALT elevation in a simulated population of humans. The difference in hepatotoxic potential between bosentan and telmisartan is consistent with clinical observations. However, DILIsym® underpredicts the incidence of bosentan toxicity. DILIsym® also predicts that bosentan will not cause toxicity in a simulated population of rats, and that the difference between the response to bosentan in rats and in humans is primarily due to the less toxic bile acid pool in rats. Our simulations also suggest a potential synergistic role for bile acid accumulation and mitochondrial electron transport chain inhibition in producing the observed toxicity in CP-724,714, and suggest that CP-724,714 metabolites may also play a role in the observed toxicity. Our work also compares the impact of competitive and noncompetitive BSEP inhibition for CP-724,714 and demonstrates that noncompetitive inhibition leads to much greater bile acid accumulation and potential toxicity. Our research demonstrates the potential for mechanistic modeling to contribute to the understanding of how bile acid transport inhibitors

  3. Statistical methods for mechanistic model validation: Salt Repository Project

    International Nuclear Information System (INIS)

    Eggett, D.L.

    1988-07-01

    As part of the Department of Energy's Salt Repository Program, Pacific Northwest Laboratory (PNL) is studying the emplacement of nuclear waste containers in a salt repository. One objective of the SRP program is to develop an overall waste package component model which adequately describes such phenomena as container corrosion, waste form leaching, spent fuel degradation, etc., which are possible in the salt repository environment. The form of this model will be proposed, based on scientific principles and relevant salt repository conditions with supporting data. The model will be used to predict the future characteristics of the near field environment. This involves several different submodels such as the amount of time it takes a brine solution to contact a canister in the repository, how long it takes a canister to corrode and expose its contents to the brine, the leach rate of the contents of the canister, etc. These submodels are often tested in a laboratory and should be statistically validated (in this context, validate means to demonstrate that the model adequately describes the data) before they can be incorporated into the waste package component model. This report describes statistical methods for validating these models. 13 refs., 1 fig., 3 tabs

  4. Simulating polar bear energetics during a seasonal fast using a mechanistic model.

    Directory of Open Access Journals (Sweden)

    Paul D Mathewson

    Full Text Available In this study we tested the ability of a mechanistic model (Niche Mapper™ to accurately model adult, non-denning polar bear (Ursus maritimus energetics while fasting during the ice-free season in the western Hudson Bay. The model uses a steady state heat balance approach, which calculates the metabolic rate that will allow an animal to maintain its core temperature in its particular microclimate conditions. Predicted weight loss for a 120 day fast typical of the 1990s was comparable to empirical studies of the population, and the model was able to reach a heat balance at the target metabolic rate for the entire fast, supporting use of the model to explore the impacts of climate change on polar bears. Niche Mapper predicted that all but the poorest condition bears would survive a 120 day fast under current climate conditions. When the fast extended to 180 days, Niche Mapper predicted mortality of up to 18% for males. Our results illustrate how environmental conditions, variation in animal properties, and thermoregulation processes may impact survival during extended fasts because polar bears were predicted to require additional energetic expenditure for thermoregulation during a 180 day fast. A uniform 3°C temperature increase reduced male mortality during a 180 day fast from 18% to 15%. Niche Mapper explicitly links an animal's energetics to environmental conditions and thus can be a valuable tool to help inform predictions of climate-related population changes. Since Niche Mapper is a generic model, it can make energetic predictions for other species threatened by climate change.

  5. Simulating polar bear energetics during a seasonal fast using a mechanistic model.

    Science.gov (United States)

    Mathewson, Paul D; Porter, Warren P

    2013-01-01

    In this study we tested the ability of a mechanistic model (Niche Mapper™) to accurately model adult, non-denning polar bear (Ursus maritimus) energetics while fasting during the ice-free season in the western Hudson Bay. The model uses a steady state heat balance approach, which calculates the metabolic rate that will allow an animal to maintain its core temperature in its particular microclimate conditions. Predicted weight loss for a 120 day fast typical of the 1990s was comparable to empirical studies of the population, and the model was able to reach a heat balance at the target metabolic rate for the entire fast, supporting use of the model to explore the impacts of climate change on polar bears. Niche Mapper predicted that all but the poorest condition bears would survive a 120 day fast under current climate conditions. When the fast extended to 180 days, Niche Mapper predicted mortality of up to 18% for males. Our results illustrate how environmental conditions, variation in animal properties, and thermoregulation processes may impact survival during extended fasts because polar bears were predicted to require additional energetic expenditure for thermoregulation during a 180 day fast. A uniform 3°C temperature increase reduced male mortality during a 180 day fast from 18% to 15%. Niche Mapper explicitly links an animal's energetics to environmental conditions and thus can be a valuable tool to help inform predictions of climate-related population changes. Since Niche Mapper is a generic model, it can make energetic predictions for other species threatened by climate change.

  6. Regulatory Technology Development Plan - Sodium Fast Reactor: Mechanistic Source Term – Trial Calculation

    Energy Technology Data Exchange (ETDEWEB)

    Grabaskas, David [Argonne National Lab. (ANL), Argonne, IL (United States). Nuclear Engineering Division; Bucknor, Matthew [Argonne National Lab. (ANL), Argonne, IL (United States). Nuclear Engineering Division; Jerden, James [Argonne National Lab. (ANL), Argonne, IL (United States). Nuclear Engineering Division; Brunett, Acacia J. [Argonne National Lab. (ANL), Argonne, IL (United States). Nuclear Engineering Division; Denman, Matthew [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Nuclear Engineering Division; Clark, Andrew [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Nuclear Engineering Division; Denning, Richard S. [Consultant, Columbus, OH (United States)

    2016-10-01

    The potential release of radioactive material during a plant incident, referred to as the source term, is a vital design metric and will be a major focus of advanced reactor licensing. The U.S. Nuclear Regulatory Commission has stated an expectation for advanced reactor vendors to present a mechanistic assessment of the potential source term in their license applications. The mechanistic source term presents an opportunity for vendors to realistically assess the radiological consequences of an incident, and may allow reduced emergency planning zones and smaller plant sites. However, the development of a mechanistic source term for advanced reactors is not without challenges, as there are often numerous phenomena impacting the transportation and retention of radionuclides. This project sought to evaluate U.S. capabilities regarding the mechanistic assessment of radionuclide release from core damage incidents at metal fueled, pool-type sodium fast reactors (SFRs). The purpose of the analysis was to identify, and prioritize, any gaps regarding computational tools or data necessary for the modeling of radionuclide transport and retention phenomena. To accomplish this task, a parallel-path analysis approach was utilized. One path, led by Argonne and Sandia National Laboratories, sought to perform a mechanistic source term assessment using available codes, data, and models, with the goal to identify gaps in the current knowledge base. The second path, performed by an independent contractor, performed sensitivity analyses to determine the importance of particular radionuclides and transport phenomena in regards to offsite consequences. The results of the two pathways were combined to prioritize gaps in current capabilities.

  7. Verification of mechanistic-empirical design models for flexible pavements through accelerated pavement testing.

    Science.gov (United States)

    2014-08-01

    The Midwest States Accelerated Pavement Testing Pooled Fund Program, financed by the highway : departments of Kansas, Iowa, and Missouri, has supported an accelerated pavement testing (APT) project to : validate several models incorporated in the NCH...

  8. Incorporation of the capillary hysteresis model HYSTR into the numerical code TOUGH

    International Nuclear Information System (INIS)

    Niemi, A.; Bodvarsson, G.S.; Pruess, K.

    1991-11-01

    As part of the work performed to model flow in the unsaturated zone at Yucca Mountain Nevada, a capillary hysteresis model has been developed. The computer program HYSTR has been developed to compute the hysteretic capillary pressure -- liquid saturation relationship through interpolation of tabulated data. The code can be easily incorporated into any numerical unsaturated flow simulator. A complete description of HYSTR, including a brief summary of the previous hysteresis literature, detailed description of the program, and instructions for its incorporation into a numerical simulator are given in the HYSTR user's manual (Niemi and Bodvarsson, 1991a). This report describes the incorporation of HYSTR into the numerical code TOUGH (Transport of Unsaturated Groundwater and Heat; Pruess, 1986). The changes made and procedures for the use of TOUGH for hysteresis modeling are documented

  9. Modeling and validation of a mechanistic tool (MEFISTO) for the prediction of critical power in BWR fuel assemblies

    International Nuclear Information System (INIS)

    Adamsson, Carl; Le Corre, Jean-Marie

    2011-01-01

    Highlights: → The MEFISTO code efficiently and accurately predicts the dryout event in a BWR fuel bundle, using a mechanistic model. → A hybrid approach between a fast and robust sub-channel analysis and a three-field two-phase analysis is adopted. → MEFISTO modeling approach, calibration, CPU usage, sensitivity, trend analysis and performance evaluation are presented. → The calibration parameters and process were carefully selected to preserve the mechanistic nature of the code. → The code dryout prediction performance is near the level of fuel-specific empirical dryout correlations. - Abstract: Westinghouse is currently developing the MEFISTO code with the main goal to achieve fast, robust, practical and reliable prediction of steady-state dryout Critical Power in Boiling Water Reactor (BWR) fuel bundle based on a mechanistic approach. A computationally efficient simulation scheme was used to achieve this goal, where the code resolves all relevant field (drop, steam and multi-film) mass balance equations, within the annular flow region, at the sub-channel level while relying on a fast and robust two-phase (liquid/steam) sub-channel solution to provide the cross-flow information. The MEFISTO code can hence provide highly detailed solution of the multi-film flow in BWR fuel bundle while enhancing flexibility and reducing the computer time by an order of magnitude as compared to a standard three-field sub-channel analysis approach. Models for the numerical computation of the one-dimensional field flowrate distributions in an open channel (e.g. a sub-channel), including the numerical treatment of field cross-flows, part-length rods, spacers grids and post-dryout conditions are presented in this paper. The MEFISTO code is then applied to dryout prediction in BWR fuel bundle using VIPRE-W as a fast and robust two-phase sub-channel driver code. The dryout power is numerically predicted by iterating on the bundle power so that the minimum film flowrate in the

  10. Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

    Energy Technology Data Exchange (ETDEWEB)

    He, Yujie [Purdue Univ., West Lafayette, IN (United States). Dept. of Earth, Atmospheric, and Planetary Sciences; Yang, Jinyan [Univ. of Georgia, Athens, GA (United States). Warnell School of Forestry and Natural Resources; Northeast Forestry Univ., Harbin (China). Center for Ecological Research; Zhuang, Qianlai [Purdue Univ., West Lafayette, IN (United States). Dept. of Earth, Atmospheric, and Planetary Sciences; Purdue Univ., West Lafayette, IN (United States). Dept. of Agronomy; Harden, Jennifer W. [U.S. Geological Survey, Menlo Park, CA (United States); McGuire, Anthony D. [Alaska Cooperative Fish and Wildlife Research Unit, U.S. Geological Survey, Univ. of Alaska, Fairbanks, AK (United States). U.S. Geological Survey, Alaska Cooperative Fish and Wildlife Research Unit; Liu, Yaling [Purdue Univ., West Lafayette, IN (United States). Dept. of Earth, Atmospheric, and Planetary Sciences; Wang, Gangsheng [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Climate Change Science Inst. and Environmental Sciences Division; Gu, Lianhong [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Environmental Sciences Division

    2015-11-20

    Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here in this study we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil RH (7.5 ± 2.4 PgCyr-1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4-0.6) in the simulated spatial pattern of soil RH with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = -0.43 to -0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

  11. Application of response surface methodology and semi-mechanistic model to optimize fluoride removal using crushed concrete in a fixed-bed column.

    Science.gov (United States)

    Gu, Bon-Wun; Lee, Chang-Gu; Park, Seong-Jik

    2018-03-01

    The aim of this study was to investigate the removal of fluoride from aqueous solutions by using crushed concrete fines as a filter medium under varying conditions of pH 3-7, flow rate of 0.3-0.7 mL/min, and filter depth of 10-20 cm. The performance of fixed-bed columns was evaluated on the basis of the removal ratio (Re), uptake capacity (qe), degree of sorbent used (DoSU), and sorbent usage rate (SUR) obtained from breakthrough curves (BTCs). Three widely used semi-mechanistic models, that is, Bohart-Adams, Thomas, and Yoon-Nelson models, were applied to simulate the BTCs and to derive the design parameters. The Box-Behnken design of response surface methodology (RSM) was used to elucidate the individual and interactive effects of the three operational parameters on the column performance and to optimize these parameters. The results demonstrated that pH is the most important factor in the performance of fluoride removal by a fixed-bed column. The flow rate had a significant negative influence on Re and DoSU, and the effect of filter depth was observed only in the regression model for DoSU. Statistical analysis indicated that the model attained from the RSM study is suitable for describing the semi-mechanistic model parameters.

  12. Exposure factors for marine eutrophication impacts assessment based on a mechanistic biological model

    DEFF Research Database (Denmark)

    Cosme, Nuno Miguel Dias; Koski, Marja; Hauschild, Michael Zwicky

    2015-01-01

    marine ecosystem (LME), five climate zones, and site-generic. The XFs obtained range from 0.45 (Central Arctic Ocean) to 15.9kgO2kgN-1 (Baltic Sea). While LME resolution is recommended, aggregated PE or XF per climate zone can be adopted, but not global aggregation due to high variability. The XF......Emissions of nitrogen (N) from anthropogenic sources enrich marine waters and promote planktonic growth. This newly synthesised organic carbon is eventually exported to benthic waters where aerobic respiration by heterotrophic bacteria results in the consumption of dissolved oxygen (DO......). This pathway is typical of marine eutrophication. A model is proposed to mechanistically estimate the response of coastal marine ecosystems to N inputs. It addresses the biological processes of nutrient-limited primary production (PP), metazoan consumption, and bacterial degradation, in four distinct sinking...

  13. Evaluation of five dry particle deposition parameterizations for incorporation into atmospheric transport models

    Directory of Open Access Journals (Sweden)

    T. R. Khan

    2017-10-01

    Full Text Available Despite considerable effort to develop mechanistic dry particle deposition parameterizations for atmospheric transport models, current knowledge has been inadequate to propose quantitative measures of the relative performance of available parameterizations. In this study, we evaluated the performance of five dry particle deposition parameterizations developed by Zhang et al. (2001 (Z01, Petroff and Zhang (2010 (PZ10, Kouznetsov and Sofiev (2012 (KS12, Zhang and He (2014 (ZH14, and Zhang and Shao (2014 (ZS14, respectively. The evaluation was performed in three dimensions: model ability to reproduce observed deposition velocities, Vd (accuracy; the influence of imprecision in input parameter values on the modeled Vd (uncertainty; and identification of the most influential parameter(s (sensitivity. The accuracy of the modeled Vd was evaluated using observations obtained from five land use categories (LUCs: grass, coniferous and deciduous forests, natural water, and ice/snow. To ascertain the uncertainty in modeled Vd, and quantify the influence of imprecision in key model input parameters, a Monte Carlo uncertainty analysis was performed. The Sobol' sensitivity analysis was conducted with the objective to determine the parameter ranking from the most to the least influential. Comparing the normalized mean bias factors (indicators of accuracy, we find that the ZH14 parameterization is the most accurate for all LUCs except for coniferous forest, for which it is second most accurate. From Monte Carlo simulations, the estimated mean normalized uncertainties in the modeled Vd obtained for seven particle sizes (ranging from 0.005 to 2.5 µm for the five LUCs are 17, 12, 13, 16, and 27 % for the Z01, PZ10, KS12, ZH14, and ZS14 parameterizations, respectively. From the Sobol' sensitivity results, we suggest that the parameter rankings vary by particle size and LUC for a given parameterization. Overall, for dp  =  0.001 to 1.0

  14. Polymerization kinetics of wheat gluten upon thermosetting. A mechanistic model.

    Science.gov (United States)

    Domenek, Sandra; Morel, Marie-Hélène; Bonicel, Joëlle; Guilbert, Stéphane

    2002-10-09

    Size exclusion high-performance liquid chromatography analysis was carried out on wheat gluten-glycerol blends subjected to different heat treatments. The elution profiles were analyzed in order to follow the solubility loss of protein fractions with specific molecular size. Owing to the known biochemical changes involved during the heat denaturation of gluten, a mechanistic mathematical model was developed, which divided the protein denaturation into two distinct reaction steps: (i) reversible change in protein conformation and (ii) protein precipitation through disulfide bonding between initially SDS-soluble and SDS-insoluble reaction partners. Activation energies of gluten unfolding, refolding, and precipitation were calculated with the Arrhenius law to 53.9 kJ x mol(-1), 29.5 kJ x mol(-1), and 172 kJ x mol(-1), respectively. The rate of protein solubility loss decreased as the cross-linking reaction proceeded, which may be attributed to the formation of a three-dimensional network progressively hindering the reaction. The enhanced susceptibility to aggregation of large molecules was assigned to a risen reaction probability due to their higher number of cysteine residues and to the increased percentage of unfolded and thereby activated proteins as complete protein refolding seemed to be an anticooperative process.

  15. Mechanistic Mathematical Modeling Tests Hypotheses of the Neurovascular Coupling in fMRI.

    Directory of Open Access Journals (Sweden)

    Karin Lundengård

    2016-06-01

    Full Text Available Functional magnetic resonance imaging (fMRI measures brain activity by detecting the blood-oxygen-level dependent (BOLD response to neural activity. The BOLD response depends on the neurovascular coupling, which connects cerebral blood flow, cerebral blood volume, and deoxyhemoglobin level to neuronal activity. The exact mechanisms behind this neurovascular coupling are not yet fully investigated. There are at least three different ways in which these mechanisms are being discussed. Firstly, mathematical models involving the so-called Balloon model describes the relation between oxygen metabolism, cerebral blood volume, and cerebral blood flow. However, the Balloon model does not describe cellular and biochemical mechanisms. Secondly, the metabolic feedback hypothesis, which is based on experimental findings on metabolism associated with brain activation, and thirdly, the neurotransmitter feed-forward hypothesis which describes intracellular pathways leading to vasoactive substance release. Both the metabolic feedback and the neurotransmitter feed-forward hypotheses have been extensively studied, but only experimentally. These two hypotheses have never been implemented as mathematical models. Here we investigate these two hypotheses by mechanistic mathematical modeling using a systems biology approach; these methods have been used in biological research for many years but never been applied to the BOLD response in fMRI. In the current work, model structures describing the metabolic feedback and the neurotransmitter feed-forward hypotheses were applied to measured BOLD responses in the visual cortex of 12 healthy volunteers. Evaluating each hypothesis separately shows that neither hypothesis alone can describe the data in a biologically plausible way. However, by adding metabolism to the neurotransmitter feed-forward model structure, we obtained a new model structure which is able to fit the estimation data and successfully predict new

  16. Simulating the effects of climate change on the distribution of an invasive plant, using a high resolution, local scale, mechanistic approach: challenges and insights.

    Science.gov (United States)

    Fennell, Mark; Murphy, James E; Gallagher, Tommy; Osborne, Bruce

    2013-04-01

    The growing economic and ecological damage associated with biological invasions, which will likely be exacerbated by climate change, necessitates improved projections of invasive spread. Generally, potential changes in species distribution are investigated using climate envelope models; however, the reliability of such models has been questioned and they are not suitable for use at local scales. At this scale, mechanistic models are more appropriate. This paper discusses some key requirements for mechanistic models and utilises a newly developed model (PSS[gt]) that incorporates the influence of habitat type and related features (e.g., roads and rivers), as well as demographic processes and propagule dispersal dynamics, to model climate induced changes in the distribution of an invasive plant (Gunnera tinctoria) at a local scale. A new methodology is introduced, dynamic baseline benchmarking, which distinguishes climate-induced alterations in species distributions from other potential drivers of change. Using this approach, it was concluded that climate change, based on IPCC and C4i projections, has the potential to increase the spread-rate and intensity of G. tinctoria invasions. Increases in the number of individuals were primarily due to intensification of invasion in areas already invaded or in areas projected to be invaded in the dynamic baseline scenario. Temperature had the largest influence on changes in plant distributions. Water availability also had a large influence and introduced the most uncertainty in the projections. Additionally, due to the difficulties of parameterising models such as this, the process has been streamlined by utilising methods for estimating unknown variables and selecting only essential parameters. © 2012 Blackwell Publishing Ltd.

  17. Controls on the spatial variability of key soil properties: comparing field data with a mechanistic soilscape evolution model

    Science.gov (United States)

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

    2016-12-01

    There is a need for better understanding the processes influencing soil formation and the resulting distribution of soil properties. Soil properties can exhibit strong spatial variation, even at the small catchment scale. Especially soil carbon pools in semi-arid, mountainous areas are highly uncertain because bulk density and stoniness are very heterogeneous and rarely measured explicitly. In this study, we explore the spatial variability in key soil properties (soil carbon stocks, stoniness, bulk density and soil depth) as a function of processes shaping the critical zone (weathering, erosion, soil water fluxes and vegetation patterns). We also compare the potential of a geostatistical versus a mechanistic soil formation model (MILESD) for predicting these key soil properties. Soil core samples were collected from 67 locations at 6 depths. Total soil organic carbon stocks were 4.38 kg m-2. Solar radiation proved to be the key variable controlling soil carbon distribution. Stone content was mostly controlled by slope, indicating the importance of erosion. Spatial distribution of bulk density was found to be highly random. Finally, total carbon stocks were predicted using a random forest model whose main covariates were solar radiation and NDVI. The model predicts carbon stocks that are double as high on north versus south-facing slopes. However, validation showed that these covariates only explained 25% of the variation in the dataset. Apparently, present-day landscape and vegetation properties are not sufficient to fully explain variability in the soil carbon stocks in this complex terrain under natural vegetation. This is attributed to a high spatial variability in bulk density and stoniness, key variables controlling carbon stocks. Similar results were obtained with the mechanistic soil formation model MILESD, suggesting that more complex models might be needed to further explore this high spatial variability.

  18. A mechanistic model for long-term nuclear waste glass dissolution integrating chemical affinity and interfacial diffusion barrier

    Energy Technology Data Exchange (ETDEWEB)

    Ma, Teqi [Northwest Institute of Nuclear Technology, No.28 Pingyu Road, Baqiao District, Xi' an,Shaanxi, 710024 (China); Mechanics and Physics of Solids Research Group, Modelling and Simulation Centre, The University of Manchester, Oxford Road, Manchester, M13 9PL (United Kingdom); Jivkov, Andrey P., E-mail: andrey.jivkov@manchester.ac.uk [Mechanics and Physics of Solids Research Group, Modelling and Simulation Centre, The University of Manchester, Oxford Road, Manchester, M13 9PL (United Kingdom); Li, Weiping; Liang, Wei; Wang, Yu; Xu, Hui [Northwest Institute of Nuclear Technology, No.28 Pingyu Road, Baqiao District, Xi' an,Shaanxi, 710024 (China); Han, Xiaoyuan, E-mail: xyhan_nint@sina.cn [Northwest Institute of Nuclear Technology, No.28 Pingyu Road, Baqiao District, Xi' an,Shaanxi, 710024 (China)

    2017-04-01

    Understanding the alteration of nuclear waste glass in geological repository conditions is critical element of the analysis of repository retention function. Experimental observations of glass alterations provide a general agreement on the following regimes: inter-diffusion, hydrolysis process, rate drop, residual rate and, under very particular conditions, resumption of alteration. Of these, the mechanisms controlling the rate drop and the residual rate remain a subject of dispute. This paper offers a critical review of the two most competitive models related to these regimes: affinity–limited dissolution and diffusion barrier. The limitations of these models are highlighted by comparison of their predictions with available experimental evidence. Based on the comprehensive discussion of the existing models, a new mechanistic model is proposed as a combination of the chemical affinity and diffusion barrier concepts. It is demonstrated how the model can explain experimental phenomena and data, for which the existing models are shown to be not fully adequate.

  19. Molten fuel motion during a fast-reactor overpower transient

    International Nuclear Information System (INIS)

    Kolesar, D.C.; Padilla, A. Jr.; Lewis, C.H.; Waltar, A.E.

    1976-01-01

    Mechanistic models for postfailure fuel behavior during hypothetical transient overpower accidents are currently being developed for incorporation into the MELT accident analysis code. A new model for the fuel-coolant interaction and for the motion of fuel in the coolant channel has been developed and incorporated into the MELT-III code. A major limitation of the mechanistic fuel motion model is its dependence on the uniform interaction region of MELT-III. Consequently, a parallel effort is currently in progress to incorporate a non-uniform interaction region into the MELT code. Combination of the fuel motion and the nonuniform interaction region models will provide the framework for development of a mechanistic fuel plateout/blockage model for transient overpower accidents

  20. Thermal tides and studies to tune the mechanistic tidal model using UARS observations

    Directory of Open Access Journals (Sweden)

    V. A. Yudin

    1997-09-01

    Full Text Available Monthly simulations of the thermal diurnal and semidiurnal tides are compared to High-Resolution Doppler Imager (HRDI and Wind Imaging Interferometer (WINDII wind and temperature measurements on the Upper-Atmosphere Research Satellite (UARS. There is encouraging agreement between the observations and the linear global mechanistic tidal model results both for the diurnal and semidiurnal components in the equatorial and mid-latitude regions. This gives us the confidence to outline the first steps of an assimilative analysis/interpretation for tides, dissipation, and mean flow using a combination of model results and the global measurements from HRDI and WINDII. The sensitivity of the proposed technique to the initial guess employed to obtain a best fit to the data by tuning model parameters is discussed for the January and March 1993 cases, when the WINDII day and night measurements of the meridional winds between 90 and 110 km are used along with the daytime HRDI measurements. Several examples for the derivation of the tidal variables and decomposition of the measured winds into tidal and mean flow components using this approach are compared with previous tidal estimates and modeling results for the migrating tides. The seasonal cycle of the derived diurnal tidal amplitudes are discussed and compared with radar observation between 80 and 100 km and 40°S and 40°N.

  1. Thermal tides and studies to tune the mechanistic tidal model using UARS observations

    Directory of Open Access Journals (Sweden)

    V. A. Yudin

    Full Text Available Monthly simulations of the thermal diurnal and semidiurnal tides are compared to High-Resolution Doppler Imager (HRDI and Wind Imaging Interferometer (WINDII wind and temperature measurements on the Upper-Atmosphere Research Satellite (UARS. There is encouraging agreement between the observations and the linear global mechanistic tidal model results both for the diurnal and semidiurnal components in the equatorial and mid-latitude regions. This gives us the confidence to outline the first steps of an assimilative analysis/interpretation for tides, dissipation, and mean flow using a combination of model results and the global measurements from HRDI and WINDII. The sensitivity of the proposed technique to the initial guess employed to obtain a best fit to the data by tuning model parameters is discussed for the January and March 1993 cases, when the WINDII day and night measurements of the meridional winds between 90 and 110 km are used along with the daytime HRDI measurements. Several examples for the derivation of the tidal variables and decomposition of the measured winds into tidal and mean flow components using this approach are compared with previous tidal estimates and modeling results for the migrating tides. The seasonal cycle of the derived diurnal tidal amplitudes are discussed and compared with radar observation between 80 and 100 km and 40°S and 40°N.

  2. Validation of mechanistic models for gas precipitation in solids during postirradiation annealing experiments

    Science.gov (United States)

    Rest, J.

    1989-12-01

    A number of different phenomenological models for gas precipitation in solids during postirradiation annealing experiments have been proposed. Validation of such mechanistic models for gas release and swelling is complicated by the use of data containing large systematic errors, and phenomena characterized by synergistic effects as well as uncertainties in materials properties. Statistical regression analysis is recommended for the selection of a reasonably well characterized data base for gas release from irradiated fuel under transient heating conditions. It is demonstrated that an appropriate data selection method is required in order to realistically examine the impact of differing descriptions of the phenomena, and uncertainties in selected materials properties, on the validation results. The results of the analysis show that the kinetics of gas precipitation in solids depend on bubble overpressurization effects and need to be accounted for during the heatup phase of isothermal heating experiments. It is shown that if only the total gas release values (as opposed to time-dependent data) were available, differentiation between different gas precipitation models would be ambiguous. The observed sustained increase in the fractional release curve at relatively high temperatures after the total precipitation of intragranular gas in fission gas bubbles is ascribed to the effects of a grain-growth/grain-boundary sweeping mechanism.

  3. Validation of mechanistic models for gas precipitation in solids during postirradiation annealing experiments

    International Nuclear Information System (INIS)

    Rest, J.

    1989-01-01

    A number of different phenomenological models for gas precipitation in solids during postirradiation annealing experiments have been proposed. Validation of such mechanistic models for gas release and swelling is complicated by the use of data containing large systematic errors, and phenomena characterized by synergistic effects as well as uncertainties in materials properties. Statistical regression analysis is recommended for the selection of a reasonably well characterized data base for gas release from irradiated fuel under transient heating conditions. It is demonstrated that an appropriate data selection method is required in order to realistically examine the impact of differing descriptions of the phenomena, and uncertainties in selected materials properties, on the validation results. The results of the analysis show that the kinetics of gas precipitation in solid depend on bubble overpressurization effects and need to be accounted for during the heatup phase of isothermal heating experiments. It is shown that if only the total gas release values (as opposed to time-dependent data) were available, differentiation between different gas precipitation models would be ambiguous. The observed sustained increase in the fractional release curve at relatively high temperatures after the total precipitation of intragranular gas in fission gas bubbles is ascribed to the effects of a grain-growth/grain-boundary sweeping mechanism. (orig.)

  4. Development of Monopole Interaction Models for Ionic Compounds. Part I: Estimation of Aqueous Henry’s Law Constants for Ions and Gas Phase pKa Values for Acidic Compounds

    Science.gov (United States)

    The SPARC (SPARC Performs Automated Reasoning in Chemistry) physicochemical mechanistic models for neutral compounds have been extended to estimate Henry’s Law Constant (HLC) for charged species by incorporating ionic electrostatic interaction models. Combinations of absolute aq...

  5. Hierarchical modeling of activation mechanisms in the ABL and EGFR kinase domains: thermodynamic and mechanistic catalysts of kinase activation by cancer mutations.

    Directory of Open Access Journals (Sweden)

    Anshuman Dixit

    2009-08-01

    Full Text Available Structural and functional studies of the ABL and EGFR kinase domains have recently suggested a common mechanism of activation by cancer-causing mutations. However, dynamics and mechanistic aspects of kinase activation by cancer mutations that stimulate conformational transitions and thermodynamic stabilization of the constitutively active kinase form remain elusive. We present a large-scale computational investigation of activation mechanisms in the ABL and EGFR kinase domains by a panel of clinically important cancer mutants ABL-T315I, ABL-L387M, EGFR-T790M, and EGFR-L858R. We have also simulated the activating effect of the gatekeeper mutation on conformational dynamics and allosteric interactions in functional states of the ABL-SH2-SH3 regulatory complexes. A comprehensive analysis was conducted using a hierarchy of computational approaches that included homology modeling, molecular dynamics simulations, protein stability analysis, targeted molecular dynamics, and molecular docking. Collectively, the results of this study have revealed thermodynamic and mechanistic catalysts of kinase activation by major cancer-causing mutations in the ABL and EGFR kinase domains. By using multiple crystallographic states of ABL and EGFR, computer simulations have allowed one to map dynamics of conformational fluctuations and transitions in the normal (wild-type and oncogenic kinase forms. A proposed multi-stage mechanistic model of activation involves a series of cooperative transitions between different conformational states, including assembly of the hydrophobic spine, the formation of the Src-like intermediate structure, and a cooperative breakage and formation of characteristic salt bridges, which signify transition to the active kinase form. We suggest that molecular mechanisms of activation by cancer mutations could mimic the activation process of the normal kinase, yet exploiting conserved structural catalysts to accelerate a conformational transition

  6. Development and Implementation of Mechanistic Terry Turbine Models in RELAP-7 to Simulate RCIC Normal Operation Conditions

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Haihua [Idaho National Lab. (INL), Idaho Falls, ID (United States); Zou, Ling [Idaho National Lab. (INL), Idaho Falls, ID (United States); Zhang, Hongbin [Idaho National Lab. (INL), Idaho Falls, ID (United States); O' Brien, James Edward [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2016-09-01

    As part of the efforts to understand the unexpected “self-regulating” mode of the RCIC (Reactor Core Isolation Cooling) systems in Fukushima accidents and extend BWR RCIC and PWR AFW (Auxiliary Feed Water) operational range and flexibility, mechanistic models for the Terry turbine, based on Sandia’s original work [1], have been developed and implemented in the RELAP-7 code to simulate the RCIC system. In 2016, our effort has been focused on normal working conditions of the RCIC system. More complex off-design conditions will be pursued in later years when more data are available. In the Sandia model, the turbine stator inlet velocity is provided according to a reduced-order model which was obtained from a large number of CFD (computational fluid dynamics) simulations. In this work, we propose an alternative method, using an under-expanded jet model to obtain the velocity and thermodynamic conditions for the turbine stator inlet. The models include both an adiabatic expansion process inside the nozzle and a free expansion process outside of the nozzle to ambient pressure. The combined models are able to predict the steam mass flow rate and supersonic velocity to the Terry turbine bucket entrance, which are the necessary input information for the Terry turbine rotor model. The analytical models for the nozzle were validated with experimental data and benchmarked with CFD simulations. The analytical models generally agree well with the experimental data and CFD simulations. The analytical models are suitable for implementation into a reactor system analysis code or severe accident code as part of mechanistic and dynamical models to understand the RCIC behaviors. The newly developed nozzle models and modified turbine rotor model according to the Sandia’s original work have been implemented into RELAP-7, along with the original Sandia Terry turbine model. A new pump model has also been developed and implemented to couple with the Terry turbine model. An input

  7. Xanthusbase: adapting wikipedia principles to a model organism database

    OpenAIRE

    Arshinoff, Bradley I.; Suen, Garret; Just, Eric M.; Merchant, Sohel M.; Kibbe, Warren A.; Chisholm, Rex L.; Welch, Roy D.

    2006-01-01

    xanthusBase () is the official model organism database (MOD) for the social bacterium Myxococcus xanthus. In many respects, M.xanthus represents the pioneer model organism (MO) for studying the genetic, biochemical, and mechanistic basis of prokaryotic multicellularity, a topic that has garnered considerable attention due to the significance of biofilms in both basic and applied microbiology research. To facilitate its utility, the design of xanthusBase incorporates open-source software, leve...

  8. Malaria's Missing Number: Calculating the Human Component of R0 by a Within-Host Mechanistic Model of Plasmodium falciparum Infection and Transmission

    OpenAIRE

    Johnston, Geoffrey L.; Smith, David L.; Fidock, David A.

    2013-01-01

    Human infection by malarial parasites of the genus Plasmodium begins with the bite of an infected Anopheles mosquito. Current estimates place malaria mortality at over 650,000 individuals each year, mostly in African children. Efforts to reduce disease burden can benefit from the development of mathematical models of disease transmission. To date, however, comprehensive modeling of the parameters defining human infectivity to mosquitoes has remained elusive. Here, we describe a mechanistic wi...

  9. Fractal growth of tumors and other cellular populations: Linking the mechanistic to the phenomenological modeling and vice versa

    International Nuclear Information System (INIS)

    D'Onofrio, Alberto

    2009-01-01

    In this paper we study and extend the mechanistic mean field theory of growth of cellular populations proposed by Mombach et al. [Mombach JCM, Lemke N, Bodmann BEJ, Idiart MAP. A mean-field theory of cellular growth. Europhys Lett 2002;59:923-928] (MLBI model), and we demonstrate that the original model and our generalizations lead to inferences of biological interest. In the first part of this paper, we show that the model in study is widely general since it admits, as particular cases, the main phenomenological models of cellular growth. In the second part of this work, we generalize the MLBI model to a wider family of models by allowing the cells to have a generic unspecified biologically plausible interaction. Then, we derive a relationship between this generic microscopic interaction function and the growth rate of the corresponding macroscopic model. Finally, we propose to use this relationship in order to help the investigation of the biological plausibility of phenomenological models of cancer growth.

  10. Patterns and causes of species richness: a general simulation model for macroecology

    DEFF Research Database (Denmark)

    Gotelli, Nicholas J; Anderson, Marti J; Arita, Hector T

    2009-01-01

    to a mechanistic understanding of the patterns. During the past two decades, macroecologists have successfully addressed technical problems posed by spatial autocorrelation, intercorrelation of predictor variables and non-linearity. However, curve-fitting approaches are problematic because most theoretical models...... in macroecology do not make quantitative predictions, and they do not incorporate interactions among multiple forces. As an alternative, we propose a mechanistic modelling approach. We describe computer simulation models of the stochastic origin, spread, and extinction of species' geographical ranges...... in an environmentally heterogeneous, gridded domain and describe progress to date regarding their implementation. The output from such a general simulation model (GSM) would, at a minimum, consist of the simulated distribution of species ranges on a map, yielding the predicted number of species in each grid cell...

  11. Drug-disease modeling in the pharmaceutical industry - where mechanistic systems pharmacology and statistical pharmacometrics meet.

    Science.gov (United States)

    Helmlinger, Gabriel; Al-Huniti, Nidal; Aksenov, Sergey; Peskov, Kirill; Hallow, Karen M; Chu, Lulu; Boulton, David; Eriksson, Ulf; Hamrén, Bengt; Lambert, Craig; Masson, Eric; Tomkinson, Helen; Stanski, Donald

    2017-11-15

    Modeling & simulation (M&S) methodologies are established quantitative tools, which have proven to be useful in supporting the research, development (R&D), regulatory approval, and marketing of novel therapeutics. Applications of M&S help design efficient studies and interpret their results in context of all available data and knowledge to enable effective decision-making during the R&D process. In this mini-review, we focus on two sets of modeling approaches: population-based models, which are well-established within the pharmaceutical industry today, and fall under the discipline of clinical pharmacometrics (PMX); and systems dynamics models, which encompass a range of models of (patho-)physiology amenable to pharmacological intervention, of signaling pathways in biology, and of substance distribution in the body (today known as physiologically-based pharmacokinetic models) - which today may be collectively referred to as quantitative systems pharmacology models (QSP). We next describe the convergence - or rather selected integration - of PMX and QSP approaches into 'middle-out' drug-disease models, which retain selected mechanistic aspects, while remaining parsimonious, fit-for-purpose, and able to address variability and the testing of covariates. We further propose development opportunities for drug-disease systems models, to increase their utility and applicability throughout the preclinical and clinical spectrum of pharmaceutical R&D. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Incorporating neurophysiological concepts in mathematical thermoregulation models

    Science.gov (United States)

    Kingma, Boris R. M.; Vosselman, M. J.; Frijns, A. J. H.; van Steenhoven, A. A.; van Marken Lichtenbelt, W. D.

    2014-01-01

    Skin blood flow (SBF) is a key player in human thermoregulation during mild thermal challenges. Various numerical models of SBF regulation exist. However, none explicitly incorporates the neurophysiology of thermal reception. This study tested a new SBF model that is in line with experimental data on thermal reception and the neurophysiological pathways involved in thermoregulatory SBF control. Additionally, a numerical thermoregulation model was used as a platform to test the function of the neurophysiological SBF model for skin temperature simulation. The prediction-error of the SBF-model was quantified by root-mean-squared-residual (RMSR) between simulations and experimental measurement data. Measurement data consisted of SBF (abdomen, forearm, hand), core and skin temperature recordings of young males during three transient thermal challenges (1 development and 2 validation). Additionally, ThermoSEM, a thermoregulation model, was used to simulate body temperatures using the new neurophysiological SBF-model. The RMSR between simulated and measured mean skin temperature was used to validate the model. The neurophysiological model predicted SBF with an accuracy of RMSR human thermoregulation models can be equipped with SBF control functions that are based on neurophysiology without loss of performance. The neurophysiological approach in modelling thermoregulation is favourable over engineering approaches because it is more in line with the underlying physiology.

  13. Verification of a mechanistic model for the strain rate of zircaloy-4 fuel sheaths during transient heating

    International Nuclear Information System (INIS)

    Hunt, C.E.L.

    1980-10-01

    A mechanistic strain rate model for Zircaloy-4, named NIRVANA, was tested against experiments where pressurized fuel sheaths were strained during complex temperature-stress-time histories. The same histories were then examined to determine the spread in calculated strain which may be expected because of variations in dimensions, chemical content and mechanical properties which are allowed in the fuel sheath specifications. It was found that the variations allowed by the specifications could result in a probable spread in the predicted strain of plus or minus a factor of two from the mean value. The experimental results were well within this range. (auth)

  14. Mechanistic Drifting Forecast Model for A Small Semi-Submersible Drifter Under Tide-Wind-Wave Conditions

    Science.gov (United States)

    Zhang, Wei-Na; Huang, Hui-ming; Wang, Yi-gang; Chen, Da-ke; Zhang, lin

    2018-03-01

    Understanding the drifting motion of a small semi-submersible drifter is of vital importance regarding monitoring surface currents and the floating pollutants in coastal regions. This work addresses this issue by establishing a mechanistic drifting forecast model based on kinetic analysis. Taking tide-wind-wave into consideration, the forecast model is validated against in situ drifting experiment in the Radial Sand Ridges. Model results show good performance with respect to the measured drifting features, characterized by migrating back and forth twice a day with daily downwind displacements. Trajectory models are used to evaluate the influence of the individual hydrodynamic forcing. The tidal current is the fundamental dynamic condition in the Radial Sand Ridges and has the greatest impact on the drifting distance. However, it loses its leading position in the field of the daily displacement of the used drifter. The simulations reveal that different hydrodynamic forces dominate the daily displacement of the used drifter at different wind scales. The wave-induced mass transport has the greatest influence on the daily displacement at Beaufort wind scale 5-6; while wind drag contributes mostly at wind scale 2-4.

  15. A Three-Stage Mechanistic Model for Solidification Cracking During Welding of Steel

    Science.gov (United States)

    Aucott, L.; Huang, D.; Dong, H. B.; Wen, S. W.; Marsden, J.; Rack, A.; Cocks, A. C. F.

    2018-03-01

    A three-stage mechanistic model for solidification cracking during TIG welding of steel is proposed from in situ synchrotron X-ray imaging of solidification cracking and subsequent analysis of fracture surfaces. Stage 1—Nucleation of inter-granular hot cracks: cracks nucleate inter-granularly in sub-surface where maximum volumetric strain is localized and volume fraction of liquid is less than 0.1; the crack nuclei occur at solute-enriched liquid pockets which remain trapped in increasingly impermeable semi-solid skeleton. Stage 2—Coalescence of cracks via inter-granular fracture: as the applied strain increases, cracks coalesce through inter-granular fracture; the coalescence path is preferential to the direction of the heat source and propagates through the grain boundaries to solidifying dendrites. Stage 3—Propagation through inter-dendritic hot tearing: inter-dendritic hot tearing occurs along the boundaries between solidifying columnar dendrites with higher liquid fraction. It is recommended that future solidification cracking criterion shall be based on the application of multiphase mechanics and fracture mechanics to the failure of semi-solid materials.

  16. Incorporation of composite defects from ultrasonic NDE into CAD and FE models

    Science.gov (United States)

    Bingol, Onur Rauf; Schiefelbein, Bryan; Grandin, Robert J.; Holland, Stephen D.; Krishnamurthy, Adarsh

    2017-02-01

    Fiber-reinforced composites are widely used in aerospace industry due to their combined properties of high strength and low weight. However, owing to their complex structure, it is difficult to assess the impact of manufacturing defects and service damage on their residual life. While, ultrasonic testing (UT) is the preferred NDE method to identify the presence of defects in composites, there are no reasonable ways to model the damage and evaluate the structural integrity of composites. We have developed an automated framework to incorporate flaws and known composite damage automatically into a finite element analysis (FEA) model of composites, ultimately aiding in accessing the residual life of composites and make informed decisions regarding repairs. The framework can be used to generate a layer-by-layer 3D structural CAD model of the composite laminates replicating their manufacturing process. Outlines of structural defects, such as delaminations, are automatically detected from UT of the laminate and are incorporated into the CAD model between the appropriate layers. In addition, the framework allows for direct structural analysis of the resulting 3D CAD models with defects by automatically applying the appropriate boundary conditions. In this paper, we show a working proof-of-concept for the composite model builder with capabilities of incorporating delaminations between laminate layers and automatically preparing the CAD model for structural analysis using a FEA software.

  17. Developing Baltic cod recruitment models II : Incorporation of environmental variability and species interaction

    DEFF Research Database (Denmark)

    Köster, Fritz; Hinrichsen, H.H.; St. John, Michael

    2001-01-01

    We investigate whether a process-oriented approach based on the results of field, laboratory, and modelling studies can be used to develop a stock-environment-recruitment model for Central Baltic cod (Gadus morhua). Based on exploratory statistical analysis, significant variables influencing...... cod in these areas, suggesting that key biotic and abiotic processes can be successfully incorporated into recruitment models....... survival of early life stages and varying systematically among spawning sites were incorporated into stock-recruitment models, first for major cod spawning sites and then combined for the entire Central Baltic. Variables identified included potential egg production by the spawning stock, abiotic conditions...

  18. Progress toward bridging from atomistic to continuum modeling to predict nuclear waste glass dissolution.

    Energy Technology Data Exchange (ETDEWEB)

    Zapol, Peter (Argonne National Laboratory, Argonne, IL); Bourg, Ian (Lawrence Berkeley National Laboratories, Berkeley, CA); Criscenti, Louise Jacqueline; Steefel, Carl I. (Lawrence Berkeley National Laboratories, Berkeley, CA); Schultz, Peter Andrew

    2011-10-01

    This report summarizes research performed for the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Subcontinuum and Upscaling Task. The work conducted focused on developing a roadmap to include molecular scale, mechanistic information in continuum-scale models of nuclear waste glass dissolution. This information is derived from molecular-scale modeling efforts that are validated through comparison with experimental data. In addition to developing a master plan to incorporate a subcontinuum mechanistic understanding of glass dissolution into continuum models, methods were developed to generate constitutive dissolution rate expressions from quantum calculations, force field models were selected to generate multicomponent glass structures and gel layers, classical molecular modeling was used to study diffusion through nanopores analogous to those in the interfacial gel layer, and a micro-continuum model (K{mu}C) was developed to study coupled diffusion and reaction at the glass-gel-solution interface.

  19. Melanie Klein's metapsychology: phenomenological and mechanistic perspective.

    Science.gov (United States)

    Mackay, N

    1981-01-01

    Freud's metapsychology is the subject of an important debate. This is over whether psychoanalysis is best construed as a science of the natural science type or as a special human science. The same debate applies to Melanie Klein's work. In Klein's metapsychology are two different and incompatible models of explanation. One is taken over from Freud's structural theory and appears to be similarly mechanistic. The other is clinically based and phenomenological. These two are discussed with special reference to the concepts of "phantasy" and "internal object".

  20. Chemical kinetic mechanistic models to investigate cancer biology and impact cancer medicine

    International Nuclear Information System (INIS)

    Stites, Edward C

    2013-01-01

    Traditional experimental biology has provided a mechanistic understanding of cancer in which the malignancy develops through the acquisition of mutations that disrupt cellular processes. Several drugs developed to target such mutations have now demonstrated clinical value. These advances are unequivocal testaments to the value of traditional cellular and molecular biology. However, several features of cancer may limit the pace of progress that can be made with established experimental approaches alone. The mutated genes (and resultant mutant proteins) function within large biochemical networks. Biochemical networks typically have a large number of component molecules and are characterized by a large number of quantitative properties. Responses to a stimulus or perturbation are typically nonlinear and can display qualitative changes that depend upon the specific values of variable system properties. Features such as these can complicate the interpretation of experimental data and the formulation of logical hypotheses that drive further research. Mathematical models based upon the molecular reactions that define these networks combined with computational studies have the potential to deal with these obstacles and to enable currently available information to be more completely utilized. Many of the pressing problems in cancer biology and cancer medicine may benefit from a mathematical treatment. As work in this area advances, one can envision a future where such models may meaningfully contribute to the clinical management of cancer patients. (paper)

  1. A mechanistic spatio-temporal framework for modelling individual-to-individual transmission-With an application to the 2014-2015 West Africa Ebola outbreak.

    Directory of Open Access Journals (Sweden)

    Max S Y Lau

    2017-10-01

    Full Text Available In recent years there has been growing availability of individual-level spatio-temporal disease data, particularly due to the use of modern communicating devices with GPS tracking functionality. These detailed data have been proven useful for inferring disease transmission to a more refined level than previously. However, there remains a lack of statistically sound frameworks to model the underlying transmission dynamic in a mechanistic manner. Such a development is particularly crucial for enabling a general epidemic predictive framework at the individual level. In this paper we propose a new statistical framework for mechanistically modelling individual-to-individual disease transmission in a landscape with heterogeneous population density. Our methodology is first tested using simulated datasets, validating our inferential machinery. The methodology is subsequently applied to data that describes a regional Ebola outbreak in Western Africa (2014-2015. Our results show that the methods are able to obtain estimates of key epidemiological parameters that are broadly consistent with the literature, while revealing a significantly shorter distance of transmission. More importantly, in contrast to existing approaches, we are able to perform a more general model prediction that takes into account the susceptible population. Finally, our results show that, given reasonable scenarios, the framework can be an effective surrogate for susceptible-explicit individual models which are often computationally challenging.

  2. A mechanistic spatio-temporal framework for modelling individual-to-individual transmission—With an application to the 2014-2015 West Africa Ebola outbreak

    Science.gov (United States)

    McClelland, Amanda; Zelner, Jon; Streftaris, George; Funk, Sebastian; Metcalf, Jessica; Dalziel, Benjamin D.; Grenfell, Bryan T.

    2017-01-01

    In recent years there has been growing availability of individual-level spatio-temporal disease data, particularly due to the use of modern communicating devices with GPS tracking functionality. These detailed data have been proven useful for inferring disease transmission to a more refined level than previously. However, there remains a lack of statistically sound frameworks to model the underlying transmission dynamic in a mechanistic manner. Such a development is particularly crucial for enabling a general epidemic predictive framework at the individual level. In this paper we propose a new statistical framework for mechanistically modelling individual-to-individual disease transmission in a landscape with heterogeneous population density. Our methodology is first tested using simulated datasets, validating our inferential machinery. The methodology is subsequently applied to data that describes a regional Ebola outbreak in Western Africa (2014-2015). Our results show that the methods are able to obtain estimates of key epidemiological parameters that are broadly consistent with the literature, while revealing a significantly shorter distance of transmission. More importantly, in contrast to existing approaches, we are able to perform a more general model prediction that takes into account the susceptible population. Finally, our results show that, given reasonable scenarios, the framework can be an effective surrogate for susceptible-explicit individual models which are often computationally challenging. PMID:29084216

  3. Mechanistic modelling of weak interlayers in flexible and semi-flexible road pavements: Part 2

    CSIR Research Space (South Africa)

    De Beer, Morris

    2012-04-01

    Full Text Available This paper (Part 2 of a two-part set of papers) discusses models and illustrates the adverse effects of weak layers, interlayers, laminations and/or weak interfaces in flexible and semi-flexible pavements, also incorporating lightly cemented layers...

  4. Numerical simulation in steam injection wellbores by mechanistic approach; Simulacao numerica do escoamento de vapor em pocos por uma abordagem mecanicista

    Energy Technology Data Exchange (ETDEWEB)

    Souza Junior, J.C. de; Campos, W.; Lopes, D.; Moura, L.S.S. [PETROBRAS, Rio de Janeiro, RJ (Brazil); Thomas, A. Clecio F. [Universidade Estadual do Ceara (UECE), CE (Brazil)

    2008-07-01

    This work addresses to the development of a hydrodynamic and heat transfer mechanistic model for steam flow in injection wellbores. The problem of two-phase steam flow in wellbores has been solved recently by using available empirical correlations from petroleum industry (Lopes, 1986) and nuclear industry (Moura, 1991).The good performance achieved by mechanistic models developed by Ansari (1994), Hasan (1995), Gomez (2000) and Kaya (2001) supports the importance of the mechanistic approach for the steam flow problem in injection wellbores. In this study, the methodology to solve the problem consists in the application of a numerical method to the governing equations of steam flow and a marching algorithm to determine the distribution of the pressure and temperature along the wellbore. So, a computer code has been formulated to get numerical results, which provides a comparative study to the main models found in the literature. Finally, when compared to available field data, the mechanistic model for downward vertical steam flow in wellbores gave better results than the empirical correlations. (author)

  5. A climatological model for risk computations incorporating site- specific dry deposition influences

    International Nuclear Information System (INIS)

    Droppo, J.G. Jr.

    1991-07-01

    A gradient-flux dry deposition module was developed for use in a climatological atmospheric transport model, the Multimedia Environmental Pollutant Assessment System (MEPAS). The atmospheric pathway model computes long-term average contaminant air concentration and surface deposition patterns surrounding a potential release site incorporating location-specific dry deposition influences. Gradient-flux formulations are used to incorporate site and regional data in the dry deposition module for this atmospheric sector-average climatological model. Application of these formulations provide an effective means of accounting for local surface roughness in deposition computations. Linkage to a risk computation module resulted in a need for separate regional and specific surface deposition computations. 13 refs., 4 figs., 2 tabs

  6. Mechanistic phenotypes: an aggregative phenotyping strategy to identify disease mechanisms using GWAS data.

    Directory of Open Access Journals (Sweden)

    Jonathan D Mosley

    Full Text Available A single mutation can alter cellular and global homeostatic mechanisms and give rise to multiple clinical diseases. We hypothesized that these disease mechanisms could be identified using low minor allele frequency (MAF<0.1 non-synonymous SNPs (nsSNPs associated with "mechanistic phenotypes", comprised of collections of related diagnoses. We studied two mechanistic phenotypes: (1 thrombosis, evaluated in a population of 1,655 African Americans; and (2 four groupings of cancer diagnoses, evaluated in 3,009 white European Americans. We tested associations between nsSNPs represented on GWAS platforms and mechanistic phenotypes ascertained from electronic medical records (EMRs, and sought enrichment in functional ontologies across the top-ranked associations. We used a two-step analytic approach whereby nsSNPs were first sorted by the strength of their association with a phenotype. We tested associations using two reverse genetic models and standard additive and recessive models. In the second step, we employed a hypothesis-free ontological enrichment analysis using the sorted nsSNPs to identify functional mechanisms underlying the diagnoses comprising the mechanistic phenotypes. The thrombosis phenotype was solely associated with ontologies related to blood coagulation (Fisher's p = 0.0001, FDR p = 0.03, driven by the F5, P2RY12 and F2RL2 genes. For the cancer phenotypes, the reverse genetics models were enriched in DNA repair functions (p = 2×10-5, FDR p = 0.03 (POLG/FANCI, SLX4/FANCP, XRCC1, BRCA1, FANCA, CHD1L while the additive model showed enrichment related to chromatid segregation (p = 4×10-6, FDR p = 0.005 (KIF25, PINX1. We were able to replicate nsSNP associations for POLG/FANCI, BRCA1, FANCA and CHD1L in independent data sets. Mechanism-oriented phenotyping using collections of EMR-derived diagnoses can elucidate fundamental disease mechanisms.

  7. Methods improvements incorporated into the SAPHIRE ASP models

    International Nuclear Information System (INIS)

    Sattison, M.B.; Blackman, H.S.; Novack, S.D.; Smith, C.L.; Rasmuson, D.M.

    1994-01-01

    The Office for Analysis and Evaluation of Operational Data (AEOD) has sought the assistance of the Idaho National Engineering Laboratory (INEL) to make some significant enhancements to the SAPHIRE-based Accident Sequence Precursor (ASP) models recently developed by the INEL. The challenge of this project is to provide the features of a full-scale PRA within the framework of the simplified ASP models. Some of these features include: (1) uncertainty analysis addressing the standard PRA uncertainties and the uncertainties unique to the ASP models and methodology, (2) incorporation and proper quantification of individual human actions and the interaction among human actions, (3) enhanced treatment of common cause failures, and (4) extension of the ASP models to more closely mimic full-scale PRAs (inclusion of more initiators, explicitly modeling support system failures, etc.). This paper provides an overview of the methods being used to make the above improvements

  8. Methods improvements incorporated into the SAPHIRE ASP models

    International Nuclear Information System (INIS)

    Sattison, M.B.; Blackman, H.S.; Novack, S.D.

    1995-01-01

    The Office for Analysis and Evaluation of Operational Data (AEOD) has sought the assistance of the Idaho National Engineering Laboratory (INEL) to make some significant enhancements to the SAPHIRE-based Accident Sequence Precursor (ASP) models recently developed by the INEL. The challenge of this project is to provide the features of a full-scale PRA within the framework of the simplified ASP models. Some of these features include: (1) uncertainty analysis addressing the standard PRA uncertainties and the uncertainties unique to the ASP models and methods, (2) incorporation and proper quantification of individual human actions and the interaction among human actions, (3) enhanced treatment of common cause failures, and (4) extension of the ASP models to more closely mimic full-scale PRAs (inclusion of more initiators, explicitly modeling support system failures, etc.). This paper provides an overview of the methods being used to make the above improvements

  9. Pathophysiology of white-nose syndrome in bats: a mechanistic model linking wing damage to mortality.

    Science.gov (United States)

    Warnecke, Lisa; Turner, James M; Bollinger, Trent K; Misra, Vikram; Cryan, Paul M; Blehert, David S; Wibbelt, Gudrun; Willis, Craig K R

    2013-08-23

    White-nose syndrome is devastating North American bat populations but we lack basic information on disease mechanisms. Altered blood physiology owing to epidermal invasion by the fungal pathogen Geomyces destructans (Gd) has been hypothesized as a cause of disrupted torpor patterns of affected hibernating bats, leading to mortality. Here, we present data on blood electrolyte concentration, haematology and acid-base balance of hibernating little brown bats, Myotis lucifugus, following experimental inoculation with Gd. Compared with controls, infected bats showed electrolyte depletion (i.e. lower plasma sodium), changes in haematology (i.e. increased haematocrit and decreased glucose) and disrupted acid-base balance (i.e. lower CO2 partial pressure and bicarbonate). These findings indicate hypotonic dehydration, hypovolaemia and metabolic acidosis. We propose a mechanistic model linking tissue damage to altered homeostasis and morbidity/mortality.

  10. Modeling process-structure-property relationships for additive manufacturing

    Science.gov (United States)

    Yan, Wentao; Lin, Stephen; Kafka, Orion L.; Yu, Cheng; Liu, Zeliang; Lian, Yanping; Wolff, Sarah; Cao, Jian; Wagner, Gregory J.; Liu, Wing Kam

    2018-02-01

    This paper presents our latest work on comprehensive modeling of process-structure-property relationships for additive manufacturing (AM) materials, including using data-mining techniques to close the cycle of design-predict-optimize. To illustrate the processstructure relationship, the multi-scale multi-physics process modeling starts from the micro-scale to establish a mechanistic heat source model, to the meso-scale models of individual powder particle evolution, and finally to the macro-scale model to simulate the fabrication process of a complex product. To link structure and properties, a highefficiency mechanistic model, self-consistent clustering analyses, is developed to capture a variety of material response. The model incorporates factors such as voids, phase composition, inclusions, and grain structures, which are the differentiating features of AM metals. Furthermore, we propose data-mining as an effective solution for novel rapid design and optimization, which is motivated by the numerous influencing factors in the AM process. We believe this paper will provide a roadmap to advance AM fundamental understanding and guide the monitoring and advanced diagnostics of AM processing.

  11. Disentangling the Role of Domain-Specific Knowledge in Student Modeling

    Science.gov (United States)

    Ruppert, John; Duncan, Ravit Golan; Chinn, Clark A.

    2017-08-01

    This study explores the role of domain-specific knowledge in students' modeling practice and how this knowledge interacts with two domain-general modeling strategies: use of evidence and developing a causal mechanism. We analyzed models made by middle school students who had a year of intensive model-based instruction. These models were made to explain a familiar but unstudied biological phenomenon: late onset muscle pain. Students were provided with three pieces of evidence related to this phenomenon and asked to construct a model to account for this evidence. Findings indicate that domain-specific resources play a significant role in the extent to which the models accounted for provided evidence. On the other hand, familiarity with the situation appeared to contribute to the mechanistic character of models. Our results indicate that modeling strategies alone are insufficient for the development of a mechanistic model that accounts for provided evidence and that, while learners can develop a tentative model with a basic familiarity of the situation, scaffolding certain domain-specific knowledge is necessary to assist students with incorporating evidence in modeling tasks.

  12. Verification of mechanistic-empirical design models for flexible pavements through accelerated pavement testing : technical summary.

    Science.gov (United States)

    2014-08-01

    Midwest States Accelerated Pavement Testing Pooled-Fund Program, financed by the : highway departments of Kansas, Iowa, and Missouri, has supported an accelerated : pavement testing (APT) project to validate several models incorporated in the NCHRP :...

  13. Mechanistic model to predict colostrum intake based on deuterium oxide dilution technique data and impact of gestation and prefarrowing diets on piglet intake and sow yield of colostrum.

    Science.gov (United States)

    Theil, P K; Flummer, C; Hurley, W L; Kristensen, N B; Labouriau, R L; Sørensen, M T

    2014-12-01

    The aims of the present study were to quantify colostrum intake (CI) of piglets using the D2O dilution technique, to develop a mechanistic model to predict CI, to compare these data with CI predicted by a previous empirical predictive model developed for bottle-fed piglets, and to study how composition of diets fed to gestating sows affected piglet CI, sow colostrum yield (CY), and colostrum composition. In total, 240 piglets from 40 litters were enriched with D2O. The CI measured by D2O from birth until 24 h after the birth of first-born piglet was on average 443 g (SD 151). Based on measured CI, a mechanistic model to predict CI was developed using piglet characteristics (24-h weight gain [WG; g], BW at birth [BWB; kg], and duration of CI [D; min]: CI, g=-106+2.26 WG+200 BWB+0.111 D-1,414 WG/D+0.0182 WG/BWB (R2=0.944). This model was used to predict the CI for all colostrum suckling piglets within the 40 litters (n=500, mean=437 g, SD=153 g) and was compared with the CI predicted by a previous empirical predictive model (mean=305 g, SD=140 g). The previous empirical model underestimated the CI by 30% compared with that obtained by the new mechanistic model. The sows were fed 1 of 4 gestation diets (n=10 per diet) based on different fiber sources (low fiber [17%] or potato pulp, pectin residue, or sugarbeet pulp [32 to 40%]) from mating until d 108 of gestation. From d 108 of gestation until parturition, sows were fed 1 of 5 prefarrowing diets (n=8 per diet) varying in supplemented fat (3% animal fat, 8% coconut oil, 8% sunflower oil, 8% fish oil, or 4% fish oil+4% octanoic acid). Sows fed diets with pectin residue or sugarbeet pulp during gestation produced colostrum with lower protein, fat, DM, and energy concentrations and higher lactose concentrations, and their piglets had greater CI as compared with sows fed potato pulp or the low-fiber diet (Pcoconut oil decreased lactose and increased DM concentrations of colostrum compared with other prefarrowing diets (P

  14. An electricity generation planning model incorporating demand response

    International Nuclear Information System (INIS)

    Choi, Dong Gu; Thomas, Valerie M.

    2012-01-01

    Energy policies that aim to reduce carbon emissions and change the mix of electricity generation sources, such as carbon cap-and-trade systems and renewable electricity standards, can affect not only the source of electricity generation, but also the price of electricity and, consequently, demand. We develop an optimization model to determine the lowest cost investment and operation plan for the generating capacity of an electric power system. The model incorporates demand response to price change. In a case study for a U.S. state, we show the price, demand, and generation mix implications of a renewable electricity standard, and of a carbon cap-and-trade policy with and without initial free allocation of carbon allowances. This study shows that both the demand moderating effects and the generation mix changing effects of the policies can be the sources of carbon emissions reductions, and also shows that the share of the sources could differ with different policy designs. The case study provides different results when demand elasticity is excluded, underscoring the importance of incorporating demand response in the evaluation of electricity generation policies. - Highlights: ► We develop an electric power system optimization model including demand elasticity. ► Both renewable electricity and carbon cap-and-trade policies can moderate demand. ► Both policies affect the generation mix, price, and demand for electricity. ► Moderated demand can be a significant source of carbon emission reduction. ► For cap-and-trade policies, initial free allowances change outcomes significantly.

  15. "Violent Intent Modeling: Incorporating Cultural Knowledge into the Analytical Process

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Nibbs, Faith G.

    2007-08-24

    While culture has a significant effect on the appropriate interpretation of textual data, the incorporation of cultural considerations into data transformations has not been systematic. Recognizing that the successful prevention of terrorist activities could hinge on the knowledge of the subcultures, Anthropologist and DHS intern Faith Nibbs has been addressing the need to incorporate cultural knowledge into the analytical process. In this Brown Bag she will present how cultural ideology is being used to understand how the rhetoric of group leaders influences the likelihood of their constituents to engage in violent or radicalized behavior, and how violent intent modeling can benefit from understanding that process.

  16. Mechanistic model coupling gas exchange dynamics and Listeria monocytogenes growth in modified atmosphere packaging of non respiring food.

    Science.gov (United States)

    Chaix, E; Broyart, B; Couvert, O; Guillaume, C; Gontard, N; Guillard, V

    2015-10-01

    A mechanistic model coupling O2 and CO2 mass transfer (namely diffusion and solubilisation in the food itself and permeation through the packaging material) to microbial growth models was developed aiming at predicting the shelf life of modified atmosphere packaging (MAP) systems. It was experimentally validated on a non-respiring food by investigating concomitantly the O2/CO2 partial pressure in packaging headspace and the growth of Listeria monocytogenes (average microbial count) within the food sample. A sensitivity analysis has revealed that the reliability of the prediction by this "super-parametrized" model (no less than 47 parameters were required for running one simulation) was strongly dependent on the accuracy of the microbial input parameters. Once validated, this model was used to decipher the role of O2/CO2 mass transfer on microbial growth and as a MAP design tool: an example of MAP dimensioning was provided in this paper as a proof of concept. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Probing the mechanistic consequences of 5-fluorine substitution on cytidine nucleotide analogue incorporation by HIV-1 reverse transcriptase.

    Science.gov (United States)

    Ray, Adrian S; Schinazi, Raymond F; Murakami, Eisuke; Basavapathruni, Aravind; Shi, Junxing; Zorca, Suzana M; Chu, Chung K; Anderson, Karen S

    2003-05-01

    Beta-D and beta-L-enantiomers of 2',3'-dideoxycytidine analogues are potent chain-terminators and antimetabolites for viral and cellular replication. Seemingly small modifications markedly alter their antiviral and toxicity patterns. This review discusses previously published and recently obtained data on the effects of 5- and 2'-fluorine substitution on the pre-steady state incorporation of 2'-deoxycytidine-5'-monophosphate analogues by HIV-1 reverse transcriptase (RT) in light of their biological activity. The addition of fluorine at the 5-position of the pyrimidine ring altered the kinetic parameters for all nucleotides tested. Only the 5-fluorine substitution of the clinically relevant nucleosides (-)-beta-L-2',3'-dideoxy-3'-thia-5-fluorocytidine (L-FTC, Emtriva), and (+)-beta-D-2',3'-didehydro-2',3'-dideoxy-5-fluorocytidine (D-D4FC, Reverset), caused a higher overall efficiency of nucleotide incorporation during both DNA- and RNA-directed synthesis. Enhanced incorporation by RT may in part explain the potency of these nucleosides against HIV-1. In other cases, a lack of correlation between RT incorporation in enzymatic assays and antiviral activity in cell culture illustrates the importance of other cellular factors in defining antiviral potency. The substitution of fluorine at the 2' position of the deoxyribose ring negatively affects incorporation by RT indicating the steric gate of RT can detect electrostatic perturbations. Intriguing results pertaining to drug resistance have led to a better understanding of HIV-1 RT resistance mechanisms. These insights serve as a basis for understanding the mechanism of action for nucleoside analogues and, coupled with studies on other key enzymes, may lead to the more effective use of fluorine to enhance the potency and selectivity of antiviral agents.

  18. Reducing Uncertainty in the Daycent Model of Heterotrophic Respiration with a More Mechanistic Representation of Microbial Processes.

    Science.gov (United States)

    Berardi, D.; Gomez-Casanovas, N.; Hudiburg, T. W.

    2017-12-01

    Improving the certainty of ecosystem models is essential to ensuring their legitimacy, value, and ability to inform management and policy decisions. With more than a century of research exploring the variables controlling soil respiration, a high level of uncertainty remains in the ability of ecosystem models to accurately estimate respiration with changing climatic conditions. Refining model estimates of soil carbon fluxes is a high priority for climate change scientists to determine whether soils will be carbon sources or sinks in the future. We found that DayCent underestimates heterotrophic respiration by several magnitudes for our temperate mixed conifer forest site. While traditional ecosystem models simulate decomposition through first order kinetics, recent research has found that including microbial mechanisms explains 20 percent more spatial heterogeneity. We manipulated the DayCent heterotrophic respiration model to include a more mechanistic representation of microbial dynamic and compared the new model with continuous and survey observations from our experimental forest site in the Northern Rockies ecoregion. We also calibrated the model's sensitivity to soil moisture and temperature to our experimental data. We expect to improve the accuracy of the model by 20-30 percent. By using a more representative and calibrated model of soil carbon dynamics, we can better predict feedbacks between climate and soil carbon pools.

  19. A Mechanistic Model of Human Recall of Social Network Structure and Relationship Affect.

    Science.gov (United States)

    Omodei, Elisa; Brashears, Matthew E; Arenas, Alex

    2017-12-07

    The social brain hypothesis argues that the need to deal with social challenges was key to our evolution of high intelligence. Research with non-human primates as well as experimental and fMRI studies in humans produce results consistent with this claim, leading to an estimate that human primary groups should consist of roughly 150 individuals. Gaps between this prediction and empirical observations can be partially accounted for using "compression heuristics", or schemata that simplify the encoding and recall of social information. However, little is known about the specific algorithmic processes used by humans to store and recall social information. We describe a mechanistic model of human network recall and demonstrate its sufficiency for capturing human recall behavior observed in experimental contexts. We find that human recall is predicated on accurate recall of a small number of high degree network nodes and the application of heuristics for both structural and affective information. This provides new insight into human memory, social network evolution, and demonstrates a novel approach to uncovering human cognitive operations.

  20. Flow regimes and mechanistic modeling of critical heat flux under subcooled flow boiling conditions

    Science.gov (United States)

    Le Corre, Jean-Marie

    Thermal performance of heat flux controlled boiling heat exchangers are usually limited by the Critical Heat Flux (CHF) above which the heat transfer degrades quickly, possibly leading to heater overheating and destruction. In an effort to better understand the phenomena, a literature review of CHF experimental visualizations under subcooled flow boiling conditions was performed and systematically analyzed. Three major types of CHF flow regimes were identified (bubbly, vapor clot and slug flow regime) and a CHF flow regime map was developed, based on a dimensional analysis of the phenomena and available data. It was found that for similar geometric characteristics and pressure, a Weber number (We)/thermodynamic quality (x) map can be used to predict the CHF flow regime. Based on the experimental observations and the review of the available CHF mechanistic models under subcooled flow boiling conditions, hypothetical CHF mechanisms were selected for each CHF flow regime, all based on a concept of wall dry spot overheating, rewetting prevention and subsequent dry spot spreading. It is postulated that a high local wall superheat occurs locally in a dry area of the heated wall, due to a cyclical event inherent to the considered CHF two-phase flow regime, preventing rewetting (Leidenfrost effect). The selected modeling concept has the potential to span the CHF conditions from highly subcooled bubbly flow to early stage of annular flow. A numerical model using a two-dimensional transient thermal analysis of the heater undergoing nucleation was developed to mechanistically predict CHF in the case of a bubbly flow regime. In this type of CHF two-phase flow regime, the high local wall superheat occurs underneath a nucleating bubble at the time of bubble departure. The model simulates the spatial and temporal heater temperature variations during nucleation at the wall, accounting for the stochastic nature of the boiling phenomena. The model has also the potential to evaluate

  1. A mechanistic model for spread of livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA) within a pig herd

    DEFF Research Database (Denmark)

    Sørensen, Anna Irene Vedel; Toft, Nils; Boklund, Anette

    2017-01-01

    Before an efficient control strategy for livestock-associated methicillin resistant Staphylococcus aureus (LA-MRSA) in pigs can be decided upon, it is necessary to obtain a betterunderstanding of how LA-MRSA spreads and persists within a pig herd, once it is introduced.We here present a mechanistic...... stochastic discrete-event simulation model forspread of LA-MRSA within a farrow-to-finish sow herd to aid in this. The model was individual-based and included three different disease compartments: susceptible, intermittent or persistent shedder of MRSA. The model was used for studying transmission dynamics...... and within-farm prevalence after different introductions of LA-MRSA into a farm. The spread of LA-MRSA throughout the farm mainly followed the movement of pigs. After spread of LA-MRSA had reached equilibrium, the prevalence of LA-MRSA shedders was predicted to be highest in the farrowing unit, independent...

  2. A 3-D CFD approach to the mechanistic prediction of forced convective critical heat flux at low quality

    International Nuclear Information System (INIS)

    Jean-Marie Le Corre; Cristina H Amon; Shi-Chune Yao

    2005-01-01

    Full text of publication follows: The prediction of the Critical Heat Flux (CHF) in a heat flux controlled boiling heat exchanger is important to assess the maximal thermal capability of the system. In the case of a nuclear reactor, CHF margin gain (using improved mixing vane grid design, for instance) can allow power up-rate and enhanced operating flexibility. In general, current nuclear core design procedures use quasi-1D approach to model the coolant thermal-hydraulic conditions within the fuel bundles coupled with fully empirical CHF prediction methods. In addition, several CHF mechanistic models have been developed in the past and coupled with 1D and quasi-1D thermal-hydraulic codes. These mechanistic models have demonstrated reasonable CHF prediction characteristics and, more remarkably, correct parametric trends over wide range of fluid conditions. However, since the phenomena leading to CHF are localized near the heater, models are needed to relate local quantities of interest to area-averaged quantities. As a consequence, large CHF prediction uncertainties may be introduced and 3D fluid characteristics (such as swirling flow) cannot be accounted properly. Therefore, a fully mechanistic approach to CHF prediction is, in general, not possible using the current approach. The development of CHF-enhanced fuel assembly designs requires the use of more advanced 3D coolant properties computations coupled with a CHF mechanistic modeling. In the present work, the commercial CFD code CFX-5 is used to compute 3D coolant conditions in a vertical heated tube with upward flow. Several CHF mechanistic models at low quality available in the literature are coupled with the CFD code by developing adequate models between local coolant properties and local parameters of interest to predict CHF. The prediction performances of these models are assessed using CHF databases available in the open literature and the 1995 CHF look-up table. Since CFD can reasonably capture 3D fluid

  3. Incorporating nitrogen fixing cyanobacteria in the global biogeochemical model HAMOCC

    Science.gov (United States)

    Paulsen, Hanna; Ilyina, Tatiana; Six, Katharina

    2015-04-01

    Nitrogen fixation by marine diazotrophs plays a fundamental role in the oceanic nitrogen and carbon cycle as it provides a major source of 'new' nitrogen to the euphotic zone that supports biological carbon export and sequestration. Since most global biogeochemical models include nitrogen fixation only diagnostically, they are not able to capture its spatial pattern sufficiently. Here we present the incorporation of an explicit, dynamic representation of diazotrophic cyanobacteria and the corresponding nitrogen fixation in the global ocean biogeochemical model HAMOCC (Hamburg Ocean Carbon Cycle model), which is part of the Max Planck Institute for Meteorology Earth system model (MPI-ESM). The parameterization of the diazotrophic growth is thereby based on available knowledge about the cyanobacterium Trichodesmium spp., which is considered as the most significant pelagic nitrogen fixer. Evaluation against observations shows that the model successfully reproduces the main spatial distribution of cyanobacteria and nitrogen fixation, covering large parts of the tropical and subtropical oceans. Besides the role of cyanobacteria in marine biogeochemical cycles, their capacity to form extensive surface blooms induces a number of bio-physical feedback mechanisms in the Earth system. The processes driving these interactions, which are related to the alteration of heat absorption, surface albedo and momentum input by wind, are incorporated in the biogeochemical and physical model of the MPI-ESM in order to investigate their impacts on a global scale. First preliminary results will be shown.

  4. Causation at Different Levels: Tracking the Commitments of Mechanistic Explanations

    DEFF Research Database (Denmark)

    Fazekas, Peter; Kertész, Gergely

    2011-01-01

    connections transparent. These general commitments get confronted with two claims made by certain proponents of the mechanistic approach: William Bechtel often argues that within the mechanistic framework it is possible to balance between reducing higher levels and maintaining their autonomy at the same time...... their autonomy at the same time than standard reductive accounts are, and that what mechanistic explanations are able to do at best is showing that downward causation does not exist....

  5. A mechanistic model of heat transfer for gas-liquid flow in vertical wellbore annuli.

    Science.gov (United States)

    Yin, Bang-Tang; Li, Xiang-Fang; Liu, Gang

    2018-01-01

    The most prominent aspect of multiphase flow is the variation in the physical distribution of the phases in the flow conduit known as the flow pattern. Several different flow patterns can exist under different flow conditions which have significant effects on liquid holdup, pressure gradient and heat transfer. Gas-liquid two-phase flow in an annulus can be found in a variety of practical situations. In high rate oil and gas production, it may be beneficial to flow fluids vertically through the annulus configuration between well tubing and casing. The flow patterns in annuli are different from pipe flow. There are both casing and tubing liquid films in slug flow and annular flow in the annulus. Multiphase heat transfer depends on the hydrodynamic behavior of the flow. There are very limited research results that can be found in the open literature for multiphase heat transfer in wellbore annuli. A mechanistic model of multiphase heat transfer is developed for different flow patterns of upward gas-liquid flow in vertical annuli. The required local flow parameters are predicted by use of the hydraulic model of steady-state multiphase flow in wellbore annuli recently developed by Yin et al. The modified heat-transfer model for single gas or liquid flow is verified by comparison with Manabe's experimental results. For different flow patterns, it is compared with modified unified Zhang et al. model based on representative diameters.

  6. Blinded prospective evaluation of computer-based mechanistic schizophrenia disease model for predicting drug response.

    Directory of Open Access Journals (Sweden)

    Hugo Geerts

    Full Text Available The tremendous advances in understanding the neurobiological circuits involved in schizophrenia have not translated into more effective treatments. An alternative strategy is to use a recently published 'Quantitative Systems Pharmacology' computer-based mechanistic disease model of cortical/subcortical and striatal circuits based upon preclinical physiology, human pathology and pharmacology. The physiology of 27 relevant dopamine, serotonin, acetylcholine, norepinephrine, gamma-aminobutyric acid (GABA and glutamate-mediated targets is calibrated using retrospective clinical data on 24 different antipsychotics. The model was challenged to predict quantitatively the clinical outcome in a blinded fashion of two experimental antipsychotic drugs; JNJ37822681, a highly selective low-affinity dopamine D(2 antagonist and ocaperidone, a very high affinity dopamine D(2 antagonist, using only pharmacology and human positron emission tomography (PET imaging data. The model correctly predicted the lower performance of JNJ37822681 on the positive and negative syndrome scale (PANSS total score and the higher extra-pyramidal symptom (EPS liability compared to olanzapine and the relative performance of ocaperidone against olanzapine, but did not predict the absolute PANSS total score outcome and EPS liability for ocaperidone, possibly due to placebo responses and EPS assessment methods. Because of its virtual nature, this modeling approach can support central nervous system research and development by accounting for unique human drug properties, such as human metabolites, exposure, genotypes and off-target effects and can be a helpful tool for drug discovery and development.

  7. On the closed form mechanistic modeling of milling: Specific cutting energy, torque, and power

    Science.gov (United States)

    Bayoumi, A. E.; Yücesan, G.; Hutton, D. V.

    1994-02-01

    Specific energy in metal cutting, defined as the energy expended in removing a unit volume of workpiece material, is formulated and determined using a previously developed closed form mechanistic force model for milling operations. Cutting power is computed from the cutting torque, cutting force, kinematics of the cutter, and the volumetric material removal rate. Closed form expressions for specific cutting energy were formulated and found to be functions of the process parameters: pressure and friction for both rake and flank surfaces and chip flow angle at the rake face of the tool. Friction is found to play a very important role in cutting torque and power. Experiments were carried out to determine the effects of feedrate, cutting speed, workpiece material, and flank wear land width on specific cutting energy. It was found that the specific cutting energy increases with a decrease in the chip thickness and with an increase in flank wear land.

  8. REM sleep behaviour disorder: prodromal and mechanistic insights for Parkinson's disease.

    Science.gov (United States)

    Tekriwal, Anand; Kern, Drew S; Tsai, Jean; Ince, Nuri F; Wu, Jianping; Thompson, John A; Abosch, Aviva

    2017-05-01

    Rapid eye movement (REM) sleep behaviour disorder (RBD) is characterised by complex motor enactment of dreams and is a potential prodromal marker of Parkinson's disease (PD). Of note, patients with PD observed during RBD episodes exhibit improved motor function, relative to baseline states during wake periods. Here, we review recent epidemiological and mechanistic findings supporting the prodromal value of RBD for PD, incorporating clinical and electrophysiological studies. Explanations for the improved motor function during RBD episodes are evaluated in light of recent publications. In addition, we present preliminary findings describing changes in the activity of the basal ganglia across the sleep-wake cycle that contribute to our understanding of RBD. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  9. Mechanistic facility safety and source term analysis

    International Nuclear Information System (INIS)

    PLYS, M.G.

    1999-01-01

    A PC-based computer program was created for facility safety and source term analysis at Hanford The program has been successfully applied to mechanistic prediction of source terms from chemical reactions in underground storage tanks, hydrogen combustion in double contained receiver tanks, and proccss evaluation including the potential for runaway reactions in spent nuclear fuel processing. Model features include user-defined facility room, flow path geometry, and heat conductors, user-defined non-ideal vapor and aerosol species, pressure- and density-driven gas flows, aerosol transport and deposition, and structure to accommodate facility-specific source terms. Example applications are presented here

  10. MECHANISTIC KINETIC MODELS FOR STEAM REFORMING OF CONCENTRATED CRUDE ETHANOL ON NI/AL2O3 CATALYST

    Directory of Open Access Journals (Sweden)

    O. A. OLAFADEHAN

    2015-05-01

    Full Text Available Mechanistic kinetic models were postulated for the catalytic steam reforming of concentrated crude ethanol on a Ni-based commercial catalyst at atmosphere pressure in the temperature range of 673-863 K, and at different catalyst weight to the crude ethanol molar flow rate ratio (in the range 0.9645-9.6451 kg catalyst h/kg mole crude ethanol in a stainless steel packed bed tubular microreactor. The models were based on Langmuir-Hinshelwood-Hougen-Watson (LHHW and Eley-Rideal (ER mechanisms. The optimization routine of Nelder-Mead simplex algorithm was used to estimate the inherent kinetic parameters in the proposed models. The selection of the best kinetic model amongst the rival kinetic models was based on physicochemical, statistical and thermodynamic scrutinies. The rate determining step for the steam reforming of concentrated crude ethanol on Ni/Al2O3 catalyst was found to be surface reaction between chemisorbed CH3O and O when hydrogen and oxygen were adsorbed as monomolecular species on the catalyst surface. Excellent agreement was obtained between the experimental rate of reaction and conversion of crude ethanol, and the simulated results, with ADD% being ±0.46.

  11. Simulation of Forest Carbon Fluxes Using Model Incorporation and Data Assimilation

    OpenAIRE

    Min Yan; Xin Tian; Zengyuan Li; Erxue Chen; Xufeng Wang; Zongtao Han; Hong Sun

    2016-01-01

    This study improved simulation of forest carbon fluxes in the Changbai Mountains with a process-based model (Biome-BGC) using incorporation and data assimilation. Firstly, the original remote sensing-based MODIS MOD_17 GPP (MOD_17) model was optimized using refined input data and biome-specific parameters. The key ecophysiological parameters of the Biome-BGC model were determined through the Extended Fourier Amplitude Sensitivity Test (EFAST) sensitivity analysis. Then the optimized MOD_17 mo...

  12. INCORPORATING MULTIPLE OBJECTIVES IN PLANNING MODELS OF LOW-RESOURCE FARMERS

    OpenAIRE

    Flinn, John C.; Jayasuriya, Sisira; Knight, C. Gregory

    1980-01-01

    Linear goal programming provides a means of formally incorporating the multiple goals of a household into the analysis of farming systems. Using this approach, the set of plans which come as close as possible to achieving a set of desired goals under conditions of land and cash scarcity are derived for a Filipino tenant farmer. A challenge in making LGP models empirically operational is the accurate definition of the goals of the farm household being modelled.

  13. Mechanistic modeling of biocorrosion caused by biofilms of sulfate reducing bacteria and acid producing bacteria.

    Science.gov (United States)

    Xu, Dake; Li, Yingchao; Gu, Tingyue

    2016-08-01

    Biocorrosion is also known as microbiologically influenced corrosion (MIC). Most anaerobic MIC cases can be classified into two major types. Type I MIC involves non-oxygen oxidants such as sulfate and nitrate that require biocatalysis for their reduction in the cytoplasm of microbes such as sulfate reducing bacteria (SRB) and nitrate reducing bacteria (NRB). This means that the extracellular electrons from the oxidation of metal such as iron must be transported across cell walls into the cytoplasm. Type II MIC involves oxidants such as protons that are secreted by microbes such as acid producing bacteria (APB). The biofilms in this case supply the locally high concentrations of oxidants that are corrosive without biocatalysis. This work describes a mechanistic model that is based on the biocatalytic cathodic sulfate reduction (BCSR) theory. The model utilizes charge transfer and mass transfer concepts to describe the SRB biocorrosion process. The model also includes a mechanism to describe APB attack based on the local acidic pH at a pit bottom. A pitting prediction software package has been created based on the mechanisms. It predicts long-term pitting rates and worst-case scenarios after calibration using SRB short-term pit depth data. Various parameters can be investigated through computer simulation. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. Mechanistic applicability domain classification of a local lymph node assay dataset for skin sensitization.

    Science.gov (United States)

    Roberts, David W; Patlewicz, Grace; Kern, Petra S; Gerberick, Frank; Kimber, Ian; Dearman, Rebecca J; Ryan, Cindy A; Basketter, David A; Aptula, Aynur O

    2007-07-01

    The goal of eliminating animal testing in the predictive identification of chemicals with the intrinsic ability to cause skin sensitization is an important target, the attainment of which has recently been brought into even sharper relief by the EU Cosmetics Directive and the requirements of the REACH legislation. Development of alternative methods requires that the chemicals used to evaluate and validate novel approaches comprise not only confirmed skin sensitizers and non-sensitizers but also substances that span the full chemical mechanistic spectrum associated with skin sensitization. To this end, a recently published database of more than 200 chemicals tested in the mouse local lymph node assay (LLNA) has been examined in relation to various chemical reaction mechanistic domains known to be associated with sensitization. It is demonstrated here that the dataset does cover the main reaction mechanistic domains. In addition, it is shown that assignment to a reaction mechanistic domain is a critical first step in a strategic approach to understanding, ultimately on a quantitative basis, how chemical properties influence the potency of skin sensitizing chemicals. This understanding is necessary if reliable non-animal approaches, including (quantitative) structure-activity relationships (Q)SARs, read-across, and experimental chemistry based models, are to be developed.

  15. A code reviewer assignment model incorporating the competence differences and participant preferences

    Directory of Open Access Journals (Sweden)

    Wang Yanqing

    2016-03-01

    Full Text Available A good assignment of code reviewers can effectively utilize the intellectual resources, assure code quality and improve programmers’ skills in software development. However, little research on reviewer assignment of code review has been found. In this study, a code reviewer assignment model is created based on participants’ preference to reviewing assignment. With a constraint of the smallest size of a review group, the model is optimized to maximize review outcomes and avoid the negative impact of “mutual admiration society”. This study shows that the reviewer assignment strategies incorporating either the reviewers’ preferences or the authors’ preferences get much improvement than a random assignment. The strategy incorporating authors’ preference makes higher improvement than that incorporating reviewers’ preference. However, when the reviewers’ and authors’ preference matrixes are merged, the improvement becomes moderate. The study indicates that the majority of the participants have a strong wish to work with reviewers and authors having highest competence. If we want to satisfy the preference of both reviewers and authors at the same time, the overall improvement of learning outcomes may be not the best.

  16. Computational Model of the Fathead Minnow Hypothalamic-Pituitary-Gonadal Axis: Incorporating Protein Synthesis in Improving Predictability of Responses to Endocrine Active Chemicals

    Science.gov (United States)

    There is international concern about chemicals that alter endocrine system function in humans and/or wildlife and subsequently cause adverse effects. We previously developed a mechanistic computational model of the hypothalamic-pituitary-gonadal (HPG) axis in female fathead minno...

  17. Mechanistic model to predict colostrum intake based on deuterium oxide dilution technique data and impact of gestation and prefarrowing diets on piglet intake and sow yield of colostrum

    DEFF Research Database (Denmark)

    Theil, Peter Kappel; Flummer, Christine; Hurley, W L

    2014-01-01

    The aims of the present study were to quantify colostrum intake (CI) of piglets using the D2O dilution technique, to develop a mechanistic model to predict CI, to compare these data with CI predicted by a previous empirical predictive model developed for bottle-fed piglets, and to study how...... composition of diets fed to gestating sows affected piglet CI, sow colostrum yield (CY), and colostrum composition. In total, 240 piglets from 40 litters were enriched with D2O. The CI measured by D2O from birth until 24 h after the birth of first-born piglet was on average 443 g (SD 151). Based on measured...... CI, a mechanistic model to predict CI was developed using piglet characteristics (24-h weight gain [WG; g], BW at birth [BWB; kg], and duration of CI [D; min]: CI, g = –106 + 2.26 WG + 200 BWB + 0.111 D – 1,414 WG/D + 0.0182 WG/BWB (R2 = 0.944). This model was used to predict the CI for all colostrum...

  18. Incorporating model parameter uncertainty into inverse treatment planning

    International Nuclear Information System (INIS)

    Lian Jun; Xing Lei

    2004-01-01

    Radiobiological treatment planning depends not only on the accuracy of the models describing the dose-response relation of different tumors and normal tissues but also on the accuracy of tissue specific radiobiological parameters in these models. Whereas the general formalism remains the same, different sets of model parameters lead to different solutions and thus critically determine the final plan. Here we describe an inverse planning formalism with inclusion of model parameter uncertainties. This is made possible by using a statistical analysis-based frameset developed by our group. In this formalism, the uncertainties of model parameters, such as the parameter a that describes tissue-specific effect in the equivalent uniform dose (EUD) model, are expressed by probability density function and are included in the dose optimization process. We found that the final solution strongly depends on distribution functions of the model parameters. Considering that currently available models for computing biological effects of radiation are simplistic, and the clinical data used to derive the models are sparse and of questionable quality, the proposed technique provides us with an effective tool to minimize the effect caused by the uncertainties in a statistical sense. With the incorporation of the uncertainties, the technique has potential for us to maximally utilize the available radiobiology knowledge for better IMRT treatment

  19. FOAM3D: A numerical simulator for mechanistic prediciton of foam displacement in multidimensions

    Energy Technology Data Exchange (ETDEWEB)

    Kovscek, A.R.; Patzek, T.W. [Lawrence Berkeley Laboratory, Berkeley, CA (United States); Radke, C.J. [Univ. of California, Berkeley, CA (United States)

    1995-03-01

    Field application of foam is a technically viable enhanced oil recovery process (EOR) as demonstrated by recent steam-foam field studies. Traditional gas-displacement processes, such as steam drive, are improved substantially by controlling gas mobility and thereby improving volumetric displacement efficiency. For instance, Patzek and Koinis showed major oil-recovery response after about two years of foam injection in two different pilot studies at the Kern River field. They report increased production of 5.5 to 14% of the original oil in place over a five year period. Because reservoir-scale simulation is a vital component of the engineering and economic evaluation of any EOR project, efficient application of foam as a displacement fluid requires a predictive numerical model of foam displacement. A mechanistic model would also expedite scale-up of the process from the laboratory to the field scale. No general, mechanistic, field-scale model for foam displacement is currently in use.

  20. Effect of ingested lipids on drug dissolution and release with concurrent digestion: a modeling approach

    Science.gov (United States)

    Buyukozturk, Fulden; Di Maio, Selena; Budil, David E.; Carrier, Rebecca L.

    2014-01-01

    Purpose To mechanistically study and model the effect of lipids, either from food or self-emulsifying drug delivery systems (SEDDS), on drug transport in the intestinal lumen. Methods Simultaneous lipid digestion, dissolution/release, and drug partitioning were experimentally studied and modeled for two dosing scenarios: solid drug with a food-associated lipid (soybean oil) and drug solubilized in a model SEDDS (soybean oil and Tween 80 at 1:1 ratio). Rate constants for digestion, permeability of emulsion droplets, and partition coefficients in micellar and oil phases were measured, and used to numerically solve the developed model. Results Strong influence of lipid digestion on drug release from SEDDS and solid drug dissolution into food-associated lipid emulsion were observed and predicted by the developed model. 90 minutes after introduction of SEDDS, there was 9% and 70% drug release in the absence and presence of digestion, respectively. However, overall drug dissolution in the presence of food-associated lipids occurred over a longer period than without digestion. Conclusion A systems-based mechanistic model incorporating simultaneous dynamic processes occurring upon dosing of drug with lipids enabled prediction of aqueous drug concentration profile. This model, once incorporated with a pharmacokinetic model considering processes of drug absorption and drug lymphatic transport in the presence of lipids, could be highly useful for quantitative prediction of impact of lipids on bioavailability of drugs. PMID:24234918

  1. Can ligand addition to soil enhance Cd phytoextraction? A mechanistic model study.

    Science.gov (United States)

    Lin, Zhongbing; Schneider, André; Nguyen, Christophe; Sterckeman, Thibault

    2014-11-01

    Phytoextraction is a potential method for cleaning Cd-polluted soils. Ligand addition to soil is expected to enhance Cd phytoextraction. However, experimental results show that this addition has contradictory effects on plant Cd uptake. A mechanistic model simulating the reaction kinetics (adsorption on solid phase, complexation in solution), transport (convection, diffusion) and root absorption (symplastic, apoplastic) of Cd and its complexes in soil was developed. This was used to calculate plant Cd uptake with and without ligand addition in a great number of combinations of soil, ligand and plant characteristics, varying the parameters within defined domains. Ligand addition generally strongly reduced hydrated Cd (Cd(2+)) concentration in soil solution through Cd complexation. Dissociation of Cd complex ([Formula: see text]) could not compensate for this reduction, which greatly lowered Cd(2+) symplastic uptake by roots. The apoplastic uptake of [Formula: see text] was not sufficient to compensate for the decrease in symplastic uptake. This explained why in the majority of the cases, ligand addition resulted in the reduction of the simulated Cd phytoextraction. A few results showed an enhanced phytoextraction in very particular conditions (strong plant transpiration with high apoplastic Cd uptake capacity), but this enhancement was very limited, making chelant-enhanced phytoextraction poorly efficient for Cd.

  2. Disruption of steroidogenesis: Cell models for mechanistic investigations and as screening tools.

    Science.gov (United States)

    Odermatt, Alex; Strajhar, Petra; Engeli, Roger T

    2016-04-01

    In the modern world, humans are exposed during their whole life to a large number of synthetic chemicals. Some of these chemicals have the potential to disrupt endocrine functions and contribute to the development and/or progression of major diseases. Every year approximately 1000 novel chemicals, used in industrial production, agriculture, consumer products or as pharmaceuticals, are reaching the market, often with limited safety assessment regarding potential endocrine activities. Steroids are essential endocrine hormones, and the importance of the steroidogenesis pathway as a target for endocrine disrupting chemicals (EDCs) has been recognized by leading scientists and authorities. Cell lines have a prominent role in the initial stages of toxicity assessment, i.e. for mechanistic investigations and for the medium to high throughput analysis of chemicals for potential steroidogenesis disrupting activities. Nevertheless, the users have to be aware of the limitations of the existing cell models in order to apply them properly, and there is a great demand for improved cell-based testing systems and protocols. This review intends to provide an overview of the available cell lines for studying effects of chemicals on gonadal and adrenal steroidogenesis, their use and limitations, as well as the need for future improvements of cell-based testing systems and protocols. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. Wear-dependent specific coefficients in a mechanistic model for turning of nickel-based superalloy with ceramic tools

    Science.gov (United States)

    López de Lacalle, Luis Norberto; Urbicain Pelayo, Gorka; Fernández-Valdivielso, Asier; Alvarez, Alvaro; González, Haizea

    2017-09-01

    Difficult to cut materials such as nickel and titanium alloys are used in the aeronautical industry, the former alloys due to its heat-resistant behavior and the latter for the low weight - high strength ratio. Ceramic tools made out alumina with reinforce SiC whiskers are a choice in turning for roughing and semifinishing workpiece stages. Wear rate is high in the machining of these alloys, and consequently cutting forces tends to increase along one operation. This paper establishes the cutting force relation between work-piece and tool in the turning of such difficult-to-cut alloys by means of a mechanistic cutting force model that considers the tool wear effect. The cutting force model demonstrates the force sensitivity to the cutting engagement parameters (ap, f) when using ceramic inserts and wear is considered. Wear is introduced through a cutting time factor, being useful in real conditions taking into account that wear quickly appears in alloys machining. A good accuracy in the cutting force model coefficients is the key issue for an accurate prediction of turning forces, which could be used as criteria for tool replacement or as input for chatter or other models.

  4. Mechanistic Prediction of the Effect of Microstructural Coarsening on Creep Response of SnAgCu Solder Joints

    Science.gov (United States)

    Mukherjee, S.; Chauhan, P.; Osterman, M.; Dasgupta, A.; Pecht, M.

    2016-07-01

    Mechanistic microstructural models have been developed to capture the effect of isothermal aging on time dependent viscoplastic response of Sn3.0Ag0.5Cu (SAC305) solders. SnAgCu (SAC) solders undergo continuous microstructural coarsening during both storage and service because of their high homologous temperature. The microstructures of these low melting point alloys continuously evolve during service. This results in evolution of creep properties of the joint over time, thereby influencing the long term reliability of microelectronic packages. It is well documented that isothermal aging degrades the creep resistance of SAC solder. SAC305 alloy is aged for (24-1000) h at (25-100)°C (~0.6-0.8 × T melt). Cross-sectioning and image processing techniques were used to periodically quantify the effect of isothermal aging on phase coarsening and evolution. The parameters monitored during isothermal aging include size, area fraction, and inter-particle spacing of nanoscale Ag3Sn intermetallic compounds (IMCs) and the volume fraction of micronscale Cu6Sn5 IMCs, as well as the area fraction of pure tin dendrites. Effects of microstructural evolution on secondary creep constitutive response of SAC305 solder joints were then modeled using a mechanistic multiscale creep model. The mechanistic phenomena modeled include: (1) dispersion strengthening by coarsened nanoscale Ag3Sn IMCs in the eutectic phase; and (2) load sharing between pro-eutectic Sn dendrites and the surrounding coarsened eutectic Sn-Ag phase and microscale Cu6Sn5 IMCs. The coarse-grained polycrystalline Sn microstructure in SAC305 solder was not captured in the above model because isothermal aging does not cause any significant change in the initial grain size and orientation of SAC305 solder joints. The above mechanistic model can successfully capture the drop in creep resistance due to the influence of isothermal aging on SAC305 single crystals. Contribution of grain boundary sliding to the creep strain of

  5. Mechanistic study of aerosol dry deposition on vegetated canopies

    International Nuclear Information System (INIS)

    Petroff, A.

    2005-04-01

    The dry deposition of aerosols onto vegetated canopies is modelled through a mechanistic approach. The interaction between aerosols and vegetation is first formulated by using a set of parameters, which are defined at the local scale of one surface. The overall deposition is then deduced at the canopy scale through an up-scaling procedure based on the statistic distribution parameters. This model takes into account the canopy structural and morphological properties, and the main characteristics of the turbulent flow. Deposition mechanisms considered are Brownian diffusion, interception, initial and turbulent impaction, initially with coniferous branches and then with entire canopies of different roughness, such as grass, crop field and forest. (author)

  6. Incorporation of ice sheet models into an Earth system model: Focus on methodology of coupling

    Science.gov (United States)

    Rybak, Oleg; Volodin, Evgeny; Morozova, Polina; Nevecherja, Artiom

    2018-03-01

    Elaboration of a modern Earth system model (ESM) requires incorporation of ice sheet dynamics. Coupling of an ice sheet model (ICM) to an AOGCM is complicated by essential differences in spatial and temporal scales of cryospheric, atmospheric and oceanic components. To overcome this difficulty, we apply two different approaches for the incorporation of ice sheets into an ESM. Coupling of the Antarctic ice sheet model (AISM) to the AOGCM is accomplished via using procedures of resampling, interpolation and assigning to the AISM grid points annually averaged meanings of air surface temperature and precipitation fields generated by the AOGCM. Surface melting, which takes place mainly on the margins of the Antarctic peninsula and on ice shelves fringing the continent, is currently ignored. AISM returns anomalies of surface topography back to the AOGCM. To couple the Greenland ice sheet model (GrISM) to the AOGCM, we use a simple buffer energy- and water-balance model (EWBM-G) to account for orographically-driven precipitation and other sub-grid AOGCM-generated quantities. The output of the EWBM-G consists of surface mass balance and air surface temperature to force the GrISM, and freshwater run-off to force thermohaline circulation in the oceanic block of the AOGCM. Because of a rather complex coupling procedure of GrIS compared to AIS, the paper mostly focuses on Greenland.

  7. Incorporation particle creation and annihilation into Bohm's Pilot Wave model

    Energy Technology Data Exchange (ETDEWEB)

    Sverdlov, Roman [Raman Research Institute, C.V. Raman Avenue, Sadashiva Nagar, Bangalore, Karnataka, 560080 (India)

    2011-07-08

    The purpose of this paper is to come up with a Pilot Wave model of quantum field theory that incorporates particle creation and annihilation without sacrificing determinism; this theory is subsequently coupled with gravity.

  8. Predicting soil-to-plant transfer of radionuclides with a mechanistic model (BioRUR)

    Energy Technology Data Exchange (ETDEWEB)

    Casadesus, J. [Servei de Camps Experimentals, Universitat de Barcelona, Avda Diagonal 645, 08028 Barcelona (Spain); Sauras-Yera, T. [Departament de Biologia Vegetal, Facultat de Biologia, Universitat de Barcelona, Avda Diagonal 645, 08028 Barcelona (Spain)], E-mail: msauras@ub.edu; Vallejo, V.R. [Departament de Biologia Vegetal, Facultat de Biologia, Universitat de Barcelona, Avda Diagonal 645, 08028 Barcelona (Spain); Centro de Estudios Ambientales del Mediterraneo, Charles Darwin 14, Parc Tecnologic, 46980 Paterna, Valencia (Spain)

    2008-05-15

    BioRUR model has been developed for the simulation of radionuclide (RN) transfer through physical and biological compartments, based on the available information on the transfer of their nutrient analogues. The model assumes that radionuclides are transferred from soil to plant through the same pathways as their nutrient analogues, where K and Ca are the analogues of Cs and Sr, respectively. Basically, the transfer of radionuclide between two compartments is calculated as the transfer of nutrient multiplied by the ratio of concentrations of RN to nutrient, corrected by a selectivity coefficient. Hydroponic experiments showed the validity of this assumption for root uptake of Cs and Sr and reported a selectivity coefficient around 1.0 for both. However, the application of this approach to soil-to-plant transfer raises some questions on which are the effective concentrations of RN and nutrient detected by the plant uptake mechanism. This paper describes the evaluation of two configurations of BioRUR, one which simplifies the soil as an homogeneous pool, and the other which considers that some concentration gradients develop around roots and therefore ion concentrations at the root surface are different from those of the bulk soil. The results show a good fit between the observed Sr transfer and the mechanistic simulations, even when a homogeneous soil is considered. On the other hand, Cs transfer is overestimated by two orders of magnitude if the development of a decreasing K profile around roots is not taken into account.

  9. Predicting soil-to-plant transfer of radionuclides with a mechanistic model (BioRUR)

    International Nuclear Information System (INIS)

    Casadesus, J.; Sauras-Yera, T.; Vallejo, V.R.

    2008-01-01

    BioRUR model has been developed for the simulation of radionuclide (RN) transfer through physical and biological compartments, based on the available information on the transfer of their nutrient analogues. The model assumes that radionuclides are transferred from soil to plant through the same pathways as their nutrient analogues, where K and Ca are the analogues of Cs and Sr, respectively. Basically, the transfer of radionuclide between two compartments is calculated as the transfer of nutrient multiplied by the ratio of concentrations of RN to nutrient, corrected by a selectivity coefficient. Hydroponic experiments showed the validity of this assumption for root uptake of Cs and Sr and reported a selectivity coefficient around 1.0 for both. However, the application of this approach to soil-to-plant transfer raises some questions on which are the effective concentrations of RN and nutrient detected by the plant uptake mechanism. This paper describes the evaluation of two configurations of BioRUR, one which simplifies the soil as an homogeneous pool, and the other which considers that some concentration gradients develop around roots and therefore ion concentrations at the root surface are different from those of the bulk soil. The results show a good fit between the observed Sr transfer and the mechanistic simulations, even when a homogeneous soil is considered. On the other hand, Cs transfer is overestimated by two orders of magnitude if the development of a decreasing K profile around roots is not taken into account

  10. Improving Watershed-Scale Hydrodynamic Models by Incorporating Synthetic 3D River Bathymetry Network

    Science.gov (United States)

    Dey, S.; Saksena, S.; Merwade, V.

    2017-12-01

    Digital Elevation Models (DEMs) have an incomplete representation of river bathymetry, which is critical for simulating river hydrodynamics in flood modeling. Generally, DEMs are augmented with field collected bathymetry data, but such data are available only at individual reaches. Creating a hydrodynamic model covering an entire stream network in the basin requires bathymetry for all streams. This study extends a conceptual bathymetry model, River Channel Morphology Model (RCMM), to estimate the bathymetry for an entire stream network for application in hydrodynamic modeling using a DEM. It is implemented at two large watersheds with different relief and land use characterizations: coastal Guadalupe River basin in Texas with flat terrain and a relatively urban White River basin in Indiana with more relief. After bathymetry incorporation, both watersheds are modeled using HEC-RAS (1D hydraulic model) and Interconnected Pond and Channel Routing (ICPR), a 2-D integrated hydrologic and hydraulic model. A comparison of the streamflow estimated by ICPR at the outlet of the basins indicates that incorporating bathymetry influences streamflow estimates. The inundation maps show that bathymetry has a higher impact on flat terrains of Guadalupe River basin when compared to the White River basin.

  11. Generative mechanistic explanation building in undergraduate molecular and cellular biology

    Science.gov (United States)

    Southard, Katelyn M.; Espindola, Melissa R.; Zaepfel, Samantha D.; Bolger, Molly S.

    2017-09-01

    When conducting scientific research, experts in molecular and cellular biology (MCB) use specific reasoning strategies to construct mechanistic explanations for the underlying causal features of molecular phenomena. We explored how undergraduate students applied this scientific practice in MCB. Drawing from studies of explanation building among scientists, we created and applied a theoretical framework to explore the strategies students use to construct explanations for 'novel' biological phenomena. Specifically, we explored how students navigated the multi-level nature of complex biological systems using generative mechanistic reasoning. Interviews were conducted with introductory and upper-division biology students at a large public university in the United States. Results of qualitative coding revealed key features of students' explanation building. Students used modular thinking to consider the functional subdivisions of the system, which they 'filled in' to varying degrees with mechanistic elements. They also hypothesised the involvement of mechanistic entities and instantiated abstract schema to adapt their explanations to unfamiliar biological contexts. Finally, we explored the flexible thinking that students used to hypothesise the impact of mutations on multi-leveled biological systems. Results revealed a number of ways that students drew mechanistic connections between molecules, functional modules (sets of molecules with an emergent function), cells, tissues, organisms and populations.

  12. Inferring the Impact of Regulatory Mechanisms that Underpin CD8+ T Cell Control of B16 Tumor Growth In vivo Using Mechanistic Models and Simulation.

    Science.gov (United States)

    Klinke, David J; Wang, Qing

    2016-01-01

    A major barrier for broadening the efficacy of immunotherapies for cancer is identifying key mechanisms that limit the efficacy of tumor infiltrating lymphocytes. Yet, identifying these mechanisms using human samples and mouse models for cancer remains a challenge. While interactions between cancer and the immune system are dynamic and non-linear, identifying the relative roles that biological components play in regulating anti-tumor immunity commonly relies on human intuition alone, which can be limited by cognitive biases. To assist natural intuition, modeling and simulation play an emerging role in identifying therapeutic mechanisms. To illustrate the approach, we developed a multi-scale mechanistic model to describe the control of tumor growth by a primary response of CD8+ T cells against defined tumor antigens using the B16 C57Bl/6 mouse model for malignant melanoma. The mechanistic model was calibrated to data obtained following adenovirus-based immunization and validated to data obtained following adoptive transfer of transgenic CD8+ T cells. More importantly, we use simulation to test whether the postulated network topology, that is the modeled biological components and their associated interactions, is sufficient to capture the observed anti-tumor immune response. Given the available data, the simulation results also provided a statistical basis for quantifying the relative importance of different mechanisms that underpin CD8+ T cell control of B16F10 growth. By identifying conditions where the postulated network topology is incomplete, we illustrate how this approach can be used as part of an iterative design-build-test cycle to expand the predictive power of the model.

  13. Mechanistic Physiologically Based Pharmacokinetic (PBPK) Model of the Heart Accounting for Inter-Individual Variability: Development and Performance Verification.

    Science.gov (United States)

    Tylutki, Zofia; Mendyk, Aleksander; Polak, Sebastian

    2018-04-01

    Modern model-based approaches to cardiac safety and efficacy assessment require accurate drug concentration-effect relationship establishment. Thus, knowledge of the active concentration of drugs in heart tissue is desirable along with inter-subject variability influence estimation. To that end, we developed a mechanistic physiologically based pharmacokinetic model of the heart. The models were described with literature-derived parameters and written in R, v.3.4.0. Five parameters were estimated. The model was fitted to amitriptyline and nortriptyline concentrations after an intravenous infusion of amitriptyline. The cardiac model consisted of 5 compartments representing the pericardial fluid, heart extracellular water, and epicardial intracellular, midmyocardial intracellular, and endocardial intracellular fluids. Drug cardiac metabolism, passive diffusion, active efflux, and uptake were included in the model as mechanisms involved in the drug disposition within the heart. The model accounted for inter-individual variability. The estimates of optimized parameters were within physiological ranges. The model performance was verified by simulating 5 clinical studies of amitriptyline intravenous infusion, and the simulated pharmacokinetic profiles agreed with clinical data. The results support the model feasibility. The proposed structure can be tested with the goal of improving the patient-specific model-based cardiac safety assessment and offers a framework for predicting cardiac concentrations of various xenobiotics. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

  14. "Ratio via Machina": Three Standards of Mechanistic Explanation in Sociology

    Science.gov (United States)

    Aviles, Natalie B.; Reed, Isaac Ariail

    2017-01-01

    Recently, sociologists have expended much effort in attempts to define social mechanisms. We intervene in these debates by proposing that sociologists in fact have a choice to make between three standards of what constitutes a good mechanistic explanation: substantial, formal, and metaphorical mechanistic explanation. All three standards are…

  15. Mechanistic evidence for a ring-opening pathway in the Pd-catalyzed direct arylation of benzoxazoles

    DEFF Research Database (Denmark)

    Sanchez, R.S.; Zhuravlev, Fedor

    2007-01-01

    The direct Pd-catalyzed arylation of 5-substituted benzoxazoles, used as a mechanistic model for 1,3-azoles, was investigated experimentally and computationally. The results of the primary deuterium kinetic isotope effect, Hammett studies, and H/D exchange were shown to be inconsistent with the r......The direct Pd-catalyzed arylation of 5-substituted benzoxazoles, used as a mechanistic model for 1,3-azoles, was investigated experimentally and computationally. The results of the primary deuterium kinetic isotope effect, Hammett studies, and H/D exchange were shown to be inconsistent...... with the rate-limiting electrophilic or concerted palladation. A mechanism, proposed on the basis of kinetic and computational studies, includes generation of isocyanophenolate as the key step. The DFT calculations suggest that the overall catalytic cycle is facile and is largely controlled by the C-H acidity...

  16. Toward mechanistic classification of enzyme functions.

    Science.gov (United States)

    Almonacid, Daniel E; Babbitt, Patricia C

    2011-06-01

    Classification of enzyme function should be quantitative, computationally accessible, and informed by sequences and structures to enable use of genomic information for functional inference and other applications. Large-scale studies have established that divergently evolved enzymes share conserved elements of structure and common mechanistic steps and that convergently evolved enzymes often converge to similar mechanisms too, suggesting that reaction mechanisms could be used to develop finer-grained functional descriptions than provided by the Enzyme Commission (EC) system currently in use. Here we describe how evolution informs these structure-function mappings and review the databases that store mechanisms of enzyme reactions along with recent developments to measure ligand and mechanistic similarities. Together, these provide a foundation for new classifications of enzyme function. Copyright © 2011 Elsevier Ltd. All rights reserved.

  17. Predicting interactions from mechanistic information: Can omic data validate theories?

    International Nuclear Information System (INIS)

    Borgert, Christopher J.

    2007-01-01

    To address the most pressing and relevant issues for improving mixture risk assessment, researchers must first recognize that risk assessment is driven by both regulatory requirements and scientific research, and that regulatory concerns may expand beyond the purely scientific interests of researchers. Concepts of 'mode of action' and 'mechanism of action' are used in particular ways within the regulatory arena, depending on the specific assessment goals. The data requirements for delineating a mode of action and predicting interactive toxicity in mixtures are not well defined from a scientific standpoint due largely to inherent difficulties in testing certain underlying assumptions. Understanding the regulatory perspective on mechanistic concepts will be important for designing experiments that can be interpreted clearly and applied in risk assessments without undue reliance on extrapolation and assumption. In like fashion, regulators and risk assessors can be better equipped to apply mechanistic data if the concepts underlying mechanistic research and the limitations that must be placed on interpretation of mechanistic data are understood. This will be critically important for applying new technologies to risk assessment, such as functional genomics, proteomics, and metabolomics. It will be essential not only for risk assessors to become conversant with the language and concepts of mechanistic research, including new omic technologies, but also, for researchers to become more intimately familiar with the challenges and needs of risk assessment

  18. Explanation and inference: Mechanistic and functional explanations guide property generalization

    Directory of Open Access Journals (Sweden)

    Tania eLombrozo

    2014-09-01

    Full Text Available The ability to generalize from the known to the unknown is central to learning and inference. Two experiments explore the relationship between how a property is explained and how that property is generalized to novel species and artifacts. The experiments contrast the consequences of explaining a property mechanistically, by appeal to parts and processes, with the consequences of explaining the property functionally, by appeal to functions and goals. The findings suggest that properties that are explained functionally are more likely to be generalized on the basis of shared functions, with a weaker relationship between mechanistic explanations and generalization on the basis of shared parts and processes. The influence of explanation type on generalization holds even though all participants are provided with the same mechanistic and functional information, and whether an explanation type is freely generated (Experiment 1, experimentally provided (Experiment 2, or experimentally induced (Experiment 2. The experiments also demonstrate that explanations and generalizations of a particular type (mechanistic or functional can be experimentally induced by providing sample explanations of that type, with a comparable effect when the sample explanations come from the same domain or from a different domains. These results suggest that explanations serve as a guide to generalization, and contribute to a growing body of work supporting the value of distinguishing mechanistic and functional explanations.

  19. Explanation and inference: mechanistic and functional explanations guide property generalization.

    Science.gov (United States)

    Lombrozo, Tania; Gwynne, Nicholas Z

    2014-01-01

    The ability to generalize from the known to the unknown is central to learning and inference. Two experiments explore the relationship between how a property is explained and how that property is generalized to novel species and artifacts. The experiments contrast the consequences of explaining a property mechanistically, by appeal to parts and processes, with the consequences of explaining the property functionally, by appeal to functions and goals. The findings suggest that properties that are explained functionally are more likely to be generalized on the basis of shared functions, with a weaker relationship between mechanistic explanations and generalization on the basis of shared parts and processes. The influence of explanation type on generalization holds even though all participants are provided with the same mechanistic and functional information, and whether an explanation type is freely generated (Experiment 1), experimentally provided (Experiment 2), or experimentally induced (Experiment 2). The experiments also demonstrate that explanations and generalizations of a particular type (mechanistic or functional) can be experimentally induced by providing sample explanations of that type, with a comparable effect when the sample explanations come from the same domain or from a different domains. These results suggest that explanations serve as a guide to generalization, and contribute to a growing body of work supporting the value of distinguishing mechanistic and functional explanations.

  20. Advanced Methods for Incorporating Solar Energy Technologies into Electric Sector Capacity-Expansion Models: Literature Review and Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Sullivan, P.; Eurek, K.; Margolis, R.

    2014-07-01

    Because solar power is a rapidly growing component of the electricity system, robust representations of solar technologies should be included in capacity-expansion models. This is a challenge because modeling the electricity system--and, in particular, modeling solar integration within that system--is a complex endeavor. This report highlights the major challenges of incorporating solar technologies into capacity-expansion models and shows examples of how specific models address those challenges. These challenges include modeling non-dispatchable technologies, determining which solar technologies to model, choosing a spatial resolution, incorporating a solar resource assessment, and accounting for solar generation variability and uncertainty.

  1. Mechanistic considerations in benzene physiological model development.

    Science.gov (United States)

    Medinsky, M A; Kenyon, E M; Seaton, M J; Schlosser, P M

    1996-12-01

    Benzene, an important industrial solvent, is also present in unleaded gasoline and cigarette smoke. The hematotoxic effects of benzene in humans are well documented and include aplastic anemia, pancytopenia, and acute myelogenous leukemia. However, the risks of leukemia at low exposure concentrations have not been established. A combination of metabolites (hydroquinone and phenol, for example) may be necessary to duplicate the hematotoxic effect of benzene, perhaps due in part to the synergistic effect of phenol on myeloperoxidase-mediated oxidation of hydroquinone to the reactive metabolite benzoquinone. Because benzene and its hydroxylated metabolites (phenol, hydroquinone, and catechol) are substrates for the same cytochrome P450 enzymes, competitive interactions among the metabolites are possible. In vivo data on metabolite formation by mice exposed to various benzene concentrations are consistent with competitive inhibition of phenol oxidation by benzene. In vitro studies of the metabolic oxidation of benzene, phenol, and hydroquinone are consistent with the mechanism of competitive interaction among the metabolites. The dosimetry of benzene and its metabolites in the target tissue, bone marrow, depends on the balance of activation processes such as enzymatic oxidation and deactivation processes such as conjugation and excretion. Phenol, the primary benzene metabolite, can undergo both oxidation and conjugation. Thus the potential exists for competition among various enzymes for phenol. Zonal localization of phase I and phase II enzymes in various regions of the liver acinus also impacts this competition. Biologically based dosimetry models that incorporate the important determinants of benzene flux, including interactions with other chemicals, will enable prediction of target tissue doses of benzene and metabolites at low exposure concentrations relevant for humans.

  2. The physicochemical process of bacterial attachment to abiotic surfaces: Challenges for mechanistic studies, predictability and the development of control strategies.

    Science.gov (United States)

    Wang, Yi; Lee, Sui Mae; Dykes, Gary

    2015-01-01

    Bacterial attachment to abiotic surfaces can be explained as a physicochemical process. Mechanisms of the process have been widely studied but are not yet well understood due to their complexity. Physicochemical processes can be influenced by various interactions and factors in attachment systems, including, but not limited to, hydrophobic interactions, electrostatic interactions and substratum surface roughness. Mechanistic models and control strategies for bacterial attachment to abiotic surfaces have been established based on the current understanding of the attachment process and the interactions involved. Due to a lack of process control and standardization in the methodologies used to study the mechanisms of bacterial attachment, however, various challenges are apparent in the development of models and control strategies. In this review, the physicochemical mechanisms, interactions and factors affecting the process of bacterial attachment to abiotic surfaces are described. Mechanistic models established based on these parameters are discussed in terms of their limitations. Currently employed methods to study these parameters and bacterial attachment are critically compared. The roles of these parameters in the development of control strategies for bacterial attachment are reviewed, and the challenges that arise in developing mechanistic models and control strategies are assessed.

  3. In silico investigation of the short QT syndrome, using human ventricle models incorporating electromechanical coupling

    Directory of Open Access Journals (Sweden)

    Ismail eAdeniran

    2013-07-01

    Full Text Available Introduction Genetic forms of the Short QT Syndrome (SQTS arise due to cardiac ion channel mutations leading to accelerated ventricular repolarisation, arrhythmias and sudden cardiac death. Results from experimental and simulation studies suggest that changes to refractoriness and tissue vulnerability produce a substrate favourable to re-entry. Potential electromechanical consequences of the SQTS are less well understood. The aim of this study was to utilize electromechanically coupled human ventricle models to explore electromechanical consequences of the SQTS. Methods and results: The Rice et al. mechanical model was coupled to the ten Tusscher et al. ventricular cell model. Previously validated K+ channel formulations for SQT variants 1 and 3 were incorporated. Functional effects of the SQTS mutations on transients, sarcomere length shortening and contractile force at the single cell level were evaluated with and without the consideration of stretch activated channel current (Isac. Without Isac, the SQTS mutations produced dramatic reductions in the amplitude of transients, sarcomere length shortening and contractile force. When Isac was incorporated, there was a considerable attenuation of the effects of SQTS-associated action potential shortening on Ca2+ transients, sarcomere shortening and contractile force. Single cell models were then incorporated into 3D human ventricular tissue models. The timing of maximum deformation was delayed in the SQTS setting compared to control. Conclusion: The incorporation of Isac appears to be an important consideration in modelling functional effects of SQT 1 and 3 mutations on cardiac electro-mechanical coupling. Whilst there is little evidence of profoundly impaired cardiac contractile function in SQTS patients, our 3D simulations correlate qualitatively with reported evidence for dissociation between ventricular repolarization and the end of mechanical systole.

  4. Investigations of incorporating source directivity into room acoustics computer models to improve auralizations

    Science.gov (United States)

    Vigeant, Michelle C.

    Room acoustics computer modeling and auralizations are useful tools when designing or modifying acoustically sensitive spaces. In this dissertation, the input parameter of source directivity has been studied in great detail to determine first its effect in room acoustics computer models and secondly how to better incorporate the directional source characteristics into these models to improve auralizations. To increase the accuracy of room acoustics computer models, the source directivity of real sources, such as musical instruments, must be included in the models. The traditional method for incorporating source directivity into room acoustics computer models involves inputting the measured static directivity data taken every 10° in a sphere-shaped pattern around the source. This data can be entered into the room acoustics software to create a directivity balloon, which is used in the ray tracing algorithm to simulate the room impulse response. The first study in this dissertation shows that using directional sources over an omni-directional source in room acoustics computer models produces significant differences both in terms of calculated room acoustics parameters and auralizations. The room acoustics computer model was also validated in terms of accurately incorporating the input source directivity. A recently proposed technique for creating auralizations using a multi-channel source representation has been investigated with numerous subjective studies, applied to both solo instruments and an orchestra. The method of multi-channel auralizations involves obtaining multi-channel anechoic recordings of short melodies from various instruments and creating individual channel auralizations. These auralizations are then combined to create a total multi-channel auralization. Through many subjective studies, this process was shown to be effective in terms of improving the realism and source width of the auralizations in a number of cases, and also modeling different

  5. Making a difference: incorporating theories of autonomy into models of informed consent.

    Science.gov (United States)

    Delany, C

    2008-09-01

    Obtaining patients' informed consent is an ethical and legal obligation in healthcare practice. Whilst the law provides prescriptive rules and guidelines, ethical theories of autonomy provide moral foundations. Models of practice of consent, have been developed in the bioethical literature to assist in understanding and integrating the ethical theory of autonomy and legal obligations into the clinical process of obtaining a patient's informed consent to treatment. To review four models of consent and analyse the way each model incorporates the ethical meaning of autonomy and how, as a consequence, they might change the actual communicative process of obtaining informed consent within clinical contexts. An iceberg framework of consent is used to conceptualise how ethical theories of autonomy are positioned and underpin the above surface, and visible clinical communication, including associated legal guidelines and ethical rules. Each model of consent is critically reviewed from the perspective of how it might shape the process of informed consent. All four models would alter the process of obtaining consent. Two models provide structure and guidelines for the content and timing of obtaining patients' consent. The two other models rely on an attitudinal shift in clinicians. They provide ideas for consent by focusing on underlying values, attitudes and meaning associated with the ethical meaning of autonomy. The paper concludes that models of practice that explicitly incorporate the underlying ethical meaning of autonomy as their basis, provide less prescriptive, but more theoretically rich guidance for healthcare communicative practices.

  6. PWR plant operator training used full scope simulator incorporated MAAP model

    International Nuclear Information System (INIS)

    Matsumoto, Y.; Tabuchi, T.; Yamashita, T.; Komatsu, Y.; Tsubouchi, K.; Banka, T.; Mochizuki, T.; Nishimura, K.; Iizuka, H.

    2015-01-01

    NTC makes an effort with the understanding of plant behavior of core damage accident as part of our advanced training. For the Fukushima Daiichi Nuclear Power Station accident, we introduced the MAAP model into PWR operator training full scope simulator and also made the Severe Accident Visual Display unit. From 2014, we will introduce new training program for a core damage accident with PWR operator training full scope simulator incorporated the MAAP model and the Severe Accident Visual Display unit. (author)

  7. Incorporating modelled subglacial hydrology into inversions for basal drag

    Directory of Open Access Journals (Sweden)

    C. P. Koziol

    2017-12-01

    Full Text Available A key challenge in modelling coupled ice-flow–subglacial hydrology is initializing the state and parameters of the system. We address this problem by presenting a workflow for initializing these values at the start of a summer melt season. The workflow depends on running a subglacial hydrology model for the winter season, when the system is not forced by meltwater inputs, and ice velocities can be assumed constant. Key parameters of the winter run of the subglacial hydrology model are determined from an initial inversion for basal drag using a linear sliding law. The state of the subglacial hydrology model at the end of winter is incorporated into an inversion of basal drag using a non-linear sliding law which is a function of water pressure. We demonstrate this procedure in the Russell Glacier area and compare the output of the linear sliding law with two non-linear sliding laws. Additionally, we compare the modelled winter hydrological state to radar observations and find that it is in line with summer rather than winter observations.

  8. Incorporation of stochastic engineering models as prior information in Bayesian medical device trials.

    Science.gov (United States)

    Haddad, Tarek; Himes, Adam; Thompson, Laura; Irony, Telba; Nair, Rajesh

    2017-01-01

    Evaluation of medical devices via clinical trial is often a necessary step in the process of bringing a new product to market. In recent years, device manufacturers are increasingly using stochastic engineering models during the product development process. These models have the capability to simulate virtual patient outcomes. This article presents a novel method based on the power prior for augmenting a clinical trial using virtual patient data. To properly inform clinical evaluation, the virtual patient model must simulate the clinical outcome of interest, incorporating patient variability, as well as the uncertainty in the engineering model and in its input parameters. The number of virtual patients is controlled by a discount function which uses the similarity between modeled and observed data. This method is illustrated by a case study of cardiac lead fracture. Different discount functions are used to cover a wide range of scenarios in which the type I error rates and power vary for the same number of enrolled patients. Incorporation of engineering models as prior knowledge in a Bayesian clinical trial design can provide benefits of decreased sample size and trial length while still controlling type I error rate and power.

  9. Mechanistic modelling of Middle Eocene atmospheric carbon dioxide using fossil plant material

    Science.gov (United States)

    Grein, Michaela; Roth-Nebelsick, Anita; Wilde, Volker; Konrad, Wilfried; Utescher, Torsten

    2010-05-01

    Various proxies (such as pedogenic carbonates, boron isotopes or phytoplankton) and geochemical models were applied in order to reconstruct palaeoatmospheric carbon dioxide, partially providing conflicting results. Another promising proxy is the frequency of stomata (pores on the leaf surface used for gaseous exchange). In this project, fossil plant material from the Messel Pit (Hesse, Germany) is used to reconstruct atmospheric carbon dioxide concentration in the Middle Eocene by analyzing stomatal density. We applied the novel mechanistic-theoretical approach of Konrad et al. (2008) which provides a quantitative derivation of the stomatal density response (number of stomata per leaf area) to varying atmospheric carbon dioxide concentration. The model couples 1) C3-photosynthesis, 2) the process of diffusion and 3) an optimisation principle providing maximum photosynthesis (via carbon dioxide uptake) and minimum water loss (via stomatal transpiration). These three sub-models also include data of the palaeoenvironment (temperature, water availability, wind velocity, atmospheric humidity, precipitation) and anatomy of leaf and stoma (depth, length and width of stomatal porus, thickness of assimilation tissue, leaf length). In order to calculate curves of stomatal density as a function of atmospheric carbon dioxide concentration, various biochemical parameters have to be borrowed from extant representatives. The necessary palaeoclimate data are reconstructed from the whole Messel flora using Leaf Margin Analysis (LMA) and the Coexistence Approach (CA). In order to obtain a significant result, we selected three species from which a large number of well-preserved leaves is available (at least 20 leaves per species). Palaeoclimate calculations for the Middle Eocene Messel Pit indicate a warm and humid climate with mean annual temperature of approximately 22°C, up to 2540 mm mean annual precipitation and the absence of extended periods of drought. Mean relative air

  10. A mathematical model for incorporating biofeedback into human postural control

    Directory of Open Access Journals (Sweden)

    Ersal Tulga

    2013-02-01

    Full Text Available Abstract Background Biofeedback of body motion can serve as a balance aid and rehabilitation tool. To date, mathematical models considering the integration of biofeedback into postural control have represented this integration as a sensory addition and limited their application to a single degree-of-freedom representation of the body. This study has two objectives: 1 to develop a scalable method for incorporating biofeedback into postural control that is independent of the model’s degrees of freedom, how it handles sensory integration, and the modeling of its postural controller; and 2 to validate this new model using multidirectional perturbation experimental results. Methods Biofeedback was modeled as an additional torque to the postural controller torque. For validation, this biofeedback modeling approach was applied to a vibrotactile biofeedback device and incorporated into a two-link multibody model with full-state-feedback control that represents the dynamics of bipedal stance. Average response trajectories of body sway and center of pressure (COP to multidirectional surface perturbations of subjects with vestibular deficits were used for model parameterization and validation in multiple perturbation directions and for multiple display resolutions. The quality of fit was quantified using average error and cross-correlation values. Results The mean of the average errors across all tactor configurations and perturbations was 0.24° for body sway and 0.39 cm for COP. The mean of the cross-correlation value was 0.97 for both body sway and COP. Conclusions The biofeedback model developed in this study is capable of capturing experimental response trajectory shapes with low average errors and high cross-correlation values in both the anterior-posterior and medial-lateral directions for all perturbation directions and spatial resolution display configurations considered. The results validate that biofeedback can be modeled as an additional

  11. A mathematical model for incorporating biofeedback into human postural control

    Science.gov (United States)

    2013-01-01

    Background Biofeedback of body motion can serve as a balance aid and rehabilitation tool. To date, mathematical models considering the integration of biofeedback into postural control have represented this integration as a sensory addition and limited their application to a single degree-of-freedom representation of the body. This study has two objectives: 1) to develop a scalable method for incorporating biofeedback into postural control that is independent of the model’s degrees of freedom, how it handles sensory integration, and the modeling of its postural controller; and 2) to validate this new model using multidirectional perturbation experimental results. Methods Biofeedback was modeled as an additional torque to the postural controller torque. For validation, this biofeedback modeling approach was applied to a vibrotactile biofeedback device and incorporated into a two-link multibody model with full-state-feedback control that represents the dynamics of bipedal stance. Average response trajectories of body sway and center of pressure (COP) to multidirectional surface perturbations of subjects with vestibular deficits were used for model parameterization and validation in multiple perturbation directions and for multiple display resolutions. The quality of fit was quantified using average error and cross-correlation values. Results The mean of the average errors across all tactor configurations and perturbations was 0.24° for body sway and 0.39 cm for COP. The mean of the cross-correlation value was 0.97 for both body sway and COP. Conclusions The biofeedback model developed in this study is capable of capturing experimental response trajectory shapes with low average errors and high cross-correlation values in both the anterior-posterior and medial-lateral directions for all perturbation directions and spatial resolution display configurations considered. The results validate that biofeedback can be modeled as an additional torque to the postural

  12. Mechanistic Studies on the Triggered Release of Liposomal Contents by Matrix Metalloproteinase-9

    Science.gov (United States)

    Elegbede, Adekunle I.; Banerjee, Jayati; Hanson, Andrea J.; Tobwala, Shakila; Ganguli, Bratati; Wang, Rongying; Lu, Xiaoning; Srivastava, D. K.; Mallik, Sanku

    2009-01-01

    Matrix metalloproteinases (MMPs) are a class of extracellular matrix degrading enzymes over-expressed in many cancers and contribute to the metastatic ability of the cancer cells. We have recently demonstrated that liposomal contents can be released when triggered by the enzyme MMP-9. Herein, we report our results on the mechanistic studies of the MMP-9 triggered release of the liposomal contents. We synthesized peptides containing the cleavage site for MMP-9 and conjugated them with fatty acids to prepare the corresponding lipopeptides. By employing Circular Dichroism spectroscopy, we demonstrate that the lipopeptides, when incorporated in liposomes, are de-mixed in the lipid bilayers and generate triple helical structures. MMP-9 cleaves the triple helical peptides, leading to the release of the liposomal contents. Other MMPs, which cannot hydrolyze triple helical peptides, failed to release the contents from the liposomes. We also observed that the rate and the extent of release of the liposomal contents depend on the mismatch between acyl chains of the synthesized lipopeptide and phospholipid components of the liposomes. Circular Dichroism spectroscopic studies imply that the observed differences in the release reflect the ability of the liposomal membrane to anneal the defects following the enzymatic cleavage of the liposome-incorporated lipopeptides. PMID:18642903

  13. Making Invasion models useful for decision makers; incorporating uncertainty, knowledge gaps, and decision-making preferences

    Science.gov (United States)

    Denys Yemshanov; Frank H Koch; Mark Ducey

    2015-01-01

    Uncertainty is inherent in model-based forecasts of ecological invasions. In this chapter, we explore how the perceptions of that uncertainty can be incorporated into the pest risk assessment process. Uncertainty changes a decision maker’s perceptions of risk; therefore, the direct incorporation of uncertainty may provide a more appropriate depiction of risk. Our...

  14. Mechanistic formulation of a lineal-quadratic-linear (LQL) model: Split-dose experiments and exponentially decaying sources

    International Nuclear Information System (INIS)

    Guerrero, Mariana; Carlone, Marco

    2010-01-01

    Purpose: In recent years, several models were proposed that modify the standard linear-quadratic (LQ) model to make the predicted survival curve linear at high doses. Most of these models are purely phenomenological and can only be applied in the particular case of acute doses per fraction. The authors consider a mechanistic formulation of a linear-quadratic-linear (LQL) model in the case of split-dose experiments and exponentially decaying sources. This model provides a comprehensive description of radiation response for arbitrary dose rate and fractionation with only one additional parameter. Methods: The authors use a compartmental formulation of the LQL model from the literature. They analytically solve the model's differential equations for the case of a split-dose experiment and for an exponentially decaying source. They compare the solutions of the survival fraction with the standard LQ equations and with the lethal-potentially lethal (LPL) model. Results: In the case of the split-dose experiment, the LQL model predicts a recovery ratio as a function of dose per fraction that deviates from the square law of the standard LQ. The survival fraction as a function of time between fractions follows a similar exponential law as the LQ but adds a multiplicative factor to the LQ parameter β. The LQL solution for the split-dose experiment is very close to the LPL prediction. For the decaying source, the differences between the LQL and the LQ solutions are negligible when the half-life of the source is much larger than the characteristic repair time, which is the clinically relevant case. Conclusions: The compartmental formulation of the LQL model can be used for arbitrary dose rates and provides a comprehensive description of dose response. When the survival fraction for acute doses is linear for high dose, a deviation of the square law formula of the recovery ratio for split doses is also predicted.

  15. Assessing the ability of mechanistic volatilization models to simulate soil surface conditions: a study with the Volt'Air model.

    Science.gov (United States)

    Garcia, L; Bedos, C; Génermont, S; Braud, I; Cellier, P

    2011-09-01

    Ammonia and pesticide volatilization in the field is a surface phenomenon involving physical and chemical processes that depend on the soil surface temperature and water content. The water transfer, heat transfer and energy budget sub models of volatilization models are adapted from the most commonly accepted formalisms and parameterizations. They are less detailed than the dedicated models describing water and heat transfers and surface status. The aim of this work was to assess the ability of one of the available mechanistic volatilization models, Volt'Air, to accurately describe the pedo-climatic conditions of a soil surface at the required time and space resolution. The assessment involves: (i) a sensitivity analysis, (ii) an evaluation of Volt'Air outputs in the light of outputs from a reference Soil-Vegetation-Atmosphere Transfer model (SiSPAT) and three experimental datasets, and (iii) the study of three tests based on modifications of SiSPAT to establish the potential impact of the simplifying assumptions used in Volt'Air. The analysis confirmed that a 5 mm surface layer was well suited, and that Volt'Air surface temperature correlated well with the experimental measurements as well as with SiSPAT outputs. In terms of liquid water transfers, Volt'Air was overall consistent with SiSPAT, with discrepancies only during major rainfall events and dry weather conditions. The tests enabled us to identify the main source of the discrepancies between Volt'Air and SiSPAT: the lack of gaseous water transfer description in Volt'Air. They also helped to explain why neither Volt'Air nor SiSPAT was able to represent lower values of surface water content: current classical water retention and hydraulic conductivity models are not yet adapted to cases of very dry conditions. Given the outcomes of this study, we discuss to what extent the volatilization models can be improved and the questions they pose for current research in water transfer modeling and parameterization

  16. Mechanistic modeling of sulfur-deprived photosynthesis and hydrogen production in suspensions of Chlamydomonas reinhardtii.

    Science.gov (United States)

    Williams, C R; Bees, M A

    2014-02-01

    The ability of unicellular green algal species such as Chlamydomonas reinhardtii to produce hydrogen gas via iron-hydrogenase is well known. However, the oxygen-sensitive hydrogenase is closely linked to the photosynthetic chain in such a way that hydrogen and oxygen production need to be separated temporally for sustained photo-production. Under illumination, sulfur-deprivation has been shown to accommodate the production of hydrogen gas by partially-deactivating O2 evolution activity, leading to anaerobiosis in a sealed culture. As these facets are coupled, and the system complex, mathematical approaches potentially are of significant value since they may reveal improved or even optimal schemes for maximizing hydrogen production. Here, a mechanistic model of the system is constructed from consideration of the essential pathways and processes. The role of sulfur in photosynthesis (via PSII) and the storage and catabolism of endogenous substrate, and thus growth and decay of culture density, are explicitly modeled in order to describe and explore the complex interactions that lead to H2 production during sulfur-deprivation. As far as possible, functional forms and parameter values are determined or estimated from experimental data. The model is compared with published experimental studies and, encouragingly, qualitative agreement for trends in hydrogen yield and initiation time are found. It is then employed to probe optimal external sulfur and illumination conditions for hydrogen production, which are found to differ depending on whether a maximum yield of gas or initial production rate is required. The model constitutes a powerful theoretical tool for investigating novel sulfur cycling regimes that may ultimately be used to improve the commercial viability of hydrogen gas production from microorganisms. © 2013 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.

  17. Application of a mechanistic model as a tool for on-line monitoring of pilot scale filamentous fungal fermentation processes-The importance of evaporation effects.

    Science.gov (United States)

    Mears, Lisa; Stocks, Stuart M; Albaek, Mads O; Sin, Gürkan; Gernaey, Krist V

    2017-03-01

    A mechanistic model-based soft sensor is developed and validated for 550L filamentous fungus fermentations operated at Novozymes A/S. The soft sensor is comprised of a parameter estimation block based on a stoichiometric balance, coupled to a dynamic process model. The on-line parameter estimation block models the changing rates of formation of product, biomass, and water, and the rate of consumption of feed using standard, available on-line measurements. This parameter estimation block, is coupled to a mechanistic process model, which solves the current states of biomass, product, substrate, dissolved oxygen and mass, as well as other process parameters including k L a, viscosity and partial pressure of CO 2 . State estimation at this scale requires a robust mass model including evaporation, which is a factor not often considered at smaller scales of operation. The model is developed using a historical data set of 11 batches from the fermentation pilot plant (550L) at Novozymes A/S. The model is then implemented on-line in 550L fermentation processes operated at Novozymes A/S in order to validate the state estimator model on 14 new batches utilizing a new strain. The product concentration in the validation batches was predicted with an average root mean sum of squared error (RMSSE) of 16.6%. In addition, calculation of the Janus coefficient for the validation batches shows a suitably calibrated model. The robustness of the model prediction is assessed with respect to the accuracy of the input data. Parameter estimation uncertainty is also carried out. The application of this on-line state estimator allows for on-line monitoring of pilot scale batches, including real-time estimates of multiple parameters which are not able to be monitored on-line. With successful application of a soft sensor at this scale, this allows for improved process monitoring, as well as opening up further possibilities for on-line control algorithms, utilizing these on-line model outputs

  18. A metabonomic approach for mechanistic exploration of pre-clinical toxicology.

    Science.gov (United States)

    Coen, Muireann

    2010-12-30

    Metabonomics involves the application of advanced analytical tools to profile the diverse metabolic complement of a given biofluid or tissue. Subsequent statistical modelling of the complex multivariate spectral profiles enables discrimination between phenotypes of interest and identifies panels of discriminatory metabolites that represent candidate biomarkers. This review article presents an overview of recent developments in the field of metabonomics with a focus on application to pre-clinical toxicology studies. Recent research investigations carried out as part of the international COMET 2 consortium project on the hepatotoxic action of the aminosugar, galactosamine (galN) are presented. The application of advanced, high-field NMR spectroscopy is demonstrated, together with complementary application of a targeted mass spectrometry platform coupled with ultra-performance liquid chromatography. Much novel mechanistic information has been gleaned on both the mechanism of galN hepatotoxicity in multiple biofluids and tissues, and on the protection afforded by co-administration of glycine and uridine. The simultaneous identification of both the metabolic fate of galN and its associated endogenous consequences in spectral profiles is demonstrated. Furthermore, metabonomic assessment of inter-animal variability in response to galN presents enhanced mechanistic insight on variable response phentoypes and is relevant to understanding wider aspects of individual variability in drug response. This exemplar highlights the analytical and statistical tools commonly applied in metabonomic studies and notably, the approach is applicable to the study of any toxin/drug or intervention of interest. The metabonomic approach holds considerable promise and potential to significantly advance our understanding of the mechanistic bases for adverse drug reactions. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

  19. [Mechanistic modelling allows to assess pathways of DNA lesion interactions underlying chromosome aberration formation].

    Science.gov (United States)

    Eĭdel'man, Iu A; Slanina, S V; Sal'nikov, I V; Andreev, S G

    2012-12-01

    The knowledge of radiation-induced chromosomal aberration (CA) mechanisms is required in many fields of radiation genetics, radiation biology, biodosimetry, etc. However, these mechanisms are yet to be quantitatively characterised. One of the reasons is that the relationships between primary lesions of DNA/chromatin/chromosomes and dose-response curves for CA are unknown because the pathways of lesion interactions in an interphase nucleus are currently inaccessible for direct experimental observation. This article aims for the comparative analysis of two principally different scenarios of formation of simple and complex interchromosomal exchange aberrations: by lesion interactions at chromosome territories' surface vs. in the whole space of the nucleus. The analysis was based on quantitative mechanistic modelling of different levels of structures and processes involved in CA formation: chromosome structure in an interphase nucleus, induction, repair and interactions of DNA lesions. It was shown that the restricted diffusion of chromosomal loci, predicted by computational modelling of chromosome organization, results in lesion interactions in the whole space of the nucleus being impossible. At the same time, predicted features of subchromosomal dynamics agrees well with in vivo observations and does not contradict the mechanism of CA formation at the surface of chromosome territories. On the other hand, the "surface mechanism" of CA formation, despite having certain qualities, proved to be insufficient to explain high frequency of complex exchange aberrations observed by mFISH technique. The alternative mechanism, CA formation on nuclear centres is expected to be sufficient to explain frequent complex exchanges.

  20. Managing mechanistic and organic structure in health care organizations.

    Science.gov (United States)

    Olden, Peter C

    2012-01-01

    Managers at all levels in a health care organization must organize work to achieve the organization's mission and goals. This requires managers to decide the organization structure, which involves dividing the work among jobs and departments and then coordinating them all toward the common purpose. Organization structure, which is reflected in an organization chart, may range on a continuum from very mechanistic to very organic. Managers must decide how mechanistic versus how organic to make the entire organization and each of its departments. To do this, managers should carefully consider 5 factors for the organization and for each individual department: external environment, goals, work production, size, and culture. Some factors may push toward more mechanistic structure, whereas others may push in the opposite direction toward more organic structure. Practical advice can help managers at all levels design appropriate structure for their departments and organization.

  1. Cognitive science as an interface between rational and mechanistic explanation.

    Science.gov (United States)

    Chater, Nick

    2014-04-01

    Cognitive science views thought as computation; and computation, by its very nature, can be understood in both rational and mechanistic terms. In rational terms, a computation solves some information processing problem (e.g., mapping sensory information into a description of the external world; parsing a sentence; selecting among a set of possible actions). In mechanistic terms, a computation corresponds to causal chain of events in a physical device (in engineering context, a silicon chip; in biological context, the nervous system). The discipline is thus at the interface between two very different styles of explanation--as the papers in the current special issue well illustrate, it explores the interplay of rational and mechanistic forces. Copyright © 2014 Cognitive Science Society, Inc.

  2. Tantalum strength model incorporating temperature, strain rate and pressure

    Science.gov (United States)

    Lim, Hojun; Battaile, Corbett; Brown, Justin; Lane, Matt

    Tantalum is a body-centered-cubic (BCC) refractory metal that is widely used in many applications in high temperature, strain rate and pressure environments. In this work, we propose a physically-based strength model for tantalum that incorporates effects of temperature, strain rate and pressure. A constitutive model for single crystal tantalum is developed based on dislocation kink-pair theory, and calibrated to measurements on single crystal specimens. The model is then used to predict deformations of single- and polycrystalline tantalum. In addition, the proposed strength model is implemented into Sandia's ALEGRA solid dynamics code to predict plastic deformations of tantalum in engineering-scale applications at extreme conditions, e.g. Taylor impact tests and Z machine's high pressure ramp compression tests, and the results are compared with available experimental data. Sandia National Laboratories is a multi program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

  3. ReactionPredictor: prediction of complex chemical reactions at the mechanistic level using machine learning.

    Science.gov (United States)

    Kayala, Matthew A; Baldi, Pierre

    2012-10-22

    Proposing reasonable mechanisms and predicting the course of chemical reactions is important to the practice of organic chemistry. Approaches to reaction prediction have historically used obfuscating representations and manually encoded patterns or rules. Here we present ReactionPredictor, a machine learning approach to reaction prediction that models elementary, mechanistic reactions as interactions between approximate molecular orbitals (MOs). A training data set of productive reactions known to occur at reasonable rates and yields and verified by inclusion in the literature or textbooks is derived from an existing rule-based system and expanded upon with manual curation from graduate level textbooks. Using this training data set of complex polar, hypervalent, radical, and pericyclic reactions, a two-stage machine learning prediction framework is trained and validated. In the first stage, filtering models trained at the level of individual MOs are used to reduce the space of possible reactions to consider. In the second stage, ranking models over the filtered space of possible reactions are used to order the reactions such that the productive reactions are the top ranked. The resulting model, ReactionPredictor, perfectly ranks polar reactions 78.1% of the time and recovers all productive reactions 95.7% of the time when allowing for small numbers of errors. Pericyclic and radical reactions are perfectly ranked 85.8% and 77.0% of the time, respectively, rising to >93% recovery for both reaction types with a small number of allowed errors. Decisions about which of the polar, pericyclic, or radical reaction type ranking models to use can be made with >99% accuracy. Finally, for multistep reaction pathways, we implement the first mechanistic pathway predictor using constrained tree-search to discover a set of reasonable mechanistic steps from given reactants to given products. Webserver implementations of both the single step and pathway versions of Reaction

  4. Mechanistic kinetic modeling generates system-independent P-glycoprotein mediated transport elementary rate constants for inhibition and, in combination with 3D SIM microscopy, elucidates the importance of microvilli morphology on P-glycoprotein mediated efflux activity.

    Science.gov (United States)

    Ellens, Harma; Meng, Zhou; Le Marchand, Sylvain J; Bentz, Joe

    2018-06-01

    In vitro transporter kinetics are typically analyzed by steady-state Michaelis-Menten approximations. However, no clear evidence exists that these approximations, applied to multiple transporters in biological membranes, yield system-independent mechanistic parameters needed for reliable in vivo hypothesis generation and testing. Areas covered: The classical mass action model has been developed for P-glycoprotein (P-gp) mediated transport across confluent polarized cell monolayers. Numerical integration of the mass action equations for transport using a stable global optimization program yields fitted elementary rate constants that are system-independent. The efflux active P-gp was defined by the rate at which P-gp delivers drugs to the apical chamber, since as much as 90% of drugs effluxed by P-gp partition back into nearby microvilli prior to reaching the apical chamber. The efflux active P-gp concentration was 10-fold smaller than the total expressed P-gp for Caco-2 cells, due to their microvilli membrane morphology. The mechanistic insights from this analysis are readily extrapolated to P-gp mediated transport in vivo. Expert opinion: In vitro system-independent elementary rate constants for transporters are essential for the generation and validation of robust mechanistic PBPK models. Our modeling approach and programs have broad application potential. They can be used for any drug transporter with minor adaptations.

  5. A Mechanistic Model of Intermittent Gastric Emptying and Glucose-Insulin Dynamics following a Meal Containing Milk Components.

    Directory of Open Access Journals (Sweden)

    Priska Stahel

    Full Text Available To support decision-making around diet selection choices to manage glycemia following a meal, a novel mechanistic model of intermittent gastric emptying and plasma glucose-insulin dynamics was developed. Model development was guided by postprandial timecourses of plasma glucose, insulin and the gastric emptying marker acetaminophen in infant calves fed meals of 2 or 4 L milk replacer. Assigning a fast, slow or zero first-order gastric emptying rate to each interval between plasma samples fit acetaminophen curves with prediction errors equal to 9% of the mean observed acetaminophen concentration. Those gastric emptying parameters were applied to glucose appearance in conjunction with minimal models of glucose disposal and insulin dynamics to describe postprandial glycemia and insulinemia. The final model contains 20 parameters, 8 of which can be obtained by direct measurement and 12 by fitting to observations. The minimal model of intestinal glucose delivery contains 2 gastric emptying parameters and a third parameter describing the time lag between emptying and appearance of glucose in plasma. Sensitivity analysis of the aggregate model revealed that gastric emptying rate influences area under the plasma insulin curve but has little effect on area under the plasma glucose curve. This result indicates that pancreatic responsiveness is influenced by gastric emptying rate as a consequence of the quasi-exponential relationship between plasma glucose concentration and pancreatic insulin release. The fitted aggregate model was able to reproduce the multiple postprandial rises and falls in plasma glucose concentration observed in calves consuming a normal-sized meal containing milk components.

  6. A mechanistic diagnosis of the simulation of soil CO2 efflux of the ACME Land Model

    Science.gov (United States)

    Liang, J.; Ricciuto, D. M.; Wang, G.; Gu, L.; Hanson, P. J.; Mayes, M. A.

    2017-12-01

    Accurate simulation of the CO2 efflux from soils (i.e., soil respiration) to the atmosphere is critical to project global biogeochemical cycles and the magnitude of climate change in Earth system models (ESMs). Currently, the simulated soil respiration by ESMs still have a large uncertainty. In this study, a mechanistic diagnosis of soil respiration in the Accelerated Climate Model for Energy (ACME) Land Model (ALM) was conducted using long-term observations at the Missouri Ozark AmeriFlux (MOFLUX) forest site in the central U.S. The results showed that the ALM default run significantly underestimated annual soil respiration and gross primary production (GPP), while incorrectly estimating soil water potential. Improved simulations of soil water potential with site-specific data significantly improved the modeled annual soil respiration, primarily because annual GPP was simultaneously improved. Therefore, accurate simulations of soil water potential must be carefully calibrated in ESMs. Despite improved annual soil respiration, the ALM continued to underestimate soil respiration during peak growing seasons, and to overestimate soil respiration during non-peak growing seasons. Simulations involving increased GPP during peak growing seasons increased soil respiration, while neither improved plant phenology nor increased temperature sensitivity affected the simulation of soil respiration during non-peak growing seasons. One potential reason for the overestimation of the soil respiration during non-peak growing seasons may be that the current model structure is substrate-limited, while microbial dormancy under stress may cause the system to become decomposer-limited. Further studies with more microbial data are required to provide adequate representation of soil respiration and to understand the underlying reasons for inaccurate model simulations.

  7. Mechanistic electronic model to simulate and predict the effect of heat stress on the functional genomics of HO-1 system: Vasodilation.

    Science.gov (United States)

    Aggarwal, Yogender; Karan, Bhuwan Mohan; Das, Barda Nand; Sinha, Rakesh Kumar

    2010-05-01

    The present work is concerned to model the molecular signalling pathway for vasodilation and to predict the resting young human forearm blood flow under heat stress. The mechanistic electronic modelling technique has been designed and implemented using MULTISIM 8.0 and an assumption of 1V/ degrees C for prediction of forearm blood flow and the digital logic has been used to design the molecular signalling pathway for vasodilation. The minimum forearm blood flow has been observed at 35 degrees C (0 ml 100 ml(-1)min(-1)) and the maximum at 42 degrees C (18.7 ml 100 ml(-1)min(-1)) environmental temperature with respect to the base value of 2 ml 100 ml(-1)min(-1). This model may also enable to identify many therapeutic targets that can be used in the treatment of inflammations and disorders due to heat-related illnesses. 2010 Elsevier Ltd. All rights reserved.

  8. Insight into the hydraulics and resilience of Ponderosa pine seedlings using a mechanistic ecohydrologic model

    Science.gov (United States)

    Maneta, M. P.; Simeone, C.; Dobrowski, S.; Holden, Z.; Sapes, G.; Sala, A.; Begueria, S.

    2017-12-01

    In semiarid regions, drought-induced seedling mortality is considered to be caused by failure in the tree hydraulic column. Understanding the mechanisms that cause hydraulic failure and death in seedlings is important, among other things, to diagnose where some tree species may fail to regenerate, triggering demographic imbalances in the forest that could result in climate-driven shifts of tree species. Ponderosa pine is a common lower tree line species in the western US. Seedlings of ponderosa pine are often subject to low soil water potentials, which require lower water potentials in the xylem and leaves to maintain the negative pressure gradient that drives water upward. The resilience of the hydraulic column to hydraulic tension is species dependent, but from greenhouse experiments, we have identified general tension thresholds beyond which loss of xylem conductivity becomes critical, and mortality in Ponderosa pine seedlings start to occur. We describe this hydraulic behavior of plants using a mechanistic soil-vegetation-atmosphere transfer model. Before we use this models to understand water-stress induced seedling mortality at the landscape scale, we perform a modeling analysis of the dynamics of soil moisture, transpiration, leaf water potential and loss of plant water conductivity using detailed data from our green house experiments. The analysis is done using a spatially distributed model that simulates water fluxes, energy exchanges and water potentials in the soil-vegetation-atmosphere continuum. Plant hydraulic and physiological parameters of this model were calibrated using Monte Carlo methods against information on soil moisture, soil hydraulic potential, transpiration, leaf water potential and percent loss of conductivity in the xylem. This analysis permits us to construct a full portrait of the parameter space for Ponderosa pine seedling and generate posterior predictive distributions of tree response to understand the sensitivity of transpiration

  9. Modeling fraud detection and the incorporation of forensic specialists in the audit process

    DEFF Research Database (Denmark)

    Sakalauskaite, Dominyka

    Financial statement audits are still comparatively poor in fraud detection. Forensic specialists can play a significant role in increasing audit quality. In this paper, based on prior academic research, I develop a model of fraud detection and the incorporation of forensic specialists in the audit...... process. The intention of the model is to identify the reasons why the audit is weak in fraud detection and to provide the analytical framework to assess whether the incorporation of forensic specialists can help to improve it. The results show that such specialists can potentially improve the fraud...... detection in the audit, but might also cause some negative implications. Overall, even though fraud detection is one of the main topics in research there are very few studies done on the subject of how auditors co-operate with forensic specialists. Thus, the paper concludes with suggestions for further...

  10. A mechanistic, globally-applicable model of plant nitrogen uptake, retranslocation and fixation

    Science.gov (United States)

    Fisher, J. B.; Tan, S.; Malhi, Y.; Fisher, R. A.; Sitch, S.; Huntingford, C.

    2008-12-01

    Nitrogen is one of the nutrients that can most limit plant growth, and nitrogen availability may be a controlling factor on biosphere responses to climate change. We developed a plant nitrogen assimilation model based on a) advective transport through the transpiration stream, b) retranslocation whereby carbon is expended to resorb nitrogen from leaves, c) active uptake whereby carbon is expended to acquire soil nitrogen, and d) biological nitrogen fixation whereby carbon is expended for symbiotic nitrogen fixers. The model relies on 9 inputs: 1) net primary productivity (NPP), 2) plant C:N ratio, 3) available soil nitrogen, 4) root biomass, 5) transpiration rate, 6) saturated soil depth,7) leaf nitrogen before senescence, 8) soil temperature, and 9) ability to fix nitrogen. A carbon cost of retranslocation is estimated based on leaf nitrogen and compared to an active uptake carbon cost based on root biomass and available soil nitrogen; for nitrogen fixers both costs are compared to a carbon cost of fixation dependent on soil temperature. The NPP is then allocated to optimize growth while maintaining the C:N ratio. The model outputs are total plant nitrogen uptake, remaining NPP available for growth, carbon respired to the soil and updated available soil nitrogen content. We test and validate the model (called FUN: Fixation and Uptake of Nitrogen) against data from the UK, Germany and Peru, and run the model under simplified scenarios of primary succession and climate change. FUN is suitable for incorporation into a land surface scheme of a General Circulation Model and will be coupled with a soil model and dynamic global vegetation model as part of a land surface model (JULES).

  11. In vitro solubility, dissolution and permeability studies combined with semi-mechanistic modeling to investigate the intestinal absorption of desvenlafaxine from an immediate- and extended release formulation.

    Science.gov (United States)

    Franek, F; Jarlfors, A; Larsen, F; Holm, P; Steffansen, B

    2015-09-18

    Desvenlafaxine is a biopharmaceutics classification system (BCS) class 1 (high solubility, high permeability) and biopharmaceutical drug disposition classification system (BDDCS) class 3, (high solubility, poor metabolism; implying low permeability) compound. Thus the rate-limiting step for desvenlafaxine absorption (i.e. intestinal dissolution or permeation) is not fully clarified. The aim of this study was to investigate whether dissolution and/or intestinal permeability rate-limit desvenlafaxine absorption from an immediate-release formulation (IRF) and Pristiq(®), an extended release formulation (ERF). Semi-mechanistic models of desvenlafaxine were built (using SimCyp(®)) by combining in vitro data on dissolution and permeation (mechanistic part of model) with clinical data (obtained from literature) on distribution and clearance (non-mechanistic part of model). The model predictions of desvenlafaxine pharmacokinetics after IRF and ERF administration were compared with published clinical data from 14 trials. Desvenlafaxine in vivo dissolution from the IRF and ERF was predicted from in vitro solubility studies and biorelevant dissolution studies (using the USP3 dissolution apparatus), respectively. Desvenlafaxine apparent permeability (Papp) at varying apical pH was investigated using the Caco-2 cell line and extrapolated to effective intestinal permeability (Peff) in human duodenum, jejunum, ileum and colon. Desvenlafaxine pKa-values and octanol-water partition coefficients (Do:w) were determined experimentally. Due to predicted rapid dissolution after IRF administration, desvenlafaxine was predicted to be available for permeation in the duodenum. Desvenlafaxine Do:w and Papp increased approximately 13-fold when increasing apical pH from 5.5 to 7.4. Desvenlafaxine Peff thus increased with pH down the small intestine. Consequently, desvenlafaxine absorption from an IRF appears rate-limited by low Peff in the upper small intestine, which "delays" the predicted

  12. Incorporating damage mechanics into explosion simulation models

    International Nuclear Information System (INIS)

    Sammis, C.G.

    1993-01-01

    The source region of an underground explosion is commonly modeled as a nested series of shells. In the innermost open-quotes hydrodynamic regimeclose quotes pressures and temperatures are sufficiently high that the rock deforms as a fluid and may be described using a PVT equation of state. Just beyond the hydrodynamic regime, is the open-quotes non-linear regimeclose quotes in which the rock has shear strength but the deformation is nonlinear. This regime extends out to the open-quotes elastic radiusclose quotes beyond which the deformation is linear. In this paper, we develop a model for the non-linear regime in crystalline source rock where the nonlinearity is mostly due to fractures. We divide the non-linear regime into a open-quotes damage regimeclose quotes in which the stresses are sufficiently high to nucleate new fractures from preexisting ones and a open-quotes crack-slidingclose quotes regime where motion on preexisting cracks produces amplitude dependent attenuation and other non-linear effects, but no new cracks are nucleated. The boundary between these two regimes is called the open-quotes damage radius.close quotes The micromechanical damage mechanics recently developed by Ashby and Sammis (1990) is used to write an analytic expression for the damage radius in terms of the initial fracture spectrum of the source rock, and to develop an algorithm which may be used to incorporate damage mechanics into computer source models for the damage regime. Effects of water saturation and loading rate are also discussed

  13. In Silico Oncology: Quantification of the In Vivo Antitumor Efficacy of Cisplatin-Based Doublet Therapy in Non-Small Cell Lung Cancer (NSCLC) through a Multiscale Mechanistic Model

    Science.gov (United States)

    Kolokotroni, Eleni; Dionysiou, Dimitra; Veith, Christian; Kim, Yoo-Jin; Franz, Astrid; Grgic, Aleksandar; Bohle, Rainer M.; Stamatakos, Georgios

    2016-01-01

    The 5-year survival of non-small cell lung cancer patients can be as low as 1% in advanced stages. For patients with resectable disease, the successful choice of preoperative chemotherapy is critical to eliminate micrometastasis and improve operability. In silico experimentations can suggest the optimal treatment protocol for each patient based on their own multiscale data. A determinant for reliable predictions is the a priori estimation of the drugs’ cytotoxic efficacy on cancer cells for a given treatment. In the present work a mechanistic model of cancer response to treatment is applied for the estimation of a plausible value range of the cell killing efficacy of various cisplatin-based doublet regimens. Among others, the model incorporates the cancer related mechanism of uncontrolled proliferation, population heterogeneity, hypoxia and treatment resistance. The methodology is based on the provision of tumor volumetric data at two time points, before and after or during treatment. It takes into account the effect of tumor microenvironment and cell repopulation on treatment outcome. A thorough sensitivity analysis based on one-factor-at-a-time and latin hypercube sampling/partial rank correlation coefficient approaches has established the volume growth rate and the growth fraction at diagnosis as key features for more accurate estimates. The methodology is applied on the retrospective data of thirteen patients with non-small cell lung cancer who received cisplatin in combination with gemcitabine, vinorelbine or docetaxel in the neoadjuvant context. The selection of model input values has been guided by a comprehensive literature survey on cancer-specific proliferation kinetics. The latin hypercube sampling has been recruited to compensate for patient-specific uncertainties. Concluding, the present work provides a quantitative framework for the estimation of the in-vivo cell-killing ability of various chemotherapies. Correlation studies of such estimates with

  14. Data-based mechanistic modeling of dissolved organic carbon load through storms using continuous 15-minute resolution observations within UK upland watersheds

    Science.gov (United States)

    Jones, T.; Chappell, N. A.

    2013-12-01

    Few watershed modeling studies have addressed DOC dynamics through storm hydrographs (notable exceptions include Boyer et al., 1997 Hydrol Process; Jutras et al., 2011 Ecol Model; Xu et al., 2012 Water Resour Res). In part this has been a consequence of an incomplete understanding of the biogeochemical processes leading to DOC export to streams (Neff & Asner, 2001, Ecosystems) & an insufficient frequency of DOC monitoring to capture sometimes complex time-varying relationships between DOC & storm hydrographs (Kirchner et al., 2004, Hydrol Process). We present the results of a new & ongoing UK study that integrates two components - 1/ New observations of DOC concentrations (& derived load) continuously monitored at 15 minute intervals through multiple seasons for replicated watersheds; & 2/ A dynamic modeling technique that is able to quantify storage-decay effects, plus hysteretic, nonlinear, lagged & non-stationary relationships between DOC & controlling variables (including rainfall, streamflow, temperature & specific biogeochemical variables e.g., pH, nitrate). DOC concentration is being monitored continuously using the latest generation of UV spectrophotometers (i.e. S::CAN spectro::lysers) with in situ calibrations to laboratory analyzed DOC. The controlling variables are recorded simultaneously at the same stream stations. The watersheds selected for study are among the most intensively studied basins in the UK uplands, namely the Plynlimon & Llyn Brianne experimental basins. All contain areas of organic soils, with three having improved grasslands & three conifer afforested. The dynamic response characteristics (DRCs) that describe detailed DOC behaviour through sequences of storms are simulated using the latest identification routines for continuous time transfer function (CT-TF) models within the Matlab-based CAPTAIN toolbox (some incorporating nonlinear components). To our knowledge this is the first application of CT-TFs to modelling DOC processes

  15. Incorporating vehicle mix in stimulus-response car-following models

    Directory of Open Access Journals (Sweden)

    Saidi Siuhi

    2016-06-01

    Full Text Available The objective of this paper is to incorporate vehicle mix in stimulus-response car-following models. Separate models were estimated for acceleration and deceleration responses to account for vehicle mix via both movement state and vehicle type. For each model, three sub-models were developed for different pairs of following vehicles including “automobile following automobile,” “automobile following truck,” and “truck following automobile.” The estimated model parameters were then validated against other data from a similar region and roadway. The results indicated that drivers' behaviors were significantly different among the different pairs of following vehicles. Also the magnitude of the estimated parameters depends on the type of vehicle being driven and/or followed. These results demonstrated the need to use separate models depending on movement state and vehicle type. The differences in parameter estimates confirmed in this paper highlight traffic safety and operational issues of mixed traffic operation on a single lane. The findings of this paper can assist transportation professionals to improve traffic simulation models used to evaluate the impact of different strategies on ameliorate safety and performance of highways. In addition, driver response time lag estimates can be used in roadway design to calculate important design parameters such as stopping sight distance on horizontal and vertical curves for both automobiles and trucks.

  16. A data-driven model for influenza transmission incorporating media effects.

    Science.gov (United States)

    Mitchell, Lewis; Ross, Joshua V

    2016-10-01

    Numerous studies have attempted to model the effect of mass media on the transmission of diseases such as influenza; however, quantitative data on media engagement has until recently been difficult to obtain. With the recent explosion of 'big data' coming from online social media and the like, large volumes of data on a population's engagement with mass media during an epidemic are becoming available to researchers. In this study, we combine an online dataset comprising millions of shared messages relating to influenza with traditional surveillance data on flu activity to suggest a functional form for the relationship between the two. Using this data, we present a simple deterministic model for influenza dynamics incorporating media effects, and show that such a model helps explain the dynamics of historical influenza outbreaks. Furthermore, through model selection we show that the proposed media function fits historical data better than other media functions proposed in earlier studies.

  17. Incorporating microbiota data into epidemiologic models: examples from vaginal microbiota research.

    Science.gov (United States)

    van de Wijgert, Janneke H; Jespers, Vicky

    2016-05-01

    Next generation sequencing and quantitative polymerase chain reaction technologies are now widely available, and research incorporating these methods is growing exponentially. In the vaginal microbiota (VMB) field, most research to date has been descriptive. The purpose of this article is to provide an overview of different ways in which next generation sequencing and quantitative polymerase chain reaction data can be used to answer clinical epidemiologic research questions using examples from VMB research. We reviewed relevant methodological literature and VMB articles (published between 2008 and 2015) that incorporated these methodologies. VMB data have been analyzed using ecologic methods, methods that compare the presence or relative abundance of individual taxa or community compositions between different groups of women or sampling time points, and methods that first reduce the complexity of the data into a few variables followed by the incorporation of these variables into traditional biostatistical models. To make future VMB research more clinically relevant (such as studying associations between VMB compositions and clinical outcomes and the effects of interventions on the VMB), it is important that these methods are integrated with rigorous epidemiologic methods (such as appropriate study designs, sampling strategies, and adjustment for confounding). Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

  18. Incorporating Social Anxiety Into a Model of College Problem Drinking: Replication and Extension

    OpenAIRE

    Ham, Lindsay S.; Hope, Debra A.

    2006-01-01

    Although research has found an association between social anxiety and alcohol use in noncollege samples, results have been mixed for college samples. College students face many novel social situations in which they may drink to reduce social anxiety. In the current study, the authors tested a model of college problem drinking, incorporating social anxiety and related psychosocial variables among 228 undergraduate volunteers. According to structural equation modeling (SEM) results, social anxi...

  19. Incorporating ligament laxity in a finite element model for the upper cervical spine.

    Science.gov (United States)

    Lasswell, Timothy L; Cronin, Duane S; Medley, John B; Rasoulinejad, Parham

    2017-11-01

    Predicting physiological range of motion (ROM) using a finite element (FE) model of the upper cervical spine requires the incorporation of ligament laxity. The effect of ligament laxity can be observed only on a macro level of joint motion and is lost once ligaments have been dissected and preconditioned for experimental testing. As a result, although ligament laxity values are recognized to exist, specific values are not directly available in the literature for use in FE models. The purpose of the current study is to propose an optimization process that can be used to determine a set of ligament laxity values for upper cervical spine FE models. Furthermore, an FE model that includes ligament laxity is applied, and the resulting ROM values are compared with experimental data for physiological ROM, as well as experimental data for the increase in ROM when a Type II odontoid fracture is introduced. The upper cervical spine FE model was adapted from a 50th percentile male full-body model developed with the Global Human Body Models Consortium (GHBMC). FE modeling was performed in LS-DYNA and LS-OPT (Livermore Software Technology Group) was used for ligament laxity optimization. Ordinate-based curve matching was used to minimize the mean squared error (MSE) between computed load-rotation curves and experimental load-rotation curves under flexion, extension, and axial rotation with pure moment loads from 0 to 3.5 Nm. Lateral bending was excluded from the optimization because the upper cervical spine was considered to be primarily responsible for flexion, extension, and axial rotation. Based on recommendations from the literature, four varying inputs representing laxity in select ligaments were optimized to minimize the MSE. Funding was provided by the Natural Sciences and Engineering Research Council of Canada as well as GHMBC. The present study was funded by the Natural Sciences and Engineering Research Council of Canada to support the work of one graduate student

  20. Why did Jacques Monod make the choice of mechanistic determinism?

    Science.gov (United States)

    Loison, Laurent

    2015-06-01

    The development of molecular biology placed in the foreground a mechanistic and deterministic conception of the functioning of macromolecules. In this article, I show that this conception was neither obvious, nor necessary. Taking Jacques Monod as a case study, I detail the way he gradually came loose from a statistical understanding of determinism to finally support a mechanistic understanding. The reasons of the choice made by Monod at the beginning of the 1950s can be understood only in the light of the general theoretical schema supported by the concept of mechanistic determinism. This schema articulates three fundamental notions for Monod, namely that of the rigidity of the sequence of the genetic program, that of the intrinsic stability of macromolecules (DNA and proteins), and that of the specificity of molecular interactions. Copyright © 2015 Académie des sciences. Published by Elsevier SAS. All rights reserved.

  1. Arsenic Exposure and Type 2 Diabetes: MicroRNAs as Mechanistic Links?

    OpenAIRE

    Beck, Rowan; Styblo, Miroslav; Sethupathy, Praveen

    2017-01-01

    Purpose of Review The goal of this review is to delineate the following: (1) the primary means of inorganic arsenic (iAs) exposure for human populations, (2) the adverse public health outcomes associated with chronic iAs exposure, (3) the pathophysiological connection between arsenic and type 2 diabetes (T2D), and (4) the incipient evidence for microRNAs as candidate mechanistic links between iAs exposure and T2D. Recent Findings Exposure to iAs in animal models has been associated with the d...

  2. Physiologically induced color-pattern changes in butterfly wings: mechanistic and evolutionary implications.

    Science.gov (United States)

    Otaki, Joji M

    2008-07-01

    A mechanistic understanding of the butterfly wing color-pattern determination can be facilitated by experimental pattern changes. Here I review physiologically induced color-pattern changes in nymphalid butterflies and their mechanistic and evolutionary implications. A type of color-pattern change can be elicited by elemental changes in size and position throughout the wing, as suggested by the nymphalid groundplan. These changes of pattern elements are bi-directional and bi-sided dislocation toward or away from eyespot foci and in both proximal and distal sides of the foci. The peripheral elements are dislocated even in the eyespot-less compartments. Anterior spots are more severely modified, suggesting the existence of an anterior-posterior gradient. In one species, eyespots are transformed into white spots with remnant-like orange scales, and such patterns emerge even at the eyespot-less "imaginary" foci. A series of these color-pattern modifications probably reveal "snap-shots" of a dynamic morphogenic signal due to heterochronic uncoupling between the signaling and reception steps. The conventional gradient model can be revised to account for these observed color-pattern changes.

  3. On the incorporation of biokinetic and mechanistic data in modeling for risk assessment

    NARCIS (Netherlands)

    Clewell, H.J.

    2007-01-01

    The goal of the studies described in this thesis was to foster the increased use of emerging scientific information and innovative methods in chemical risk assessments, in order to assure the protection of public health while limiting the economic and social consequences of over-regulation. The

  4. [Incorporation of an organic MAGIC (Model of Acidification of Groundwater in Catchments) and testing of the revised model using independent data sources]. [MAGIC Model

    Energy Technology Data Exchange (ETDEWEB)

    Sullivan, T.J.

    1992-09-01

    A project was initiated in March, 1992 to (1) incorporate a rigorous organic acid representation, based on empirical data and geochemical considerations, into the MAGIC model of acidification response, and (2) test the revised model using three sets of independent data. After six months of performance, the project is on schedule and the majority of the tasks outlined for Year 1 have been successfully completed. Major accomplishments to data include development of the organic acid modeling approach, using data from the Adirondack Lakes Survey Corporation (ALSC), and coupling the organic acid model with MAGIC for chemical hindcast comparisons. The incorporation of an organic acid representation into MAGIC can account for much of the discrepancy earlier observed between MAGIC hindcasts and paleolimnological reconstructions of preindustrial pH and alkalinity for 33 statistically-selected Adirondack lakes. Additional work is on-going for model calibration and testing with data from two whole-catchment artificial acidification projects. Results obtained thus far are being prepared as manuscripts for submission to the peer-reviewed scientific literature.

  5. Are adverse effects incorporated in economic models? An initial review of current practice.

    Science.gov (United States)

    Craig, D; McDaid, C; Fonseca, T; Stock, C; Duffy, S; Woolacott, N

    2009-12-01

    To identify methodological research on the incorporation of adverse effects in economic models and to review current practice. Major electronic databases (Cochrane Methodology Register, Health Economic Evaluations Database, NHS Economic Evaluation Database, EconLit, EMBASE, Health Management Information Consortium, IDEAS, MEDLINE and Science Citation Index) were searched from inception to September 2007. Health technology assessment (HTA) reports commissioned by the National Institute for Health Research (NIHR) HTA programme and published between 2004 and 2007 were also reviewed. The reviews of methodological research on the inclusion of adverse effects in decision models and of current practice were carried out according to standard methods. Data were summarised in a narrative synthesis. Of the 719 potentially relevant references in the methodological research review, five met the inclusion criteria; however, they contained little information of direct relevance to the incorporation of adverse effects in models. Of the 194 HTA monographs published from 2004 to 2007, 80 were reviewed, covering a range of research and therapeutic areas. In total, 85% of the reports included adverse effects in the clinical effectiveness review and 54% of the decision models included adverse effects in the model; 49% included adverse effects in the clinical review and model. The link between adverse effects in the clinical review and model was generally weak; only 3/80 (manipulation. Of the models including adverse effects, 67% used a clinical adverse effects parameter, 79% used a cost of adverse effects parameter, 86% used one of these and 60% used both. Most models (83%) used utilities, but only two (2.5%) used solely utilities to incorporate adverse effects and were explicit that the utility captured relevant adverse effects; 53% of those models that included utilities derived them from patients on treatment and could therefore be interpreted as capturing adverse effects. In total

  6. The general dynamic model

    DEFF Research Database (Denmark)

    Borregaard, Michael K.; Matthews, Thomas J.; Whittaker, Robert James

    2016-01-01

    Aim: Island biogeography focuses on understanding the processes that underlie a set of well-described patterns on islands, but it lacks a unified theoretical framework for integrating these processes. The recently proposed general dynamic model (GDM) of oceanic island biogeography offers a step...... towards this goal. Here, we present an analysis of causality within the GDM and investigate its potential for the further development of island biogeographical theory. Further, we extend the GDM to include subduction-based island arcs and continental fragment islands. Location: A conceptual analysis...... of evolutionary processes in simulations derived from the mechanistic assumptions of the GDM corresponded broadly to those initially suggested, with the exception of trends in extinction rates. Expanding the model to incorporate different scenarios of island ontogeny and isolation revealed a sensitivity...

  7. Incorporation of chemical kinetic models into process control

    International Nuclear Information System (INIS)

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

    1981-01-01

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

  8. Mechanistic study of manganese-substituted glycerol dehydrogenase using a kinetic and thermodynamic analysis.

    Science.gov (United States)

    Fang, Baishan; Niu, Jin; Ren, Hong; Guo, Yingxia; Wang, Shizhen

    2014-01-01

    Mechanistic insights regarding the activity enhancement of dehydrogenase by metal ion substitution were investigated by a simple method using a kinetic and thermodynamic analysis. By profiling the binding energy of both the substrate and product, the metal ion's role in catalysis enhancement was revealed. Glycerol dehydrogenase (GDH) from Klebsiella pneumoniae sp., which demonstrated an improvement in activity by the substitution of a zinc ion with a manganese ion, was used as a model for the mechanistic study of metal ion substitution. A kinetic model based on an ordered Bi-Bi mechanism was proposed considering the noncompetitive product inhibition of dihydroxyacetone (DHA) and the competitive product inhibition of NADH. By obtaining preliminary kinetic parameters of substrate and product inhibition, the number of estimated parameters was reduced from 10 to 4 for a nonlinear regression-based kinetic parameter estimation. The simulated values of time-concentration curves fit the experimental values well, with an average relative error of 11.5% and 12.7% for Mn-GDH and GDH, respectively. A comparison of the binding energy of enzyme ternary complex for Mn-GDH and GDH derived from kinetic parameters indicated that metal ion substitution accelerated the release of dioxyacetone. The metal ion's role in catalysis enhancement was explicated.

  9. Mechanistic study of manganese-substituted glycerol dehydrogenase using a kinetic and thermodynamic analysis.

    Directory of Open Access Journals (Sweden)

    Baishan Fang

    Full Text Available Mechanistic insights regarding the activity enhancement of dehydrogenase by metal ion substitution were investigated by a simple method using a kinetic and thermodynamic analysis. By profiling the binding energy of both the substrate and product, the metal ion's role in catalysis enhancement was revealed. Glycerol dehydrogenase (GDH from Klebsiella pneumoniae sp., which demonstrated an improvement in activity by the substitution of a zinc ion with a manganese ion, was used as a model for the mechanistic study of metal ion substitution. A kinetic model based on an ordered Bi-Bi mechanism was proposed considering the noncompetitive product inhibition of dihydroxyacetone (DHA and the competitive product inhibition of NADH. By obtaining preliminary kinetic parameters of substrate and product inhibition, the number of estimated parameters was reduced from 10 to 4 for a nonlinear regression-based kinetic parameter estimation. The simulated values of time-concentration curves fit the experimental values well, with an average relative error of 11.5% and 12.7% for Mn-GDH and GDH, respectively. A comparison of the binding energy of enzyme ternary complex for Mn-GDH and GDH derived from kinetic parameters indicated that metal ion substitution accelerated the release of dioxyacetone. The metal ion's role in catalysis enhancement was explicated.

  10. Application of mechanistic empirical approach to predict rutting of superpave mixtures in Iraq

    Directory of Open Access Journals (Sweden)

    Qasim Zaynab

    2018-01-01

    Full Text Available In Iraq rutting is considered as a real distress in flexible pavements as a result of high summer temperature, and increased axle loads. This distress majorly affects asphalt pavement performance, lessens the pavement useful service life and makes serious hazards for highway users. Performance of HMA mixtures against rutting using Mechanistic- Empirical approach is predicted by considering Wheel-Tracking test and employing the Superpave mix design requirements. Roller Wheel Compactor has been locally manufactured to prepare slab specimens. In view of study laboratory outcomes that are judged to be simulative of field loading conditions, models are developed for predicting permanent strain of compacted samples of local asphalt concrete mixtures after considering the stress level, properties of local material and environmental impacts variables. All in all, laboratory results were produced utilizing statistical analysis with the aid of SPSS software. Permanent strain models for asphalt concrete mixtures were developed as a function of: number of passes, temperature, asphalt content, viscosity, air voids and additive content. Mechanistic Empirical design approach through the MnPAVE software was applied to characterize rutting in HMA and to predict allowable number of loading repetitions of mixtures as a function of expected traffic loads, material properties, and environmental temperature.

  11. A model of ruminal volatile fatty acid absorption kinetics and rumen epithelial blood flow in lactating Holstein cows

    DEFF Research Database (Denmark)

    Storm, Adam Christian; Kristensen, Niels Bastian; Hanigan, Mark D

    2012-01-01

    Ruminal absorption of volatile fatty acids (VFA) is quantitatively the most important nutrient flux in cattle. Historically, VFA absorption models have been derived primarily from ruminal variables such as chemical composition of the fluid, volume, and pH. Recently, a mechanistic model incorporated...... exchange across the rumen wall that incorporates epithelial blood flow as a driving force for ruminal VFA removal. The bidirectional fluxes between the ruminal and epithelial pool of VFA were assumed mass action driven, given that passive diffusion of nonionized VFA is the dominant transmembrane VFA flux...... of body weight. The rate constants related to the flux from ruminal fluid to epithelium were in the order isobutyrate rate constants for fluxes of isobutyrate, acetate, propionate, and butyrate...

  12. Development of a mechanistically based computer simulation of nitrogen oxide absorption in packed towers

    International Nuclear Information System (INIS)

    Counce, R.M.

    1981-01-01

    A computer simulation for nitrogen oxide (NO/sub x/) scrubbing in packed towers was developed for use in process design and process control. This simulation implements a mechanistically based mathematical model, which was formulated from (1) an exhaustive literature review; (2) previous NO/sub x/ scrubbing experience with sieve-plate towers; and (3) comparisons of sequential sets of experiments. Nitrogen oxide scrubbing is characterized by simultaneous absorption and desorption phenomena: the model development is based on experiments designed to feature these two phenomena. The model was then successfully tested in experiments designed to put it in jeopardy

  13. Incorporation of detailed eye model into polygon-mesh versions of ICRP-110 reference phantoms.

    Science.gov (United States)

    Nguyen, Thang Tat; Yeom, Yeon Soo; Kim, Han Sung; Wang, Zhao Jun; Han, Min Cheol; Kim, Chan Hyeong; Lee, Jai Ki; Zankl, Maria; Petoussi-Henss, Nina; Bolch, Wesley E; Lee, Choonsik; Chung, Beom Sun

    2015-11-21

    The dose coefficients for the eye lens reported in ICRP 2010 Publication 116 were calculated using both a stylized model and the ICRP-110 reference phantoms, according to the type of radiation, energy, and irradiation geometry. To maintain consistency of lens dose assessment, in the present study we incorporated the ICRP-116 detailed eye model into the converted polygon-mesh (PM) version of the ICRP-110 reference phantoms. After the incorporation, the dose coefficients for the eye lens were calculated and compared with those of the ICRP-116 data. The results showed generally a good agreement between the newly calculated lens dose coefficients and the values of ICRP 2010 Publication 116. Significant differences were found for some irradiation cases due mainly to the use of different types of phantoms. Considering that the PM version of the ICRP-110 reference phantoms preserve the original topology of the ICRP-110 reference phantoms, it is believed that the PM version phantoms, along with the detailed eye model, provide more reliable and consistent dose coefficients for the eye lens.

  14. A preliminary study of mechanistic approach in pavement design to accommodate climate change effects

    Science.gov (United States)

    Harnaeni, S. R.; Pramesti, F. P.; Budiarto, A.; Setyawan, A.

    2018-03-01

    Road damage is caused by some factors, including climate changes, overload, and inappropriate procedure for material and development process. Meanwhile, climate change is a phenomenon which cannot be avoided. The effects observed include air temperature rise, sea level rise, rainfall changes, and the intensity of extreme weather phenomena. Previous studies had shown the impacts of climate changes on road damage. Therefore, several measures to anticipate the damage should be considered during the planning and construction in order to reduce the cost of road maintenance. There are three approaches generally applied in the design of flexible pavement thickness, namely mechanistic approach, mechanistic-empirical (ME) approach and empirical approach. The advantages of applying mechanistic approach or mechanistic-empirical (ME) approaches are its efficiency and reliability in the design of flexible pavement thickness as well as its capacity to accommodate climate changes in compared to empirical approach. However, generally, the design of flexible pavement thickness in Indonesia still applies empirical approach. This preliminary study aimed to emphasize the importance of the shifting towards a mechanistic approach in the design of flexible pavement thickness.

  15. Dynamic and accurate assessment of acetaminophen-induced hepatotoxicity by integrated photoacoustic imaging and mechanistic biomarkers in vivo.

    Science.gov (United States)

    Brillant, Nathalie; Elmasry, Mohamed; Burton, Neal C; Rodriguez, Josep Monne; Sharkey, Jack W; Fenwick, Stephen; Poptani, Harish; Kitteringham, Neil R; Goldring, Christopher E; Kipar, Anja; Park, B Kevin; Antoine, Daniel J

    2017-10-01

    The prediction and understanding of acetaminophen (APAP)-induced liver injury (APAP-ILI) and the response to therapeutic interventions is complex. This is due in part to sensitivity and specificity limitations of currently used assessment techniques. Here we sought to determine the utility of integrating translational non-invasive photoacoustic imaging of liver function with mechanistic circulating biomarkers of hepatotoxicity with histological assessment to facilitate the more accurate and precise characterization of APAP-ILI and the efficacy of therapeutic intervention. Perturbation of liver function and cellular viability was assessed in C57BL/6J male mice by Indocyanine green (ICG) clearance (Multispectral Optoacoustic Tomography (MSOT)) and by measurement of mechanistic (miR-122, HMGB1) and established (ALT, bilirubin) circulating biomarkers in response to the acetaminophen and its treatment with acetylcysteine (NAC) in vivo. We utilised a 60% partial hepatectomy model as a situation of defined hepatic functional mass loss to compared acetaminophen-induced changes to. Integration of these mechanistic markers correlated with histological features of APAP hepatotoxicity in a time-dependent manner. They accurately reflected the onset and recovery from hepatotoxicity compared to traditional biomarkers and also reported the efficacy of NAC with high sensitivity. ICG clearance kinetics correlated with histological scores for acute liver damage for APAP (i.e. 3h timepoint; r=0.90, P<0.0001) and elevations in both of the mechanistic biomarkers, miR-122 (e.g. 6h timepoint; r=0.70, P=0.005) and HMGB1 (e.g. 6h timepoint; r=0.56, P=0.04). For the first time we report the utility of this non-invasive longitudinal imaging approach to provide direct visualisation of the liver function coupled with mechanistic biomarkers, in the same animal, allowing the investigation of the toxicological and pharmacological aspects of APAP-ILI and hepatic regeneration. Copyright © 2017

  16. Thermal-hydraulic and characteristic models for packed debris beds

    International Nuclear Information System (INIS)

    Mueller, G.E.; Sozer, A.

    1986-12-01

    APRIL is a mechanistic core-wide meltdown and debris relocation computer code for Boiling Water Reactor (BWR) severe accident analyses. The capabilities of the code continue to be increased by the improvement of existing models. This report contains information on theory and models for degraded core packed debris beds. The models, when incorporated into APRIL, will provide new and improved capabilities in predicting BWR debris bed coolability characteristics. These models will allow for a more mechanistic treatment in calculating temperatures in the fluid and solid phases in the debris bed, in determining debris bed dryout, debris bed quenching from either top-flooding or bottom-flooding, single and two-phase pressure drops across the debris bed, debris bed porosity, and in finding the minimum fluidization mass velocity. The inclusion of these models in a debris bed computer module will permit a more accurate prediction of the coolability characteristics of the debris bed and therefore reduce some of the uncertainties in assessing the severe accident characteristics for BWR application. Some of the debris bed theoretical models have been used to develop a FORTRAN 77 subroutine module called DEBRIS. DEBRIS is a driver program that calls other subroutines to analyze the thermal characteristics of a packed debris bed. Fortran 77 listings of each subroutine are provided in the appendix

  17. Mechanistic aspects of ionic reactions in flames

    DEFF Research Database (Denmark)

    Egsgaard, H.; Carlsen, L.

    1993-01-01

    Some fundamentals of the ion chemistry of flames are summarized. Mechanistic aspects of ionic reactions in flames have been studied using a VG PlasmaQuad, the ICP-system being substituted by a simple quartz burner. Simple hydrocarbon flames as well as sulfur-containing flames have been investigated...

  18. Incorporation of basic side chains into cryptolepine scaffold: structure-antimalarial activity relationships and mechanistic studies.

    Science.gov (United States)

    Lavrado, João; Cabal, Ghislain G; Prudêncio, Miguel; Mota, Maria M; Gut, Jiri; Rosenthal, Philip J; Díaz, Cecília; Guedes, Rita C; dos Santos, Daniel J V A; Bichenkova, Elena; Douglas, Kenneth T; Moreira, Rui; Paulo, Alexandra

    2011-02-10

    The synthesis of cryptolepine derivatives containing basic side-chains at the C-11 position and their evaluations for antiplasmodial and cytotoxicity properties are reported. Propyl, butyl, and cycloalkyl diamine side chains significantly increased activity against chloroquine-resistant Plasmodium falciparum strains while reducing cytotoxicity when compared with the parent compound. Localization studies inside parasite blood stages by fluorescence microscopy showed that these derivatives accumulate inside the nucleus, indicating that the incorporation of a basic side chain is not sufficient enough to promote selective accumulation in the acidic digestive vacuole of the parasite. Most of the compounds within this series showed the ability to bind to a double-stranded DNA duplex as well to monomeric hematin, suggesting that these are possible targets associated with the observed antimalarial activity. Overall, these novel cryptolepine analogues with substantially improved antiplasmodial activity and selectivity index provide a promising starting point for development of potent and highly selective agents against drug-resistant malaria parasites.

  19. Semi-mechanistic partial buffer approach to modeling pH, the buffer properties, and the distribution of ionic species in complex solutions.

    Science.gov (United States)

    Dougherty, Daniel P; Da Conceicao Neta, Edith Ramos; McFeeters, Roger F; Lubkin, Sharon R; Breidt, Frederick

    2006-08-09

    In many biological science and food processing applications, it is very important to control or modify pH. However, the complex, unknown composition of biological media and foods often limits the utility of purely theoretical approaches to modeling pH and calculating the distributions of ionizable species. This paper provides general formulas and efficient algorithms for predicting the pH, titration, ionic species concentrations, buffer capacity, and ionic strength of buffer solutions containing both defined and undefined components. A flexible, semi-mechanistic, partial buffering (SMPB) approach is presented that uses local polynomial regression to model the buffering influence of complex or undefined components in a solution, while identified components of known concentration are modeled using expressions based on extensions of the standard acid-base theory. The SMPB method is implemented in a freeware package, (pH)Tools, for use with Matlab. We validated the predictive accuracy of these methods by using strong acid titrations of cucumber slurries to predict the amount of a weak acid required to adjust pH to selected target values.

  20. A mechanistic ecohydrological model to investigate complex interactions in cold and warm water-controlled environments. 2. Spatiotemporal analyses

    Directory of Open Access Journals (Sweden)

    Simone Fatichi

    2012-05-01

    Full Text Available An ecohydrological model Tethys-Chloris (T&C described in the companion paper is applied to two semiarid systems characterized by different climate and vegetation cover conditions. The Lucky Hills watershed in Arizona represents a typical small, ``unit-source'' catchment of a desert shrub system of the U.S. southwest. Two nested basins of the Reynolds Creek Experimental watershed (Idaho, U.S.A., the Reynolds Creek Mountain East and Tollgate catchments, are representative of a semiarid cold climate with seasonal snow cover. Both exhibit a highly non-uniform vegetation cover. A range of ecohydrological metrics of the long-term model performance is presented to highlight the model capabilities in reproducing hydrological and vegetation dynamics both at the plot and the watershed scales. A diverse set of observations is used to confirm the simulated dynamics. Highly satisfactory results are obtained without significant (or any calibration efforts despite the large phase-space dimensionality of the model, the uncertainty of imposed boundary conditions, and limited data availability. It is argued that a significant investment into the model design based on the description of physical, biophysical, and ecological processes leads to such a consistent simulation skill. The simulated patterns mimic the outcome of hydrological and vegetation dynamics with high realism, as confirmed from spatially distributed remote sensing data. Further community efforts are warranted to address the issue of thorough quantitative assessment. The current lack of appropriate data hampers the development and testing of process-based ecohydrological models. It is further argued that the mechanistic nature of the T&C model can be valuable for designing virtual experiments and developing questions of scientific inquiry at a range of spatiotemporal scales.

  1. A Mechanistic Model of Onset of Flow Instability Due to Mergence of Bubble Layers in a Vertical Narrow Rectangular Channel

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Juh Yung; Chang, Soon Heung; Jeong, Yong [KAIST, Daejeon (Korea, Republic of)

    2016-05-15

    The onset of flow instability (OFI) is the one of important boiling phenomena since it may induce the premature critical heat flux (CHF) at the lowest heat flux level due to sudden flow excursion in a single channel of multichannel configuration. Especially prediction of OFI for narrow rectangular channel is very crucial in relevant to thermal-hydraulic design and safety analysis of open pool-type research reactors (RRs) using plate-type fuels. Based on high speed video (HSV) technique, the authors observed and determined that OFI and the minimum premature CHF in a narrow rectangular channel are induced by abrupt pressure drop fluctuation due to the mergence of facing bubble boundary layers (BLs) on opposite boiling surfaces. In this study, new mechanistic OFI model for narrow rectangular channel heated on both sides has been derived, which satisfies with the real triggering phenomena. Force balance approach was used for modeling of the maximum BLT since the quantity is comparable to the bubble departure diameter. From the validation with OFI database, it was shown that the new model fairly well predicts OFI heat flux for wide range of conditions.

  2. The E. coli pET expression system revisited-mechanistic correlation between glucose and lactose uptake.

    Science.gov (United States)

    Wurm, David Johannes; Veiter, Lukas; Ulonska, Sophia; Eggenreich, Britta; Herwig, Christoph; Spadiut, Oliver

    2016-10-01

    Therapeutic monoclonal antibodies are mainly produced in mammalian cells to date. However, unglycosylated antibody fragments can also be produced in the bacterium Escherichia coli which brings several advantages, like growth on cheap media and high productivity. One of the most popular E. coli strains for recombinant protein production is E. coli BL21(DE3) which is usually used in combination with the pET expression system. However, it is well known that induction by isopropyl β-D-1-thiogalactopyranoside (IPTG) stresses the cells and can lead to the formation of insoluble inclusion bodies. In this study, we revisited the pET expression system for the production of a novel antibody single-chain variable fragment (scFv) with the goal of maximizing the amount of soluble product. Thus, we (1) investigated whether lactose favors the recombinant production of soluble scFv compared to IPTG, (2) investigated whether the formation of soluble product can be influenced by the specific glucose uptake rate (q s,glu) during lactose induction, and (3) determined the mechanistic correlation between the specific lactose uptake rate (q s,lac) and q s,glu. We found that lactose induction gave a much greater amount of soluble scFv compared to IPTG, even when the growth rate was increased. Furthermore, we showed that the production of soluble protein could be tuned by varying q s,glu during lactose induction. Finally, we established a simple model describing the mechanistic correlation between q s,lac and q s,glu allowing tailored feeding and prevention of sugar accumulation. We believe that this mechanistic model might serve as platform knowledge for E. coli.

  3. Incorporating spatial autocorrelation into species distribution models alters forecasts of climate-mediated range shifts.

    Science.gov (United States)

    Crase, Beth; Liedloff, Adam; Vesk, Peter A; Fukuda, Yusuke; Wintle, Brendan A

    2014-08-01

    Species distribution models (SDMs) are widely used to forecast changes in the spatial distributions of species and communities in response to climate change. However, spatial autocorrelation (SA) is rarely accounted for in these models, despite its ubiquity in broad-scale ecological data. While spatial autocorrelation in model residuals is known to result in biased parameter estimates and the inflation of type I errors, the influence of unmodeled SA on species' range forecasts is poorly understood. Here we quantify how accounting for SA in SDMs influences the magnitude of range shift forecasts produced by SDMs for multiple climate change scenarios. SDMs were fitted to simulated data with a known autocorrelation structure, and to field observations of three mangrove communities from northern Australia displaying strong spatial autocorrelation. Three modeling approaches were implemented: environment-only models (most frequently applied in species' range forecasts), and two approaches that incorporate SA; autologistic models and residuals autocovariate (RAC) models. Differences in forecasts among modeling approaches and climate scenarios were quantified. While all model predictions at the current time closely matched that of the actual current distribution of the mangrove communities, under the climate change scenarios environment-only models forecast substantially greater range shifts than models incorporating SA. Furthermore, the magnitude of these differences intensified with increasing increments of climate change across the scenarios. When models do not account for SA, forecasts of species' range shifts indicate more extreme impacts of climate change, compared to models that explicitly account for SA. Therefore, where biological or population processes induce substantial autocorrelation in the distribution of organisms, and this is not modeled, model predictions will be inaccurate. These results have global importance for conservation efforts as inaccurate

  4. Fuzzy Logic-Based Model That Incorporates Personality Traits for Heterogeneous Pedestrians

    Directory of Open Access Journals (Sweden)

    Zhuxin Xue

    2017-10-01

    Full Text Available Most models designed to simulate pedestrian dynamical behavior are based on the assumption that human decision-making can be described using precise values. This study proposes a new pedestrian model that incorporates fuzzy logic theory into a multi-agent system to address cognitive behavior that introduces uncertainty and imprecision during decision-making. We present a concept of decision preferences to represent the intrinsic control factors of decision-making. To realize the different decision preferences of heterogeneous pedestrians, the Five-Factor (OCEAN personality model is introduced to model the psychological characteristics of individuals. Then, a fuzzy logic-based approach is adopted for mapping the relationships between the personality traits and the decision preferences. Finally, we have developed an application using our model to simulate pedestrian dynamical behavior in several normal or non-panic scenarios, including a single-exit room, a hallway with obstacles, and a narrowing passage. The effectiveness of the proposed model is validated with a user study. The results show that the proposed model can generate more reasonable and heterogeneous behavior in the simulation and indicate that individual personality has a noticeable effect on pedestrian dynamical behavior.

  5. REVIEW OF MECHANISTIC UNDERSTANDING AND MODELING AND UNCERTAINTY ANALYSIS METHODS FOR PREDICTING CEMENTITIOUS BARRIER PERFORMANCE

    Energy Technology Data Exchange (ETDEWEB)

    Langton, C.; Kosson, D.

    2009-11-30

    Cementitious barriers for nuclear applications are one of the primary controls for preventing or limiting radionuclide release into the environment. At the present time, performance and risk assessments do not fully incorporate the effectiveness of engineered barriers because the processes that influence performance are coupled and complicated. Better understanding the behavior of cementitious barriers is necessary to evaluate and improve the design of materials and structures used for radioactive waste containment, life extension of current nuclear facilities, and design of future nuclear facilities, including those needed for nuclear fuel storage and processing, nuclear power production and waste management. The focus of the Cementitious Barriers Partnership (CBP) literature review is to document the current level of knowledge with respect to: (1) mechanisms and processes that directly influence the performance of cementitious materials (2) methodologies for modeling the performance of these mechanisms and processes and (3) approaches to addressing and quantifying uncertainties associated with performance predictions. This will serve as an important reference document for the professional community responsible for the design and performance assessment of cementitious materials in nuclear applications. This review also provides a multi-disciplinary foundation for identification, research, development and demonstration of improvements in conceptual understanding, measurements and performance modeling that would be lead to significant reductions in the uncertainties and improved confidence in the estimating the long-term performance of cementitious materials in nuclear applications. This report identifies: (1) technology gaps that may be filled by the CBP project and also (2) information and computational methods that are in currently being applied in related fields but have not yet been incorporated into performance assessments of cementitious barriers. The various

  6. Review Of Mechanistic Understanding And Modeling And Uncertainty Analysis Methods For Predicting Cementitious Barrier Performance

    International Nuclear Information System (INIS)

    Langton, C.; Kosson, D.

    2009-01-01

    Cementitious barriers for nuclear applications are one of the primary controls for preventing or limiting radionuclide release into the environment. At the present time, performance and risk assessments do not fully incorporate the effectiveness of engineered barriers because the processes that influence performance are coupled and complicated. Better understanding the behavior of cementitious barriers is necessary to evaluate and improve the design of materials and structures used for radioactive waste containment, life extension of current nuclear facilities, and design of future nuclear facilities, including those needed for nuclear fuel storage and processing, nuclear power production and waste management. The focus of the Cementitious Barriers Partnership (CBP) literature review is to document the current level of knowledge with respect to: (1) mechanisms and processes that directly influence the performance of cementitious materials (2) methodologies for modeling the performance of these mechanisms and processes and (3) approaches to addressing and quantifying uncertainties associated with performance predictions. This will serve as an important reference document for the professional community responsible for the design and performance assessment of cementitious materials in nuclear applications. This review also provides a multi-disciplinary foundation for identification, research, development and demonstration of improvements in conceptual understanding, measurements and performance modeling that would be lead to significant reductions in the uncertainties and improved confidence in the estimating the long-term performance of cementitious materials in nuclear applications. This report identifies: (1) technology gaps that may be filled by the CBP project and also (2) information and computational methods that are in currently being applied in related fields but have not yet been incorporated into performance assessments of cementitious barriers. The various

  7. Roughness Versus Charge Contributions to Representative Discrete Heterogeneity Underlying Mechanistic Prediction of Colloid Attachment, Detachment and Breakthrough-Elution Behavior Under Environmental Conditions.

    Science.gov (United States)

    Johnson, William; Farnsworth, Anna; Vanness, Kurt; Hilpert, Markus

    2017-04-01

    The key element of a mechanistic theory to predict colloid attachment in porous media under environmental conditions where colloid-collector repulsion exists (unfavorable conditions for attachment) is representation of the nano-scale surface heterogeneity (herein called discrete heterogeneity) that drives colloid attachment under unfavorable conditions. The observed modes of colloid attachment under unfavorable conditions emerge from simulations that incorporate discrete heterogeneity. Quantitative prediction of attachment (and detachment) requires capturing the sizes, spatial frequencies, and other properties of roughness asperities and charge heterodomains in discrete heterogeneity representations of different surfaces. The fact that a given discrete heterogeneity representation will interact differently with different-sized colloids as well as different ionic strengths for a given sized colloid allows backing out representative discrete heterogeneity via comparison of simulations to experiments performed across a range of colloid size, solution IS, and fluid velocity. This has been achieved on unfavorable smooth surfaces yielding quantitative prediction of attachment, and qualitative prediction of detachment in response to ionic strength or flow perturbations. Extending this treatment to rough surfaces, and representing the contributions of nanoscale roughness as well as charge heterogeneity is a focus of this talk. Another focus of this talk is the upscaling the pore scale simulations to produce contrasting breakthrough-elution behaviors at the continuum (column) scale that are observed, for example, for different-sized colloids, or same-sized colloids under different ionic strength conditions. The outcome of mechanistic pore scale simulations incorporating discrete heterogeneity and subsequent upscaling is that temporal processes such as blocking and ripening will emerge organically from these simulations, since these processes fundamentally stem from the

  8. Developing a stochastic parameterization to incorporate plant trait variability into ecohydrologic modeling

    Science.gov (United States)

    Liu, S.; Ng, G. H. C.

    2017-12-01

    The global plant database has revealed that plant traits can vary more within a plant functional type (PFT) than among different PFTs, indicating that the current paradigm in ecohydrogical models of specifying fixed parameters based solely on plant functional type (PFT) could potentially bias simulations. Although some recent modeling studies have attempted to incorporate this observed plant trait variability, many failed to consider uncertainties due to sparse global observation, or they omitted spatial and/or temporal variability in the traits. Here we present a stochastic parameterization for prognostic vegetation simulations that are stochastic in time and space in order to represent plant trait plasticity - the process by which trait differences arise. We have developed the new PFT parameterization within the Community Land Model 4.5 (CLM 4.5) and tested the method for a desert shrubland watershed in the Mojave Desert, where fixed parameterizations cannot represent acclimation to desert conditions. Spatiotemporally correlated plant trait parameters were first generated based on TRY statistics and were then used to implement ensemble runs for the study area. The new PFT parameterization was then further conditioned on field measurements of soil moisture and remotely sensed observations of leaf-area-index to constrain uncertainties in the sparse global database. Our preliminary results show that incorporating data-conditioned, variable PFT parameterizations strongly affects simulated soil moisture and water fluxes, compared with default simulations. The results also provide new insights about correlations among plant trait parameters and between traits and environmental conditions in the desert shrubland watershed. Our proposed stochastic PFT parameterization method for ecohydrological models has great potential in advancing our understanding of how terrestrial ecosystems are predicted to adapt to variable environmental conditions.

  9. Adolescent Decision-Making Processes regarding University Entry: A Model Incorporating Cultural Orientation, Motivation and Occupational Variables

    Science.gov (United States)

    Jung, Jae Yup

    2013-01-01

    This study tested a newly developed model of the cognitive decision-making processes of senior high school students related to university entry. The model incorporated variables derived from motivation theory (i.e. expectancy-value theory and the theory of reasoned action), literature on cultural orientation and occupational considerations. A…

  10. A Mass Balance Model for Designing Green Roof Systems that Incorporate a Cistern for Re-Use

    Directory of Open Access Journals (Sweden)

    Manoj Chopra

    2012-11-01

    Full Text Available Green roofs, which have been used for several decades in many parts of the world, offer a unique and sustainable approach to stormwater management. Within this paper, evidence is presented on water retention for an irrigated green roof system. The presented green roof design results in a water retention volume on site. A first principle mass balance computer model is introduced to assist with the design of these green roof systems which incorporate a cistern to capture and reuse runoff waters for irrigation of the green roof. The model is used to estimate yearly stormwater retention volume for different cistern storage volumes. Additionally, the Blaney and Criddle equation is evaluated for estimation of monthly evapotranspiration rates for irrigated systems and incorporated into the model. This is done so evapotranspiration rates can be calculated for regions where historical data does not exist, allowing the model to be used anywhere historical weather data are available. This model is developed and discussed within this paper as well as compared to experimental results.

  11. Semi-mechanistic Model Applied to the Search for Economically Optimal Conditions and Blending of Gasoline Feedstock for Steam-cracking Process

    Directory of Open Access Journals (Sweden)

    Karaba Adam

    2016-01-01

    Full Text Available Steam-cracking is energetically intensive large-scaled process which transforms a wide range of hydrocarbons feedstock to petrochemical products. The dependence of products yields on feedstock composition and reaction conditions has been successfully described by mathematical models which are very useful tools for the optimization of cracker operation. Remaining problem is to formulate objective function for such an optimization. Quantitative criterion based on the process economy is proposed in this paper. Previously developed and verified industrial steam-cracking semi-mechanistic model is utilized as supporting tool for economic evaluation of selected gasoline feedstock. Economic criterion is established as the difference between value of products obtained by cracking of studied feedstock under given conditions and the value of products obtained by cracking of reference feedstock under reference conditions. As an example of method utilization, optimal reaction conditions were searched for each of selected feedstock. Potential benefit of individual cracking and cracking of grouped feedstocks in the contrast to cracking under the middle of optimums is evaluated and also compared to cracking under usual conditions.

  12. A Mechanistic Reliability Assessment of RVACS and Metal Fuel Inherent Reactivity Feedbacks

    Energy Technology Data Exchange (ETDEWEB)

    Grabaskas, David; Brunett, Acacia J.; Passerini, Stefano; Grelle, Austin

    2017-09-24

    GE Hitachi Nuclear Energy (GEH) and Argonne National Laboratory (Argonne) participated in a two year collaboration to modernize and update the probabilistic risk assessment (PRA) for the PRISM sodium fast reactor. At a high level, the primary outcome of the project was the development of a next-generation PRA that is intended to enable risk-informed prioritization of safety- and reliability-focused research and development. A central Argonne task during this project was a reliability assessment of passive safety systems, which included the Reactor Vessel Auxiliary Cooling System (RVACS) and the inherent reactivity feedbacks of the metal fuel core. Both systems were examined utilizing a methodology derived from the Reliability Method for Passive Safety Functions (RMPS), with an emphasis on developing success criteria based on mechanistic system modeling while also maintaining consistency with the Fuel Damage Categories (FDCs) of the mechanistic source term assessment. This paper provides an overview of the reliability analyses of both systems, including highlights of the FMEAs, the construction of best-estimate models, uncertain parameter screening and propagation, and the quantification of system failure probability. In particular, special focus is given to the methodologies to perform the analysis of uncertainty propagation and the determination of the likelihood of violating FDC limits. Additionally, important lessons learned are also reviewed, such as optimal sampling methodologies for the discovery of low likelihood failure events and strategies for the combined treatment of aleatory and epistemic uncertainties.

  13. Petroacoustic Modelling of Heterolithic Sandstone Reservoirs: A Novel Approach to Gassmann Modelling Incorporating Sedimentological Constraints and NMR Porosity data

    Science.gov (United States)

    Matthews, S.; Lovell, M.; Davies, S. J.; Pritchard, T.; Sirju, C.; Abdelkarim, A.

    2012-12-01

    Heterolithic or 'shaly' sandstone reservoirs constitute a significant proportion of hydrocarbon resources. Petroacoustic models (a combination of petrophysics and rock physics) enhance the ability to extract reservoir properties from seismic data, providing a connection between seismic and fine-scale rock properties. By incorporating sedimentological observations these models can be better constrained and improved. Petroacoustic modelling is complicated by the unpredictable effects of clay minerals and clay-sized particles on geophysical properties. Such effects are responsible for erroneous results when models developed for "clean" reservoirs - such as Gassmann's equation (Gassmann, 1951) - are applied to heterolithic sandstone reservoirs. Gassmann's equation is arguably the most popular petroacoustic modelling technique in the hydrocarbon industry and is used to model elastic effects of changing reservoir fluid saturations. Successful implementation of Gassmann's equation requires well-constrained drained rock frame properties, which in heterolithic sandstones are heavily influenced by reservoir sedimentology, particularly clay distribution. The prevalent approach to categorising clay distribution is based on the Thomas - Stieber model (Thomas & Stieber, 1975), this approach is inconsistent with current understanding of 'shaly sand' sedimentology and omits properties such as sorting and grain size. The novel approach presented here demonstrates that characterising reservoir sedimentology constitutes an important modelling phase. As well as incorporating sedimentological constraints, this novel approach also aims to improve drained frame moduli estimates through more careful consideration of Gassmann's model assumptions and limitations. A key assumption of Gassmann's equation is a pore space in total communication with movable fluids. This assumption is often violated by conventional applications in heterolithic sandstone reservoirs where effective porosity, which

  14. A realistic closed-form radiobiological model of clinical tumor-control data incorporating intertumor heterogeneity

    International Nuclear Information System (INIS)

    Roberts, Stephen A.; Hendry, Jolyon H.

    1998-01-01

    Purpose: To investigate the role of intertumor heterogeneity in clinical tumor control datasets and the relationship to in vitro measurements of tumor biopsy samples. Specifically, to develop a modified linear-quadratic (LQ) model incorporating such heterogeneity that it is practical to fit to clinical tumor-control datasets. Methods and Materials: We developed a modified version of the linear-quadratic (LQ) model for tumor control, incorporating a (lagged) time factor to allow for tumor cell repopulation. We explicitly took into account the interpatient heterogeneity in clonogen number, radiosensitivity, and repopulation rate. Using this model, we could generate realistic TCP curves using parameter estimates consistent with those reported from in vitro studies, subject to the inclusion of a radiosensitivity (or dose)-modifying factor. We then demonstrated that the model was dominated by the heterogeneity in α (tumor radiosensitivity) and derived an approximate simplified model incorporating this heterogeneity. This simplified model is expressible in a compact closed form, which it is practical to fit to clinical datasets. Using two previously analysed datasets, we fit the model using direct maximum-likelihood techniques and obtained parameter estimates that were, again, consistent with the experimental data on the radiosensitivity of primary human tumor cells. This heterogeneity model includes the same number of adjustable parameters as the standard LQ model. Results: The modified model provides parameter estimates that can easily be reconciled with the in vitro measurements. The simplified (approximate) form of the heterogeneity model is a compact, closed-form probit function that can readily be fitted to clinical series by conventional maximum-likelihood methodology. This heterogeneity model provides a slightly better fit to the datasets than the conventional LQ model, with the same numbers of fitted parameters. The parameter estimates of the clinically

  15. In Silico Oncology: Quantification of the In Vivo Antitumor Efficacy of Cisplatin-Based Doublet Therapy in Non-Small Cell Lung Cancer (NSCLC through a Multiscale Mechanistic Model.

    Directory of Open Access Journals (Sweden)

    Eleni Kolokotroni

    2016-09-01

    Full Text Available The 5-year survival of non-small cell lung cancer patients can be as low as 1% in advanced stages. For patients with resectable disease, the successful choice of preoperative chemotherapy is critical to eliminate micrometastasis and improve operability. In silico experimentations can suggest the optimal treatment protocol for each patient based on their own multiscale data. A determinant for reliable predictions is the a priori estimation of the drugs' cytotoxic efficacy on cancer cells for a given treatment. In the present work a mechanistic model of cancer response to treatment is applied for the estimation of a plausible value range of the cell killing efficacy of various cisplatin-based doublet regimens. Among others, the model incorporates the cancer related mechanism of uncontrolled proliferation, population heterogeneity, hypoxia and treatment resistance. The methodology is based on the provision of tumor volumetric data at two time points, before and after or during treatment. It takes into account the effect of tumor microenvironment and cell repopulation on treatment outcome. A thorough sensitivity analysis based on one-factor-at-a-time and latin hypercube sampling/partial rank correlation coefficient approaches has established the volume growth rate and the growth fraction at diagnosis as key features for more accurate estimates. The methodology is applied on the retrospective data of thirteen patients with non-small cell lung cancer who received cisplatin in combination with gemcitabine, vinorelbine or docetaxel in the neoadjuvant context. The selection of model input values has been guided by a comprehensive literature survey on cancer-specific proliferation kinetics. The latin hypercube sampling has been recruited to compensate for patient-specific uncertainties. Concluding, the present work provides a quantitative framework for the estimation of the in-vivo cell-killing ability of various chemotherapies. Correlation studies of

  16. Comparative approaches from empirical to mechanistic simulation modelling in Land Evaluation studies

    Science.gov (United States)

    Manna, P.; Basile, A.; Bonfante, A.; Terribile, F.

    2009-04-01

    The Land Evaluation (LE) comprise the evaluation procedures to asses the attitudes of the land to a generic or specific use (e.g. biomass production). From local to regional and national scale the approach to the land use planning should requires a deep knowledge of the processes that drive the functioning of the soil-plant-atmosphere system. According to the classical approaches the assessment of attitudes is the result of a qualitative comparison between the land/soil physical properties and the land use requirements. These approaches have a quick and inexpensive applicability; however, they are based on empirical and qualitative models with a basic knowledge structure specifically built for a specific landscape and for the specific object of the evaluation (e.g. crop). The outcome from this situation is the huge difficulties in the spatial extrapolation of the LE results and the rigidity of the system. Modern techniques instead, rely on the application of mechanistic and quantitative simulation modelling that allow a dynamic characterisation of the interrelated physical and chemical processes taking place in the soil landscape. Moreover, the insertion of physical based rules in the LE procedure may make it less difficult in terms of both extending spatially the results and changing the object (e.g. crop species, nitrate dynamics, etc.) of the evaluation. On the other side these modern approaches require high quality and quantity of input data that cause a significant increase in costs. In this scenario nowadays the LE expert is asked to choose the best LE methodology considering costs, complexity of the procedure and benefits in handling a specific land evaluation. In this work we performed a forage maize land suitability study by comparing 9 different methods having increasing complexity and costs. The study area, of about 2000 ha, is located in North Italy in the Lodi plain (Po valley). The range of the 9 employed methods ranged from standard LE approaches to

  17. Development and application of a mechanistic model to estimate emission of nitrous oxide from UK agriculture

    International Nuclear Information System (INIS)

    Brown, L.; Jarvis, S.C.; Syed, B.; Goulding, K.W.T.; Li, C.

    2002-01-01

    A mechanistic model of N 2 O emission from agricultural soil (DeNitrification-DeComposition - DNDC) was modified for application to the UK, and was used as the basis of an inventory of N 2 O emission from UK agriculture in 1990. UK-specific input data were added to DNDC's database and the ability to simulate daily C and N inputs from grazing animals and applied animal waste was added to the model. The UK version of the model, UK-DNDC, simulated emissions from 18 different crop types on the 3 areally dominant soils in each county. Validation of the model at the field scale showed that predictions matched observations well. Emission factors for the inventory were calculated from estimates of N 2 O emission from UK-DNDC, in order to maintain direct comparability with the IPCC approach. These, along with activity data, were included in a transparent spreadsheet format. Using UK-DNDC, the estimate of N 2 O-N emission from UK current agricultural practice in 1990 was 50.9Gg. This total comprised 31.7Gg from the soil sector, 5.9Gg from animals and 13.2Gg from the indirect sector. The range of this estimate (using the range of soil organic C for each soil used) was 30.5-62.5Gg N. Estimates of emissions in each sector were compared to those calculated using the IPCC default methodology. Emissions from the soil and indirect sectors were smaller with the UK-DNDC approach than with the IPCC methodology, while emissions from the animal sector were larger. The model runs suggested a relatively large emission from agricultural land that was not attributable to current agricultural practices (33.8Gg in total, 27.4Gg from the soil sector). This 'background' component is partly the result of historical agricultural land use. It is not normally included in inventories of emission, but would increase the total emission of N 2 O-N from agricultural land in 1990 to 78.3Gg. (Author)

  18. Development and application of a mechanistic model to estimate emission of nitrous oxide from UK agriculture

    Energy Technology Data Exchange (ETDEWEB)

    Brown, L.; Jarvis, S.C. [Institute of Grassland and Environmental Research, Okehampton (United Kingdom); Syed, B. [Cranfield Univ., Silsoe (United Kingdom). Soil Survey and Land Research Centre; Sneath, R.W.; Phillips, V.R. [Silsoe Research Inst. (United Kingdom); Goulding, K.W.T. [Institute of Arable Crops Research, Rothamsted (United Kingdom); Li, C. [University of New Hampshire (United States). Inst. for the Study of Earth, Oceans and Space

    2002-07-01

    A mechanistic model of N{sub 2}O emission from agricultural soil (DeNitrification-DeComposition - DNDC) was modified for application to the UK, and was used as the basis of an inventory of N{sub 2}O emission from UK agriculture in 1990. UK-specific input data were added to DNDC's database and the ability to simulate daily C and N inputs from grazing animals and applied animal waste was added to the model. The UK version of the model, UK-DNDC, simulated emissions from 18 different crop types on the 3 areally dominant soils in each county. Validation of the model at the field scale showed that predictions matched observations well. Emission factors for the inventory were calculated from estimates of N{sub 2}O emission from UK-DNDC, in order to maintain direct comparability with the IPCC approach. These, along with activity data, were included in a transparent spreadsheet format. Using UK-DNDC, the estimate of N{sub 2}O-N emission from UK current agricultural practice in 1990 was 50.9Gg. This total comprised 31.7Gg from the soil sector, 5.9Gg from animals and 13.2Gg from the indirect sector. The range of this estimate (using the range of soil organic C for each soil used) was 30.5-62.5Gg N. Estimates of emissions in each sector were compared to those calculated using the IPCC default methodology. Emissions from the soil and indirect sectors were smaller with the UK-DNDC approach than with the IPCC methodology, while emissions from the animal sector were larger. The model runs suggested a relatively large emission from agricultural land that was not attributable to current agricultural practices (33.8Gg in total, 27.4Gg from the soil sector). This 'background' component is partly the result of historical agricultural land use. It is not normally included in inventories of emission, but would increase the total emission of N{sub 2}O-N from agricultural land in 1990 to 78.3Gg. (Author)

  19. Development and application of a mechanistic model to estimate emission of nitrous oxide from UK agriculture

    Science.gov (United States)

    Brown, L.; Syed, B.; Jarvis, S. C.; Sneath, R. W.; Phillips, V. R.; Goulding, K. W. T.; Li, C.

    A mechanistic model of N 2O emission from agricultural soil (DeNitrification-DeComposition—DNDC) was modified for application to the UK, and was used as the basis of an inventory of N 2O emission from UK agriculture in 1990. UK-specific input data were added to DNDC's database and the ability to simulate daily C and N inputs from grazing animals and applied animal waste was added to the model. The UK version of the model, UK-DNDC, simulated emissions from 18 different crop types on the 3 areally dominant soils in each county. Validation of the model at the field scale showed that predictions matched observations well. Emission factors for the inventory were calculated from estimates of N 2O emission from UK-DNDC, in order to maintain direct comparability with the IPCC approach. These, along with activity data, were included in a transparent spreadsheet format. Using UK-DNDC, the estimate of N 2O-N emission from UK current agricultural practice in 1990 was 50.9 Gg. This total comprised 31.7 Gg from the soil sector, 5.9 Gg from animals and 13.2 Gg from the indirect sector. The range of this estimate (using the range of soil organic C for each soil used) was 30.5-62.5 Gg N. Estimates of emissions in each sector were compared to those calculated using the IPCC default methodology. Emissions from the soil and indirect sectors were smaller with the UK-DNDC approach than with the IPCC methodology, while emissions from the animal sector were larger. The model runs suggested a relatively large emission from agricultural land that was not attributable to current agricultural practices (33.8 Gg in total, 27.4 Gg from the soil sector). This 'background' component is partly the result of historical agricultural land use. It is not normally included in inventories of emission, but would increase the total emission of N 2O-N from agricultural land in 1990 to 78.3 Gg.

  20. Incorporation of human factors into ship collision risk models focusing on human centred design aspects

    International Nuclear Information System (INIS)

    Sotiralis, P.; Ventikos, N.P.; Hamann, R.; Golyshev, P.; Teixeira, A.P.

    2016-01-01

    This paper presents an approach that more adequately incorporates human factor considerations into quantitative risk analysis of ship operation. The focus is on the collision accident category, which is one of the main risk contributors in ship operation. The approach is based on the development of a Bayesian Network (BN) model that integrates elements from the Technique for Retrospective and Predictive Analysis of Cognitive Errors (TRACEr) and focuses on the calculation of the collision accident probability due to human error. The model takes into account the human performance in normal, abnormal and critical operational conditions and implements specific tasks derived from the analysis of the task errors leading to the collision accident category. A sensitivity analysis is performed to identify the most important contributors to human performance and ship collision. Finally, the model developed is applied to assess the collision risk of a feeder operating in Dover strait using the collision probability estimated by the developed BN model and an Event tree model for calculation of human, economic and environmental risks. - Highlights: • A collision risk model for the incorporation of human factors into quantitative risk analysis is proposed. • The model takes into account the human performance in different operational conditions leading to the collision. • The most important contributors to human performance and ship collision are identified. • The model developed is applied to assess the collision risk of a feeder operating in Dover strait.

  1. Simulation and mechanistic investigation of the arrhythmogenic role of the late sodium current in human heart failure.

    Directory of Open Access Journals (Sweden)

    Beatriz Trenor

    Full Text Available Heart failure constitutes a major public health problem worldwide. The electrophysiological remodeling of failing hearts sets the stage for malignant arrhythmias, in which the role of the late Na(+ current (I(NaL is relevant and is currently under investigation. In this study we examined the role of I(NaL in the electrophysiological phenotype of ventricular myocytes, and its proarrhythmic effects in the failing heart. A model for cellular heart failure was proposed using a modified version of Grandi et al. model for human ventricular action potential that incorporates the formulation of I(NaL. A sensitivity analysis of the model was performed and simulations of the pathological electrical activity of the cell were conducted. The proposed model for the human I(NaL and the electrophysiological remodeling of myocytes from failing hearts accurately reproduce experimental observations. The sensitivity analysis of the modulation of electrophysiological parameters of myocytes from failing hearts due to ion channels remodeling, revealed a role for I(NaL in the prolongation of action potential duration (APD, triangulation of the shape of the AP, and changes in Ca(2+ transient. A mechanistic investigation of intracellular Na(+ accumulation and APD shortening with increasing frequency of stimulation of failing myocytes revealed a role for the Na(+/K(+ pump, the Na(+/Ca(2+ exchanger and I(NaL. The results of the simulations also showed that in failing myocytes, the enhancement of I(NaL increased the reverse rate-dependent APD prolongation and the probability of initiating early afterdepolarizations. The electrophysiological remodeling of failing hearts and especially the enhancement of the I(NaL prolong APD and alter Ca(2+ transient facilitating the development of early afterdepolarizations. An enhanced I(NaL appears to be an important contributor to the electrophysiological phenotype and to the dysregulation of [Ca(2+](i homeostasis of failing myocytes.

  2. Incorporating genetic variation into a model of budburst phenology of coast Douglas-fir (Pseudotsuga menziesii var

    Science.gov (United States)

    Peter J. Gould; Constance A. Harrington; Bradley J. St Clair

    2011-01-01

    Models to predict budburst and other phenological events in plants are needed to forecast how climate change may impact ecosystems and for the development of mitigation strategies. Differences among genotypes are important to predicting phenological events in species that show strong clinal variation in adaptive traits. We present a model that incorporates the effects...

  3. A mechanistic model of an upper bound on oceanic carbon export as a function of mixed layer depth and temperature

    Directory of Open Access Journals (Sweden)

    Z. Li

    2017-11-01

    Full Text Available Export production reflects the amount of organic matter transferred from the ocean surface to depth through biological processes. This export is in large part controlled by nutrient and light availability, which are conditioned by mixed layer depth (MLD. In this study, building on Sverdrup's critical depth hypothesis, we derive a mechanistic model of an upper bound on carbon export based on the metabolic balance between photosynthesis and respiration as a function of MLD and temperature. We find that the upper bound is a positively skewed bell-shaped function of MLD. Specifically, the upper bound increases with deepening mixed layers down to a critical depth, beyond which a long tail of decreasing carbon export is associated with increasing heterotrophic activity and decreasing light availability. We also show that in cold regions the upper bound on carbon export decreases with increasing temperature when mixed layers are deep, but increases with temperature when mixed layers are shallow. A meta-analysis shows that our model envelopes field estimates of carbon export from the mixed layer. When compared to satellite export production estimates, our model indicates that export production in some regions of the Southern Ocean, particularly the subantarctic zone, is likely limited by light for a significant portion of the growing season.

  4. Global dynamics of a PDE model for aedes aegypti mosquitoe incorporating female sexual preference

    KAUST Repository

    Parshad, Rana

    2011-01-01

    In this paper we study the long time dynamics of a reaction diffusion system, describing the spread of Aedes aegypti mosquitoes, which are the primary cause of dengue infection. The system incorporates a control attempt via the sterile insect technique. The model incorporates female mosquitoes sexual preference for wild males over sterile males. We show global existence of strong solution for the system. We then derive uniform estimates to prove the existence of a global attractor in L-2(Omega), for the system. The attractor is shown to be L-infinity(Omega) regular and posess state of extinction, if the injection of sterile males is large enough. We also provide upper bounds on the Hausdorff and fractal dimensions of the attractor.

  5. Modelling and Simulation of a Manipulator with Stable Viscoelastic Grasping Incorporating Friction

    Directory of Open Access Journals (Sweden)

    A. Khurshid

    2016-12-01

    Full Text Available Design, dynamics and control of a humanoid robotic hand based on anthropological dimensions, with joint friction, is modelled, simulated and analysed in this paper by using computer aided design and multibody dynamic simulation. Combined joint friction model is incorporated in the joints. Experimental values of coefficient of friction of grease lubricated sliding contacts representative of manipulator joints are presented. Human fingers deform to the shape of the grasped object (enveloping grasp at the area of interaction. A mass-spring-damper model of the grasp is developed. The interaction of the viscoelastic gripper of the arm with objects is analysed by using Bond Graph modelling method. Simulations were conducted for several material parameters. These results of the simulation are then used to develop a prototype of the proposed gripper. Bond graph model is experimentally validated by using the prototype. The gripper is used to successfully transport soft and fragile objects. This paper provides information on optimisation of friction and its inclusion in both dynamic modelling and simulation to enhance mechanical efficiency.

  6. Incorporating NDVI in a gravity model setting to describe spatio-temporal patterns of Lyme borreliosis incidence

    Science.gov (United States)

    Barrios, J. M.; Verstraeten, W. W.; Farifteh, J.; Maes, P.; Aerts, J. M.; Coppin, P.

    2012-04-01

    Lyme borreliosis (LB) is the most common tick-borne disease in Europe and incidence growth has been reported in several European countries during the last decade. LB is caused by the bacterium Borrelia burgdorferi and the main vector of this pathogen in Europe is the tick Ixodes ricinus. LB incidence and spatial spread is greatly dependent on environmental conditions impacting habitat, demography and trophic interactions of ticks and the wide range of organisms ticks parasite. The landscape configuration is also a major determinant of tick habitat conditions and -very important- of the fashion and intensity of human interaction with vegetated areas, i.e. human exposure to the pathogen. Hence, spatial notions as distance and adjacency between urban and vegetated environments are related to human exposure to tick bites and, thus, to risk. This work tested the adequacy of a gravity model setting to model the observed spatio-temporal pattern of LB as a function of location and size of urban and vegetated areas and the seasonal and annual change in the vegetation dynamics as expressed by MODIS NDVI. Opting for this approach implies an analogy with Newton's law of universal gravitation in which the attraction forces between two bodies are directly proportional to the bodies mass and inversely proportional to distance. Similar implementations have proven useful in fields like trade modeling, health care service planning, disease mapping among other. In our implementation, the size of human settlements and vegetated systems and the distance separating these landscape elements are considered the 'bodies'; and the 'attraction' between them is an indicator of exposure to pathogen. A novel element of this implementation is the incorporation of NDVI to account for the seasonal and annual variation in risk. The importance of incorporating this indicator of vegetation activity resides in the fact that alterations of LB incidence pattern observed the last decade have been ascribed

  7. Benefits of incorporating spatial organisation of catchments for a semi-distributed hydrological model

    Science.gov (United States)

    Schumann, Andreas; Oppel, Henning

    2017-04-01

    To represent the hydrological behaviour of catchments a model should reproduce/reflect the hydrologically most relevant catchment characteristics. These are heterogeneously distributed within a watershed but often interrelated and subject of a certain spatial organisation. Since common models are mostly based on fundamental assumptions about hydrological processes, the reduction of variance of catchment properties as well as the incorporation of the spatial organisation of the catchment is desirable. We have developed a method that combines the idea of the width-function used for determination of the geomorphologic unit hydrograph with information about soil or topography. With this method we are able to assess the spatial organisation of selected catchment characteristics. An algorithm was developed that structures a watershed into sub-basins and other spatial units to minimise its heterogeneity. The outcomes of this algorithm are used for the spatial setup of a semi-distributed model. Since the spatial organisation of a catchment is not bound to a single characteristic, we have to embed information of multiple catchment properties. For this purpose we applied a fuzzy-based method to combine the spatial setup for multiple single characteristics into a union, optimal spatial differentiation. Utilizing this method, we are able to propose a spatial structure for a semi-distributed hydrological model, comprising the definition of sub-basins and a zonal classification within each sub-basin. Besides the improved spatial structuring, the performed analysis ameliorates modelling in another way. The spatial variability of catchment characteristics, which is considered by a minimum of heterogeneity in the zones, can be considered in a parameter constrained calibration scheme in a case study both options were used to explore the benefits of incorporating the spatial organisation and derived parameter constraints for the parametrisation of a HBV-96 model. We use two benchmark

  8. A watershed modeling approach to streamflow reconstruction from tree-ring records

    International Nuclear Information System (INIS)

    Saito, Laurel; Biondi, Franco; Salas, Jose D; Panorska, Anna K; Kozubowski, Tomasz J

    2008-01-01

    Insight into long-term changes of streamflow is critical for addressing implications of global warming for sustainable water management. To date, dendrohydrologists have employed sophisticated regression techniques to extend runoff records, but this empirical approach cannot directly test the influence of watershed factors that alter streamflow independently of climate. We designed a mechanistic watershed model to calculate streamflows at annual timescales using as few inputs as possible. The model was calibrated for upper reaches of the Walker River, which straddles the boundary between the Sierra Nevada of California and the Great Basin of Nevada. Even though the model incorporated simplified relationships between precipitation and other components of the hydrologic cycle, it predicted water year streamflows with correlations of 0.87 when appropriate precipitation values were used

  9. Recent Progresses in Incorporating Human Land-Water Management into Global Land Surface Models Toward Their Integration into Earth System Models

    Science.gov (United States)

    Pokhrel, Yadu N.; Hanasaki, Naota; Wada, Yoshihide; Kim, Hyungjun

    2016-01-01

    The global water cycle has been profoundly affected by human land-water management. As the changes in the water cycle on land can affect the functioning of a wide range of biophysical and biogeochemical processes of the Earth system, it is essential to represent human land-water management in Earth system models (ESMs). During the recent past, noteworthy progress has been made in large-scale modeling of human impacts on the water cycle but sufficient advancements have not yet been made in integrating the newly developed schemes into ESMs. This study reviews the progresses made in incorporating human factors in large-scale hydrological models and their integration into ESMs. The study focuses primarily on the recent advancements and existing challenges in incorporating human impacts in global land surface models (LSMs) as a way forward to the development of ESMs with humans as integral components, but a brief review of global hydrological models (GHMs) is also provided. The study begins with the general overview of human impacts on the water cycle. Then, the algorithms currently employed to represent irrigation, reservoir operation, and groundwater pumping are discussed. Next, methodological deficiencies in current modeling approaches and existing challenges are identified. Furthermore, light is shed on the sources of uncertainties associated with model parameterizations, grid resolution, and datasets used for forcing and validation. Finally, representing human land-water management in LSMs is highlighted as an important research direction toward developing integrated models using ESM frameworks for the holistic study of human-water interactions within the Earths system.

  10. Using expert knowledge to incorporate uncertainty in cause-of-death assignments for modeling of cause-specific mortality

    Science.gov (United States)

    Walsh, Daniel P.; Norton, Andrew S.; Storm, Daniel J.; Van Deelen, Timothy R.; Heisy, Dennis M.

    2018-01-01

    Implicit and explicit use of expert knowledge to inform ecological analyses is becoming increasingly common because it often represents the sole source of information in many circumstances. Thus, there is a need to develop statistical methods that explicitly incorporate expert knowledge, and can successfully leverage this information while properly accounting for associated uncertainty during analysis. Studies of cause-specific mortality provide an example of implicit use of expert knowledge when causes-of-death are uncertain and assigned based on the observer's knowledge of the most likely cause. To explicitly incorporate this use of expert knowledge and the associated uncertainty, we developed a statistical model for estimating cause-specific mortality using a data augmentation approach within a Bayesian hierarchical framework. Specifically, for each mortality event, we elicited the observer's belief of cause-of-death by having them specify the probability that the death was due to each potential cause. These probabilities were then used as prior predictive values within our framework. This hierarchical framework permitted a simple and rigorous estimation method that was easily modified to include covariate effects and regularizing terms. Although applied to survival analysis, this method can be extended to any event-time analysis with multiple event types, for which there is uncertainty regarding the true outcome. We conducted simulations to determine how our framework compared to traditional approaches that use expert knowledge implicitly and assume that cause-of-death is specified accurately. Simulation results supported the inclusion of observer uncertainty in cause-of-death assignment in modeling of cause-specific mortality to improve model performance and inference. Finally, we applied the statistical model we developed and a traditional method to cause-specific survival data for white-tailed deer, and compared results. We demonstrate that model selection

  11. Development and evaluation of a dimensionless mechanistic pan coating model for the prediction of coated tablet appearance.

    Science.gov (United States)

    Niblett, Daniel; Porter, Stuart; Reynolds, Gavin; Morgan, Tomos; Greenamoyer, Jennifer; Hach, Ronald; Sido, Stephanie; Karan, Kapish; Gabbott, Ian

    2017-08-07

    A mathematical, mechanistic tablet film-coating model has been developed for pharmaceutical pan coating systems based on the mechanisms of atomisation, tablet bed movement and droplet drying with the main purpose of predicting tablet appearance quality. Two dimensionless quantities were used to characterise the product properties and operating parameters: the dimensionless Spray Flux (relating to area coverage of the spray droplets) and the Niblett Number (relating to the time available for drying of coating droplets). The Niblett Number is the ratio between the time a droplet needs to dry under given thermodynamic conditions and the time available for the droplet while on the surface of the tablet bed. The time available for drying on the tablet bed surface is critical for appearance quality. These two dimensionless quantities were used to select process parameters for a set of 22 coating experiments, performed over a wide range of multivariate process parameters. The dimensionless Regime Map created can be used to visualise the effect of interacting process parameters on overall tablet appearance quality and defects such as picking and logo bridging. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Projected Climate Impacts to South African Maize and Wheat Production in 2055: A Comparison of Empirical and Mechanistic Modeling Approaches

    Science.gov (United States)

    Estes, Lyndon D.; Beukes, Hein; Bradley, Bethany A.; Debats, Stephanie R.; Oppenheimer, Michael; Ruane, Alex C.; Schulze, Roland; Tadross, Mark

    2013-01-01

    Crop model-specific biases are a key uncertainty affecting our understanding of climate change impacts to agriculture. There is increasing research focus on intermodel variation, but comparisons between mechanistic (MMs) and empirical models (EMs) are rare despite both being used widely in this field. We combined MMs and EMs to project future (2055) changes in the potential distribution (suitability) and productivity of maize and spring wheat in South Africa under 18 downscaled climate scenarios (9 models run under 2 emissions scenarios). EMs projected larger yield losses or smaller gains than MMs. The EMs' median-projected maize and wheat yield changes were 3.6% and 6.2%, respectively, compared to 6.5% and 15.2% for the MM. The EM projected a 10% reduction in the potential maize growing area, where the MM projected a 9% gain. Both models showed increases in the potential spring wheat production region (EM = 48%, MM = 20%), but these results were more equivocal because both models (particularly the EM) substantially overestimated the extent of current suitability. The substantial water-use efficiency gains simulated by the MMs under elevated CO2 accounted for much of the EMMM difference, but EMs may have more accurately represented crop temperature sensitivities. Our results align with earlier studies showing that EMs may show larger climate change losses than MMs. Crop forecasting efforts should expand to include EMMM comparisons to provide a fuller picture of crop-climate response uncertainties.

  13. Mathematical modeling of drug release from lipid dosage forms.

    Science.gov (United States)

    Siepmann, J; Siepmann, F

    2011-10-10

    Lipid dosage forms provide an interesting potential for controlled drug delivery. In contrast to frequently used poly(ester) based devices for parenteral administration, they do not lead to acidification upon degradation and potential drug inactivation, especially in the case of protein drugs and other acid-labile active agents. The aim of this article is to give an overview on the current state of the art of mathematical modeling of drug release from this type of advanced drug delivery systems. Empirical and semi-empirical models are described as well as mechanistic theories, considering diffusional mass transport, potentially limited drug solubility and the leaching of other, water-soluble excipients into the surrounding bulk fluid. Various practical examples are given, including lipid microparticles, beads and implants, which can successfully be used to control the release of an incorporated drug during periods ranging from a few hours up to several years. The great benefit of mechanistic mathematical theories is the possibility to quantitatively predict the effects of different formulation parameters and device dimensions on the resulting drug release kinetics. Thus, in silico simulations can significantly speed up product optimization. This is particularly useful if long release periods (e.g., several months) are targeted, since experimental trial-and-error studies are highly time-consuming in these cases. In the future it would be highly desirable to combine mechanistic theories with the quantitative description of the drug fate in vivo, ideally including the pharmacodynamic efficacy of the treatments. Copyright © 2011 Elsevier B.V. All rights reserved.

  14. Analysis of PWR control rod ejection accident with the coupled code system SKETCH-INS/TRACE by incorporating pin power reconstruction model

    International Nuclear Information System (INIS)

    Nakajima, T.; Sakai, T.

    2010-01-01

    The pin power reconstruction model was incorporated in the 3-D nodal kinetics code SKETCH-INS in order to produce accurate calculation of three-dimensional pin power distributions throughout the reactor core. In order to verify the employed pin power reconstruction model, the PWR MOX/UO_2 core transient benchmark problem was analyzed with the coupled code system SKETCH-INS/TRACE by incorporating the model and the influence of pin power reconstruction model was studied. SKETCH-INS pin power distributions for 3 benchmark problems were compared with the PARCS solutions which were provided by the host organisation of the benchmark. SKETCH-INS results were in good agreement with the PARCS results. The capability of employed pin power reconstruction model was confirmed through the analysis of benchmark problems. A PWR control rod ejection benchmark problem was analyzed with the coupled code system SKETCH-INS/ TRACE by incorporating the pin power reconstruction model. The influence of pin power reconstruction model was studied by comparing with the result of conventional node averaged flux model. The results indicate that the pin power reconstruction model has significant effect on the pin powers during transient and hence on the fuel enthalpy

  15. Towards a functional model of mental disorders incorporating the laws of thermodynamics.

    Science.gov (United States)

    Murray, George C; McKenzie, Karen

    2013-05-01

    The current paper presents the hypothesis that the understanding of mental disorders can be advanced by incorporating the laws of thermodynamics, specifically relating to energy conservation and energy transfer. These ideas, along with the introduction of the notion that entropic activities are symptomatic of inefficient energy transfer or disorder, were used to propose a model of understanding mental ill health as resulting from the interaction of entropy, capacity and work (environmental demands). The model was applied to Attention Deficit Hyperactivity Disorder, and was shown to be compatible with current thinking about this condition, as well as emerging models of mental disorders as complex networks. A key implication of the proposed model is that it argues that all mental disorders require a systemic functional approach, with the advantage that it offers a number of routes into the assessment, formulation and treatment for mental health problems. Copyright © 2013 Elsevier Ltd. All rights reserved.

  16. Incorporation of Markov reliability models for digital instrumentation and control systems into existing PRAs

    International Nuclear Information System (INIS)

    Bucci, P.; Mangan, L. A.; Kirschenbaum, J.; Mandelli, D.; Aldemir, T.; Arndt, S. A.

    2006-01-01

    Markov models have the ability to capture the statistical dependence between failure events that can arise in the presence of complex dynamic interactions between components of digital instrumentation and control systems. One obstacle to the use of such models in an existing probabilistic risk assessment (PRA) is that most of the currently available PRA software is based on the static event-tree/fault-tree methodology which often cannot represent such interactions. We present an approach to the integration of Markov reliability models into existing PRAs by describing the Markov model of a digital steam generator feedwater level control system, how dynamic event trees (DETs) can be generated from the model, and how the DETs can be incorporated into an existing PRA with the SAPHIRE software. (authors)

  17. Assessment of models for steam release from concrete and implications for modeling corium behavior in reactor cavities

    International Nuclear Information System (INIS)

    Washington, K.E.; Carroll, D.E.

    1988-01-01

    Models for concrete outgassing have been developed and incorporated into a developmental version of the CONTAIN code for the assessment of corium behavior in reactor cavities. The resultant code, referred to as CONTAIN/OR in order to distinguish it from the released version of CONTAIN, has the capability to model transient heat conduction and concrete outgassing in core-concrete interaction problems. This study focused on validation and assessment of the outgassing model through comparisons with other concrete response codes. In general, the model is not mechanistic; however, there are certain important processes and feedback effects that are treated rigorously. The CONTAIN outgassing model was compared against two mechanistic concrete response codes (USINT and SLAM). Gas release and temperature profile predictions for several concrete thicknesses and heating rates were performed with acceptable agreement seen in each case. The model was also applied to predict corium behavior in a reactor cavity for a hypothetical severe accident scenario. In this calculation, gases evolving from the concrete during nonablating periods fueled exothermic Zr chemical reactions in the corium. Higher corium temperatures and more concrete ablation were observed when compared with that seen when concrete outgassing was neglected. Even though this result depends somewhat upon the makeup of the corium sources and the concrete type in the cavity, it does show that concrete outgassing can be important in the modeling of corium behavior in reactor cavities. In particular, the need to expand the traditional role of CORCON from steady-state ablation to the consideration of more transient events is clearly evident as a result of this work. 5 refs., 11 figs., 1 tab

  18. A generalized linear-quadratic model incorporating reciprocal time pattern of radiation damage repair

    International Nuclear Information System (INIS)

    Huang, Zhibin; Mayr, Nina A.; Lo, Simon S.; Wang, Jian Z.; Jia Guang; Yuh, William T. C.; Johnke, Roberta

    2012-01-01

    Purpose: It has been conventionally assumed that the repair rate for sublethal damage (SLD) remains constant during the entire radiation course. However, increasing evidence from animal studies suggest that this may not the case. Rather, it appears that the repair rate for radiation-induced SLD slows down with increasing time. Such a slowdown in repair would suggest that the exponential repair pattern would not necessarily accurately predict repair process. As a result, the purpose of this study was to investigate a new generalized linear-quadratic (LQ) model incorporating a repair pattern with reciprocal time. The new formulas were tested with published experimental data. Methods: The LQ model has been widely used in radiation therapy, and the parameter G in the surviving fraction represents the repair process of sublethal damage with T r as the repair half-time. When a reciprocal pattern of repair process was adopted, a closed form of G was derived analytically for arbitrary radiation schemes. The published animal data adopted to test the reciprocal formulas. Results: A generalized LQ model to describe the repair process in a reciprocal pattern was obtained. Subsequently, formulas for special cases were derived from this general form. The reciprocal model showed a better fit to the animal data than the exponential model, particularly for the ED50 data (reduced χ 2 min of 2.0 vs 4.3, p = 0.11 vs 0.006), with the following gLQ parameters: α/β = 2.6-4.8 Gy, T r = 3.2-3.9 h for rat feet skin, and α/β = 0.9 Gy, T r = 1.1 h for rat spinal cord. Conclusions: These results of repair process following a reciprocal time suggest that the generalized LQ model incorporating the reciprocal time of sublethal damage repair shows a better fit than the exponential repair model. These formulas can be used to analyze the experimental and clinical data, where a slowing-down repair process appears during the course of radiation therapy.

  19. Modelling the active site of NiFe hydrogenases: new catalysts for the electro-production of H2 and mechanistic studies

    International Nuclear Information System (INIS)

    Canaguier, S.

    2009-01-01

    NiFe hydrogenases are unique metalloenzymes that catalyze H + /H 2 interconversion with remarkable efficiency close to the thermodynamic potential. Their active site consists of a hetero-bimetallic complex containing a nickel ion in a sulphur-rich environment connected by two thiolate bridges to an organometallic cyano-carbonyl iron moiety. In order to improve the understanding of the enzymatic mechanism and to obtain new base-metal electrocatalysts for H 2 production, we synthesized a series of bio-inspired low molecular weight model complexes with the butterfly structure Ni(μ-S 2 )M (M= Ru, Mn and Fe). All these compounds displayed a catalytic activity of hydrogen production. Modulating the electronic and steric properties of the ruthenium center allowed optimizing the catalytic performances of these compounds in terms of stability, catalytic rate and overpotential. Mechanistic studies of the catalytic cycle of the Ni-Ru complexes have also been carried out. They allowed us to suggest a bio-relevant bridging hydride as the catalytic intermediate. Finally, we synthesized one of the first Ni-Fe complexes that is both a structural and a functional model of NiFe hydrogenase. (author) [fr

  20. In Vitro–In Vivo Correlation for Gliclazide Immediate-Release Tablets Based on Mechanistic Absorption Simulation

    OpenAIRE

    Grbic, Sandra; Parojcic, Jelena; Ibric, Svetlana; Djuric, Zorica

    2010-01-01

    The aim of this study was to develop a drug-specific absorption model for gliclazide (GLK) using mechanistic gastrointestinal simulation technology (GIST) implemented in GastroPlusTM software package. A range of experimentally determined, in silico predicted or literature data were used as input parameters. Experimentally determined pH-solubility profile was used for all simulations. The human jejunum effective permeability (Peff) value was estimated on the basis of in vitro measured Caco-2 p...

  1. Fast Biological Modeling for Voxel-based Heavy Ion Treatment Planning Using the Mechanistic Repair-Misrepair-Fixation Model and Nuclear Fragment Spectra

    Energy Technology Data Exchange (ETDEWEB)

    Kamp, Florian [Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut (United States); Department of Radiation Oncology, Technische Universität München, Klinikum Rechts der Isar, München (Germany); Physik-Department, Technische Universität München, Garching (Germany); Cabal, Gonzalo [Experimental Physics–Medical Physics, Ludwig Maximilians University Munich, Garching (Germany); Mairani, Andrea [Medical Physics Unit, Centro Nazionale Adroterapia Oncologica (CNAO), Pavia (Italy); Heidelberg Ion-Beam Therapy Center, Heidelberg (Germany); Parodi, Katia [Experimental Physics–Medical Physics, Ludwig Maximilians University Munich, Garching (Germany); Wilkens, Jan J. [Department of Radiation Oncology, Technische Universität München, Klinikum Rechts der Isar, München (Germany); Physik-Department, Technische Universität München, Garching (Germany); Carlson, David J., E-mail: david.j.carlson@yale.edu [Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut (United States)

    2015-11-01

    Purpose: The physical and biological differences between heavy ions and photons have not been fully exploited and could improve treatment outcomes. In carbon ion therapy, treatment planning must account for physical properties, such as the absorbed dose and nuclear fragmentation, and for differences in the relative biological effectiveness (RBE) of ions compared with photons. We combined the mechanistic repair-misrepair-fixation (RMF) model with Monte Carlo-generated fragmentation spectra for biological optimization of carbon ion treatment plans. Methods and Materials: Relative changes in double-strand break yields and radiosensitivity parameters with particle type and energy were determined using the independently benchmarked Monte Carlo damage simulation and the RMF model to estimate the RBE values for primary carbon ions and secondary fragments. Depth-dependent energy spectra were generated with the Monte Carlo code FLUKA for clinically relevant initial carbon ion energies. The predicted trends in RBE were compared with the published experimental data. Biological optimization for carbon ions was implemented in a 3-dimensional research treatment planning tool. Results: We compared the RBE and RBE-weighted dose (RWD) distributions of different carbon ion treatment scenarios with and without nuclear fragments. The inclusion of fragments in the simulations led to smaller RBE predictions. A validation of RMF against measured cell survival data reported in published studies showed reasonable agreement. We calculated and optimized the RWD distributions on patient data and compared the RMF predictions with those from other biological models. The RBE values in an astrocytoma tumor ranged from 2.2 to 4.9 (mean 2.8) for a RWD of 3 Gy(RBE) assuming (α/β){sub X} = 2 Gy. Conclusions: These studies provide new information to quantify and assess uncertainties in the clinically relevant RBE values for carbon ion therapy based on biophysical mechanisms. We present results from

  2. Mechanistic approach for the kinetics of the decomposition of nitrous oxide over calcined hydrotalcites

    Energy Technology Data Exchange (ETDEWEB)

    Dandl, H.; Emig, G. [Lehrstuhl fuer Technische Chemie I, Erlangen (Germany)

    1998-03-27

    A highly active catalyst for the decomposition of N{sub 2}O was prepared by the thermal treatment of CoLaAl-hydrotalcite. For this catalyst the reaction rate was determined at various partial pressures of N{sub 2}O, O{sub 2} and H{sub 2}O in a temperature range from 573K to 823K. The kinetic simulation resulted in a mechanistic model. The energies of activation and rate coefficients are estimated for the main steps of the reaction

  3. A mechanistic approach to postirradiation spoilage kinetics of fish

    International Nuclear Information System (INIS)

    Tukenmez, I.

    2004-01-01

    Full text: In order to simulate postirradiation spoilage of fish, the mechanistic aspects of the growth of surviving microorganisms during chill storage and their product formation in irradiated fish were analyzed. Anchovy (Engraulis encrasicholus) samples those unirradiated and irradiated at 1, 2 and 3 kGy doses of gamma radiation were stored at +2 o C for 21 days. Total bacterial counts (TBC) and trimethylamine (TMA) analysis of the samples were done periodically during storage. Depending on the proposed spoilage mechanism, kinetic model equations were derived. By using experimental data of TBC and TMA in the developed model, the postirradiation spoilage parameters including growth rate constant, inital and maximum attainable TBC, lag time and TMA yield were evaluated and microbial spoilage of fish was simulated for postirradiation storage. Shelf life of irradiated fish was estimated depending on the spoilage kinetics. Dose effects on the kinetic parameters were analyzed. It is suggested that the kinetic evaluation method developed in this study may be used for quality assessment, shelf life determination and dose optimization for radiation preservation of fish

  4. DOUBLE-SHELL TANK (DST) HYDROXIDE DEPLETION MODEL FOR CARBON DIOXIDE ABSORPTION

    International Nuclear Information System (INIS)

    OGDEN DM; KIRCH NW

    2007-01-01

    This document generates a supernatant hydroxide ion depletion model based on mechanistic principles. The carbon dioxide absorption mechanistic model is developed in this report. The report also benchmarks the model against historical tank supernatant hydroxide data and vapor space carbon dioxide data. A comparison of the newly generated mechanistic model with previously applied empirical hydroxide depletion equations is also performed

  5. A model for life predictions of nickel-base superalloys in high-temperature low cycle fatigue

    Science.gov (United States)

    Romanoski, Glenn R.; Pelloux, Regis M.; Antolovich, Stephen D.

    1988-01-01

    Extensive characterization of low-cycle fatigue damage mechanisms was performed on polycrystalline Rene 80 and IN100 tested in the temperature range from 871 to 1000 C. Low-cycle fatigue life was found to be dominated by propagation of microcracks to a critical size governed by the maximum tensile stress. A model was developed which incorporates a threshold stress for crack extension, a stress-based crack growth expression, and a failure criterion. The mathematical equivalence between this mechanistically based model and the strain-life low-cycle fatigue law was demonstrated using cyclic stress-strain relationships. The model was shown to correlate the high-temperature low-cycle fatigue data of the different nickel-base superalloys considered in this study.

  6. CONTAIN calculations of direct containment heating in the Surry plant

    International Nuclear Information System (INIS)

    Williams, D.C.; Louie, D.L.Y.

    1988-01-01

    The draft NUREG-1150 risk analysis performed for the Surry plant identified direct containment heating (DCH) as a potentially dominant contributor to the total public risk associated with this plant. At that time, however, detailed mechanistic calculations of DCH loads were unavailable. Subsequently, a series of analyses of DCH scenarios using the CONTAIN-DCH code was performed in order to put the treatment of DCH on a firmer basis in the final draft of NUREG-1150. The present paper describes some of the results obtained for the Surry plant. A developmental model for DCH has been incorporated into CONTAIN code. This model includes mechanistic treatments of reasonably well-understood phenomena (e.g., heat and mass transfer), together with a parametric treatment of poorly understood phenomena for which mechanistic models are unavailable (e.g., debris de-entrainment from the gas stream due to debris-structure interactions). The DCH model was described in an earlier report, but the present version incorporates a number of advances, including treatment of the chemical equilibria involved in the iron-steam reaction

  7. A modified Wright-Fisher model that incorporates Ne: A variant of the standard model with increased biological realism and reduced computational complexity.

    Science.gov (United States)

    Zhao, Lei; Gossmann, Toni I; Waxman, David

    2016-03-21

    The Wright-Fisher model is an important model in evolutionary biology and population genetics. It has been applied in numerous analyses of finite populations with discrete generations. It is recognised that real populations can behave, in some key aspects, as though their size that is not the census size, N, but rather a smaller size, namely the effective population size, Ne. However, in the Wright-Fisher model, there is no distinction between the effective and census population sizes. Equivalently, we can say that in this model, Ne coincides with N. The Wright-Fisher model therefore lacks an important aspect of biological realism. Here, we present a method that allows Ne to be directly incorporated into the Wright-Fisher model. The modified model involves matrices whose size is determined by Ne. Thus apart from increased biological realism, the modified model also has reduced computational complexity, particularly so when Ne⪡N. For complex problems, it may be hard or impossible to numerically analyse the most commonly-used approximation of the Wright-Fisher model that incorporates Ne, namely the diffusion approximation. An alternative approach is simulation. However, the simulations need to be sufficiently detailed that they yield an effective size that is different to the census size. Simulations may also be time consuming and have attendant statistical errors. The method presented in this work may then be the only alternative to simulations, when Ne differs from N. We illustrate the straightforward application of the method to some problems involving allele fixation and the determination of the equilibrium site frequency spectrum. We then apply the method to the problem of fixation when three alleles are segregating in a population. This latter problem is significantly more complex than a two allele problem and since the diffusion equation cannot be numerically solved, the only other way Ne can be incorporated into the analysis is by simulation. We have

  8. The mechanistic bases of the power-time relationship

    DEFF Research Database (Denmark)

    Vanhatalo, Anni; Black, Matthew I; DiMenna, Fred J

    2016-01-01

    .025) and inversely correlated with muscle type IIx fibre proportion (r = -0.76, P = 0.01). There was no relationship between W' (19.4 ± 6.3 kJ) and muscle fibre type. These data indicate a mechanistic link between the bioenergetic characteristics of different muscle fibre types and the power-duration relationship...

  9. A MULTI-RESOLUTION FUSION MODEL INCORPORATING COLOR AND ELEVATION FOR SEMANTIC SEGMENTATION

    Directory of Open Access Journals (Sweden)

    W. Zhang

    2017-05-01

    Full Text Available In recent years, the developments for Fully Convolutional Networks (FCN have led to great improvements for semantic segmentation in various applications including fused remote sensing data. There is, however, a lack of an in-depth study inside FCN models which would lead to an understanding of the contribution of individual layers to specific classes and their sensitivity to different types of input data. In this paper, we address this problem and propose a fusion model incorporating infrared imagery and Digital Surface Models (DSM for semantic segmentation. The goal is to utilize heterogeneous data more accurately and effectively in a single model instead of to assemble multiple models. First, the contribution and sensitivity of layers concerning the given classes are quantified by means of their recall in FCN. The contribution of different modalities on the pixel-wise prediction is then analyzed based on visualization. Finally, an optimized scheme for the fusion of layers with color and elevation information into a single FCN model is derived based on the analysis. Experiments are performed on the ISPRS Vaihingen 2D Semantic Labeling dataset. Comprehensive evaluations demonstrate the potential of the proposed approach.

  10. A model to incorporate organ deformation in the evaluation of dose/volume relationship

    International Nuclear Information System (INIS)

    Yan, D.; Jaffray, D.; Wong, J.; Brabbins, D.; Martinez, A. A.

    1997-01-01

    Purpose: Measurements of internal organ motion have demonstrated that daily organ deformation exists during the course of radiation treatment. However, a model to evaluate the resultant dose delivered to a daily deformed organ remains a difficult challenge. Current methods which model such organ deformation as rigid body motion in the dose calculation for treatment planning evaluation are incorrect and misleading. In this study, a new model for treatment planning evaluation is introduced which incorporates patient specific information of daily organ deformation and setup variation. The model was also used to retrospectively analyze the actual treatment data measured using daily CT scans for 5 patients with prostate treatment. Methods and Materials: The model assumes that for each patient, the organ of interest can be measured during the first few treatment days. First, the volume of each organ is delineated from each of the daily measurements and cumulated in a 3D bit-map. A tissue occupancy distribution is then constructed with the 50% isodensity representing the mean, or effective, organ volume. During the course of treatment, each voxel in the effective organ volume is assumed to move inside a local 3D neighborhood with a specific distribution function. The neighborhood and the distribution function are deduced from the positions and shapes of the organ in the first few measurements using the biomechanics model of viscoelastic body. For each voxel, the local distribution function is then convolved with the spatial dose distribution. The latter includes also the variation in dose due to daily setup error. As a result, the cumulative dose to the voxel incorporates the effects of daily setup variation and organ deformation. A ''variation adjusted'' dose volume histogram, aDVH, for the effective organ volume can then be constructed for the purpose of treatment evaluation and optimization. Up to 20 daily CT scans and daily portal images for 5 patients with prostate

  11. Using a cognitive architecture in educational and recreational games : How to incorporate a model in your App

    NARCIS (Netherlands)

    Taatgen, Niels A.; de Weerd, Harmen; Reitter, David; Ritter, Frank

    2016-01-01

    We present a Swift re-implementation of the ACT-R cognitive architecture, which can be used to quickly build iOS Apps that incorporate an ACT-R model as a core feature. We discuss how this implementation can be used in an example model, and explore the breadth of possibilities by presenting six Apps

  12. Energy efficiency optimisation for distillation column using artificial neural network models

    International Nuclear Information System (INIS)

    Osuolale, Funmilayo N.; Zhang, Jie

    2016-01-01

    This paper presents a neural network based strategy for the modelling and optimisation of energy efficiency in distillation columns incorporating the second law of thermodynamics. Real-time optimisation of distillation columns based on mechanistic models is often infeasible due to the effort in model development and the large computation effort associated with mechanistic model computation. This issue can be addressed by using neural network models which can be quickly developed from process operation data. The computation time in neural network model evaluation is very short making them ideal for real-time optimisation. Bootstrap aggregated neural networks are used in this study for enhanced model accuracy and reliability. Aspen HYSYS is used for the simulation of the distillation systems. Neural network models for exergy efficiency and product compositions are developed from simulated process operation data and are used to maximise exergy efficiency while satisfying products qualities constraints. Applications to binary systems of methanol-water and benzene-toluene separations culminate in a reduction of utility consumption of 8.2% and 28.2% respectively. Application to multi-component separation columns also demonstrate the effectiveness of the proposed method with a 32.4% improvement in the exergy efficiency. - Highlights: • Neural networks can accurately model exergy efficiency in distillation columns. • Bootstrap aggregated neural network offers improved model prediction accuracy. • Improved exergy efficiency is obtained through model based optimisation. • Reductions of utility consumption by 8.2% and 28.2% were achieved for binary systems. • The exergy efficiency for multi-component distillation is increased by 32.4%.

  13. Mechanistic studies of carbon monoxide reduction

    Energy Technology Data Exchange (ETDEWEB)

    Geoffroy, G.L.

    1990-06-12

    The progress made during the current grant period (1 January 1988--1 April 1990) in three different areas of research is summarized. The research areas are: (1) oxidatively-induced double carbonylation reactions to form {alpha}-ketoacyl complexes and studies of the reactivity of the resulting compounds, (2) mechanistic studies of the carbonylation of nitroaromatics to form isocyanates, carbamates, and ureas, and (3) studies of the formation and reactivity of unusual metallacycles and alkylidene ligands supported on binuclear iron carbonyl fragments. 18 refs., 5 figs., 1 tab.

  14. Developing Baltic cod recruitment models II : Incorporation of environmental variability and species interaction

    DEFF Research Database (Denmark)

    Köster, Fritz; Hinrichsen, H.H.; St. John, Michael

    2001-01-01

    We investigate whether a process-oriented approach based on the results of field, laboratory, and modelling studies can be used to develop a stock-environment-recruitment model for Central Baltic cod (Gadus morhua). Based on exploratory statistical analysis, significant variables influencing...... affecting survival of eggs, predation by clupeids on eggs, larval transport, and cannibalism. Results showed that recruitment in the most important spawning area, the Bornholm Basin, during 1976-1995 was related to egg production; however, other factors affecting survival of the eggs (oxygen conditions......, predation) were also significant and when incorporated explained 69% of the variation in 0-group recruitment. In other spawning areas, variable hydrographic conditions did not allow for regular successful egg development. Hence, relatively simple models proved sufficient to predict recruitment of 0-group...

  15. The loss of ecosystem services due to land degradation. Integration of mechanistic and probabilistic models in an Ethiopian case study

    Science.gov (United States)

    Cerretelli, Stefania; Poggio, Laura; Gimona, Alessandro; Peressotti, Alessandro; Black, Helaina

    2017-04-01

    Land and soil degradation are widespread especially in dry and developing countries such as Ethiopia. Land degradation leads to ecosystems services (ESS) degradation, because it causes the depletion and loss of several soil functions. Ethiopia's farmland faces intense degradation due to deforestation, agricultural land expansion, land overexploitation and overgrazing. In this study we modelled the impact of physical factors on ESS degradation, in particular soil erodibility, carbon storage and nutrient retention, in the Ethiopian Great Rift Valley, northwestern of Hawassa. We used models of the Sediment retention/loss, the Nutrient Retention/loss (from the software suite InVEST) and Carbon Storage. To run the models we coupled soil local data (such as soil organic carbon, soil texture) with remote sensing data as input in the parametrization phase, e.g. to derive a land use map, to calculate the aboveground and belowground carbon, the evapotraspiration coefficient and the capacity of vegetation to retain nutrient. We then used spatialised Bayesian Belief Networks (sBBNs) predicting ecosystem services degradation on the basis of the results of the three mechanistic models. The results show i) the importance of mapping of ESS degradation taking into consideration the spatial heterogeneity and the cross-correlations between impacts ii) the fundamental role of remote sensing data in monitoring and modelling in remote, data-poor areas and iii) the important role of spatial BBNs in providing spatially explicit measures of risk and uncertainty. This approach could help decision makers to identify priority areas for intervention in order to reduce land and ecosystem services degradation.

  16. A model for arsenic anti-site incorporation in GaAs grown by hydride vapor phase epitaxy

    Energy Technology Data Exchange (ETDEWEB)

    Schulte, K. L.; Kuech, T. F. [Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706 (United States)

    2014-12-28

    GaAs growth by hydride vapor phase epitaxy (HVPE) has regained interest as a potential route to low cost, high efficiency thin film photovoltaics. In order to attain the highest efficiencies, deep level defect incorporation in these materials must be understood and controlled. The arsenic anti-site defect, As{sub Ga} or EL2, is the predominant deep level defect in HVPE-grown GaAs. In the present study, the relationships between HVPE growth conditions and incorporation of EL2 in GaAs epilayers were determined. Epitaxial n-GaAs layers were grown under a wide range of deposition temperatures (T{sub D}) and gallium chloride partial pressures (P{sub GaCl}), and the EL2 concentration, [EL2], was determined by deep level transient spectroscopy. [EL2] agreed with equilibrium thermodynamic predictions in layers grown under conditions in which the growth rate, R{sub G}, was controlled by conditions near thermodynamic equilibrium. [EL2] fell below equilibrium levels when R{sub G} was controlled by surface kinetic processes, with the disparity increasing as R{sub G} decreased. The surface chemical composition during growth was determined to have a strong influence on EL2 incorporation. Under thermodynamically limited growth conditions, e.g., high T{sub D} and/or low P{sub GaCl}, the surface vacancy concentration was high and the bulk crystal was close to equilibrium with the vapor phase. Under kinetically limited growth conditions, e.g., low T{sub D} and/or high P{sub GaCl}, the surface attained a high GaCl coverage, blocking As adsorption. This competitive adsorption process reduced the growth rate and also limited the amount of arsenic that incorporated as As{sub Ga}. A defect incorporation model which accounted for the surface concentration of arsenic as a function of the growth conditions, was developed. This model was used to identify optimal growth parameters for the growth of thin films for photovoltaics, conditions in which a high growth rate and low [EL2] could be

  17. Mechanistic origin of dragon-kings in a population of competing agents

    Science.gov (United States)

    Johnson, N.; Tivnan, B.

    2012-05-01

    We analyze the mechanistic origins of the extreme behaviors that arise in an idealized model of a population of competing agents, such as traders in a market. These extreme behaviors exhibit the defining characteristics of `dragon-kings'. Our model comprises heterogeneous agents who repeatedly compete for some limited resource, making binary choices based on the strategies that they have in their possession. It generalizes the well-known Minority Game by allowing agents whose strategies have not made accurate recent predictions, to step out of the competition until their strategies improve. This generates a complex dynamical interplay between the number V of active agents (mimicking market volume) and the imbalance D between the decisions made (mimicking excess demand). The wide spectrum of extreme behaviors which emerge, helps to explain why no unique relationship has been identified between the price and volume during real market crashes and rallies.

  18. Incorporating Yearly Derived Winter Wheat Maps Into Winter Wheat Yield Forecasting Model

    Science.gov (United States)

    Skakun, S.; Franch, B.; Roger, J.-C.; Vermote, E.; Becker-Reshef, I.; Justice, C.; Santamaría-Artigas, A.

    2016-01-01

    Wheat is one of the most important cereal crops in the world. Timely and accurate forecast of wheat yield and production at global scale is vital in implementing food security policy. Becker-Reshef et al. (2010) developed a generalized empirical model for forecasting winter wheat production using remote sensing data and official statistics. This model was implemented using static wheat maps. In this paper, we analyze the impact of incorporating yearly wheat masks into the forecasting model. We propose a new approach of producing in season winter wheat maps exploiting satellite data and official statistics on crop area only. Validation on independent data showed that the proposed approach reached 6% to 23% of omission error and 10% to 16% of commission error when mapping winter wheat 2-3 months before harvest. In general, we found a limited impact of using yearly winter wheat masks over a static mask for the study regions.

  19. Assessing the Role of Climate Variability on Liver Fluke Risk in the UK Through Mechanistic Hydro-Epidemiological Modelling

    Science.gov (United States)

    Beltrame, L.; Dunne, T.; Rose, H.; Walker, J.; Morgan, E.; Vickerman, P.; Wagener, T.

    2016-12-01

    Liver fluke is a flatworm parasite infecting grazing animals worldwide. In the UK, it causes considerable production losses to cattle and sheep industries and costs farmers millions of pounds each year due to reduced growth rates and lower milk yields. Large part of the parasite life-cycle takes place outside of the host, with its survival and development strongly controlled by climatic and hydrologic conditions. Evidence of climate-driven changes in the distribution and seasonality of fluke disease already exists, as the infection is increasingly expanding to new areas and becoming a year-round problem. Therefore, it is crucial to assess current and potential future impacts of climate variability on the disease to guide interventions at the farm scale and mitigate risk. Climate-based fluke risk models have been available since the 1950s, however, they are based on empirical relationships derived between historical climate and incidence data, and thus are unlikely to be robust for simulating risk under changing conditions. Moreover, they are not dynamic, but estimate risk over large regions in the UK based on monthly average climate conditions, so they do not allow investigating the effects of climate variability for supporting farmers' decisions. In this study, we introduce a mechanistic model for fluke, which represents habitat suitability for disease development at 25m resolution with a daily time step, explicitly linking the parasite life-cycle to key hydro-climate conditions. The model is used on a case study in the UK and sensitivity analysis is performed to better understand the role of climate variability on the space-time dynamics of the disease, while explicitly accounting for uncertainties. Comparisons are presented with experts' knowledge and a widely used empirical model.

  20. Metal accumulation in the earthworm Lumbricus rubellus. Model predictions compared to field data

    Science.gov (United States)

    Veltman, K.; Huijbregts, M.A.J.; Vijver, M.G.; Peijnenburg, W.J.G.M.; Hobbelen, P.H.F.; Koolhaas, J.E.; van Gestel, C.A.M.; van Vliet, P.C.J.; Jan, Hendriks A.

    2007-01-01

    The mechanistic bioaccumulation model OMEGA (Optimal Modeling for Ecotoxicological Applications) is used to estimate accumulation of zinc (Zn), copper (Cu), cadmium (Cd) and lead (Pb) in the earthworm Lumbricus rubellus. Our validation to field accumulation data shows that the model accurately predicts internal cadmium concentrations. In addition, our results show that internal metal concentrations in the earthworm are less than linearly (slope < 1) related to the total concentration in soil, while risk assessment procedures often assume the biota-soil accumulation factor (BSAF) to be constant. Although predicted internal concentrations of all metals are generally within a factor 5 compared to field data, incorporation of regulation in the model is necessary to improve predictability of the essential metals such as zinc and copper. ?? 2006 Elsevier Ltd. All rights reserved.

  1. Life at the Common Denominator: Mechanistic and Quantitative Biology for the Earth and Space Sciences

    Science.gov (United States)

    Hoehler, Tori M.

    2010-01-01

    The remarkable challenges and possibilities of the coming few decades will compel the biogeochemical and astrobiological sciences to characterize the interactions between biology and its environment in a fundamental, mechanistic, and quantitative fashion. The clear need for integrative and scalable biology-environment models is exemplified in the Earth sciences by the challenge of effectively addressing anthropogenic global change, and in the space sciences by the challenge of mounting a well-constrained yet sufficiently adaptive and inclusive search for life beyond Earth. Our understanding of the life-planet interaction is still, however, largely empirical. A variety of approaches seek to move from empirical to mechanistic descriptions. One approach focuses on the relationship between biology and energy, which is at once universal (all life requires energy), unique (life manages energy flow in a fashion not seen in abiotic systems), and amenable to characterization and quantification in thermodynamic terms. Simultaneously, a focus on energy flow addresses a critical point of interface between life and its geological, chemical, and physical environment. Characterizing and quantifying this relationship for life on Earth will support the development of integrative and predictive models for biology-environment dynamics. Understanding this relationship at its most fundamental level holds potential for developing concepts of habitability and biosignatures that can optimize astrobiological exploration strategies and are extensible to all life.

  2. A Mechanistic Model for Drug Release in PLGA Biodegradable Stent Coatings Coupled with Polymer Degradation and Erosion

    Science.gov (United States)

    Zhu, Xiaoxiang; Braatz, Richard D.

    2015-01-01

    Biodegradable poly(D,L-lactic-co-glycolic acid) (PLGA) coating for applications in drug-eluting stents has been receiving increasing interest as a result of its unique properties compared with biodurable polymers in delivering drug for reducing stents-related side effects. In this work, a mathematical model for describing the PLGA degradation and erosion and coupled drug release from PLGA stent coating is developed and validated. An analytical expression is derived for PLGA mass loss that predicts multiple experimental studies in the literature. An analytical model for the change of the number-average degree of polymerization (or molecular weight) is also derived. The drug transport model incorporates simultaneous drug diffusion through both the polymer solid and the liquid-filled pores in the coating, where an effective drug diffusivity model is derived taking into account factors including polymer molecular weight change, stent coating porosity change, and drug partitioning between solid and aqueous phases. The model is used to describe in vitro sirolimus release from PLGA stent coating, and demonstrates the significance of simultaneous sirolimus release via diffusion through both polymer solid and pore space. The proposed model is compared to existing drug transport models, and the impact of model parameters, limitations and possible extensions of the model are also discussed. PMID:25345656

  3. Advances in HTGR fuel performance models

    International Nuclear Information System (INIS)

    Stansfield, O.M.; Goodin, D.T.; Hanson, D.L.; Turner, R.F.

    1985-01-01

    Advances in HTGR fuel performance models have improved the agreement between observed and predicted performance and contributed to an enhanced position of the HTGR with regard to investment risk and passive safety. Heavy metal contamination is the source of about 55% of the circulating activity in the HTGR during normal operation, and the remainder comes primarily from particles which failed because of defective or missing buffer coatings. These failed particles make up about 5 x 10 -4 fraction of the total core inventory. In addition to prediction of fuel performance during normal operation, the models are used to determine fuel failure and fission product release during core heat-up accident conditions. The mechanistic nature of the models, which incorporate all important failure modes, permits the prediction of performance from the relatively modest accident temperatures of a passively safe HTGR to the much more severe accident conditions of the larger 2240-MW/t HTGR. (author)

  4. Secondary clarifier hybrid model calibration in full scale pulp and paper activated sludge wastewater treatment

    Energy Technology Data Exchange (ETDEWEB)

    Sreckovic, G.; Hall, E.R. [British Columbia Univ., Dept. of Civil Engineering, Vancouver, BC (Canada); Thibault, J. [Laval Univ., Dept. of Chemical Engineering, Ste-Foy, PQ (Canada); Savic, D. [Exeter Univ., School of Engineering, Exeter (United Kingdom)

    1999-05-01

    The issue of proper model calibration techniques applied to mechanistic mathematical models relating to activated sludge systems was discussed. Such calibrations are complex because of the non-linearity and multi-model objective functions of the process. This paper presents a hybrid model which was developed using two techniques to model and calibrate secondary clarifier parts of an activated sludge system. Genetic algorithms were used to successfully calibrate the settler mechanistic model, and neural networks were used to reduce the error between the mechanistic model output and real world data. Results of the modelling study show that the long term response of a one-dimensional settler mechanistic model calibrated by genetic algorithms and compared to full scale plant data can be improved by coupling the calibrated mechanistic model to as black-box model, such as a neural network. 11 refs., 2 figs.

  5. Digital terrain model generalization incorporating scale, semantic and cognitive constraints

    Science.gov (United States)

    Partsinevelos, Panagiotis; Papadogiorgaki, Maria

    2014-05-01

    Cartographic generalization is a well-known process accommodating spatial data compression, visualization and comprehension under various scales. In the last few years, there are several international attempts to construct tangible GIS systems, forming real 3D surfaces using a vast number of mechanical parts along a matrix formation (i.e., bars, pistons, vacuums). Usually, moving bars upon a structured grid push a stretching membrane resulting in a smooth visualization for a given surface. Most of these attempts suffer either in their cost, accuracy, resolution and/or speed. Under this perspective, the present study proposes a surface generalization process that incorporates intrinsic constrains of tangible GIS systems including robotic-motor movement and surface stretching limitations. The main objective is to provide optimized visualizations of 3D digital terrain models with minimum loss of information. That is, to minimize the number of pixels in a raster dataset used to define a DTM, while reserving the surface information. This neighborhood type of pixel relations adheres to the basics of Self Organizing Map (SOM) artificial neural networks, which are often used for information abstraction since they are indicative of intrinsic statistical features contained in the input patterns and provide concise and characteristic representations. Nevertheless, SOM remains more like a black box procedure not capable to cope with possible particularities and semantics of the application at hand. E.g. for coastal monitoring applications, the near - coast areas, surrounding mountains and lakes are more important than other features and generalization should be "biased"-stratified to fulfill this requirement. Moreover, according to the application objectives, we extend the SOM algorithm to incorporate special types of information generalization by differentiating the underlying strategy based on topologic information of the objects included in the application. The final

  6. Gold Incorporated Mesoporous Silica Thin Film Model Surface as a Robust SERS and Catalytically Active Substrate

    Directory of Open Access Journals (Sweden)

    Anandakumari Chandrasekharan Sunil Sekhar

    2016-05-01

    Full Text Available Ultra-small gold nanoparticles incorporated in mesoporous silica thin films with accessible pore channels perpendicular to the substrate are prepared by a modified sol-gel method. The simple and easy spin coating technique is applied here to make homogeneous thin films. The surface characterization using FESEM shows crack-free films with a perpendicular pore arrangement. The applicability of these thin films as catalysts as well as a robust SERS active substrate for model catalysis study is tested. Compared to bare silica film our gold incorporated silica, GSM-23F gave an enhancement factor of 103 for RhB with a laser source 633 nm. The reduction reaction of p-nitrophenol with sodium borohydride from our thin films shows a decrease in peak intensity corresponding to –NO2 group as time proceeds, confirming the catalytic activity. Such model surfaces can potentially bridge the material gap between a real catalytic system and surface science studies.

  7. Mechanistic Features of Nanodiamonds in the Lapping of Magnetic Heads

    Directory of Open Access Journals (Sweden)

    Xionghua Jiang

    2014-01-01

    Full Text Available Nanodiamonds, which are the main components of slurry in the precision lapping process of magnetic heads, play an important role in surface quality. This paper studies the mechanistic features of nanodiamond embedment into a Sn plate in the lapping process. This is the first study to develop mathematical models for nanodiamond embedment. Such models can predict the optimum parameters for particle embedment. From the modeling calculations, the embedded pressure satisfies p0=3/2·W/πa2 and the indentation depth satisfies δ=k1P/HV. Calculation results reveal that the largest embedded pressure is 731.48 GPa and the critical indentation depth δ is 7 nm. Atomic force microscopy (AFM, scanning electron microscopy (SEM, and Auger electron spectroscopy (AES were used to carry out surface quality detection and analysis of the disk head. Both the formation of black spots on the surface and the removal rate have an important correlation with the size of nanodiamonds. The results demonstrate that an improved removal rate (21 nm·min−1 can be obtained with 100 nm diamonds embedded in the plate.

  8. Mechanistic features of nanodiamonds in the lapping of magnetic heads.

    Science.gov (United States)

    Jiang, Xionghua; Chen, Zhenxing; Wolfram, Joy; Yang, Zhizhou

    2014-01-01

    Nanodiamonds, which are the main components of slurry in the precision lapping process of magnetic heads, play an important role in surface quality. This paper studies the mechanistic features of nanodiamond embedment into a Sn plate in the lapping process. This is the first study to develop mathematical models for nanodiamond embedment. Such models can predict the optimum parameters for particle embedment. From the modeling calculations, the embedded pressure satisfies p 0 = (3/2) · (W/πa (2)) and the indentation depth satisfies δ = k1√P/HV. Calculation results reveal that the largest embedded pressure is 731.48 GPa and the critical indentation depth δ is 7 nm. Atomic force microscopy (AFM), scanning electron microscopy (SEM), and Auger electron spectroscopy (AES) were used to carry out surface quality detection and analysis of the disk head. Both the formation of black spots on the surface and the removal rate have an important correlation with the size of nanodiamonds. The results demonstrate that an improved removal rate (21 nm · min(-1)) can be obtained with 100 nm diamonds embedded in the plate.

  9. Incorporating excitation-induced dephasing into the Maxwell-Bloch numerical modeling of photon echoes

    International Nuclear Information System (INIS)

    Burr, G.W.; Harris, Todd L.; Babbitt, Wm. Randall; Jefferson, C. Michael

    2004-01-01

    We describe the incorporation of excitation-induced dephasing (EID) into the Maxwell-Bloch numerical simulation of photon echoes. At each time step of the usual numerical integration, stochastic frequency jumps of ions--caused by excitation of neighboring ions--is modeled by convolving each Bloch vector with the Bloch vectors of nearby frequency detunings. The width of this convolution kernel follows the instantaneous change in overall population, integrated over the simulated bandwidth. This approach is validated by extensive comparison against published and original experimental results. The enhanced numerical model is then used to investigate the accuracy of experiments designed to extrapolate to the intrinsic dephasing time T 2 from data taken in the presence of EID. Such a modeling capability offers improved understanding of experimental results, and should allow quantitative analysis of engineering tradeoffs in realistic optical coherent transient applications

  10. Simulation of Forest Carbon Fluxes Using Model Incorporation and Data Assimilation

    Directory of Open Access Journals (Sweden)

    Min Yan

    2016-07-01

    Full Text Available This study improved simulation of forest carbon fluxes in the Changbai Mountains with a process-based model (Biome-BGC using incorporation and data assimilation. Firstly, the original remote sensing-based MODIS MOD_17 GPP (MOD_17 model was optimized using refined input data and biome-specific parameters. The key ecophysiological parameters of the Biome-BGC model were determined through the Extended Fourier Amplitude Sensitivity Test (EFAST sensitivity analysis. Then the optimized MOD_17 model was used to calibrate the Biome-BGC model by adjusting the sensitive ecophysiological parameters. Once the best match was found for the 10 selected forest plots for the 8-day GPP estimates from the optimized MOD_17 and from the Biome-BGC, the values of sensitive ecophysiological parameters were determined. The calibrated Biome-BGC model agreed better with the eddy covariance (EC measurements (R2 = 0.87, RMSE = 1.583 gC·m−2·d−1 than the original model did (R2 = 0.72, RMSE = 2.419 gC·m−2·d−1. To provide a best estimate of the true state of the model, the Ensemble Kalman Filter (EnKF was used to assimilate five years (of eight-day periods between 2003 and 2007 of Global LAnd Surface Satellite (GLASS LAI products into the calibrated Biome-BGC model. The results indicated that LAI simulated through the assimilated Biome-BGC agreed well with GLASS LAI. GPP performances obtained from the assimilated Biome-BGC were further improved and verified by EC measurements at the Changbai Mountains forest flux site (R2 = 0.92, RMSE = 1.261 gC·m−2·d−1.

  11. Improvements in Modelling Bystander and Resident Exposure to Pesticide Spray Drift: Investigations into New Approaches for Characterizing the 'Collection Efficiency' of the Human Body.

    Science.gov (United States)

    Butler Ellis, M Clare; Kennedy, Marc C; Kuster, Christian J; Alanis, Rafael; Tuck, Clive R

    2018-03-17

    The BREAM (Bystander and Resident Exposure Assessment Model) (Kennedy et al. in BREAM: A probabilistic bystander and resident exposure assessment model of spray drift from an agricultural boom sprayer. Comput Electron Agric 2012;88:63-71) for bystander and resident exposure to spray drift from boom sprayers has recently been incorporated into the European Food Safety Authority (EFSA) guidance for determining non-dietary exposures of humans to plant protection products. The component of BREAM, which relates airborne spray concentrations to bystander and resident dermal exposure, has been reviewed to identify whether it is possible to improve this and its description of variability captured in the model. Two approaches have been explored: a more rigorous statistical analysis of the empirical data and a semi-mechanistic model based on established studies combined with new data obtained in a wind tunnel. A statistical comparison between field data and model outputs was used to determine which approach gave the better prediction of exposures. The semi-mechanistic approach gave the better prediction of experimental data and resulted in a reduction in the proposed regulatory values for the 75th and 95th percentiles of the exposure distribution.

  12. Electrochemical processes and mechanistic aspects of field-effect sensors for biomolecules

    Science.gov (United States)

    Huang, Weiguo; Diallo, Abdou Karim; Dailey, Jennifer L.; Besar, Kalpana

    2017-01-01

    Electronic biosensing is a leading technology for determining concentrations of biomolecules. In some cases, the presence of an analyte molecule induces a measured change in current flow, while in other cases, a new potential difference is established. In the particular case of a field effect biosensor, the potential difference is monitored as a change in conductance elsewhere in the device, such as across a film of an underlying semiconductor. Often, the mechanisms that lead to these responses are not specifically determined. Because improved understanding of these mechanisms will lead to improved performance, it is important to highlight those studies where various mechanistic possibilities are investigated. This review explores a range of possible mechanistic contributions to field-effect biosensor signals. First, we define the field-effect biosensor and the chemical interactions that lead to the field effect, followed by a section on theoretical and mechanistic background. We then discuss materials used in field-effect biosensors and approaches to improving signals from field-effect biosensors. We specifically cover the biomolecule interactions that produce local electric fields, structures and processes at interfaces between bioanalyte solutions and electronic materials, semiconductors used in biochemical sensors, dielectric layers used in top-gated sensors, and mechanisms for converting the surface voltage change to higher signal/noise outputs in circuits. PMID:29238595

  13. Incorporating an extended dendritic growth model into the CAFE model for rapidly solidified non-dilute alloys

    International Nuclear Information System (INIS)

    Ma, Jie; Wang, Bo; Zhao, Shunli; Wu, Guangxin; Zhang, Jieyu; Yang, Zhiliang

    2016-01-01

    We have extended the dendritic growth model first proposed by Boettinger, Coriell and Trivedi (here termed EBCT) for microstructure simulations of rapidly solidified non-dilute alloys. The temperature-dependent distribution coefficient, obtained from calculations of phase equilibria, and the continuous growth model (CGM) were adopted in the present EBCT model to describe the solute trapping behaviors. The temperature dependence of the physical properties, which were not used in previous dendritic growth models, were also considered in the present EBCT model. These extensions allow the present EBCT model to be used for microstructure simulations of non-dilute alloys. The comparison of the present EBCT model with the BCT model proves that the considerations of the distribution coefficient and physical properties are necessary for microstructure simulations, especially for small particles with high undercoolings. Finally, the EBCT model was incorporated into the cellular automaton-finite element (CAFE) model to simulate microstructures of gas-atomized ASP30 high speed steel particles that were then compared with experimental results. Both the simulated and experimental results reveal that a columnar dendritic microstructure preferentially forms in small particles and an equiaxed microstructure forms otherwise. The applications of the present EBCT model provide a convenient way to predict the microstructure of non-dilute alloys. - Highlights: • A dendritic growth model was developed considering non-equilibrium distribution coefficient. • The physical properties with temperature dependence were considered in the extended model. • The extended model can be used to non-dilute alloys and the extensions are necessary in small particles. • Microstructure of ASP30 steel was investigated using the present model and verified by experiment.

  14. Incorporating an extended dendritic growth model into the CAFE model for rapidly solidified non-dilute alloys

    Energy Technology Data Exchange (ETDEWEB)

    Ma, Jie; Wang, Bo [State Key Laboratory of Advanced Special Steel, Shanghai University, Shanghai 200072 (China); Shanghai Engineering Technology Research Center of Special Casting, Shanghai 201605 (China); Zhao, Shunli [Research Institute, Baoshan Iron & Steel Co., Ltd, Shanghai 201900 (China); Wu, Guangxin [State Key Laboratory of Advanced Special Steel, Shanghai University, Shanghai 200072 (China); Shanghai Engineering Technology Research Center of Special Casting, Shanghai 201605 (China); Zhang, Jieyu, E-mail: zjy6162@staff.shu.edu.cn [State Key Laboratory of Advanced Special Steel, Shanghai University, Shanghai 200072 (China); Shanghai Engineering Technology Research Center of Special Casting, Shanghai 201605 (China); Yang, Zhiliang [State Key Laboratory of Advanced Special Steel, Shanghai University, Shanghai 200072 (China); Shanghai Engineering Technology Research Center of Special Casting, Shanghai 201605 (China)

    2016-05-25

    We have extended the dendritic growth model first proposed by Boettinger, Coriell and Trivedi (here termed EBCT) for microstructure simulations of rapidly solidified non-dilute alloys. The temperature-dependent distribution coefficient, obtained from calculations of phase equilibria, and the continuous growth model (CGM) were adopted in the present EBCT model to describe the solute trapping behaviors. The temperature dependence of the physical properties, which were not used in previous dendritic growth models, were also considered in the present EBCT model. These extensions allow the present EBCT model to be used for microstructure simulations of non-dilute alloys. The comparison of the present EBCT model with the BCT model proves that the considerations of the distribution coefficient and physical properties are necessary for microstructure simulations, especially for small particles with high undercoolings. Finally, the EBCT model was incorporated into the cellular automaton-finite element (CAFE) model to simulate microstructures of gas-atomized ASP30 high speed steel particles that were then compared with experimental results. Both the simulated and experimental results reveal that a columnar dendritic microstructure preferentially forms in small particles and an equiaxed microstructure forms otherwise. The applications of the present EBCT model provide a convenient way to predict the microstructure of non-dilute alloys. - Highlights: • A dendritic growth model was developed considering non-equilibrium distribution coefficient. • The physical properties with temperature dependence were considered in the extended model. • The extended model can be used to non-dilute alloys and the extensions are necessary in small particles. • Microstructure of ASP30 steel was investigated using the present model and verified by experiment.

  15. Incorporation of oxygen contribution by plant roots into classical dissolved oxygen deficit model for a subsurface flow treatment wetland.

    Science.gov (United States)

    Bezbaruah, Achintya N; Zhang, Tian C

    2009-01-01

    It has been long established that plants play major roles in a treatment wetland. However, the role of plants has not been incorporated into wetland models. This study tries to incorporate wetland plants into a biochemical oxygen demand (BOD) model so that the relative contributions of the aerobic and anaerobic processes to meeting BOD can be quantitatively determined. The classical dissolved oxygen (DO) deficit model has been modified to simulate the DO curve for a field subsurface flow constructed wetland (SFCW) treating municipal wastewater. Sensitivities of model parameters have been analyzed. Based on the model it is predicted that in the SFCW under study about 64% BOD are degraded through aerobic routes and 36% is degraded anaerobically. While not exhaustive, this preliminary work should serve as a pointer for further research in wetland model development and to determine the values of some of the parameters used in the modified DO deficit and associated BOD model. It should be noted that nitrogen cycle and effects of temperature have not been addressed in these models for simplicity of model formulation. This paper should be read with this caveat in mind.

  16. Overview of the South African mechanistic pavement design analysis method

    CSIR Research Space (South Africa)

    Theyse, HL

    1996-01-01

    Full Text Available A historical overview of the South African mechanistic pavement design method, from its development in the early 1970s to the present, is presented. Material characterization, structural analysis, and pavement life prediction are discussed...

  17. Mechanistic Target of Rapamycin-Independent Antidepressant Effects of (R)-Ketamine in a Social Defeat Stress Model.

    Science.gov (United States)

    Yang, Chun; Ren, Qian; Qu, Youge; Zhang, Ji-Chun; Ma, Min; Dong, Chao; Hashimoto, Kenji

    2018-01-01

    The role of the mechanistic target of rapamycin (mTOR) signaling in the antidepressant effects of ketamine is controversial. In addition to mTOR, extracellular signal-regulated kinase (ERK) is a key signaling molecule in prominent pathways that regulate protein synthesis. (R)-Ketamine has a greater potency and longer-lasting antidepressant effects than (S)-ketamine. Here we investigated whether mTOR signaling and ERK signaling play a role in the antidepressant effects of two enantiomers. The effects of mTOR inhibitors (rapamycin and AZD8055) and an ERK inhibitor (SL327) on the antidepressant effects of ketamine enantiomers in the chronic social defeat stress (CSDS) model (n = 7 or 8) and on those of ketamine enantiomers in these signaling pathways in mouse brain regions were examined. The intracerebroventricular infusion of rapamycin or AZD8055 blocked the antidepressant effects of (S)-ketamine, but not (R)-ketamine, in the CSDS model. Furthermore, (S)-ketamine, but not (R)-ketamine, significantly attenuated the decreased phosphorylation of mTOR and its downstream effector, ribosomal protein S6 kinase, in the prefrontal cortex of susceptible mice after CSDS. Pretreatment with SL327 blocked the antidepressant effects of (R)-ketamine but not (S)-ketamine. Moreover, (R)-ketamine, but not (S)-ketamine, significantly attenuated the decreased phosphorylation of ERK and its upstream effector, mitogen-activated protein kinase/ERK kinase, in the prefrontal cortex and hippocampal dentate gyrus of susceptible mice after CSDS. This study suggests that mTOR plays a role in the antidepressant effects of (S)-ketamine, but not (R)-ketamine, and that ERK plays a role in (R)-ketamine's antidepressant effects. Thus, it is unlikely that the activation of mTOR signaling is necessary for antidepressant actions of (R)-ketamine. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  18. A constitutive mechanical model for gas hydrate bearing sediments incorporating inelastic mechanisms

    KAUST Repository

    Sánchez, Marcelo

    2016-11-30

    Gas hydrate bearing sediments (HBS) are natural soils formed in permafrost and sub-marine settings where the temperature and pressure conditions are such that gas hydrates are stable. If these conditions shift from the hydrate stability zone, hydrates dissociate and move from the solid to the gas phase. Hydrate dissociation is accompanied by significant changes in sediment structure and strongly affects its mechanical behavior (e.g., sediment stiffenss, strength and dilatancy). The mechanical behavior of HBS is very complex and its modeling poses great challenges. This paper presents a new geomechanical model for hydrate bearing sediments. The model incorporates the concept of partition stress, plus a number of inelastic mechanisms proposed to capture the complex behavior of this type of soil. This constitutive model is especially well suited to simulate the behavior of HBS upon dissociation. The model was applied and validated against experimental data from triaxial and oedometric tests conducted on manufactured and natural specimens involving different hydrate saturation, hydrate morphology, and confinement conditions. Particular attention was paid to model the HBS behavior during hydrate dissociation under loading. The model performance was highly satisfactory in all the cases studied. It managed to properly capture the main features of HBS mechanical behavior and it also assisted to interpret the behavior of this type of sediment under different loading and hydrate conditions.

  19. Organophotocatalysis: Insights into the Mechanistic Aspects of Thiourea-Mediated Intermolecular [2+2] Photocycloadditions.

    Science.gov (United States)

    Vallavoju, Nandini; Selvakumar, Sermadurai; Pemberton, Barry C; Jockusch, Steffen; Sibi, Mukund P; Sivaguru, Jayaraman

    2016-04-25

    Mechanistic investigations of the intermolecular [2+2] photocycloaddition of coumarin with tetramethylethylene mediated by thiourea catalysts reveal that the reaction is enabled by a combination of minimized aggregation, enhanced intersystem crossing, and altered excited-state lifetime(s). These results clarify how the excited-state reactivity can be manipulated through catalyst-substrate interactions and reveal a third mechanistic pathway for thiourea-mediated organo-photocatalysis. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Incorporating wind availability into land use regression modelling of air quality in mountainous high-density urban environment.

    Science.gov (United States)

    Shi, Yuan; Lau, Kevin Ka-Lun; Ng, Edward

    2017-08-01

    Urban air quality serves as an important function of the quality of urban life. Land use regression (LUR) modelling of air quality is essential for conducting health impacts assessment but more challenging in mountainous high-density urban scenario due to the complexities of the urban environment. In this study, a total of 21 LUR models are developed for seven kinds of air pollutants (gaseous air pollutants CO, NO 2 , NO x , O 3 , SO 2 and particulate air pollutants PM 2.5 , PM 10 ) with reference to three different time periods (summertime, wintertime and annual average of 5-year long-term hourly monitoring data from local air quality monitoring network) in Hong Kong. Under the mountainous high-density urban scenario, we improved the traditional LUR modelling method by incorporating wind availability information into LUR modelling based on surface geomorphometrical analysis. As a result, 269 independent variables were examined to develop the LUR models by using the "ADDRESS" independent variable selection method and stepwise multiple linear regression (MLR). Cross validation has been performed for each resultant model. The results show that wind-related variables are included in most of the resultant models as statistically significant independent variables. Compared with the traditional method, a maximum increase of 20% was achieved in the prediction performance of annual averaged NO 2 concentration level by incorporating wind-related variables into LUR model development. Copyright © 2017 Elsevier Inc. All rights reserved.

  1. Mechanistic and Economical Characteristics of Asphalt Rubber Mixtures

    Directory of Open Access Journals (Sweden)

    Mena I. Souliman

    2016-01-01

    Full Text Available Load associated fatigue cracking is one of the major distress types occurring in flexible pavement systems. Flexural bending beam fatigue laboratory test has been used for several decades and is considered to be an integral part of the new superpave advanced characterization procedure. One of the most significant solutions to prolong the fatigue life for an asphaltic mixture is to utilize flexible materials as rubber. A laboratory testing program was performed on a conventional and Asphalt Rubber- (AR- gap-graded mixtures to investigate the impact of added rubber on the mechanical, mechanistic, and economical attributes of asphaltic mixtures. Strain controlled fatigue tests were conducted according to American Association of State Highway and Transportation Officials (AASHTO procedures. The results from the beam fatigue tests indicated that the AR-gap-graded mixtures would have much longer fatigue life compared with the reference (conventional mixtures. In addition, a mechanistic analysis using 3D-Move software coupled with a cost analysis study based on the fatigue performance on the two mixtures was performed. Overall, analysis showed that AR modified asphalt mixtures exhibited significantly lower cost of pavement per 1000 cycles of fatigue life per mile compared to conventional HMA mixture.

  2. A Novel Approach of Understanding and Incorporating Error of Chemical Transport Models into a Geostatistical Framework

    Science.gov (United States)

    Reyes, J.; Vizuete, W.; Serre, M. L.; Xu, Y.

    2015-12-01

    The EPA employs a vast monitoring network to measure ambient PM2.5 concentrations across the United States with one of its goals being to quantify exposure within the population. However, there are several areas of the country with sparse monitoring spatially and temporally. One means to fill in these monitoring gaps is to use PM2.5 modeled estimates from Chemical Transport Models (CTMs) specifically the Community Multi-scale Air Quality (CMAQ) model. CMAQ is able to provide complete spatial coverage but is subject to systematic and random error due to model uncertainty. Due to the deterministic nature of CMAQ, often these uncertainties are not quantified. Much effort is employed to quantify the efficacy of these models through different metrics of model performance. Currently evaluation is specific to only locations with observed data. Multiyear studies across the United States are challenging because the error and model performance of CMAQ are not uniform over such large space/time domains. Error changes regionally and temporally. Because of the complex mix of species that constitute PM2.5, CMAQ error is also a function of increasing PM2.5 concentration. To address this issue we introduce a model performance evaluation for PM2.5 CMAQ that is regionalized and non-linear. This model performance evaluation leads to error quantification for each CMAQ grid. Areas and time periods of error being better qualified. The regionalized error correction approach is non-linear and is therefore more flexible at characterizing model performance than approaches that rely on linearity assumptions and assume homoscedasticity of CMAQ predictions errors. Corrected CMAQ data are then incorporated into the modern geostatistical framework of Bayesian Maximum Entropy (BME). Through cross validation it is shown that incorporating error-corrected CMAQ data leads to more accurate estimates than just using observed data by themselves.

  3. Does Mechanistic Thinking Improve Student Success in Organic Chemistry?

    Science.gov (United States)

    Grove, Nathaniel P.; Cooper, Melanie M.; Cox, Elizabeth L.

    2012-01-01

    The use of the curved-arrow notation to depict electron flow during mechanistic processes is one of the most important representational conventions in the organic chemistry curriculum. Our previous research documented a disturbing trend: when asked to predict the products of a series of reactions, many students do not spontaneously engage in…

  4. THMC Modeling of EGS Reservoirs -- Continuum through Discontinuum Representations. Capturing Reservoir Stimulation, Evolution and Induced Seismicity

    Energy Technology Data Exchange (ETDEWEB)

    Elsworth, Derek [Pennsylvania State Univ., State College, PA (United States); Izadi, Ghazal [Pennsylvania State Univ., State College, PA (United States); Gan, Quan [Pennsylvania State Univ., State College, PA (United States); Fang, Yi [Pennsylvania State Univ., State College, PA (United States); Taron, Josh [US Geological Survey, Menlo Park, CA (United States); Sonnenthal, Eric [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-07-28

    This work has investigated the roles of effective stress induced by changes in fluid pressure, temperature and chemistry in contributing to the evolution of permeability and induced seismicity in geothermal reservoirs. This work has developed continuum models [1] to represent the progress or seismicity during both stimulation [2] and production [3]. These methods have been used to resolve anomalous observations of induced seismicity at the Newberry Volcano demonstration project [4] through the application of modeling and experimentation. Later work then focuses on the occurrence of late stage seismicity induced by thermal stresses [5] including the codifying of the timing and severity of such responses [6]. Furthermore, mechanistic linkages between observed seismicity and the evolution of permeability have been developed using data from the Newberry project [7] and benchmarked against field injection experiments. Finally, discontinuum models [8] incorporating the roles of discrete fracture networks have been applied to represent stimulation and then thermal recovery for new arrangements of geothermal wells incorporating the development of flow manifolds [9] in order to increase thermal output and longevity in EGS systems.

  5. The CAFE model: A net production model for global ocean phytoplankton

    Science.gov (United States)

    Silsbe, Greg M.; Behrenfeld, Michael J.; Halsey, Kimberly H.; Milligan, Allen J.; Westberry, Toby K.

    2016-12-01

    The Carbon, Absorption, and Fluorescence Euphotic-resolving (CAFE) net primary production model is an adaptable framework for advancing global ocean productivity assessments by exploiting state-of-the-art satellite ocean color analyses and addressing key physiological and ecological attributes of phytoplankton. Here we present the first implementation of the CAFE model that incorporates inherent optical properties derived from ocean color measurements into a mechanistic and accurate model of phytoplankton growth rates (μ) and net phytoplankton production (NPP). The CAFE model calculates NPP as the product of energy absorption (QPAR), and the efficiency (ϕμ) by which absorbed energy is converted into carbon biomass (CPhyto), while μ is calculated as NPP normalized to CPhyto. The CAFE model performance is evaluated alongside 21 other NPP models against a spatially robust and globally representative set of direct NPP measurements. This analysis demonstrates that the CAFE model explains the greatest amount of variance and has the lowest model bias relative to other NPP models analyzed with this data set. Global oceanic NPP from the CAFE model (52 Pg C m-2 yr-1) and mean division rates (0.34 day-1) are derived from climatological satellite data (2002-2014). This manuscript discusses and validates individual CAFE model parameters (e.g., QPAR and ϕμ), provides detailed sensitivity analyses, and compares the CAFE model results and parameterization to other widely cited models.

  6. Toward a Rational and Mechanistic Account of Mental Effort.

    Science.gov (United States)

    Shenhav, Amitai; Musslick, Sebastian; Lieder, Falk; Kool, Wouter; Griffiths, Thomas L; Cohen, Jonathan D; Botvinick, Matthew M

    2017-07-25

    In spite of its familiar phenomenology, the mechanistic basis for mental effort remains poorly understood. Although most researchers agree that mental effort is aversive and stems from limitations in our capacity to exercise cognitive control, it is unclear what gives rise to those limitations and why they result in an experience of control as costly. The presence of these control costs also raises further questions regarding how best to allocate mental effort to minimize those costs and maximize the attendant benefits. This review explores recent advances in computational modeling and empirical research aimed at addressing these questions at the level of psychological process and neural mechanism, examining both the limitations to mental effort exertion and how we manage those limited cognitive resources. We conclude by identifying remaining challenges for theoretical accounts of mental effort as well as possible applications of the available findings to understanding the causes of and potential solutions for apparent failures to exert the mental effort required of us.

  7. Models of Superoxide Dismutases

    Energy Technology Data Exchange (ETDEWEB)

    Cabelli, Diane E.; Riley, Dennis; Rodriguez, Jorge A.; Valentine, Joan Selverstone; Zhu, Haining

    1998-05-20

    In this review we have focused much of our discussion on the mechanistic details of how the native enzymes function and how mechanistic developments/insights with synthetic small molecule complexes possessing SOD activity have influenced our understanding of the electron transfer processes involved with the natural enzymes. A few overriding themes have emerged. Clearly, the SOD enzymes operate at near diffusion controlled rates and to achieve such catalytic turnover activity, several important physical principles must be operative. Such fast electron transfer processes requires a role for protons; i.e., proton-coupled electron transfer (''H-atom transfer'') solves the dilemma of charge separation developing in the transition state for the electron transfer step. Additionally, outer-sphere electron transfer is likely a most important pathway for manganese and iron dismutases. This situation arises because the ligand exchange rates on these two ions in water never exceed {approx}10{sup +7} s{sup -1}; consequently, 10{sup +9} catalytic rates require more subtle mechanistic insights. In contrast, copper complexes can achieve diffusion controlled (>10{sup +9}) exchange rates in water; thus inner-sphere electron transfer processes are more likely to be operative in the Cu/Zn enzymes. Recent studies have continued to expand our understanding of the mechanism of action of this most important class of redox active enzymes, the superoxide dismutases, which have been critical in the successful adaptation of life on this planet to an oxygen-based metabolism. The design of SOD mimic drugs, synthetic models compounds that incorporate this superoxide dismutase catalytic activity and are capable of functioning in vivo, offers clear potential benefits in the control of diseases, ranging from the control of neurodegenerative conditions, such as Parkinson's or Alzheimer's disease, to cancer.

  8. Existing pavement input information for the mechanistic-empirical pavement design guide.

    Science.gov (United States)

    2009-02-01

    The objective of this study is to systematically evaluate the Iowa Department of Transportations (DOTs) existing Pavement Management Information System (PMIS) with respect to the input information required for Mechanistic-Empirical Pavement Des...

  9. A neural population model incorporating dopaminergic neurotransmission during complex voluntary behaviors.

    Directory of Open Access Journals (Sweden)

    Stefan Fürtinger

    2014-11-01

    Full Text Available Assessing brain activity during complex voluntary motor behaviors that require the recruitment of multiple neural sites is a field of active research. Our current knowledge is primarily based on human brain imaging studies that have clear limitations in terms of temporal and spatial resolution. We developed a physiologically informed non-linear multi-compartment stochastic neural model to simulate functional brain activity coupled with neurotransmitter release during complex voluntary behavior, such as speech production. Due to its state-dependent modulation of neural firing, dopaminergic neurotransmission plays a key role in the organization of functional brain circuits controlling speech and language and thus has been incorporated in our neural population model. A rigorous mathematical proof establishing existence and uniqueness of solutions to the proposed model as well as a computationally efficient strategy to numerically approximate these solutions are presented. Simulated brain activity during the resting state and sentence production was analyzed using functional network connectivity, and graph theoretical techniques were employed to highlight differences between the two conditions. We demonstrate that our model successfully reproduces characteristic changes seen in empirical data between the resting state and speech production, and dopaminergic neurotransmission evokes pronounced changes in modeled functional connectivity by acting on the underlying biological stochastic neural model. Specifically, model and data networks in both speech and rest conditions share task-specific network features: both the simulated and empirical functional connectivity networks show an increase in nodal influence and segregation in speech over the resting state. These commonalities confirm that dopamine is a key neuromodulator of the functional connectome of speech control. Based on reproducible characteristic aspects of empirical data, we suggest a number

  10. Incorporating Social System Dynamics into the Food-Energy-Water System Resilience-Sustainability Modeling Process

    Science.gov (United States)

    Givens, J.; Padowski, J.; Malek, K.; Guzman, C.; Boll, J.; Adam, J. C.; Witinok-Huber, R.

    2017-12-01

    In the face of climate change and multi-scalar governance objectives, achieving resilience of food-energy-water (FEW) systems requires interdisciplinary approaches. Through coordinated modeling and management efforts, we study "Innovations in the Food-Energy-Water Nexus (INFEWS)" through a case-study in the Columbia River Basin. Previous research on FEW system management and resilience includes some attention to social dynamics (e.g., economic, governance); however, more research is needed to better address social science perspectives. Decisions ultimately taken in this river basin would occur among stakeholders encompassing various institutional power structures including multiple U.S. states, tribal lands, and sovereign nations. The social science lens draws attention to the incompatibility between the engineering definition of resilience (i.e., return to equilibrium or a singular stable state) and the ecological and social system realities, more explicit in the ecological interpretation of resilience (i.e., the ability of a system to move into a different, possibly more resilient state). Social science perspectives include but are not limited to differing views on resilience as normative, system persistence versus transformation, and system boundary issues. To expand understanding of resilience and objectives for complex and dynamic systems, concepts related to inequality, heterogeneity, power, agency, trust, values, culture, history, conflict, and system feedbacks must be more tightly integrated into FEW research. We identify gaps in knowledge and data, and the value and complexity of incorporating social components and processes into systems models. We posit that socio-biophysical system resilience modeling would address important complex, dynamic social relationships, including non-linear dynamics of social interactions, to offer an improved understanding of sustainable management in FEW systems. Conceptual modeling that is presented in our study, represents

  11. Mechanistic Basis of Cocrystal Dissolution Advantage.

    Science.gov (United States)

    Cao, Fengjuan; Amidon, Gordon L; Rodríguez-Hornedo, Naír; Amidon, Gregory E

    2018-01-01

    Current interest in cocrystal development resides in the advantages that the cocrystal may have in solubility and dissolution compared with the parent drug. This work provides a mechanistic analysis and comparison of the dissolution behavior of carbamazepine (CBZ) and its 2 cocrystals, carbamazepine-saccharin (CBZ-SAC) and carbamazepine-salicylic acid (CBZ-SLC) under the influence of pH and micellar solubilization. A simple mathematical equation is derived based on the mass transport analyses to describe the dissolution advantage of cocrystals. The dissolution advantage is the ratio of the cocrystal flux to drug flux and is defined as the solubility advantage (cocrystal to drug solubility ratio) times the diffusivity advantage (cocrystal to drug diffusivity ratio). In this work, the effective diffusivity of CBZ in the presence of surfactant was determined to be different and less than those of the cocrystals. The higher effective diffusivity of drug from the dissolved cocrystals, the diffusivity advantage, can impart a dissolution advantage to cocrystals with lower solubility than the parent drug while still maintaining thermodynamic stability. Dissolution conditions where cocrystals can display both thermodynamic stability and a dissolution advantage can be obtained from the mass transport models, and this information is useful for both cocrystal selection and formulation development. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

  12. A Fibrocontractive Mechanochemical Model of Dermal Wound Closure Incorporating Realistic Growth Factor Kinetics

    KAUST Repository

    Murphy, Kelly E.

    2012-01-13

    Fibroblasts and their activated phenotype, myofibroblasts, are the primary cell types involved in the contraction associated with dermal wound healing. Recent experimental evidence indicates that the transformation from fibroblasts to myofibroblasts involves two distinct processes: The cells are stimulated to change phenotype by the combined actions of transforming growth factor β (TGFβ) and mechanical tension. This observation indicates a need for a detailed exploration of the effect of the strong interactions between the mechanical changes and growth factors in dermal wound healing. We review the experimental findings in detail and develop a model of dermal wound healing that incorporates these phenomena. Our model includes the interactions between TGFβ and collagenase, providing a more biologically realistic form for the growth factor kinetics than those included in previous mechanochemical descriptions. A comparison is made between the model predictions and experimental data on human dermal wound healing and all the essential features are well matched. © 2012 Society for Mathematical Biology.

  13. A Fibrocontractive Mechanochemical Model of Dermal Wound Closure Incorporating Realistic Growth Factor Kinetics

    KAUST Repository

    Murphy, Kelly E.; Hall, Cameron L.; Maini, Philip K.; McCue, Scott W.; McElwain, D. L. Sean

    2012-01-01

    Fibroblasts and their activated phenotype, myofibroblasts, are the primary cell types involved in the contraction associated with dermal wound healing. Recent experimental evidence indicates that the transformation from fibroblasts to myofibroblasts involves two distinct processes: The cells are stimulated to change phenotype by the combined actions of transforming growth factor β (TGFβ) and mechanical tension. This observation indicates a need for a detailed exploration of the effect of the strong interactions between the mechanical changes and growth factors in dermal wound healing. We review the experimental findings in detail and develop a model of dermal wound healing that incorporates these phenomena. Our model includes the interactions between TGFβ and collagenase, providing a more biologically realistic form for the growth factor kinetics than those included in previous mechanochemical descriptions. A comparison is made between the model predictions and experimental data on human dermal wound healing and all the essential features are well matched. © 2012 Society for Mathematical Biology.

  14. Generative Mechanistic Explanation Building in Undergraduate Molecular and Cellular Biology

    Science.gov (United States)

    Southard, Katelyn M.; Espindola, Melissa R.; Zaepfel, Samantha D.; Bolger, Molly S.

    2017-01-01

    When conducting scientific research, experts in molecular and cellular biology (MCB) use specific reasoning strategies to construct mechanistic explanations for the underlying causal features of molecular phenomena. We explored how undergraduate students applied this scientific practice in MCB. Drawing from studies of explanation building among…

  15. A mechanistic model to study the thermal ecology of a southeastern pacific dominant intertidal mussel and implications for climate change.

    Science.gov (United States)

    Finke, G R; Bozinovic, F; Navarrete, S A

    2009-01-01

    Developing mechanistic models to predict an organism's body temperature facilitates the study of physiological stresses caused by extreme climatic conditions the species might have faced in the past or making predictions about changes to come in the near future. Because the models combine empirical observation of different climatic variables with essential morphological attributes of the species, it is possible to examine specific aspects of predicted climatic changes. Here, we develop a model for the competitively dominant intertidal mussel Perumytilus purpuratus that estimates body temperature on the basis of meteorological and tidal data with an average difference (+/-SE) of 0.410 degrees +/- 0.0315 degrees C in comparison with a field-deployed temperature logger. Modeled body temperatures of P. purpuratus in central Chile regularly exceeded 30 degrees C in summer months, and values as high as 38 degrees C were found. These results suggest that the temperatures reached by mussels in the intertidal zone in central Chile are not sufficiently high to induce significant mortality on adults of this species; however, because body temperatures >40 degrees C can be lethal for this species, sublethal effects on physiological performance warrant further investigation. Body temperatures of mussels increased sigmoidally with increasing tidal height. Body temperatures of individuals from approximately 70% of the tidal range leveled off and did not increase any further with increasing tidal height. Finally, body size played an important role in determining body temperature. A hypothetical 5-cm-long mussel (only 1 cm longer than mussels found in nature) did reach potentially lethal body temperatures, suggesting that the biophysical environment may play a role in limiting the size of this small species.

  16. Mechanistic Understanding of Microbial Plugging for Improved Sweep Efficiency

    Energy Technology Data Exchange (ETDEWEB)

    Steven Bryant; Larry Britton

    2008-09-30

    Microbial plugging has been proposed as an effective low cost method of permeability reduction. Yet there is a dearth of information on the fundamental processes of microbial growth in porous media, and there are no suitable data to model the process of microbial plugging as it relates to sweep efficiency. To optimize the field implementation, better mechanistic and volumetric understanding of biofilm growth within a porous medium is needed. In particular, the engineering design hinges upon a quantitative relationship between amount of nutrient consumption, amount of growth, and degree of permeability reduction. In this project experiments were conducted to obtain new data to elucidate this relationship. Experiments in heterogeneous (layered) beadpacks showed that microbes could grow preferentially in the high permeability layer. Ultimately this caused flow to be equally divided between high and low permeability layers, precisely the behavior needed for MEOR. Remarkably, classical models of microbial nutrient uptake in batch experiments do not explain the nutrient consumption by the same microbes in flow experiments. We propose a simple extension of classical kinetics to account for the self-limiting consumption of nutrient observed in our experiments, and we outline a modeling approach based on architecture and behavior of biofilms. Such a model would account for the changing trend of nutrient consumption by bacteria with the increasing biomass and the onset of biofilm formation. However no existing model can explain the microbial preference for growth in high permeability regions, nor is there any obvious extension of the model for this observation. An attractive conjecture is that quorum sensing is involved in the heterogeneous bead packs.

  17. Mechanistic considerations used in the development of the probability of failure in transient increases in power (PROFIT) pellet-zircaloy cladding (thermo-mechanical-chemical) interactions (pci) fuel failure model

    International Nuclear Information System (INIS)

    Pankaskie, P.J.

    1980-05-01

    A fuel Pellet-Zircaloy Cladding (thermo-mechanical-chemical) interactions (PCI) failure model for estimating the Probability of Failure in Transient Increases in Power (PROFIT) was developed. PROFIT is based on (1) standard statistical methods applied to available PCI fuel failure data and (2) a mechanistic analysis of the environmental and strain-rate-dependent stress versus strain characteristics of Zircaloy cladding. The statistical analysis of fuel failures attributable to PCI suggested that parameters in addition to power, transient increase in power, and burnup are needed to define PCI fuel failures in terms of probability estimates with known confidence limits. The PROFIT model, therefore, introduces an environmental and strain-rate dependent Strain Energy Absorption to Failure (SEAF) concept to account for the stress versus strain anomalies attributable to interstitial-dislocation interaction effects in the Zircaloy cladding

  18. A mathematical model for maximizing the value of phase 3 drug development portfolios incorporating budget constraints and risk.

    Science.gov (United States)

    Patel, Nitin R; Ankolekar, Suresh; Antonijevic, Zoran; Rajicic, Natasa

    2013-05-10

    We describe a value-driven approach to optimizing pharmaceutical portfolios. Our approach incorporates inputs from research and development and commercial functions by simultaneously addressing internal and external factors. This approach differentiates itself from current practices in that it recognizes the impact of study design parameters, sample size in particular, on the portfolio value. We develop an integer programming (IP) model as the basis for Bayesian decision analysis to optimize phase 3 development portfolios using expected net present value as the criterion. We show how this framework can be used to determine optimal sample sizes and trial schedules to maximize the value of a portfolio under budget constraints. We then illustrate the remarkable flexibility of the IP model to answer a variety of 'what-if' questions that reflect situations that arise in practice. We extend the IP model to a stochastic IP model to incorporate uncertainty in the availability of drugs from earlier development phases for phase 3 development in the future. We show how to use stochastic IP to re-optimize the portfolio development strategy over time as new information accumulates and budget changes occur. Copyright © 2013 John Wiley & Sons, Ltd.

  19. Comparison in the calculation of committed effective dose using the ICRP 30 and ICRP 60 models for a repeated incorporation by inhalation of I-125

    International Nuclear Information System (INIS)

    Carreno P, A.L.; Cortes C, A.; Alonso V, G.; Serrano P, F.

    2005-01-01

    Presently work, a comparison in the calculation of committed effective dose using the models of the ICRP 30 and those of the ICRP 60 for the analysis of internal dose due to repeated incorporation of I-125 is shown. The estimations of incorporated activity are obtained starting from the proportionate data for an exercise of inter comparison, with which it should be determined the internal dose later on. For to estimate the initial activity incorporated by repeated dose was assumed that this it was given through of multiple individual incorporations which happened in the middle points of the monitoring periods. The results using the models of the ICRP 30 and of the ICRP 60 are compared and the causes of the differences are analyzed. (Author)

  20. Position-specific isotope modeling of organic micropollutants transformations through different reaction pathways

    Science.gov (United States)

    Jin, Biao; Rolle, Massimo

    2016-04-01

    Organic compounds are produced in vast quantities for industrial and agricultural use, as well as for human and animal healthcare [1]. These chemicals and their metabolites are frequently detected at trace levels in fresh water environments where they undergo degradation via different reaction pathways. Compound specific stable isotope analysis (CSIA) is a valuable tool to identify such degradation pathways in different environmental systems. Recent advances in analytical techniques have promoted the fast development and implementation of multi-element CSIA. However, quantitative frameworks to evaluate multi-element stable isotope data and incorporating mechanistic information on the degradation processes [2,3] are still lacking. In this study we propose a mechanism-based modeling approach to simultaneously evaluate concentration as well as bulk and position-specific multi-element isotope evolution during the transformation of organic micropollutants. The model explicitly simulates position-specific isotopologues for those atoms that experience isotope effects and, thereby, provides a mechanistic description of isotope fractionation occurring at different molecular positions. We validate the proposed approach with the concentration and multi-element isotope data of three selected organic micropollutants: dichlorobenzamide (BAM), isoproturon (IPU) and diclofenac (DCF). The model precisely captures the dual element isotope trends characteristic of different reaction pathways and their range of variation consistent with observed multi-element (C, N) bulk isotope fractionation. The proposed approach can also be used as a tool to explore transformation pathways in scenarios for which position-specific isotope data are not yet available. [1] Schwarzenbach, R.P., Egli, T., Hofstetter, T.B., von Gunten, U., Wehrli, B., 2010. Global Water Pollution and Human Health. Annu. Rev. Environ. Resour. doi:10.1146/annurev-environ-100809-125342. [2] Jin, B., Haderlein, S.B., Rolle, M

  1. An idealized radiative transfer scheme for use in a mechanistic general circulation model from the surface up to the mesopause region

    International Nuclear Information System (INIS)

    Knoepfel, Rahel; Becker, Erich

    2011-01-01

    A new and numerically efficient method to compute radiative flux densities and heating rates in a general atmospheric circulation model is presented. Our method accommodates the fundamental differences between the troposphere and middle atmosphere in the long-wave regime within a single parameterization that extends continuously from the surface up to the mesopause region and takes the deviations from the gray limit and from the local thermodynamic equilibrium into account. For this purpose, frequency-averaged Eddington-type transfer equations are derived for four broad absorber bands. The frequency variation inside each band is parameterized by application of the Elsasser band model extended by a slowly varying envelope function. This yields additional transfer equations for the perturbation amplitudes that are solved numerically along with the mean transfer equations. Deviations from local thermodynamic equilibrium are included in terms of isotropic scattering, calculating the single scattering albedo from the two-level model for each band. Solar radiative flux densities are computed for four energetically defined bands using the simple Beer-Bougert-Lambert relation for absorption within the atmosphere. The new scheme is implemented in a mechanistic general circulation model from the surface up to the mesopause region. A test simulation with prescribed concentrations of the radiatively active constituents shows quite reasonable results. In particular, since we take the full surface energy budget into account by means of a swamp ocean, and since the internal dynamics and turbulent diffusion of the model are formulated in accordance with the conservation laws, an equilibrated climatological radiation budget is obtained both at the top of the atmosphere and at the surface.

  2. A computational model incorporating neural stem cell dynamics reproduces glioma incidence across the lifespan in the human population.

    Directory of Open Access Journals (Sweden)

    Roman Bauer

    Full Text Available Glioma is the most common form of primary brain tumor. Demographically, the risk of occurrence increases until old age. Here we present a novel computational model to reproduce the probability of glioma incidence across the lifespan. Previous mathematical models explaining glioma incidence are framed in a rather abstract way, and do not directly relate to empirical findings. To decrease this gap between theory and experimental observations, we incorporate recent data on cellular and molecular factors underlying gliomagenesis. Since evidence implicates the adult neural stem cell as the likely cell-of-origin of glioma, we have incorporated empirically-determined estimates of neural stem cell number, cell division rate, mutation rate and oncogenic potential into our model. We demonstrate that our model yields results which match actual demographic data in the human population. In particular, this model accounts for the observed peak incidence of glioma at approximately 80 years of age, without the need to assert differential susceptibility throughout the population. Overall, our model supports the hypothesis that glioma is caused by randomly-occurring oncogenic mutations within the neural stem cell population. Based on this model, we assess the influence of the (experimentally indicated decrease in the number of neural stem cells and increase of cell division rate during aging. Our model provides multiple testable predictions, and suggests that different temporal sequences of oncogenic mutations can lead to tumorigenesis. Finally, we conclude that four or five oncogenic mutations are sufficient for the formation of glioma.

  3. Shorebird Migration Patterns in Response to Climate Change: A Modeling Approach

    Science.gov (United States)

    Smith, James A.

    2010-01-01

    The availability of satellite remote sensing observations at multiple spatial and temporal scales, coupled with advances in climate modeling and information technologies offer new opportunities for the application of mechanistic models to predict how continental scale bird migration patterns may change in response to environmental change. In earlier studies, we explored the phenotypic plasticity of a migratory population of Pectoral sandpipers by simulating the movement patterns of an ensemble of 10,000 individual birds in response to changes in stopover locations as an indicator of the impacts of wetland loss and inter-annual variability on the fitness of migratory shorebirds. We used an individual based, biophysical migration model, driven by remotely sensed land surface data, climate data, and biological field data. Mean stop-over durations and stop-over frequency with latitude predicted from our model for nominal cases were consistent with results reported in the literature and available field data. In this study, we take advantage of new computing capabilities enabled by recent GP-GPU computing paradigms and commodity hardware (general purchase computing on graphics processing units). Several aspects of our individual based (agent modeling) approach lend themselves well to GP-GPU computing. We have been able to allocate compute-intensive tasks to the graphics processing units, and now simulate ensembles of 400,000 birds at varying spatial resolutions along the central North American flyway. We are incorporating additional, species specific, mechanistic processes to better reflect the processes underlying bird phenotypic plasticity responses to different climate change scenarios in the central U.S.

  4. Incorporation of a Wind Generator Model into a Dynamic Power Flow Analysis

    Directory of Open Access Journals (Sweden)

    Angeles-Camacho C.

    2011-07-01

    Full Text Available Wind energy is nowadays one of the most cost-effective and practical options for electric generation from renewable resources. However, increased penetration of wind generation causes the power networks to be more depend on, and vulnerable to, the varying wind speed. Modeling is a tool which can provide valuable information about the interaction between wind farms and the power network to which they are connected. This paper develops a realistic characterization of a wind generator. The wind generator model is incorporated into an algorithm to investigate its contribution to the stability of the power network in the time domain. The tool obtained is termed dynamic power flow. The wind generator model takes on account the wind speed and the reactive power consumption by induction generators. Dynamic power flow analysis is carried-out using real wind data at 10-minute time intervals collected for one meteorological station. The generation injected at one point into the network provides active power locally and is found to reduce global power losses. However, the power supplied is time-varying and causes fluctuations in voltage magnitude and power fl ows in transmission lines.

  5. Dynamic mechanistic modeling of the multienzymatic one-pot reduction of dehydrocholic acid to 12-keto ursodeoxycholic acid with competing substrates and cofactors.

    Science.gov (United States)

    Sun, Boqiao; Hartl, Florian; Castiglione, Kathrin; Weuster-Botz, Dirk

    2015-01-01

    Ursodeoxycholic acid (UDCA) is a bile acid which is used as pharmaceutical for the treatment of several diseases, such as cholesterol gallstones, primary sclerosing cholangitis or primary biliary cirrhosis. A potential chemoenzymatic synthesis route of UDCA comprises the two-step reduction of dehydrocholic acid to 12-keto-ursodeoxycholic acid (12-keto-UDCA), which can be conducted in a multienzymatic one-pot process using 3α-hydroxysteroid dehydrogenase (3α-HSDH), 7β-hydroxysteroid dehydrogenase (7β-HSDH), and glucose dehydrogenase (GDH) with glucose as cosubstrate for the regeneration of cofactor. Here, we present a dynamic mechanistic model of this one-pot reduction which involves three enzymes, four different bile acids, and two different cofactors, each with different oxidation states. In addition, every enzyme faces two competing substrates, whereas each bile acid and cofactor is formed or converted by two different enzymes. First, the kinetic mechanisms of both HSDH were identified to follow an ordered bi-bi mechanism with EBQ-type uncompetitive substrate inhibition. Rate equations were then derived for this mechanism and for mechanisms describing competing substrates. After the estimation of the model parameters of each enzyme independently by progress curve analyses, the full process model of a simple batch-process was established by coupling rate equations and mass balances. Validation experiments of the one-pot multienzymatic batch process revealed high prediction accuracy of the process model and a model analysis offered important insight to the identification of optimum reaction conditions. © 2015 American Institute of Chemical Engineers.

  6. Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act

    Directory of Open Access Journals (Sweden)

    Conor P. McGowan

    2017-10-01

    Full Text Available Assessment of a species' status is a key part of management decision making for endangered and threatened species under the U.S. Endangered Species Act. Predicting the future state of the species is an essential part of species status assessment, and projection models can play an important role in developing predictions. We built a stochastic simulation model that incorporated parametric and environmental uncertainty to predict the probable future status of the Sonoran desert tortoise in the southwestern United States and North Central Mexico. Sonoran desert tortoise was a Candidate species for listing under the Endangered Species Act, and decision makers wanted to use model predictions in their decision making process. The model accounted for future habitat loss and possible effects of climate change induced droughts to predict future population growth rates, abundances, and quasi-extinction probabilities. Our model predicts that the population will likely decline over the next few decades, but there is very low probability of quasi-extinction less than 75 years into the future. Increases in drought frequency and intensity may increase extinction risk for the species. Our model helped decision makers predict and characterize uncertainty about the future status of the species in their listing decision. We incorporated complex ecological processes (e.g., climate change effects on tortoises in transparent and explicit ways tailored to support decision making processes related to endangered species.

  7. Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act

    Science.gov (United States)

    McGowan, Conor P.; Allan, Nathan; Servoss, Jeff; Hedwall, Shaula J.; Wooldridge, Brian

    2017-01-01

    Assessment of a species' status is a key part of management decision making for endangered and threatened species under the U.S. Endangered Species Act. Predicting the future state of the species is an essential part of species status assessment, and projection models can play an important role in developing predictions. We built a stochastic simulation model that incorporated parametric and environmental uncertainty to predict the probable future status of the Sonoran desert tortoise in the southwestern United States and North Central Mexico. Sonoran desert tortoise was a Candidate species for listing under the Endangered Species Act, and decision makers wanted to use model predictions in their decision making process. The model accounted for future habitat loss and possible effects of climate change induced droughts to predict future population growth rates, abundances, and quasi-extinction probabilities. Our model predicts that the population will likely decline over the next few decades, but there is very low probability of quasi-extinction less than 75 years into the future. Increases in drought frequency and intensity may increase extinction risk for the species. Our model helped decision makers predict and characterize uncertainty about the future status of the species in their listing decision. We incorporated complex ecological processes (e.g., climate change effects on tortoises) in transparent and explicit ways tailored to support decision making processes related to endangered species.

  8. Modeling water scarcity over south Asia: Incorporating crop growth and irrigation models into the Variable Infiltration Capacity (VIC) model

    Science.gov (United States)

    Troy, Tara J.; Ines, Amor V. M.; Lall, Upmanu; Robertson, Andrew W.

    2013-04-01

    Large-scale hydrologic models, such as the Variable Infiltration Capacity (VIC) model, are used for a variety of studies, from drought monitoring to projecting the potential impact of climate change on the hydrologic cycle decades in advance. The majority of these models simulates the natural hydrological cycle and neglects the effects of human activities such as irrigation, which can result in streamflow withdrawals and increased evapotranspiration. In some parts of the world, these activities do not significantly affect the hydrologic cycle, but this is not the case in south Asia where irrigated agriculture has a large water footprint. To address this gap, we incorporate a crop growth model and irrigation model into the VIC model in order to simulate the impacts of irrigated and rainfed agriculture on the hydrologic cycle over south Asia (Indus, Ganges, and Brahmaputra basin and peninsular India). The crop growth model responds to climate signals, including temperature and water stress, to simulate the growth of maize, wheat, rice, and millet. For the primarily rainfed maize crop, the crop growth model shows good correlation with observed All-India yields (0.7) with lower correlations for the irrigated wheat and rice crops (0.4). The difference in correlation is because irrigation provides a buffer against climate conditions, so that rainfed crop growth is more tied to climate than irrigated crop growth. The irrigation water demands induce hydrologic water stress in significant parts of the region, particularly in the Indus, with the streamflow unable to meet the irrigation demands. Although rainfall can vary significantly in south Asia, we find that water scarcity is largely chronic due to the irrigation demands rather than being intermittent due to climate variability.

  9. Mathematical Description and Mechanistic Reasoning: A Pathway toward STEM Integration

    Science.gov (United States)

    Weinberg, Paul J.

    2017-01-01

    Because reasoning about mechanism is critical to disciplined inquiry in science, technology, engineering, and mathematics (STEM) domains, this study focuses on ways to support the development of this form of reasoning. This study attends to how mechanistic reasoning is constituted through mathematical description. This study draws upon Smith's…

  10. A selenium-deficient Caco-2 cell model for assessing differential incorporation of chemical or food selenium into glutathione peroxidase.

    Science.gov (United States)

    Zeng, Huawei; Botnen, James H; Johnson, Luann K

    2008-01-01

    Assessing the ability of a selenium (Se) sample to induce cellular glutathione peroxidase (GPx) activity in Se-deficient animals is the most commonly used method to determine Se bioavailability. Our goal is to establish a Se-deficient cell culture model with differential incorporation of Se chemical forms into GPx, which may complement the in vivo studies. In the present study, we developed a Se-deficient Caco-2 cell model with a serum gradual reduction method. It is well recognized that selenomethionine (SeMet) is the major nutritional source of Se; therefore, SeMet, selenite, or methylselenocysteine (SeMSC) was added to cell culture media with different concentrations and treatment time points. We found that selenite and SeMSC induced GPx more rapidly than SeMet. However, SeMet was better retained as it is incorporated into proteins in place of methionine; compared with 8-, 24-, or 48-h treatment, 72-h Se treatment was a more sensitive time point to measure the potential of GPx induction in all tested concentrations. Based on induction of GPx activity, the cellular bioavailability of Se from an extract of selenobroccoli after a simulated gastrointestinal digestion was comparable with that of SeMSC and SeMet. These in vitro data are, for the first time, consistent with previous published data regarding selenite and SeMet bioavailability in animal models and Se chemical speciation studies with broccoli. Thus, Se-deficient Caco-2 cell model with differential incorporation of chemical or food forms of Se into GPx provides a new tool to study the cellular mechanisms of Se bioavailability.

  11. A multi-layered mechanistic modelling approach to understand how effector genes extend beyond phytoplasma to modulate plant hosts, insect vectors and the environment.

    Science.gov (United States)

    Tomkins, Melissa; Kliot, Adi; Marée, Athanasius Fm; Hogenhout, Saskia A

    2018-03-13

    Members of the Candidatus genus Phytoplasma are small bacterial pathogens that hijack their plant hosts via the secretion of virulence proteins (effectors) leading to a fascinating array of plant phenotypes, such as witch's brooms (stem proliferations) and phyllody (retrograde development of flowers into vegetative tissues). Phytoplasma depend on insect vectors for transmission, and interestingly, these insect vectors were found to be (in)directly attracted to plants with these phenotypes. Therefore, phytoplasma effectors appear to reprogram plant development and defence to lure insect vectors, similarly to social engineering malware, which employs tricks to lure people to infected computers and webpages. A multi-layered mechanistic modelling approach will enable a better understanding of how phytoplasma effector-mediated modulations of plant host development and insect vector behaviour contribute to phytoplasma spread, and ultimately to predict the long reach of phytoplasma effector genes. Copyright © 2018. Published by Elsevier Ltd.

  12. Position-specific isotope modeling of organic micropollutants transformation through different reaction pathways

    International Nuclear Information System (INIS)

    Jin, Biao; Rolle, Massimo

    2016-01-01

    The degradation of organic micropollutants occurs via different reaction pathways. Compound specific isotope analysis is a valuable tool to identify such degradation pathways in different environmental systems. We propose a mechanism-based modeling approach that provides a quantitative framework to simultaneously evaluate concentration as well as bulk and position-specific multi-element isotope evolution during the transformation of organic micropollutants. The model explicitly simulates position-specific isotopologues for those atoms that experience isotope effects and, thereby, provides a mechanistic description of isotope fractionation occurring at different molecular positions. To demonstrate specific features of the modeling approach, we simulated the degradation of three selected organic micropollutants: dichlorobenzamide (BAM), isoproturon (IPU) and diclofenac (DCF). The model accurately reproduces the multi-element isotope data observed in previous experimental studies. Furthermore, it precisely captures the dual element isotope trends characteristic of different reaction pathways as well as their range of variation consistent with observed bulk isotope fractionation. It was also possible to directly validate the model capability to predict the evolution of position-specific isotope ratios with available experimental data. Therefore, the approach is useful both for a mechanism-based evaluation of experimental results and as a tool to explore transformation pathways in scenarios for which position-specific isotope data are not yet available. - Highlights: • Mechanism-based, position-specific isotope modeling of micropollutants degradation. • Simultaneous description of concentration and primary and secondary isotope effects. • Key features of the model are demonstrated with three illustrative examples. • Model as a tool to explore reaction mechanisms and to design experiments. - We propose a modeling approach incorporating mechanistic information and

  13. Incorporating Measurement Error from Modeled Air Pollution Exposures into Epidemiological Analyses.

    Science.gov (United States)

    Samoli, Evangelia; Butland, Barbara K

    2017-12-01

    Outdoor air pollution exposures used in epidemiological studies are commonly predicted from spatiotemporal models incorporating limited measurements, temporal factors, geographic information system variables, and/or satellite data. Measurement error in these exposure estimates leads to imprecise estimation of health effects and their standard errors. We reviewed methods for measurement error correction that have been applied in epidemiological studies that use model-derived air pollution data. We identified seven cohort studies and one panel study that have employed measurement error correction methods. These methods included regression calibration, risk set regression calibration, regression calibration with instrumental variables, the simulation extrapolation approach (SIMEX), and methods under the non-parametric or parameter bootstrap. Corrections resulted in small increases in the absolute magnitude of the health effect estimate and its standard error under most scenarios. Limited application of measurement error correction methods in air pollution studies may be attributed to the absence of exposure validation data and the methodological complexity of the proposed methods. Future epidemiological studies should consider in their design phase the requirements for the measurement error correction method to be later applied, while methodological advances are needed under the multi-pollutants setting.

  14. Fast charging technique for high power LiFePO4 batteries: A mechanistic analysis of aging

    Science.gov (United States)

    Anseán, D.; Dubarry, M.; Devie, A.; Liaw, B. Y.; García, V. M.; Viera, J. C.; González, M.

    2016-07-01

    One of the major issues hampering the acceptance of electric vehicles (EVs) is the anxiety associated with long charging time. Hence, the ability to fast charging lithium-ion battery (LIB) sys